patterns of population growth in nepal - Institute for Social and ...

PATTERNS OF POPULATION GROWTH IN NEPAL
DEVENDRA PRASAD SHRESTHA
A THESIS SUBMITTED TO THE UNIVERSITY OF MYSORE FOR THE
DEGREE OF DOCTOR OF PHILOSOPHY IN ECONOMICS THROUGH
THE INSTITUTE FOR SOCIAL AND ECONOMIC CHANGE-BANGALORE
1989

C E R T I F I CAT E
I hereby certify that I have guided and
supervised the preparation and writing of the
thesis entitled NPatterns of Population Growth
in Nepal" by Mr. Devendra Prasad Shrestha who
worked on this topic at the Institute for Social
and Economic Change, Bangalore from June 1984
to April 1989.
I also certify that the thesis has not
previously formed the basis for the award of
any Degree, Diploma, or Associate Fellowship of
the University of Mysore or any other University.
April, 1989
0'~~
P.Hanumantha Rayappa
Professor and Head
Population Research Centre
Institute for Social and
Economic Change
Bangalore 560 072

DECLARATION
-----------
I hereby declare that the present thesis
titled -Patterns of Population Growth in Nepalis
the outcome of the original research work
undertaken and carried out by me under the
guidance of Dr.P.Hanumantha Rayappa, Professor,
Population Research Centre, Institute for Social
and Economic Change, Bangalore.
Due acknowledgements
have been made wherever anything has been
borrowed from other sources.
. I also declare that the material of the
thesis has not formed, in anyway, the basis for
the award of any Degree, Diploma or Associate
Fellowship previously of the University of Mysore
or any other University.
April, 1989
~~~f

AC

I acknowledge my gratitude to the Institute
for Social and Economic Change for granting me a
fellowship for pursuing this study. I would also
like to record my deep sense of gratitude to
Tribhuvan University, Kathmandu, Nepal, for granting
me leave which enabled me to pursue and complete
this study. My thanks are also to the University
of Mysore for providing me registration facilities.
Central Bureau of Statistics, Kathmandu,
Nepal, was kind enough in providing me the copies
of the relevant census volumes. Thanks are also due
to the officials of government departments and
organisations viz., Departments of Food and Agricultural
Marketing Services, Health, Irrigation, Cooperatives,
Education, and Road for their co-operation
in providing the required data. Agricultural Inputs
Corporation and Agricultural Development Bank also
provided me the required data and also the relevant
materials. I am thankful to all of them.
I am very much thankful to my teacher
Mr. Prithivi R.Legal, Central Economics Department,
Tribhuvan University, who had always been a source .
of inspiration. SpeCial thanks are also to my hostel
friends S.S.Jena, M.S.Parthasarathy, H.Shailendra,

N.Sivanna, V.Selvaraju, T.V.Sekhar, Joseph, Sukhpal
Singh, and'M.H.Balasubramanya for their co-operation.
Mr. Krishna Chandran helped me in computer
processing of data for analysis and Mr.Lingaraju
provided assistance in drawing the maps.
I am grateful
to both of them.
My sincere gratitude and indebtedness to my
parents, brothers and sister who had been a constant
source of encouragement to me.
I am also deeply
indebted to my wife Sheela, daughter Srijana, and
son Sanketh for their sacrifice during the periods
of their staying away from me and for firmly standing
by me in the periods of stress and strain.
I thank the ISEC library staff for their
valuable cooperation.
Finally, I am thankful to Mr.T.Srinivasa Murthy
for his prompt and excellent typing of the
manuscript.
Bangalore
April, 1989
Devendra Prasad Shreatha

CON TEN T S
ACKNO\tv"LEDGEMENT
LIST OF TABLES
LIST OF MAPS
Page
i
vii
x
CHAPTER I : INTRODUCTION 1
1.1 Background 1
1.2 Statement of the Problem 5
1.3 Objectives of the Study 9
1.4 Organization of the Study 10
CHAPTER II I METHODOLOGY 12
2.1 Data and Their Sources 13
2.2 Quality of Data and
Their Limitations 17
2.3 Techniques of Analysis 20
CHAPTER III I
POPULATION GROWTH IN NEPAL:
A HISTORICAL PERSPECTIVE 24
3.1 Nepal and Its People 24
3.2 Estimates of Population
of Nepal in Earlier Periods 28
3.3 History of Census Taking
in Nepal 30
3.4 Population in the Present
Century 33
3.5 Population Distribution
in Nepal 36
CHAPTER IV : BEHAVIOUR OF THE COMPONENTS OF
POPULATION GROWTH 41
4.1 Mortality 42
4.2 Fertility 50
4.3 Emigration and Immigration 63

CHAPTER V
v
: REGIONAL PATTERNS OF
POPULATION GROWTH
Page
70
5.1 Patterns of Population Growth
by Regions, 1911-1981 71
5.2 Patterns of Population Growth
by Sub-Regions,1952/54-1981 74
5.3 Patterns of Population Grov/th
by Districts, 1971-81 79
CHAPTER VI : LEVELS OF AGRICULTURAL DEVELOIMENT
AND PATTERNS OF POPULATION GROWTH 105
6.1 Introduc~ion 105
6.2 Conceptual Framework 106
6.3 Hypothesised Relationship 112
6.4 Empirical Findings from
other Studies 115
6.5 Agricultural Development in
NepalI A Brief Overview 121
6.6 Selection of Indicators of
Agricultural Development 130
6.7 Levels of Agricultural
Development 131
6.8 Agricultural Development and
Popula tion Growth: Some
Emerging Patterns 139
CHAPTER VII I
PATTERNS OF URBAN POPULATION GROWTH
IN NEPAL 150
7.1 Introduction 150
7.2 Conceptual Framework 151
7.3 Empirical Findings from
Other Studies 155
7.4 Level and Trends of Urban
Growth 161
7.5 Growth of Towns 169
7.6 Functional Classification of
Towns and Urban Population
Gro~·th 176

vi
Page
CHAPTER VIII: LEVELS OF SOCIO-ECONOMIC
DEVELOPMENT AND PATTERNS OF
POPULATION GROWTH 188
8.1 Introduction 188
8.2 Conceptual Framework 190
8.3 Hypothesized Relationship 198
8.4 Empirical Findings from
Relotec Literature 201
8.5 Socio-~conomic Development
in NepalI An Overview 214
8.6 Selection of Socio-Economic
Development Indicators 225
8.7 Levels of Socio-Economic
Development 227
8.8 Socio-Economic Development
and Population Growth: Some
Emerging Patterns 238
CHAPTER IX : SUMMARY AND CONCLUSION 250
9.1 Summary
9.2 Concluding Remarks
250
258
BIBLIOGRAPHY
*********

LIST OF TABLES
Table
No.
3.1
3.2
4.1
Estimates of Population for Nepal,
1750-1900
Population Size and Gxowth in
Nepal, 1911 to 1981
Population Distribution and Land
Axea by Natural Regions of Nepal,
1952/54-1981
Estimates of Selected Mortality
Indicators, 1952-1984
Estimates of Cxude Birth Rates,
1952/54-1981
4.3 Age-Specific Fertility Rates,
1971-1981
4.7
5.1
5.2
5.3
Mean Number of Children Ever Born
by Curxent Age for All Ever Married
Women, 1971-1986
Percentage Distribution of Never­
Married and Ever-Married Women, 15
Years of Age and Above, 1971-1986
Percentage of Currently Married
Women who have Ever Heard of Family
Planning, Ever Used a Method and
Cuxrently Using a Method,1976-1986
Estimates of Volume of Irmdgxation
and Emigration, 1941-1983
Annual Intexcensal Gxowth Rate
(Geometxic) for Regions of Nepal,
1911-1981
Annual Intercensal Growth Rate
(Geometric) of Population fox Regions
and Sub-Regions of Nepal,1952/54-1981
Rate of Total Incxease and Its Components
for the Districts of Nepal
Duxing 1971-1981
Page
No.
30
34
37
51
56
60
62
64
72
77
85-88

viii
Table
No.
5.4
5.5
Rate of Total Increase and Its
Components for Regions and Sub­
Regions of Nepal, 1971-81
Classification of Regions, Sub­
Regions and Districts According
to the Emerging Patterns of Population
Change, 1971-81
Page
No.
89
98-100
Appendix 5.1
Regions/Sub-Regions and Their
Corresponding Districts
6.1
6.2
6.4
6.5
Some Selected Indicators of Agricultural
Development in Nepal,
1961-62 to 1981-82
Rotated Factor Loadings of Agricul
tural Variables
Distribution of Districts by Regions
and Levels of Agricultural
Development
Levels of Agricultural Development
and Demographic Indicators: Some
Emerging Patterns
Zero-Order Correlation Coefficients
Between DemographiC Indicators and
Scores of Agricultural Development
Appendix 6.1
Districtwise Factor Scores and
Ranks by Agricultural Development
7.1
Percentage Distribution of Urban and
Rural Population, and Intercensal
Annual Growth Rate, 1952/54-1981
Growth Rate of Urban Population by
Size Classes,1952/54 - 1981
104
127-129
132-133
138
140
144
147-149
163
166

ix
Table
No.
7.4
7.5
Growth Rates of Towns,1952/54-1981
Functional Classification of Towns
and Growth Rates During 1971-81
Rate of Urban Popula tion Growth and
Sex Ratio by Functional Groups of
Towns
Functional Categories of Towns and
Growth Rates, 1971-81
Page
No.
170
181
183
186
8.1
8.2
8.3
8.4
8.5
Selected Indicators of Socio­
Economic Development in Nepal
Rotated Factor Loadings of Socio­
Economic Variables
Distribution of Districts by Regions
and Levels of Socio-Economic
Development
Levels of Socio-Economic Development
and Demographic Indicators:
Emerging Patterns
Zero-Order Correlation Coefficients
Between Demographic Indicators and
Scores of Socio-Economic Development
Appendix 8.1
Districtwise Factor Scores and Ranks
by Spcio-Economic Development
9.1
Demographic and Socio-Economic
Indicators for Nepal and Its Regions
and Threshold Values
217-220
228-230
236
239
243
245-249
262-264
*********

Map
No.
LIST OF MAPS
Page
3.1 Nepal-Natural Regions •• 26
5.1 Regions and Sub-Regions of Nepal • • 75
5.2 Classification of the Districts
of Nepal According to Rate of Total
Increase • • 95
5.3 Classification of the Districts of
Nepal According to Rate of Natural
Increase • • 96
5.4 Classification of the Districts
of Nepal According to Rate of Net
Migration • • 97
6.1 Levels of Agricultural Development
by Districts of Nepal, 1981/82 • • 137
8.1 Levels of Socio-Economic Development
by Districts of Nepal, 1981/82 • • 234
*********

CHAPTER .!
INTRODUCTION

CHAPTER I
INTRODUCTION
1.1 Background:
Nepal is an independent Hindu kingdom in the
world. It 1s also one of the less developed countries
whose per capita income is estimated to be $ 133 in
1985-86. The average annual growth rate of Gross
Domestic Product (GDP) during the period 1970-71 to
1984-85 is estimated to be 2.8 per cent which is
slightly higher than the annual rate of growth of population
which stood at 2.66 per cent during 1971-81.
About 94 per cent of the total population still resides
in rutal areas. The caloric intake of food of its
people covers only 86 per cent of the total nutritional
requirements in 1980 (CBS, 1987a:vii). Adult
literacy rate stood at 19 per cent in 1981. Life
expectancy at birth stands at 51 years and infant
mortality rate is estimated to be 111 in 1986 (CBS,
1986). '!be Nepalese economy is also characterised by
higher degree of income inequality as about 47 per
cent of the share in total income is concentrated in
the hands of 10 per cent of the richest households in
rural Nepal (Islam et al./ 1982: 38).

2
The economy of Nepal 15 predominated by agriculture
as its contribution to the GDP is to the
extent of 62 per cent in 1985-86.
Agricultuxal
sector accounts for 75 per cent of the exports of the
country and absorbs nearly 91 per cent of the total
labour force.
Notwithstanding its dominant position
in the economy, it has still remained at a subsistence
level. However, a few significant developments in
different aspects of agricultural sector in recent
years cannot be overlooked. Some of the major changes
are with regard to cultivated area, cropped area,
cropping intensity, irrigation, use of high yielding
varieties, use of chemical fertilisers, use of agricul
tural machinery like tractors and pumpsets, etc.
In spite of these achievements, gains in agricul
tural production are not very impressive.
The
agricul tural production has grown at an annual rate
of 1.5 per cent during 1970/71 to 1984~5
Whereas
population growth was about 2.7 per cent per annum
during the same period (CBS, 1987 a: vii). Only after
1980, agricul turalproduction started getting some
momentum and during Sixth Five 'rear Plan period
(1980-85) agricultural production has grown at a rate

3
of 3.2 per cent per annum.
What is noteworthy, however,
is that most of the increase in agr1cultural
production was due to expansion in cropped area
rather than increase 1n its productivity as producti- .
vity bas remained almost constant t- _ Ministry
of Finance, 1986: 13).
It should be noted here that
there exist wide regional disparities in the growth
of agr ieu! tur al sector in Nepal.
Industrial development in Nepal is very much in
its infancy. According to 1981 census le ss than 1
per cent of the economically active population is
engaged in manufacturing sector. Its share in GDP is
merely 5 per cent in 1983-84.
However, some steady
progress in industrial sector has been observed in
recent years. The number of manufacturing establiShments
and the number of worker s engaged in these manufacturing
establishments have shown a steady progress.
There exist wide disparities in the growth of industries
across the country as big industries are concentrated
only in a few pockets of the country.
Like iDaustrial development, the level of
urbanization in Nepal is also very low as only 6.3
per cent of the total population is urban in 1981.

4
If we exclude the capital city of Kathmandu the percentage
urban population comes down to only 4.8 per
cent. Notwi~~standing
its present level, its growth,
however, is very significant. In 1952-54 only 2.9
per cent of the total population was urban. During
1971-81 urban population increased by 107 per cent
and grew at an annual rate of 7.5 per cent compared
to a growth rate of 2.4 per cent in the rural areas
(CBS, 1987a: 180). The urban population in Nepal is
unevenly distributed across regions.
Nepalese economy is beset with the problems of
poverty, malnutrition, unemployment and underemployment,
high income concentration, etc. However, along
with agricultural and industrial progress in recent
years significant developments have been witnessed in
various facets of the economy. When viewed against
the background of where the country started 2S to 30
years ago, substantial progress has been made. Public
health services - both preventive and curative - have
been improved. Number of hospitals, hospital beds,health
posts, doctors have increased significantly. Likewise,
number of schools and higher educational institutions
have grown remarkably as a result of which
literacy

5
level has increased and per cent of school going
children in various levels has moved upward. One of
the significant achievements of planning during last
two and half decades in Nepal has been in creating
infrastructure in terms of transport and communications.
Transport and communications were exclusively
by foot three decades ago. But now most parts of the
country are linked with better transport facilities.
The total road length has increased during this short
span of time. Similarly, more and more people have
access to safe and piped drinking water facilities
and electricity. Whatever little has been achieved
has not been distributed equally across the country,
thus resulting in inter-regional disparities in the
levels of development.
1.2 Statement of the Problem:
Nepal has been experiencing rapid population
growth in recent years. The annual rate of growth of
population which stood at 1.64 per cent during 1952/54-61
and 2.10 per cent during 1961-71 reached an unprecedented
level of 2.66 per cent during 1971-81. There
are also significant regional variations in the rate

6
of growth of population and they seem to be widening
over time. For example, Terai region * compared to
Mountain and Hill regions has been experiencing
relatively higher rates of population growth. This
region recorded a very high annual rate of growth
of 4.12 per cent during 1971-81 compared to 1.35 and
1.65 per cent of Mountain and Hill regions, respectively,
during the same period. Similarly, variations
have been quite large in the growth rates of population
across districts during 1971-81. The average
annual growth rate varied from a very high rate of
9.39 per cent in Kanchanpur district tx) a negative
growth of 2.72 per cent in Humla district.
In the light of the above findings, the following
questions could be raised: (1) Why population
growth in Nepal has accelerated in recent years, (ii)
what factors could be acccunted for the variations in
.
population growth rates across regions and districts,
and (iii) why the variations have been widening over
time.
These emerging situations could probably be
attributed to the differential behaviour of the
* The country may be divided into three natural
regions - Mountain, Hill and Terai. Details of
each region will be provided in ch~ter Three.

.,
components of population growth i. e., birth, death
and net migration and the variations in these componets
by regions and districts. The variations in
the components of population could, among other
things, be attributed to the existing disparities in
the levels of development across regions and districts
in Nepal.
It has been well recognised that there is a
strong association between levels of socio-economic
development and population gro~rth. '!be process of
socio-economic development may alter the course of
mortality, fertility and migration Which in turn would
affect population growth. A knowledge of this relationship
is useful in understanding the nature and
the extent of changes expected in population growth
and its components, given the level of development.
The theory of demographic transition is an effort in
this direction. The theory, in brief, states that
any country undergoing industrialisation and socioeconomic
development experiences the following three
to four stages in its mortality and fertility behaviour:
(i) high mortality and high fertility, (ii)
declining mortality with unchanged fertility,

8
(iii) declining mortality and declining fertili~,
and (iv) low rrortality and low fertility. The
sequence and pace of decline in mortality and fertility
and the time taken to complete the transition
vary from country to country depending upon the
level of development achieved (Teitelbaum, 1975).
Another effort to explain this relationship
between economic and social development_with fertility
is the II threshold hypothesis" which postulates that
fertility will Show little or no change until a
threshold level is reached after Which changes in
fertility will occur along with changes in development
indicators (Hauser, 1979).
It is, thus, evident from
both the theoretical developments that there is a
strong association between socio-economic development
and population growth.
Many studies have examined the relationship
between socio-economic development and population
growth both from macro and micro perspectives. At the
macro level, both time series and cross sectional data
have been used. At the micro level the relationships

9
with reference to specific components of population
growth have been highlighted. In the specific setting
of Nepal, however, previous studies have not tried to
understand the patterns of population growth either
by levels of agricultural development or by socioeconomic
development. Furtherrrore, no attempt has
been made to explain the variations in population
growth at the disaggregated level (districts) in terms
of its components.
This could perhaps be due to the
non-availability of data on the components of population
growth at the district level. Hence, the present
study has been designed to explain the vaxiations in
population growth in terms of its components
at the
disaggregated level by estimating them and also to
understand the patterns of population growth by levels
of agricultural development and levels of socioeconomic
development in Nepal.
1.3 Ob1ectives of the Study:
The specific objectives of the study are:
(i)
to examine the patterns of population
growth in Nepal by regions and districts,
(ii)
to estimate the components of population
growth i.e., bixth, death and net migration during
1971-81 at the district level,

10
(iii) to delineate the patterns of population
growth by
(iv)
levels of agricultural development,
to examine the patterns of urban population
growth, and
(v)
to delineate the patterns of population.
growth by levels of socio-economic development.
1.4 Organization of the Stugy:
The present stlldy is divided into nine chapters.
The remaining parts of this study are organized as
follows:
In Chapter Two we will present the methodology
which includes the type of data used, their
sources, quality and the techniques employed in analyzing
the data.
In the next chapter (Chapter 'Ihree)
historical gro'I1th of population in Nepal will be
presented. This is followed by a discussion on the
behaviour of the components of population growth in
Chapter Four.
Chapter Five then presents the patterns
of population gro'I1th in Nepal by regions and districts.
Subsequently, in Chapter Six, an attempt is made to
examine the patterns of population growth by levels of
agricultural development.
Similarly, Chapter Seven
examines the patterns of urban population growth and

11
Chapter Eight examines the patterns of population
growth by levels of socio-economic development.
Finally, in Chapter Nine, a summary of the major findings
of the study and their policy implications are
presented. The relevance of the findings with demo-·
graphic theory is also mentioned.

CHAPTER II
METHODOLOGY

CHAPTER II
ME'lHOOOWGY
In the present study district has been considered
as the unit of analysis. This is because of
the fact that district Which is the lowest administrative
unit in Nepal is sufficiently large enough
to enable us to carry out a meaningful analysis.
Secondly, the districts also exhibit wide variation
in their levels of development. So meaningful patterns
of population growth by levels of development could
be analysed by districts.
Data on derrographic indicators, agricultural
development indicators and socio-economic development
indicators have been obtained for 75 districts of
Nepal. As far as possible, comparable data have been
gathered for the districts. Data pertaining to derrographic
indicators refer to the period 1971-81 and
agricultural and socio-economic development indicators
refer to 1981/82. The data, their sources, quality
and limitations and techniqu~of analysis employed are
discussed below.

13
2.1 Data and their Sources:
The present study is mainly based on data
available from secondary sources. Rate of growth of
population and its components viz., birth, death and
net migration have been estimated. For these, data
on size of population by regions and districts for
different census years were obtained from population
censuses carried out by Central Bureau of Statistics
(CBS), Nepal. The population figures adjusted for
the 1981 boundary of all 75 districts are also
available in 1971 (Gurung, 1981). In order to decompose
the population growth into its components
estimates of birth, death and net migration are required.
Till 1984/85 vital registration system covered only
40 districts in Nepal and in all these districts the
coverage of births and deaths are incomplete (CBS,
1987a: 339). Hence, indirect demographic techniques
have been used to estimate the components of populatton
growth. The techniques have been described in
detail in Chapter Five. The use of these techniques
warranted following information:
(i) The number of children ever born classified by
five year age group of mother from 15-19 to
45-49;

14
(ii)
'!he number of children born during the year
preceding the surveyor census classified by
five year age group of mother,
(iii) The number of children surviving classified
by five year age group of mother,
(iv)
(v)
The total ntUnber of \«)men in each five year age
group (irrespective of marital status), and
The total population.
The fertility tables in the 1971 and 1981 censuses
provide the above information at the district
level.
In order to arrive at the levels of agricultural
development of districts an index of agricultural
development has been obtained by using 12 indicators.
List of indicators selected is provided in Ch~ter
Six. The data required were obtained from various
sources both published and unpublished as the required
data were not available from a single source. Data
on agricultural output of various crops, area under
these crops and national average price of these crops
were obtained from Agricultural Statistics of Nepal,
1983 and Agricultural Marketing Information Bulletin

15
(Special Issue) 1986, of the Office of the Department
of Food and Agricultural Marketing Division. Data on
agricultural workers, arable land, irrigated area,
were obtained from Population Census of 1981, Sample
Census of Agriculture, 198~of the Office of the CBS.
Similarly, data relating to cultivated area and gross
cropped area were collected from Land Resource l-iapping
Project. Information on loan disbursement for farm
mechanization and irrigation and the number of cooperatives
were obtained from Agricultural Development
Bank and Department of Cooperatives, re~ectively.
Data on high yielding varieties of seeds and fertilizers
were obtained from Basic Statistics of Agricultural
Inputs in Nepal, Office of the Agricultural
Input Corporation.
The data on urban growth by urban units, distribution
of \rt1Orkers by major industry groups by urban
units etc., have been obtained from various publications
of the CBS like Population Censuses of 1952/54
to 1981, specially from Urban Area Tables.
In add.! tion to agricultural development indicators,
some more dimensions of development have been
added to generate an index of overall socio-economic

16
development.
21 indicators have been used to obtain
the index of socio-economic development.
List of
indicators selected is provided in Chapter Eight. The
data and their sources on agricultural development
indicators have already been mentioned above.
Industrial
development indicators like number of manufacturing
establishments, number of workers employed,
energy consumption, value added, etc. were obtained
from Census of ¥

17
2.2 Quality of Data and their Limitations:
Here an attempt has been made to assess the
quali ty of data used in the present study and mention
some of their limitations. Census data in Nepal like
in many other developing countries suffer from
various limitations. These include coverage error,
misreporting of ages due to age heaping, and digital
preference, underreporting of births and deaths,
displacements of vital events, omission of infant
deaths etc. Because of these problems in census data
in general and fertility and roc>rtali ty data in particular,
their accuracy and reliability have been
questioned. However, the techniques that have been
used to estimate the vi tal rates take care of certain
data problems like omission and underreporting of
children ever born and reference period errors ~
selecting a suitable correction
factor.
Similarl~ data on agriculture have several in-
,consistencies because figures vary from one source
to the other. To overcome this problem districtwise
estimates provided by the Land Resource ~1n9 ,
Project have been used for total cropped area and
cultivated area. '!be estimates of Land Resource Mapping
Project appear generally much more consistent as the

figures wi thin the same ecological zones are remarkably
homogeneous (FAO/DFAMS, 1986: 5). Similarly,
for data on irrigated area by districts the estimates
of Sample Census of Agriculture, 1981, have
been used.
To overcome the problem of corcparability
comparable data from the same source and for the
same point in time have been used as far as possible.
Data on some of the indicator s which were considered
very essential were either not available or
not reliable if they were available. For exarcple, with
regard to the data on area under high yielding
varieties of seeds Sample Census of Agriculture, 1981,
has reported that of the 75 districts in Nepal only
28 districts have reported to have used high yielding
varieties (HYVs) Which is difficult to accept because
this information is in contradiction with the sales
figure of HYVs by districts obtained from Agricul tural
Input Corporation which shows that HYVs are sold in
almost 65 districts in Nepal.
However, 1n view of
the importance of this variable as an indicator of
agricul tural development, the sales figures of HYVs
of paddy, Wheat and maize seeds have been considered
as a proxy of area under HYVs.
Similarly, the

19
information on number of tractors, purnpsets, power
tillers were not available at all. So the information
on loan disbursement on farm mechanization
and irrigation obtained by Agricultural Development
Bank were used as a proxy of extent of mechanization.
Districtwise prices of all ten crops (paddy,
wheat, maize, barley, millet as cereals and sugarcane,
jute, potato, tobacco and oilseeds as cash
crops) included are not available and hence national
average prices have been considered for all the
districts to estimate the gross value of agricultural
output. Due to the non-availability of data at
district level on some of the indicator s., even though
they are important.,could not be considered.
These
include: percentage of villages electrified, per
capita income, total number of vehicles, per capita
electricity consumption, number of newspapers under
circulation etc. Further, districtwise data on
surfaced road length and percentage of people benefitted
by piped drinking water ".. ere not available
for 1981 and hence data for the year 1976 have been
considered.

20
2.3 Techniques of Analysis:
In this section the analytical tools that have
been employed in analysing the data are presented.
In order to classify the districts based on their
levels of agricultural and socio-economic development
an index of agricultural development I
and socioeconomic
development were separately constructed. In
order to obtain the index of agricultural and socioeconomic
development the factor analysis technique
was adopted.
A brief description of the technique
is given below:
Factor Analysis Technique:
n X ij - Xj
FX.
]
where
=
=
the index of development of i th district
factor loading on Xj th variable
= value of Xj th variable of the i th district
Xj = mean of the Xj th variable
th
SD Xj
= standard deviation of Xj. variable
i = 1 1 2 1 •••••• 75

21
The
index is nothing but the factor
score. A few steps involved in deriving the index
(factor score) are provided below:
1. At the first stage unrotated factor matrix
were obtained. The entries of the matrix are
known as factor loadings. Kaiser's criterion
(i.e., eigen value greater than 1) was used to
determine the number of factors to be
extracted (Sudarshan, 1985: 22; Fong, 1987:
550).
2. The unrotated factor matrix was rotated by
using varimax method.
3. The rotated factor matrix was later multiplied
by the standardized data matrix and thus factor
scores were obtained.
Here we have considered only first two factors and
thus the first two factor scores as an index of agricultural
development and socio-economic development.
Based on this index the districts were grouped into
three levels of agricultural development and socioeconomic
development viz., high, moderate and low.
The reason for adopting this technique to construct
an index of agricultural development and socio-

economic development is that it does explicitly ta~e
into account the problem of multi-collinearity among
the original indicators by orthogonizing the
whole
set of variables through a process of linear transformation.
Furthermore, unlike other techniques
\-:here \-:eights are not scienti fically and obj ectively
assigned this technique assigns weights objectively
to t~e
included variables for constructing an index
of development. The weights are nothing but factor
loadings.
Factor analysis technique has been widely used
to analyse the regional differences in development.
The technique was popularised by Berry (1960),Adelman
and ;·:.orris (1967), Rati Ram (1982), Hagood (1943),
Schiedvimick (1970), Pal (1975), Rao (1977) and
Gulati (1977).
The work of Berry, Adelman, Rati Ram
relates to the international comparison whereas the
work of Pal, Rao and Gulati relates to India.
In addi tion, an attempt has also been made to
functionally classify the urban areas and relate th~
wi th their gro\·:th in population. So urban units are
functionally classified following the method adopted
by Wilkinson (1964). The details of the method is
provided in Chapter Seven.

23
~
In order to know the nature of the relationships
between levels of development i.e., agricultural
and socio-economic development and population
.~
'growth, simple averages and correlation techniques
have been adopted.

CliAPTER III
POPULATION GROH'lH IN NEPAL : A HIS'roRICAL PERSPECTIVE

CHAPTER III
POPULATION GROWTH IN NEPAL: A HISTORICAL PERSPECTIVE
In the present chapter, an attempt is made
to
present the gro\'l'th of population in Nepal from a
historical perspective. After providing a brief background
information about Nepal, estimation of population
available for earlier periods from different
sources have been provided.
The history of census
taking in Nepal, population count of Nepal as
available during the present century and the spatial
distribution of population have also been presented.
3.1 Nepal and its People:
Nepal is a small landlocked country surrounded
by two big neighbourers namely, India and China.
It
has a total area of 147,181 sq.km with a total
length of 885 kms from east to west, and with an
average width of 193 kms from north to south.
It is
located between longitudes 80 0 4' to 88°12' east and
lati tudes 26 0 22'
to 30 0 27' north.
On the basis of altitude the country can be
divided into three natural regions stretching from
east to west: (i) the Mountain or Himalayan region,

25
(ii) the Hill region, and (iii) the Terai region
(Eap 3.ll. '!he l'.ountain region lies in the northern
part of the country at an al ti rude from 4,877 meter s
to 8,839 meters above the sea level. This region
occupies 35.2 per cent of the total land area and the
high Himalayan region is always covered with snow.
Since the climate is very cold and the land is not
sui table for cultivation, this region is very thinly
populated. The Hill region lies mostly between 610
meters and 4877 meters in altitude and accounts for
41.7 per cent of the total land area. This region
which is the largest one also includes Kathmandu
Valley where the capital city Kathmandu is situated.
The arable land of this region is densely populated.
The Terai region includes the low flat land belt, most
of which are fertile and dense forest areas of the
country. This region lies in the extreme southern
part of the country and extends from east to west along
the Indo-Gangetic plain. This region occupies 23.1
per cent of the total land area of Nepal and happens
to be the thickly populated region of the country.
Small stretches and pockets of plain land between the
Hills and Terai are similar to Terai region and are
often referred to as Inner Terai.

--~~..-7.7r~.~ttW~k=~U.~=-ff.=-==
__ _
« ------------~--..,\O
~
2
-
-
2
~
_, ~
0- ::'..J ~
E tx--
--
--

27
Nepal has an ethnically complex population
as there are 75 different ethnic groups speaking
50 different languages. However, on the basis of
their origin, language and cultural connections
most of these ethnic groups can be classified into
t~~
broad categories:
1. Tibeto-Hangoloids or Tibeto-Nepal ese
2. Indo-Aryans or Indo-Nepalese
The racial composition of the population differs
along \-li th the al ti tude. The higher al ti tude is inhabited
by Sherpas, Limbus, Tamangs and Bhotiyas.
The mid-Hountain region is inhabited by Magar s,
Gurungs, Newars, Brahmins and Chettriyas. In the
Terai region dominant position is held by mainly
Tharu, Danuwar, Chepang and Indian immigrants.
However,
in recent times owing to the movement 0 f
people because of the development of transport net-
.
work one finds a mixture of different races in the
various parts of the country.
people of Nepal are Hindus.
The majority of the
'!he religious composition
of population as recorded in the 1981 census
is as follows: Hindus 89.5 per cent, Buddhists 5.3
per cent, ~mslims
2.7 per cent and other religious
groups 2.5 per cent.

~f
"
28
.,
~ '..
..
"
;:~
Some 50 different languages are spoken in
different parts of the country. According to 1981
census 58.36 per cent of the people speak Nepali
language which is also the official language in
the country. '!be second major language is Ma1thali
spoken by 11.11 per cent followed by Bhojpuri
which is reported as the roother tongue of 7.61 per
cent of the people. Rest of the population speak
various other languages like Tamang, Tharu, Newari,
etc.
3.2 Estimates of Population of Nepal in Earlier
Periods
The practice of conducting population census
\Olas virtually non-existent in ancient times in Nepal.
However, several estimates of population are
available for the country from different sources.
Based on the historical demographic records Poffenberger
extrapolated the size of the population between
the year 1750 and 1800, and arrived at a figure
of 3 million people (Poffenberger, 1980: 26). Kirkpatrick
estimated the population of an area somewhQt
larger than modern Nepal to be roughly 500,000 at the

29
end of the 16th Century. Similarly, Hamil ton using
the figures obtained from the tax census data estimated
the population to be 2.5 million in 1810
(Seddon, 1987: 2). Fraser on the basis of the
information provided by the officials of Nepalese
Government estimated the population of Nepal to be
3.66 million around the year 1820 (ESCAP, 1980: 11).
Macfarlane estimated the population of Nepal to be
3 million in 1850 (Macfarlane, 1976: 204). During
the mid-19th Century British Government was very
much interested to know the size of the population
of Nepal for the purposes of trade and army recruitment.
They arrived at ~ figure of 2 million in
1879 whereas the claim of Nepalese Government was
5 million persons. Oldfield estimated the population
to be 4 million and considered the Nepalese
Government's estimate of 5 million as an intentional
exaggeration (ESCAP, 1980: 11). The estimate of
Vansittart at the beginning of this Century was
close to that of Oldfield.
The various population estimates of earlier
periods have been summarised in Table 3.1.

30
Table 3.1: Estimates of Populetion for Nepal,
1750-1900
Year
Total
Population
Source/Author
1750 3,063,300 Poffenberger ( 1980)
1800 500,000 Kirkpatr ick ( 1811)
1810 2,500,000 Hamilton ( 1819)
1820 3,661,200 Fraser ( 1820)
1850 3,000,000 Macfarlane (1976)
1879 4,000,000 Oldfield (1880)
1900 4,000,000 Vansittart (1906)
Note: For details of the source please refer to
bibliography.
3.3 History of Census Taking in Nepal:
unlike some western countries, Nepal does not
have a long history of census taking. The census of
1911 was the first of its kine and since then the
practice of census taking is continuing more or
less onCe in ten years. HO\-leVer, there are some
evidences to sho'v; that the population count in one

31
ferm or the other prevailed even before 1911.
However,
the efforts of the different governments
to
conduct population census in the country remained
incomplete upto the end of 19th century (Kansakar,
1977: 2).
As stated above population census was conducted
for the fir st time in Nepal in 1911.
The
secone census was conducted in 1920, third in 1930
and fourth in 1941.
All these four censuses were
conducted during Rana regime (1846-1950).
With regard
to the usefulness of census data for demographic
analysis it has rightly been observed that "though
these census counts provide bench mark data for a
s'b.:dy of country's population grov;th, not much
importance has been attached to the results of these
enumerations for various reasons. First, very little
is known about the concepts and definitions used in
these enumerations.
Secondly, the task was entrusted
to the agents of landlords who adopted their own
methods of enumeration.
The apparent weakness of
the system and the lack of supervision waulo have
resulted in inaccurate and incomplete enumeration.
Thirdly, in the absence of any published reports and
details about sex, age, spatial and other

32
characterist1cs,the data from these counts do not
lend themselves to any meaningful demographic analysisN
(ESCAP, 1980: 12). More serious doubts
regarding the very existence of early censuses have
been raised by Krotki and Thakur (Krotki & Thakur,
1971: 89).
The first census on a more scientific and
systematic basis in Nepal started only in 1952-54.·
This was also the first modern and complete census
of Nepal using internationally accepted concepts
and comparable to censuses of other countries
(Department of Statistics, 1958: 1). Census of
1952 was carried out in the two areas of the country
in two different years. The eastern part of the
country was covered in 1952 except Mahottari district
and the census of the central and western parts
including Mahottari was completed in 1954. Since
1952/54 three more censuses on modern lines were
conducted in 1961 1 1971 and latest being in 1981.

I 33
~ ,
3.4 Population in the Present Century:
.,
.~ By 1981 Nepal has completed eight successive
censuses in the country.
Size and gro\·;th of population
in Nepal from 1911 to 1981 are presented in
Table 3.2.
\Vhen the data given in Table 302 for
the last seventy years are looked into they reveal
three distinct periods in the demographic history
of Nepal: (a) 1911 to 1930, (b) 1930 to 1961, and
(c) 1961 to 1981.
During the first phase of demographic
history, i.e., 1911 to 1930, the size of
population of Nepal v:as declining and the net decrease
in the country's population vias about 107 thousand.
Some of the important reason~
for this decline are:
(a) heavy casuality of the Gorkha troops in the
First \·lorld vlar, (b) high incidence of mortality due
to Influenza epidemic of 1917, (c) large scale recruitment
of Gorkha soldiers to serve in the British
army dUI:ing FiI:st l"loI:ld Hac, and (d) undeI:enumeration
in the 1920 and 1930 censuses (ESCAP, 1980: 12). Thus
one can conclude that the natural increase of population
growth has very little to do with the absolute
decline in population of the country; instead it was
a combination of natural calamities and undercounting.

34
• r'-<
,i~Table
3.2: Population Size and Gro\Jth in Nepal,
1911 to 1981
Census
year
population
Intercensal
var ia tion (%)
Annual Growth
Rate
(Geometric)
1911
5,638,749
1920
5,573,788
-1.15
-0.13
1930
5,532,574
-0.73
-0.07
1941
6,283,649
13.57
1.16
1952/54
8,256,625
31.39
2.30
1961
9,412,996
14.00
1.65
1971
11,555,983
22.76
2.07
1981
15,020,839
30.00
2.66
Source: Central Bureau of Statistics (1987):
Population ?-bnograph of Nepal, Table 1.2

1 SEC UeRJRY 8 lNG 6 l()RE
A~. N _.~.? _':?-~_4... . - ......... -
18· 6 91
R 304-, 609 0,+9 ~
35
~~R
In sharp contrast to the period between
1911-1930 the following thirty year period between
1930-1961 recorded an increase of over 3.89 million
population.
During this period population growth of
Nepal was positive and erratic. The annual grouth
rate which was 1.16 per cent during 1930-42, reached
to 2.30 per cent during 1942-52/54 and again
declined to 1.65 per cent during 1952/54-1961 • During
1930-41 period two important events occurred; one is
the earthquake of 1934 which took significant number
of lives and the second is a large scale recruitment
of Nepalese soldier s for the Second World \·Jar.
The
sudden spurt in the annual rate of growth of population
from 1.16 per cent during 1930-41 to 2.30 per
cent during 1941-1952/54 appears to be rather unusual.
The phenomenal increase during this period could be
partly explained by the return of discharged military
personnel after Second Wo~ld
War, and better enumeration
of country's population in 1952/54 (Selvaratnam,
1973: 18).
The population gro\tlth of Nepal has been much
more rapid after 1961. As a result of the very high
annual growth rate of 2.11 per cent and 2.66 per cent

36
during 1961-71 and 1971-81, respectively, the population
during last two decades has shot up by 5.6
million. The main reason for such a rapid and unprecedented
growth rate in population after 1961
could be attributed to the rapid fall in mortality
rate without any corresponding decline in fertility
which remained almost constant at a high level. A
detailed discussion of the behaviour of the
components
of population growth will be deal t within the
subsequent chapters.
3.5 Population Distribution in Nepal:
The spatial distribution of population and its
change over time deserve some attention. The distribution
of the population of Nepal by its natural
regions for the census year 5
1952/54 to 1981 are
presented in Table 3.3.
One thing that strikes by looking at data in
Table 3.3 is that there is an unequal distribution
of population across the regions in relation to their
share of total area. 'nle Mountain region which
accounts for 35.2 per cent of the land area of the
country contained only 8.7 per cent of the total
,

Natural
Regions
Area in Percent Population
sq.km of total
(1981)
area 1952/54 1961 1971 1981
Mountain 51,817 35.2 -
1,138,610 1,302,896
(9.9) (8.7)
Hill 61,345 41.7 6,071,407 7,163,115
(52.5) (47.7)
Mountain 113,162 76.9 5,349,988 5,991.297 7,210,017 8,466,011
and Hill (64.8) (63.6) (62.4) (56.4) w
~
Terai 34,019 23.1 2,906,637 3,421,699 4,345,966 6,556,828
(35.2) (3604) (37.6) (43.6)
Nepal 147,181 100 8,256,625 9,412,996 11,555,983 15,022,839
Note:
The figure in the parenthesis indicates the percentage.
Source, Central Bureau of Statistics (1987): Population Monograph of Nepal,
Table 2.1 and Table 2.2.

38
population thus showing a lowest population density
of 25 persons per sq.km among other regions.
In contrast to this, the Terai region which accounts
for 23.1 per cent of land area contained 43.6 per
cent of the total population in 1981 thus recording
the highest population density of 196 persons per
sq.km. It is, however, interesting to note here
that the share of Hill region in the total population
which is 47.7 per cent is almost proportionate
to its land share of 41.7 per cent in 1981. It is,
thus, evident that there is significant interregional
differences in population distribution and
density in Nepal.
The phenomenon of unequal distribution of
population in relation to area is also equally true
arrong the sub-regions. The Western z..1ountain which
accounts for about 20 per cent of the total area
among all other sub-regions has merely 3.53 per cent
of the total population whereas the Eastern Terai
which accounts for al::ou t 10 per cent of the total
area contains 28.23 per cent of the total population
in 1981.

39
From the table it is also evident that there
is a gradual decline in the proportionate share of
Mountain and Hill in the total population over the
30 years period. It has declined from 64.8 per cent
in 1952-54 to 56.4 per cent in 1981. In contrast to
this, Terai region has been experiencing a steady
rise in its proportion to total population during
the same period. Terai region recorded an increase
by almost 9 per cent from 35.2 per cent to 43.6 per
cent during the same period. The gradual decline in
the proportion of population in Mountain and Hill
region and a steady rise in Terai region can be
attributed to out-migration from Mountain and Hill
to Terai region. During 1971-81 there was a net
transfer of 410,000 people from Mountain and Hill
region to Terai (CBS, 1987a: 19).
The spatial distribution of population in
Nepal and the changes in 1 t appear s to be mostly
influenced by environmental and geographical conditions.
Mountain region is sparsely populated probably
because of the unfavourable environmental and
geographical conditions like, rugged topography,
extreme cold climate, acute scarcity of cultivable

40
land, poor quality of soil etc., whereas Tera! is
densely populated because of the favour able geographical
co nell lions. like favourable terrain, availability
of cultivable land, better soil condition,
favourable climate etc. Owing to these geographical
factors the pattern of population distribution is
changing more in favour of Terai region.
Besides these environmental and geographical
factors the current developmental activities which
are mostly concentrated in Tera! region could
have also caused the pattern of distribution to
change in favour of Terai region. Further, the eradication
of Malaria from the Terai region has caused
a massive internal migration of the MOuntain and
Hill people for settlement in this region. Government's
resettlement programme of the Mountain and
Hill people to Tera! is also to a large extent
reSJPOnsible for the changing pattern of population
distribution in Nepal.

QiAPTER IV
BEHAVIOUR OF THE COMPONENTS OF POPULATION GROWTH

CHAPTER IV
BEHAVIOUR OF '!HE COHPONENTS OF PO PULA TION GRO.,"l}l
In view of the rapid growth of population in
Nepal in recent years, it is imperative to know the
behaviour of the components of population gro\'lth
i.e., fertility, mortality and migration. This may
help us to understand and explain the unprecedented
growth of population in terms of its components. In
order to understand their behaviour an attempt has
been made in this chapter to present the available
estimates of fertility, mortality and migration over
time. The possible determinants of the components
of population growth have also been indicated by
looking at the available literature for Nepal.
Until mid-1970s, there was no vital registration
system in Nepal. In view of this, mortality
and fertility rates have been estimated using the
census and survey data for various time periods. Data
available from Nepalese censuses like the census of
other developing countries suffer from underreporting
of deaths and births and hence the mortality and
fertility levels obtained from these data are not
reliable. However, demographers have applied indirect

42
techniques to obtain plausible estimates of mortality
and fertility for Nepal for various time
periods.
4.1 Mortality
1a. Crude Death Rate (CDR):
Various estimates of CDR available for Nepal
are presented in Table 4.1.
It is quite evident
from this table that in the early 19505 CDR was quite
high in Nepal and it varied between 30 and 44 (UN,
1960; Thakur, 1963) in early 1950s and between 22 and
32 in early 1960s (Gubhaju, 1974; Krotk1 and Thakur,
1971). The variations could be attributed to the
different techniques adopted to estimate this rate.
For example, Thakur after using backward survival
ratio method for the adjusted age data of 1952-54
census arrived at a CDR of 44 per thousand population
whereas Vaidyanathan and Gaige applied a quasi-stable
population model and arrived at an estimate of 36.7
for 1954.
The estimated CDR for 1971-81 was 13.5 and
a rrore recent estimate of 10.9 for 1984 has been
obtained by New Era (1986).
New Era, however, obtained
this estimate by using the direct information on

Rates Expect~on of Life
Male
at Birth
Female Both
Source/ Au tho J:
Male Female Both
1952-54 30
- - -
United Nations (1960)
1953-55 44 -
ThakUI: (1963)
1954 36.7 260 250 27.1 28.5 - Vaidyanathan and
Gaige (1973)
CBS (1987a)
1953-61 27.0 34.8 38.4 -
1961 32.0 30.2 33.0 Krotlti & 'lhakw: (1971)
1961-71 21.4 - -
37 00 36.6 36.8 CBS (1987a)
1961-71 -
200 186 - 42.9 38.9 Gubhaju (1974)
1971 24.0 - - 41.9 3901 U. S. BuI:eau of
• w
Census (1979)
1974-75 19.5 141 123 133 46.0 42.5 -
CBS (1976)
1976 22.2 128 138 134 43.4 41.1 CBS (1977)
- 1977-78 17.1 110 98 104 CBS (1978)
1971-81 13.5 144 150 147 46.3 4402 45.3 CBS (1987a)
1981 147 142 144* 50.8 48.1 49.5 CBS (1987a)
1984 10.9 - 110+ 52.9 New Era (1986)
Notel
FOI: details of the source please see bibliography
* refers to 1978
+ refers to 1981

.,
deaths which occurred during the two years preceding
the survey. With the existing levels of socioeconomic
development in the country the estimated
CDR of 13.5 for 1971-81 by CBS as well as the estimate
of 10.9 by New Era appear to be on the lower
side. However, the available estimates of CDR presented
in Table 4.1 clearly indicate a steady decline
in CDR over the years. The estimates of CBS also
suggest a decline by 50 per cent from 27.0 during
1953-61 to 13.5 during 1971-81. Despite this gradual
decline, the current CDR of Nepal is relatively high
compared to some of the other developing countries
of the wor ld.
lb. Infant Mortality Rate (IMR):
Like CDR several authors have attempted to
estimate the level
of IMR in Nepal by using indirect
techniques. A summary of the various estimates
are presented in Table 4.1. The earliest estimate
of IMR Was made by Vaidyanathan and Gaige for
1954 and they arrived at an estimate of 260 infant
deaths for male.s and 250 infant deaths for females per
thousand live births. The estimate was based on the
stable population technique applied to the adjusted

•
4S
age sex distribution of the 1952/54 census.
Similarly,
Gubhaju using the census age sex distribution
arrived at an estimate of 200 infant deaths
for males and 186 infant deaths for females.
More
recent estimates of IMR have come from various
other sources.
New Era (1986) has obtained an
estimate of 110 for the year 1981.
Nepal ~ertility
and Family Planning Survey, on the other hand, had
obtained an estimate of 103 for the year 1984 based
on the pregnancy history (Ministry of Health, 1987).
Similarly, using indirect technique Demographic
Sample Survey of 1986-87 estimated an IMR of 110-113
for the year 1983.
All these estimates point out
that there has been a considerable decline in IMR
in Nepal over a period of 35 years but the present
level of IMR is still on the higher side.
le.
Life Expectancy:
One of the indicator s of the mortality conditions
of a country is the expectation of life at
birth. A summary of the estimates of life expectancy
for Nepal is presented in Table 4.1. Variations
have been noticed in the estimated life expectancy
for the same year or period by different sources.

46
Gubhaju's estimates of 42.9 for males and 38.9 £Or
females for the period 1961-71 were considerably
higher than CBS estimates of 37.0 for males and
36.6 for females. Another notable observation is
that all the estimates for 1950s indicate a higher
life expectancy for females than males. But during
1960s this trend has been rever sed and also has
continued in the subsequent period depicting a
higher life expectancy for males than females.
Although
infant mortality in Nepal is found to be
higher for males than for females, child mortality
(between age one to five) is found to be higher for
females than for males (CBS 1987 a: 314). This may
partly explain the low life expectancy of females
compared to males. On the whole it can be concluded
from Table 4.1 that there has been a rise in the
life expectancy for males as well as females in
Nepal over last 35 years.
1d. Causes of Mortality Decline in Nepal:
The gradual decline in mortality level witnessed
in Nepal since 1960s could be attributed
mainly to the rapid expansion of public health facilities.
Prior to 1950s health facilities were

47
limited, preventive health care facilities were meagre,
and epidemic diseases like Cholera, Tuberculosis
Small Pox etc., were rampant. After 1950s many
health projects started providing specific preventive
services. The Malaria Eradication Organisation
was established in 1958, the Leprosy and Tuberculosis
Control Project in 1965, the Small Pox Eradication
Proj ect in 1967 and the NFPMCH (Nepal Family Planning
and Maternity and Child Health) Project in 1966. A
Community Health and Integration Division was also
established in 1969 with the aim of delivering more
community oriented health services which was subsequently
expanded in 1976 to form a part of Integrated
Cotmnlllity He~th Programme. These health projects
have contributed substantially in arr~sting the incidence
of epidemic diseases.
In addition to preventive health measures,
impressive progress also has been made in providing
curative health services. Prior to 1956 health faci-
1i ties were restricted to 34 hospi tala, 39 health
posts and 649 hospital beds. Now their numbers have
reached to 89 hospitals, 745 health posts, and
3,767 hospital beds in 1986. Similarly there has
been a significant increase in the health manpower

48
such as doctors, nurses and m1d\';ives, health loJOrkers,
etc. The decline in death rate has been mainly due
to the expansion of the public health programme
and
to the raising of the health standard of the population
during the last three plan periods (ESCAP,1980:49).
Another important factor which could be attributed
for the reduction in mortality level in Nepal
is the increase in the supply of piped drinking water
to a larger segment of its population. A heal th
survey carried out in one district of the Western
Hills in 1975 found that diarrhoea and gastrointestinal
disorders appeared to be the major causes
of death and ill health (Nepal, Institute of Medicine,
1975: 34). Similarly, in another study it. was found
that infective and parasitic diseases form the major
proportion (36%) of the diseases among the inpatients
in the hospital (ESCAP, 1980: 106).
Eradication
of intestinal parasites is possible through
improved water supplies and sanitation.
In Nepal
the percentage of the people benefitted by piped
drinking water has increased from 4.4 per cent in
1961-62 to 22.4 per cent in 1984-85. This must have
curtailed the deaths caused by intestinal parasites.

49
Malnutrition is still considered to be a great
hazard to the general health of the population. Very
high level of malnutrition among the children is
reported in several studies conducted so far. '!be
Nepal Health Survey Which was conducted in 1965-66
found that about 4 per cent of all children below 9
years of age are affected by "clinical malnutrition M
and also found the population of Nepal as a whole to
be strikingly unhealthy.
Pourbaix similarly found in
an anthropometric survey carried out in 1974 that 71
per cent of the surveyed children were reported to
have "stunted" growth -
low height for their age and
19 per cent were reported to have a problem called
"wasting" - low weight for their height (Thapa, 1980:
152). The Nepal Nutrition Status Survey of 1975
found a very low nutrition level in rural areas. The
survey \'/hich concentrated on children in mo st susceptible
ages found that 52 per cent of the children had
suffered from long term undernutrition, 7 per cent
from acute undernutrition and 4 per cent both from
acute and chronic undernutrition (Seddon, 1987: 69).

'" ,
f 50
.,
~
.(
4.2 Fertility
2a. Crude Birth Rate (CBR):
Various estimates of CBR are available since
1950s and there are considerable variations among
the various estimates of CBR as can be seen in
Table 4.2. For instance, it varied from a lowest
estimate of 40.0 per thousand (CBS) to a highest
estimate of 48.7 (Vaidyanathan and Gaige) during
1950s. The estimates of CBR for 1960s range from
41 to 47. Unlike the estimates for 1950s and 1960s,
the estimates available for 1970s do not vary much
and they are within the range of 42 to 43.4.
censuses three demographic sanple surveys were
conducted in 1974-75, 1976 and 1977-78.
Besides
T.hese ,sample
surveys together with Nepal Fertility Survey conducted
in 1976 provide more reliable estimates of
the CBR of the country for mid-1970s.
These estimates
also vary considerably.
'l1le variations in
these estimates "might rather be a reflection of the
relative efficiencies with WhiCh the different
surveys were carried out and processed than any real
differences in the level of fertility in successive
years N (CBS 1 1978: 2).

51
J
Table 4.2: Estimates of Crude Birth Rates,
1952/54-1981
•
Period!
Year
1951-61
1954
1961
1961-66
1961-71
1966-71
1971
1974-75
1976
1977-78
1971-81
1981
1981
1984
Central Bureau of
Statistics (CBS)
Estimate
40.0 (CBS, 1964)
41.0 (CBS, 1977)
-
42.87 (CBS 1974)
44.7 adjusted
(CBS, 1976)
46.8 adjusted
(CBS 1978)
42.6 adjusted
(CBS, 1978)
42.5 (CBS,
1987a) *
42.2 (CBS,
1987.t**
42.4 (C::BS,
1987a)***
-
Other Estimates
48.0 (u.S. Bureau of
Census, 1979)
48.7 (Vaidyanathan
and Gaige, 1973)
47.0 (Krotki and
'lhakur, 1971)
44.6 (U.S. Bureau of
Census, 1979)
-
43.8 (U.S. Bureau of
Census, 1979)
42.4 (Gubhaju , 1974)
-
45.5 adjusted (~nistry
of Heal th,
1977)
-
-
-
44.9 (Karki, 1984)
35.1 (New Era, 1986)
Note I
* Based on reverse survival ratio method
** Based on stable population model
*** Based on P/F ratio method.

52
In order to obtain the most plausible estimates
of CBR during 1980s, CBS has used three
different techniques.
From these estimates there
1s enough reason to believe that the CBR in 1981
was ,.,.i thin the narrow range of 42 to 43.
It
should, however, be noted here that Karki (1985)
wi th the application of plF (Brass) method obtained
a CBR of 44.9 for 1981 Which is higher by 2.5
births per thousand obtained by CBS for the same
method.
The inconsistency in the estimates could
probably be due to the selection of different
multipliers or correction factor by the authors.
From the estimates of U.S Bureau of Census
it is clear that there has been a steady decline
o ~ CBR in Nepal. CBR is reported to have declined
from 48 during 1951-61 to 44.6 during 1961-66 and
further to 43.8 during 1966-71.
In contrast to the
aboVe, the estimates obtained by CBS indicate a
steady rise in CBR over time. CBR is reported to
have increased from 40 during 1951-61 to 41 during
1961-71 and further to 42.5 during 1971-81
(Table 4.2).

53
2.b Age-Specific Fertility Rate (ASFR):
Slightly refined measure of fertility is the
ASFR.
Several estimates of ASFR by CBS are
available, Which are based on census or sample
survey data. The pattern of ASFR presented in
Table 4.3 indicate peak fertility for the 25-29 age
group.
Except in the case of one estimate all the
estimates display the highest ASFR for the 25-29
age group. However, in almost all ~1e estimates
the fertility levels in the age groups 20-24 and
25-29 differ-only slightly.
Thus ASFR in Nepal is more or less of the
broad peak pattern. Further, the pattern of ASFR
shown in the table may be described as an early
marriage, high fertility pattern. However, the
table suggests that much of the change in fertility
.
occurred among the younger age group 15-19. Fertility
has declined significantly for the age group
15-19 changing from 114 in 1974-75 period to 81 in
1981 (Table 4.3).

Table 4,31 Age-~ecific Fertili~ Rates, 1971-1981
per 1,000 Women
Year/
Period
15-19
Age-Specific Fertility Rates to Ages
20-24 25-29 30-34 35-39 40-44 45-49 TFR*
Source
1971 87
235 264 220 162 88 34 5,45
CBS (1987a)
1974-75 114
270 297 260 169 89 50 6.2
CBS (1976)
1976 138
305 284 252 170 95 34 6,0
CBS (1978)
1977-78 127
294 294 252 180 92 24 6.2
CBS (1978)
U1
~
1981 81
241 252 232 197 145 111 6.3
CBS (1987a)
*TFR = Tbtal Fertility Rate.

55
.c Total Fertility Rate (TFR):
Table 4.3 also presents the estimates of TFR
s obtained by CBS. It may be observed from the
able that all the estimates except in 1971 show
'an increasing trend over the years. It is evident
from the table that TFR has increased by at least
one child during the period 1971-81. The TFR of
6.3 in 1981 could be considered quite high When comparee
to some of the other developing countries of
the world (Table 4.3).
2.d Cumulctive Fertility:
Table 4.4 presents cumulative fertility measured
by the mean number of children ever born by
ever married women in their reproductive period.
From the table it is clear that there has been underreporting
of births in 1971 and 1981 censuses because
in both the censuses the cumulative fertility
estimates are quite low (4.0 in 1971 and 3.7 in
1981) • There appears to be better coverage of cumulative
fertility in the surveys 1976, 1984 and 1986
than in the censuses. This is evident from the
higher cumulative fertility of more than 5 live

56
~le 4.41
l-'!ean Number of Children Ever Born by
Current Age for All Ever Married Women,
1971-1986
Age
Group
1971 a 1976 b 1981 C 1984 d 1986 e
15 - 19 0.3 0.3 0.4 0.5 0.5
20 - 24 1.1 1.4 1.2 1.6 1.5
25 - 29 2.2 2.9 2.1 2.9 2.8
30 - 34 3.1 4.1 3.0 4.0 4.0
35 39 3.7 5.1 3.4 4.8 4.8
40 - 44 4.0 5.5 3.7 5.5 5.5
45 - 49 4.0 5.7 3.7 5.8 5.7
Source
a ·•
CBS (1975 a)
b ·•
Ministry of Health ( 1977)
c ·•
CBS (1984 a)
d New Era (1986)
e ·•
CBS (1987 b)

57
births per \t.1Oman by the end of 49 years. The
cumulative fertility in 1986 has still remained
close to that of 1976 thus indicating a little or
no change in cumulative fertility over the last
ten years.
An analysis of the various measures of fertility
indicate that there is no appreciable decline
in the fertility level, and the present level of
fertility in Nepal is considerably high compared
to some of the other developing countries of the
world.
Some of the important factors responsible
for such a high level of fertility in Nepal are
examined below.
2.e Determinants of Fertility:
One of the important factors responsible for
high fertility in Nepal is low male and female ages
at marriage. Although the female as well as male
age at marriage are still low in Nepal, an upward
trend in age at marriage is evident. Female singulate
mean age at marriage which was estimated to be
15.1 in 1961 increased to 16.7 in 1971 and further
increased to 17.1 in 1981 (CBS, 1987a: 101).
The

58
singulate mean age at marriage for females in
1986 as estimated by Nepal Fertility and Family
Planning Survey is 18.9 (l-1inistry of Health, 1987:
61). This showed a significant rise in the age
at marriage by almost t~~ years during 1981-86.
In Nepal studies on the impact of a rise in
age at marriage on fertility are lacking. However,
a study made by Tuladhar and others indicated that
by increasing the mean age at marriage for females
upto 21 years, the growth rate of the population
may be reduced to 1.8 per cent (Tuladhar et. al.,
1975). It has been claimed that if female age at
marriage climbed to 19 or 20 years the fertility
reductions resulting there from would be in the
range of 16-30 per cent (Rao et.al., 1986: 71).
But in Nepal according to the latest estimate for
1986 the female age at marriage has not yet reached
19 years. Thus we may infer that because of slow
rise in age at marriage in Nepal its impact on
fertility may be negligible.
Mari tal status is also an important demographic
factor Which affects the fertility behaviour.
Until 1976 there has been an increase in the

59
proportion of ever-married ~umen in the age group
of 20-24. This has increased from 92.1 per cent
in 1971 to 94 per cent in 1976. However, there
has been a drop after 1976 as the proportion of
.ever-married women in the age group 20-24 has
dropped from 94.0 per cent in 1976 to 86.9 per cent
in 1981 and to 85.2 per cent in 1986 (Table 4.5).
One change that has been observed is that there has
been an increasing proportion of singles in the
younger age group 15-19. The proportion of single
or never-married in the age group 15-19 has increased
from 39.3 per cent in 1971 to 61.8 per cent
in 1986. Thus the higher proportion of ever-married
w:>men at the peak of their reproductive span is an
important factor for the higher level of fertility
in Nepal.
The persistent high birth rate in Nepal is
supported by the larger propor tion of the younger
female population in the age group of 0-14. In
fact, the proportion shows an increasing trend in
successive censuses: 38.55%, 40.50% and 40.74% in
1961, 1971 and 1981, respectively. Due to the
higher proportion of younger female proportion in the

TaJ:Ue 4.:>1 percengge D1Stl10UCIOii 01 L46feZ Narried and Ever-Married Women, 15 Yeaz:s
of Age and Above, 1971-1986
Age of
Women
1971 Census 1 1976 NFS1 1981 Census l NFFS 1986 2
Never Ever Never Ever Never Ever Never Evez:
Married Married Married Married Married Married Married Married
15 - 19 39.3 60.7 37.3 62.7 49.2 50.8 61.8 38.2
20 - 24 7.9 92.1 6.0 94.0 13.1 86.9 14.9 85.2
25 - 29 2.7 97.3 1.8 98.2 5.3 94.7 4.2 95.8
30 - 34 1.4 98.6 1.2 9808 3.1 96.9 1.8 98.2
0\
0
35 - 39 1.1 98.9 0.6 99.4 2.6 97.4 008 99.2
40 - 44 0.9 99 0 1 0.5 99.5 2.5 97.5 1 0 6 98.4
45 - 49 0.8 99.2 0.7 99.3 2.9 97.1 1.4 98.6
Sources 1. CBS (1987 a)
2. Ministry of Health (1987)

61
age group of 0-14 higher proportion of the young
females enter into the reproductive age group Which
could again lead to rise in the fertility level.
One of the important reasons for the continued
higher level of fertility in Nepal could be the'
lower contraceptive prevalence rate. Although there
}las been a steady rise in the knowledge as well as
use of contraceptives in Nepal over the years the
present prevalence rate can be considered as very
low. Only 15.8 per cent of the currently married
women of group 15-50 are reported to have ever used
any method of contraception in 1986 and the percentage
of current users is even smaller at 15 per cent
(Table 4.6). The table also indicates that there has
been a significant rise in the knowledge about
family planning. '!he proportion of currently married
women ever heard of any f&~ily planning device has
increased from 22.1 per cent in 1976 to 51.9 in 1981
and this has further increased to 55.9 per cent in
1986.

62
Table 4.6: Percentage of Currently r-:arried Women Who
Have EVer Heard of Family Planning, Ever
Used a Method and Currentlz Using a Method)
1976-1986
Type NFS1 NCPS 2 New Era 3 NFFS4
1976 1981 1984 1986
1. Ever Heard of
a Method 21.3 51.9 55.9
2. Ever Used a
Method 4.0 8.6 20.8 15.8
3. Currently Using
a Method 3.0 6.8 16.7 15.1
-
Note: The NFS 1976, NCPS 1981 and New Era 1984
refer to women aged 15-49 years While NFFS
1986 refers to women aged 15-50 years
Source: 1. Ministry of Health (1977)
2. Ministry of Health (1983)
3. New Era (1986)
4. IIlinistry of Health (1987)

63
4.3 Emig~ation and Immig~ation:
The contribution of international migration
(aifference between emigration and immig~ation)on
the population growth of Nepal has always been
a
matter of debate.
This is because data on emigration
and immigration are extremely limited in Nepal
(Islam et.al., 1982).
Most of the available estimates
on emigration and immigration come from
different censuses and sample surveys and are
summarized in Table 4.7. On the whole, the importance
of migration on the population growth of Nepal
cannot be minimised.
q
3.. Estimates of Immigration and Emigration in
NepalI
'!be censuses of 1941 and 1952-54 of Nepal
obtained information only on emigrants (Nepalese who
were away from Nepal for at least six months of the
year) as both the censuses did not elicit any information
on irmnigration.
So the net effect of international
migration could not be ascertained till
1952-54. '!he number of emigrants were 81,817 in
1941 which increased to 198,120 in 1952-54. In terms
of percentage of the total enumerated population 1 t
was 1.30 per cent and 2.34 per cent in 1941 and

.A.g....., ... 'Q" -...,. .......::::I'-' ..... IUCJ.\..c:D VI.. ,,-~~'-&1I1"C' U' ......... hii4L9:&:CSCl:a:U •• 0"0 -,_yU. •
Year/
Period
Net International
Immigration Emigration Migration Source
(Immigration-
Emigr ation)
1941 NA 81,817 (1.30) NA Kansakar (1974)
1952-57 NA 198, 120 (2.34) NA Kansakar (1974)
1961 337,620 (3.6) 328,470 (3.35) +9,150 Kansakar (1974)
1971 337,448 (2.9) 486,600 -149,152 CBS (1975 b), India,
Office of the Registrar
General ( 1974)
1974-75 34,000 43,000 -9,000 CBS (1976)
1976 44,000 73,000 _29,000 CBS (1977)
1978 44,000 72,000 -28,000 CBS (1978)
1981 234,039 (1.55) 402,977 (2.7) -168,938 CBS (1984 b)
1986 28* NA CBS (1987 b)
0'1
.;:..
NA = Not Available
* per 1000 population
Figures in parenthesis refer to the percentage to the total population.

65
1952-54, respectively. The 1961 census estimated
328,470 emigrants and 337,620 immigrants (foreign
born population residing in the country) resulting
in a net immigration of 9,150 persons. The 1971
census enumerated 337,448 immigrants but did not
collect any information on persons who had left
Nepal. However, the Indian census of 1971 recorded
486,600 immigrants from Nepal thus resulting in a
net emigration to the magnitude of 149,152 persons
provided we accept the estimate of immigrants
from Nepal recorded in Indian census of 1971. It
should, however, be noted here that both the
Nepalese and Indian censuses have provided a divergent
figure on the volume of Nepalese emigrants to
India in 1951 and 1961. The 1981 census of Nepal
recorded 402,977 emigrants and 234,049 immigrants
resulting in a net emigration of 168,938 persons.
However, it is believed that there has been a undercounting
of immigrants in 1981 census (CBS, 1987b:
29) •
The Deroographic Sample SUrvey of 1974-75
estimated the number of emigrants and imnigrants
as 43,000 and 34,000, respectively, thus resulting
in a net loss of 9,000 persons from the country. A

66
survey conducted in 1983 revealed that the Terai
region alone had received 418,748 immigrants. The
survey also reported that the annual growth of
immigrants was 4.5 per cent per year since 1958
(Karki, 1987: 26).
Similarly, the Demographic
Sample Survey of 1986 estimated that there were 28
immigrants per thousand population for the country
as a whole which amounts to about 481,749 persons.
The comparable figure in 1981 census was 16 immigrants
per 1000 population for the country as a
whole. This apparent discrepancy between census and
Demographic Sample Survey on immigrants are mostly
due to the under counting of immigrants in the
census (CBS, 1987b: 29).
There exist conflicting versions regarding
the movement of people in and out of Nepal and its
importance in
the population growth of the country.
New Era observed the migration of Nepalese to India
as a safety valve for over population in Nepal
(New Era, 1981: 135).
In contrast to this, the
ARTEP study showed that the relative magnitude of
immigration and emigration probably underwent
a change during the sixties with the result
that Nepal had a net immigration of about 190,000

67
persons per year during the period 1966-1971 (ARTEP,
1974: Appendix 1-0.2). On the contrary, CBS has
ignored the effects of net international migration
on population growth in view of lack of reliable
data on emigration and immigration (CBS, 1987a: 13).
3b. Causes of Inrnigration and Emigration:
Even if serious doubts have been raised on
the reliability of emigration and immigration data,
it cannot be denied that there has been a considerable
arrount of migration from and to the country.
Both "push" and "pull" factor s have been attributed
as the possible reasons for this roovement.
The push
factors leading to emigration appears to be nonavailability
of usable land for cultivation, increas-
,ing concentration of land ownership, population
pressure and declining agricultural productivity
(Banister and Tbapa, 1981: 76). These push factors
appear to be roore prominent in l-lountain and Hill
regions.
Similarly, the pull factors in the foreign
land were better economic opportunity in India
including attractive salary, better education, open
border and cultural and religious ties, etc.

68
A survey conducted in 1983 revealed communal
riots, lack of peace, inadequate employment, declining
economic condition, family tension and quarrels
as the main push factors for the movem~n~. These
reasons were indicated by immigrants. The pull
factors operating in Nepal and particularly in
Terai region were business in agriculture and wood
products, lack of skilled labour in Nepal, open
border, cultural and religious ties, etc. The
National Commission on Population has pointed out
that out of a total of 418,748 foreigners in Nepal,
49 per cent came to Nepal for employment specially
in the urban areas and about 20 per cent of the total
immigrants came 00 Nepal for trade and commerce
(Karki, 1987: 20).
Marriage is also considered as one of the
important causes for the movement of population in
and out of the country- The movement of women
across the Nepal India border for the purpose of
marriage has not been a one way phenomenon. In 1961,
the sex ratio of the foreign born in Nepal was only
56 males per 100 female immigrants and in 1971 it
was only 58 males per 100 females (Tuladhar et.al.,

69
1978: 41). This ratio carne down to 44 in 1981
census (CBS, 1984b: 78). One reason for the low
sex ratio of foreign born persons in Nepal could
be that many women from India move into the nearby
Terai region to marry and settle down. Similarly,
there could also be movement of women from
Nepal to India, for the same reason. The increase
in Nepalese born female population from 216,200
to 239,600 as reported in 1961 and 1971 Censuses of
India probably indicates the movement of Nepal
born women to India for marriage continued during
the 1960s (Banister and Thapa, 1981: 80). Stressing
the importance of marriage as the cause of
immigration of Terai women to bordering districts
of India, Davis observed that ·in the border
districts of Bihar, for instance, there were only
37 males to every 100 females of Nepalese birth,
while in non-border districts the ratio was 303
per 100· (as cited in Poffenberger, 1980: 50). All
these clearly reveal the role of marriage in the
emigration and immigration process in Nepal to
the neighbouring states on the Indian side.

CHAPTER V
REGIONAL PATTERNS OF POPULATION GROWTH

CHAPTER V
REGIONAL PATTERNS OF POPULATION GRO~TH
In this chapter, an attempt has been made to
discern the regional patterns of population growth
in Nepal.
In view of the nature of data available
three different reference periods are selected, viz.,
1911-1981, 1952/54-1981, and 1971-1981. For the
reference period 1911-1981 an attempt has been made
to discern the patterns by three regions. Similarly,
for the second reference period 1952/54-1981, the
country has been divided into four broad regions and
population growth has been analysed by these regions
and their sub-regions.
For the reference period
1971-1981, attempt has been made to discern the patterns
of population growth by districts.·
It should, however, be mentioned here that the
main limitations of the analysis of first two periods
is that both suffer from the problem of non-comparability
of data due to internal boundary changes. However,
they throw some light on the patterns of population
growth by regions and sub-regions.
The analysis
for the third period does not suffer from this
problem as the boundary adjusted figures are available
and,hence, the data are comparable.

71
5.1 Patterns of Population Gro\lth by Regions,
1911-1981:
In order to discern the patterns of population
growth during 1911-1981 the country is divided into
three regions: (a) Mountain and Hill (hereafter will
be called Hill region in this section and subsequent
section ), (b) Kathmandu Valley, and (c) Terai. It
should be noted here that ~~untain
and Hill regions
are in fact separate regions and Kathmandu valley
falls under Hill region. The type of classification
which has been followed here, however, is mainly
guided by the availability of data. Time series data
are available by three regions as mentioned above.
There are significant variations in the rate of growth
of population between sub-regions in each of these
regions but since the data are available only from
1952/54 onwards this has been dealt separately in the
subsequent section.
The unequ~
size of population coupled with
the differential rates of growth between 1911 to 1981
has led to uneven patterns of population growth
between the three major regions of the country.
The
annual rate of growth of the three regions during 1911
to 1981 are presented in Table 5.1. Among the three

72
Table 5.1:
Annual Intercensal Growth Rate
(Geometric) for Regions of Nepal,
1911-1981
REGIONS
Intercensal
period Hill Kathmandu Terai Nepal
Valley
1911 - 1920 -0.51 0.60 0.36 -0.13
1920 - 1930 -0.02 1.56 0.04 -0.07
1930 - 1941 1.65 1.81 0.03 1.16
1941 - 1952/54 2.44 2.15 2.70 2.30
1952/54 - 1961 1.42 1.42 2.06 1.65
1961 - 1971 1.09 3.01 3.38 2.07
1971 - 1981 1.43 2.16 4.12 2.66
- -
1911 - 1971 1.05 1.26 .L.U ~
1911 - 1981 1.10 1.39 h12 1.41
Source: ESCAP (1980), Population of Nepal .. Countr~
Monograph Series No.6, p.16
Central Bureau of Statistics (CBS) (1984),
Population Census, 1981, General Characteristics
Tables, Vol.1, Part 1.

73
regions, Hill region has experienced the lowest growth
in population during 1911-1981.
In the first two
decades the Hill region experienced negative rate of
growth in population followed by a sudden high annual
growth rate in the subsequent decades.
This was again
followed by the low population growth rate in the
remaining three decades from 1952/54 to 1981.
Thus,
the Hill region does not seem to have experienced a
systematic growth during the whole period. On the
whole the rate of population growth in this region can
be considered as moderate.
The population growth pattern of Kathmandu
Valley is more or less the same as that of Hill
region.
In the initial two decades this region has
experienced a slow and negative growth.
This is followed
by a higher growth in subsequent decades.
The
growth rate of population in Kathmandu Valley has not
been systematic. But on the Whole the rate of population
growth in this region could be considered high.
Terai region is the fastest growing region
during this period.
It has experienced higher growth
compared to national growth during six decades out of
total seven.
This region has never experienced

74
negative growth during the period.
There has been
a continuous rise in annual growth rate since
1952/54. Among all the regions the population
growth in this region has been high or very high.
Better insights into the pattern of population
growth in Nepal can be obtained for the second reference
period which also takes into consideration the
sub-regions within each region.
5.2 Patterns of Population Growth by Sub-Regions,
1952/54 - 1981:
Like the inter-regional differences in the
population gro~~
rate there are also remarkable
differences among the sub-regions of each region. To
analyse the patterns of population growth by subregions
for the period 1952/54 -
1981 we have again
divided the country into four different regions.
In
this section Tera! region is further divided into
Inner Terai and Terai. Each region except Kathmandu
Valley is further divided vertically from east to west
into three sub-regions and they are illustrated in
l-~ap 5.1 * In the case of Kathmandu Valley I however,
* In the map Mountain and Hill regions are separately
shown even though both are considered here as one
region. In the subsequent section Mountain and
Hill regions are separately treated.

./'J"
r~··
l."
/w EST E! ~ N ~.
""
: .--.., .
~
REGIONS AND SUB-RESIONS OF NEPAL
.., o .1(1
.se. .. : 1 :2000 000
'"
JII .;to .....
~
£. ~ ~I ? ~
;- ( M 0 IJ N T A I N\.,./"'"' .. '7
~ oS' ') ..,...-..,
(~~:,.- '\ ~ ~
. ~'" ~ ~
-"'r"",, ~
~.1.- .. "'-
~
"" t
~ C
a: N T ~
A
I. flO ~" (I 1""-"'" .J'-7'
\ ,.. z.. < \..// _ W l.....,.. "-...............
"'~/'v:"N\ ~J~""--. / /
",,\ ~ -i'
1
~;::-,< H I L I... I ~
'J::i;~:.. ~A ~E T~A'-:..: "'
~ C If N R A c: N .. (CO.
')
~~ .. 0-'~- \..
R A I ~ Ar N
AS.,.
It n", '" 0 II N r A. I Ii.-
til
C M ~ CENTRAl.. MOUNiAIN
K V : I

76
this is not desired btcause of its typical valley
topography.
1. Hill a) Eastern Hill
b) Central Hill
c) Western Hill
2. Inner -Terai a) Eastern Inner Terai
b) Central Inner Terai
c) Western Inner Terai
3. Terai a) Eastern Terai
b) Central Terai
c) Western Terai
4. Kathmandu Valley
Table 5.2 gives the annual rate of growth of
population by regions and sub-regions during 1952/54-81
period.
·Within the Hill region, Central Hill is experiencing
higher growth
compared to Eastern and
Western Hill.
It may also be observed that the
annual rate of growth of population does not show a
marked difference among the sub-regions of Hill region
unlike in other sub-regions.
When annual rate of
growth of population during 1952/54-1971 are compared

77
Annual Intercensal Gro~th Rate (Geometric)
of Population for Regions and Su~Regions
of Nepal, 1952/54 - 1981.
egions and
ub-Regions
Period
1952/54 1961-71 1971-81
-61
1952/54
-71
1952/54
-81
• Hill
astern Hill
entral Hill
estern Hill
1.42
1.24
1.60
1.43
1.09
0.76
1 0 58
0.88
1.43
- 1.17
1.51
i.63
1.24
- 0.98
1.59
1.12
1.31
- 1.04
1.56
1.30
2. Kathmandu
Valley
3. Inner Tera1
astern Inner
Terai
entral Inner
Terai
Western Inner
Terai
1.42
0017
0.29
1.24
2.99
5.46
2.16
-
3.77
2.82
4.73
2.48
1.78
3.57
2.94
2.15
3.98
4. Terai*
Eastern Terai
Centr al Ter ai
Western Tera1
All Nepal
2.37
2.57
1.73
1.81
1.65
3.24
2.99
3.59
4.58
2.07
4.20
- 3.61
4.87
6.93
2.66
2.85
2.81
2.76
3.34
1.88
- 3.09
3.33
3.51
4.61
2.16
Source:
Central Bureau of Statistics, Population Censuses
of 1952/54, 1961, 1971 and 1981.
* The Terai region has been further split into Inner
Terai and Terai, hence the figure for Terai
appeared in Table 5.1 and Table 502 do not correspond
with each other.

78
with that of 1971-81, Eastern Hill has been experiencing
low to moderate growth as compared to
moderate growth of Central and Western Hill.
Inner Terai has experienced a very rapid
growth in population especially after 1960s. Wi thin
Inner Terai region Western Inner Terai bas experienced
fastest growth in population during the same
period. It should also be noted that among all the
sub-regions Western Inner Terai region is also the
second fastest growing sub-region during the entire
period. The population growth among the three subregions
of Inner Terai varies appreciably. specially
during 1961-71.
However, the variations have
declined in the subsequent period. It is also
interesting to note that the growth rate 1n the
region increased from Eastern to Western Inner Terai.
During the whole period. population growth of Eastern
Inner Terai has been frem low to highl aDd. in the
case of Central and Western Inner Terai the growth
rate can be considered as high and very high,
respectively.

79
All the three sub-regions in Tera! are
experiencing rapid growth in population during the
period 1952/54-81, the Western Tera! being the
fastest one among them and also among all other subregions
within the country.
It is only t.1Us region
and its sub-regions which have also got the
distinction of a continuous rise in annual growth
rate of population in all the decades.
Growth rate
bas also increased from Eastern to Western Tera!
except dUring 1952/54-61. Like the Inner Tera!,
significant variations can also be observed in the
growth rates of population within the sub-regions
of Terai and these variations are becoming 1arger over
time. On the whole, the rate of growth of population
of Eastern and Central Tera! bas been hi9h to very
bigh as compared to very high of Western Terai.
5.3 Patterns of Population Growth by Districts,
1971-81:
Here an attempt has been made to explain the
variations in population growth across districts in
terms of its c~nents and discern the patterns. To
fulfil this objective we need to decompose population
9rowth into its components viz., (1) Crude Death

80
Rate (CDR), (2) Crude Birth Rate (CBR), and (2)
Rate of Net Migration (RNM).
The information on
the components of natural increase (births minus
deaths) and net migration for all 75 districts are
not available. These components have been estimated
for all the districts as well as for five
regions and their sub-regions.
The indirect demographic
techniques adopted in estimating the CBR
and CDR are explainecL below in detail.
The p/F Ratio method originally developed
by Brass has been used to estimate the adjusted
age-specific fertility rates (Brass, 1975).
Using
the adjusteq age-specific fertility rates (AASFR)
adjusted crude birth rates (ACBR) have been esti-
mated. While adopting this technique P 2/F 2 * and
P3/F3 * have been considered separately as a correction
factor for adjusting the age-specific fertility
rate. From the AASFR, ACBR have been obtained both
for P 2
/F2 and P,!F3.
The average of these t\III'O has
* P2 and P 3
refer to children ever. born of women
in the age group 20-24 and 25-29, respectively,
while F 2 and F 3 are estimated average cumulative
fertility levels.

81
been considered as a representative rate for the
particular year. Main reason for selecting P 2
/F2
and P3/F3 as a correction factor for adjusting the
ASFR is that the data for these age groups 20-24
and 25-29 are expected to be more accurate as the
events are more recent and pari ties are low. In
the case of higher age groups the data are likely
to be affected by recall lapse. In the case of
early age group of 15-19 the number of events are
usually small. The estimates of ACBR are obta1.ned
separately for 1971 and 1981 and the average of the
two has been considered as the intercensal ACBR for
the period 1971-81.
Similarly, for the estimation of crude
death rate (CDR) in the fu st stage Trussel' s
method of estimating child mortality was adopted
(Trussel, 1975). This method is essentially a
Trussel variant of the original Brass method. First
we estimated value of proportion dead among children
ever born to women in each of the age group 15-19
to 45-49. This information was used to estimate
the probability of dying (~) and probability of

82
surviving children by age x (lx) corresponding to
the age of women by using Trussel multipliers
(UN, 1983). It was assumed here that ·West"model of
Coale and Demeny Model Life Table was representative
of true mortality patterns of Nepal. Because
it was confirmed that the age pattern of infant
and child mortality from the Nepal Fertility Survey
1976 fits quite closely with the pattern implied
in the ·West· model of the Coale and Demeny Model
Life Table (Goldman et.al •• 1979). Using the
averages of 13 (probability of surviving from birth
to age 3) and 15 (probability of surviving from
birth to age 5) the mortality level was identified
for 1971 and 1981, separately for both sexes following
the ·West· model. 13 and 15 correspond here to
women in the age group of 25-29 and 30-34, respectively.
In the final stage age-specific death
rates corresponding to identified level of mortality
were then applied to the age distribution of population
of 1971 and 1981 censuses for male and female
separately to arrive at the total nud::>er of deaths.
The average of 1971 and 1981 deaths was considered
as the total number of deaths during 1971-81. These

83
deaths duzing 1971-81 were again divided by midyear
population of 1971-81 to obtain the crude
death rate during 1971-81.
It should be mentioned here that we did
not rely on census survival method or stable popula
tion model as both the methods are ba sed on the
assumption of closed population.
But for the district
level estimate, as in our case, this assumption
does not seem to be
realistic. The method
which we adopted also suffers from some other
limitations. It is important to note that this
method of estimating child mortali ty is based on
the assumption that fertility and child mortality
must have remained constant in the past. In the
case of Nepal, fertility has almost remained constant
while mortall ty has been decllning lnthe
recent past. The reference period to which the
child mortall ty xefers uses the coefficient given
by Trussel. It was found that the 13 estimate
refers to a period of about 4 years before the census
and lS estimate to a time of about 6 yeaxs before
the census.
Since the mortality level estlmates
axe based on the average of 13 and 15 it can be
said to represent the level sometime at about

84
5 years before the 'Census. Therefore, this would
be a good approximation of average mortality
level during the decade.
However, to the extent
the child mortality deviates from the "West- pattern
the adul t mortality could be affected. After
having obtained the ACBR and CDR the balancing
equation technique was used to arrive at the rate
of net migration during 1971-81.
There may be some degree of error in the
estimates.
However, in the absence of the estimates
for all the 75 districts they provide some
indication about the differences with regard to the
components of population growth.
Information OD
rate of total increase and its components by districts
and regions and their suD-regions are pre-
Table
sented in Tabla 5.3 andiS.4, respectively.

85
Table 5.3: Rate of Total Increase and Its ComEonen t§
for the Districts of Ne~al during 1971-81
Sl.
No. District. RTI RNI RNM ACBR CDR
1. Taplejung 6.7 26.40 -19.70 40.27 13.87
2. Panchathar 5.3 28.67 -23.37 44.40 15.73
3. Ilam 7.6 31.93 -24.33 43.86 11.93
4. Jhapa 76.5 32.12 +44.38 43.72 11.60
5. Terathum 1.6 23.15 -21.55 40.75 17.60
6. Dhankuta 16.3 26.34 -10.04 40.96 14.62
7. Morang 61.7 30.22 +31.48 42.59 12.37
8. Sunsari 37,.5 32.03 + 5.47 43.69 11.66
9. Sankhuwasabha 8.4 26.88 -18.48 42.28 15.40
10.- Solokhallbu 7.9 22.89 -14.99 41.58 18.69
11. Bhojpur 8.0 24.97 -16.97 43.53 18.56
12. Khotang 6.1 26.93 -20.83 42.23 15.30
13. Okhal dbung a 10.5 24.22 -13.72 42.94 18.72
14. Udayapur 33.1 29.77 + 3.33 44.79 15.02.
15. Saptari 26.4 28.81 - 2.41 38.71 9.90
16. Siraha 21.9 25.84 - 3.94 41.12 15.28
17. Dolakha 11.8 25.47 -13.67 42.36 16.89
18. Ramechap 4.0 26.00 -22.00 43.87 17.87
19. Slndhull 21.20 29.65 - 8.45 47.37 17.72
Contd ••

86
Table' 5.3 (contd •• )
51.
No. D1str1c::t RTI RNI RNM ACBR CDR
20. Dhanukha 27.2 29.78 - 2.58 41.58 11.80
21. Mahottcu:1 19.2 20.78 - 1.58 38.33 17.55
22. Sar1ah1 41.4 24.86 +16.54 39.41 14.55
23. S1ndhupalchowk 10.8 22.33 -11.53 39.20 16.87
24. Rasuwa -16.3 28.58 -44.88 40~48 11.90
25. Nuwakot 19.2 25.13 - 5.93 41.69 16.56
26. Dhad1ng 13.4 22.10 - 8.70 42.37 20.27
27. Kavrepalanchowk
23.8 24.73 - 0.93 39.78 15.05
28. Bhaktapur 27.0 26.36 + 0.64 42.73 16.37
29. Kathmandu 21.2 22.04 - 0.84 37.44 15.40
30. Lal! tpur 25.8 24.48 + 1.32 40.43 15.95
31. Makwanpur 36.7 30.10 + 6.60 45.78 15.68
32. Ch!twaa 35.2 31.91 + 3.29 43.84 11.93
33. Rautahat 26.3 10.47 +15.83 31.83 21.36
34. Bara 31.7 24.62 + 7.08 33.7. 9.12
35. Parsa 34.7 17.62 +17.08 32.92 15.30
36. Gorkha 20.8 15.58 + 5.22 33.35 17.77
37. Lamjung 19.8 22.14 - 2.34 41.12 18.98
38. Tanahu 29.6 22.04 + 7.56 36.88 14.84
39. Syangja 8.6 23.28 -14.68 42.01 18.73
40. Kaski 30.0 22.01 + 7.99 36.72 14.71
contd ••

87
Table 5.3 (contd •• )
51.
No. District RTI RNI RNM ACBR CDR
41. Manang -5.7 18.02 -23.72 35.05 17.03
42. Mustang -4.8 11.77 -16.57 29.24 17.47
43. Myagdi 14.5 29.99 -15.49 45.24 15.25
44. Parbat 15.0 28.11 -16.61 44.54 16.43
45. Baglung 27.5· 25.26 + 2.24 42.30 17.04
46. Gulmi 7.5 28.31 -20.81 45.87 17.56
47. Palpa 18.3 22.75 - 4.45 39.33 16.58
48. Nawalparasi 53.1 28.32 +24.78 44.67 16.35
49. Rupendehi 45.3 26.52 +18.78 39.38 12.86
50. Kapilyastu 27.8 18.58 + 9.22 34.32 15.74
51. Arghakhanchi 19.1 27.22 - 8.12 41.83 14.61
52. Pyuthan 7.5 21.11 -13.61 41.01 19.90
53. Rolpa 3.2 24.81 -21.61 47.06 22.25
54. Rukum 23.2 29.53 - 6.33 48.03 18.50
55. Salyan 21.0 22.95 - 1.95 46.13 23.18
56. Dang 36.0 39.51 - 3.44 52.01 12.50
57. Banke 46.3 21.71 +24.59 37.21 15.50
58. Bardiya 68.3 20.03 +48.27 37.57 17.54
59. Surkhet 26.5 26.30 + 0.20 46.43 20.13
60. Dailekh 13.0 27.75 -17.45 48.47 20.72
61. Jajarkot 13.8 21.65 7.85 46.25 24.60
62. Dolpa 14.4 20.46 - 6.06 39.73 19.27
contd ••

88
Table 5.3 (contd •. )
S1.
No. District:.... RTI RNI RNM ACBR CDR
63. Jumla 14.4 13.54 + 0.86 48.28 34.74
64. Kalikot 18.6 24.45 - 5.85 43.73 19.28
65. Mugu 43.7 21.18 +22.52 47.16 25.98
66. Humla -27.2 7.77 -34.97 36.81 29.04
67. Bajura 19.8 8.73 +11.07 40.53 31.80
68. BajhaD:g 13.3 20.07 - 6.77 36.45 16.38
69. Acbham 12.5 17.95 - 5.44 40.15 22.20
70. Dot! 18.5 21.84 - 3.34 40.95 19.11
71. K811a11 66.6 27.70 +38.30 42.05 14.35
72. Kanchanpur 93.9 27.20 +66.70 40.29 13.09
73. Dade1ahura 36.8 19.57 +17.23 40.42 20.85
74. Baitadi 13.5 14.77 - 1.27 34.79 20.02
75. Darchu1a 18.5 16.53 + 1.97 38.72 22.19
Nepal 26.6 25.35 + 1.25 41.05 15.70
Note I RTI - Rate of Total Increase
RNI - Rate of Natural Increase
RNM - Rate of Net Migration .
ACBR - Adjusted Crude Birth Rate
CDR - Crude Death Rate.

89
Table 5.4: Rate of Total Increase and Its Components·
for Regions and Sub-Regions of Nepal«
1971-81
Regionsl
Sub-Regions
RTI**
RNI
RNM
ACBR
CDR
1. Mountain
Eastern Mountain
Central Mountain
Western Mountain
11.26
9.53
-11.98
16.26
19.69
24.80
19.45
16.59
- 8.43
-15.27
-31.43
- 0.33
40.11
41.14
34.92
41.42
20.42
16.34
15.47
24.83
2. Hill
Eastern Hill
Central Hill
Western Hill
15.75
10.35
18.21
17.22
24.22
26.33
24.15
22.56
- 8.47
-15.98
- 5.94
- 5.34
42.28
42.48
41.02
43.60
18.06
16.15
16.87
21.04
3. Kathmandu
Valley
4. Inner Terai
Eastern Inner
Tera!
Central Inner
Terai
Western Inner
Terai
23.49
33.00
24.30
32.18
- 0.81
+ 0.82
40.20
46.75
15.90
14.57
26.53 29.71 - 3.18 46.08 16.37
35.92 31.01 + 4.91 44.81 13.80
36.06 39.51 - 3.44 52.01 12.50
5. Tera!
Eastern Tera!
Central Tera!
Western Ter a1
41.56
37.23
42.37
66.12
25.40 +16.16
25.20 +12.03
24.48 +17.89
26.66 +39.46
39.62
38.88
39.46
41.78
14.22
13.68
14.98
15.12
Note: * The estimates of CDR and ACBR referred in Table
5.4 for regions and their sub-regions are average
rates obtained by adding up the rates of all the
districts together falling in each region and
sub-region. District falling in each region and
sub-region are presented in Appendix 5.1.
** Boundry adjusted.

90
Crude Death Rate (CDR): CDR ranges from a very low
level of 9.12 per thousand per year in Sara district
of
Terai region to a very high rate of 34.74 in
Jumla district of Mountain region. The CDR of Jumla
district appear s to be abnormally high.
However
there are two other districts of Mountain region
whose CDR are also close to 30 or more
• They
are Humla with 29.04 and Bajora with 31.80. CDR
also varies across regions, the maximum being 20.42
per thousand per year in Mountain region and minimum
being 14.22 in Terai region. Variations in CDR is
more glaring across sub-regions. It is the highest
wi th 24.83 in Western Mountain region and lowest with
12.50 in Western Inner Terai.
Crude Birth Rate (CBR): Like CDR, CBR also varies
appreciably across districts in Nepal.
It ranges
from a very high rate of 52.01 per thousand per
year in Dang district to a low rate of 29.24 in
Mustang district. Among regions it varies marginally
from 46.75 in Inner Terai region to 39.62 in Terai
region. However, across sub-regioDs again the variations
are quite large. It varies from a highest rate
of 52.01 in Western Inner Terai to a lowest of 34.92

91
in Central Mountain.
It should be noted here that
variations in both CBR and CDR across districts are
larger than regional and sub-regional variations.
Rate of Natural Increase (RNI):
It has already been pOinted out that there are
variations in CDR and CBR across districts, regions
and sub-regions.
These variations in CDR and CBR
have resulted in the variations in RNI in population.
It varies from a very high rate of 39.51 persons per
thousand per year in Dang district to a very low rate
of 7.77 in Humla district. Between regions and subregions
the range of variation is not as large as in
districts. It varies from 32.18 in Inner Terai
region to 19.69 in Mountain region.
In the case of
4-
sub-regions it ranges from maximum of 39.51 in
,.
6-
Western Inner Terai to minimum of 16.59 in Western
'"
Mountain.
Rate of Net Migration (RNM)I
Like RNI, the RNM also shows significant
variations across districts. It ranges from a very
high rate of net in-migration of the Order of 66.70
persons per thousand per year in Kanchanpur district
to a rate of net out-migration of the order of -44.88

92
persons per thousand per year in Rasuwa district.
Similarly, between regions and sub-regions also it
ranges from a very high rate of net in-migration of
the order of 39.46 in Western Terai to a very high
rate of net out-migration of the order of -31.43 in
Central Mountain. In the case of regions it varies
from a high rate of net in-migration of 16.16 in
Terai region to a net out-migration of -8.43 in
Mountain. It 1s interesting to note that out of the
total 75 districts almost two-third of the districts
i.e •• 46 have experienced net out-migration with
varying magnitudes from low to very high during 1971-
Sl. Remaining 29 districts have experienced net inmigration
during the same period.
Rate of Total Increase (RTI):
SUbstantial variations in the RTI across
regions, sub-regions and districts can be seen from
Table 5.3 (for districts) and Table 5.4 (for regions
and sub-regions). The RTI varies from a very high
level of 93.90 per thousand per year in Kanchanpur
district to a negative growth of -27.20 per thousand
per year in Humla district during the period 1971-81.

93
Across regions the RTI varies from a high rate of
41.56 in Tera! region to a low rate of 11.26 in
Mountain region. Similarly, across sub-regions the
RTI varies from the very high level of 66.12 per
thousand per year in Western Terai region to a negative
growth of -11.98 in Central Mountain region.
Based on the discussion provided so far it
would be interesting to know whether any typical
patterns of population growth could be discerned on
the basis of which a meaningful groupings of districts,
sub-regions and regions can be made. In order to do
this the following cut off points separately for RTI,
RNI and RNM are adopted. However, the selection of
cut off points are rather arbitrary.
Rate of Total
Increase
Very
high 30 above
High 20 to 30
Moderate
10 to 20
Rate of Natural Rate of Net
Increase Migration
very
high 20 above
Higb 15 to 20
very high
net inmigration
+10 above
Moderate
10 to 15
High net
inmigration
+5 to 10
Low net
1nmigration
+5 to 0
contd ••

94
Rate of Total
Increase
Low o to 10
Nega- Less
tive than 0
Rate of Natural
Increase
Low Below 10
Rate of Net
Migration
Low net outmigration
0 to 5
High net
outmigration
Very high
net outmigration
-5 to -10
-10
above
Classification of districts into the above
mentioned categories of RTI, RNI and RNM are
illustrated in Maps 5.2, 5.3 and 5.4 respectively.
Table 5.5
presents the patterns of population
change observed between regions, sub-regions
and districts of Nepal.

-
1
1
i
!;
~
I
I
]
:! .
0
a
0
•
~.

~
~
0
0
~ g
~ 10)
~
0
§
i
n ~
f..
~
(!)
15 ~
it, ~ A
~ ~
:J) u
( U
.J~
J
~
0

MAP £0.4
. . .
... . . . . ,-.
~:.~
..
ACCORDIN6 TO RATE OF NET MIGRATION
sc.olol: J:.aoo 000
a t - 6C1 100 ltD llJO "' ...
N
II
I
VB!RY HI6H NIlT IN-MIeRA/ION
HIGH NET IN-MIGRATION
LOW NET IN-MI6~AT/ON
..
..... .. LO~ NET OUT-MIGAAT/ON
HI6H NET OUT-MIGRATION
h' · .. ··.7 VERY HI6H NET OUT-MIGRATION
171te.rnaUoYla.L Bw.w:Ia!!f -h
.Pisinct BounJa!'y
__ --

Patterns of Population Change, 1971-81.
Type Patterns of Population Change Regions/Sub-Regions Districts
Total
No.of
districts
1. VIr! H1gh Rate of Total Increase 19
a. Very High Rate of Natural Terai,Eastern, Central 4, 7,22, 48, 49,
Increase and Western Terai 57, 58, 65, 71, 72 10
A.
b. Very High Rate of Net
In-migration
a. Very H1gh or H1gh Rate of 8, 31, 34, 40, 35,
Natural Increase
--- 73 6 \0
B.
00
b. Very H1gh or H1gh Rate of
Net In-migration
a. Very High Rate of Natural Inner Terai, Central 14, 32, S6 3
Increase
and Western Inner
c.
Tera!
b. Low Net In-migration or
Low Net Out-migration
2. Hiah ~~1;~LQf Total Increas. 16
A.
a. Very High, High or Moderate
Rate of Natural Increase
-
33, 36, 38, SO 4
b. Very High or High Rate of
Net In-migration
-
eontd •••

Type Patterns of Population Change Region/Sub-Regions Districts
Total
No.of
districts
a. Very High Rate of Natural
B. Increase 28, 30, 45, 59 4
b. Low Net In-migration
a. Very High Rate of Natural Kathmandu Valley and 15, 16, 19, 20
c.
Increase Eastern Inner Terai 27, 29, 54, 55
b. Low or High Net Out- "
migration
3. Moderate Rate of Toral Increase 23
\0
a. Very High or High Rate of Mountain, Hill, 6, 13, 17, 23, 25, \0
Natural Increase Eastern, 'Central, 26, 43, 44, 51, 60, 15
A.
Western Hill 61, 62, 64, 68, 69
b. Very High Net Out-migration
a. Very High Rate of Natural,
B. Increase
---
21, 37, 47, 70 4
b. Low Net Out-migration
a. High or Moderate Rate of
c.
Natural Increase Western Mountain 63, 74, 75 3
b. Low Net In-migration or
Low net Out-migration
contd •••
8

Type
Patterns of Population Change
Regions/Sub-Regions
Districts
Total
No.of
districts
D.
a. Low Rate of Natural Increase
b. Very Higb Rate of Net
In-migration
67
1
4. Low Rate of Total Increase
a. Very High Rate of
Natural Increase
5.
A.
B.
b. Very High Rate of Net
Out-migration
Negative Rate of Total Increasl
a. Very High or High Rate of
b. Very High Rate of Net
Out-migration
a. Moderate of Low Rate of
Natural Increase
b. Very High Net Out-migration
Bastern Mountain
Central Mountain
---
1, 2, 3, S, 9, 10,
11, 12, 18, 39, 46,
52, 53
24, 41
42, 66
13
4
-
2
2
....
o
*
Because of the problem of space districts are represented by numbers which correspond
with the serial numbers in Table 5.3.

101
Entire Terai, Central and Western part of
Inner Terai and 19 out of 7S districts have
emerged as the areas of very high growth during
1971-81. The rate of natural increase in these
districts during the decade is very high. In
addition to this, the districts belonging to this
category owe their very high growth to considerable
amount of net in-migration. Of the 19
districts belonging to this category, 16 districta
are experiencing very high or high rate of net
in-migration.
Among geographical regions and sub-regions
it is only the Kathmandu Valley and Eastern Inner
Terai which recorded a high growth of population
during 1971-81. Sixteen districts also recorded
a high growth of population. With regard to the
components of population growth in one set of
districts the high growttl of population could be
attributed to both very high rate of natural increase
and net in-migration. The another set of
districts although have experienced low or high
net ou~gration have exhibited high RTI only
because of very high RNI.

102
Areas belonging to moderate category are
Mountain, the Western part, Hill and its Eastern
and Central part. Interestingly, a maximum number
of districts of 23 fall within this category. The
contributing factors in this category are not as
clear as in very high and high category.
The
varying magnitudes from low to high of both RNI
and RNM could be attributed for moderate growth in
population.
The low category includes 13 districts and
Eastern part of Mountain.
The low growth of population
of this category can be attributed mainly
to considerable amount of net out-migration as all
districts recorded a high degree of net outmigration
during 1971-81.
Central Mountain region as well as " districts
have experienced a strikingly high loss of
population during 1971-81.
The negative growth of
population in these districts is also the result
of very high degree of net out-migration from
these districts.

103
From the above discussion it is quite
evident that variations in the rate of growth of
population across regions and districts in Nepal
are systematically related to variations in both
rate of natural increase and rate of net migration.
It may also be concluded that migration
is probably more important than rate of natural
increase in determining the variations in the
rate of total increase in population because the
variations in rate of Det migration are quite
large than the variationsin rate of natural
•
increase.

Req~on8/Sub-Req~ons and The~r CorresponC~ng D~5tr~cts
Mountain
Hill Kathmandu Inner Tera! Terai
Bastern Central Western Valley
Eastern Eastern Eastern
Taplejung Panchathax Nuwaltot Pyuthan Bhaktapur Udayapur Jhapa
Sanskhuwasabba 118111 Dhading Rolpa Kathmandu Sindhuli Moxang
Solokhambu Terathum Gorkha Rulcum Lal!tpur
Central
Sunsari
Dolakha Dhankuta Lamjung Salyan Saptar!
S1ndhupalchowk Bhojpux Tanahu Surkhet Makwanpur S!raha
Khotang Syangja Da11ekh Ch!twan Dhanukha
Cen~
Okhaldhunga Kaski Jajarkot Mahottar!
Rasuwa Ramechap Myagdi Accham Westexn Sarlah!
Manang KavrepalaD- Parbat Doti Rautahat
Mustang chowk Baglung Dadeldhura Dang Baxa ....
0
Palpa Ba1tad1
Western
Parsa or:.
Arghakhanch!
Dolpa
Central
Jumla
Kal!kot
Nawalparasi
Mugu
Rupendeh1
Kap1lvastu
Humla
Bajura
~ajhang
Oarchula
Western
Banke
Bardiya
Ka!lal!
Kanchanpur

CHAPTER VI
LEVELS OF AGRICULTURAL DEVEIDPMENT AND
PATTERNS OF POPULATION GROWTH
•

LEVELS OF AGRICULTURAL DEVELOPl·:ENT AND PATTERNS OF
POFLJLATION GRm'lTH
6.1 Introduction
Agriculture occupies a proQinent place in
less developed countries (LDCs) as the majority of
people earn their livelihood from this sector. In
most of the LDCs all out efforts are being made to
increase the agricultural output.
Green revolution
is now spreading in many LDCs.
This has led to
higher agricultural productivity and has also altered
the modes of production and economic relationships in
the country side. Since agricultural development and
population growth art very much inter-related the
potential consequences of agricultural development
efforts on demographic developments are of concern.
The objective of this chapter is to understand
the patterns of population growth by levels of
agricultural development in Nepal.
The chapter
begins with the conceptual framework wherein the
mechanism of the effects of agricultural development
on the components of population growth has been spelt
out. In the next section, certain relations has been
hypothesized between agricultural development and

106
population growth and its components. This is
followed by a review of relevant literature pertaining
to the relationship between agricultural
development and population growth. In the subsequent
two sections the overview of agricultural
development in Nepal and the indicators selected
to represent the agricultural development have been
presented. Finally, in the last section, we have
attempted to discern the patterns of population
growth and its components by levels of agricultural
development in Nepal.
6.2 Conceptual Framework
It has been generally accepted that the cause
and effect relationship between agricultural development
and population growth can run both ways i.e ..
population growth once generated has significant
influence on the agriculture sector in terms of
supply of labour, and demand for food. S1miluly,
the changes in agriculture may influence the population
growth via its components. Because any development
in agriculture may alter the course of
mortality, fertility and migration and, as a result,
the rate of growth of population.

107
To start with, response of fertility as a
consequence of agricultural development seems rather
uncertain. It may have both positive as well as
negative effects on fertility (Basu, 1978). As
agricultural development occurs farm income and
several other economic variables undergo significant
change. These changes aLe postulated to have
an ultimate effect on demand dimension of tertili ty
behaviour though the impact is to a large extent
indirect. The negative effect i.e •• its effect to
reduce fertility by influencing the demand for
children follows essentially the following paths.
1. One of the important components of agricultural
development is the use of improved agricultural
practices such as purchase of improved seeds,
chemical fertilizers. plant protection materials,
tube wells.implements, etc., Which finally increase
the agricultural productivity. The use of improved
agricultural practices requires more working capital.
As the demand for working capital increases with
improved agricultural practices, changes in 'life
style' take place particularly for those directly
benefitted from agricultural development. Such

108
changes in life style together: with exposure to ur:ban
ar:eas influence the individuals' psychological perspective
on children. This is particularly reflected
through higher aspirations for children which
influence the perceived economic costs of children
i.e., nurture cost, education cost, opportunity cost.
All these costs are likely to influence the demand
for additional children and, hence, the fertility
(Basu, 1978). Similarly, a rise in agricultural productivity
not only increases income but also raises
the reward for the labour performed outside the home
i.e., wages. This m~es the rearing of children more
expensive which,in turn,may cause fertility to
decline (Basu,1978; Mueller, 197.; Kulkarni, 1981,
Ali, 1981).
2. Agricultural mechanization which is also a
part of agricultUral development works as a mechanism
of labour saving and thus re4uces the value of children
as productive agents on the farm and may decrease
fertility.
3. Agricultural modernization is expected to
increase the supply and availability of food thereby
reducing malnutxi tion. This leads to decline in
infant mortality rate. The decline in infant

109
mortality rate will affect the fertility directly
through lactation effect and indirectly through the
desired number of surviving children. Both these
effects will lead to reductions in fertility.
4., Agricultural progress will increase rural
income and hence reduce the resource constraint on
fertility decisiQns (Mueller, 1974).
Agricul tural development sometimes may also
induce to have more children. This positive response
follows the following paths.
1. Agricultural development is followed by an
increase in agricultural activity which creates more
work opportunities and also leads to growth in
allied sector (i.e., trade) thus leading to higher
demand for labour. This coupled with increased
ability to bear the cost of rearing children as a
result of an increase in per capita income may
increase the demand for children (Ali, 19811 Basu,
1978).

110
2. Agricultural development leads to an increase
in productivity and income. '!he rise in income may
increase fertility directly through increased nutrition
and improved health condition of spouse
(Seetharam, 1971; Cassan, 1976; FAO, 1977).
3. Agricultural processes being nUmerous,a large
family is sometimes considered to be an asset unless
agricultural processes are intensively mechanised.
From the foregoing discussion it is rather
difficult to ascertain any unidirectional change in
fertility in response to agricultural development in
LOes.
The behaviour of mortality in response to
agricul tural development is somewhat certain. Agricultural
development also implies intensive cultivation
and the intensive cultivation given the transportation
facility will diminish famines. Similarly,
agricultural development is accompanied by ample
food supplies per capita and, thus, the improvement
in level of nutrition which reduces the frequency of
malnutrition and hence the deaths caused by malnutrition
(Mueller, 197.). On the other hand,

111
agricultural development sometimes may also cause
mortality to increase. The increase in mortality
could be due to salinity and water logging resulting
from the introduction of irrigational facilities as
both may spread epidemics like cholera, malarialete.
However, the mortality rising impact of agricultural
development related activities is less recognised
than its mortality reducing impact.
The position of migration again seems to be
80IDewba t UD

112
area (Seetharam,1971; Rao and Sahu, 1987). Thus,
the provision of irrigational facilities provides
scope for in-migration of farmers and labourers.
In-migration, however, would be quite large initially
but over a period of time it will get stabilized.
On the other hand, in the event of more and
more mechanisation in agricul ture along with a
widening non-agricultural sector in the urban areas
there is the possibility of migration from rural to
urban areas.
6.3 Hypothesized Relationships:
On the basis of conceptual framework provided
above following relationships could be hypothesized
between agricultural development and population
growth and its components:
1. The response of fertility to agricultural development
could be both positive and negative. The
negative effect operates through several intermediate
variables such as:changes in the attitude towards preferred
family size due to higher parental aspiration,
increase in the perceived cost of children, employment
aspirations of women, adoption of modern methods of

113
contraception, etc. All these will tend to reduce
fertility. Similarly, the positive effect operates
through increasing ability to bear the children,the
improved health condition of spouse, children as
an asset to derive various utilities from them. All
these will tend to increase fertility. Because of
both positive and negative effects of agricultural
development on fertility,it is rather difficult to
ascertain any unidirectional change in fertility in
response to agricultural development in its initial
stage. Thus, an uncertain relationship could be
hypothesized between the two.
2. The mortality response to agricultural devel~nt
mainly operates through better standards of
and
living L ample supply of food per capita which increase
the level of nutrition and thus reduce
the
deaths caused by malnutrition. A negative relationship
between the two is, thus, hypothesized.
3. Due to observed negative J:elationships between
agJ:icul tUJ:al development and mortality levels and
uncertain J:elationsh1p between agricultural development
and fertility levels the nature of the relationship
between agricultural development and rate of

114
natu~al inc~ease in population will also be unce~tain.
This ~elationship, howeve~, may not always
hold true as the ~ate of natu~al inc~ease may be
mo~e influenced by the behaviou~ of mortality and
less of that of fe~tility.
4. Development of agriculture gene~ally leads to
an increase in demand for labour at least during
certain seasons. This attracts the labour from neighbouring
areas through higher wage levels. Development
of agriculture, on the othe~ hand, may also
lead to decrease in out-migration of labour which
otherwise would have occurred. The reduction in outmigration
and an increase in the inflow of mig~ation,
both tempo~ary and seasonal, will add to the
growth of population in agriculturally prosperous
areas. Thus,a positive association between agricultural
development and net mig~ation could be bypothesized.
5. As already stated, £e~tili ty behaviour in the
early stage of agricultural development is not ce~tain.
However, mortality tends to be inversely
~elated and net migration tends to be positively
related with agricultural development.
Therefore, it

115
could be hypothesised tgat population growth rate
will also be higher in the areas undergoing the
process of agricultural transformation.
6.4 Empirical Findings from Other Studies:
In this section a brief review of the available
studies on the relationship between agricultural
development and population growth is presented. Few
related studies carried out in other countries are
only reviewed here as there appears to be no
studies on Nepal on this specific issue. The review
focusses on the findings of these studies with
regard to population growth and its components as
related with agricultural development.
(1) Agricul tural Development and Fertility'
In his study of Ta1wan,Japan and South Korea,
Kocher (1973) observed the simultaneous trends of
declining fertility, enhanced agricultural productivity
and increasing egalitarian rural income distribution.
Mueller (1974) looked at the historical
record of the change in demographic and agricultural
development in Taiwan, Japan and Punjab (Indian State)
and found that there was a temporary rise in birth

116
rate due to the increase in agricultural production.
But over time fertility declined due to reduced
mortality rates, increase in perceived costs of
children with higher parental aspirations and changes
in the attitude towards preferred family size. Mueller
(1971) in her another study,Where she analyzed the
island-wise sample survey data of 675 Taiwanese farmers,found,in
general, agricultural development
altering the attitude of farmers towards the economics
of family size. She also found that there was a
decline in the perceived utility of children as
productive agents on the farm and as a source of
economic security. Mean ideal family size was also
found negatively related to income measures.
The
data, however. did not support the hypothesis that
high income per se leads farmers to feel that they
can support more children.
Singh (1978) in his study of Punjab State of
India did not find any clear relationship between
agricultural development and fertility and thus concluded
that the impact of agricultural development
on fertility is mostly indirect. Basu and others
(1979) conducted an exploratory study of 14 villages -

117
8 experimental and 6 control-in Gujarat State of
India to evaluate the impact of green revolution on
demographic behaviour. They found that agriculturally
developed villages had a lower cumulative
fertility than undeveloped villages. Ali (1981)
in his study of impact of agricultural modernisation
on crude birth rate in 11 districts of Indian
Punjab, pOinted out that agricultw:al improvements, if
equally distributed, lead to decline in fertility.
Chaudhary (1983) in Bangladesh found a positive
relationship between rate of growth of agriculture
output and child women ratio. However, this relationship
was not statistically significant. Faxooqui
(1984) in the process of identifying the important
factors responsible for bringing about the sustained
reduction in rural fertility level in Pakistan
observed that the rise in rural income of the farmers
from agriculture sector has a depressing effect
on fertility. However. the results were not statistically
significant. Levy (1985) tried to find out
the effect of mechanization, changing cropping
pattern and farming profitability on fertility in
the context of Egyptian agriculture for 1975-76. '!be
findings of the study supported the hypothesis that

118
mechanization has a negative effect on fertility
because of the substi tute for child labour.
The
change in cropping pattern in terms of shift from
cotton farming where the demand for labour is very
high to vegetable farming had a negative effect on
the demand for child labour and desired family
size, and thus concluded that the high labour
the
intensity in cotton farming is one o~basic conditions
motivating Egyptian farmers to have relatively
large families •.
(2) Agricul tural Development and Mortalitya
Mueller (1974) in her study of Taiwan, Japan
and Punjab (InMan State) found the reduction in
dea th rate in all the three countries due to
advancement in agriculture. Singh (1978) in his
study of the impact of agricultural development on
demographic transition in Punjab found an inverse
relationship between agricultural development and
mortality. Ali (1981) in his study of 11 districts
of Indian State of Punjab found that agricultural
improvements lead to decline in infant mortality
rate.

119
(3) Agricultural Development and Natural Increase
in Population:
ESCAP (1975) conducted a comparative study of
population growth and agricultUIal change in three
selected countries, namely, Japan, Sri Lanka, India.
The study was addressed to test the hypothesis that
agricultural changes are not related to the rate of
natural changes in population. The study found that
agricultural changes are not, by and large, related
to change in the rate of natural increase in population.
(4) Agricultural Development and Migration:
ESCAP (1975) study va~ also addressed to test
the hypothesis that agricultural changes are related
to migration. This hypothesis was supported by the
findings of the study of Sri Lanka but not by those
studies of Japan and India. However, it is worth
noting here that in the Indian State of Punjab during
1951-61 the rate of growth of agricultural production
was positively and significantly correlated with
rate of migration. In the. state of Orissa, the
study revealed that demographic variables do not bear
any systematic relationship with agricultural changes
during 1951-71.

120
A Study by Mitra and Mukherji (1980) which was
based on distl:ict level agricu1 tural and demographic
data covering 282 districts in India pointed out an
unexpected finding of experiencing out-migration by
the higher order agricultural productivity districts
and attracting population through in-migration
by
lower order productivity districts. Choudhary (1983)
found a positive relationship between rate of growth
of output and net migration. Districts experiencing
high growth in agricul ture output in Bangladesh experienced
high net inmigration and districts with
low growth in output experienced net out-migration.
s. Agricul tural Development and Population Growth,
Mueller (1974) in her study of 'l'aiwan, Japan
and Punjab (Indian State) found that the initial
consequence of agricultural development and amelioration
of economic conditions vas a sharp rise in population.
Bhattacharjee (1978) using the district as
the unit of analysis in Karnataka state of India for
1951-71 found positive correlation between growth in
agricul ture and in the growth of rural population. It
was also found that the districts having higher grcnith
111 agriculture have gained population in rural areas

121
through in-migration. There was also the increase in
labour force in primary sector in higher agriculture
growth districts. Thus he concluded that there is a
tendency for high rate of population growth particularly
rural population to be associated with high
rate of agricultural development.
A study conducted
by Booth (1985) in Japanese agriculture found that
the areas having greatest agricultural potential were
having rapid population growth and the important
factor responsible for this was migration.
High fertility
and lower mortality were found to be not so much
responsible for the rapid population growth.
6.5 Agricultural Development in Nepala A Brief
Overview:
Agriculture occupies a very significant place
in the economy of Hepal..
This sector alone contributes
about 59 per cent of the total GDP in 1984-85.
About 91 per cent of the economically active population
is engaged in this sector. Agriculturi!products
alone constitute more than 60 per cent of all exports.
Therefore, it is obvious that the fortunes of all the
agr icul tur al worker s as well as the economy depend
on its performance. Similarly, the raw materials

122
required by the industrial sector is mostly produced
in agriculture and forest sector.
It is because of
its predominance in the economy and its close inputoutput
and demand linkages with the non-agricultural
sectors, agricultural development constitutes an
essential component of the strategy for the overall
development of the country.
From the inception of its planned effort for
development in 1956, His Majesty's Government of
Nepal has been paying attention to develop the agricul
tural sector. This is mainly through various programmes
such as land reforms, research and extension
of improved technology, distribution of improved
seeds and fertilisers, irrigation facilities and
command area development, integrated rural development
programme, agricultural credit, co-operatives
and support price measures. As a result of these prograrnmes,Nepalese
agriculture has undergone some
changes.
Attempt has been made in Table 6.1 to present
data to indicate the agricultural development in
Nepal during last two decades with the help of some
selected indicators. From the table it is evident

123
that in the last two decades, agriculture sector in
Nepal has experienced a marked improvement as
all
other indicators except one experienced a steady
increase over a period of time.
Nepal had in 1961-62, a total cultivated area
of 1,685,000 hectares which was around 12 per cent
of the total land area. Over time the cul ti va ted
area has gone up to 2,638,000 in 1981-82 which
amounts to about 18 per cent of the total land area.
This increase reflects an annual growth rate of 2.83
per cent during the period 1961-81.
Cropped area
has also increased from 1,662.000 hectares to
hectares
4,291,000Lwith an annual growth rate of 7.91 per
cent during the same period which is quite high COlllpared
to the rate of increase in cultivated area.
As a resul t of this the cropping intensity has gone
up from 98.6 to 162.65 during the same period. It
is thus evident that about 63 per cent of the total
cultivate~ area is used for cultivation more than
once.
Even more conspicuous was the rise in the
area under high yielding varieties which increased
from meagre 12,500 hectares (0.64 per cent of total
cropped area) 1n 1964-65 to 1,161,500 hectares
(27.06 per cent of total cropped area) in 1981-82

124
thus showing an addition of 1,149,000 hectares
under high yielding varieties.
Total irrigated area has also gone up substantially
from 58,000 hectares in 1961-62 to 584,000
in 1981-82, an addition of 526,000 hectares during
the period. As a result of this, the irrigated area
as a percentage of total cropped area has gone up
from 3.49 per cent to 13.61 per cent. There has
been an impressive increase in the use of chemical
fertilisers as its use has shot up from 2,096 metric
tons in 1964-65 to 56,459 metric tons in 1981. Thus,
the average use of fertilisers stood at 13.15 Kg.
per hectare of cropped area in 1981 compared to
1.09 kg in 1964-65. With regard to the mechanisation
aspect of Nepalese agriculture, there were only
64 tractors and 30 pumpsets in 1964-65. The number
of tractors reached 4,315 in· 1981/82 and pumpsets
reached 5,225 in 1975. It should, however, be noted
the..
here that due to nature of terrain in the hill
A
areas and relatively smaller size of farms there,
the use of tractors and pumpsets are mainly concentrated
in Terai (Banskota, 1980: 105).

125
Farmer co-operatives have gone up from 293
in 1975-76 to 713 in 1981-82. The total loan
disbursement by Agricultural Development Bank for
various agricul tural development activities has
also risen from 1.6 million rupees in 1964-65 to
256 million rupees in 1980-81. The increase in the
various inputs in agriculture over time has resulted
in the steady ri se in the index of agricul tural
production from 82 in 1961-62 to 115 in 1974-75 and
a further rise to 129 in 1981-82.
In spite of these achievements, the average
yield of agricultural products has remained stagnant
or declined. This has resulted in a decline in
per capita food (cereals) availability from 335 Kg
in 1961/62 to 257 Kg in 1981/82 (Table 6.1). There
has also been a deterioration in the distribution
of land holdings in Nepal despite the implementation
of land reform programmes in 1960s. '!'he study by
Lee and others on the distribution of ownership of
land holdings showed a very high level of Gin! coefficient
of 0.57 and 0.69 for 1961 and 1971, respectively
(Lee et.al., 1982&40). This problem
appears to have continued. even in 1981.
The sample

126
Census of Agriculture in 1981 showed that two-third
of the total households have holdings less than
one hectare and account for merely 17.4 per cent
of the total cultivated land whereas about 9 per
cent of the households have holdings of more than
3 hectazes controlling 47 per cent of the total cultivated
land.
It should be mentioned here that there exist
wide regional variations in the levels of agricultural
development.
The cultivated land is unevenly
distributed among the regions. The average size of
land holding in Mountain and Hill regions in 1981/82
1s 0.12 hectare, whereas in Terai region it is 0.21
hectare. Extent of mechanization, and irrigational
facilities are quite high in Terai region compared
to Mountain and Hill. Similarly #
the consumption of
chemical fertilizers is high and the area under HYVs
is more in Terai region compared to Mountain and
Hill.

~ .&.::JfO.l.-o.c.
Indi.cators 1961-62 8 1964-65 b 1969-70 c 1974_75 d 1981-82 e
1. Cultivated area ('000
hectares) 1,685 1,831 1,980 2,326 2,638
2. Cropped area ('000 hectares) 1,662 1,917 2,193 2,364 4,291
3. Cropping Intensity + 98.6 104.7 110.8 102.6 162.65
4. Area under HYV's ('000
hectares) NA 12.5 140.7 548.5 1161.5
(0.65) (6.42) (23.70) (27.06)
5. Irrigated Area 58 68 128 182 584 t-J
-.J
( • 000 hectares) (3.49) (3.55) (5.84) (7.70) (13.61)
6. Consumption of chemical NA 2,096 15,898 36,361 56,459
fertilisers (metric ton) (1.09) (7.25) (15.38) (13.15)
7. Total No.of tractors NA 64 293 2,245 4,315
8. No.of pumpsets NA 30 900 1,870 5,225*
9. No.of Co-operatives NA NA 293 713
10. Per capita availability
of cereal grains (Kg.) 335 301 307 257
....
contd ••

Ind:1cators 1961_62 a 1964-6S b 1969-70 c 1974_7S d 1981-82 e
11. Total Agr icul tur al Development
Bank loan disbursement
(millions Rs.)
NA
1.6
34 181 256
12. Indices of Agricul tural
production (Base triennium
ending 1969-70 • 100)
82
96
-
115 129
Notesl + Cropped Area / Cultivated Area x 100
* Refers to 1980-81
NA - Not Available
Figures in the paranthesis refer to percentage of total cropped area.
....
N
(l)
Source I 1 & 2 (a,b,c & d) Department of -- Food and Agricultural Marketing Services
(DFAMS), Hand Book of Agricultural Statistics, March, 1979.
1 & 2 (0) FAO/DFAMS, Guidelines for Revision of Crops Statistics in Districts
Not Yet Cadastrally Surveyed, Early Warning Project, February, 1986.
4 (b & c) & 11 (b & c) DFAMS, A9ricultural Statistics of Nepal, July, 1972.
4 (d) DFAMS, Agricultural Statistics of Nepal, November, 1977.

4 (e) Ministry of Finance, Economic Survey Fiecal Year 1985-86, July, 1986.
5 (a), 7(b & c), 8(b,c & d), Mahesh Banskota and Ishwar Lohani, Nepalese
Agriculture A Comparative Evaluation, CEDA/Nepal, 1982.
5 (b,c & d) D.B. Amatya, Nepal Fiscal Issues - New Challenges, Sterling
Publishers, Delhi, 1986.
5 (e) Central Bureau of Statistics (CBS), National Sample Census of Agriculture
1981-82, July, 1985.
6 (b,c & d) Agricultural Input Corporation, Basic Statistics of Agricultural
Inputs in Nepal, 1983.
6 (e), 9(e) & 11 (d&e) DFAMS, Hand Book of Agricultural Statistics of Nepal,
September, 1986.
7 (d & e) Department of Police, From Unpublished Official Records
~
N
\0
8 (e) David Seddon, Nepal: A State of Poverty, Vikas Publishing House, Delhi, 1987.
9 (d) Co-operative Department, From Unpublished Official Records
10 (a,b, c, d & e) For Production Figures of Cereals (Paddy, Wheat, Maize, ~illet
& Barley) DFAMS, Agricultural Statistics of Nepal, 1972, 1977 & 1986. For
Population Figures of 1961-62 and 1981-82, CBS, Population Census of 1961 and
!2§l. For Population Figures of 1969-70 and 1974-75 CBS, Population Projection
of Nepal 1971-86, May 1974.
12 DFAMS, Agricultural Statistics of Nepal, 1972 & 1977 and Hand Book of
Agricultural Statistics of Nepal 1986.

130
6.6 Selection of Indicators of Agricultural
Development:
No single indicator can represent the phenomenon
of agricultural development as development itself
is multi-dimensional in nature and anyone
single indicator cannot capture it. So, in the present
study agricultural development 1s
defined in
terms of some of its dimensions based on twelve
indicators. The indicators selected to represent
agricultural development across districts in Nepal
are as follows,
1) Cultivated area per agricultural worker in
hectares,
2) Cropping intensity, *
3)
4)
InvesbDent on farm mechanisation and irrigation
per hectaIe of cropped area,
Inves~ent on farm mechanisation and irrigation
per agricultural worker,
5) Number of co-operatives per agricultural worker,
6) Consumption of chemical fertiliser per hectare of
cropped area,
7) Use of high yielding varieties of seeds (paddy,
whea t and maize) per hectare of cxopped area in
these crops,
* Cropping intensity has been defined as the ratio
of cropped area to cultivated area where cropped
area also includes land sown more than once.

131
8) Yield of paddy per hectare,
9) Yield of maize per hectare,
10) Yield of wheat per hectare,
11) Percentage of irrigated area to total arable
land, and
12) Gross value of agricultural output per agricultural
worker.
It should be mentioned here that the selection
of indicators is mainly based on the availability and
comparability of data at district level.
6.7 Levels of Agricultural Development:
In order to obtain the levels of agricultural
development of all the 75 districts of Nepal, factor
analysis technique is used and the results are presented
in Table 6.2 which gives the varimax rotated
factor loadings of 12 indicators. The factor loadings
in the table indicate the net correlation between
each factor and the observed variable. All the three
factors will be examined in some more detail below:
From the table it is clear that three factors
taken together explained about 69 per cent of the
overall variance in the data matrix. Of the set of
variables selected to represent the agricultural

Tab1e 6.21 Rotated Factor ~oad~ngs Qf AQr~cu1tura1 Var~.b~es
Variables
• Factor loadings of Factor Communality
1 2 3
1. Cult1vated area per agricultural worker
in hectares 0.825 -0.322 -0.020 0.786
2. Cropping intensity 0.074 0.117 0.889 0.809
3. Investment on farm mechanisation and
irrigation per hectare of cropped area 0.870 0.196 0.158 0.821
4. Investment on farm mechanisation and
irrigation per agricultural worker QI9~Q -0.025 0.224 0.916
f-A
s. Number of cooperatives per agricultural w
to.)
H",worker 0.747 0.223 -0.238 0.664
6. Consumption of chemical fertilisers per
hectare of cropped area -0.049 0.650 0.009 0.425
7. Use of high yielding varieties of seeds
(paddy, wheat and maize) per hectare of
cropped area in these crops 0.530 0.258 -0.418 0.523
8. Yield of paddy per hectare -0.187 0.824 0.090 0.725
contd ••••

Tab1e 6.2 (contd •• )
Variables
Factor loadings of Factor
1 2 3
Comnunality
9. Yield of maize per hectare 0.291 0.760 0.049 0.666
10. Yield of wheat per hectare 0.415 0.744 -0.069 0.731
11. Percentage of irrigated area to total
arable land .2..&558 0.105 0.385 0.470
12. Gross value of agricultural output per
agricultural worker 0.817 0.097 -0.073 0.683
Explained variance 4.645 2.314 1.262 8.221
...
\.oJ
\.oJ
Percentage of explained variance 38.707 19.285 10.516 68.509
Cumulative variance (%) 38.707 57.992 68.509

134
development of the district around 39 per cent of
the total variance is explained by first factor
alone. This factor is represented as indicated by
high individual factor loadings by 7 variables:
cultivated area per agricultural worker, investment
on farm mechanisation and irrigation per hectare of
cropped area and per agricultural worker, number of
co-operatives per agricul tural worker, use of high
yielding varieties of seeds, gross value of agricul
tuLal output, and percentage of irrigated area to
total cropped area. Looking into the loadings of
the variables with the factors more specifically,
Factor 1 may be interpreted to represent the
"modernization" aspect of agricultural development.
Out of 69 per cent of the total variance, an additional
19 per cent of the variance of the district's
agricul tural development comes from Factor 2. The
four const! tuent variables of this factor are:
consumption of chemical fertilizers, yield of paddy,
maize and wheat. The Factor 2 can be interpreted to
represent the soil condition or fertility aspect of
land. The Factor 3 has high loadings with only one
variable 1.e., cropping intensity and explains only

135
11 per cent of the total variance. Hence, we have
confined our fuxther analysis to only first
factors.
two
Using rotated factor loadings of the two
factors, factor scores of all the 75 districts are
obtained. The technique involved in obtaining the
factor scores from rotated factor loadings has already
been explained in detail in Chapter Two.
factor scores, thus obtained,are given in the
Appendix 6.1.
The
In the present study, first two factor scores
have been treated as
separate indices of agricultural
development,each representing different dimensions
of agricultural development. In order to
classify the districts by levels of agricultural development,
first the factor scores of all 75 districts
are ranked in descending order. The group of 25 districts
falling under first 25 ranks are treated as
agriculturally highly developed. Similarly, the
districts falling under 26 to 50 ranks and 51 to 75
ranks are treated under moderate and low category,
respectively. Districts, thus classified into three

136
categories based on first factor scores are illustrated
in Map. 6.1.
Similar Procedure has been
followed to classify the districts by levels of
agricultural development based on second factor
of
score. Thus, the two factors agricultural develop-
/'.
ment have been considered and districts are classified
into high, moderate and low categories. The
selection of cut off point is, however, arbitrary.
The regional distribution of districts separately
by each factor of agricultural development are
presented in Table 6.3.
It is evident from the table that there is a
significant regional variation in agricultural
development in Nepal.
Distribution of districts by
first factor reveals that, of the total 18 districts
of Terai region, 17 districts exhibited high level
of agricultural development.
Contrary to tbis,around
50 per cent of the districts in Mountain and Hill
regions recorded low level of agricultural developmente
Low and moderate levels, taken together,accounted
for more than 90 per cent of the districts in
Mountain and Hill regions.
In the case of Kathmandu
Valley and Inner Terai, all the districts of both the

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Levels
of agricultural
development
Fir at Factor
Moun- Hill Kath- Inner Tera! Total
tain mandu Tera!
Valley
Second Factor
MOUD- Hill Kath- Inner
tain mandu Terai
Valley
Terai
Total
High 1 3 1 3 17 25
2 6 3 3
11
25
Moderate 5 15 2 2 1 25
5 14 2
4
25
Low 10 15 25
9 13
3
25
Total 16 33 3 5 18 75
16 33 3 5
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7S
....
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139
regions exhibited high or moderate level of agricultural
development.
More or less similar patterns
of distribution emerge when Factor 2 is considered.
Thus,we may conclude that the importance
of natural regions is very much obvious in understanding
the agricultural development process and
hence, population growth patterns in Nepal.
6.8 Agricultural Development and Population Growth:
Some Emerging Patterns
Xn order to understand the relationship
between levels of agricultural development and population
gro~th,
and its components, the unweighted
average rates for all the demographic indicators falling
within each level of agricultural development
(High, Moderate and Low) have been worked out and are
presented in Table 6.4. These results present some
interesting patterns of population growth by levels of
agricultural development. Factor 1 which represents
the modernization aspect of agricultural development
clearly reveals a declining pattern in crude
death rate with higher levels of agricultural development.
The average crude death rate for low, moderate
and high categories are 20.65, 17.02 and 14.29,

140
respectively. Thus, it may be stated that higher the
level of agricultural development lower the crude
death rate.
Table 6.41 Levels of Agricultural Development and
Demographic Indicators: Some Emergino
Patterns
Levels of
Demographic Indicators
Agricultural
CDR ACBR RNI RNM RTI Density
Development
1st Factor
High 14.29 40.36 26.07 +14.37
Moderate 17.02 41.12 24.10 - 6.04
Low 20.65 42.34 21.69 - 9.22
2nd Factor
High 14.63 40.77 26.14 + 5.15
Moderate 17.10 42.26 25.16 - 3.22
Low 20.22 41.16 20.94 - 2.91
40.79 235.14
16.93 170.58
13.50 78.00
31.29 279.89
21.04 125.44
18.03 80.17
Note, CDR - Crude Death Rate
-
ACBR - Adjusted Crude Birth Rate
~ - Rate of Natural Increase
RNM - Rate of Net Migration
RTI - Rate of Total Increase.

141
This has clearly brought out the inverse relationship
between levels of agricultural development and crude
death rate as hypothesized earlier.
Adjusted Crude Birth Rate also shows a similar
declining pattern with higher levels of agricultural
development. The average adjusted crude birth rate
for low, moderate and high categories are 42.34, 41.12
and 40.36,respectively. Although the observed pattern
has shown an inverse relationship between levels of
agricultural development and adjusted crude birth
rate,the relationship does not appear to be strong
as the differences in adjusted crude birth rate between
the three categories are marginal.
It is interesting to note an increasing pattern
of rate of natural increase with higher levels of
agricul tural development. The pattern has emerged
due to the marked decline in crude death rate without
having a corresponding decline, of similar magnitude,
in crude bir th rate.
The average rate of net migration presented in
the table reveals that rate of net migration varies
with levels of agricultural development.
Districts

142
exhibiting high levels of agricultural development
inhave
recorded high ne~migration. In contrast, the
districts exhibiting lower levels of agricultural
development have recorded high net out-migration.
Thus, a pattern of high in-migration with higher
levels of agricultural development and vice versa
could be observed.
Conversely, higher out-migration
with lower levels of agricultural development and
vice versa could also be observed.
Thus,a positive
relationship between levels of agricultural development
and rate of net migration can be seen here.
The results presented in Table 6.4 also clearly
reveal an increasing pattern of rate of total
increase of population with higher levels of agricul
tural development.
The districts with high
levels of agricultural development have experienced
an average rate of total increase of 40.79 persons
per thousand per year which correspondingly decreased
to 16.93 and 13.50 in moderate and low categories,
respectively. Thus, it may be concluded that there
exists a direct relationship between levels of
agricultural development and RTI.
S~lar kind of
pattern has been observed between levels of

143
agricul tural development and density. This is
evident from our finding of highest density of 235
persons per sq.km. in high category to lowest
average density of 78 in low category, moderate
category with 170 falling in between.
More or
less similar relationship has emerged between agricultural
development and demographic indicators
when
Factor 2 is considered.
From the above findings,it may be stated that
the population growth of the districts in the high
category of agricultural development is high
mainly due to both high natural increase and high
net in-migration. On the contrary, the low population
growth of the districts in the low category
of agricultural development is mainly due to high
net out-migration.
But the variation in the population
growth rate across districts with respect to
the levels of agricultural development could be
attributed more to net in-migration and net outmigration
than to rate of natural increase as rate
of natural increase does not vary much between high
and low category of agricultural development.

144
In order to substantiate our findings and also
to ascertain the direction of relationship between
levels of agricultural development and demographic
variables,the zero-order correlation coefficients
between each factor of agricultural development with
each demographic indicator was obtained separately.
The results are presented in Table 6.5.
Table 6,5:
Zero-order Correlation Co-efficient&
Between Demographic Indicators and Scores
of Agricultural Development
Demographic Indicators
Correlation
Co-efficient
1. Crude Death Rate
2. Crude Birth Rate
3. Rate of Natural
Increase
4. Rate of Net Migration
5. Rate of Total Increase
6. Density (per sq.km)
Factor 1
-0.592**
-0.158
0,341**
0.500**
0.545**
0.254*
Factor 2
-0.334**
-0.120
0.113
0.168
0.249*
0.780**
• Significant at 5 per cent level
•• Significant at 1 per cent level

145
Our earlier findings of the positive association
between levels of agricultural development
(Factor 1) and rate of total increase in population,
rate of natural increase, rate of net migration
and density have been further confirmed by the
examination of zero-order correlation coefficients
of the demographic indicators with factor scores of
agricultural development.
All the correlation coefficients
are in the expected direction and are
statistically significant at 1 per cent level of
significance except density indicator which is again
significant at 5 per cent level of significance.
Similarly, the strong negative relationship between
levels of agricultural development and crude death
rate has also been confirmed and it is statistically
significant at I per cent level of significance.
Interest~ngly,
negative relationShip between levels
of agricultural development and crude birth rate has
been observed.
However, the relationship is not
statistically significant.
Similarly, our earlier findings of the positive
association between levels of agricultural development
(Factor 2) and rate of total increase, rate of

146
natural increase, rate of net migration and density
has also been confirmed by the examination of zeroorder
correlation coefficients (Table 6.5). All
the coefficients are in the expected direction.
Density is statistically significant at 1 per cent
level and rate of total increase at 5 per cent level
of significance. But the rate of natural increase
and rate of net migration are not statistically
significant even at 10 per cent level. The negative
relationship between levels of agricultural development
and crude death rate has also been confirmed
and it is significant at 1 per cent level. A negative
relationship with crude birth rate has been
•
observed. But the association appears to be weak as
it is not significant even at 10 per cent level. All
our findings, thus, supported the relationship which
we hypothesized earlier between agricultural development
and population growth and its components.

147
APPENDIX .b!
Districtwise Factor Scores and Ranks b;i Agricultural
Develo;ement
Factor Score/Rank
Sl. District
No. I Rank II Rank
1 2 3 4 5 6
1. Taplejung - 0.938 33 2.041 10
2. Panchathar - 2.777 52 -0.911 46
3. Illam - 0.243 28 1.018 14
4. Jhapa 5.751 13 -0.716 43
5. Terathum - 1.597 36 -1.852 63
6. Dhankuta 0.219 25 -0.514 37
7. Morang 5.453 15 0.416 23
8. Sunsari 10.821 2 2.095 9
9. Sankhuwasabha - 1.141 34 -0.437 34
10. So 1 okhambu - 4.430 69 -1.890 64
11. Ehojpur - 3.366 56 -1.557 59
12. Khotanj - 3.889 64 -2.499 69
13. Okhaldhunga - 2.372 45 -1.357 53
14. Udayapur 0.672 22 -0.273 31
15. saptari 5.317 16 -1.443 56
16. Siraha 7.144 9 1.109 12
17. Dolakha - 2.914 53 -0.553 38
18. R amec hap - 0.449 30 -2.044 67
19. Sindhuli 0.456 31 0.209 27
20. Dhanukha 5.702 14 0.341 24
21. Mabottari 3.078 20 -0.345 33
22. Sarlahl 7.937 5 0.434 22
23. Slndhupalchowk _ 2.482 46 0.210 26
24. RasuW8 - 0.439 29 -1.208 49
contd ••

148
Appendix 6-1 (contd •• )
1 2 3 4 5 6
25. Nuwakot - 2.368 44 1.110 26
26. Dhading - 2.979 54 0.054 29
27. Kavreplanchowk - 2.512 48 0.656 18
28. Bhaktapur 1.524 21 10.598 2
29. Kathmandu - 0.739 32 12.538 1
30. Lalitpur - 1.639 37 4.487 4
31. Makwanpur - 0.187 27 2.406 8
32. Chitwan 12.194 1 2.489 7
33. Rauthahat - 0.141 26 -0.759 44
34. Bara 8.385 4 3.843 5
35. Parsa 8.949 3 7.133 3
36. Gorkha - 3.523 58 -1.534 57
37. Lamjung - 2.057 42 -1.241 SO
38. Tanahu - 1.858 40 0.618 19
39. Syangja - 2.278 43 0.220 25
40. Kask1 0.239 23 -0.554 39
41. Manang - 1. 275~, 3S -3.132 74
42. Mustang 3.399 19 0.833 16
43. Myagdi - 3.347 55 -1.063 48
44. Parbat - 3.847 63 -0.492 36
45. Baglung - 2.448 47 0.753 17
46. Gulmi - 1.847 39 -0.923 47
47. Palpa - 2.609 49 - 1.368 55
48. Nawalparasi 6.681 10 2.574 6
49. Rupendehi 7.444 6 1.101 13
50. Kapilvastu 5.792 12 0.513 20
51. Arghakhanchi - 2.679 51 0.017 30
contd ••

149
Appendix 6·1 (contd •• )
1 2 3 4 5 6
52. pyuthan - 3.592 59 0.169 28
53. Rolpa - 4.884 73 - 1.819 62
54. Rukum - 4.618 71 - 2.505 70
55. Salyan - 2.652 50 - 0.596 41
56. Dang 7.153 8 0.967 15
57. Banke 4.874 17 - 1.289 51
58. Bardiya 4.406 18 0.485 21
59. Surkhet 0.221 24 0.645 42
60. Dallekh - 3.545 57 - 0.853 45
61. Jajarkot - 4.211 68 - 1.988 66
62. Dolpa - 4.763 72 - 0.558 40
63. Jwnla - 3.697 60 - 1.302 S2
64. Kal1Jcot - 5.745 75 - 2.667 73
65. Mugu - 4.130 67 - 1.626 60
66. Humla - 4.093 66 - 3.223 75
67. Bajura - 3.736 61 - 1.366 54
68. Bajhang - 4.009 65 - 1.950 65
69. Achham - 3.737 62 - 2.603 71
70. Doti - 1.994 41 - 0.473 35
71. Kallal! 7.199 7 - 1.542 58
72. Kanchanpur 6.112 11 - 0.274 32
73. Dadeldhura - 1.685 38 - 1.702 61
74. Baltadi - 4.967 74 - 2.377 68
75. Darchula - 4.442 70 - 2.608 72

CHAPTER VII
PATTERNS OF URBAN POPULATION GROWTH IN ltEPAL

-
CHAPTER VII
PATTERNS OF URBAN POPULATION GROWTH IN NEPAL
7.1 Introduction:
Urbanisation in Nepal is a recent phenomenon.
It is estimated that only 2.1 per cent of the total
population of Nepal was urban in 1941 which has
reached 6.3 per cent in 1981.
This level is relati
vely low when compared to the level of urbanization
in some of the other neighbouring Asian
countries. However, there has been a phenomenal
growth in the urban population by 107 per cent
during 1971-81. At this rate the urban population
in Nepal is expected to be doubled just in 9 years
(CBS, 19871 181).
The number of urban units in Nepal bas
increased over time. In 1981 their number bas
reached 23 and out of these 23 urban uni ts the
capital city Kathmandu is the only one urban area
having more than 100 thousand population.
The
trend rates of growth show a considerable variation
across towns over time.
Functions performed by
each of these urban un! ts to a larger extent have
lead to such variations.

-
151
The objective of this chapter is to examine
the patterns of urban population growth in Nepal.
In the next section, the conceptual framework has
been presented wherein emphasis has been placed on
understanding the process and mechanism of the
relationship between industrial development and
urban population growth. In the subsequent section,
the empirical findings from other related studies
are presented. This is followed by an analysis of
levels of urban growth and trend rates of growth
of towns.
Finally, the growth of towns is
examined in relation to their functions to discern
the patterns of urban population growth in the
country.
7.2 conceptual Framework:
It has been an established fact that industrial
development provides a sound and expanding
base for urban growth.
When industrial development
takes place. population grows in response to the
demand for work created by industrial development.
Establishment of large industries in turn create.
demand for ancillary and service industries with
addi tional potential for employment.
On the other

--
152
hand, the growing size of population resulting
from industrial development itself creates demand
for various types of services and infrastructure
which in turn provide an additional impetus to
industrialization. Furthermore, the growing
size
of population provides a sound base for the development
of other functions such as trade, commerce
and services. These activities provide opportunities
for investment and hence employment. The
greater opportunities for employment together with
the existence of higher wage in urban areas result
in the transfer of labour from rural to urban
areas. This urbanward migration streams may also
be regarded as the response of "pull- exercised by
the better economic opportunities available 1n
urban areas.
The growth and development of any urban place
depends very much on its functional composition
and set up.
The attraction of an industrial or
commercial town will not be of the same degree as
those of a service or a transport town.
Furthermore,
towns whose functions are diversified in
nature are likely to grow faster because they offer

153
economies of scale in many economic activities
which arise from better communication, better
transportation, more specialized division of
labour, and more diverse labour market as it
naturally attracts more investment and hence
employment. This coupled with more diversified
labour market attracts various types of people.
The impact of industrial development and
urbanization on fertility behaviour is important.
As a country develops from an agrarian society
into an industrial one, the attitudesof couples
towards children undergo significant changes.
Children will no longer remain as producers and
as providers of security in old age. Because there
will be an increase in the income of the parents
in proportion to the degree of indusuialization
enabling them to save which will, in turn, reduce
their dependence on children as a buffer against
adversity (Cho et al., 1977). Moreover, in urban
areas children tend to become increasingly a financial
buIden (Oberai and Singh, 1981). The other
intermediate variables through which fertility gets
affected are: increased work opportunity of varied
nature, educational opportunities and emergence

154
of nuclear family. Industrial development and
urbanization are also followed by behavioural
changes in social process and individual decision
making. Behavioural mechanism for the decline in
fertility are delayed marriage and increased
acceptance of family planning. The wider effect
of industrial development and urbanization through
various process variables will lead towards the
preference of small family size (Rosen and
Siumons, 1971).
Relating to mortality response, it has been
widely accepted that industrial development and
urbanization generally help to bring down mortality
level as industrial development and urban growth
are always followed by infrastructaral development
in the fields of nutrition, public health, sanitation,
drinking water and education. All these
infrastructural development will bring down mainly
the infant and child mortality which in turn will
reduce the overall mortality level.

155
7.3 Empirical Findings f;om Other Studies:
Bose (1982) observed a very high growth rate
in population of more than 75 per cent during
1971-81 in some 21 cities in India. Industrialization
in these cities has been attributed for such
a high growth rate in population. Rao and Samuel
(1985) in their study of Bangalore city and agglomeration
also found a consistent increase in growth
rate of uxban population since 1951-61.
The
authors attributed this to the industrial expansion
that had taken place during 60s and 70s in and
around Bangalore. Chaudhary (1982) in his study
on urbanization in Bangladesh which covered the
period from 1901 to 1974 observed a phenomenal
growth in urban Population and their regional variation.
This was attributed to rapid industrial
development during 1960s and disproportionate location
of industries in areas where urban centres
were concentrated. As a departure from the findings
of the above studiesl the study of Wu (1976)
which was based on data collected from a sample
survey of two places in Taiwan showed that there
was no relationship between industrialization and

156
urbanization. This was attributed to a very high
commuting ratio in both the areas where transportation
facilities were very good.
Suri (1971) in his comparative study of
rapidly growing and declining towns based on an
All India sample of 100 towns from each category
observed that the highest percentage increase in
population was in manufacturing towns (industrial
towns) and a declining growth in artisan towns
(household industry towns). A clear relationship
between functional type and growth rates has been
brought out by D'Souza (1976) in his study for
Punjab state of India for the period 1961-71. The
study found manufacturing towns registering highest
growth rate followed by trade, service and artisan
towns in that order. In a similar study carried
out by Raman and Ram Krishna (1970) for West Bengal
state for the period 1951-61 found manufacturing
towns registering highest growth and also highest
density.
In a study of urbanization in Pakistan
based on empirical data for the period 1951-71
Burki (1974) observed development of towns to be
closely dependent on the nature of their agricultural
hinterland.

157
Zarate (1967) used the Mexican census and
vi tal registration data to test the hypothesis
that urban fertility is inversely related to the
proportion of urban population in secondary
sector. The results showed a posi live association
between the two thus suggesting the nonvalidity
of the hypothesis. Liv' s (1976) study
of Taiwan. on the other hand. established a
negative relationship between urbanization and
fertili ty. In their attempt to establish some
linkages between industrialization, social class
and fertility in five communities of Brazil, Rosen
and Simmons (1971) observed the prevalence of
small family size in all social strata in the industrial
cities. Findings also supported their hypothesis
that industrialization influences fertility
through shifts in the social status of women.
Lebowitz (1973) in his study of the influence of
urbanization and industrialization on birth and
death rates in Japan and Mexico found that the
death rates were negatively related to urbanization
and industrialization in both the countries.
However. birth rate was found negatively related
only in Japan but not in Mexico. Jaworski (1985)

158
in his attempt to test the hypothesis that urbanization
mitigates the demographic explosion in the
Third World Countries observed the negative association
between higher level of urbanization and
fertility, births, deaths and child mortality. The
author also observed urbanization_resulting in a
tendency to reduced population growth and increased
life expectancy. However, these relationships were
practically non-existent in sub Saharan Africa.
Oberai and Singh (1981) after examining the data
generated from two household surveys,one from rural
and another from urban areas in Ludhiana district
in Indian Punjab concluded that there was a significant
difference in fertility patterns in rural
and urban areas. Urban areas were found to have
desired a small number of children than those in
rural areas.
What emerges from the empirical findings of
related literature cited above are that:
(i) there exists a positive association between
industrial development and growth of urban population,

159
(ii) industrial development and urbanization are
negatively related with fertility and mortality,
(iii) there is also a close association between
growth of towns and their functions.
In this
regard manufacturing towns have been observed growing
faster than any other types of towns.
At the outset it should be noted here that
industrial development in Nepal is very much in its
infancy.
According to 1981 population census less
than 1 per cent of the economically active population
is engaged in manufacturing sector. Its share
in GDP is merely 5 per cent in 1983/84.
The stru~
cture of industries still show a predominance of
traditional industries like food processing whose
share in total industrial composition accounts for
72 per cent in 1981. However, the number of manufacturing
establishments and persons engaged in these
establishments have shown a steady progress in
recent years. Disparities in industrial development
across regions are very much striking in
Nepal.
Industries are very much confined to a
few specific pockets of the country. Out of the
total of 4.903 industrial establishments in 1981/82,

-------------------------------------.
160
3,472 (71 per cent) are concentrated in the selected
pockets of eastern and central regions of the
country.
Because of the poor state of industrialization
and urbanization in Nepal any study which
tries to establish the relationship between industrial
development, urban growth and population
the
growth in Nepal may not come out wi~desired
results. This problem has been further complicated
by the non-avail abil i ty of data on industrial development
indicators by urban units. They are
available by districts only.
Furthermore, the
estimates of the components of urban population
growth i.e., births, deaths and migration for urban
units are not available.
In view of these problems
in the present chapter we have not attempted to
delineate the patterns of urban population growth
and its components by industrial development.
have rather confined our analysis to the examination
of the growth of towns in relation to their
functions.
We

'161
7.4 Levels and Trends of Urban Growth:
At the outset it should be noted here that
an indepth analysis of the growth of urban population
in Nepal requires some caution because of
definitional problems.
There has been a change
in the definition of urban unit from one census
to another and, hence, the data are not strictly
comparable.
In 1952/54 census urban areas were
defined purely on the basis of population size.
In 1961 census, however, in addition to minimum
population size some other criteria were also
added to qualify a locality into urban.
A locality
was defined as urban if it consists of 5,000
or more population with facilities such as h1ghschool,
college, government offices, other offices,
bazar, communication lines and manufacturing
(CBS, 1967). Afterwards a Town Panchayat Act was
passed in 1962 Which defined the urban area as
aan area having not less than 10,000 population-.
But this population size criterion was not
with
strictly followed as the locali tiesLless than
10,000 population were also declared as urban areas
in the 1971 census.
*
On the other hand, some areas
* These towns were: Illam (7,299), Bhadrapur
(7,499), Tansen (6,434) and Rajbiraj (7,832).

162
having a population of 10,000 or more were not
considered as urban. ** This clearly manifests
the arbitrariness involved in defining an urban
area in Nepal.
Subsequently, the population size
criterion was once again reduced from 10,000 in
1962 to 9,000 in 1976. Even if one strictly
follows the criteria laid down in the censuses,
frequent changes in town or urban,area boundaries
make the comparison a verydi£ficult task.
Levels and trends of urban growth in Nepal
have been presented in Table 7.1. The data
clearly reveal the changing levels of urban growth
over the years. There has been a steady rise in
the proportion of urban population. In 1952/54
only about 3 per cent of the population was urban
which has increased to 6.3 per cent by 1981.
The
increase in the proportion of urban population has
been very impressive after 1971.
During the decade
1971-81 urban population increased by 107 per cent.
This percentage increase should be considered quite
high compared to 37.4 per cent in the previous
decade.
** There were 12 such areas. To mention a few:
Shivaganj (17,891), Bhokraha (16,835), Damak
(13,993) and Hatiya (12,939).

.:.
163
Table 7.1: Percentage Distribution of Urban and
Rural Po~lation, and Intercensal
Annual Growth Rate~ 1952L54-1981
Intercensal
Annual Growth Rate
Census % % change
Year Urban Rural in Urban Rural Total
Urban
Population
(%)
1952/
54 2.9 97.1
1961 3.6 96.4 42.5 4.53 1.56 1.65
1971 4.0 96.0 37.4 3.22 2.03 2.07
1981 6.3 93.7 107.1 7.55 2.40 2.66
Sources Central Bureau of Statistics (CBS), Population
Censuses of 1952/54, 1961, 1971 and
1981.
The phenomenal growth of urban population
during 1971-81 may be explained partly by the
I
I
emergence of seven new towns in 1981, extension of
boundar ies of some existing towns through the
merger of some new areas, and partly by the development
effort in the country. The contribution of
new seven towns alone to the total urban
....

164
population in Nepal was around 17 per cent (the
total population of these new seven towns was
160,768).
The rapid! ty in the growth of urban population
is also reflected in the annual growth rate.
Annual growth rate of urban population has been
constantly increasing over the period except during
1961-71. The decline in annual growth rate during
1961-71 compared to 1952/54-61 could be attributed
to the declassification of 5 towns in 1971. A
reversal of this trend occurred during 1971-81 as
the annual growth rate of urban population touched
a peak of 7.55 per cent in comparison to its modest
growth rate of 3.22 per cent during 1961-71.
Urban
population in Nepal is growing at a faster rate
than that of rural population since 1952/54.
7.4.1 Population Growth by Size Class:
Two methods are available to estimate the
growth of urban population by size class which are
known as ·city" and ·class· method (Gibbs, 1966).
The former method which is also known as
·instantaneous· method compares the number of people

165
in a given size class of cities and towns at two
points in time ignoring shift of individual towns
from one class to another during the period. The
latter method considers particular towns (i.e.,
in this case, those in a given size class) at.the
start of the period and traces the subsequent
growth to the end of the period without concern
for the fact that some of them may have shifted to
another size class during the intervening time.
This method is also commonly known as ·continuous·
method. These two methods give different estimates
of urban growth. In the first method, growth rates
are affected by the movements of towns into and out
of the size classes and also by declassification
and emergence of new towns during the decade(s).
Hence, the second method is more appropriate for
comparing growth rates by size classes (Rao, 1988).
This method is used here to show the growth by
size class of towns.
I t can be seen from Table 7.2 that the
class V
towns have registered the highest growth
during 1952/54-61.
In the subsequent decade
1961-71, in spite of the decline in its growth rate

-,
Table 7.2. Growth Rate of Urban population by Size Classes, 1952/54 -1981
(Continuous Method)
Size Class
of Town
1952/54 - 61
No.of
towns
Annual
Growth
Rate(")
No.of
towns
1961-71
Arumal
Growth
Rate(%)
No.of
towns
1971-81
Annual
Growth
Rate (%)
I
100,000 +
1
1.59
1 2.17
1
4.47
II
III
50,000 - 99,999
20.000 - 49,999
2
1.14
3 2.10
1
5
3.02
5.69
.....
CI
CI
IV
10,000 - 19,999
2
3.04
3 3.40
5
8.19
V
5,000 - 9,999
5
7.55
4 6.88
4
5.24
-----------~-----------------------~--~--~----~--------------------------~-
All size class
towns 10 11 16
Source I
Central Bureau of Statistics (CBS). Population Censuses of 1952/S{.
1981, 1971 and 1981.
I
.. ~

167
compared to other size classes which experienced
the rise in their growth rates, it has maintained
the distinction of the highest growth size class
among all other size class of towns. .The decline
in the growth rate of class V towns during 1961-71
and further during 1971-81 is due to the declassification
of 4 towns in 1971. During the last
decade 1971-81 class IV towns registered the highest
annual growth rate of 8.19 per cent. This higher
growth rate to a certain extent i8 due to more
than three-fold increase in the population of
Birgunj town. No meaningful patterns of urban population
growth emerge by size class of towns specially
during 1971-81.
One of the important features of urban growth
in Nepal is its regional variation. The patterns of
urban structure in Nepal across regions show an
unequal distribution of urban population and this
pattern still persists in 1981. However, there is
a remarkable change in recent periods. Kathmandu
Valley which alone accounted for a major share of
82.58 per cent of the country's urban population in
1952/54 bas only 37.99 per cent in 1981. In

168
contrast to this l the share of Terai region has
increased appreciably from 17.42 per cent to 48.12
per cent during the same period. Hill region had
no urban population till 1952/54. In 19611 it had
a meagre share of 4.83 per cent Which increased to
13.79 per cent by 1981.
The continuous decline in the share of Kathmandu
Valley and a steady rise in the share of
Hill and Terai in the total urban population could
be partly attributed to the differential rates of
urban growth duzing 1961-71 and 1971-81. This
coupled with the emergence of 7 new towns (5 in
Tera! and 2 in Hill) in 1981 have further boosted
the urban growth rate of Hill and Terai. Hill
region registered an alarmingly high annual growth
rate of 11.35 per cent and 9.59 per cent l
respectivelYI
during 1961-71 and 1971-81. Terai region
also exhibited a high· growth of 4.62 per cent and
very high growth of 10.49 per cent during the same
period. Contrary to this, Kathmandu Valley recorded
only marginal growth of 1.35 per cent and slightly
higher growth rate of 3.76 per cent during the
same periods.

169
7.5 Growth of Towns:
The number of towns in Nepal has been growing
over time. The 1952/54 census recognised 10 town
panchayats as urban areas. In 1961, 6 more localities
were incorporated as town panchayats which
increased the total number of towns to 16. In the
subsequent census of 1971, 5 towns were declassified
and equal number of new localities were again
incorporated as town panchayats thus keeping the
total number of towns unchanged. In the latest
census of 1981 seven more localities were considered
as urban areas. Thus, in 1981 census 23 town panchayats
were considered as urban areas.
The population growth rates of towns presented
in Table 7.3 should be interpreted with caution as
1 t reflects all the components of urban population
growths (a) natural increase (balance of births over
deaths in urban places), (b) net migration (the
balance of total movements into urban places over
movements out of these areas), and (c) expansion of
urban areas through changes in urban boundary by
means of annexation of adjacent rural areas. Because
of the non-avail abi li ty of these data by urban

170
Table 7,3: Growth Rates of Towns, 1952/54 to 1981
Town
Illam
Bhadrapur
Popu- Annual Growth Rates (%)
lation
1981 1952/54- 1961-71 1971-81
61
9,773 2.92
9,761 2.64
Biratnagar
93,544 18.48*
2,43
7.29
Dharan
42,146
7,20
Rajbiraj
16,444
4,03
7,42
Janakpur
34,840
4,70
8,91
Lalitpur
79,875
1.54
2,13
3,02
Bhaktapur
48,472
0,59
1,60
1,89
Kathmandu
235,160
1,59
2.17
4.47
Hetauda
34,792
7,65
Birgunj
43,642
0,88
1,88
12,11**
Pokbara
46,642
13.37**
8,17
'l'ansen
13,125
2.25
7.13
Siddharthanagar
31,119
5,88
Butwal
22,583
5,66
Nepalgunj
34,015
4.75
3,97
3,69
*
The very high growth of Biratnagar is partly due
to the change in its boundary and partly due to
heavy influx of Nepalese refugee from Burma,
Assam (India) and Pakistan.
** The high growth rate in Pokhara and Birgunj is
due to the incorporation of more rural areas
into the town panchayat boundary.
Source: Central Bureau of Statistics (CBS) ,Population
Censuses of 1952/54, 1961, 1971 & 1981.

171
units i.e., towns, it is diffieul t to decompose the
growth of urban areas into each component.
However,
an attempt to understand the process of growth of
towns may be very much helpful in urban growth
patterns.
Among the 8 towns which registel:ed a continuous
growth over successive decades, Kathmandu,
capital city of Nepal, is one among them.
This is
the only prime city of Nepal which has more than
one lakh population. In spite of being the focal
point of socio-economic development, locus of political
and economic powers and centre for education
and administJ:ation, the growth rate of Kathmandu
city until 1970s was relatively slow.
The main
reason was that the city specially the inner city
had approached the saturation point in providing
housing and tbel:e was less and less space left every
year for additional housing.
However, the growth
rate has been much higher in the outer city and in
the fl:inge al:eas (Joshi, 1974). During 1971-81,
Kathmandu city picked up its momentwn in annual
gl:owth rate which stood at 4.47 per cent compal:ed
to 2.17 pel: cent during 1961-71.
The pl:obable l:eason
for high growth could be the merger of the outer

172
city in Kathmandu town where the growth rate has
been quite high.
The growth process of the other town i.e.,
Bhalt tapur which is in the close proximity of the
capital city Kathmandu is not very impressive
throughout the period. In all the three decades
its growth rates were lower than the national
growth average. The low growth rate during
1952/54-61 was partly due to the differences in
areal unit. A further relatively low growth rate
during 1961-71 could be its inability to compete
with Kathmandu. As a result of this, it is believed
that most of the people of this town have moved to
Kathmandu (Joshi, 1974: 246). This process is
believed to have continued during 1971-81 also. In
the case of another town Lali tpur which is in a
more closer proximity of the capital city Kathmandu,
the growth rates show a gradual increase.
Biratnagar and Pokhara experienced a fluctuating
growth rates. It should be noted here that
Biratnagar recorded the highest annual growth rate
of 18.48 per cent during 1952/54-61 and Pokhara

173
recorded a highest annual growth rate of ll.37
per cent during 1961-71.
In both the towns the
higher growth rate could be attributed to the
incorporation of rural areas into the urban areas
(Joshi, 1974; (New Era, 1981).In addition, the
higher growth rate of Biratnagar during 1952/54-61
could also be attributed to the heavy influx of
Nepalese refugees from Burma, Assam (India), and
Pakistan (Joshi, 1974).
In the case of Pokhara
it is believed that the construction of two
important highways linking Pokhara wi tb Kathmandu
and with Indian boarder in the 1970s could have
resul ted in the movement of people to Pokhar a
significantly (Banister and Thapa, 1981). Al though
the annual growth rate of both the towns have
fluctuated for some time, growth rates have
remained to a relatively higher level during
1971-81.
Biratnagar is the most important industrial
centre and second largest town of the country and
also a major commercial centre linked with well
connected transportation network.
In contrast,
Pokhara is an important tourist place. There has

174
also been expansion in administration and it has
emerged as a major administrative centre which
cou16 have contr ibu ted to the movement of people
to this town (New Era, 1981). Furthermore, both
the towns have emerged as the two maj or centres
for higher education after Kathmandu.
All these
could have resulted in the rapid growth of urban
population in these towns.
The very slow growth rate of Birgunj town
during 1952/54-61 was mainly due to the separation
of an area called Chhapkaiya from the town
panchayat area of Birgunj (Joshi, 1974). A sudden
revival during 1971-81 to the extent of 12.11 per
cent annual growth rate which is the highest among
all other towns during 1971-81 could be again due
to the incorporation of that area in B1rgunj town
panchayat. Apart from this, Birgunj has a sound
industrial and commercial base.
Birgunj has been
linked by road with all the maj or towns of the
coun try. It al so happens to be a maj or administrative
and education centre.

175
A fe\-l more towns are also experiencing very
high annual growth rates ranging from 5 per cent
to around 9 per cent during 1971-81. They are:
Dharan, Rajbiraj, Hetauda, Janakpur, Butwal,
Bhairahawa and Tansen.
One thing which is common
with all these towns except Tansen is that they
belong to plain (Terat) region of the country where
transportation network is better developed. Dharan,
Hetauda and Janakpur have developed as industrial
towns and have sound commercial base.
Siddharthanagar
and Butwal which are located at the confluence
of road routes have emerged and developed
into new commercial localities after the completion
of Siddhartha highway in 1968.
A study
rela ted to the Central Region (Siddharthanagar
and Butwal fall in this region) showed that a
relatively large proportion of present urban
centres developed as business centre only after
1968 when Siddhartha highway was completed(Blaikie
et.al., 1980).
Urban population has increased quite
.
rapidly in Tansen in the last decade mainly because
of expansion of municipal boundaries.

176
·In addition, Tansen has remained an important
urban centre for higher education since long time.
On the other hand, Nepalgunj has experienced almost
stagnant growth. Nepalgunj which lies in
western region remained isolated from rest of the
country for long time due to its poor transportation
network which could be attributed to the
stagnant growth.
It could thus be stated that the towns which
grew considerably were centres of industry and
commerce and were located at vantage points on the
road routes. Some of the towns grew because they
have developed as important educational and administrative
centres.
7.6 Functional Classification of Towns and Urban
Population Growth:
Here an attempt has been made to classify
the towns by their maj or functions and relate it
with the growth of urban population in Nepal.
The classification of male workers into 9
categories in 1981 census formed the basis of this
analysis. These categories are: (1) Agriculture,

177
(ii) Mining, (iii) Manufacturing, (iv) Electricity,
(v) Construction, (vi) Commerce and trade,
(vii) Transport, (viii) Finance and business,
and (ix) Personal and community services.
The nine categories are regrouped into four
major groups by combining (i) and (ii) and designating
it as agricultural town (A), (iii) and" (v) as
manufacturing towns (M), (vi) and (viii) as trade
and commerce towns (C) and (iv), (vii) and (~)
as service towns (s). This regrouping is done in
view of the very insignificant proportion of male
labour force employed in some activities. While
classifying these towns 1971 is treated as the
base. In 1971 there were only 16 towns. Thus only
16 towns which are found to be common between 1971
to 1981 have been consi~ed for the purpose of
this analysis.
7.6.1 Methods of Classificationl
In order to functionally classify the towns
a method developed by Wilkinson (1964) has been
followed.
The method is outlined briefly below.

178
Agricultur~activities
occupy a very important
place in the industrial classification of
economically active population in most of the urban
units of Nepal. In view of this agricultural
activities have been given a primary consideration
in functionally classifying the towns of Nepal.
In this method only male workers are considered
because male rather than the total labour force
was used in an attempt to reduce the effect of the
higher level of female labour force participation
in the unpaid family worker category. Further,
for international comparisons male rather than
total labour force data are more consistent in
definition and reporting (Wilkinson, 1964). For
the purpose of this study we have defined a town
as an agricul tural town if more than fifty per cent
of the male workers are engaged in.agriculture,
forestry, fishing and mining. The criterion of SO
per cent is arbitrary but it more or less conforms
to the corresponding overall proportions of urban
areas. For categorizing the towns not falling in
agriculture category an alternative approach based
on ratios showing relative commitment of the labour

179
fo~ce to each of the ~emaining th~ee catego~1es
was adopted. The ~atios a~e derived as follows:
Manufactu~ing
(M)
M I (c + S)
Trade and Commerce (C)
C I (M + S)
Services (5)
S / (M + C) .
Where (M), (e) and (5) refer to percentage of
urban males in manufacturing, trade and commerce,
and services,~espectively. Similar ratios a~e also
calculated for the total of 16 towns to obtain
the overall ratio.
These ratios for the total urban male
labour force were used as the basis for determining
functional category as follows, if in a category
the town ratio is higher than the corresponding
overall ratio then the town is classified as belonging
to that category. If a town falls in more than
one category then it is assigned to that category
which shows the largest percentage deviation with
respect to overall ratio (Raman and Ramkrishna, 1970) •

180
A town is considered for classification into one
or more of theae categories viz., manufacturing,
trade and commerce, and services only when that
town has not already been assigned to agriculture
category.
It should be noted here that if a town is
classified into any category other than ag,riculture
(A) then it does not necessarily Eean that
the percentage of workers in that category is
more than that in agriculture. For example,
preliminarily Dharan town was allocated to trade
and commerce category and services category, the
percentage of male workers being 21 per cent and
30.18 per cent. respectively. which are less than
the 37.16 per cent in agriculture category. This
can be expected since this method of classification
indicates emphasis relative to the total urban
structure in employment composition of individual
cities rather than specialization (Wilkinson. 1964).
The results of the preliminary and subsequent
allocations of towns emerging from the method are
summarised in Table 7.4.

181
Table 7!4:
Towns
Functional Classification of Towns and
Growth Rates During 1971-81
Functional Classification Annual
Growth
Pre1iminary Final Rates (%)
Allocation Allocation 1971-81
Illam Agricul ture Agriculture 2.92
Bhadrapur Services Services 2.64
Biratnaoar Manufacturing Manufacturing 7.29
Dharan Trade & Com- Trade & 7.20
mmerce,Services Commerce
Rajbiraj Services Services 7.42
Janakpur Manufacturing Manufacturing 8.91
Lalitpur Agriculture Agriculture 3.02
Bhaktapur Agr ieu! ture Agriculture 1.89
Kathmandu Agriculture Agriculture 4.47
Hetauda Agricul ture Agriculture 7.65
Birgunj Agr icul ture Agriculture 12.11
pokhara Agriculture Agriculture 8.17
Tan sen Agricul ture Agricul ture 7.13
Siddhartha- Trade & Trade "
nagar CORlllerce Cormterce 5.88
Butwal Trade " Trade &
Commerce CoD'lDerce 5.60
Nepalgunj Agricul ture Agriculture 3.69

182
Having classified the towns based on their
functions an attempt has been made to relate it
wi th the growth rate of urban population. Table
7.4 presents the functional classification of
towns and their annual growth rates dw:1ng 1971-81.
No meaningful patterns have emerged between functional
type and growth rate as the annual growth
rates of towns within each functional type varies
significantly. For example, agricultural towns
have experienced both highest and lowest annual
growth during 1971-81, Birgunj with highest annual
growth rate of 12.11 and Bhaktapur with lowest of
1.89 per cent. Similar is the case in service
towns. However, with regard to manufacturing and
commerce towns all the towns have uniformly experienced
higher annual growth.
Since the above findings do not give a clear
pattern an attempt has been made to understand the
patterns of urban growth by their functions by
pooling the towns falling in each category and
calculating the unweighted average of annual growth
rates for each category. The results which are
presented in Table 7.5 present some interesting

183
patterns of urban population growth by functional
groups of towns.
Table 7,51 Rate of Urban Population Growth and
Sex ratio by Functional Groups of Towns
Functional
Group
No.of
Towns
Annual Growth
Rate (%)
1971-81
Manufacturing 2 8.10
Trade &
Commerce 3 6.24
Agriculture 9 5.70
Services 2 5.03
Sex Ratio·
1190
1099
1161
1226
• Males per thousand females.
A clear pattern could be observed between
functional groups and growth rates of urban population
from Table 7.5. As expected, manufactur ing
towns recorded the highest average annual ;rowth
rate of 8,10 per cent during 1971-81 followed by
trade and commerce with 6.24 per cent, agriculture
with 5.70 per cent and services with 5.03 per cent,
in that order. These findings lead us to conclude
that manufacturing towns grow much faster than any
other types of towns.
Sex ratio to a certain

184
extent confirms our findings as the sex ratio
measured as males per 1000 of females is quite
large in service and manufacturing towns. The
reason for higher sex ratio in service and manufacturing
towns could be due to the sex selective
male migration for seeking jobs, and higher education.
However, the extent of variation among
categories is not so significant. The above findings
should be interpreted with caution because of
the lesser number of towns falling in some of the
functional gra.ps.
In the above discussion we attempted to
classify the towns into specific categories and then
relate them with urban population growth.
But what
is generally observed is that towns are basically
diversified in nature 80 far as their functions are
concerned. Taking into account the diversified
nature of their functions here an attempt has been
made to classify the towns based on their functions
into three major categories viz., monofunctional,
bifunctional and multifunctional. To achieve this
objective unlike four categorization of towns which
was done earlier we have made it into five categories

185
making transport as a separate category and keeping
other as it was.
Having mentioned this we
have followed the following criteria for classifying
the towns functionally.
1. If the percentage of male workers under any
of the five activities is equal to or exceeds 40
per cent,such a town is regarded as monofunctional.
2. If the percentage of male workers is less
than 40 per cent in each activity
ana if the percentage
against any two activities adds upto 60
or more then such a town has been classified as
bifunctional, and
3. I f the total percentage of the male worker s
engaged in the two major activities does not corne
upto 60 per cent, then the third predominant occupation
is taken into consideration and the town is
categorized as multifunctional.
The distribution of towns that have emerged
after applying the above criteria and their growth
rate of population is presented in Table 7.6.

186
Table 7,6: Functional Categories of Towns and
Growth Rates, 1971-81
Functional
Categories
No.of
Towns
Annual Growth
Rate (%.)
1.
2.
3.
Monofunctional
Primary
Activities
Bifunctional
Primary Activities
cum Se'rvices
Multifunctional
Primary cum
Commerce cum
Services
11
4
1
4.84
7.38
7.29
From the table it is apparent that bifunctional
and multifunctional towns are growtng much
faster than monofunctional towns.
A slight
departure from the general rule is higher rate of
growth of urban population in bifunctional compared
to multifunctional towns.
It could be due to onll

187
one town falling in the multifunctional category.
However, the difference between the two is very
negligible. Thus we can conclude that bifunctional
and multifunctional towns have better prospects
of growth than monofunctional towns.

CHAPTER VIII
LEVELS OF SOCIO-ECONOMIC DEVELOPMENT AND
PATTERNS OF POPULATION GROWTH

CHAPTER VI I I
LEVELS OF SOCIO-ECONOHIC DEVELOPZW:ENT AND PATTERNS
OF POPULATION GRO\"rrH
8.1 Introduction:
It has generally been accepted that the relationship
between socio-economic development and
population growth can go in either direction.
Population growth once generated has significant
influence on the socio-economic development. Similarly,
the changes in socio-economic development
have significant influence on the demographic behaviour.
Thus, it hardly needs to be emphasised
that they are mutually interdependent and interacting.
It is also an accepted fact that there is
considerable variability in the socio-economic
development across countries of the world. As a
resul t of this, the sequence and extent of decline
in mortality and fertility and the time taken to
complete the transition have varied from country
to country. Similar to inter country disparities,
intra-country disparities in the levels of development
are also quite common in majority of the

189
countries of the world.
Nepal is no exception to
this rule. There are wide range of variations in
population growth rates as well as levels of
socio-economic development across different regions
and districts of the country.
Disparities in the
levels of development are expected because of the
variations in topography, endowment of natural
resources, and allocation of resources by government
and other agencies. Disparities in the levels
of development have a significant bearing on the
demographic behaviour as it has been widely
accepted that the levels of socio-economic development
do influence population growth via its components
i.e., fertility, mortality and migration.
It is in this context that an attempt has been made
in this chapter to delineate the patterns of
population growth by levels of socio-economic
development in Nepal.
In Section 8.2, the conceptual framework
bas been presented wherein emphasis has been given
on understanding the processes and mechanisms
involved in the relationship between socio-economic
development and population growth and its components.

190
Based on conceptual framework, certain relationships
have been hypothesized between socioeconomic
development and population growth and
its components in Section 8.3. This is followed
by a review of relevant literature pertaining to
the relationship between the two in Section 8.4.
In Sections 8.5 and 8.6 an overview of socioeconomic
development in Nepal and the indicators
selected to obtain the index of socio-economic
development have been mentioned. Finally, in
SectiOD 8.7, we have delineated the patterns of
population growth and its components by levels of
socio-economic development.
8.2 Conceptual Framework:
Fertility:
Socio-economic development is accompanied by
several concom1ttant changes: (a) changes in household
location due to migration, (b) changes in occupation,
(c) Changes in the education that people receive and
in educational requirements resulting from changing
occupational opportunities, and (d) changes in income.
Leibenstein referred to these changes as -basic
developmental changes- which affect the cost-benefit

191
elements of children and thus fertility. The
economic value of children as source of labour,
income, and old age security etc., decline in
importance as a consequence of the impact of the
basic developmental changes and hence the desire
for children will be reduced.
Similarly, relative
cost of children e.g., nurture cost, education
cost, opportunity cost of mother, felt
mobility cost to the parents etc., are likely to
increase and this will act as a deterent for
further desire for children (Leibenstein, 1979).
The effect of education on fertility is
widely recognized.
The increase in educational
level resulting from an increase in economic level
has several consequences inimical to high fertility.
As a consequence of high level of education,
there will be more positive attitudes towards
birth control and also better access to various
means of birth control, higher labour force participation,
rise in age at marriage, higher
parental aspirations for themselves and their
children, and higher status of women.
All these

192
will lead to reduction in fertility (Heer, 1966~
Mc Greevery and Birdsall, 1974; Cassen,1976;
Morawetz, 1978).
Socio-economic development increases the
work participation rate of women.
There are
several ways in which work and fertility may be
related. Firstly, there will be a conflict between
work and child bearing of women Which will
reduce the desired family size. However, the conflict
between work and child bearing depends upon
the alternative means of child care. Secondly,
work may enhance the status of women in their
families which may increase their ability to limit
fertility successfully.
Finally, work may
increase women's exposure to various birth control
measures. However, what is more important is the
nature and place of work (Cassen, 19761 Oberai
and Singh, 1981).
Furthermore, as a consequence
of socia-economic development the traditional
system of extended family undergoes change
to
nuclear family. Because of the extended family
being replaced by nuclear family fertility behaviour
is affected largely due to the requirement of more
parental time for rearing of children.

193
Another change that may frequently accompany
economic development and possibly inimical
to high fertility is an increased rate of social
and economic mobility. It can be assumed that a
high level of social mobility is associated with
the inclination towards modern amenities which
may lead to an increased use of conspicuous consumption
as a means of demonstrating high status.
An increase in conspicuous consumption in turn
would necessitate a diversion of funds from other
types of consumption including the consumption
expenditure of raising a large family (Heer, 1966).
Economic development is also accompanied
by better opportunity in the distant place which
requires mobility. But the willingness to move
from one place to another will be largely constrained
by the perceived mobility cost to the
parents. Parents or potential parents may be less
mobile if they have more number of children and
thus are depTived of better opportunity. However,
this view does not seem to have been substantiated
empirically (Leibenstein, 1979). Initially,
mobility will be male selective among the married

194
couple due to the uncertainties in the new place.
So, this will separate husbands from wives
during the crucial life cycle phase when couples
are fertile and may have the effect of lowering
completed family size (Oberai and Singh, 1981).
It can also be supposed that a usual consequence
of increase in socio-economic development
is a decline in mortality level especially infant
and child mortality.
Some of the fertility
reducing effects of infant and child mortality
rate are of a biological nature. The decline in
infant and child mortality rate will bring down
the fertility through various effects viz.,
"physiological effect" (lactation effect),Ureplacement
effect" and "insurance effect" (Preston,
1975; Cassen, 1976; Birdsall, 1977).
It is also widely accepted that fertility
decline depends more strongly on the alteration
of long established beliefs, customs and institutions.
The process of economic change weakens
the force of traditional customs and beliefs and
thus helps to reduce fertility (Coale and Hoover,
1955) •

195
Socio-economic development may some times
be favourable to higher fertility. One change
that may frequently accompany economic development
is an increase in level of nutrition. The higher
nutritional level of women may increase fecundity
and hence fertility. Similarly, an improvement
in adult mortality will lengthen the duration of
the fertile period of marital union and thus may
increase fertility. The rise in economic level
may enhance the ability of parents to bear the
cost of rearing additional children which may lead
to higher fertility. Fertility rising impact of
socio-economic development, however, is less
pronounced than the fertility reducing impact.
fwlortality:
The mortality effect of socio-economic development
is more clear. Looking into the comparative
and historical mortality patterns, Goldscheider
has observed that "First and most important,
no evidence, historically or comparatively
appears to invalidate the general positive relation
between socio-economic development and mortality
reduction" (Goldscheider, 1971: 122).

196
It has been widely accepted that mortality
level is associated with nutritional level,hygiene,
sanitation, health care system, general condition
of living and prevalence of communicable and
epidemic diseasea.Socio-economic development has
a direct effect on these factors and thus helps to
reduce mortality level. Socio-economic development
which implies increase in general living
standard and improvement in the nutritional level
through an improvement in the quantity and quality
of food helps to reduce mortality level. Similarly,
socio-economic development also implies
changes in the amount and quality of health care, .
applications of public health standards in sanitation,
sewerage and water supply, general control
of the epidemic diseases and improvements in distributing
these benefits throughout the society. All
these amenities directly increase the health condition
of the people and thus reduce the mortality
level. So, it is through better nutritional level,
health condition, medical facilities and control
over epidemics that socio-economic development
reduces mortality level.

197
Migration:
How is migration related to socio-economic
development? Ravenstein's -Laws of Migration",
Stouffer's model of -Intervening Opportunities",
and Lee's "Push-Pull Hypothesis·, all are contributions
in this direction. The relationship of
migration to economic condition is generally such
as to bring about migratory increase of population
in areas of relatively more opportunity and migratory
losses in areas of scanty opportunity (UN,
1973).
Regional disparities in development has been
the growing concern among researchers as well as
policy makers.
Unequal distribution of natural
reSOUIces lead to regional inequalities in development.
As the socio-economic development takes place,
naturally the better endowed places develop faster
and attract more investment than the less endowed.
This results in regional disparities in employment
opportunities, education and social infrastructure
facilities. This, in turn, acts as a pull factor
to the people living in a comparatively backward
or less developed regions. Thus, there will be a

198
redistribution of population from less developed
regions to highly developed or developed regions
where the concentration of development efforts
(economic activities, social services and investment)
is more. Thus, it is internal migration
that accounts for most of the population redistri_
bution, indispensable as an accompaniment to the
economic growth.
8.3 Hypothesized Relationships:
On the basis of conceptual framework presented
above, following relationships could be
hypothesized between socio-~conomic
development
and population growth and its components.
1. The fertility reducing effects of socioeconomic
development operates through several
intermediate variables such as: (i) decline in
traditional values; (ii) break-up of the extended
family system; (iii) urbanization; (iv) improved
education and improved socio-economic status of
women; (v) increase in the cost of child rearing;
(vi) reduction in the reliance on children for
old age security; (vii) decline in the preference

199
for male children; (viii) decline in the overall
mortality rate, especially the infant mortality
rate; (ix) increased economic and social mobility
of parents; and (x) introduction of and improvements
in the birth control measures. The changes
in these intermediate variables, however, depend
largely upon the levels of development of the
countries concerned.
In the initial stage of development
the changes in these intermediate variables
may not be so large to bring down the fertility
immediately. The relationship between socioeconomic
development and fertility thus appears
to be rather weak in the initial stagesof socioeconomic
development.
2. Socio-economic development will lead to the
fulfilment of some of the basic needs of the
common people like food and nutrition, public
health and sanitation, safe drinking water, housing
and education.
It will thus improve the standards
of living of the people.
Fulfilment of the basic
needs of the people and improvement in standards
of living coupled with the advancement in medical
technology will bring down mortality level. Thus,

200
an inverse relationship between socio-economic
development and mortality has been commonly
observed.
3. Natural increase in population is affected
more by mortality than fertility because socioeconomic
development has an immediate impact on
mortality whereas its impact on fertility involves
a time lag. ~~reover,
the relationship of socioeconomic
development with fertility is expected
to be weak at the initial stages of development.
Hence, a positive association between socioeconomic
development and natural increase in population
could be postulated.
4. Socio-economic development not only leads to
an increase in demand for labou~ but also motivates
people to move to relatively more developed areas.
Conversely, it also results in the reduction in
out-migration of people from the areas. Thus,
reduction in out-migration and increase in the inflow
of migrants, including temporary and seasonal,
will tend to add to the growth of population in
more developed areas. Generally, it has been
observed that more developed areas tend to grow at

201
a more faster pace because of migration.
A positive
relationship between socio-economic development
and net in-migration can thus be postulated.
5. Fertility behaviour in the early stages of
development appears to be uncertain. However, mortality
tends to be inversely related with socioeconomic
development, thus resulting in a higher
natural increase with socio-economic development.
This coupled with higher in-migration would
increase the rate of growth of population in the
areas undergoing the process of socio-economic
transformation. A positive relationship could
thus be hypothesized between socio-economic development
and population growth.
8.4 Empirical Findings from Related Literature:
Here an attempt has been made to review the
major studies in the field of socio-economic
development as ti1ey relate to population growth.
While reviewing the related studies, the population
growth and its components, fertility,
mortality and migration are discussed separately.

202
A large number of studies have been carried out
both in developed and less developed countries
to investigate tl1e effect of socio-economic development
on fertility. Here, findings of some of
the studies which focus on mainly less developed
countries have been presented. It, however, does
not exhaust the voluminous literature available
on the subject.
Socio-Economic Development and Fertility:
In a study conducted for a sample of 35
nations, both developed and underdeveloped,
Weintraub (1962) found that crude birth rate was
positively related to per capita income, infant
mortality rate and proportion of farm population.
Heer and Turner (1965) 1n their study carried out
for 318 local areas in 18 Latin American nations
observed an inverse relationship between level of
economic development and fertility. Heer (1966)
in his theory of the relationship between economic
development and fertility postulated that the
direct and indirect effects of economic development,
taken together, cause fertility to decline

203
with an increase in economic development. He,
however, in his study of 41 developing and developed
countries observed the inadequacy of data
either to prove or refute his theory.
Janowitz (1971) in her attempt to investigate
the impact of socio-economic development on
changing levels of fertility of 57 countries of
the world for 1960 found that the fertility
varied cross sectionally with region as well as
with the level of development.
Ekanem (1972) in
his study based on 32 developing countries found
that the crude birth rate was negatively associated
with per capita income and per cent urban
and positively associated with per cent illiterate,
labour force in agriculture and infant
mortality rate. Janowitz (1973) in her another
study of four groups of countries found that there
was no relationship between fertility changes and
socio-economic changes.
Thus, she refutes the
modernization theory of the decline in fertility
and suggested for the formulation of models to
explore more complex relation between fertility
and socio-economic development.

204
Farooq and Tuncer (1974) while investigating
long term relationship between fertility
and various developmental variables at the province
level in Turkey covering the period
1935-1965 found that the proportion married and
literacy had an independent impact on fertility.
These two variables combined accounted for more
than 70 per cent of the regional variation in
crude birth rate. In an attempt to examine the
decline in birth rate in Kerala State of India,
Krishnan (1975) found that education, lower
mortality and longer expectation of life reflecting
the state of health were significant factors.
Oechsli and Kirk (1975) in their study of 25
Latin American countries observed that there was
a strong association between modernization and
birth rate. More specifically, they found a
demographic transition pattern in which a fall in
birth rate follows modernization and development.
Cho and others (1977) conducted a ctoss
sectional study of both micro as well as macro
determinants of fertility decline in South Korea.
In the macro analysis, they found that the increase
in income, in education, and in age at marriage

205
exert strongest influence in the fertility decline
of the nation as a whole. Similarly, the
micro study observed that there is a negative
relationship between economic development and
utility of children and positive association
between economic development and cost of rearing
children. Thus, they concluded that economic
development and modernization stimulate the small
family norm.
Morawetz (1978) in his cross country
study of 47 countries observed that basic needsoriented
policies may indeed bring about an
eventual reduction in fertility rates as well as
mortality rates.
A strong statistical association between
improvement in economic conditions and decline in
the CBR for Srilanka and Korea was found in a
study carried out by Srinivasan (1979) which
covered the period between 1958 and 1973.
However,
in the case of India the relationship was not so
strong and often the direction was not clear.
Using the 1979 Rural Fertility Survey carried out
in Egypt, Kelley and others (1982) found that the
desired number of children declined with socioeconomic
development.
They also found the

206
increasing use of contraceptive method with socioeconomic
development. Similarly, ~cNicoll and
Singarimbun (1982) in their attempt to find out
the proximate and background determinants of
fertility decline in Indonesia found increased
contraceptive use as a proximate determinant and
the rise in the socio-economic development of the
country as the background variable.
Pathak and Murthy (1982) using the 1975
data of 13 countries of Asia tried to ascertain
the effect of socio-economic variables on fertility.
They found that literacy, urbanization,GlW
per capita and economically active female population
were some of the important background variables
linked with fertility decline. They also
found that infant mortality rates and family planning
are the most proximate variables linked with
fertility decline.
Gubhaju's study (1983) based on Nepal Fertility
Survey data of 1976 found the fertility differential
in Nepal by socio-economic variables.
Of all the variables examined, the study found

207
marital duration having greatest impact on fertility.
The study also found that education of
husband rather than wives had both indirect
effect through age at marriage and direct effect.
Pathak and Hurthy (1985) -in another study
of 12 states of India for the year 1971 and 1981
found that there was a significant negative association
bet\'leen all the selected socio-economic
variables and CBR except lim.
Socio-Economic Development and Hortality:
Stockwell and Hutchinson (1975) in their
cross country study of 70 countries of the world
found that mortality was highly correlated in a
negative direction with soc1~economic
development.
Using the 1976 Nepal Fertility Survey data
Thapa and Retherford (1982) observed a differential
infant mortality rate across the regions of Nepal.
The study also observed the higher infant morta-
Ii ty rate in countryside than in the town.
The
study further observed education of fathers having
significant impact on infant mortality rate.

208
Yang and Pendleton (1980) in their study of
124 countries, of which 94 were LDCs, found a
very strong set of direct and indirect relation
between indicators of economic development and
mortality. The empirical test of the model demonstrated
that lower mortality in LDCs was dependent
on socio-economic factor and health services and
thus refuted the hypothesis that mortality
decline in LOes is not associated with socioeconomic
development but because of the diffusion
of health and medical techniques.
Similarly, in a time series as well as cross
section study of India, Das and Dey (1983) found
that social development, economic development and
public health programme factorswere very important
in explaining variation in mortality rate. 98 per
cent of the observed variation in levels of
mortality was explained by urbanization, per capita
income, per capita availability of foodgrains and
dispensary population ratio. Pathak and Murthy
(1985) in their study of 12 states of India found
that there was a negative association between all
the selected socio-economic variables and crude

209
death rate. Infant mortality rate as a socioeconomic
variable was found to be positively
associated with crude death rate.
With the aim of establishing the association
between socio-economic development and mortality.
Farag (1982) in his study of Syrian Governorates
found that the region which stands high
on the scale of socio-economic development showed
the lowest level of mortality and, conversely,
region which occupies the lowest scale of socioeconomic
development showed the highest mortality.
The correlation coefficient between mortality
and socio-economic development also supported the
above findings.
Socia-Economic Development and Migration:
Mahto (1985) in his district level analysiS
of three states of Eastern India, namely, Orissa,
Bihar and West Bengal during 1971-81 found close
positive association between level of economic
development and spatial patterns of male migrants.
Between 38.5 and 46.7 per cent of the variation in
the percentage of male migration in 1971 was

210
explained by levels of economic development.
The study also found a strong positive and significant
association between the temporal change
in economic development and temporal change in
the percentage of male migrants. The study further
revealed that the variation or change in
the levels of economic development was able to
explain less than 50 per cent of the variation
or change in the share of male migration, but
could not explain female migration or total
migration at all which the author attributed to
deficiency of data.
Similarly, Gumber (1983) in his cross
sectional study of the districts of Gujarat state
during 1970s
revealed a strong association between
levels of development and migration. Relatively
better developed districts attracted more
migrants from other districts than from within
the district. The study also observed differing
rates of migration at different levels of development
varying from net out-migration in less developed
districts to net in-migration in developed
districts.

211
Hussein's (1987) study of Egyptean Governorates
revealed that net migration was more strongly
related to socio-economic conditions at the destination
than at the origin. The study also found
more developed Governorates working as major
attracting areas. More developed governorates
attracted about 87 per cent of the total internal
migration in Egypt.
Furthermore, 89 per cent of
the out-migration from less developed Governorates
were found to have gone to more developed areas.
Socio-Economic Development and population Growth:
Kulkarni (1973) in her attempt to examine
the patterns of population growth in 315 districts
of India during 1961-71 as related to economic
regionalization observed that at a higher level
of development, a larger percentage of districts
was showing higher rates of population growth.
This direct positive relationship was further confirmed
when the average population growth rate for
each level was calculated. Similar finding was
obtained by Rastogi (1974) in uttar Pradesh.
His
findings indicated a positive association between
economic development and population growth and

212
this was mostly explained by high degree of inmigration
in developed districts in comparison
to less developed districts. This study also
found a positive association between levels of
development and in-migration rate. Das (1980)
identified four development factors to be related
with population growth in India. They were:
-industrial development·, ·social development·,
·agricultural development" and IIdevelopment constraints·.
All the vambles,
taken together,
explained 95.6 per cent of the total variance in
population growth rate.
Similarly, Stockwell and Laidlaw (1980)
carried out a study of 31 LOes
to measure the
association between economic development and
population growth rate. The rate of economic
development was defined as an increase in real per
capita GNP.
They found negative association between
rate of economic development and population
growth rate during 19705.
However, the relationship
was not statistically significant. ~~re
interestingly, the study also found the steady
decline in the magnitude of negative association

213
(co~~elation coefficient being -0.71 and -0.37
du~ing 1950s and 1960s, ~espectively). Bhattacha~jee
(1982) obtained simila~ findings fo~ five
states of India. His findings indicated a positive
association between socio-economic development and
population g~owth. Howeve~, no clear cut pattern
was observed between socio-economic development
and net migration ~ate.
A study of Malgarkar and Panandiker (1982)
found socio-economic development -
explaining about
75 per cent of the variation in crude birth rate and
crude death rate. They, thus, concluded that there is
an effective relationship between socio-economic
development and demographic trend. D'Souza's (1983)
findings for Haryana and Punjab states of Indi.,was
a departure from the findings of the above studies.
He did not find any clear cut relationship between
socio-economic development and population growth.
Tenuous nature of the ~ela tionship between economic
development and population growth has been observed
as the villages which were simila~ in population
growth ~ates we~e dissim1la~ in thei~ levelsof development.
S1vamurthy and Ahamad (1984) found a weak

214
negative association between index of economic
development and natural increase for Bangladesh.
However, the study observed a significant negative
association between index of economic development
and fertility. Significant positive association
was also observed be~Teen index of economic development
and net in-migration.
8.5 Socio-Economic Development in Nepal: ~
Overview:
For a century Nepal was under the rule of
Ranas during which period hardly any attention was
paid towards the systematic development of the
country. Only after the over-throw of Rana
regime in 1951 planned efforts
for Bocioeconomic
developm~nt of the country were initiated
with the adoption of First Five Year Plan. So far
Nepal has completed six periodic plans. During
this period if one loOks at the economic front of
the country the achievements are not very impressive.
Based on the esperience of first four
plans it has been observed that "planning has
failed to stimulate significant growth in
production per head" (Blaikie, 1983: 58).

215
Real GDP grew during the last 15 years
(1970-85) at an annual rate of 2.80 per cent.
Population during the same period increased at
an annual rate of 2.66 per cent. This shows a
very negligible rise in real per ca~ita GDP
(CBS, 1987a).
Hence, it may be concluded that
the economy during the last 15 years remained
almost stagnant. The structure of the economy
has also not witnessed any significant shifts
during last two decades. When compared to
1964/65 the share of agriculture sector in GDP
has come down from 65.23 per cent to 58.59 per
cent in 1979/80 but it has remained almost stagnant
afterwards. Similarly, the share of manufacturing
sector which was 4.14 per cent in
1974/75 stood slightly higher at 4.57 per cent
in 1984/95 thus showing no appreciable change
during the period. Despite three decades of
planned development neither real GDP nor the
structure of the economy has experienced any
marked improvement.

216
However, considerable changes have taken
place over the last 20 years in different sectors
of the economy. Analysing the changes that have
taken place during 1954-1974, ARTEP observed:
"Nepal has, nonetheless seen considerable changes
over the last 20 years. Levels of medical care
and education have increased immesurably. Communications
between major towns have improved out
of all recognition and the quality and efficiency
of the government administration is much improved"
(ARTEPI 1978, 1-2). The data indicating the
changes which the country witnessed during last
two decades have been presented in Table 8.1.
The urban population in Nepal which was
limited to only 3.6 per cent in 1961 has increased
to 6.3 per cent in 1981.
Similarly, the percentage
of workers engaged in secondary and tertiary
sector has also increased from 5.4 per cent to
7.0 per cent during the same period. However,
these changes appear to be modest.

217
Table 8.1: Selected Indicators of Socio-Economic
Development in Nepal
Indicators
Year
-----------------D----------
1961/62 a 1971/72 1981/82 c
1. Percentage of
urban population 3.60 4.00 6.30
2. Percentage of
workers in
secondary and
tertiary sectors 5.42 5.63 7.00
3. No.of registered
manufacturing 1,257 2,434 4,903
establishments (65/66) (72/73)
4. No.of persons
employed in registered
manufacturing
14,397 47,638 81, 050
establishments (65/66) (72/73)
5. Effective
Literacy Rate (ex.) 8.9 14.3 23.5
6. Percentage of
school going
children in the
age group of
6-15 years· 8.43 18.68 46.50
7. No.of, schools
(General) 4,157 8,369 14,332
8. No.of hospitals 35 51 73
9. No.of hospital
beds 797 1,983 2,586
contd •••

218
Table 8.1 (contd •• )
Indicators
Years
1961/62 a 1971/72 b 1981/82 c
10. No.of health
posts NA 193 744
11. No.of doctors 128 342 678
(76/77) (82/83)
12. No.of post offices 409 751 1,526
(73/74)
13. Surfaced road
length (km) 907 2,504 5,270
14. Electricity
(installed capa- 7.070 37,996 154,244
city) (KW) (83/84)
15. Electrification:
Population 100 NA 1,100
Benefitted('OOO) (85/86)
16. Drinking water
facility 20.299 51,935 173,402
(in '000 lts/day) (83/84)
17. Population benefitted
by piped
dr inking water 416 654 2,126
( • 000) (83/84)
18. CCXM1ercial bank 23 NA 263
branches
Note:
The years in the parentheses refer to the
next nearest year for which data are
available.
NA: Not available
* population of age group 6-15 have been
obtained from the censuses of 1961, 1971
and 1981.
contd ••••

219
Sourcesl
1 & 5 Central Bureau of Statistics (CBS),
Population Monograph of Nepal,Kathmandu,
1987, p.180 and p.128.
2(a & b) Central Bureau of Statistics (CBS),
The Analysis of the Population Statistics
of Nepal, Kathmandu, 1977, p.172.
2c As in 1, p.216
3 & 4 Central Bureau of Statistics (CBS),
Census of ¥~nufacturin7 Establishments,
1965/66, 1972/73, 1976 77 and 1981/82,
Kathmandu.
6(a) to 14(a), 16(a) to 18(a):
Central Bureau of Statistics (CBS),
Shankhikiya Zhalak (2017/18 RO. Tulana Ma
2041/42) in Nepali, Kathmandu, 1985.
15 (a & c)Ministry of Power Resources, HMG/Nepal.
Vidyut Vikas in Nepali published during
national exhibition, Mansir 2043 (November/
December 1986) Kathmandu.
6(b) to 9{b), 14 (b & c), 16(b & c) and 17 (b & c)
Central Bureau of Statistics CBS), Arthik
Varsha 2027/28 Ko Ra 2040/41 Ko Vikas
S'Eandhi Pragati Sthiti Ko Yak Zhalak
( n Nepali), Kathmandu, 1984.
6 (c) & 7 (c)
Central Bureau of Statistics (CBS)
Statistical Pocket Book, Kathmandu,1984,
pp.64-68.
8(c), 9{c), lOCb & c)
Ministry of Health, HMG/Nepal, Health
Information Bulletin, Vol.2, No.2,
Kathmandu, 1986.
contd •••

220
11(b)
11(c)
Ram Bahadur K.C. "Development of Rural
Poor", Nepalese Economic Journal, Vol.1,
1979, p.59.
Central Bureau of Statistics (CBS),
Statistical Pocket Book, Kathmandu, 1984,
p.76.
12(b & c) Central Bureau of Statistics (CBS),
Statistical Pocket Book, Kathmandu,
1982, p.118 and 1984, p.107.
13(b & c) Department of Roads, Nepal Ko Sadak
Ishathiti 2041, Kathmandu, 2041, p.l.
18(c)
Central Bureau of Statistics, Nepal in
Figures, Kathmandu, 1983.

221
There has been a steady rise both in the
number of manufacturing establishments and employment
over time. The number of manufacturing
establishments increased from 1,257 units in
1965/66 to 4,903 units in 1981/82, volume of
employment increased from 14,397 persons to
81,050 persons. Similarly, gross industrial output
increased from Rs.416 million to Rs.7,098
million and value added increased from 60.3 million
to Rs.2,361 million during the same period.
In the field of education too the country
has experienced a record growth.
There bas been
a tremendous rise in the number of general schools.
As a result of this the percentage of school
going children in the age group of 6-15 years has
shot up to 46.50 per cent in 1981/82. Both the
factors have resulted in a higher literacy rate
which stood at 23.50 per cent in 1981 compared to
8.9 per cent in 1961/62 •
.
Until 1961 health facilities in the country
were very much limited and heavily concentrated
in certain parts of the country. Preventive health
care facilities were very meagre.
Malaria was

222
very common, epidemic disease like cholera, tuberculosis,
small pox etc., were very much rampant.
After 1956 various programmes on preventive
health services were launched. As a result of
this, the incidence of malaria, small pox and
cholera have dropped significantly. After the
assessment of the situation in 1977 Nepal was
officially declared a small pox free country
(ESCAP, 1980).
Similarly, significant achievements
have been made in curative health services. Health
facilities were restricted to 35 hospitals, 797
hospital beds and 128 doctors in 1961.
Now, the
number of hospitals, health posts, hospital beds
and doctors have reached 73, 744, 2,506 and 678,
respectively, in 1981/82.
Transport sector is one of the areas in
which the country has recorded impressive achievements.
Surfaced road length in 1961 was limited
to only 907 krns and major parts of the country
remained isolated due to the lack of transportation
network.
In 1981/82 the country's surfaced
road length has reached 5,270 kmsand now the
country has relatively good transportation network.

223
The development in power sector has also
been quite noticeable. The total installed capacity
of electricity generation has increased
tremendously from 7,070 KW in 1961 to 154,244 KW
in 1983/84. As a resul t of this, the population
benefitted by this achievement has also increased
by 11 times during the period from 0.1 million
people to 1.10 million people. Similarly, the
piped drinking water facility has also gone up
significantly by almost 8 times from 20.29 million
litres per day to 173.4 million litres per day
during the same period. As a result of this, the
population benefitted by piped drinking water
facility has reached 2.12 million people in
1983/84 from 0.4 million in 1961. Commercial
banking services is also another area where the
country has made significant progress during the
last twenty years.
Its branches have gone up from
23 in 1961 to 263 in 1981. Its service is also
spreading fastly to all the parts of the country
covering more rural areas.
It should, however, be noted here that there
exists significant regional imbalances in socioeconomic
development in Nepal which are largely

224
due to its physical setting into plains (Terai),
" JaiD,
hills and mountains (Shrestha L 1978). Being in
the plains its highly favourable physical environment
has offered more development possibilities
in Terai compared to Hill and Mountain regions.
This has attracted various development projects
in the past and also at present which have contributed
to its development to a larger extent.
Terai region, compared to Hill and Y~untain,
In
per
heetare of
capita income is higher, population per cultivated
"
area is low, irrigational facility is more, literacy
rate is higher, industrial development and
urban centres are more, transport and coltlTlUnication
network is better and availability of social services
such as schools, hospitals, health centres
and health posts is far better. Furthermore, Terai
region is food surplus area whereas Hill and Mountain
are seriously in deficit. Kathmandu Valley
which is a small pocket and where the capital
city
Kathmandu is located, however, is the most prosperous
region of the country. It should also be
mentioned here that the eastern and central part of
the country is relatively more developed than the
western part in all respects.

225
8.6 Selection of Socio-Economic Development
Indicators:
Development 1s a multi-dimentional phenomenon.
Its definition varies widely among social scientists,
economists, geographers, sociologists, etc. However,
in the present study our major concern is to obtain
the levels of socio-economic development of districts.
In order to arrive at this objective 23 indicators
have been considered which are mainly based on
the availability of comparable data. The main
sectors from where these indicators have been drawn
concern with agriculture, industry, health, education,
transport and comnunication, power and banking.
By selecting 23 indicators of development from
different sectors of the economy we are introducing
diversity in content to suit the broad canvass that
-development- encompasses. By diversity in content
we mean that the indicators selected reflect the
various dimensions of development.
By doing so we
would expect more accurate and representative levels
of development of districts. The list of indicators
selected to obtain--the index of socio-economic
development are as followsl

226
1.
Cultivated area per agricultural worker
in hectares,
2.
3.
4.
s.
Cropping intensity,
Investment on f~m mechanization and
It

227
17. Effective literacy rate (%),
18. Percentage of school going children in the
age group of 6-15 years,
19. No.of post offices per 100,000 population,
20. Radiosin use per 100,000 population,
21. No.of commercial banks per 100,000 population,
22. Surfaced road length per 10,000 persons per
100 sq.km, and
23. Piped drinking water supply per head per
year in (Gallons).
8.7 Levels of Socio-Economic Development:
In order to arrive at the levels of socioeconomic
development of all 75 districts, factor
analysis technique has been employed.
The results
are presented in Table 8.2 which provide the
varimax rotated factor loadings of 23 variables.
The factor loadings in the table indicate the net
correlation between each factor and the observed
variables. From the table it is clear that five
factors (dimensions of socia-economic development)
together explained about 73 per cent of the overall
variance in the data matrix.

Tab1e 8.21 Rotated Factor Load~n95 of Soc~o Economic Variables
Variables
Factor Loadings of Factor
1 2 3 4 5
Communality
1. Cultivated Area per
agricultural worker in hectares
-0.188 -0,772 0.068 -0.173 0.230
0.719
2. Cropping Intensity
0.217 0.015 0,644 -0.363 -0.167
0.624
3. Investment on farm
mechanization and
irrigation per total
cropped area
4. No.of Co-operatives per
agricultural work~r
0.214 -0.847 0.237 0.037 -0.120
0.194 -0.765 -0.164 0.054 0.030
0.837
0.654
tv
tv
co
5. Consumption of chemical
fertilizers per total
croped area
0.853 0.078 0.013 0.071 0.099
0.749
6. Use of high yielding
varities of seeds per
cropped area
7. Percentage of irrigated area
to total arable land
0.231 -n,540 -0.106 0.136 0.554
-0.061 -0.492 0.406 -0.045 0.143
0.683
0.434
8. Gross value of agricultural
out-put per agricultural
worker
0.128 -Q.837 -0.175 -0.073 -0.111
0.767
contd ••

~.Le O'.~~ '~"-"AA-"""'."
Variables
Factor Loadings of Factor
1 2 3 4 5
Communality
9. Percentage of workers
in secondary and
tertiary sector 0!559 -0.629 -0.074 0.092 -0.224 0.774
10. Value added per workers
engaged in industrial
establishments -0.103 -0.352 0.283 0.217 -0.313 0.361
11. No.of persons employed
in regd. industrial
establishments per
100,000 population 0.744 -0.474 0.156 0.052 -0.075 0.812
12. No.of regd working \0 '"
establishments per
100,000 population 0163~ -0.613 0.151 0.121 -0.220 0.870
13. Electricity consumption
per industrial worker
in (. 000 Rs.) Q.625 -0.256 0.107 ~.073 0.139 0.493
14. Percentage of urban
population 0.846 -0.210 0.063 0.183 -0.233 0.852
15. No.of hospital beds per
100,000 population 0.805 -0.021 -0.232 0.278 0.003 0.780
16. No.of heal th~ posts',
health centres and
ayurvedic centres per
100,000 population -0.130 0.491 -0.252 -0.246 0.111 0.395
contd ••••

Tab~e 8.21 (contd •• )
I
Variables
Factor Loadings of Factor
1 2 3 4 5
Communality
17. Effective Literacy Rate (%) 0.489 -0.133 0.029 0.740 -0.008 0.805
18. Percentage of school going
children in the age group
of 6 - 15 years 0.411 0.108 -0.165 0.795 -0.093 0.850
19. No.of post offices per
100,000 population -0.081 0.150 -0.912 -0.022 0.127 0.878
20. Radios1n use per 100,000
population ~835 -0.051 -0.174 0.375 -0.066 0.876
!'J
'..oJ
-:>
21. No.of commercial banks
per 100,000 of population 0.402 -0.170 -0.809 -0.035 -0.133 0.865
22. Surfaced road length per
10,000 person per 100 Sq.Km. 0.488 -0.160 0.042 0.123 -Q._6~2 0.747
23. Piped drinking water supply
per head per year in
(Gallons) 0.894 0.001 -0.078 0.216 -0.191 0.888
Explained variance 8.32 3.90 2.33 1.14 1.01
Percentage of explained variance 36.19 16.96 10.13 4.97 4.43
Cumulative variance (%) 36.19 53.15 63.29 68.26 72.69

231
Around 37 per cent of the overall variance
is explained by Factor 1 alone. This factor is
represented (as indicated by high individual factor
loadings) by nine variables: fertilizer consumption,
workers in secondary and tertiary sector,
employment in industrial establishments, number of
industrial establishments, electricity consumed
by industries, percentage urban, hospital beds,
radio in use, and piped drinking water supply.
Looking into the loadings of the variables,
Factor 1 is identified as "industrial development/
modernization".
Out of the 73 per cent of the overall
variance, 17 per cent of the variance is explained
by Factor 2.
The five variables of this factor
are: cultivated area, investment on farm mechanization
and irrigation, cooperatives, use of high
yielding varieties of seeds, and gross value of
agricul tural output. All these variables represent
the dimension of agricultural development.
Thus
Factor 2 represents "agricultural development".
It should be noted here that the loadings of these
variables are negative.
In other words, districts

232
which record low/negative factor scores would
be characterized by high degree of agricultural
development and vice versa.
Factor 3 has high loadings with three variables
viz., cropping intensity, number of post
offices, and number of commercial banks. These
three variables are very much different from each
other. However, this factor may be considered to
represent a dimension of "infrastructural development".
This factor represents 10 per cent of
the overall variance.
Factor 4 represents "educational· developmentN.
The variables which record high loadings
are literacy and enrolment rate. Factor 5 represents
development of "transportation system".
Only one variable which has high loading with this
factor is surfaced road length. Factor 4 and
Factor 5, however, represent only about 5 and 4.5
per cent of the overall varianc~,
respectively.
In the present chapter we have confined our
analysis to first two factors (dimensions of socioeconomic
development) -
industrial development/
modernization and agricultural development.

233
Using the rotated factor loadings matrix of
the first two factors, factor scores of all the
75 districts are obtained. The technique involved
in obtaining the factor scores has already been
explained in detail in Chapter Two.
The factor
scores of the districts thus obtained and their
corresponding ranks are given in the Appendix 8.1.
As mentioned above, in the present chapter
first two factors are considered each of which
represent separate dimension of socio-economic
development.
In order to classify the districts
by levels of socio-economic development based on
first factor scores, first the factor scores of
all 75 districts are ranked in descending order.
The group of 25 districts falling under first 25
ranks are treated under high category. Similarly,
the districts falling under 26 to 50 ranks and
51 to 75 ranks are treated under moderate and ~
category, respectively. Districts,thus classified
into three categories based on first factor
scores are illustrated in MapS.l. In the case of
second factor scores, the rankings have to be
looked from reverse order as the loadings of the

-
,..r: .... ::.
.: ...... .
-
/
....... .
.. . . ... ~ .. .
. . . . . . .

235
variables, as already mentioned above, are negatively
correlated with Factor 2.
All the 75 districts
have been classified into three levels of
socio-economic development based on factor scores
for Factor 1 and 2 separately. The selection of
cut off point is, however, arbitrary. The regional
distribution of districts separately by each
factor of socio-economic development are presented
in Table 8.3.
From the table it is evident that there is
significant regional variations in socio-economic
development in Nepal.
Distribution of districts
by first factor reveals that out of 18 districts
of Terai region, 12 districts exhibited high and
6 districts showed moderate level of socioeconomic
development. Similarly, all the districts
of Kathmandu Valley exhibited high level of socioeconomic
development.
In contrast to this, of the
total 16 districts in Mountain region,10 districts
recorded low level of development and only 2 districts
in this region exhibited high level of
development, remaining 4 are under moderate category.
Similarly, in Hill region 27 out of 33
districts are concentrated in bottom two categories

Table 8Ll' Distribution of Districts by HeglQns~n9_Leve~Q~_Socio-EcQnomic p_evelopment
Levels of Factor 1 Factor 2
Socio-
Economic Moun- Hill Kath- Inner Terai Total Moun- Hill Kath- Inner Terai Total
Deve1op- tain mandu Teral tain mandu Terai
ment Valley Valley
High 2 6 3 2 12 25 1 1 3 3 17 25
Moderate 4 13 2 6 25 4 18 2 1 25
Low 10 14 1 25 11 14 25
Total 16 33 3 5 18 75 16 33 3 5 18 75
~
W
0\

237
of moderate and low with only 6 districts falling
in high category. In the case of Inner Terai,however,
they are more or less equally distributed
among the three categories.
The distribution of districts by Factor 2
reveals a more clear picture of the regional disparities
in development (Table 8.3). All three
districts of Kathmandu valley and 17 out of 18
districts in Terai region recorded high level of
development.
Contrary to this only one district
each in Mountain and Hill region recorded high level
of development.
About 69 and 43 per cent of the
districts in Mountain and Hill regions, respectively
experienced lowest level of development.
Districts
falling in moderate and low categories taken together
account about 96 per cent of the districts in both
the regions thus suggesting their low level of development.
Inner Terai region,however, presents more
or less similar pattern as in first factor.
Thus,
it may be stated that the importance of different
regions is very much obvious in understanding the
socia-economic development process in Nepal.

238
8.8 Socio-Economic Development and Population
Growth: Some Emerging Patterns
In order to understand the relationship between
levels of socio-economic development and population
growth, and its components the unweighted
average rates for all the demographic indicators
for the districts falling within each level of
development have been worked out and are presented
in Table 8.4. These results present some interesting
patterns of population growth by levels of
socio-economic development in Nepal.
When considered Factor 1, the behaviour of
crude death rate by each level of socio-economic
development is as expected.
The average crude death
rate (CDR) for low, moderate and high categories
are 20.91, 16.90 and 14.17, respectively. The inverse
relationship between levels of socio-economic
development and CDR could be clearly observed here.
A similar declining pattern with higher
levels of socio-economic development could also be
observed for adjusted crude birth rate (ACBR). The
average ACBR for low, moderate and high categories
are 42.63, 41.30 and 39.86, respectively. However,
ACBR does not exhibit much variation by three

239
Table 8,4: Levels of Socio-Economic Development and
Demographic Indicators: Emerginq Patterns
Levels of
Socio-
Economic
Development
Demographic Indicators
CDR ACBR RNI RNM RTI Density
Industrial Developmentl
Modernization
Factor 1
High 14,17 39.86 25.69 + 5.27 30.96 266.59
Moderate 16.90 41.30 24.40 - 2.82 21.58 151.45
Low 20.91 42.63 21.72 - 8.96 12.76 67.06
Agricul tural Development
Factor 2
High 14.18 39.98 25.80 +11.26 37.06 291.19
Moderate 17.03 41.48 24.45 - 9.42 15.03 123.62
Low 20.76 42.33 21.57 - 8.38 13.19 70.30
Note: CDR ·•
Crude Death Rate
ACBR , Adjusted Crude Birth Rate
RNI ·•
Rate of Natural Increase
, Rate of Net Migration
RNM
RTI
, Rate of Total Increase

240
levels of socio-economic development.
There is
also a trend of increase in natural rate of population
growth (RNI) with higher levels of socioeconomic
development. As socio-economic development
has much strong inverse association with CDR
than ACBR the trend of increase in RNI with higher
levels of socio economic development are quite as
expected.
The rate of net migration (RNH) is expected
to be positively related with the levels of sqcioeconomic
development and the results show that it
is in the expected direction. A clear pattern of
high net in-migration with higher levels of socioeconomic
development and high net out-migration
with lower levels of socio-economic development
can be observed from the table. This has clearly
brought out the positive relationship between
levels of socio-economic development and rate of
net migration (Rm1).
In the case of rate of total increase CRTI)
in population it is very interesting to observe
higher RTI with higher levels of socio-economic
development.
Districts with high levels of

•
241
socio-economic development have experienced high
average RTI of 30.96 per thousand per year which
correspondingly decreased to 21.58 and 12.76 in
moderate and low category, respectively. Thus it
may be concluded that there exists a positive
relationship between levels of socio-economic development
and RTI.
This relationship has emerged
mainly because of the positive relationship of both
the components of total increase i.e., RNI and RNM
with levels of socio-economic development. Similarly,
as expected population density is also positively
associated with the levels of socio-economic development.
The average population density is highest
with 266.59 persons per sq.km. in high category and
lowest with 67.06 in low category, moderate category
with 151.45 falling in between.
With respect to Factor 2 similar patterns
could be observed as observed above in the case of
Factor 1. The results are very much close to each
other (Table 8.4). It should be emphasized here
that Factor 2 represents the dimension of agricultural
development.
The findings that we have
obtained thus reinforce our earlier findings in
Chapter Six.

242
Our above findings have been further confirmed
by zero-order correlation coefficients
obtained between demographic indicators and each
factor scores. The results are presented in
Table 8.5. Our earlier findings of the positive
association between levels of socio-economic
development (Factor 1) and RNI, RNM, RTI and
Density has been further confirmed by the correlation
coefficients. All the correlation coefficients
are in the expected direction. However,
only density and RTI are statistically significant
at 1 and 5 per cent level, respectively_
Similarly, the negative relationship between
levels of socio-economic development and CDR and
ACBR has also been confirmed.
However, only CDR
is statistically significant at 1 per cent level.
With regard to the correlation coefficient
of demographic indicators with second factor
scores it should be remembered
here that the
loadings in Factor 2 which represents agricultural
development are negative.
In other words, districts
which recorded low/negative factor scores
would be characterised by higher degree of agricultural
development.
Therefore, the positive

243
Table 8.5: Zero-Order Correlation Coefficients
between Demographic Indicators and
Scores of Socio-Economic Development
Correlation Co-efficients
Demographic Indicators
Crude Death Rate
Adjusted Crude Birth
Rate
Rate of Natural
Increase
Rate of Net Migration
Rate of Total Increase
Density (per sq.km)
Industrial
Development/
Modernization
Factor 1
-0.363**
-0.203
0.134
0.210
0.255*
0.758**
Agricultural
Development
Factor 2
0.546**
0.229*
-0.258*
-0.483**
-0.512**
-0.448**
* Significant at 5 per cent level
** Significant at 1 per cent level.

244
coefficients bet\veen Factor 2 and crude death
rates and crude birth rates indicate that where
agricultural development is low (i.e., level of
Factor 2 high) crude death rates and crude birth
rates tend to be high. Similarly, the negative
coefficient bebieen Factor 2 and RNI, RNN, RTI as
well as density suggests that wherever agricultural
development is high (i.e., level of Factor 2
low) the RNI, RNM, RTI and density tend to be
high. All the signs are in the expected direction
and also statistically significant at 1 per
cent level except RNI which is statistically
significant at 5 per cent level. Similarly, CDR
and CBR are statistically significant at 1 and 5 ,
per cent level, respectively. With Factor 2 all
six indicators are statistically significant. All
our findings thus supported the relationships
which were hypothesized between socio-economic
development and population growth and its
componen ts •
What has clearly emerged from all these
findings is the meaningful patterns of population
growth and its components with levels of socioeconomic
development in Nepal.

245
APPENDIX 8.1
Distr ictwise Factor Scores and Ranks by Socio-Economic
Development
51.
No.
Districts
Socio-Economic Development
-
Factor Scores
I Rank II Rank
1 2 3 4 5 6
1. Taplejung -3.685 58 3.643 51
2. Panchathar -3.550 54 4.318 58
3. Illam 1.891 16 0.515 31
4. Jhapa 4.359 13 -7.372 8
5. Teratbum 0.309 24 1.626 36
6. Dhankuta 0.736 22 -0.361 27
7. Morang 8.424 6 -8.668 4
8. Sunseri 6.260 8 -11.640 2
9. Sankhuwasabha -2.787 44 2.468 42
10. Solokhambo -2.034 39 4.550 61
11. Bhojpur -3.220 49 2.890 47
12. Khotanj -4.212 62 4.727 63
13. Okhaldhunga -3.118 48 3.521 49
14. Udayapur -2.713 43 -0.062 28
15. Saptari 1.611 17 -6.630 14
contd ••••

246
APPENDIX 8·1 (contd •• )
1 2 3 4 5 6
16. S1raha -0.782 28 -6.191 15
17. Dolakha -3.213 50 3.759 53
18. Ramechap -3.215 51 0.469 30
19. S1ndhu11 -3.571 55 1.109 34
20. Dhanukha 5.183 10 -8.091 6
21. Mahottari -1.558 36 _4.165 21
22. Sarlahi -1.134 32 -7.168 10
23. S1ndhupal Chowk -2.576 41 3.604 50
24. Rasuwa -3.270 53 0.858 32
25. Nuwakot -0.871 29 2.172 40
26. Dhading -3.799 59 2.597 44
27. Bhaktapur 17.205 3 -5.994 16
28. Kavrepalan Chowk 0.178 25 1.920 39
29. Kathmandu 43.227 1 -8.530 5
30. Lalitpur 17.687 2 -4.440 20
31. Makwanpur 5.193 9 -2.143 25
32. Chitwan 7.885 7 -11.679 1
contd •••

247
APPENDIX 8·1 (contd. ,)
1 2 3 4 5 6
33. Rauthahat -1.910 38 -0.437 26
34. Bara 0.495 23 -7.221 9
35. Parsa 9.714 4 -11.393 3
36. Gorkha -2.854 45 4.308 57
37. Larnjung -1.452 35 1.437 35
38. Tanahu -1.104 31 2.605 45
39. Syangja -1.374 34 2.571 43
40. Kaski 8.684 5 -2.899 23
41. Manang 0.919 21 0.360 29
42. Mustang 4.665 11 -2.365 24
43. Myagdi -3.116 47 4.259 56
44. Parbat -1.586 37 3.917 54
45. Bag lung -2.945 46 2.866 46
46. Gulmi -1.260 33 1.655 37
47. palpa 0.976 19 2.322 41
48. Nawalparasi 0.964 20 -5.897 17
49. Rupendehi 4.158 14 -7.814 7
SO. Kapilvastu -0.643 27 -7.014 11
contd ••••

248
APPENDIX 8·.1 (contd ••• )
1 2 3 4 5 6
51. Arghakhanchi -2.221 40 3.292 48
52. Pyuthan -4.148 61 4.625 62
53. Rolpa -5.112 69 5.060 66
54. Rukum -5.052 68 4.915 64
55. Salyan -4.649 64 4.015 55
56. Dang -1.013 30 -5.370 19
57. Banke 4.514 12 -6.746 13
58. Bardiya -2.673 42 -3.395 22
59. Surkhet 0.434 26 1.015 33
60. Dailekh -4.817 65 4.479 60
61. Jajarkot -5.319 73 5.090 67
62. Dolpa -4.418 63 5.173 68
63. Jumla 3.624 56 4.420 59
64. Kalikot -6.062 75 6.805 74
65. Mugu -5.646 74 6.003 73
66. Humla -5.296 72 8.307 75
67. Bajura -5.287 71 5.363 71
contd ••••

249
APPENDIX 8·1 (contd•••')
1 2 3 5 6
68. Bajhang -5.151 70 5.340 69
69. Achharn -4.989 67 5.355 70
70. Doti 4.858 66 3.703 52
71. Kailal! 1.071 18 -6.910 12
72. Kanchanpul: 2.856 15 -5.657 18
73. Dadeldhura -3.251 52 1.783 38
74. Baitadi -9.919 60 5.395 72
75. Dal:chula -3.667 57 4.947 65

CHAPTER IX
SUMMARY AND CONCLUSION

CHAPTER IX
SUMMARY AND CONCLUSION
9.1 Summary:
Nepal has been experiencing rapid population
growth in recent years. There are also significant
variations in the rate of growth of population
across different regions and districts. These
emerging situations on the population front could, .
among other things, probably be attributed to the
existing disparities in the levels of development
across different regions and districts. It has
been widely accepted that there is a strong associdevelopment
ation between levels of socio-economicLand population
growth.
The process of socio-economic development
may alter the course of mortality, fertility,
and migration which, in turn, would affect population
growth. A knowledge of this relationship is
useful in understanding the nature and the extent
of changes expected in population growth and its
components given the level of development.
The
"theory of demographic transition- and the "threshold
hypothesis" are theoretical attempts in understanding
these relationships.

251
Many studies have examined the relationship
between socio-economic development and population
growth both from macro and micro perspectives. In
the specific setting of Nepal, however, previous
studies have not tried to understand the patterns
of population growth by levels of agricultural
development and/or socio-economic development.
Furthermore, no attempt has been made to explain
the variations in population growth at the disaggregated
level (districts) in terms of data on
the components of population growth at the district
level. Hence, the present study has been designed
to explain the variations in population growth in
terms of its components at the disaggregated level
by estimating them and to understand the patterns
of population growth by levels of agricultural
development and by levels of socio-economic development
in Nepal.
The specific objectives of the study are:
(i)
to examine the patterns of population
growth in Nepal by regions and districts,

252
(ii) to estimate the components of population
growth i.e., birth, death and migration
during 1971-81 at the district level,
(iii) to delineate the patterns of population
growth by levels of agricultural development,
(iv) to examine the patterns of urban
population growth, and
(v)
to delineate the patterns of population
growth by levels of socia-economic development.
At the outset it was shown that the demo-
9raphic history of Nepal revealed three distinct
periods: (i) a period of decline in population
size during 1911-30, (ii) a period of erratic growth
in population during 1930-61, and (iii) a period of
rapid growth in population during 1961-81.
The
spurt in the rate of growth of population during
1961-81 was attributed to the rapid decline in
mortality level without a corresponding decline in
fertility. The effect of net international migration
was considered to be negligible. The steady
mainly
decline in the mortality level in the country wasL
attributed to the rapid expansion of health facilities
(both preventive and curative), and the

253
increase in the supply of piped drinking water.
Unlike mortality, fertility, which has remained
almost constant over time at a high rate, has
been attributed to various factors like lower
female age at marriage, marital status distribution,
larger proportion of younger female population,and
lower contraceptive prevalence rate. In
the case of immigration and emigration it was
pointed out that their behaviour remained quite
uncertain due to extremely limited and defective
data. However, both immigration and emigration
were attributed to factors like ·push-pull· and
marriage across borders with Indian states.
It was also shown that there exist significant
variations among different regions, sUbregions
and districts with regard to the rate of
growth of population. During 1911-81, Hill and
Mountain regions experienced the lowest and Terai
region the highest rate of growth of population,
with Kathmandu Valley falling in between. Within
each region western segment, by and large,witr.essed
rapid growth in relation to central or eastern

254
segment of the ~ame region. Considering particularly
the 1971-81 decade, it was shown that by
districts the annual rate of growth of population
varied from a very high rate of 9.39 per cent to a
negative growth rate of 2.72 per cent. Attempts
were made to decompose the population growth into
its components to explain the large variations
across distJ:icts. The components of population
growth i.e., birth, death, and net migration were
estimated by using indirect demographic techniques.
P!F Ratio method originally developed by Brass was
made use of to estimate the adjusted crude birth
rate. Similarly, Trussel variant of the original
Brass method of estimating child mortality was
used to obtain the level of mortality and thus the
crude death rate. After having obtained crude
birth rate and crude deat.'1 rate the balancing
equation procedure was used to arrive at the rate
of net migration. The estimates obtained showed
wide variations in all the three components of
population growth across districts during 1971-81.
Thus, the variations in the rate of growth of population
was found to be systematically related to
the variations in the rate of natural increase and

255
net migration.
Based on the variations in the
rate of growth of population and the relative
importance of the rate of natural increase and
rate of net migration districts were classified
into specified demographic patterns of very high,
population
high, moderate, low and negative rate of total L
increase.
In the present study district was considered
as the unit of analysis. An understanding of the
patterns of population growth separately by levels
of agricultural development and socio-economic
development warranted an index of development both
agricultural and socio-economic.
In order to
arxive at such an index 12 indicators representing
agricultural development and 23 indicators representing
socio-economic development were considered.
All the data, which referred to 1981/82, were
gathered from various published and unpublished
sources.
Factor analysiS technique was employed
to obtain the factors (dimensions) of agricultural
and socio-economic development.
Each of the factor
(dimension) was treated as a separate dimension of
development.
Only two factors, in each,

256
(agricultural development and socio-economic
development) were considered. On the basis of
factor scores, 75 districts were classified into
three levels of agricultural and socio-economic
development viz., high, moderate and low. Considerable
variability in the levels of development
among the districts was observed. Majority of the
districts which belonged to Terai, Inner Terai and
Kathmandu Valley recorded higher levels of both
agricultural and socio-economic development. With
very few exceptions almost all the districts in
Mountain and Hill regions recorded moderate or low
levels of development.
An inverse relationship was hypothesized
between crude death rate (CDR), and levels of agricultural
development and socio-economic development
and an uncertain/weak relationship in the case of
crude birth rate (CBR).
Similarly, with regard to
rate of natural increase (RNI), rate of net migration
(RNM), rate of total increase (RTI) and
population density a positive association was hypothesized.
The behaviour of CDR by levels of agricultural
development and socio-economic development

257
was in the expected direction showing a declining
trend in CDR with higher levels of agricultural
and socio-economic development. CBR also exhibited
similar declining trend with higher levels
of agricultural and socio-economic development.
However, the variations in CBR between the levels
of development were not large which indicated a
very weak association. A trend of increase in RNI
with higher levels of agricultural and socioeconomic
development was also observed.
Similarly,
the RNM exhibited a positive association. As a
consequence to these, it was found that RTI was
positively associated with levels of agricultural
and socio-economic development. Density also
exhibited positive association. EXamination of
zero-order correlation coefficients of the demographic
indicators with factor scores of agricultural
and socio-economic development also confirmed
the above findings.
The findings, thus, showed
that all the demographic indicators exhibited more.
or less similar patterns both by levels of agricultural
and socio-economic development which is only
to be expected in a·country like Nepal.

258
In spite of the very low level of urbanization,
it was shown that the growth of urban population
was very rapid in Nepal in recent years.
Attempts were made to understand the relationship
between population growth of towns and their
functions. Wilkinson's method was followed to
functionally classify the towns. The results
revealed that the manufacturing towns recorded the
highest rate of growth of population followed by
trade and commerce, agriculture, and service towns
in that order. Quite expectedly, bifunctional and
multifunctional towns exhibited higher rate of
growth of population than monofunctional towns.
9.2 Concluding Remarks:
The findings of the study indicate that the
patterns of population growth in the country is
closely related to its socio-economic conditions.
On the basis of our findings it may also be mentioned
that if the disparities in the levels of development
among different regions and districts are not
minimized the present patterns of population
growth are likely to continue. This suggests the

259
need for reducing the disparities in the levels of
development through more coordinated efforts on
balanced regional development which will to a larger
extent help in minimizing the existing inter-regional
and inter-district migration. The development ot
backward regions and areas may-also help in bringing
down the levels of mortality and fertility. In
this regard, National Commission on Population
(NCP, 1984) in one of its studies has suggested the
following recommendations to reduce the interregional
disparities and improve the living conditions
of the people of Mountain and Hills:
(1) concentration of Integrated Rural Development
programme in the Mountain and Hills with more
emphasis on horticulture and livestock development,
(ii) promotion of cottage and small scale industries,
and
(iii) growth of secondary and tertiary economic
activities through planned promotion of urban centres
and provision of power through micro-hydel
projects.

260
relevant.
These policy recolm'lendations appear to be
In this respect the question is can
"development- alone be considered as a suitable
policy measure. for reducing fertility and thus
ar resting the growth of population? If the answer
the
is inLaffirmative then this follows one more relevant
question i.e.,are the present levels of
socio-economic conditions high enough to bring
about a genuine fertility transition? These
questions could be answered with the help of wellknown
threshold
hypothesis. The threshold hypothesis
postulates that: -in a developing country,
the fertility is initially high.
Improving economic
and social conditionS are likely to have litt4e if
any effect on fertility until a certain economic
and social level is reached, but once that level is
achieved, fertility is likely to enter a decided
decline) and to continue downward until it is again
stabilized on a much lower planeR (UN, 19651 143).
Attempt has been made to gather the information on
some selected indicators of socio-economic development
for the country as well as its regions to
compare them wi th given threshold level. From

261
cross-national analysis, United Nations (1965),
Kirk (1971), Mari Bhat (1975), and Srikantan (1977)
have obtained threshold levels for a number of
indicators. We have used Srikantan's thresholds
for the sake of comparison, since these are based
on more recent data.
Values of various indicators for the country
and each of the region along with the threshold
ranges obtained by Srikantan are given in Table
t"e.
9.1. For some of ,.. indicators values are not
available. Apparently, for the country none of
the indicators have reached the threshold level.
Almost all the indicators are still far below the
lower threshold level. Among regions only
Kathmandu Valley has attained threshold levels for
four indicators out of total 10 indicators for
which data were available. With the existing situation,
where more than 40 per cent of the people live
below poverty line, most of the basic minimum needs
of the people are unmet and malnutrition is common,
the rapid improvements in the levels of all these
indicators in the near future appear to be an

Table 9,1. Demographic and Socio-Economic Indicators for Nepal and Its Regions
& Threshold Values
Threshold
Indicators Range Nepal
(Srikantan) 1981
Regions
Moun- Kathmandu Inner
tain Hill Valley Terai Terai
1 2 3 4 5 6 7 8
Male life expectancy 64,1-66,4 50,88 NA NA NA NA NA
Female life expectancy 66.4-69.2 48.1 NA HA RA RA NA
Per cent of women
15-19 unmarried 78.4-89.1 49.2 59,6 56,3 65,1 52,9 34.4
Per cent of women
15-24 unmarried 54.2-67.5 30.2 38.8 36.7 43.6 32.4 18.8
Per capita gross domestic
product (GDP) in
US $ 704-1056 153.4 NA NA NA NA NA
Per cent of GOP from
agricultural sector 23.0-6.0 57.1 NA NA NA NA NA
Per cent of economically
active population in
agricultural sector 53.4-26,2 90.4 95.7 95,6 75.5 90.3 86.8
Per cent of economically
acti ve mal es in
agricultural sector 50,7-26,4 87.8 94.4 94.1 69,S 88.7 84.7
N
0\
N
contd •••

Table 9.1 (contd •• )
1 2 3 4 5 6 7 8
Per cent of temale population
literate 55.4-69.5 11.5 7.8 10.9 30.5 13.0 11.6
Per cent of population
6-15 in school 49.0-79.0 46.5 41.1 47.8 87.7 42.1 41.7
Per cent of population
in places 100000 + 9.0-41.6 1.5 Nil Nil 30.7 Nil Nil
Per cent of population
in places 20000 + 17.7-63.2 7.1 Nil 0.8 47.4 6.5 9.6
Radio receivers per
1000 population 41-279 12.1 8.4 11.1 44.9 10.9 9.8 f\J
0\
Population per
w
hospital bed 290-220 5809 11329 11401 673 13464 8117
population per doctor 1300-1100 22157+ NA NA NA NA NA
population per aurae 1130-530 7306+ NA NA NA NA NA
Per capita energy
consumption 687-2499 14 * NA NA NA NA NA
CODtd •••

Table 9.1 ~contd •• 1
1 2 3 4 5 6 7 8
No.of indicators below
lower threshold level 17 10 10 6 10 10
No.of indicators above
lower, below upper level 0 0 0 3 0 0
No.of indicators above
upper level 0 0 0 1 0 0
Notel NA - Not Available1 * refers to 1979; + refers to 1982/83.
The value of indicators shown in table for regions refer to the pooled data of
all the districts falling in each region.
Sources I 1,2 - Central Bureau of Statistics (CBS),Population Monograph of Nepal,
Kathmandu, 1987, p.268.
3,4,5,7,8,9,11,12,13 - Census Reports, 1981.
5,6 - Central Bureau of Statistics (CBS),Statistical Pocket Book, Kathmandu,
1986, p.2S3 and 240.
10 - Ministry of Education and Culture, -Nepal Ko Shaichik Thathayank Pratibedan
~, pp.91-98.
14 - Ministry of Health, Health Information Bulletin, Vol.2, No.2, Kathmandu,
1986, p.20.
15,16 - Central Bureau of Statistics (CBS), Statistical Pocket Book, Kathmandu,
1986, p.20.
""' 0\
4).
17 - David,A.S., and ZIvetz, Laurie, The Population Problem of Nepal I Causes
and Treatment, National Commission of Population, Kathmandu, 1982, p.20.

265
uphill task in Nepal.
Thus, according to the
threshold hypothesis, conditions in the country in
general and regions in particular, with the
possible exception of Kathmandu Valley, are not
favourable to fertility decline. Berlson (1978)
looking into the demographic rates and their
trends and the social setting of 29 countries, to
examine their chances of bringing reductions in
crude birth rates to 20 by 2000, has placed Nepal
in the unlikely category.
However, the experience of some of the areas
in under developed countries have shown that
fertility could be reduced without attaining the
threshold level. For instance, the studies conducted
in Kerala and Karnataka statesof India showed
a decline in total fertility rate without attaining
the threshold level and this was attributed to
family planning programme (Zachariah, 1983; Rao et.al,
1986) • Thus it has been empbasi zed that the mere
reliance on development as a contraceptive will not
solve the ~ediate problem of population growth.
v/hat is required, however, is the implementation of

266
family welfare programme in a more vigorous and
imaginative way.
Thus, efforts are to be made on
both the fronts - development and population
fronts - if the country has to achieve socioeconomic
development coupled with slower rate of
growth in population. Mauldin and Berlson (1978)
after analysing data for 94 developing countries
of the world concluded that if a country wished to
reduce its fertility it should seek a high degree
of modernization and adopt a substantial family
planning programme.
It should be mentioned here
that in Nepal the discontinuation rates for temporary
methods of contraceptive are very large:
there are substantial unmet needs for contraception
and in the case of permanent methods there is
insufficient capacity to match current demand.
Furthermore, studies have indicated that the
knowledge, ever use, and current use of contraception
are relatively higher in uxban than in
rural areas (Ministry of Health, 1987).
These
observations indicate the need for launcing family
planning programme much more vigorously. The programme
should also be geared more towards the rural

267
areas.
Family planning alone may not give the
desired results. Along with it, non-formal educathrough
tion, adult education, population educati0q! mass
media,and maternity and child health programme
should also be launched simultaneously with much
more vigour.
As far as the relevance of our findings with
demographic theory is concerned,it should be recalled
here that the demographic transition theory
has generated a few very general hypotheses according
to which it was postulated that mortality
generally responds more quickly than fertility to
the inventions in medical technology and developmente
This appears to be the case in the Nepalese
context. However, the pace of mortality decline
experienced in Nepal has been quite steady and has
resulted largely because of imported technology and
only marginally due to the pace and level of general
development. Similarly, the findings are quite
in line with the -threshold hypothesis" because
development indicators in Nepal have not attained
the minimum threshold levels and fertility has also

268
remained unchanged. So far as the adoption of
these theoretical developments as a guiding principle
for policy matters is concerned it appears
that Nepal cannot afford to wait to attain the
threshold levels in order to tackle its immediate
problem of population growth.

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