The 1995/1996 Household Income, Expenditure - (PDF, 101 mb ...

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VI.24 nominal rental fee. In the context of rent control, estimates of the subjective valuation of dwelling space are extremely important. Such estimates inform the willingness to move as much as the willingness to pay, and can be aggregated to provide a benchmark for the social costs of rent control. All household heads were asked: "If you would rent the dwelling today, what amount of rent could you receive per month?" This "key money proxy," or "keyrent" as it came to be known, was then annualized. For ordinary and furnished renters, the difference between actual and subjective rent approaches consumer surplus for individual cases. The obvious question is whether consumer surplus, properly adjusted for housing characteristics quality, is higher for owners than for renters. For owners, annualized keyrent should be very near to imputed rental value. The former estimate has a more subjective connotation, more opinionated content; the latter comes from coaching the respondent that taxes indicated dwelling costs, and that the estimate should be based on a dwelling with about the same age and amenities. During the enumerator training phase, there were concerns raised about owners' imputation, whether the respondent would be afraid, or really would be capable, of providing a good estimate for the value of the dwelling. The distribution of owners' imputed rent estimates is worthy of further analysis, especially as an excellent departure for research into imputation bias in the HIECS. VLF.l Intensity of Use of Housing Services A simple indication of the intensity of use of housing services in the country can be derived from the ratio of household members to the number of rooms in the dwelling. This ratio can be further classified by area, tenure, and household expenditure level. Table VIA does this, for survey weighted data (the data are weighted to make inferences about housing at the national level). At first glance one might consider it surprising that rural areas have higher dwelling intensity, and may ascribe this result to the inability to classify households so strictly as either rural or urban. However, households designated rural have more members, and dwellings in rural areas traditionally have fewer rooms. Rural Qena governorate has the highest number of persons per room (1.68) and urban Kafr-Shiekh the lowest (1.07). The use intensity in the tenure group "Other," which includes squatters, the homeless, people living in the City of the Dead, is extremely high. As unadjusted household expenditures rise the number of persons per room exhibits an S-shaped curve; economies of scale in housing appear to reach a plateau at about one and onehalf persons per room.. VLF.2 Inventory of Durable Goods Dividing the 14,805 households into unweighted average annual expenditure quintiles of 2,961 households each, the 1995/1996 HIECS sample frequencies for the existence of household durable goods produces the typical conclusion that the richest quintile owns the most amenities, the poorest quintile the fewest. The frequencies below only characterize the sample and without weighting should not be assumed to represent all Egyptian households. Even if weighted the estimates should not be considered reasonable (or
VI.2S statistically significant) without accounting for variance. For example, only .78% of sampled households own a private automobile. In May of 1996 the Ministry of Transportation estimated the number of "private vehicles" in Egypt to be 1.075 million (with "other vehicles" given as 1.059 million). If "private vehicles" are defined as private automobiles and motorcycles, the inference from sample information given the number of households presumed to exist in Egypt (12,343,580) would produce an overestimate of 1.5 million private vehicles in the country. 1995/1996 HIECS Durable Goods, by Quintile, N = 14,805 Durable Good Quint! Quint2 Quint3 Quint4 Quint5 Car 2 5 12 30 528 Motorcycle 93 204 252 316 363 Bicycle 4 15 19 39 67 Phone 79 175 303 535 1369 Refrigerator 900 1433 1745 2097 2573 Freezer 12 22 31 64 402 Cooker 1259 1752 2026 2298 2665 Washing 1508 2221 2462 2663 2836 Machine Dish Washer 2 9 10 11 90 Water Heater 175 336 543 821 1686 Vacuum 25 50 93 215 878 Air 2 3 6 21 201 Conditioning Fan 996 1420 1696 2050 2421 Heater 32 45 97 155 492 Clothes Iron 703 1361 1747 2084 2565 Color TV 475 933 1250 1553 2222 Black & White 1358 1515 1436 1251 886 TV VCR 11 22 77 183 746 Stereo System 1366 1811 1990 2221 2571 Personal 0 2 1 10 103 Computer Black & white TVs appear to be the only goods for which the number of
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The 1995/1996 Household Income, Exp
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Project'Background Executive Summar
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Chapter I_ Ov'"er"V"ie"" aI1d Proce
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1.11 decreases average household si
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1.13 HIECS as well as international
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1.15 respondent acceptance. These a
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mothelUs were expected to be more s
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1.22 material. There should be a cl
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elied upon, resistance to analytica
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in the speed of processing of any s
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I.E Global Edits 1.28 In late Novem
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Name, Size, and Level of HIECS Raw
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mandatory by law; 16) Reporting err
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Appendix LA Comparing Estimates fro
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The dependent variable is the tth o
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where and R = f g' are estimates of
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Table 1.1 1995/1996 HIECS Sample Si
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Table 1.3 Update Rate ({Sampled-Ori
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Table 1.5 Average Annualized Data E
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Table I.7 Annualized Error Characte
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Table 1.9 One-Way Analysis ofVarian
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MI: University of Michigan, 1980. L
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Sequential List of Tables and Figur
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Digit Preference Indices Digit 5 10
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proper income variable. There is st
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II.10 6.33% of HIECS households sai
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11.12 Percentage Changes in Median
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11.15 involves the difficulty in de
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household per capita income did not
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Table n.1 Asymptotic Properties ofB
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Table 11.2 Household Average Annual
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Table II.3 Household Average Annual
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Table n.3 Household Average Annual
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Table II.5 Earners Classified by Re
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Table II.7 Household Average Annual
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Table n.s 199011991 HIECS Equivalen
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INDIVIDUAL WAGES AND SALARIES INDIV
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Table 11.13 Regression of Level Hou
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Table 11.16 Average Expenditures fo
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Table 11.18 Elasticities for Subsid
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1982. Tellis, Gerard, "The Price El
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Sequential List of Tables III.2 Tab
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IIL5 wages have hardly kept pace wi
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IH.E Household Poverty in Egypt II!
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111.14 number of poor households wo
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III. 20 Cairo, both the richest and
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Appendix lILA Statistical Formulas
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Table II!. 1 Poverty Rate Rankings
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Table III.3a Poverty Rate Rankings
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Table III.3c Poverty Rate Rankings
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'able III.5 Poverty Rate Rankings b
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"able It!. 7a Poverty Rate Rankings
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Bibliography - Chapter III. Poverty
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179, 1993. Rodgers, John L., and Jo
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Sequential List of Tables and Figur
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IV.S The unemployed are further cla
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IV.8 did not permit even a good est
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3. Secondary Industry 4. Machine In
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IV.IS the benchmark from which to m
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IV.18 Finally, standard human capit
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Table IV.2 Individual Incomes by So
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Table IV.4 Wage Regression Results
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Page 171 and 172: sequential List of Tables and Figur
Page 173 and 174: V.4 To underscore the critical impo
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Page 179 and 180: V.10 telephone calls, in mind. Note
Page 182 and 183: V.E Dissemination and Publication V
Page 184: Appendix V.A An Alternate Estimator
Page 187 and 188: (19) E (20 ) t I col, a, t = = Eo 1
Page 190 and 191: Table V.l Comparison of Major Group
Page 193: Figure Y.3 Example ofEgypt's Price
Page 196 and 197: 272-278, 1980. Pollak, R.A., "The S
Page 198 and 199: Sequential List of Tables and Figur
Page 200: VI.4 often two or more floors, with
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Page 207: VI.II consumption of housing. Assum
Page 214: Rent Elasticities VI.18 1990/1991 O
Page 217 and 218: VI.2! Considering utilities as elec
Page 219: Classification of Housing Type and
Page 223: VI.27 values) is positive: 587.51 f
Page 226 and 227: Figure VI. 1 A Synopsis of Egyptian
Page 231 and 232: Table VI.4 PersonslRoom, by Area, T
Page 233 and 234: Table VI.5 Average Housing Expendit
Page 235 and 236: Table VI.6 Ratio ofImputed Value of
Page 237 and 238: Table VI.7 Comparison ofConsumer Su
Page 239 and 240: Frankena, Mark, "Alternative Models
Page 241 and 242: Development in Egypt: Investing in
Page 243: Sequential List of Tables and Figur
Page 248 and 249: VIL7 of age of the household head c
Page 250 and 251: Two-Way Classification of Attained
Page 252: VILli The table above shows that, f
Page 255 and 256: Table VI!. 1 Estimates ofProportion
Page 258: Table VI!.3 Enrollment Ratios (Freq
Page 261 and 262: Bibliography - Chapter VII. Educati
Page 263 and 264: Sequential List of Tables and Figur
Page 265 and 266: VIII. 4 surgical or procedural, ane
Page 267 and 268: VIII. 6 level, additional education
Page 269 and 270: Table VIlLI Mean Medical Expenditur
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Table VIII.3 Household Average Annu
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Bibliography - Chapter VII. Medical
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IX.A Introduction · IX.2 An offici
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IX.S and later found that the infor
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IX.I0 higher quality, less costly i
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The 1995/1996 Household Income, Exp
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Guidelines A Survey on Income, Expe
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Objectives ofthe survey: 1. Identif
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traditions, and holding back inform
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Survev FORMS A. Auxiliary form (For
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Field Work: visit will be before th
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. Vegetables group -- onion, cucumb
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* If the household consumed a commo
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four sub-totals (8-1), (8-2), (8-3)
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The editor is the link between the
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7. Confirming that all families in
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5. Domicile It is the place where t
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8. Working condition The relationsh
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General Instructions Instructions f
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abroad. This table is completed in
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These are simple examples that defi
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This second group contains the foll
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poultry husbandry owned by the hous
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• Underwear winter and summer rea
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Table (6): Household expenses of fu
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This table does not include free se
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ecorded in the overall value column
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'" Expenses during the three months
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of this income on the individuals o
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Data Entry Manual
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First: Editing Coverage The 1995/19
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1 through 20: 4. If the reply to qu
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Instructions for Office Coding ,. ,
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January takes code "01" etc. d. Rur
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011100 121101 122103 131102 131103
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261176 261183 261199 262101 262102
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331911 331916 331917 331919 331999
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442301 442302 442303 491101 491103
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Occupation Codes 9 621502 Milker 62
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742112 742209 742214 742301 742302
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826107 826199 826203 826204 826206
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Economic Activity Codes
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Economic Activity Codes 2 fibers ex
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CONSUMPTION 8888 HEADCOVER-FEM 1620
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FRESH-VEG-TOTAL 359 BLANKETS-COTION
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MEATS-TOTAL 515 SCHOOL-TRANS 2912 C
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CPI item codes 7 GRILLED-FISH 1109
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The HIECS Data Dictionary
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Page 3 Data Dictionary: HIECS Creat
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Page 12 Data Dictionary: HIECS Crea
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Page 21 Data Dictionary: HIEes Crea
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Page 59 Data Dictionary: HIECS crea
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REFRMT.SAS 1 options pagesize=60; l
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REFRMT.SAS 3 if source4=4 then sour
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*/i REFRMT.SAS 5 if bwtv=2 then bwt
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REFRMT.SAS 7 data in. If; "infile a
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REFRMT.SAS 9 output out=codecomm; t
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REFRMT.SAS 11 annval=annval/100 i p
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REFRMT.SAS 13 proc means; var earne
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WTCALC.SAS 1 0ptions pagesize=60; l
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else if gov=13 and urbrur=O then do
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*CAPMAS and Cairo Demographic Cente
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SAS Occupation and Economic Activit
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HKFIX.SAS 2 if occu=413109 then occ
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Summary Statistics of All Questionn
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SUMMARY STATS FROM THE DEMOGRAPHIC
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SUMMARY STATS FROM THE INVENTORY RE
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SUMMARY STATS FROM THE FOOD AND BEV
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SUMMARY STATS FROM THE CLOTHING REC
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SUMMARY STATS FROM THE HOUSING AND
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SUMMARY STATS FROM THE HOUSEHOLD FU
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SUMMARY STATS FROM THE HOUSEHOLD FU
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SUMMARY STATS FROM THE MEDICAL RECO
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SUMMARY STATS FROM THE PRIVATE TRAN
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SUMMARY STATS FROM THE COMMUNICATIO
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SUMMARY STATS FROM THE CSE (OTHER)
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SUMMARY STATS FROM THE HOTEL, COFFE
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SUMMARY STATS FROM THE PERSONAL CAR
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SUMMARY STATS FROM THE WAGE AND SAL
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AVERAGE PERCENT CONTRIBUTION OF SEP
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SUMMARY STATS FROM THE LANDS RECORD
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SUMMARY STATS FROM THE OTHER SOURCE
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SAS Files for Construction of CENVA
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if gov=23 and if gov=25 and if gov=
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proc delete data=work.sort5; run; p
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@7 finlwt @15 males @17 females @19
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options pagesize=60 i libname in 'c
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if occu=832104 then occu=732104; if
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MAKEVARI • SAS 6 or gov=27 or gOV
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