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

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The dependent variable is the tth observation on Y in the gth group, II is the overall (or "grand") mean, and E t1c is a stochastic disturbance term. The sum of the G g will equal zero. The regression model is Y tg = 13 1 + 13 2 X t2 + 13 3 X t3 + ... + 13 G X tG + E tg where X tg = 1 if the .observation belongs in the gth group and = 0 otherwIse. (g = 2,3,•..,G) The intercept in the regression model (f3 1 ) will equal II + 01 of the ANOVA model, f3 1 + f3 2 will equal II + 02' etc. Appendix LD Weighting Procedures and Estimation15 Basic Weight The probability of selection of the households in a particular sample shiakha or village is: where: l\ij = probability of selection for the sample households in the j-th sample "chunk" in the i-th sample PSU (shiakha/village) in the hth stratum (governorate, urban/rural) 91= number of sample "chunks" to be selected in the h-th stratum 1.36 l\hi = total population (measure of size) in the 1986 census frame for the i-th sample PSU in the h-th stratum l\h = total population in the 1986 census frame for the h-th stratum qi = total number of "chunks" into which the i-th PSU in the h-th stratum is divided 111tIij = number of in-scope households selected in the j-th sample "chunk" in the i-th sample PSU in the h-th stratum (generally equal to 30, or 15 in the case of the sample for the first 6 months) 15 Excerpted from Megill (1995). total number of housing units in the updated listing for the
j-th sample "chunk" in the i-th sample PSU in the h-th stratum (Due to household listing anomalies) (M hU ) is unknown, and it is not possible to calculate the exact probabilities specu-ied previously. An approximate probability is: where: M bij M bi 1500 :::i 1500 = total number of households in the 1986 census frame for the i-th PSU (shiakha/village) in the h-th stratum Mter substituting these values, the probability of selection reduces to the following expression: Phij The basic sampling weight, or expansion factor, is calculated as the inverse of this probability of selection. Given the probability specified above, the basic weight can be expressed as follows: where: Whij = basic weight for the sample households in the j-th sample "chunk" in the i-th sample PSU in the h-th stratum First Phase Weight Adjustment for Noninterviews The first phase weight adjustment factor can be defined as follows: where: first phase weight adjustment factor for the sample 1.37
Page 1 and 2: The 1995/1996 Household Income, Exp
Page 3 and 4: Project'Background Executive Summar
Page 5 and 6: Chapter I_ Ov'"er"V"ie"" aI1d Proce
Page 11 and 12: 1.11 decreases average household si
Page 13 and 14: 1.13 HIECS as well as international
Page 15: 1.15 respondent acceptance. These a
Page 19 and 20: mothelUs were expected to be more s
Page 22 and 23: 1.22 material. There should be a cl
Page 24 and 25: elied upon, resistance to analytica
Page 26 and 27: in the speed of processing of any s
Page 28 and 29: I.E Global Edits 1.28 In late Novem
Page 30 and 31: Name, Size, and Level of HIECS Raw
Page 32 and 33: mandatory by law; 16) Reporting err
Page 34 and 35: Appendix LA Comparing Estimates fro
Page 40 and 41: where and R = f g' are estimates of
Page 42 and 43: Table 1.1 1995/1996 HIECS Sample Si
Page 44 and 45: Table 1.3 Update Rate ({Sampled-Ori
Page 47 and 48: Table 1.5 Average Annualized Data E
Page 49 and 50: Table I.7 Annualized Error Characte
Page 51 and 52: Table 1.9 One-Way Analysis ofVarian
Page 53 and 54: MI: University of Michigan, 1980. L
Page 55: Sequential List of Tables and Figur
Page 59 and 60: Digit Preference Indices Digit 5 10
Page 61 and 62: proper income variable. There is st
Page 63 and 64: II.10 6.33% of HIECS households sai
Page 65: 11.12 Percentage Changes in Median
Page 68: 11.15 involves the difficulty in de
Page 72: household per capita income did not
Page 75 and 76: Table n.1 Asymptotic Properties ofB
Page 78 and 79: Table 11.2 Household Average Annual
Page 80 and 81: Table II.3 Household Average Annual
Page 82 and 83: Table n.3 Household Average Annual
Page 84 and 85: 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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USAID/EAP, "Findings of the Employm
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sequential List of Tables and Figur
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V.4 To underscore the critical impo
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V.C.2 Implementation of Current Wei
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V.10 telephone calls, in mind. Note
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V.E Dissemination and Publication V
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Appendix V.A An Alternate Estimator
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(19) E (20 ) t I col, a, t = = Eo 1
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Table V.l Comparison of Major Group
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Figure Y.3 Example ofEgypt's Price
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272-278, 1980. Pollak, R.A., "The S
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VI.4 often two or more floors, with
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VI.? notoriously difficult to regul
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VI.II consumption of housing. Assum
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Rent Elasticities VI.18 1990/1991 O
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VI.2! Considering utilities as elec
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Classification of Housing Type and
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VI.2S statistically significant) wi
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VI.27 values) is positive: 587.51 f
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Figure VI. 1 A Synopsis of Egyptian
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Table VI.4 PersonslRoom, by Area, T
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Table VI.5 Average Housing Expendit
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Table VI.6 Ratio ofImputed Value of
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Table VI.7 Comparison ofConsumer Su
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Frankena, Mark, "Alternative Models
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Development in Egypt: Investing in
Page 243:
Page 248 and 249:
VIL7 of age of the household head c
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Two-Way Classification of Attained
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VILli The table above shows that, f
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Table VI!. 1 Estimates ofProportion
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Table VI!.3 Enrollment Ratios (Freq
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Bibliography - Chapter VII. Educati
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VIII. 4 surgical or procedural, ane
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VIII. 6 level, additional education
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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 ,. ,
Page 357 and 358:
January takes code "01" etc. d. Rur
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011100 121101 122103 131102 131103
Page 361 and 362:
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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