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

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V.A Introduction l V.3 One of the stated goals of the technical assistance effort for the 1995/1996 HIECS was a review of the methodology and practice of measuring price inflation in Egypt. As written and agreed upon, the scope of work for the HIECS made it abundantly clear that the mere production of expenditure weights could not be considered the ultimate measure of success in the project. USAID believed that all the effort to produce precise and unbiased estimates for consumers' budgets would come to naught if those estimates were used in a faulty consumer price index. Recognizing that estimates would only be as good as the sum of their parts, awareness of the real variability and misrepresentation of average prices had to inform the very design of the HIECS. On numerous occasions, I approached CAPMAS leadership with the request for component price data and access to the CPI processing staff to research some of the pressing concerns of price measurement: price aggregation patterns and variance, the effect of delaying the use of weights and the representation of the prices themselves, the pricing scheme and standards of data collection, the price instruments, processing problems, etc. Having some experience with the institutional constraints within CAPMAS, and (from more than four years with the US Bureau of Labor Statistics) a background sensitivity to the sources of bias in inflation measurement, my prior attitude was wholesale skepticism. The inflation numbers coming from CAPMAS reflected neither the location nor the scale of the index for the cost of living. The fact that I was not even permitted to research the issues (and thereby, however partly, fulfill the terms of the technical assistance agreement) only served to deepen my cynicism. In early 1997, a number of circumstances brought economic data issues, and specifically the measurement of inflation, to the fore. The data debate renewed when the International Monetary Fund sent a delegation to scrutinize data for decision makers. The CPI representative of the IMF made concise recommendations and pointed to the need to exploit the present circumstances for corrective action. A new openness about data quality, timeliness, representation and access for policy and investment began to characterize the upper echelons of the Egyptian political leadership. Noteworthy was the formation of a ministerial round table devoted to data sharing. Supporting data sources were ready: the processing phase for the census of population neared its maturity, and preliminary estimates for population weights for outlet areas could be produced by May; the expenditure weights from the HIECS were by now stable and known quantities. The time is clearly right for fixing the index, but the real question remains, can CAPMAS do it? Building a high-quality CPI index is an extremely complex undertaking under any circumstances. There is a snowball effect to correction; once parts of the price collection method or the aggregation scheme are properly adjusted, the estimates are changed in small but extremely important ways, so that the final outcome is often a matter not of scientific rigor but of political or administrative feasibility. Perhaps another way to phrase the question is: has CAPMAS delayed correction for too long? 1 This chapter owes much to the conversations I had with the IMP's Mission representative for the price index, John Sungren.
V.4 To underscore the critical importance of measuring inflation properly, we ask one simple question: "Have expenditures (incomes, or wages) increased or decreased in the 1990s?" Redrawing the table from Chapter II, it is clear that the answer depends on the CPr. Percentage Changes in Median Expenditures, Incomes, and Wages, 1990/1991 1995/1996 Estimate for Average Household 1990/1991 - 1995/1996 % Increase (+ or -) Median Expenditures, Unadjusted + 27.61% Median Expenditures, Adjusted by All-items CPI and Equivalence - 30.03% Median Incomes, Unadjusted + 39.23% Median Incomes, Adjusted by All-items CPI, and Equivalence - 23.80% Median Wages & Salaries, Unadjusted + 40.39% Median Wages & Salaries, Adjusted by All-items cpr - 22.19% Female Median Wages, Unadjusted + 52.29% Female Median Wages, Adjusted by All-items CPI - 15.99% Male Median Wages, Unadjusted + 38.88% Male Median Wages, Adjusted by All-items CPI - 23.17% The drastic declines shown in real incomes and expenditures between the two survey periods are dependent on the official (mis)measurement of inflation. Poverty results over time (the Foster Greer Thorbecke indices of Chater III), as well as wages adjusted for the qualities of human capital (Chapter IV), are similarly sensitive to the way the nominal value of money is deflated to account for price increases. It is difficult to state when, and how, the measurement of inflation diverged from actual price changes. The official cpr produced by CAPMAS probably overstated inflation for the first three years of the decade, and then subsequently began to understate it, to the point of the current, absuredly low, rates. In terms of policy prescriptions, the degree and the mechanism of the bias itself is less important than the de facto mismeasurement. V.B The Cost of Living and Measurement The theoretical relation between a price index and the true cost of living should introduce a discussion of the measurement of the cost of living. CAPMAS uses a Laspeyres-type estimator as Egypt's Consumer Price Index
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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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Page 126 and 127: Table II!. 1 Poverty Rate Rankings
Page 128 and 129: Table III.3a Poverty Rate Rankings
Page 130 and 131: Table III.3c Poverty Rate Rankings
Page 132 and 133: 'able III.5 Poverty Rate Rankings b
Page 134 and 135: "able It!. 7a Poverty Rate Rankings
Page 136 and 137: Bibliography - Chapter III. Poverty
Page 138 and 139: 179, 1993. Rodgers, John L., and Jo
Page 140 and 141: Sequential List of Tables and Figur
Page 143 and 144: IV.S The unemployed are further cla
Page 146 and 147: IV.8 did not permit even a good est
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Page 166: Table IV.4 Wage Regression Results
Page 169 and 170: USAID/EAP, "Findings of the Employm
Page 171: sequential List of Tables and Figur
Page 176: V.C.2 Implementation of Current Wei
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
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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 214: Rent Elasticities VI.18 1990/1991 O
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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
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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 ,. ,
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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
show all

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