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

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VIII. 5 Average Annual Expenditures on Medical Goods and Services, and Budget Shares of Medical Expenditures, Rural and Urban, by Quintile, for Two HIECS 1990/1991 Overall Quintl Quint2 Quint3 Quint4 Quint5 Rural Mean (£E) 154.47 97.33 134.03 149.36 170.04 221.62 Rural Share (%) 3.22 2.09 2.57 2.90 3.43 5.13 Urban Mean 219.00 152.86 179.10 200.95 256.18 305.97 (£E) Urban Share 4.50 2.59 3.15 3.68 5.08 8.02 (%) 1995/1996 Rural Mean (£E) 208.47 158.93 172.79 190.89 214.97 299.33 Rural Share (%) 3.36 2.38 2.75 3.01 3.35 5.20 Urban Mean 301.71 236.77 261.02 288.02 343.02 376.27 (£E) Urban Share 4.39 3.15 3.52 3.93 4.90 6.38 (%) Budget shares for medical goods and services rise over the quintiles of equivalence-adjusted expenditures. In the rural areas, budget shares have risen over time; in the urban areas, they have declined for the higher quintiles: this is an artifact of constrained supply in rural areas. The urban shares in the highest quintile are quite high, reflecting the high cost of elective medicine and procedures chosen by the richest patients. VIII.B.3 Regressing Medical Expenditures The third type of comparison which might be made over time has to do with the relative effect of household characteristics on household total annual medical expenditures. Table VIII.2 shows the coefficient values for household demographic effects on total medical expenditures for both surveys. These demographics include attributes of the head of the household (age, sex and education), household total expenditure, number of individuals fitting into each of six age/sex categories for children, the number of household members, and the region of the country. The equations are in level £E. Overall the fit of both equations is acceptable given the criterion of experience, and with the application of the usual caveat, that these are not deterministic models. It must also be noted that the 1990/1991 HIECS equation's intercept is not significant at an acceptable level; this could be due to a non-unique merging of the three data sets, because the medical expenditures datafile is missing the variable for PERIOD (the quarter of the year in which the data were collected). Being a male household head is associated with a decrease in medical expenditures, ceteris paribus. After the head reaches a secondary education
VIII. 6 level, additional educational attainment affects medical expenditures negatively. An intuitive interpretation is that additional education serves to keep the household ever healthier. The coefficients on total expenditure suggest that 4 piasters of each additional £E spent by the household will go to medical goods and services - in line with the overall budget shares. An unexpected and significant finding is that additional household members are associated with smaller overall medical expenditures - one additional member will decrease medical expenditures 5.62 £E in 1990/1991 and 12.93 £E in 1995/1996 - this is probably a combination of budget strain and household scale economies. We will see a similar relationship (next section) of household size to per capita medical expenditures. The regions having the lowest expenditures (the numeraire is Cairo) are, expectedly, in Upper Egypt and the Frontier governorates. VIlLC 1995/1996 Household Average and Per Capita Medical Expenditures Regional and household-size breakdowns of per capita expenditures on medical goods and services in the recent survey (Tables VIIl.3 and VIllA) point clearly to differential access based on geography. Per capita expenditures on medical goods and services in the rural areas are only about one-half what they are in urban areas. Not surprisingly, in average terms the regional distribution of medical expenditures parallels the regional distribution of total expenditures (see Table Il.3), and per capita expenditures are similar. The budget shares shown in Table VIlL3 are different from the shares shown above for two reasons: a) they are not equivalence-adjusted, and b) they are formed as a less-biased ratio of sample-summed numerator over sample-summed denominator instead of as an average of household-level ratios (as above). Both average and per capita expenditures for medical goods and services fall over most of the curve as household members increase; there is a point, after ten members, when both curves bend upward. As households grow in size their members receive an ever declining share of medical expenditures. Naturally the standard errors of the estimates in Table VIIlA fall with the number of cases and rise with the number of household members (keeping precise track of many expenditure sources being more complicated). VIlLD Conclusion Admittedly there are a number of extensions 2 to make to the analysis of medical expenditures. A focus on the distribution of insurance payments would serve to broaden the understanding of in-kind payments made to employees, and would inform models correlating illness prevention with incidence. In two other health related surveys in Egypt, the National Household Health Care Utilization and Expenditure Survey, and the linked Provider Survey, the Cairo Demographic Center and the Egyptian Ministry of Health estimated that 70% of the surveyed population was not covered by any 2 Scott Moreland of the Population Project Consortium of Egypt (PPC) suggested these classifications.
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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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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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Page 226 and 227: Figure VI. 1 A Synopsis of Egyptian
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Page 265: VIII. 4 surgical or procedural, ane
Page 269 and 270: Table VIlLI Mean Medical Expenditur
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Page 273 and 274: Bibliography - Chapter VII. Medical
Page 275: IX.A Introduction · IX.2 An offici
Page 278: IX.S and later found that the infor
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Page 285 and 286: The 1995/1996 Household Income, Exp
Page 287 and 288: Guidelines A Survey on Income, Expe
Page 289 and 290: Objectives ofthe survey: 1. Identif
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Page 293 and 294: Survev FORMS A. Auxiliary form (For
Page 295 and 296: Field Work: visit will be before th
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Page 301 and 302: four sub-totals (8-1), (8-2), (8-3)
Page 304 and 305: The editor is the link between the
Page 306 and 307: 7. Confirming that all families in
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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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