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A FOOD DEMAND ANALYSIS FOR EGYPT
Anna Conte∗
JEL Classification: C42, D1, I3, Q11, R2 Keywords: survey data analysis, household behavior and family economics,
welfare and poverty, aggregate demand analysis, prices, house-hold analysis
1. Introduction Egypt is a country of North-East Africa, known all over the world for
Pyramids and all the other monuments that reflect its prodigious ancient his-tory.
However, it is also known to development economists for its evident prob-lems of undernutrition, illiteracy of the population and lack of infrastructures, among the others, that seriously undermine bases for a solid development process.
In this paper, cross-sectional data from Egyptian households are used to estimate a food demand system. Such a system provides useful information and parameters to be used for simulating outcomes of alternative reforms, in order to evaluate the economic, political and technical feasibility of policies targeted to improving the welfare of the poor, reducing infant mortality and malnutrition and promoting social equity. In particular words, a food demand analysis with its purpose to estimate income elasticities, own-price elasticities and cross-price elasticities of the most important food aggregates is required to understand the paths a public policy reform should undertake to induce people to direct their consumption targets towards those foods whose nutri-ents are low and necessary in their diet, increasing their welfare.
The work is organized as follows: in section 1, you can find a description of the conceptual framework of this work; in section 2, there is a brief de-scription of data used for the analysis; in section 3, it is outlined the structure of Egyptian population and household composition, followed by a detailed derivation of equivalence scales according to the Rothbarth model; section 4 briefly delineates the theoretical model and the econometric instruments used to estimate the Egyptian food demand system and the main results from the ∗ Luiss Guido Carli, Tor Vergata University and Food and Agriculture Organization of the United Nations. E-mail address: [email protected] author wants to thank Andre Croppenstedt for his friendship and his kind and patient su-pervision of this work and also Randy Stringer and Fabrizio Bresciani for their constructive suggestions and critiques.
207
estimation of that system; section 5 outlines the analysis of per capita intakes for calories.
2. Conceptual framework Demand analyses based on cross-sectional data usually assume that prices
are constant. That assumption allows to easily estimate Engel functions and consequently food demand own-price and cross-price elasticities.
When a survey only contains information on both expenditure and quan-tity consumed of a certain food, a measure of prices can be obtained by divid-ing expenditure by quantity. Such a ratio is called “unit value” and, unlike market price, it reflects the household’s choice of food quality. In other words, unit values contain choices among foods of the same kind but differ-ing in characteristics or quality levels. For this reason, unit values are not constant across households and induce biased estimates of own-price and cross-price elasticities, if used as proxies for market prices1.
The most common approach to handle such a problem is Deaton’s2. It modifies the well-known Almost Ideal Demand System (AIDS) model3 in order to take into account estimation bias due to quality effects.
We will follow this approach.
3. Data source The Egypt Integrated Household Survey (EIS) 19974 collects detailed in-
formation on the quantity and expenditure of several foods consumed by a sample of households in Egypt. The data set also contains a plenty of infor-mation about the socio-demographic and economic characteristics of Egyp-tian households. Accordingly, it includes all the information necessary for analyzing household food consumption patterns in Egypt. It is targeted to provide policy makers with instruments for short-run and long-run reforms, mainly aimed to reduce poverty and improve welfare.
The EIS sample includes 2,500 households, selected according a classical two-stage design5. Such a sample selection was designed to produce a self-
1 Details can be found in A. Deaton (2000). 2 A. Deaton (2000). 3 See A. Deaton and J. Muellbauer (1980b) and A. Deaton (2000). 4 The Egypt Integrated Household Survey (EIS) 1997 is provided by International Food Policy Research Institute (IFPRI) in collaboration with Ministry of Agriculture and Lnd Reclamation and with Ministry of Trade and Supply. 5 In the first stage, primary sampling units are randomly selected in each strata with probability proportional to the number of households contained. In the second stage, a given number of households is randomly selected from each primary sampling units. This way, each household has the same probability to be selected and participate the survey. See, for example, A. Deaton (2000).
208
weighting sample, representative of the household population in 20 Egyptian governorates. The survey scheme included 5 strata (1 = metropolitan area, 2 = lower urban area, 3 = lower rural area, 4 = upper urban area, 5 = upper rural area) and 125 primary sampling units.
Among the 2,500 households participating in the survey only 1,875 (75%) completed the consumption part of the questionnaire. Those households were asked to report quantities and expenditures for 121 foods consumed during the 7 days preceding the interview. For each food item, households are also asked to report the total quantity consumed and the total expenditure divided into three categories: purchased; grown by themselves; received from other sources6. For a full description see appendix 1.
Some of the observations presented missing values. Sometimes, quantities were reported but not expenditures or vice versa. Sometimes, quantities were expressed into “number of items consumed” instead of kilograms or another units with a certain exchanging rate with kilograms. Such a situation required to convert all quantities into the same units and to replace missing quantities and expenditures.
In those cases, we first converted into kilograms quantities expressed in other units (ton, quintal, gram, pound ounce, litre and millilitre) according to standard conversion tables. Secondarily, we replaced quantities in items and missing quantities with ones computed by diving each household’s expendi-ture for a certain food with its “mean unit value per kilogram”. This “mean unit value per kilogram” was obtained by first computing unit values only for those households reporting quantities in kilograms, then averaging them within primary sampling units; when this procedure produced no result, we calculated these mean unit values averaging within governorates; rarely, we also needed nationwide averages. Finally, we replaced missing expenditures with ones evaluated by multiplying quantities with the so-obtained “mean unit values for kilograms”7.
After imputation, we aggregated foods into 8 groups8: bread and cereals (cer), pulses (pul), eggs and milk products (dai), cooking oils (oil), vegeta-bles, fruits and nuts (vef), fish and meat (fem), spices (spi), sweets and drinks (sed)9. Appendix 1 and 2 present detailed summary statistics for the entire list of food contained in each category.
6 For the last two categories total expenditure is just an estimate of the expenditure would have occurred at market prices. 7 The unit value is treated as missing, if a household did not consume a certain foods. 8 We aggregated according to the weight in terms of expenditure each of the component of a certain food group has in the total expenditure for that food group. 9 Nof indicates the group of non-food goods.
209
4. Structure of the population and equivalence scales Decision about consumption are clearly influenced by the composition of
the household, their geographical location and their educational level. These are all variables that need to be taken into account in a food demand analysis. For this reason, this section is dedicated to their description.
4.1. Population pyramids The first and very explicative step in this purpose is the construction of
population pyramids for Egypt. Table 1 shows the estimated density at each age level of the population as a whole (top) and of the urban (central) and rural (bottom) subpopulation as proportion of total Egyptian population. The x-axis of Table 1 shows the estimated density of the population whilst the y-axis shows different age levels. The higher up the y-axis the older the popula-tion. The left half of the pyramids show age distribution of the male popula-tion and the right half the female distribution.
These pyramids show not to have a peculiar structure, but common to most developing countries. The wide base of the pyramids indicate that a large proportion of the population is young. In effect, the population is mainly composed of people aged (0-40). This is an indicator of a high birth rate in rural areas as well as in urban.
The narrow tops indicate a small proportion of the population is old im-plying a high death rate, especially in rural areas. Men are more than women at birth, but they show a higher mortality after 40. On women side, there is a clear evidence of a high mortality rate in fertility age, but women’s survival rate after 40 clearly appear to be higher than men’s. Comparing urban and rural pyramids shows a much higher mortality rate after 40 in rural areas, even if female population appear to have a high mortality in fertility age even in urban population.
4.2. Household composition It is not uncommon that an Egyptian household is composed of several
families. In our sample, the number of family nuclei per household varies from 0 to 4, with the highest average number of member per household in rural areas (strata 3 and 5).
Table 2 presents the mean composition of Egyptian households per strata and number of family nuclei in the household (denoted by “head”). As ex-pected, households in rural areas contain, on average, the highest number of children, grandchildren, parents and relatives.
210
4.3. Equivalence scales Children’s and adolescents’ needs are different from adults’. Nobody
could maintain that a family composed of two adults and two kids is, ceteris paribus, equal to one composed of four adults! Thus, it is necessary to find an age-based weight for each of the young components of a household.
Equivalence scales are just index numbers that measure the cost of a child for a household in terms of adult equivalent. Several models deriving equiva-lence scales can be found in the literature10. The most commonly used are Engel and Rothbarth models11.
We derived equivalence scales by Rothbarth’s procedure, because its re-sults are not substantially different from the ones obtained by Engel’s method but are more robust12.
Rothbarth model for equivalence scales is based on the idea that the pres-ence of children in a household affects, actually lowers, adults’ welfare and in particular their consumption of “adult goods”.
Rothbarth’s procedure is composed of 4 steps. The first step requires iden-tifying those adults good among several non-food commodity groups. We constructed the 7 commodity groups listed in Table 5. Labeling a non-food commodity group as an adult good required to construct a system of equa-tions, where the dependent variables, household’s expenditures for each of the considered commodity groups, were regressed on the number of children in the age brackets [0-5], [6-10] and [10-14], conditional on the sum of the coefficients on expenditure level for non food-commodity groups being equal to 1. Those age brackets are respectively indicated as LB, MB and HB. In the Rothbarth model, a commodity group can be labeled as a adult good when we cannot reject the null hypothesis that the coefficients on the bracketed ages are jointly not significantly different from 0, according to the F-test reported in Table 5.
10 See, for example, Barten (1964), Visaria (1987) and Price and Houthakker (1971). 11 See, for example, Tsakloglou, P. (1991).12 Results obtained by Engel method are available upon request.
211
Tab. 1
010
2030
4050
6070
8090
100
age
.0125 .01 .0075 .0075 .01 .0125percent of total population
males females
Estimated Egyptian male and female population by age, 1997
010
2030
4050
6070
8090
100
age
.0125 .01 .0075 .0075 .01 .0125percent of total population
males females
Estimated Egyptian urban population by age, 1997
010
2030
4050
6070
8090
100
age
.0125 .01 .0075 .0075 .01 .0125percent of total population
males females
Estimated Egyptian rural population by age, 1997
212
Tab. 2 average number of members per strata distributed by the number of family heads household
strata head 1 2 3 4 5 Total 0 3.600 4.250 6.500 4.167 7.200 4.750 1 4.809 4.835 6.307 5.100 6.938 5.854 2 4.000 0.000 8.000 7.000 5.000 6.667 3 0.000 6.000 0.000 0.000 0.000 6.000 4 0.000 0.000 0.000 0.000 5.000 5.000 Total 4.759 4.832 6.316 5.090 6.934 5.840
average number of children per strata distributed by the number of family heads household strata head 1 2 3 4 5 Total 0 2.067 2.000 2.000 2.333 4.400 2.417 1 2.634 2.593 3.091 2.703 3.472 2.994 2 2.000 0.000 3.000 0.000 3.000 2.333 3 0.000 2.000 0.000 0.000 0.000 2.000 4 0.000 0.000 0.000 0.000 0.000 0.000 Total 2.610 2.586 3.081 2.690 3.473 2.983
average number of grandchildren per strata distributed by the number of family heads household strata head 1 2 3 4 5 Total 0 0.000 0.500 0.167 0.333 0.000 0.139 1 0.100 0.122 0.593 0.197 0.455 0.351 2 0.000 0.000 1.667 0.000 0.000 0.833 3 0.000 0.000 0.000 0.000 0.000 0.000 4 0.000 0.000 0.000 0.000 0.000 0.000 Total 0.095 0.126 0.594 0.199 0.451 0.349
average number of parents per strata distributed by the number of family heads household strata head 1 2 3 4 5 Total 0 0.067 0.000 1.000 0.000 0.200 0.222 1 0.066 0.087 0.185 0.108 0.262 0.162 2 0.000 0.000 0.333 1.000 0.000 0.333 3 0.000 0.000 0.000 0.000 0.000 0.000 4 0.000 0.000 0.000 0.000 0.000 0.000 Total 0.066 0.086 0.193 0.109 0.261 0.163
average number of other relatives per strata distributed by the number of family heads household strata head 1 2 3 4 5 Total 0 0.333 0.500 2.000 0.000 1.000 0.667 1 0.158 0.214 0.633 0.276 0.887 0.515 2 0.000 0.000 0.667 4.000 0.000 1.000 3 0.000 0.000 0.000 0.000 0.000 0.000 4 0.000 0.000 0.000 0.000 0.000 0.000 Total 0.164 0.217 0.646 0.281 0.885 0.518
average number of other relatives per strata distributed by the number of family heads household strata head 1 2 3 4 5 Total 0 0.000 0.000 0.000 0.333 0.000 0.056 1 0.000 0.008 0.004 0.003 0.003 0.004 2 0.000 0.000 0.000 0.000 0.000 0.000 3 0.000 0.000 0.000 0.000 0.000 0.000 4 0.000 0.000 0.000 0.000 0.000 0.000 Total 0.000 0.008 0.004 0.008 0.003 0.004
213
Tab. 3
schooling
00.050.1
0.150.2
0.250.3
0.350.4
0.45
0 5 10 15 20 25
number of years
perc
enta
ge o
f tot
al
popu
latio
n
total_populat ion urban rural
schooling: urban population
0
0.05
0.1
0 5 10 15 20 25
number of years
perc
enta
ge o
f ur 0.15
0.3
on
0.2
0.25
ban
popu
lati
schooling: rural population
00.050.1
0.150.2
0.250.3
0.350.4
0.450.5
0 5 10 15 20 25number of years
perc
enta
ge o
f rur
al p
opul
atio
n
214
The second step consisted of constructing the adult goods share, that is the xpenditures for ad oods old ex
ressed the so- ed a goods are oso other d phica variab
ssion I we can reject the null hypothesis that co ficient are significantly different one from other t 5%.
to choose it as reference regression deriv g Egyp equivalence scales, think that we made in the last step14
Tab. 4
Summary statistics of main variables used for Rothbarth model
proportion of e ult g over the househ total pendi-tures.
For the third step we reg obtain dult sh n the bracketed ages and al emographic and geogra l les13. Only in regre ef s onbracketed ages each a Thisresult suggested for in tian
.
Variable Obs Mean Std. dev. Min Max
M thly total expenditure 2472 8350.83 13437.11 67.61 297761.60
Food share 2472 0.11 0.11 0.00 1.00
T expenditure in non-food commodities (Xa) 2472 555.80 429.39 0 4829.20
M thly expenditure in adult goods (X) 2472 511.85 406.29 0 4778.95
LB = children aged [0-4] 2 0.64 0.90 0 6.00
M children aged [5-9] 245 0.72 1.29 0 10.00
HB = children aged [10-14] 0 9.00
997 Egyptian Pound
on
otal
on
453
3 B =
2453 0.77 0.96
In 1
everal different bracketed ages. Our final
sures of goodness of fit, test of statistical difference among e estimated coefficients on the different bracketed ages and of the joint significance
f those coefficients. All the results are upon request. 14 To calculate the adult equivalent of a ch rtain bracketed age, it is sufficient to cal-
late the opposite of the ratio between the estimated coefficient on that bracketed age over the estimated coefficient on th l and to multiply the so-obtained numb
13 the same procedure for s We followed meachoice was based on
tho available
ild in a cecu
e logarithm of X, to take its exponentiaer by 2.
215
Tab. 5
System of equations for expenditure on n y groups on-food commodit
non-food commo ps Intercept ult LB MB R2 F-statistic dity grou Xad HB
alcool, tobacco, adul nf, mix exp
-23.959 (7.580)
7
5.26(3.293)
-2.351 (2.344)
7(3 0.871 2.588
meals out 10.854 (3.662)
9
-1.5(1.041)
-0.005 (0.723)
-(1 0.091 0.731
fuel, transports 9.244 (1.672)
8 2)
-0.9(0.8
0.444 (0.578)
4(0 0.235 9.571*
medical care . .
0.051 0.003)
-0.779 (
1.738 38 1.970
infrequent expenditures . .
0.066 (0.005)
-3.398 (2.139)
0.357 (1.533)
-4.(2.082) 0.137 2.180
household dwelling . .
0.008 1)
0.261 (0.4
-0.573 (0.327)
0.284 (0 0.567 1.257
charity 4.243 0.061 1.151 0.395 -4.333 0.145 1.983
*null hypothesis reje
systems of equations by seemingly unrelated regression (SURE) constrai : coefficients on Xadult sum to 1 standar errors in parentheses
tcloths, oth 0.76(0.008)
0
.200
.512)
0.01(0.003)
37
0.041 .024)
0.02(0.00
69 23)
.250
.822)
( 1.547) (1.124) -3.2(1.501) 0.221
137
(0.00 62) .461)
(7.8210 (0.005) (1.868) (1.305) (1.854)
cted at the 5% significance level
ntd
Tab. 6
Engel curves for the budget share of adult goods
adult good share I II III
_cons 0.616 (0.015)
0.611 0.638 (0.019) (0.026)
log(X) -0.060 (0.002)
-0.058 .002)
-0.057 (0.002)
LB 0.007 (0.002)
6 (0.002)
0.005 (0.002)
MB (0.0 (0.2 1)
HB 0.009 (0
0.007 (
0.007 )
+ other variables
+ other variables and governorate dum-
mies
(0
0.00
0.003 0.003 0.0001) 001) (0.00
.002) 0.002) (0.002
R2 0.4839 0.5282 0.5472
only in regression I coefficients on bracketed ages are significantly different at 5% standard errors in parentheses
216
217
henomenon, common to both urban and rural pop
Implied equivalence scales for the cost of a child (regression I)
Table 7 shows a u-shaped structure of weights that has many different ex-planations. One can think, for example, that children play an important role in their first years, when the mortality rate is high, then their care is delegate to educational structures during basic instruction, finally their burden grows after primary instruction, when the most part of children leaves schools to enter the job market (this p
ulation, can be observed in table 3.
Tab. 7
LB MB HB
weight 0.238 0.114 0.313
e
(primary
)uf()pln(z)xln(w 0GicGc
1HHcGHic
0Gic
0G
0GGic +++++= ∑
=
θγβα (5.1)
and the unit value equation
1Gic
N
1HHcGHic
1Gic
1G
1GGic u)pln(z)xln()vln( ++++= ∑
=
ψγβα , (5.2)
5. The Egyptian food demand system To solve the problem of the bias induced by using unit valu s instead of
market prices in our demand equation system for Egypt, we make use of Deaton’s methodology, developed in a series of papers (Deaton, 1987a, 1987b, 1988, 1990) an summarized in a well-known book (Deaton, d 2000).
He makes use of spatial variation in unit values to estimate own-price and cross-price-elasticities. It is based on the assumption that quality effects are reflected in deviations of unit values from their geographical cluster means
sampling unit level averages of unit values per food group). Such that, quality effects can be filtered out of unit values by regressing cluster demeaned unit values on households’ characteristics. Further information about quality effects are obtained from the covariance of residuals of that re-gression and the regression of expenditure share on total expenditure and households’ characteristics.
Then, Deaton’s methodology requires a system of two equations, both
functions of unobserved market prices Hcp , the budget share equation
N
where indexes food groups, households and cluster, that is primary sampling units15 or segment. Among the explanator variables, is house-hold ’s total expenditure (used as a proxy for total income), is a vector of household’s characteristics (a full description of in appendix 2), is a cluster fixed effect in the budget share.
Table 8 show onal) and cross-price elasticities. Standard errors, in parentheses, ar ed by 1000 boot-strap simulations. All the own-price elasticities are negative.
Demand for cereals and bread (cer) is relatively more elastic than for the other food g p h act that it includes subsidized bread16 that is sold to the population at a veryare significant at 5%, except for fish and meat (fem) group. This can be due to the fact that the distribution u values as for the food group fem as well as for both fish and m i
In Table 9, you can find the vector of income elasticities. These are all negative and significant at 5%, except for the fish and meat group that has contrari tes that all foods are considered infe-rior goo e r a al goods.
G i cy ix
i izvariables used can be found
Gcfs the matrix of own-price (principal
e o dbta
iagin
rou s. T is may reflect the f low price. All cross-price elasticities
of im
no
it daleat s b .
ly a positive sign. ds,
T an
hisd
fame
ct at
deth
noat exc pt fo fish re regarded as norm
15 As data are colle d o lu s ou o (p ary m g n , households in the same cluster live in close geographical proximity. So, they are m likely con-fronted with similar market prices. 16 Called “baladi bread”.
cte n c ster of h seh lds rim sa plin u its)ore
218
219
Tab. 8 ce (principal diagonal) and cross-price elasticities estimates Own-pri
cer pul dai oil vef fem spi sed nof
cer 0.044 (0.169)
0.086 (0.127)
-0.165 (0.211)
-0.491 (0.189)
-0.026 (0.072)
-0.188 (0.140)
0.667 (0.180)
-1.834 (0.283)
0.303 (0.110)
pul 0.374 (0.182)
-0.087 . )
-0.088 (0.221)
-0.101 (0.387)
0.057 (0.069)
-0.076 (0.176)
-0.019 (0.268)
0.730 (0.278)
-1.064 (0.188) (0 137
dai -0.923 (0.215)
0.187 .119)
0.045 68)
-0.988 7)
0.033 4)
0.094 3)
0.210 (0.162)
0.049 (0.221)
0.190 (0.093) (0 (0.1 (0.34 (0.05 (0.13
oil 0.241 (0.154)
.621 .151)
0.050 (0.172)
-0.402 (0.282)
0.047 (0.047)
0.030 (0.126)
-0.087 (0.154)
0.122 (0.217)
-0.073 (0.092)
-0(0
vef 0.028 (0.134)
. 7
.108) -0.261 (0.361)
0.548 (0.432)
-0.073 (0.061)
-0.110 (0.122)
-0.330 (0.
-0.219 (0.217)
-0.061 (0.094)
0(0
02145)
fem -0.462 (0.160)
.148 .100)
0.307 (0 7)
-0.961 (0 9)
-0.119 (0 )
-0.209 (0. )
0.(0.
-0.304 (0.114)
-0.032 (0.091)
-0(0 .24 .14 .042 089
362 080)
spi 0.348 (0.532)
0.388 (0.354
1 )
)
1.243 (0.611)
-0.315 (0.928)
0.336 (0.350) )
-0(0.
.83755
)
-2.(0.
555895
-0.(0.
595178
-0.(0.
040349)
sed 0.136 (0.188)
0.043 (0.137)
3(0 0)
(0 3)
(0
(0
0.710 (0.190)
-0.345 (0.261)
-0.042 (0.127)
-0.16.21
-0.632.27
-0.007.050)
-1.457.228)
nof -0.029 (0.027)
0.021 (0.020)
0.087 (0.031)
-0.135 (0.031)
-0.019 (0.011)
-0.078 (0.023)
-0.532 (0.017)
-0.128 (0.037)
0.024 (0.023)
Standard error tions and reported in parentheses s are obtained by 1000 bootstrap simula
Tab. 9
Income elasticities
food group
cer -0.01806913 (0.0095788)
pul -0.01925758 (0.0050072)
dai -0.00434421 (0.0021477)
oil -0.007427 (0.0029844)
vef -0.01434223 (0.0061113)
fem 0.01608837 (0.0819998)
spi -0.00167314 (0.0002136)
sed -0.0043489 (0.0001045)
Standard errors in parentheses
er, cross-sectional data from Egyptian households are used to esti-ma
ies targeted to improving the welfare of the poor, reducing infant mortality and malnutrition and promoting social equity. Such a food demand analysis allows to understand the paths a public policy reform should undertake to induce people to direct their consumption targets towards those foods whose nutrients are low and necessary in their diet, increasing their welfare.
6. Conclusions In this papte a food demand system. Such a system provides useful information and pa-
rameters to be used for simulating outcomes of alternative reforms, in order to evaluate the economic, political and technical feasibility of polic
220
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ch t Dev pme o ofor the W rld nk.
oping trie : less s fro if yea of th Living Standards Measurement Study, W hin on, D . Th o an vol. 1 pp. 9 3
PRA , S.J HO HA E .S. 971) he A ys f F ily B getsCambridge, Ca
TSAKbridge Un
OG OU, (19 “ ma n an omp o tw imp models of eq vale ce sc es fo hildr ”, E om ou l, v 101pp. 343- 7.
V IA, . (19 ), “S d enti s in n trition s in ural rea ofGujarat ate: n in im r uj t Ins ute ng, working paper n. 7, Ahmedabad, India: Gujarat Institute of Area Planning.
221
APPENDIX 1 market home ctio othe ces produ n r sourgrains and
cereals Obs Mean Std. Std. Std. Dev. Obs Mean Dev. Obs Mean Dev.
quantity wheat 279 10.91 11.90 181 15.78 14.37 13 9.54 13.67 Sorgum flour 18 8.22 8.93 3 21.67 4.93 1 0.25 . Maize flour 390 8.09 9.59 166 11.21 11.47 10 8.70 4.57 Other cerals 2 1.25 1.06 0 0 Wheat(free m
flour arket) 504 7.94 11.05 10 8.25 7.70 2 0.25 0.00
Wheat flour ized) (subsid 599 15.42 11.76 4 18.38 10.83 3 8.00 5.29
Other flour 67 4.15 6.01 4 9.75 3.10 1 3.00 . Rice 2 122 12.54 12.48 37 096 3.81 3.64 5.15 8.61 Macaroni 1467 1.68 1.23 2 3.00 2.83 16 2.38 2.80 Ferik 54 0.74 0.64 6 0.88 0.21 4 0.56 0.31 Other cereal products 256 3.27 0.99 1.45 0 9 1.84
Other bread 22 7.40 6.44 41 1.18 1.13 5 0.59 0.40 Fino bread 809 1.87 1.47 0 2 1.28 0.00 Shami bread 45 1.15 1.10 0 1 0.92 . White baladi read 119 5.78 6.31 0 2 9.75 4.60 b
Baladi bread(dark) 54 0.64 6 21 4 0.31 0.74 0.88 0. 0.56
expenditure wheat 279 11.12 13.12 06 15.81 13 4.36 2.99 181 15.Sorgum flour 7.37 8.19 16.27 5.00 0.75 18 3 1 . M 390 7.09 8.29 166 9.33 9.35 10 5.96 3.79 aize flour Other cerals 2 1.63 0.53 0 0 Wheat flour
ket) (free mar 504 7.32 9.57 10 8.47 7.73 2 0.38 0.04
Wheat flour ed) (subsidiz 599 9.83 7.74 4 8.85 4.26 3 4.80 2.69
Other flour 11.05 3.41 67 4.41 4.47 4 1 4.00 . Rice 2096 5.05 4.48 122 15.11 13.88 10.68 37 6.34 Macaroni 1467 2.81 2.06 2 2.43 1.17 16 3.61 4.35 Ferik 54 1.72 1.39 6 2.29 1.03 4 1.44 0.88 Other cereaproducts
l 8. 15.81 256 3.97 4.78 0 9 28
Other bread 41 3.44 2.66 22 14.32 11.47 5 2.10 1.43 Fino bread 809 3.23 2.53 0 2 2.00 0.00 Shami bread 1. 45 2.45 2.07 0 1 00 . White baladi bread 119 4.65 4.62 0 2 8.75 1.77
Balad(dark)
i bread 54 1.72 1.39 6 2.29 1.03 4 1.44 0.88
222
price wheat 279 1.05 0.36 181 0.95 0.53 13 0.80 0.37 Sorgum r 1.21 0.58 0.76 0.18 3.00 flou 18 3 1 . Maize flour 390 0.89 0.26 166 1.05 1.31 10 0.71 0.25 Other cerals 2 1.75 1.06 0 0 Wheat flo(free ma
ur rket) 504 1.22 0.48 10 1.16 0.32 2 1.50 0.14
Wheat flo(subsidiz
ur ed) 0.55 0.20 0.19 599 0.67 0.19 4 3 0.68
Other flour 67 1.49 0.67 4 1.14 0.19 1 1.33 . Rice 2096 1.39 0.20 122 1.25 0.26 37 1.91 3.74 Macaroni 1.73 0.46 1467 1.70 0.37 2 1.13 0.67 16 Ferik 54 2.63 1.20 6 2.61 0.86 4 2.50 0.71 Other cereal products 256 4.62 1.95 0 9 5.19 1.77
Other bread 41 3.28 1.17 22 2.18 0.71 5 3.57 0.00 Fino bread 809 1. 0.00 1.80 0.63 0 2 56Shami bread 45 2.62 1.60 0 1 1.09 . White baladi bread 119 1.09 0.69 0 2 0.96 0.27
Baladi bread (dark) 54 2.63 1.20 6 2.61 0.86 4 2.50 0.71
market home production other sources
Obs Mean Std. Dev. Obs Mean Std. Dev. Obs Mean Std. Dev.
quantity dairy prod-ucts and
eggs
Other cheese 554 1.05 0.83 108 2.74 2.40 20 0.83 0.51 Cheese (old) 340 0.71 0.79 134 0.53 0.31 1.18 2.23 29 Cheese (rumi) 2 0. 65 0.35 0.22 0 1 50 . Cheese (white) 1235 0.72 0.57 95 1.63 1.07 31 0.81 0.56 Yogurt 430 0.95 0.80 7 1.43 0.69 0 Other milk product 4 4.22 1.65 1 3.00 . 0 Sour milk 42 1.78 1.56 74 3.71 4.82 21 1.43 0.88 Cream 49 0.67 0.57 102 0.96 0.82 23 0.60 0.35 Baby milk 46 0.97 1.27 0 0 Condensed nd concen-
trated milk 5 2.80 1.25 0 2 2.75 1.06 a
milk 1190 3.33 2.27 298 5.82 4.61 78 2.38 1.74 eggs 1492 1.03 0.69 624 1.13 0.82 28 1.09 1.68
223
expenditure dairy prod-ucts and
eggs
Other cheese 8 4 5 1.81 1.17 554 2.72 2.01 10 4.6 3.8 20Cheese
7 (old) 340 2.2 2.28 134 2.90 2.70 29 1.88 1.38 Cheese (rumi) 265 0 2 5.3 3.5 0 1 8 0 .0 . Cheese(white)
1235 0 5 7 7 4.0 2.9 95 4.9 3.6 31 2.79 1.73
Yogurt 430 8 1 1 2.7 2.3 7 3.29 1.9 0 Other mproduct
ilk 4 3.16 1.24 1 2.25 . 0
Sour milk 7 2 42 1.8 1.6 74 3.73 4.81 21 1.62 1.22 Cream 49 5.61 4.39 102 7.18 4.69 23 5.30 3.34 Baby milk 6 8 8 0 4 5.9 4.7 0 Condensed a
nd concen-
milktrated 5 4.97 2.23 0 2 3 5 .7 0.35 milk 1190 6 9 5.4 3.6 298 7.65 5.99 78 3.12 2.19 eggs 1492 4 7 3.7 2.6 624 3.64 2.75 28 3.63 5.60
price dairy prod-ucts and
eggs
Other cheese 554 3.02 2.37 108 1.82 0.50 20 2.27 0.67 Chees(old)
e 6 8 4 340 4.0 3.0 13 3.56 2.63 29 4.43 3.10
Cheese (rumi) 265 5 0 1 16.00 15.5 4.0 0 . Cheese ( 235 1 8 4.35 2.73 white) 1 6.36 2.65 95 3.3 1.4 31Yogurt 5 9 430 3.0 0.7 7 2.37 0.93 0 Other milk product 4 0.75 0 0.0 1 0.75 . 0 Sour milk 42 0 9 4 1.2 0.6 74 1.17 0.6 21 1.27 0.85 Cream 49 0 6 2 2 9.4 3.6 10 8.37 2.8 23 9.09 3.37 Baby milk 0 0 46 10.53 6.15 Condensed
cen-k 5 1.80 0.23 0 1.50 0.71
and contrated mil 2 milk 1190 7 3 8 1.6 0.4 29 1.41 0.60 78 1.36 0.37 eggs 1492 3.64 0.61 624 3.27 0.93 28 3.26 0.62
224
market home production other sources
Obs Mean Std. Dev. Obs Mean Std. Dev. Obs Mean Std. Dev.
quantity pulses
Full 2029 1.08 0.87 38 1.56 0.98 12 1.21 1.33 Taamaya 1686 4.70 16.42 11 0.98 0.61 10 0.66 0.77 Lentils 1178 0.74 0.85 0 6 0.54 0.49 Chicpeas 1.00 67 0.52 0.37 1 . 0 Helba 459 0.39 0.32 0 6 0.52 0.73 Kidney
beans 556 0.68 0.63 1 0.25 . 3 0.83 0.29 Black eyed
0 0.46
0 0.35
0 0.18 peas 389 .58 2 .75 2 .38Otpulses
her 55 1.14 1.10 1 3.00 0
expenditure pulses
Full 2029 2 2.40 1.83 38 3.14 .16 12 1.15 0.63 Taamaya 1686 2.47 1.99 11 2.47 1.34 10 1.34 1.71 Lentils 1178 2.04 1.96 0 6 1.29 0.91 Chicpeas 67 1.61 1.03 1 00 . 0 2.Helba 4 0.82 0.64 0.83 0.58 59 0 6 Kidbeans
ney 556 2.04 1.47 1 0.75 . 3 2.83 0.76
Black eyed peas 389 1.83 1.19
2 2.13 1.24
2 1 .45 0.78
Other pulses 55 1.46 1.14 1 1 .50 . 0
price pulses
Full 2029 2.42 1.01 38 2.24 0.87 12 1.49 0.82 Taamaya 1686 2.06 0.97 11 2.62 0.38 10 1.91 0.15 Lentils 1178 2.80 0.53 0 6 2.58 0.34 Chicpeas 67 3.53 1.64 1 2.00 . 0 Helba 459 2.24 0.88 0 6 2.67 1.75 Kidney beans 556 3.24 0.74 1 3.00 . 3 3.50 0.50 Black eyed peas 389 3.33 0.84
2 2.75 0.35
2 3.80 0.28
Other pulses 55 2.10 2.23 1 0.50 . 0
225
m harket ome production other sources
Obs M O Mean Std. Dev. bs ean Std. Dev. Obs Mean Std. Dev.
quantity Cooking
oils
full 2029 1.08 0.87 38 1.56 0.98 12 1.21 1.33 taam 1 4 16.42 686 .70 11 0.98 0.61 10 0.66 0.77 lent 1 0 0.85 178 .74 0 6 0.54 0.49 chpe 67 0.52 0.37 1 1.00 0 . helb 459 0.39 0.32 0 6 0.52 0.73 beki 5 0 0.63 . 0.29 56 .68 1 0.25 3 0.83
e nditxpe ure Cooking
oils
whea 2029 2.40 1.83 38 3.14 2.16 12 1.15 0.63 sorg 1686 2.47 1.99 11 2.47 1.34 10 1.34 1.71 maiz 1 2 1.96 178 .04 0 6 1.29 0.91 otce 67 1 1.03 .61 1 2.00 . 0 wffm 4 0 0.64 59 .82 0 6 0.83 0.58 wfsu 5 2 1.47 56 .04 1 0.75 . 3 2.83 0.76
price Cooking
oils
whea 2029 2.42 1.01 38 2.24 0.87 12 1.49 0.82 sorg 1686 2.06 0.97 11 2.62 0.38 10 1.91 0.15 maiz 1178 2.80 0.53 0 6 2.58 0.34 otce 67 3 1.64 . .53 1 2.00 0 wffm 459 2 0.88 0 .24 6 2.67 1.75 wfsu 5 3 0.74 1 3.00 . 56 .24 3 3.50 0.50
226
market home pr on other sooducti urces
Obs Mean St Obs M Std. Dev. Obs Std. Dev. d. Dev. ean Mean
quantity vegetables Potatoes 2248 3.43 2.42 14 6.84 4.98 22 3.77 6.09 Onions 2153 1.23 1.00 29 1.41 0.71 17 2.17 5.90 Garlic 1590 0.37 0.42 46 0.45 0 0.29 0.18 .25 29 Tomatoes 4.50 0.71 2261 3.13 2.13 2 16 2.47 1.60 Tomato
r sauce opaste 132 0.50 0.80 1 0.15 . 1 0.50 . Green leafy v 602 1.09 1.03 1 3 0.60 0.36 egetables 1 1.46 1.09 Cabbage 690 1.93 1.72 7 3.10 2.04 11 2.44 1.56 Cauliflowerl 353 0.96 0.55 2 2.50 0.71 6 2.21 3.33 Artichoke 37 0.94 0.63 0 0 Eggplant 313 1.13 0.57 2 0.67 0.47 3 1.00 0.50 Squash 567 1.45 0.97 2 4.00 2.83 7 2.21 1.85 Okra 80 0.59 0.55 5 0.75 0.71 1 0.25 . Mulikiyya 0 0.30 482 0.52 0.45 26 0.55 .38 14 0.53 Green cowpeas 22 0.76 0.60 0 1 0.50 . Green peas 676 1.41 0.79 2 3.00 1.41 8 1.29 0.71 Pepperoni 364 0.56 0.46 0 2 2.25 2.47 Cucumber 768 1.26 0.97 0 6 1.33 0.98 Green beans 124 1.13 0.82 1 2.00 . 0 Carrots 1003 1.50 1.21 0 6 2.04 1.49 Taro 257 1.32 0.81 0 3 1.00 0.87 Other vegetables 3.82 4.26 1.39 127 0.99 1.14 13 7 2.04
e nditxpe ure vegetables Potatoes 2248 2.17 1.53 14 4.59 5.11 22 2.36 4.26 Onions 2153 1.04 0.86 29 1.20 0.82 17 2.13 5.92 Garlic 1590 0.44 0.50 46 0.50 0 0.39 0.29 .37 29 Tomatoes 2.35 1.20 2261 3.47 2.52 2 16 2.30 1.93 Tomato
r 1.35 3.50
sauce opaste 132 1.77 1 0.25 . 1 . Grve
een leafy getables 602 0.87 0.78 11 0.74 0.53 3 0.60 0.36
Cabbage 690 1.74 1.23 7 2.50 1.98 11 2.39 2.17 Cauliflowerl 353 1.43 0.83 2 3.00 0.00 6 2.21 3.33 Artichoke 37 1.79 1.21 0 0 Eggplant 313 1.28 0.68 2 0.50 0.00 3 0.92 0.14 Squash 567 1.57 1.01 2 4.00 2.83 7 2.71 2.27 Okra 80 2.49 1.87 5 1.60 0.55 1 5.00 .
227
Mulikiyya 482 1.34 1.28 26 1.21 1.01 14 1.82 1.48 Green cowpeas 22 1.58 1.42 0 1 1.00 . Green peas 676 1.97 1.15 25 1.06 8 1.34 1.03 2 3.P 3 1.17 0.83 2.40 2.26 epperoni 64 0 2 Cucumber 768 1.81 1.55 0 6 2.04 2.00 Green beans 124 1.86 1.60 1.29 1 . 0 Carrots 1 0. 0.68 003 0.61 0.45 0 6 83Taro 2 1.24 0.68 0.80 0.61 57 0 3 Other vegetables 127 0.98 0.93 13 2.58 2.66 7 1.25 0.52
price vegetables Potatoes 2248 0 0.60 0.17 0.63 0.16 0.65 .19 14 22 Onions 2153 0.83 0.29 0.90 0.34 29 17 1.00 0.45 Garlic 1590.00 1 1.27 1.06 1.52 1.12 1.51 .44 46 29 Tomatoes 2261.00 0.55 0.35 0.41 1.15 0.50 2 16 0.98 Tomato sauce or paste 13 6.57 3.77 1.67 7.00 2.00 1 . 1 . Green leafy
602.00 11 0.55 0.17 vegetables 0.91 0.51 3 1.00 0.00 Cabbage 690.00 1.02 0.44 7 0.75 0.14 11 0.99 0.43 Cauliflowerl 353.00 1.50 0.06 2 1.25 0.35 6 1.00 0.00 Artichoke 37.00 1.89 0.11 0 0 Eggplant 313.00 1.21 0.45 2 1.00 0.71 3 1.06 0.42 Squash 567.00 1.14 0.38 2 1.00 0.00 7 1.29 0.39 Okra 80.00 20.00 6.17 6.71 5 3.00 1.41 1 . Mulikiyya 482.00 2.86 1.44 0.84 14 3.50 2.02 26 2.25Gcow 22. 0 2.36 1.43 0 1 2.00
reen peas 0 .
Green 67 1.13 0.18 1.04 0.43 peas 6.00 1.44 0.51 2 8
Pepperoni 36 1.30 0.42 4.00 2.32 0.93 0 2 Cucumber 76 1.45 0.43 1.46 0.46 8.00 0 6 Green beans 124.00 1.90 1.08 1 0.80 . 0 Carrots 10 03.00 0.47 0.26 0 6 0.40 0.08 Taro 25 7.00 0.98 0 Other vegetables 1 1.21 0.78 27 1.55 13
228
market home pr uction othe es od r sourc
Obs Mean St St Sd. Dev. Obs Mean d. Dev. Obs Mean td. Dev.
quantity Fruits and nuts
Nuts 72 0.55 0.49 0 2 0.33 0.25 Dried 0. 0. fruits 17 36 32 0 0 Other fruits 8 1.31 0.59 0 0 Pinapple 0 0 0 Guava 3 1.67 1.15 0 1 2. 00 . Dates 67 1.73 3.03 1.73 1.32 1.14 0.86 12 9 Strawberries 94 2.00 1.36 1.56 0.82 1 . 10 1.65 Figs 2 2.50 0.71 0 0 Pears 1 1.00 . 0 0 Peach 2. 0.00 7 1.64 0.90 0 2 00Plum 1 2.00 . 0 0 Apricoat 6 2.86 2.42 0 1 3.00 . Cantelope 1 2. 17 2.09 .00 0 1 00 . Watermelon 1 2.00 . 0 0 Grapes 0 0 0 Apples 38 1.57 1 1. 0.71 .12 0 2 50Mangoes 0 0 0 Tangerines 5.17 4.25 649 2.63 1.97 3 26 2.85 3.66 Grapefruit 4 3. 1. 2. 0.47 25 50 0 2 33Lemons 900 0.57 1.38 12 1.17 1.05 10 1.08 1.45 Oranges 1 5.92 2.29 844 3.16 2.20 6 78 4.20 6.05 Bananas 739 2.21 1.15 1 2.00 . 33 2.62 1.94
expenditure Fruits and nuts
Nuts 72 2.74 2.41 0 2 1.88 0.53 Dried fruits 17 2.26 1.62 0 0 Other fruits 8 1.48 0 0 2.63 Pinapple 0 0 0 Guava 3 1.20 0.60 1 2.50 . 0 Dates 67 2.40 6.08 1.89 9 2.19 2.79 12 2.70 S 2.88 1.62 4.00 10 2.81 2.07 trawberries 94 1 . Figs 2 6.00 0.00 0 0 Pears 1 5.00 . 0 0 Peach 7 3.21 1.93 0 2 5.00 0.00 Plum 1 2.00 . 0 0 Apricoat 6 1.86 1.57 0 1 2.40 . Cantelope 17 3.99 3.23 0 1 2.50 . Watermelon 1 4.00 . 0 0 Grapes 0 0 0 Apples 38 10.08 6.48 0 2 8.50 4.95 Mangoes 0 0 0
229
T 649 2.21 1.66 3 3.93 3.20 26 2.78 3.81 angerines Grapefruit 4 2.60 0.95 0 2 1.75 0.35 Lemons 900 0.82 0.70 12 1.98 2.44 10 1.09 1.16 O 4 ranges 184 2.65 1.86 6 4.70 1.08 78 3.50 4.16 B 4.85 3.42 ananas 739 4.22 2.60 1 4.00 . 33
price Fruits and
nuts
Nuts 9 0 8.49 72 6.28 5.22 0 2 .0Dried fruits 17 7.91 4.79 0 0 Other fruits 8 1.94 0.32 0 0 Pinapple 0 0 0 Gu 3 0.80 0.35 0 1 1.25 . ava Dates 67 1.31 0.61 12 1.63 0.42 9 1.86 1.19 St es 2.00 1.80 0.70 rawberri 94 1.86 0.55 1 . 10 Figs 2 2.50 0.71 0 0 Pears 1 5.00 . 0 0 Peach 7 1.96 0.68 2 2.50 0.00 0 Plum 1.00 1 . 0 0 Apricoat 6 0.65 0.00 0 1 0.80 . Cantelope 17 1.82 0.71 0 1 1.25 . W 1 2.00 . 0 0 atermelonGrapes 0 0 0 Apples 38 6.61 1.59 0 2 5.50 0.71 Mangoes 0 0 0 Tangerines 649 0.75 0.10 0.93 0.33 0.85 0.27 3 26 Gr 0 apefruit 4 0.85 0.19 2 0.75 0.00 Lemons 900 2.20 0.79 12 1.69 0.71 10 1.20 0.41 O 0 5 0.19 ranges 1844 0.85 0.23 6 0.84 0.19 78 .8B 739 1.91 0.50 1 2.00 . 33 1.92 0.47 ananas
hom ction other urces market e produ so
Obs Mean S Obs S Std. Dev. Mean td. Dev. Obs Mean td. Dev.
quantity Fish and
meat
Fresh fish 752 1.90 1.21 2 1.75 1.06 15 1.43 1.01 Frozen fish 410 1.74 0.95 0 2 2.00 1.41
Canned fish 48 0.75 0.69 0 1 1.25 .
Smoked or salted fish 102 0.71 0.58 1 1 0 0.33 .00 . 6 .79
Crustecians 3 1.00 0.50 0 0 Fresh
chicken 180 2.40 1.40 26 2.46 985 2.72 1.87 2.83 Frozen chicken 43 2.08 1.56 3 3.67 0.58 0
230
Duck and 2.87 1.54 93 2.63 1.34 9 1.91 2.03 geese 54
Pigeon 15 1.43 0.75 1.77 1.11 4.32 2.28 34 6 Rabbit 9 1.80 1.05 8 2.56 1.75 2 1.50 0.00 Turkey 3 3.17 3.33 1 4 .55 . 0
F 1517 1.50 2.51 2 3.00 2.83 39 1.96 1.45 resh beef Frozen
46 1.20 0.99 0 0 beef Canned
beef 8 1.19 0.71 0 0 Lamb 47 4.06 5.20 7 11.79 17.46 19 3.70 2.62 Goat 17 1.82 2.82 10 11.70 11.34 6 0.88 0.59
Camel 95 1.38 0.97 0 4 0.63 0.25 Other
processed meats 126 0.45 0.39 0 0 Other meats 24 1.21 0.62 0 1 0.25 .
e ndixpe ture Fish and
meat
Fr h 14.00 8.49 8.98 7.44 esh fis 752 9.29 7.22 2 15 Frozen 410 5.48 3.34 0 2 9.25 8.13 fish
Canned fish 48 4.33 4.58 0 1 2.50 .
Smoked or salted 5 fish 102 4.90 4.17 1 .00 . 6 7.25 3.19
Cr s 3 11.33 3.51 0 0 ustecianFresh
chicken 985 14.31 9.56 180 14.45 7.53 16.89 12.60 26 Frozen chicken 43 12.17 7.03 3 28 0 6. .0 93 0
Duck and geese 54 22.50 14.63 93 21.28 10.99 9 24.94 17.73 Pigeon 15 11.67 5.79 34 16.28 9.30 6 22.17 11.16 Rabbit 9 13.83 4.83 8 14.75 9.65 2 10.00 0.00 Turkey 3 35.50 36.77 1 50.00 . 0
Fresh beef 1517 21.53 33.52 2 43.50 37.48 39 29.51 22.75 Frozen
beef 46 10.83 8.96 0 0 Canned
beef 8 9.28 9.82 0 0 Lamb 47 56.57 66.07 7 136.71 171.16 19 56.58 40.32 Goat 17 26.18 47.50 10 167.90 171.45 6 10.67 7.69
Camel 95 16.66 10.98 0 4 7.63 2.93 Other
processed meats 126 4.00 3.45 0 0 Other meats 24 8.49 5.42 0 1 5.00 .
231
price Fish and
meat
Fresh fish 7.27 752 4.97 2.45 2 0.00 15 8.00 6.75 Frozen fish 0.81 0 2 4.25 6 410 3.15 1.0
Canned fish 8.49 6.58 0 1 2.00 48 .
Smoked or s ed fish 7.17 4.08 1 00 6 10.58 2 alt 102 5. . 5.0
Crustecians 14.11 8.37 0 0 3 F
chiresh cken 5.40 1.21 180 37 1.61 6.30 985 6. 26 1.47
Frozen chicken 6.34 1.73 0.77 0 43 3 7.56
Duck and ese 7.75 1.31 93 28 1.73 16.01 4 ge 54 8. 9 10.6
Pigeon 8.40 1.59 34 53 1.26 5.25 15 9. 6 0.47Rabbit 9 8.65 2.66 8 6.00 0.93 2 6.67 0.00 Turkey 3 11.00 4.00 1 11.00 . 0
F 1.73 2 15.50 2.12 39 14.84 resh beef 1517 14.48 1.16 Frozen
eef 9.05 2.24 0 0 b 46 Canned
eef 7.41 3.59 0 0 b 8 Lamb 14.60 2.62 7 81 2.54 14.89 9 47 13. 19 1.5Goat 17 12.67 1.67 10 2.07 12.17 13.71 6 1.33
Camel 95 12.24 0.86 4 12.25 0 0.50 Other
processed meats 126 9.48 4.86 0 0 Other meats 24 7.78 4.49 0 1 20.00 .
232
Appendix 2
Variables used in regressions for modified AIDS model estimation
Dependent variables Obs Mean Std. dev. Min Max
Food group unit values
V_cer 1875 1.411 0.540 0.367 6.244
V_pul 1875 2.515 0.713 0.050 9.533
V_dai 1875 3.858 1.782 0.500 14.375
V_oil 1875 6.439 3.316 1.000 22.652
V_vef 1875 1.300 0.581 0.526 6.843
V_fem 1875 10.046 3.427 1.500 27.134
V_sed 1875 6.168 2.705 0.500 31.631
v_spi 1875 5.200 4.140 0.100 30.394
Food group budget shares
w_cer 1875 0.076 0.057 0.004 0.429
w_pul 1875 0.029 0.019 0.000 0.120
w_dai 1875 0.056 0.033 0.002 0.252
w_oil 1875 0.043 0.025 0.001 0.215
w_vef 1875 0.070 0.033 0.005 0.428
w_fem 1875 0.131 0.073 0.009 0.661
w_spi 1875 0.006 0.005 0.000 0.088
w_sed 1875 0.040 0.022 0.004 0.212
Food group quantities
q_cer 1875 15.321 18.040 0.200 166.429
q_pul 1875 2.714 3.979 0.086 130.667
q_dairy 1875 3.866 3.321 0.100 39.422
q_oils 1875 1.622 1.016 0.188 8.093
q_vef 1875 13.042 8.259 0.500 84.663
q_fem 1875 3.518 3.743 0.250 84.000
q_sed 1875 1.891 2.107 0.042 50.591
q_spic 1875 0.386 0.958 0.019 35.000
233
234
Independent variables Obs Mean Std. dev. Min Max
Number of females in the household
<= 5 years 1875 0.337067 0.638073 0 4
> 5, <= 10 1875 0.357867 0.642198 0 4
> 10, <= 18 1875 0.576 0.83606 0 8
> 18, <= 50 1875 1.245333 0.857868 0 8
< 50 1875 0.424533 0.551544 0 4
<= 5 years 1875 0.326933 0.605291 0 4
> 5, <= 10 1875 0.363733 0.646778 0 5
> 10, <= 18 1875 0.644267 0.874678 0 6
> 18, <= 50 1875 1.2864 1.028205 0 8
< 50 1875 0.392533 0.513996 0 4
