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OCR for page 499
E
Measuring Relative Poverty
with DHS Data
This appendix briefly describes how the panel defined urban poverty for the pur-
poses of its DHS analyses, leaving a more complete account to Hewett and Mont-
gomery (2001~. Recall that in the DHS program, no information is collected on
incomes or consumption expenditures, the two variables commonly used to mea-
sure household standards of living. However, a few other items are collected that
can serve as crude proxy measures of living standards. We can distinguish three
categories of such items: the ownership of various consumer durables; descrip-
tors of the quality of housing; and measures of access to services, such as water
supply and electricity. Of the three, we limit attention to the consumer durables
and housing measures. This is because we want to explore whether poverty is
associated with a lack of access to public services, and with that goal in mind,
poverty cannot be defined in terms of these same services. The items used in the
panel's index are ownership of a refrigerator, television, radio, bicycle, motorcy-
cle, or car; the number of sleeping rooms in the dwelling; and whether its floor is
of a finished material. Montgomery, Gragnolati, Burke, and Paredes (2000) and
Filmer and Pritchett (2001) discuss the performance of such proxies as measures
of living standards.
Using these durables and housing quality items, we proceeded to define poverty
in relative terms. We carried out a principal components analysis a method
not unlike factor analysis to extract from the DHS indicators a single score that
could be interpreted as an index of the household's standard of living. (Hewett
and Montgomery, 2001, compare results from confirmatory factor analysis with
those from principal components analysis and find little empirical difference be-
tween them.) For each DHS survey, we classified as "relatively poor" those urban
households whose index scores fell into the lowest quartile of the urban scores for
that survey. The same approach was used to characterize rural households.
499
OCR for page 500
500
CITIES TRANSFORMED
This emphasis on the relative aspect of poverty was all but forced upon us
by the nature of the data collected in the DHS surveys. The proxy measures
form a heterogenous group and are not directly comparable to measures of income
or consumption. These data do not provide the necessary raw materials for a
defensible measure of absolute poverty. Furthermore, ownership of consumer
durables differs so greatly between urban and rural settings that to form one index
common to both settings might well be misleading. Having decided to estimate
separate indices for urban and rural households, we were left with little alternative
but to rank households within their sectors of residence. One advantage of such
sector-specific relative poverty measures is that they retain their meaning when
we make comparisons across countries at different levels of income per capita,
whereas absolute poverty measures would be too closely associated with national
income per capita to allow for meaningful comparisons.
Unfortunately, the durables and housing measures are not always available
and consistently defined in all DHS surveys. In Round 1 of the DHS program,
questions on these measures were asked only of households that happened to have
in residence a woman of reproductive age. Hence for the 27 DHS surveys in
this round, the data gathered are not representative of the general population of
households. The situation changed in Rounds 2 and 3 of the DHS program, when
such information began to be collected for all households. Even in these rounds,
however, the availability of any particular item in a survey is not guaranteed. The
problem is compounded by differences in the coding schemes across surveys and
by the lack of variation of some items in particular countries or sectors. The
durables and housing measures that can be used to construct an index will there-
fore vary from one country to another, and within countries from urban to rural
areas.
Although the panel's intention had been to explore rural differences in relative
living standards as well as urban, we found that the DHS-based indices could
not always identify a lowest quartile of rural households. This is especially so
in very poor countries, where many households lack most or all of the consumer
durables items. Further research on this front is needed, but to pursue the issue of
rural diversity in any greater depth would have led the panel away from its main
. . .
priories.
Tables E-1 and E-2 (mentioned in Chapter 5) shed light on the likelihood of
(relative) poverty and access to services for households containing a woman who
is a recent migrant, by comparison with other households.
OCR for page 501
MEASURING RELATIVE POVERTY WITH DHS DATA
501
TABLE E-1 Urban Migrant-Nonmigrant Differences in Poverty and Access to Services,
All Recent Migrants, by Region
Access to
Piped or
DHS Surveys Relatively In-home Flush
in Region Poor Water Toilet Electricity
Migrant Proportion Less Nonmigrant Proportion
North Africa 0.015 0.037 0.011 - 0.016
Sub-Saharan Africa 0.009 0.029 0.042 0.025
Southeast Asia 0.035 0.036 0.056 0.042
South, Central, West Asia 0.014 0.035 0.042 0.062
Latin America 0.054 - 0.018 0.001 - 0.015
TOTAL 0.022 0.021 0.031 0.023
Number of Surveys and Significance
North Africa
Surveys
Significant
Significant migrant disadvantage
Sub-Saharan Africa
Surveys
Significant
Significant migrant disadvantage
Southeast Asia
Surveys
Significant
Significant migrant disadvantage 1 0 0
South, Central, West Asia
Surveys
Significant
Significant migrant disadvantage 2 0
Latin America
Surveys
Significant
Significant migrant disadvantage
TOTALS
Surveys
Significant
Significant migrant disadvantage
6 3 2
o
39
8
5
36
13
4 4
o
o
o
33
16
3
2
11 9 10
5 4 4
18
10
10
78
25
19
o
o
35
6
3
1
o
6
4
o
14 16
3
66 64
21 25
3
9
3
3
54
14
4
NOTE: Estimates and tests from probit models, adjusted for city size and woman's
age.
OCR for page 502
502
CITIES TRANSFORMED
TABLE E-2 Urban Migrant-Nonmigrant Differences in Poverty and Access to Services,
by Type of Origin Area and Region
Access to
DHS Surveys
in Region
North Africa
Surveys
Disadvantage, city origin
Disadvantage, town origin
Disadvantage, rural origin
Sub-Saharan Africa
Surveys
Disadvantage, city origin
Disadvantage, town origin
Disadvantage, rural origin
Southeast Asia
Surveys
Disadvantage, city origin
Disadvantage, town origin
Disadvantage, rural origin
South, Central, West Asia
Surveys
Disadvantage, city origin
Disadvantage, town origin
Disadvantage, rural origin
Latin America
Surveys
Disadvantage, city origin
Disadvantage, town origin
Disadvantage, rural origin
TOTALS
Surveys
Disadvantage, city origin
Disadvantage, town origin
Disadvantage, rural origin
Relatively
Poor
Piped or
In-home
Water
Flush
Toilet Electricity
6
o
o
5
3
o
o
o
o
o
33 32 29 31
2
o
9
4 4
O O
2 0 0
2 0 0
7 5 7
o
o
o
1
15 12 13
5
65 56
5 2
10 0
33 14
o
o
o
o
o
11 11
o
o
54 45
o
20 15
3
o
o
o
3
o
o
o
7
o
4
o
2
NOTE: Estimates and tests from probit models, adjusted for city size and woman's
age.
Representative terms from entire chapter:
origin disadvantage
