Counting Women in Poverty: Potential Pitfalls in Conventional Poverty

Analysis

Peter Lanjouw, DECPIPREM Knowledge and Learning Weeks

“Exploring the Intersections between Poverty and Gender”

World Bank, May 8, 2012

The principal problem Scouring the data for insights A second problem The sensitivity of conclusions Can we estimate θ?

◦ Engel-estimates◦ Estimates from subjective welfare models

Remaining caveats

Outline

Conventional poverty analysis is based on a measure of household per capita consumption (or income)◦ Household consumption aggregate is built up from multiple

components Food Basic Non-food items Education (and health) expenditures Consumer durables Housing

Household consumption is divided through by household size to yield per capita consumption◦ Our best estimate of individual welfare

This approach side-steps whole issue of intra-household distribution

Huge and growing literature to study within-household allocation and distribution, but as yet no established procedure for capturing differential welfare levels at the individual level.

The principal problem

What if we focus on poverty of female headed households? Of widows?

Rural India, 1986/7 NSS data (Dreze and Srinivasan, 1997)Family Type Incidence of PovertyAll Households 63.4%Male-Headed 63.8%Female-Headed 57.7%Widow-Headed 58.3%Extended;male-headed68.2%

Scouring the data for insights

The use of a per capita measure of consumption imposes an assumption of no economies of scale in consumption.

Where might such economies come from?◦ Consumption of public goods within the

household (radio, water pump) ◦ Bulk purchase discounts on perishable food

items◦ Economies in food preparation (fuel, time)

A Second Problem:Economies of Scale in Consumption

Suppose money metric of consumer’s welfare has an elasticity of θ with respect to household size. Then welfare measure of a typical member of any household is measured in monetary terms by:

Economies of Scale in Consumption

nxx *

Suppose that ρ is the proportion of household expenditure on purely private goods, and 1- ρ is allocated to public goods.

Then the correct monetary measure of per-capita welfare is:

Solving for θ yields:  

Economies of Scale in Consumption

xnx

nx )1()(

)ln(

)1ln(

nn

In India (in 1986/7) average household size is 5.35. ◦ If ρ =0.9 then θ=0.79◦ If ρ =0.7 then θ=0.50◦ If ρ =0.5 then θ=0.31

Are conclusions sensitive?

Economies of Scale in Consumption

 The head-count ratio and economies of scale 

Household Type

Mean size

Economies of scale parameter θ

1 0.8 0.6 0.4

All households

5.35 63.4 59.6 54.5 49.5

Male-headed

5.56 63.8 59.4 53.9 48.6

Female-headed

3.60 57.7 61.6 62.0 62.6

Widow-headed

3.32 58.3 63.8 65.1 66.2

Extended; male-headed

6.78 68.2 60.3 51.0 43.5

Source: Drèze and Srinivasan (1997), Table 4.

The picture in Vietnam is more nuanced (Lanjouw and Marra, VHLSS 2010)

Household size θ=1 θ=0.8 θ=0.6 θ=0.4 θ=0.2

All households 4.489 0.209 0.212 0.219 0.228 0.236 Low dependency rate 3.689 0.089 0.102 0.124 0.157 0.187 High dependency rate 4.883 0.375 0.369 0.380 0.378 0.374 Widow-headed 4.129 0.215 0.232 0.260 0.282 0.302 Female-headed 4.031 0.149 0.165 0.182 0.202 0.225 Male-headed 4.618 0.226 0.225 0.230 0.235 0.239 Extended family 3+ children 7.456 0.563 0.524 0.467 0.391 0.328

The per capita assumption is not innocuous.

Conclusions as to the relative poverty of widows versus others, or large households (many children) versus small (elderly), are usually quite sensitive. ◦ Big issue in regions (ECA) where there are big

debates regarding public spending priorities (pensions versus child benefits)

◦ Note, over time, economies of scale parameters could evolve (Lanjouw, et al, 2004)

Economies of Scale in Consumption

Econometric analysis of Engel curves with cross section data offers one entry point.

Regress food share on the log of expenditure per person, including household composition as well as household size in the specification (Lanjouw and Ravallion, 1995)

Lanjouw and Ravallion (1995) estimate a value for θ of around 0.6 for rural Pakistan.

Lanjouw and Marra (2012) obtain an estimate of 0.68-0.69 for rural and urban Vietnam.

Lokshin and Ravallion (2002) obtain an estimate of around 0.4 in Russia.

Subjective welfare data provide an alternative entry point to gauge presence of economies of scale (Ravallion and Lokshin, 2002, Pradhan and Ravallion, 2000, Ravallion, 2012)

Lanjouw and Marra (2012) obtain an estimate for θ of around 0.53 for Vietnam.

Can we estimate θ?

Engel-curve analysis is prey to a fundamental identification problem◦ Problem first pointed out by Pollack and Wales (1979)

Deaton and Paxson (1998) find further puzzles with this line of enquiry.◦ Holding per capita income constant larger households report

spending a smaller share of their budget on food. Ravallion (2012) points to concerns with the

interpretation of the subjective welfare-based estimates of θ◦ It is not clear that persons with different personalities respond

in the same way to subjective welfare questions. ◦ Controlling for latent personality effects with panel data results

in non-robust estimates of θ (Lokshin and Ravallion, 2001).

Remaining Caveats