Download Economies of Scale in Consumption

Peter Lanjouw, DECPI
PREM Knowledge and Learning Weeks
“Exploring the Intersections between Poverty
and Gender”
World Bank, May 8, 2012
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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
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Remaining caveats
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Conventional poverty analysis is based on a measure
of household per capita consumption (or income)
◦ Household consumption aggregate is built up from multiple
components
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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
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This approach side-steps whole issue of intrahousehold distribution
Huge and growing literature to study withinhousehold allocation and distribution, but as yet no
established procedure for capturing differential
welfare levels at the individual level.
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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 Poverty
All Households
Male-Headed
Female-Headed
Widow-Headed
Extended;male-headed
63.4%
63.8%
57.7%
58.3%
68.2%
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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)
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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:
x
x  
n
*
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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:
x
x
  ( )  (1   ) x

n
n
Solving for θ yields:
 
 ln( 1   
ln( n)

n
)
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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
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Are conclusions sensitive?
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
Maleheaded
5.56
63.8
59.4
53.9
48.6
Femaleheaded
3.60
57.7
61.6
62.0
62.6
Widowheaded
3.32
58.3
63.8
65.1
66.2
Extended;
maleheaded
6.78
68.2
60.3
51.0
43.5
Source: Drèze and Srinivasan (1997), Table 4.
Household
size
All households
4.489
Low dependency rate
3.689
High dependency rate
4.883
Widow-headed
4.129
Female-headed
4.031
Male-headed
4.618
Extended family 3+ children
7.456
θ=1
θ=0.8 θ=0.6 θ=0.4 θ=0.2
0.209 0.212 0.219 0.228 0.236
0.089 0.102 0.124 0.157 0.187
0.375 0.369 0.380 0.378 0.374
0.215 0.232 0.260 0.282 0.302
0.149 0.165 0.182 0.202 0.225
0.226 0.225 0.230 0.235 0.239
0.563 0.524 0.467 0.391 0.328
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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)
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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.
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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)
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Lanjouw and Marra (2012) obtain an estimate for θ of around 0.53
for Vietnam.
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Engel-curve analysis is prey to a fundamental
identification problem
◦ Problem first pointed out by Pollack and Wales (1979)
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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.
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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).