Peter Lanjouw, DECPI
Michael Lokshin, DEPI
Zurab Sajaia, DECPI
Roy vand der Weide, DECPI
With
Professor James Foster (GWU)
Module 4, Feb 28-March 1, 2011
Monday Feb 28
 Session 1 (Peter Lanjouw): 9:00-11:00
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◦
◦
◦
Opening Remarks and Introductions
Concepts, Definitions and Data
Constructing a Consumption Indicator:
Adjustments for Family Composition and Size

Session 2 (Michael Lokshin): 11:15-12:30

Session 3 (Michael Lokshin and Zurab
Sajaia): 2:00-3:30
◦ Poverty Lines
◦ Poverty Measures: Properties and Profiles
◦ ADePT Software for Poverty Analysis
Tuesday, March 1
 Session 4 (Roy van der Weide): 9:00-10:30
◦ Statistical Inference and Poverty Decomposition

Session 5 (Professor James Foster): 10:3012:00
◦ New Frontiers in Poverty Measurement I
 Multidimensional poverty measurement
 Chronic versus transient poverty

Session 6 (Peter Lanjouw): 2:00-3:30
◦ New Frontiers in Poverty Measurement II
 Small area estimation of poverty
 Making non-comparable data comparable
 Developing pseudo-panel data for poverty
comparisons
What do we mean by “poverty”?

Common definition:

More narrow definition:

Less narrow definition:
◦ Lack of command over commodities; “..a
severe constriction of the choice set [over
commodities]” (Harold Watts)
◦ Lack of specific consumptions (e.g. too little
food energy intake; too little of specific
nutrients; too little leisure.)
◦ Poverty as lack of “welfare” e.g., lack of
“capabilitiy”: inability to achieve certain
“functionings” (“beings and doings”) (Amartya
Sen)
Other important definitions
 Consumption: destruction of goods and
services by use
 Expenditure: consumption valued at prices
paid (whether or not there was an actual
transaction)
 Income: maximum possible expenditure on
consumption without depleting assets
Often used interchangeably, but beware!

1.
Poverty data can inform, and misinform,
anti-poverty policy.
The growth strategy
Has poverty increased? Did growth help the poor?
How did relative price changes affect the poor? What
is the impact of food price fluctuations? Who were
the losers and who were the gainers from economywide policy reforms? (ex-ante versus ex-post)
2.
Social Spending
Who uses public services? At what cost? Who
benefits from government subsidies? On average,
versus at the margin? Who will be hurt by
retrenchment?
3.
Targeted Interventions
Who are the target groups? How should transfers be
allocated? How much impact will they have on
poverty?
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How do we measure “welfare”?
When do we say someone is "poor"?
How do we aggregate data on welfare into a
measure of “poverty”?
How robust are the answers?

Common practice emphasizes economic
welfare:
◦ add up expenditures on all commodities consumed
(with imputed values at local market prices) and
◦ deflate by a poverty line (depending on household
size and composition and location/date)

“real expenditure” or “welfare ratio”


Survey data
Differ according to:
◦ - the unit of observation (household/individual),
◦ - no. observations over time (cross-section/panel);
◦ - living standards indicator (consumption/income)

Survey design
Does the sample frame cover the entire
population? Is there a response bias? What is the
sample structure (clustering, stratification)?

Goods coverage and valuation
Is the goods coverage comprehensive? Is the
survey integrated (e.g. price analysis)? Are there
valuation problems?

Variability and the time period of survey
Is there significant variability over time? Can this be
encompassed within the recall period? What are the
implications for the choice between consumption
and income?

Inter-personal comparisons
Is consumption a sufficient statistic? What other
variables matter? (Prices, demographics, publicly
provided goods)

Income per capita

Consumption per equivalent single adult

Food-share ("Engel's Law")

Nutritional indicators
◦ Poor indicator when incomes vary; hard to
measure
◦ Problems with forming scales; composition
versus size economies; intra-household
inequality.
◦ Sources of noise: other parameters; problem
of income elasticity near unity. Identification
problems.
◦ "Welfarist" critique (welfare and nutrition are
different things); nutritional requirements/
anthropometric standards.

Anthropological methods
◦ Concerns about representativeness and
objectivity; lack of integration with other
methods. We can learn a lot from case studies,
but they don’t represent a whole country.

Subjective/qualitative methods
◦ Can provide useful extra information – to help
solve the identification and referencing problems.
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

Use a comprehensive consumption
measure, spanning consumption space
Choice between income and consumption is
largely driven by the greater likelihood of
accuracy of information on consumption.
Recognize the limitations of consumption
based measures; look for supplementary
measures, esp access to public services,
subjective welfare, for complementary
insights.


The consumption measure serves as the
foundation upon which much of the
subsequent poverty analysis rests.
Principles
◦ Should be comprehensive
◦ Retain transparency and credibility
◦ Goal is to be able to rank individuals credibly in
terms of welfare





Construct a food consumption measure
Add basic non-food items (from consumption
module)
Add other non-food items (other modules)
Add housing expenditures
Add use-value of consumer durables

Surveys typically ask about food consumption,
item by item, over a specific reference period.
◦ In general, the longer (and more disaggregated) the list
of items, the higher is food consumption

Sometimes information is asked about
consumption in a typical reference period (e.g.
month).
◦ This has the attraction of helping to overcome
seasonality concerns.


Surveys vary in terms of recall periods
◦ Some surveys use diary methods rather than recall
periods.
We expect that the longer the reference period,
the more expenditures are likely to be biased
downwards (recollection difficulties)



But, the shorter the reference period, the noisier are
the expenditure data.
◦ This can hamper poverty comparisons.
Food expenditures should include not only
purchased items but also consumption out of home
production.
◦ Home production should be valued using local
market prices (preferably farm-gate)
Most surveys record not only food expenditures, but
also quantities
◦ This information is of use for the construction of
poverty lines
◦ When dealing with separate price, quantity and
frequency information, on an item by item basis,
one often needs to impute certain missing values.




The typical consumption module includes a
range of non-food items alongside food.
Other parts of the questionnaire may also
include certain non-food expenditures (housing
section, education and health sections)
Key issue is to distinguish between investments
and consumption (avoid double counting).
Health expenditures are usually excluded
◦ Lumpy
◦ If we include we should also have a good
measure of need.



Two Additional omissions:
◦ Leisure
◦ Public goods
The problem is essentially one of pricing:
◦ Should we value an unemployed person’s
leisure based on wages in a market to which
the individual has no access?
◦ What is the value to individuals of publicly
provided goods?
Imputations for public goods and leisure are
likely to compromise credibility and usefulness
of welfare measures.
◦ We should still document who gets public
services, or is unemployed, and examine
whether these are poor or rich.





In most settings a minority of households rent their
dwelling, and a majority reside in their own homes.
Home-owners consume a stream of services from
their homes. This is precisely what rentors pay for
with their rent.
The challenge is thus to impute for home-owners
what they would be paying in rent if they were
renting rather than owning their house.
Many surveys ask specifically what a household
would pay in rent if it were renting. Where credible
this number can be used for home owners.
Elsewhere one can try to predict rent paid based on
regression models estimated on subset of renting
households.



Purchases of irregular, lumpy items such as
consumer durables (tv, car, etc.) cannot be
directly added to the consumption definition.
◦ Many households are unlikely to make such
purchases within the reference period of the
survey.
◦ But many will be consuming a stream of
services from those items that they own.
Surveys often solicit information on the age of
assets owned, original purchase price, and
current replacement price.
Based on this information it is possible to
calculate the consumption stream of services
from the durable as:
◦ Consumption Stream = Current value*(real
interest rate + depreciation rate).
The Headcount With Alternative Consumption Aggregations
Consumption
Aggregate
Ecuador
Nepal
Brazil
Food Spending plus
Basic Non-Food Spending
1.00
1.00
1.00
Food plus Basic Non-Food
Spending Including Energy
and Education Spending
0.85
0.91
0.89
Above With Actual or Imputed
Water Expenditures
0.81
n/a
n/a
Above With Actual or Imputed
Value of Housing Services
0.70
0.77
0.65
Above With Imputed Value
of Owned Consumer Durables
0.68
0.76
n/a
Do not compare Apples with Oranges!!!
Figure 1a. Poverty headcount rate (%) at $1.25/person/day by module type
66.8
62.8
64.6
59.5
54.9
55.6
55.1
47.5
1. Recall: Long, 2. Recall: Long,
14 day
7 day
3. Recall:
4. Recall:
5. Recall: Long
Subset, 7 day Collapse, 7 day Usual 12 month
6. Diary: HH,
7. Diary: HH,
8. Diary:
Frequent
Infrequent
Personal
24
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Ultimate goal is to arrive at a money metric of
individual welfare.
Consumption (and income) aggregates are
usually constructed at the level of the
household.
Convention is to divide household consumption
by the number of family members to arrive at a
measure of per capita consumption.
This approach sidesteps two issues:
◦ Different people may have different needs
◦ The cost per person of reaching a certain
welfare level may be lower in large households
than small ones.

In principle equivalence scales can be
used to adjust for differences in needs.
◦ E.g. If a child needs half as much as an adult,
then a two adult - two child household will
consist of three equivalent adults.
◦ If the total consumption of household is 120
then equivalent-consumption will equal 40.
All four individuals will be allocated this
equivalent-consumption.

Where do equivalence scales come from?
◦ Huge range of candidate scales



Nutritional scales – derived from health
studies. At best can be used to deflate
food expenditures.
Behavioral scales – econometric
estimates based on observed allocations.
Major difficulties with identification. For
example, if we observe that female
children get less, do they need less? Or
is it that they are systematically
discriminated against?
Little guidance as to which scales are
best. One option to conduct sensitivity
analysis. (India example)
The head-count ratio and equivalence scales
Household
Type
Equivalence scales
(1,1,1)
(1,1,0.6)
(1,0.8,0.6)
(1,0.7,0.4)
All households
63.4
63.2
62.9
63.8
Male-headed
63.8
63.6
63.5
64.5
Femaleheaded
57.7
57.4
54.3
52.7
Widow-headed
58.3
61.9
58.2
58.6
Extended;
male-headed
68.2
69.5
67.6
67.4
Source: Drèze and Srinivasan (1997), Table 3.
Note: The equivalence scales are written as triplets indicating the weights for ‘adult male’, ‘adult
female’ and ‘child’, in that order.


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We often find that poverty profiles do not
change much as a result of equivalence
scale adjustments.
Use of per capita welfare measure may not
be too misleading
This is an empirical question that needs to
be checked on a case-by-case basis.


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)

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
*



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
)

In Ecuador, average household size is
4.76.
◦ If ρ =0.9 then θ=0.8
◦ If ρ =0.7 then θ=0.51




If average size = 6
◦ ρ =0.9 then θ=0.77
◦ ρ =0.7 then θ=0.49
Problem, as with equivalence scales, is
that there isn’t a good way of estimating
θ
Best bet is sensitivity analysis again.
(India Example)
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.


Message now is that the per capita
assumption is not innocuous.
Conclusions as to the relative poverty of
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)



Martin Ravallion, Poverty Lines in Theory
and Practice, Living Standards Measurement
Study Working Paper 133, World Bank,
Washington DC., 1998.
Martin Ravallion, "Issues in Measuring and
Modeling Poverty", Economic Journal, Vol.
106, September 1996, pp. 1328-44.
Martin Ravallion, Poverty Comparisons,
Fundamentals of Pure and Applied
Economics Volume 56, Chur, Switzerland:
Harwood Academic Publishers, 1994.
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Beegle, K., De Weerdt, J., Friedman, J., and Gibson, J.
(2011) ‘Methods of Household Consumption
Measurement Through Surveys: Experimental Results
from Tanzania’ Policy Research Working Paper No. 5501,
the World Bank.
Hentschel and Lanjouw (1995) ‘Aggregating Consumption
Components and Setting Demographic Scales:
Implications for Measured Poverty in Ecuador’, mimeo,
DECRG.
Lanjouw, J. and Lanjouw, P. (2002) How to Compare
Apples and Oranges: Poverty Measurement Based on
Different Measures of Consumption, Review of Income
and Wealth 47(1), 25-42.
Deaton, A. and Zaidi, S. (1999) ‘Guidelines for
Constructing Consumption Aggregates for Use as a
Money-Metric Welfare Measure’, LSMS working paper No
135.
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Deaton, A. and Paxson, C. (1998) Economies of
Scale, Household Size and the Demand for Food,
Journal of Political Economy, 106(5): 897-930.
Lanjouw, P.F. and Ravallion, M. (1995): Poverty and
Household Size, Economic Journal, Vol 105, No.
433.
Lanjouw, J., Lanjouw, P., Milanovic, B., and
Paternostro, S. (2004) Economies of Scale and
Poverty: the Impact of Relative Price Shifts During
Economic Transition, Economics of Transition 12(3)
509-536.