BENEFIT INCIDENCE ANALYSIS FOR PUBLIC CHILD HEALTH AND NUTRITION PROGRAMS IN PERU

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BENEFIT INCIDENCE ANALYSIS FOR PUBLIC CHILD
HEALTH AND NUTRITION PROGRAMS IN PERU

• Martín Valdivia

February 2004
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Description of the study

• Analyze the targeting performance of 3 of the
  largest public food transfer programs for
  children in Peru
• School Breakfast (SB)
• Vaso de Leche (VL) - Glass of Milk
• Aggregate of food transfer programs for children
  under 3 (PANFAR, PACFO, PAI, wawa-wasi/PRONOEI)
• Uses individual data instead of household data
• Allows to identify leakages within the household
  when specific age groups are identified and
  consumption occurs at home
• Test the robustness of targeting measures
  (undercoverage, leakage) to changes in
• The specific poverty line assumed and
• The size and scale of the program

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Summary of analyzed programs
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Size of analyzed programs

• These programs concentrated over the 80 of
  public resources allocated to food programs by
  the year 2000

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Coverage of social programs by quintile
household vs individual samples

• Analysis at the household level suggests a much
  larger pro-poor bias for all programs
• In both cases, the CHOFP aggregate shows the
  largest pro poor bias

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Targeting errors Leakage and undercoverage

• Undercoverage proportion of programs target
  population that does not receive a transfer.
  Leakage Proportion of program beneficiaries that
  are not part of the target population
• VL program stands as the program with worst
  leakage, especially in urban areas
• There does not seem to be any systematic relation
  between the size of the program and their
  targeting.

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Leakage within the household

• Target population is defined in 3 dimensions
• age
• school affiliation
• socio-economic status
• A leakage occurs not only when the beneficiary is
  from a non-poor household, but also because
  he/she is not from the target age group
• We can check the importance of each restriction
  by re-estimating the leakage rate while removing
  one restriction at a time

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Leakage rates under alternative set of
restrictions

• The age restriction is significantly much larger
  for the VL program and the CHOFP aggregate, which
  are programs that allow for consumption within
  the household.
• For VL program, 1 out of 4 leaks are poor but out
  of the age range
• For the CHOFP aggregate, almost 1 out of 2
• Result is consistent with findings in Alcazar
  et.al. (2003) using PETS, for VL
• The school restriction is not significant for
  neither the SB nor the SI program.

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Targeting errors and the poverty line

• Programs focus on the neediest and most
  vulnerable, but
• Poverty status is not unarbitrarily determined.
  For the purpose of the study, we use expenditure
  information and a poverty line, which is always
  arbitrarily determined
• More importantly, program officials do not use
  household surveys to identify the socio-economic
  level of the potential beneficiaries
• limited to geographic targeting instruments
• even with individual targeting instruments, they
  base their decision on some observable
  characteristics to determine the poverty level
  (proxy-means tests)
• Consequently, it is important to check if
  estimates of targeting performance change
  significantly as we move the poverty line

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Comparing social programs across the income
distribution

• Figure compares the concentration curves (CCs)
  for the four programs
• A CC plots the proportion of beneficiaries to the
  left of any point of the income distribution
• The CC of the CHOFP aggregate clearly dominates
  those of the rest of the programs,
• it can be said that CHOFP has the largest
  pro-poor bias, regardless of the level of the
  poverty line.
• No significant difference appears between the VL
  and SB programs

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Incidence analysis at the margin

• The proportion of poor and non-poor that benefit
  of a program at a given time may not be a good
  indicator of how an expansion, or contraction,
  would affect the poor.
• Positive participation costs can imply early or
  late capture of a program by the non-poor, if
  they differ for the poor and non-poor, and change
  with the scale of the program.
• The higher costs related to reaching more remote
  areas is often raised as the typical argument in
  favor of early capture.
• Late capture could result from the fact that
  small pilot projects are more carefully monitored
  and face less political pressures.

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Incidence analysis at the margin II

• We can follow Younger (2002) and use the
  heterogeneity across regions and over time to
  estimate the impact of a program expansion or
  contraction for the poor. The idea is to estimate
  the following equation
• The dependent variable is the program
  participation rate for quantile q in a given
  domain in a particular year. The explanatory
  variable is the program participation rate for
  the specific year.
• can be interpreted as the marginal effect of
  an increase in program participation at the
  national level on the participation rate in a
  particular quantile
• would indicate that a general
  expansion (contraction) in coverage will cause a
  more than proportional increase (reduction) in
  participation for that quantile

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Marginal Incidence Analysis (MIA) for the SB and
VL programs
School Breakfast 1997-2000

• We can estimate the so that they sum to
  five, and plot a marginal CC for each program
• Then, we can compare the marginal CCs with the
  average ones
• Disregarding the age restriction, both programs
  appear to be more pro-poor at the margin than on
  average
• These results suggest that, even though both
  programs show a mediocre targeting performance on
  the average, they seem to have a more pro poor
  behavior on the margin.
• This means that cutting (expanding) them would
  (benefit) the poorest more than proportionately

Vaso de Leche 1997-2000
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Summary of results and implications

• First, the age restriction is found to be very
  important for VL and CHOFP programs, which are
  the ones that allow for consumption within the
  household,
• The VL program stops being the one with the worst
  targeting performance and the CHOFP aggregate
  becomes by far the program with lowest leakage.
  (34)
• This result suggests that food programs that
  allow for consumption of the ration in the
  household are not able to impose their
  preferences on the distribution of the transfer
  across household members, regardless of the
  nature of the ration.
• Lack of consideration of these intra-household
  arrangements reduce the size of the transfer per
  capita and limit the possibility for them to have
  a nutritional impact on the target population.
  (consistent with Stifel and Alderman, 2003)

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Summary of results and implications II

• Second, I find that the SB and VL programs has a
  very pro-poor behavior at the margin despite
  having a very mediocre targeting performance on
  average (early capture)
• It suggests the need to be cautious about making
  decisions based on the average targeting
  performance of programs. They could show large
  leakages on the average, but still a cut
  (expansion) could damage (benefit) the poor more
  than proportionately
• One usual explanation is that programs start in
  more urban areas that are easier and less costly
  to reach

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Summary of results and implications III

• Nevertheless, it is important to look at delivery
  mechanisms organized for these programs
• In both cases, the central government assigns
  resources by district based on poverty map. Then,
  municipalities identify localities on a need
  basis. Within localities, mothers clubs define
  actual beneficiaries
• In practice, any mothers club that gets to be
  registered will never be retired as a
  beneficiary. Some with registered households
• Anecdotal evidence suggest the following new
  entrants tend to be from very poor localities
  but, as time passes, their economic situation
  improves but they cannot be taken out of the
  registry
• It is important to notice that any of these
  explanations take the priority away from
  improving proxy-means test instruments. The
  latter focus on the political economy behind
  delivery mechanisms

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