Mexico’s Oportunidades: Self- Selection in Targeted Social Programs César Martinelli Professor of Economics, ITAM, Mexico City and Wilson Center/Comexi Public Policy Scholar and Susan W. Parker Professor of Economics, CIDE, Mexico City

Introduction  Conditional cash transfers (CCT) have become a major poverty alleviation strategy across Latin America Mexico, Honduras, Nicaragua, Jamaica, Colombia, Brazil, Argentina, Ecuador  Key innovation: condition grants to investment in children’s human capital Current and future poverty reduction goals, e.g. by improving HK of children today, expectation that future poverty will be reduced

Introduction, continues  How are beneficiaries selected, in context where income not observable? As in other social programs in developing countries, based on information provided by applicant Obvious incentives to misreport

Introduction, continues  According to economic theory, applicants will underreport given material incentives  Lying is consider immoral by many, perhaps most moral thinkers … need to look at the evidence  Stigma (social embarrassment) and self-deception may lead to overreporting

Objectives of paper  What is prevalence of misreporting in social programs?  Who misreports?  What impact on who receives benefits?

Objectives, continues  Previous studies limited by lack of information on misreporting  Take advantage of context where program verified economic conditions, allows us to compare reported with actual conditions

Description of Oportunidades  Large scale poverty alleviation program  Begun in 1997 in rural areas, expanded to urban areas in By 2004, 5 million beneficiary families (1/4 of all households)  Cash transfers conditional to investment in human capital Regular school attendance of children Regular clinic visits of family members Transfers given directly to mother Average monthly benefits: US$30, overall increase of 30% over monthly income

Description of Oportunidades cont.  Health and nutrition component: Basic health care package Fixed income linked to clinic attendance Nutritional supplements given to pregnant women and children aged 0 to 2 (or up to age 5 if malnutrition perceived)

Monthly Benefits

Description of Oport. cont.  Targeting differs between rural and urban Oportunidades  Rural targeting: Geographic: poor communities identified using community poverty index Household: ALL HH in eligible communities applied socio-economic questionnaire, regression analysis (proxy means test) carried out to determine who was poor/eligible on basis of characteristics

Description of Oport. cont.  Urban areas: interviewing all households deemed too costly, Self-selection introduced  Urban targeting: Geographic: poor urban areas identified Program modules set up in poor areas during 2 months, where household go to apply for benefits Households applied socio-economic questionnaire in the module, based on answers, households declared initially eligible Initially eligible HH receive follow up visit to verify info reported in module. Final classification made

Issues in Self-Selection 1. Who is aware of the program? 2. Who applies to the program? 3. How is eligibility determined?... at these three stages it is possible to introduce mistakes (give program to who is “not poor” or deny it to who is “poor”) We focus on stage 3 in this talk— stages 1 and 2: work in progress

Eligibility: Poverty Regression  Problem to determine who is “poor”: unreliability of income or consumption data  Methodology: poverty regression… search for observable household characteristics that are correlated with income and estimate a “poverty score”

Oportunidades poverty regression (poor: score ≥ 0.69)  Family size/number of rooms  Family size  Female head  Number of children below 11  Head has no schooling  1 to 5 years of schooling  Age head (years)  No toilet  Toilet w/o running water  Unpaved floor  No gas boiler  No refrigerator  No washing machine  Neither car nor truck  Rural area  Region  Constant                 From to 0 

Selection of urban beneficiaries  Applicants to Oportunidades were asked to answer questionnaire about household characteristics  Self-report was used to determined preliminary eligibility using poverty regression  Household visits to verify answers to questionnaire and assess definitive eligibility status

Data ENCASURB: 1. Inclusion questionnaire, carried out at the module 2. Additional questionnaire after initial eligibility determines, carried out at the module 3. Verification questionnaire, carried out at household

Characteristics of applicants

Definitions For each good g,  A g : applicants who assert having it  D g : applicants who deny having it  H g : found having the good  N g : found not having the good Then:

A model of misreporting w g : belief of applicant about weight of good g in poverty score δ: applicant’s assessment of probability of verification visit p: belief about penalty for getting caught underreporting B a : (monthly) benefits from program for applicant’s household Y a : (monthly) household expenditure (as proxy for income) X a : education, age, gender, etc of applicant

A model of misreporting, continues

 Applicant underreport good g if  Applicant overreport good g if  Assumptions: Risk aversion coeff. = 1 Random terms are Gumbel distributed (i.e. use logit regressions)

Mg. effects of program benefits

Beliefs vs. true relative weights

Mg. effect of years of education

Male rather than female reporter

Underreporting vs. final status

Conclusions  Underreporting is widespread  Overreporting occurs for goods whose absence is associated with poverty—so have weight in poverty regression!  Both under and overreporting are sensitive to program benefits: evidence of a cost of lying and a stigma consideration (even in front of strangers!)  Need to revisit poverty regression methodology  More generally: room for cross-fertilization between social policy design and behavioral economics

Reference  Deception and Misreporting in a Social Program (by Cesar Martinelli and Susan Parker) available at