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  • Table describes the characteristics of the household members

    2018-10-26

    Table 2 describes the characteristics of the household members in each group. Employment rates and the average number of weekly hours worked among PBF beneficiaries are higher for group A1 (men) and lower for group B1 (married women). On the other hand, the participation rate is very similar between married male beneficiaries and non-beneficiaries. The beneficiaries belonging to the group of married mothers are the youngest. Single or independent mothers, however, have higher average schooling levels. Table 3 shows the targeting ability of the PBF according to the income eligibility criterion by family groups. A family is considered eligible if monthly per capita household income is less than or equal to R$120.00. The PBF indicator variable is equal to one if the family declares to have a PBF beneficiary in the family. It is important to note that the targeting is imperfect. A significant number of PBF beneficiaries did not meet the eligibility criterion and are still included in the program. In other words, their income is greater than R$120.00, but they still receive the benefit. Assuming the PNAD information about income is accurate raises the question of whether individuals might be manipulating their income information in order to qualify for the program. In this case, assessments of the PBF\'s impact PBF on outcomes relied on the variation of participation in the program, based on the discontinuity of a running variable that determines the eligibility criterion will likely be biased. Fig. 2 shows the kernel density functions for the monthly net household income per capita of the PBF transfers in 2006. First, the average income of recipients is below the income cutoff for eligibility (R$120.00). Another important characteristic of recipient households is the existence of a larger concentration of observations below the cutoff value, compared to the distribution of non-recipients. Despite the greater proportion of beneficiaries among poor families, there are a non-negligible number of PBF participants whose monthly per capita household income is higher than the cutoff value. These characteristics raise two possibilities:
    Methodology
    Results
    Conclusions In this paper, we assessed the existence of eligibility status manipulation by individuals for participation in the PBF. Our goal was to investigate a possible channel for this type of manipulation through changes in the time allocation decisions of individuals. The PBF eligibility criterion establishes that Boc-Pro-OH manufacturer with a monthly family income per capita equal to or below R$120.00 are eligible for the program. Evidence of manipulation was obtained through the formal test proposed by McCrary (2008). We found that (i) there is a greater density of individuals immediately below the threshold level of the eligibility criterion for the PBF along the ex ante family income per capita distribution; (ii) individuals immediately below the threshold level of the eligibility criterion PBF are more likely to participate in the program; and (iii) individuals immediately below the threshold level of the eligibility criterion PBF are less likely to participate in the labor market, less likely to be employed, and work fewer hours in the labor market. Moreover, individuals who are less attached to the labor market are the ones associated with the manipulation of their eligibility status. Finally, most of the results are robust for different periods or at different cutoff points. Our findings contribute to two debates in the microeconomic development literature. First, there is a discussion of the best way to targeting social programs. The targeting mechanism can use objective information (e.g., household surveys) to construct means tests or proxy means tests, or subjective information directly from the individuals or communities, or even a combination of both source of information. There are trade-offs involved in this choice. The use of subjective information is more sensitive to shocks that change the eligibility status. On the other hand, it is more prone to misinformation or conflicting information. The use of objective information can be more verifiable but less sensitive to changes in the eligibility status. Moreover, there is a tarde-off between means tested and proxy means tested programs. The means tested targeting is more likely to incur in inclusion error whereas the proxies means tested targeting is more likely to incur in exclusion error. There are scant evidences on these trade-offs. Among the few ones, Alatas et al. (2012) show evidence of the trade-off between the uses of objective or subjective information. They run an experiment on Indonesia on three approaches to targeting the poor families: proxy means tests, community targeting where individuals rank everyone from richest to poorest, and a hybrid of both. They find that proxy means tests perform a little better in targeting the poor but community targeting results in better satisfaction perhaps because the apply a different concept of to being poor. Camacho and Conover (2011), on the other hand, show evidence of inclusion error from a program in Colombia where local politicians manipulate for their own interests the information collection from “poor” households in order to classify them to the central government welfare program. Different from these two studies, our results add to this debate by presenting new evidence of the cost of the use of proxy means tests through inclusion error driven directly by the manipulation of the households themselves.