and zero for 1998 (before the law was passed), and ��� denotes an idiosyncratic error term. For this regression, we also include as control the individual ́s age (in weeks). In our second regression, �� takes the value of 1 if individual _i_ in cohort c turned age 14 in the first semester of 1999 and 0 if (s)he belongs to the cohort that turned 14 in the second half of 1998. Table 1 shows the groups under comparison in each case. Because the data provides exact dates of birth, we run the regressions using a 26 week-bandwidth (6month) as can be inferred from table 1.

In both regression models, the parameter of interest,  , provides the intent-totreat (ITT) effect. In other words, the impact of the ban on the cohort hindered from participating in the formal labor force at age 14.

# **4. DATA & RESULTS**

The sample used in this paper is drawn from the Brazilian household surveys ( _Pesquisa Nacional por Amostra de Domicilios_ – PNAD) of 1998 and 1999. The PNAD is an annual household survey that covers around 100,000 households and about 320,000 individuals. It is a major source of microdata in Brazil, and is a nationally representative survey that contains detailed information on each household’s socio-economic characteristics, demographic data, household income, and labor force status. The Brazilian Bureau of Statistics (IBGE) provides the exact reference date for when data collection is carried out and we used that information to identify the treatment and comparison groups.<sup>9</sup> Our results are exclusive for urban areas.

We used three measures of child labor: labor force participation rates as a whole without distinguishing between sectors, participation in the formal labor force, and participation rates in the informal labor force.<sup>10</sup> Table 2 shows ITT estimates on child labor incidence and reports the mean for the comparison group before the change in law. As can be seen, participation rates among boys are much higher compared to girls, and predominantly informal. We could therefore expect a higher impact of the change in law on boys. The first block of table 2 compares different cohorts keeping the age differential constant, whereas the second block compares the same cohort before and after the change in law. The estimates are very similar and point to a reduction in child labor of 4 percentage points for boys. Compared to a different cohort, the fall in participation rates was of 36 percent over the comparison group. Instead, if we used participation rates of the comparison group one year before, the drop in participation rates approached 80 percent. In both cases, the effect is almost fully driven by a reduction in participation rates in the informal sector. We found no impact on girls.

# **CONCLUSION**

This paper contributes to the literature on the impact of child labor laws by delving into the short-term impacts of the Brazilian Constitutional Amendment of December

> 9 According to IBGE, the reference date is the last week of September. There can be some variability in the exact day, but it is usually September 26 or 27.

> 10 The dummy variable for labour force participation rates takes the value of 1 if the individual is either (1) employed or looking for a job or was an active worker in the week of reference but was prevented from working due to external causes in the week of reference, or (2) worked in the last 12 months, and zero otherwise. A formal worker is someone working with a work permit ( _carteira assinada_ ) issued by the Brazilian Ministry of Labour and zero otherwise, whereas an informal worker is someone who works without such permission. This definition does not include domestic servants. In Brazil, domestic servants are covered by a separate legislation.

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