not significant at conventional levels, they are consistent with a pattern whereby the BDH lottery affected spending on education and school attainment.

The second panel of Table 4 focuses on child work. Approximately 54 percent of children in the control group were working at the time of the follow-up survey, a number that is about 8 percentage points higher than at baseline; once again, the ageing of the study population accounts for these patterns. As with the schooling measures, there are substantial numbers of children who stop working or start to work during the study period. Turning to the effects of winning the BDH lottery, the coefficients in Table 4 show that the probability of working is approximately 5.4 to 6.2 percentage points lower for lottery winners; lottery winners are also more likely to stop working during the study period, and less likely to start working.

The third panel in Table 4 reports the results from Tobit regressions of hours worked. These coefficients suggest that children who won the lottery worked approximately two-and-ahalf hours less than other children. Estimates from CLAD regressions are larger, although less precise (the coefficient on lottery winners is -4.03, with a standard error of 2.55); those from OLS regressions are generally smaller (the coefficient is -0.84, with a standard error of 0.57).<sup>13</sup> The general pattern suggests that children who won the BDH lottery worked fewer hours, although there is some uncertainty about the magnitude of the changes.

A comparison of the enrollment and child work results from specifications with more or less controls shows that the coefficients on lottery winners are reasonably insensitive to the addition of covariates—in some cases, the coefficients go up (in absolute value), in other cases they go down. The absence of systematic changes is not a result of the lack of explanatory power of the additional covariates: For example, the R-squared in the enrollment regression goes up from 0.187 in the specification with basic controls, to 0.356 in the specification with extended controls, and to 0.370 in the specification that includes canton fixed effects; these patterns are similar for other outcomes. The fact that the coefficient of interest does not change systematically as more covariates are included in the regression provides further evidence that the randomized assignment into treatment and control groups was successful.

> 13 The reported CLAD estimates are based on regressions with the full set of controls, with a continuous variable in age instead of the age fixed effects; the reason for this is that we had convergence problems when we included either the age dummies or the canton fixed effects.  The Tobit coefficient for a comparable specification is -2.36, with a standard error of 0.97.  This is very close to the coefficients in Table 4, which suggests that replacing the age dummies with the continuous variable in age does not substantively alter the estimated effects.  Standard errors in the CLAD estimates are bootstrapped, and take account of within-sibling correlations.  The OLS estimates are based on regressions with the full set of controls and canton fixed effects.

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