ment growth across over 600 industries is plausibly uncorrelated with local economic shocks or unobserved local factors, affecting local employment growth only through the industry composition at the local level.<sup>2</sup> Our data – administrative data on BF beneficiaries as well as matched employer-employee data on formal employment – enables us to follow movements in and out of BF as well as formal dependent employment without interruption from 2012 up to 2019.<sup>3</sup> Our primary results suggest that local employment growth leads to a small – yet statistically significant – increase in the probability of beneficiary families leaving the BF program. A 10% growth in local employment raises the exit probability by 0.342 percentage points, increasing the average transition rate of program exit from 8.61% to 8.69%. In addition, we find that these exogenous “rising tides” at the local level cause an increase in the probability of having at least one adult family member in a formal dependent job. Several robustness checks, such as replicating the analysis at the municipality level and checking for administrative capacities of the local authorities confirm our results.

Those findings indicate that the poor are responsive to local improvement in the labor market and confirm that a program can be operated in ways that are responsive to such income changes.<sup>4</sup> Nevertheless, the small size of the effects also highlights the relevance of policies that strengthen the capabilities and support of the poor to seize labor market opportunities.<sup>5</sup> Heterogeneity analysis of our results, in fact, shows that exits are concentrated among those households that are less likely to face labor force participation constraints, with fewer young children and more spare adult labor. This is consistent with the descriptive findings of another recent study on the family-level correlates of the BF benefit duration (Morgandi _et al._ , 2023).

The question is highly relevant for governments in many developing countries. After deploying CCTs on a large scale, often as a response to economic downturns, policymakers are now facing new challenges connected with their institutionalization. For programs to include new cohorts of young eligible beneficiaries, policymakers need to establish exit criteria that do not reverse the program’s gains. The prevailing practice in high-income countries has been to link

> 2Using the leave-one-out estimator we calculate the national growth rate by excluding the local growth rate of the municipality we are calculating the instrument for. Thus, we rule out that the national growth rate is driven by the local growth rate. Given the large number of municipalities the scenario is unlikely, however, the strategy increases the credibility of our instrument.

> 3Our analysis stops in 2019 since re-certification requirements were suspended in 2020-2021 due to the COVID19 pandemic.

> 4Exiting BF voluntarily enables the option of a guaranteed return to the program. If people exit through cross-checks they need to reapply to the program and might be subject to a waiting list. When individuals graduate from the program obtaining formal dependent employment they are eligible to other in-work benefits such as the family benefit _Salario Familiar_ .

> 5Mourelo and Escudero (2017) show that active labor market policies integrated in cash transfer can increase the probability of having a formal job.

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