the historic record of a set of variables related to the composition of the household and to the cash transfers it received.

We have constructed our treatment variable using seven available variables in the ENCEL panel:<sup>36</sup> (1) the length of exposure for households (period in which the households appear as beneficiaries of the program), (2) the total amounts transferred into a household up until 2003, 2007 and 2017, (3) the number of people comprising of a household (excluding “temporary” members), (4) the number of youths in a household of primary school age, (5) the number of youths in a household of secondary school age, (6) the number of youths in a household of high school age, and (7) the number of elderly adults in a household.

It is important to note that estimating the degree of exposure of the households to the program in this manner is similar, in spirit, to the strategies that use deterministic functions of exogenous variables.<sup>37</sup> The main difference of this study with other efforts to estimate the effects of the program is that, instead of calculating years of eligibility according to the individual’s age or potential transfers in accordance with family composition, it is estimated empirically, taking advantage of ENCEL’s complete panel, allowing a better partitioning of the working sample in order to differentiate the types of households that are statistically homogeneous, according to their historic domestic arrangements and cash transfers received from the program.<sup>38</sup> We consider that the empirical correlation between the households’ composition and the temporal distribution of the transfers hardly reflects the disposition of certain type of families with some parents being more concerned over their children than others, or children with having greater cognitive abilities or being better adapted to school life. Rather, correlation is a result of households’ observance of the operational rules of the program over time. Therefore, we take the resulting latent classes as groups of households with different intensities of exposure to PROSPERA.

The results of the latent classes analysis strongly suggest that a model with two classes fits the data well, and that a model with three classes does not provide an additional improvement in fit with the data (see Appendix B). Based in this analysis, we have determined that the model of two classes is most accurate for our study.

According to the results of our selected model, the association of the latent class variable is strong and meaningful.<sup>39</sup> The class which was labeled as being low treatment intensity has consistently produced higher probabilities of having smaller household sizes, with fewer youths of school-age, fewer elderly adults, histories (7%) of shorter participation in the program and, correspondingly, a lower volume of cash transfers (34% per household and 10% per adult equivalent using a uni-parametric scale), in comparison with the other class. This class groups

> 36 It is important to note that each of these variables is in the ENCEL panel with different periodicity and pattern of missing values.

> 37 See Kugler and Rojas (2018) and Fernald, Gertler and Neufeld (2010).

> 38 The evaluation of the potential transfers is a particularly complex task since there is no information in the panel between 2007 and 2017.

> 39 The details of the 293 parameters evaluated are not shown for brevity, but they are available to interested readers if requested from the authors of this study.

22