ranges from 1 (lowest) to 10 (highest), and is represented by 0 if, in a year, there was no MEPV registered. The data set covers 1960 to 2012.

One aim is to categorize individuals, in a reasonable fashion, based on the intensity of their exposure to MEPVs in early adulthood using equation (1). However, the paper first addresses the fact that the intensity of MEPV exposure in young adulthood, by construction, may be endogenous. The median share of the urban population in the country is therefore used over the early adulthood years of individuals as an instrument to circumvent this potential endogeneity.<sup>17</sup> (This issue is discussed in appendix A.) The data for the urban population share in the country are from the World Development Indicators database.<sup>18</sup> Once the endogeneity issue has been addressed, the intensity of MEPV exposure index is computed residually.<sup>19</sup> To categorize individuals based on the intensity of their exposure, the sample is split into terciles, and t-tests are performed. The t- statistics indicate there is no significant difference between the two lower terciles. Therefore, individuals with (residually computed) MEPV exposure indexes in the upper tercile are considered to have experienced MEPVs at a high intensity in young adulthood, while the result is a 0 (no or low-intensity MEPV exposure in young adulthood) among those in the two lower terciles. The residually defined MEPV index for those in the upper tercile is between 0.74 and 1.00.<sup>20</sup> For the parametric and nonparametric analysis, the circumstance variables include the social background of the fathers of the individuals and a dummy for the intensity of MEPV exposure in early adulthood. The set of circumstances therefore identifies eight types, that is, the results of four father social backgrounds, times two MEPV exposure intensities. As noted by Ferreira and Gignoux (2008, 2011), the number of categories for each circumstance (here, the social background of fathers and the intensity of MEPV exposure in early adulthood) is restricted to four or fewer to reduce the number of types exhibiting zero or few observations in the sample. This is highly relevant for the nonparametric analysis, which relies on the precision of the estimates of conditional means for each type (or cell of the partition). A description of the sample, along with summary statistics on earnings (the main dependent variable) and the circumstance variables, is presented in the next subsection.

# **Summary Statistics**

Appendix B, table B.1 presents the breakdown of the final sample by the social backgrounds of fathers, the social characteristics of the individuals, and the circumstance categories. A look at the

> 17 The rationale for using the share of the median urban population over the individual’s early adulthood years is in �� line with the argument laid out above, that is, to ensure that �� �0 in equation (1) holds for every individual.

> 18 See WDI (World Development Indicators) (database), World Bank, Washington, DC, http://data.worldbank.org/products/wdi.

> 19 The fractional logit estimation technique is used because the dependent variable, the intensity of MEPV exposure, is bounded between 0 and 1 (Papke and Wooldridge 1996).

> 20 Rankings of individuals in the initial MEPV index compared with rankings using the residually determined MEPV index, with the respective cutoff measures (upper tercile versus two lower terciles), are stable. The kappa coefficient is about 0.9, indicative of an almost perfect agreement (Viera and Garett 2005).

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