The Heckman model takes into account labor income censorship by estimating a model of the probability of earning labor income (in this case identified as the probability of labor participation), and uses this probability to correct the Mincer equation. This correction takes into account the relationship between income and the decision to work.

Due to the possible differences in labor participation by gender, separate models for males and females were estimated. In addition to the variables of the Mincer model we used an indicator for whether a member of the household is a child zero to five years of age, whether the individual has a partner, whether the individual cohabits with their partner, and for the household’s income excluding the income of the individual of analysis.

The argument for endogeneity between the human capital variables and income proposes that the person with more cognitive capacity may decide to invest more in building human capital, and that they would potentially be individuals with greater social connections, which could lead to better labor opportunities with greater income. This implies that the human capital variables would be correlated to the error term in the Mincer equation (Schultz, 2002). This problem can be solved with instrumental variables; variables that are strongly related to the independent variable, and not related to the dependent variable (McFadden, 1999).

The instrumental variables methods and estimation is presented in greater detail in Appendix D. First, we verified the presence of endogeneity using Durbin and Wu-Hausman’s tests. In both tests for years of study we find a p-value of 0.36, indicating that we cannot reject the null hypothesis of exogeneity. However, in the test for height we find a p-value <0.01, indicating we reject the null hypothesis of exogeneity, and must treat height as an endogenous variable.

As in previous studies (Gutierrez, 2012; Ribero and Nuñez, 2000; Schultz, 2002), to instrument for height we use variables measured at the level of the village: the _marginalization_ (poverty) index of the villages in 1995 and in 2000, the total population of the villages, and 1998 prices of several food items: nixtamal (corn prepared for making tortilla dough), wheat flour, pasta, cookies, beans, eggs, sardines, sugar and oil.<sup>15</sup> We use an F test to test the capacity of the proposed instruments to explain the variability in height, finding that while not perfect, these instruments are reasonably strong. Finally, we tested for over-identification of the model that could result in the correlation with the error term, finding a chi square test with a p-value of 0.134, indicating that we do not reject the null hypothesis.

Using the instrumental variables for height, the estimated return model is: Where ln�W�� is the natural logarithm of the income per hour reported by individual _i_ ; S<sup>�</sup> � is the predicted value of the health indicator from the first stage instrumental variables regression and is expressed here as the natural logarithm of height, hence the coefficient, δ, is an elasticity; H� is a vector of household characteristics (including the provider); X� is a vector of individual characteristics; E� is an indicator of individual _i_ ’s labor participation; and Z� is a vector of individual characteristics that determine labor market participation.

> 15The prices were collected in the village questionnaire of the ENCEL 1998-March.  In the cases where the prices were not reported in the village, the average of the municipality (~ county) or state was used for the same.

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