Table 1. Intergenerational mobility in height among the rural population of PROSPERA

||(1)||(2)||(3)||
|---|---|---|---|---|---|---|
|VARIABLES|OLS|Tobit|OLS|Tobit|OLS|Tobit|
|ln provider’s|0.483***|0.484***|0.422***|0.423***|0.411***|0.411***|
|height ()|(0.015)|(0.016)|(0.015)|(0.016)|(0.015)|(0.016)|
|Speaks|||||-0.010***|-0.010***|
|indigenous|||||(0.002)|(0.002)|
|language|||||||
|Migrant|||||0<br>(0.001)|-0.003*<br>(0.001)|
|Constant|2.656***|2.696***|2.956***|3.007***|3.017***|3.065***|
||(0.078)|(0.084)|(0.076)|(0.081)|(0.076)|(0.081)|
|Adjusted R<br>squared|0.566||0.584||0.589||
|Observations|4,385||4,161||4,161||

Notes: _(1)_ = Estimations controlling by the young adult’s age and gender variables; provider’s age, gender and schooling. _(2)_ = in addition to the variables of (1), state of residence from the ENCEL, _marginalization_ (poverty) index in 1995 of the villages in the sample, and identification of the control or treatment village of the experimental evaluation of 1997-2000. (3)= in addition to the variables in (2), speaking and indigenous language and migrant. OLS= Ordinary least squares. Clustered standard errors in parentheses. Level of significance *** _p<_ 0.01, ** _p<_ 0.05, * _p<_ 0.1. Source: estimations performed based on data from the Evaluation of Rural Households Survey (ENCEL) 2017, complemented with data from the ENCEL panel 1997-2000.

The persistence coefficients (in provider’s height) are consistent, regardless of whether OLS is used or the Tobit models, corrected for censorship, are used. However, we observe that controlling for migration and indigenous background improves precision and thus statistical significance (model 2). The estimation that controls for state of residence and migration / indigenous background modifies the persistence coefficient. That is, controlling for the effects of the context increases the mobility potential, which we estimate as 58%. This coefficient is similar to the magnitude order observed for the case of the United States in a similar study (AkbulutYuksel and Kugler, 2016).

Indigenous background and migration are associated with lower height, although this does not significantly affect the estimate of persistence (Table 1, Column 3, Tobit estimations). Thus, it is expected that the mobility potential in height for these groups is of similar magnitude to the rest of the population.

In contrast to the educational mobility analysis, when analyzing health outcomes such as height, the persistence coefficient reflects both intergenerational mobility, and genetic and epigenetic components. In this case it is essential to incorporate in the analysis the kinship of the analyzed individuals with the individual identified as their provider in our data. When we restrict the sample to individuals, whose providers are their biological father or mother, the persistence coefficient increases slightly to 0.44. On the contrary, if the provider is not the father or the mother, the persistence coefficient decreases to 0.33 (estimations not shown). For the purposes of this analysis we interpret the difference in estimated mobility between these two samples, 0.11, as an approximation of the effect size attributable to genetics and heritable epigenetics.

For purposes of the analysis we use the full sample, considering both the cases where the individual and provider are and are not genetically related. We do this for several reasons: it 24