# **Interaction between Parent’s Education and Occupation: Complementary, Substitutes or Separable?**

An important advantage of the empirical models discussed above is that they provide a straight-forward way to test the nature of interaction between parent’s occupation and education in determining intergenerational persistence in schooling. Consider, for example, the estimating equation (13) above; from the theoretical analysis in section (2), it is easy to derive the conditions under which parental education and non-farm occupation can be complementary, i.e., _λ_ 1 _>_ 0 implying( _ψ_ 1<sup>_n> ψ_</sup> 1<sup>_f_</sup> ), substitutes, i.e., _λ_ 1 _<_ 0 implying ( _ψ_ 1<sup>_n< ψ_</sup> 1<sup>_f_</sup> ) , or separable, i.e., _λ_ 1 = 0 implying ( _ψ_ 1<sup>_n_=</sup><sup>_ψ_</sup> 1<sup>_f_</sup> ). The prevailing view among many observers is that nonfarm occupation and education are likely to be complementary in determining children’s education, leading to cumulative forces of inequality in educational attainment and income in villages in developing countries (see, for example, Rama et al. (2015)). Yet, to the best of our knowledge, there is no evidence in the literature on the existence and the nature of the interaction between parent’s education and occupation in determining children’s educational attainment. Also, without a formal model, the economic mechanisms behind the hypothesized complementarity cannot be assessed. According to the theoretical model above, such complementarity requires that returns to education for the parents is higher in non-farm occupations, i.e., _R_<sup>_pn_</sup> _> R_<sup>_pf_</sup> .<sup>26</sup> This is one of the predictions that we take to the data as a test of the importance of economic mechanisms underlying the observed pattern of intergenerational educational persistence.

# **(4) Data**

For our main empirical analysis, we use two exceptionally rich surveys that collected data on children irrespective of their residency status at the time of the survey. The data for rural India come from the Rural Economic and Demographic Survey (REDS) carried out by the National Council for Applied Economic Research, and the source of the data for rural China is the China Family Panel Studies (CFPS) implemented by the Institute of Social Science Survey unit of Peking University.<sup>27</sup>

> 26If private school locations are motivated by higher income associated with nonfarm activities, then school quality may also play a role in generating complementarity. In this case, the productivity of parental investment _θ_ 2 will be correlated with occupation, i.e., _θ_ 2<sup>_n> θ_</sup> 2<sup>_f_.</sup> 27One might wonder why we chose not to use the IHDS 2012 round survey for India which would provide a survey year close to the survey year of CFPS in China. The CFPS and REDS are the most comparable in that they provide _a random sample of parents_ with information on all their children irrespective of the residency status of a child at the time of the survey. The IHDS, in contrast, contains _a random sample of children_ with information on their parents irrespective of their residency status at the time of the survey.

14