country.<sup>34</sup> Since the expansion of private schooling has been much larger in India compared to that in China during the study period, the value of _θ_ 2 is likely to be higher in India.

It is important to recognize that the “returns to education” for the parents (i.e., _R_<sup>_pj_</sup> ) differ from most of the available estimates of returns to education for three reasons. First, we are interested in the total income of all household members rather than the individual income (i.e., not only father’s income). Second, the focus of the existing literature has been on labor market returns, while our analysis requires both labor and non-labor income. Third, father’s education in our analysis is not only a measure of human capital, but a summary statistic for a family’s socio-economic status and captures the effects of other correlated factors, for example, mother’s education due to assortative matching in the marriage market.<sup>35</sup> Thus, we need a measure of permanent household income.

The Chinese Household Income Project (CHIP) provides us with high quality household income data for rural households for multiple years (5 years in CHIP 2002, and 3 years in CHIP 1995).<sup>36</sup> Unlike China, the data on household income in rural India are, however, more limited; we are not aware of any household survey data set that has good quality income information for consecutive multiple years, similar to the CHIP data on China. We thus take household expenditure reported in the National Sample Survey as our measure of household permanent income.

Table 4 (panel A) provides estimates of household-level returns to education, _R_<sup>_pn_</sup> and _R_<sup>_pf_</sup> , in rural China and tests the null hypothesis that _R_<sup>_pn_</sup> = _R_<sup>_pf_</sup> using data from two rounds (1995 and 2002) of the Chinese Household Income Project (CHIP) survey. The standard errors are clustered at the primary sampling unit (county). The estimates based on the 5-year average income of a household in CHIP 2002 data in the last two columns of Table 4 show that the null hypothesis cannot be rejected with a P-value equal to 0.58.<sup>37</sup> The evidence from the 1995 data (three year average income) also delivers a similar conclusion: the null hypothesis cannot be rejected with a P-value of 0.33.<sup>38</sup> The conclusion that

> 34To see this clearly, consider the polar case where schooling is provided only by the government free of charge and there is no private schools (or private tutoring). In this case, the scope for parental financial investment to improve a child’s educational attainment is effectively nonexistent, making _θ_ 2 ≈ 0. 35The available estimates on Mincerian labor market returns to education at the individual level in China show low returns in the early years after the reform, but there is evidence of increasing returns in the later years, as one would expect with the deepening of the labor market. The evidence also suggests higher labor market returns in nonfarm occupations (DeBrauw and Rozelle (2008)).

> 36Note that the estimates of the effects of father’s education on household permanent income using CHIP data do not suffer from truncation bias, unlike the estimates of intergenerational persistence; whether some of the children were nonresident at the time of the survey is not relevant for this analysis.

> 37The 5 year income data cover from 1998 to 2002 in the CHIP 2002.

> 38The 3 years income data in CHIP 1995 cover 1991, 1993, and 1995.

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