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Working papers

  • Eliciting Maternal Beliefs about the Technology of Skill Formation (with Irma Elo and Jennifer Culhane).
    • In this paper, we formulate a model of early childhood development in which mothers have subjective expectations about the technology of skill formation. The model is useful for understanding how maternal knowledge about child development affects the maternal choices of investments in the human capital of children. Unfortunately, the model is not identified from data that are usually available to econometricians. To solve this problem, we conduct a study where mothers were interviewed to elicit maternal expectations about the technology of skill formation. We interviewed a sample of socioeconomically disadvantaged African-American women. We find that the median subjective expectation about the elasticity of child development with respect to investments is between 4% and 19%. In comparison, when we estimate the technology of skill formation from the CNLSY/79 data, we find that the elasticity is between 18% and 26%. We use the model and our unique data to answer a simple but important question: What would happen to investments and child development if we implemented a policy that moved expectations from the median to the objective estimates that we obtain from the CNLSY/79 data?  According to our estimates, maternal investments would go up by between 4% and 24% and the stocks of cognitive skills at age 24 months would subsequently increase between 1% and 5%. Needless to say, the impacts of such a policy would be even higher for mothers whose expectations were below the median.
  • The Production of Child Human Capital: Endowments, Investments, and Fertility (with Anna Aizer).
    • We study how endowments, investments and fertility interact to produce human capital in childhood. We begin by providing empirical support for two key features of existing models of human capital: that investments and existing human capital are complements in the production of later human capital (dynamic complementarity) and that parents invest more in children with higher endowments due to the complementarity between endowments and investments (static complementarity). For the former, we exploit an exogenous source of investment, the launch of Head Start in 1966, and estimate greater gains from preschool in the IQ of those with the highest stocks of early human capital, consistent with dynamic complementarity. For the latter, we are able to overcome the potential endogeneity and measurement error associated with traditional measures of endowment based on health at birth. When we do, we find that parents invest more in highly endowed children. Moreover, we find that the degree of reinforcement increases with family size. Thus, an increase in quantity leads not only to a decline in average quality (the quantity-quality tradeoff) but to an increase in the variation in quality, due to both greater variation in endowments (from more children) and greater reinforcing investments. These findings can be explained by extending the quantity-quality trade-off model to include heterogeneous child endowments and parental preferences that feature complementarity between quality and quantity and moderate aversion to inequality in child human capital within the household.
  • Gaps in Early Investments in Children.
    • The human capital profiles of children start to diverge at an early age. Part of this divergence is explained by the differences in the environment that children experience early in their lives. This paper proposes a simple model to quantify the importance of four determinants of early investments: (i) heterogeneity in budget sets; (ii) heterogeneity in preferences; (iii) heterogeneity in the beliefs about the technology of skill formation; and (iv) heterogeneity in human capital at birth. This quantification is important to inform the design of policies that can be implemented should policymakers choose to act to reduce inequality in outcomes. I find that heterogeneity in preferences and beliefs plays an important role in explaining gaps in investments. I discuss possible interpretations of the findings as well as their policy implications.
  • Investments in Children when Markets Are Incomplete (new version coming soon).
    • This paper proposes a model of investments in the cognitive skills of children that is based on three features: that it takes time to build a child's stock of cognitive skills; that parental resources evolve stochastically over time; and that parents face constraints that limit their ability to transfer resources across states of nature, across time, and across generations. These constraints distort the equilibrium allocation of investments throughout a child's life and, in turn, produce sub-optimal stocks of cognitive skills. In order to verify the quantitative importance of these distortions, I estimate the model's key parameters and I compute its steady-state equilibrium. I show that the empirically- grounded steady-state explains a variety of facts about cognitive skills, education, and child development. For example, it correctly predicts selection into college by quartiles of family income and terciles of skills measured at adolescent years. Moreover, it is consistent with gaps in cognitive skills that are present at early ages. Finally, it reproduces the pattern of selection into college based on cognitive skills. I use the model to evaluate the impact of different remediation policies on the stationary distribution of cognitive skills and welfare. I analyze the effects of a 50% tuition subsidy, a targeted early investment subsidy, and a targeted early and late investment subsidy that is contingent on parental resources. I show that the policy that subsidizes early and late childhood investments dominates the other policies in welfare, since it is the one that generates the highest equivalent variation across all deciles of permanent income. This also generates a stationary distribution of cognitive skills that first-order stochastically dominates the ones generated by the baseline economy and the other remediation policies.

© Flávio Cunha / 713 348 3312 / Flavio.Cunha at rice dot edu

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