Flavio Cunha

Estimating the Technology of Cognitive and Noncognitive Skill Formation.

This paper formulates and estimates multistage production functions for childrens cognitive and noncognitive skills. Skills are determined by parental environments and investments at different stages of childhood. We estimate the elasticity of substitution between investments in one period and stocks of skills in that period to assess the benefits of early investment in children compared to later remediation. We establish nonparametric identification of a general class of production technologies based on nonlinear factor models with endogenous inputs. A by-product of our approach is a framework for evaluating childhood and schooling interventions that does not rely on arbitrarily scaled test scores as outputs and recognizes the differential effects of the same bundle of skills in different tasks. Using the estimated technology, we determine optimal targeting of interventions to children with different parental and personal birth endowments. Substitutability decreases in later stages of the life cycle in the production of cognitive skills. It increases slightly in later stages of the life cycle in the production of noncognitive skills. This finding has important implications for the design of policies that target the disadvantaged. For some configurations of disadvantage and for some outcomes, it is optimal to invest relatively more in the later stages of childhood than in earlier stages.

Formulating, Identifying and Estimating the Technology of Cognitive and Noncognitive Skill Formation

This paper estimates models of the evolution of cognitive and noncognitive skills and explores the role of family environments in shaping these skills at different stages of the life cycle of the child. Central to this analysis is identification of the technology of skill formation. We estimate a dynamic factor model to solve the problem of endogeneity of inputs and multiplicity of inputs relative to instruments. We identify the scale of the factors by estimating their effects on adult outcomes. In this fashion we avoid reliance on test scores and changes in test scores that have no natural metric. Parental investments are generally more effective in raising noncognitive skills. Noncognitive skills promote the formation of cognitive skills but, in most specifications of our model, cognitive skills do not promote the formation of noncognitive skills. Parental inputs have different effects at different stages of the child’s life cycle with cognitive skills affected more at early ages and noncognitive skills affected more at later ages.

The Economics and Psychology of Inequality and Human Development

Recent research on the economics of human development deepens understanding of the origins of inequality and excellence. It draws on and contributes to personality psychology and the psychology of human development. Inequalities in family environments and investments in children are substantial. They causally affect the development of capabilities. Both cognitive and noncognitive capabilities determine success in life but to varying degrees for different outcomes. An empirically determined technology of capability formation reveals that capabilities are self-productive and cross-fertilizing and can be enhanced by investment. Investments in capabilities are relatively more productive at some stages of a childs life cycle than others. Optimal child investment strategies differ depending on target outcomes of interest and on the nature of adversity in a childs early years. For some configurations of early disadvantage and for some desired outcomes, it is efficient to invest relatively more in the later years of childhood than in the early years.

Chapter 12 Interpreting the Evidence on Life Cycle Skill Formation

Abstract This paper presents economic models of child development that capture the essence of recent findings from the empirical literature on skill formation. The goal of this essay is to provide a theoretical framework for interpreting the evidence from a vast empirical literature, for guiding the next generation of empirical studies, and for formulating policy. Central to our analysis is the concept that childhood has more than one stage. We formalize the concepts of self-productivity and complementarity of human capital investments and use them to explain the evidence on skill formation. Together, they explain why skill begets skill through a multiplier process. Skill formation is a life cycle process. It starts in the womb and goes on throughout life. Families play a role in this process that is far more important than the role of schools. There are multiple skills and multiple abilities that are important for adult success. Abilities are both inherited and created, and the traditional debate about nature versus nurture is scientifically obsolete. Human capital investment exhibits both self-productivity and complementarity. Skill attainment at one stage of the life cycle raises skill attainment at later stages of the life cycle (self-productivity). Early investment facilitates the productivity of later investment (complementarity). Early investments are not productive if they are not followed up by later investments (another aspect of complementarity). This complementarity explains why there is no equity-efficiency trade-off for early investment. The returns to investing early in the life cycle are high. Remediation of inadequate early investments is difficult and very costly as a consequence of both self-productivity and complementarity.

The Identification and Economic Content of Ordered Choice Models with Stochastic Thresholds

This paper extends the widely used ordered choice model by introducing stochastic thresholds and interval-specific outcomes. The model can be interpreted as a generalization of the GAFT (MPH) framework for discrete duration data that jointly models durations and outcomes associated with different stopping times. We establish conditions for nonparametric identification. We interpret the ordered choice model as a special case of a general discrete choice model and as a special case of a dynamic discrete choice model.

The Evolution of Inequality, Heterogeneity and Uncertainty in Labor Earnings in the U.S. Economy

A large empirical literature documents a rise in wage inequality in the American economy. It is silent on whether the increase in inequality is due to greater heterogeneity in the components of earnings that are predictable by agents or whether it is due to greater uncertainty faced by agents. Applying the methodology of Cunha, Heckman, and Navarro (2005) to data on agents making schooling decisions in different economic environments, we join choice data with earnings data to estimate the fraction of future earnings that is forecastable and how this fraction has changed over time. We find that both predictable and unpredictable components of earnings have increased in recent years. The increase in uncertainty is substantially greater for unskilled workers. For less skilled workers, roughly 60% of the increase in wage variability is due to uncertainty. For more skilled workers, only 8% of the increase in wage variability is due to uncertainty. Roughly 26% of the increase in the variance of returns to schooling is due to increased uncertainty. Using conventional measures of income inequality masks the contribution of rising uncertainty to the rise in the inequality of earnings for less educated groups.

Early life height and weight production functions with endogenous energy and protein inputs

Highlights • We estimate height and weight production functions for infants.• We focus on the role of energy and protein intake.• We use IV to control for endogeneity and estimate a number of models.• The results indicate that protein play an important role in height and weight change.

Decomposing Trends in Inequality in Earnings into Forecastable and Uncertain Components.

A substantial empirical literature documents the rise in wage inequality in the American economy. It is silent on whether the increase in inequality is due to components of earnings that are predictable by agents or whether it is due to greater uncertainty facing them. These two sources of variability have different consequences for both aggregate and individual welfare. Using data on two cohorts of American males, we find that a large component of the rise in inequality for less skilled workers is due to uncertainty. For skilled workers, the rise is less pronounced.

Subjective Rationality, Parenting Styles, and Investments in Children

I argue that a model in which parents act with subjective rationality is consistent with the evidence on parenting styles, investments, and child development described by Kalil (Chap. 5). By rationality, I mean that investment in children and parenting style choices can be explained by a model of optimization under constraints. By subjective, I mean that parents rely on their own assessments about the constraints in order to make choices. Data that motivate these assumptions and confirm the implications of the model are presented. The model generates new insights about policies to foster the development of children’s human capital.

You Are What Your Parents Think: Height and Local Reference Points

Recent estimates are that about 170 million children under i¬ ve years of age are stunted, with signii¬ cant long-run negative consequences on their schooling, cognitive skills, health and economic productivity. Understanding what determines such growth retardation,therefore, is very important. We build a structural model for nutritional choices and height growth with reference–dependent preferences. Parents care about the relative height of their child compared to some reference population. In our empirical model, reference height is an equilibrium object determined by the parental nutritional choices for earlier cohorts in the same village. Taking advantage of a protein-supplementation experiment in Guatemala, we use exogenous variations in differential height growth paths between treated and control villages to estimate the model. We conduct a number of counterfactual policy simulations. First, we i¬ nd that reference point changes account for up to 60% of the 1.7 cm in height difference between experimental and control villages at 24 months of age. Second,focusing on one-period effects, to obtain the same mean effects as an 1 cm increase in reference points would require a protein-price discount of 37 percent or an income increase of 60 percent. Third, endogenous reference points changes lead to signii¬ cant policy spillovers: under poor-targeted subsidy policies, richer households over time gain up to 50 percent of the height gains of poorer households; under an universal subsidy policy, poorer households’ height gains increase from an initially low level by up to 4.8 times across periods as richer households,who also receive subsidies, help push up height reference points.