Linearity in Instrumental Variables Estimation: Problems and Solutions

The linear IV estimator, in which the dependent variable is a linear function of a potentially endogenous regressor, is a major workhorse in empirical economics. When this regressor takes on multiple values, the linear specification restricts the marginal effects to be constant across all margins. This paper investigates the problems caused by the linearity restriction in IV estimation, and discusses possible remedies. We first examine the biases due to nonlinearity in the commonly used tests for non-zero treatment effects, selection bias, and instrument validity. Next, we consider three applications where theory suggests a nonlinear relationship, yet previous research has used linear IV estimators. We find that relaxing the linearity restriction in the IV estimation changes the qualitative conclusions about the relevant economic theory and the effectiveness of different policies.linear model, variable treatment intensity, nonlinearity, instrumental variables

Household Choices and Child Development

The growth in labor market participation among women with young children has raised concerns about the potential negative impact of the mother's absence from home on child outcomes. Recent data show that mother's time spent with children has declined in the last decade, while the indicators of children’s cognitive and noncognitive outcomes have worsened. The objective of our research is to estimate a model of the cognitive development process of children nested within an otherwise standard model of household life cycle behavior. The model generates endogenous dynamic interrelationships between the child quality and employment processes in the household, which are found to be consistent with patterns observed in the data. The estimated model is used to explore the effects of schooling subsidies and employment restrictions on household welfare and child development.Time Allocation; Child Development; Household Labor Supply

What Linear Estimators Miss: Re-Examining the Effects of Family Income on Child Outcomes

This paper uses a rich Norwegian dataset to re-examine the causal relationship between family income and child outcomes. Motivated by theoretical predictions and OLS results that suggest a nonlinear relationship, we depart from previous studies in allowing the marginal effects on children’s outcomes of an increase in family income to vary across the income distribution. Our nonlinear IV and fixed-effect estimates show an increasing, concave relationship between family income and children's educational attainment and IQ. The linear estimates, however, suggest small, if any, effect of family income, because they assign little weight to the large marginal effects at the lower part of the income distribution.instrumental variables estimation, fixed effects estimation, nonlinearities, child development, family income, linear models

Policymakers must be mindful that transfers to households to support young children will also be used to finance parents’ leisure and consumption

There is a growing consensus among academics and policymakers that interventions in early childhood to improve cognitive skills help to boost those made later during adolescence. In new research, Daniela Del Boca, Christopher Flinn, and Matthew Wiswall find evidence to support these interventions, but they argue that policymakers need to understand that households do not act solely to maximize their child’s development. They write that while government transfers of money and goods to households to support young children will be used to support them, they may also be used by parents to finance their own purchases of consumption goods and leisure

Genes, Education, and Labor Market Outcomes: Evidence from the Health and Retirement Study

Recent advances have led to the discovery of specific genetic variants that predict educational attainment. We study how these variants, summarized as a genetic score variable, are associated with human capital accumulation and labor market outcomes in the Health and Retirement Study (HRS). We demonstrate that the same genetic score that predicts education is also associated with higher wages, but only among individuals with a college education. Moreover, the genetic gradient in wages has grown in more recent birth cohorts, consistent with interactions between technological change and labor market ability. We also show that individuals who grew up in economically disadvantaged households are less likely to go to college when compared to individuals with the same genetic score, but from higher socioeconomic status households. Our findings provide support for the idea that childhood socioeconomic status is an important moderator of the economic returns to genetic endowments. Moreover, the finding that childhood poverty limits the educational attainment of high-ability individuals suggests the existence of unrealized human potential