EARNINGS FUNCTIONS AND RATES OF RETURN

The internal rate of return to schooling is a fundamental economic parameter that is often used to assess whether expenditure on education should be increased or decreased. This paper considers alternative approaches to estimating marginal internal rates of return for different schooling levels. We implement a general nonparametric approach to estimate marginal internal rates of return that take into account tuition costs, income taxes and nonlinearities in the earnings-schooling-experience relationship. The returns obtained by the more general method differ substantially from Mincer returns in levels and in their evolution over time. They indicate relatively larger returns to graduating from high school than from graduating from college, although both have been increasing over time.

Earnings Functions, Rates of Return and Treatment Effects: The Mincer Equation and Beyond

This paper considers the interpretation of "Mincer rates of return." We test and reject the Mincer model. It fails to track the time series of true returns. We show how repeated cross section and panel data improves the ability of analysts to estimate the ex ante and ex post marginal rate of returns. Accounting for sequential revelation of information calls into question the validity of the internal rate of return as a tool for policy analysis. The large estimated psychic costs of schooling found in recent work helps to explain why persons do not attend school even though the financial rewards for doing so are high. We present methods for computing distributions of ex post and ex ante returns.

Earnings Functions and Rates of Return

The internal rate of return to schooling is a fundamental economic parameter that is often used to assess whether expenditure on education should be increased or decreased. This paper considers alternative approaches to estimating marginal internal rates of return for different schooling levels. We implement a general nonparametric approach to estimate marginal internal rates of return that take into account tuition costs, income taxes and nonlinearities in the earnings-schooling-experience relationship. The returns obtained by the more general method differ substantially from Mincer returns in levels and in their evolution over time. They indicate relatively larger returns to graduating from high school than from graduating from college, although both have been increasing over time.schooling, marginal internal rate of return, nonparametric estimation

2011-02 Estimating and Testing Non-Linear Models Using Instrumental Variables

In many empirical studies, researchers seek to estimate causal relationships using instrumental variables. When few valid instruments are available, researchers typically estimate models that impose a linear relationship between the dependent variable and the endogenous variable, even when the true model is likely to be non-linear. In the presence of non-linearity, ordinary least squares (OLS) and instrumental variable (IV) estimators identify different weighted averages of the underlying marginal causal effects, so the traditional Hausman test (applied to mis-specified linear models) is uninformative about endogeneity. We build on this insight to develop a new exogeneity test that is robust to non-linearity in the endogenous regressor. This test compares the IV estimator applied to the mis-specified linear model with an appropriately weighted average of all marginal effects estimated from the correctly specified non-linear model using OLS. Notably, our test works well even when only a single valid instrument is available, and the true model cannot be estimated using IV methods. We re-visit three recent empirical examples to show how the test can be used to shed new light on the role of non-linearity