This chapter discusses how applied researchers in corporate finance can address endogeneity concerns. We begin by reviewing the sources of endogeneity—omitted variables, simultaneity, and measurement error—and their implications for inference. We then discuss in detail a number of econometric techniques aimed at addressing endogeneity problems, including instrumental variables, difference-in-differences estimators, regression discontinuity design, matching methods, panel data methods, and higher order moments estimators. The unifying themes of our discussion are the emphasis on intuition and the applications to corporate finance.

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Endogeneity in Empirical Corporate Finance1

I survey the literature post Ledyard (Handbook of Experimental Economics, ed. by J. Kagel, A. Roth, Chap. 2, Princeton, Princeton University Press, 1995) on three related issues in linear public goods experiments: (1) conditional cooperation; (2) the role of costly monetary punishments in sustaining cooperation and (3) the sustenance of cooperation via means other than such punishments. Many participants in laboratory public goods experiments are “conditional cooperators” whose contributions to the public good are positively correlated with their beliefs about the average group contribution. Conditional cooperators are often able to sustain high contributions to the public good through costly monetary punishment of free-riders but also by other mechanisms such as expressions of disapproval, advice giving and assortative matching.

https://www.cepr.org/sites/default/files/events/papers/796_CHAUDHURI.pdf

Sustaining cooperation in laboratory public goods experiments: a selective survey of the literature

Two decades after its original publication, The Analysis of Household Surveys is reissued with a new preface by its author, Sir Angus Deaton, recipient of the 2015 Nobel Prize in Economic Sciences. This classic work remains relevant to anyone with a serious interest in using household survey data to shed light on policy issues. This book reviews the analysis of household survey data, including the construction of household surveys, the econometric tools useful for such analysis, and a range of problems in development policy for which this survey analysis can be applied. The author's approach remains close to the data, using transparent econometric and graphical techniques to present data in a way that can clearly inform policy and academic debates. Chapter 1 describes the features of survey design that need to be understood in order to undertake appropriate analysis. Chapter 2 discusses the general econometric and statistical issues that arise when using survey data for estimation and inference. Chapter 3 covers the use of survey data to measure welfare, poverty, and distribution. Chapter 4 focuses on the use of household budget data to explore patterns of household demand. Chapter 5 discusses price reform, its effects on equity and efficiency, and how to measure them. Chapter 6 addresses the role of household consumption and saving in economic development. The book includes an appendix providing code and programs using STATA, which can serve as a template for the users' own analysis.

The analysis of household surveys

This paper examines a novel mechanism linking fertility and growth. Household fertility is determined by relative wages of women and men. Increasing women's wages reduces fertility by raising the cost of children relatively more than household income. Lower fertility raises the level of capital per worker which in turn, since capital is more complementary to women's labor input than men's, raises women's relative wages. This positive feedback leads to the possibility of multiple steady-state equilibria. Countries with low initial capital may converge to a development trap with high fertility, low capital, and low relative wages for women.

The Gender Gap, Fertility and Growth

Although theoretical models of labor supply and the family are well developed, there are few credible estimates of key empirical relationships in the work-family nexus. This study uses a new instrumental variable, the sex composition of the first two births in families with at least two children, to estimate the effect of additional children on parents' labor supply. Instrumental variables estimates using the sex mix are substantial but smaller than the corresponding ordinary least squares (OLS) estimates. Moreover, unlike the OLS estimates, the female labor supply effects estimated using sex-mix instruments appear to be absent among more educated women and women with high-wage husbands. We also find that married women who have a third child reduce their labor supply by as much as women in the full sample, while there is no relationship between wives' child-bearing and husbands' labor supply. Finally results to estimates produced using twins to generate instruments. Estimates using twins instruments are very close to the estimates generated by sex-mix instruments, once the estimators are corrected for differences in the ages of children whose birth was caused by the instruments. The estimates imply that the labor supply consequences of child-bearing disappear by the time the child is about 13 years old.

Children and Their Parents' Labor Supply: Evidence from Exogenous Variation in Family Size

"This paper estimates semiparametric reduced-form neoclassical models of life-cycle fertility in Sweden.... The estimated model integrates aspects of life cycle fertility that have previously been studied in isolation of each other: completed fertility, childlessness, interbirth intervals, and the time series of annual birth rates. The main objective of this paper is to determine which aspects of life cycle fertility, if any, are sensitive to male income and female wages."

https://www.jstor.org/stable/info/2938322

The relationship between wages and income and the timing and spacing of births: evidence from Swedish longitudinal data.

This paper develops a tractable econometric model of optimal migration, focusing on expected income as the main economic influence on migration. The model improves on previous work in two respects: it covers optimal sequences of location decisions (rather than a single once-for-all choice) and it allows for many alternative location choices. The model is estimated using panel data from the National Longitudinal Survey of Youth on white males with a high-school education. Our main conclusion is that interstate migration decisions are influenced to a substantial extent by income prospects. The results suggest that the link between income and migration decisions is driven both by geographic differences in mean wages and by a tendency to move in search of a better locational match when the income realization in the current location is unfavorable.

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The effect of expected income on individual migration decisions

Among the central theoretical developments in the econometric analysis of nonexperimental microeconomic data has been the analysis of selectivity bias. Following the work of James Heckman (1974), statistical techniques were developed in the 1970s to consistently estimate the parameters of these models. One potential drawback to the application of these techniques is their sensitivity to the assumed parametric distribution of the unobservable error terms in the model. In recent years, a number of estimation methods for selection models have been developed which do not impose parametric forms on error distributions; these methods are termed "semiparametric," since only part of the model of interest (the regression function) is parametrically specified. While the statistical theory of these semiparametric estimators has received much attention, practical applications of the methods are lacking (an exception being the paper by Joel Horowitz and George Neumann, 1987). In this paper, we use semiparametric methods to reanalyze data on the labor supply of married women first studied by Thomas Mroz (1987) using parametric methods. The object of this reanalysis is to determine whether Mroz's results are sensitive to his parametric assumptions.

Semiparametric Estimation of Selection Models: Some Empirical Results

The paper develops a tractable econometric model of optimal migration, focusing on expected income as the main economic influence on migration. The model improves on previous work in two respects: it covers optimal sequences of location decisions (rather than a single once-for-all choice), and it allows for many alternative location choices. The model is estimated using panel data from the NLSY on white males with a high school education. Our main conclusion is that interstate migration decisions are influenced to a substantial extent by income prospects. The results suggest that the link between income and migration decisions is driven both by geographic differences in mean wages and by a tendency to move in search of a better locational match when the income realization in the current location is unfavorable.

James R. Walker

Papers

The relationship between wages and income and the timing and spacing of births: evidence from Swedish longitudinal data.

The effect of expected income on individual migration decisions

Semiparametric Estimation of Selection Models: Some Empirical Results

The Effect of Expected Income on Individual Migration Decisions

Using Goodness of Fit and Other Criteria to Choose among Competing Duration Models: A Case Study of Hutterite Data