
Contents
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19.1 Introduction 19.1 Introduction
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19.2 Economic Framework 19.2 Economic Framework
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19.3 Heterogeneous Intercepts and Slopes 19.3 Heterogeneous Intercepts and Slopes
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19.3.1 Intercept Heterogeneity Models 19.3.1 Intercept Heterogeneity Models
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19.3.2 Intercept and Slope Heterogeneity Models 19.3.2 Intercept and Slope Heterogeneity Models
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19.4 Measurement Error 19.4 Measurement Error
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19.5 Endogeneity 19.5 Endogeneity
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19.5.1 Identification 19.5.1 Identification
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19.5.2 State Dependence and Dynamic Panels 19.5.2 State Dependence and Dynamic Panels
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19.6 Sample Composition Dynamics 19.6 Sample Composition Dynamics
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19.7 Summary and Policy Implications 19.7 Summary and Policy Implications
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Notes Notes
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References References
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19 Panel Econometrics of Labor Market Outcomes
Get accessThomas J. Kniesner is the Krishner Professor of Economics and Senior Research Associate in the Center for Policy Research at Syracuse University, a Professor of Economics at Claremont Graduate University, and a Research Fellow at IZA.
Carol Martin Gatton Chair in Microeconomics at University of Kentucky and Founding Director of University of Kentucky Center for Poverty Research
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Published:05 May 2015
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Extract
Introduction
Over the past four decades, advances in panel data econometrics have been intertwined with advances in labor economics. The tight link surely owes in part to the early availability of household panel data such as the Panel Study of Income Dynamics (PSID), the National Longitudinal Survey (NLS), and the negative income tax experiments. But it also stems from the fact that panel data offer numerous benefits for labor market research in terms of economically and econometrically richer models. This led to seminal research on life-cycle models of labor supply that developed new panel methods for separating state dependence from unobserved heterogeneity, allowing endogenous wages (Heckman 1978; MaCurdy 1981), considering earnings dynamics with growth rate heterogeneity and other autocorrelation processes (Lillard and Weiss 1979; MaCurdy 1982), modeling human capital investments that yielded new approaches to controlling for latent ability (Hausman and Taylor 1981), and to considering labor market interventions that in turn yielded new techniques for the evaluation of programs (Heckman and Robb 1985). The use of panel data also come with additional complications for labor market research that in turn led to advances in panel econometrics, such as how to control for attrition (Hausman and Wise 1979) and measurement error (Griliches and Hausman 1986).
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