Nonlinear Correlated Random Effects Models with Endogeneity and Unbalanced Panels

Michael Bates, Leslie Papke and Jeffrey Wooldridge ()
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Jeffrey Wooldridge: Michigan State University

No 202305, Working Papers from University of California at Riverside, Department of Economics

Abstract: We present simple procedures for estimating nonlinear panel data models in the presence of unobserved heterogeneity and possible endogeneity with respect to time-varying unobservables. We combine a correlated random effects approach with a control function approach while accounting for missing time periods for some units. We examine the performance of the approach in comparisons with standard estimators using Monte Carlo simulation. We apply the methods to estimate the effects of school spending on student pass rates on a standardized math exam. We find that a 10 percent increase in spending leads to an approximately two percentage point increase in math pass rates.

Keywords: Control function; instrumental variables; education finance (search for similar items in EconPapers)
JEL-codes: C33 C36 I22 I26 (search for similar items in EconPapers)
Pages: 36 Pages
Date: 2022-09, Revised 2023-08
New Economics Papers: this item is included in nep-dcm
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https://economics.ucr.edu/repec/ucr/wpaper/202305.pdf First version, 2022 (application/pdf)
https://economics.ucr.edu/repec/ucr/wpaper/202305R.pdf Revised version, 2023 (application/pdf)

Related works:
Journal Article: Non linear correlated random effects models with endogeneity and unbalanced panels (2024)
Working Paper: Nonlinear Correlated Random Effects Models with Endogeneity and Unbalanced Panels (2022)
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Persistent link: https://EconPapers.repec.org/RePEc:ucr:wpaper:202305

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