 A Correlated Random Coefficient panel model with time-varying endogeneityLouise Laage Journal of Econometrics, 2024, vol. 242, issue 2 Abstract: This paper studies a class of linear panel models with random coefficients. We do not restrict the joint distribution of the time-invariant unobserved heterogeneity and the covariates. We investigate identification of the average partial effect (APE) when fixed-effect techniques cannot be used to control for the correlation between the regressors and the time-varying disturbances. Relying on control variables, we develop a constructive two-step identification argument. The first step identifies nonparametrically the conditional expectation of the disturbances given the regressors and the control variables, and the second step uses “between-group” variation, correcting for endogeneity, to identify the APE. We propose a natural semiparametric estimator of the APE, show its n asymptotic normality and compute its asymptotic variance. The estimator is computationally easy to implement, and Monte Carlo simulations show favorable finite sample properties. As an empirical illustration, we estimate the average elasticity of intertemporal substitution in a labor supply model with random coefficients. Keywords: Panel data; Random coefficients; Time-varying endogeneity; Control function approach (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:242:y:2024:i:2:s0304407624001507 DOI: 10.1016/j.jeconom.2024.105804 Access Statistics for this article Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson More articles in Journal of Econometrics from Elsevier |
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