Semiparametric estimation of panel data models without monotonicity or separability

Songnian Chen and Xi Wang

Journal of Econometrics, 2018, vol. 206, issue 2, 515-530

Abstract: Nonseparable panel data models with fixed effects have received a great deal of attention in the literature. Monotonicity is a common assumption in these settings, which may be violated in practice. Monotonicity-based estimators are inconsistent and the associated inference misleading under misspecification. In this paper, we propose some semiparametric estimators without imposing the monotonicity restriction. Under regularity conditions, our estimators are consistent and asymptotically normal. Our simulation suggests that our estimators work well in finite samples.

Keywords: Panel data; Fixed effects; Nonseparable models (search for similar items in EconPapers)
JEL-codes: C14 C23 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:206:y:2018:i:2:p:515-530

DOI: 10.1016/j.jeconom.2018.06.012

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