Robust estimation with exponentially tilted Hellinger distance

Bertille Antoine and Prosper Dovonon

Journal of Econometrics, 2021, vol. 224, issue 2, 330-344

Abstract: This paper is concerned with estimation of parameters defined by moment equalities. We introduce the exponentially tilted Hellinger distance (ETHD) estimator which is efficient under correct specification, and robust to both global and local misspecification. In the spirit of Schennach (2007), ETHD combines the Hellinger distance and the Kullback–Leibler information criterion. We show that it achieves optimal minimax robust properties under local deviations from the model and remains well-behaved under global misspecification.

Keywords: Moment condition models; Global misspecification; Local misspecification; Hellinger distance; Minimax robust estimation; Semiparametric efficiency (search for similar items in EconPapers)
JEL-codes: C01 C13 C14 C36 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Related works:
Working Paper: Robust Estimation with Exponentially Tilted Hellinger Distance (2020)
Working Paper: Robust Estimation with Exponentially Tilted Hellinger Distance (2018)
Working Paper: ROBUST ESTIMATION WITH EXPONENTIALLY TILTED HELLINGER DISTANCE (2018)
Working Paper: ROBUST ESTIMATION WITH EXPONENTIALLY TILTED HELLINGER DISTANCE (2017)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:224:y:2021:i:2:p:330-344

DOI: 10.1016/j.jeconom.2020.03.027

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