Partly linear instrumental variables regressions without smoothing on the instruments

Jean-Pierre Florens () and Elia Lapenta ()
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Jean-Pierre Florens: Toulouse School of Economics
Elia Lapenta: CREST and ENSAE

TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, 2024, vol. 33, issue 3, No 15, 897-920

Abstract: Abstract We consider a semiparametric partly linear model identified by instrumental variables. We propose an estimation method that does not smooth on the instruments and we extend the Landweber–Fridman regularization scheme to the estimation of this semiparametric model. We then show the asymptotic normality of the parametric estimator and obtain the convergence rate for the nonparametric estimator. Our estimator that does not smooth on the instruments coincides with a typical estimator that does smooth on the instruments but keeps the respective bandwidth fixed as the sample size increases. We propose a data driven method for the selection of the regularization parameter, and in a simulation study we show the attractive performance of our estimators.

Keywords: Instrumental variables regression; Partly linear model; Ill posed inverse problem; Landweber–Fridman regularization; 45P05; 62G20; 62G08; 62G10; 62P20 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11749-024-00931-z

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