SMU SOE Online Seminar (Mar 3, 2022, 8.30am-10am):Bias Correction and Robust Inference in Semiparametric Models

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ABSTRACT This paper analyzes several different biases that emerge from the (possibly) low-precision nonparametric ingredient in a semiparametric model. We show that both the variance part and the bias part of the nonparametric ingredient can lead to some biases in the semiparametric estimator, under conditions weaker than typically required in the literature. We then propose two bias-robust inference procedures, based on multi-scale jackknife and analytical bias correction, respectively. We also extend our framework to the case where the semiparametric estimator is constructed by some discontinuous functionals of the nonparametric ingredient. The simulation study shows that both bias-correction methods have good finite-sample performance. Keywords: Semiparametric two-step estimation, nonparametric estimator, bias, robust inference, multi-scale jackknife, analytical bias correction. JEL Codes: C13, C14 Click here to view the paper. Click here to view the speaker's profile.		This seminar will be held virtually via Zoom. A confirmation email with the Zoom details will be sent to the registered email by 2 March 2022.
		PRESENTER Xiye Yang Rutgers University
		RESEARCH INTERESTS Econometric Theory Financial Econometrics Empirical Finance
		DATE: 3 March 2022 (Thursday)
		TIME: 8.30am - 10.00am