Asymptotic inference for dynamic panel estimators of infinite order autoregressive processes

Yoon-Jin Lee, Ryo Okui and Mototsugu Shintani

Journal of Econometrics, 2018, vol. 204, issue 2, 147-158

Abstract: In this paper we consider the estimation of a dynamic panel autoregressive (AR) process of possibly infinite order in the presence of individual effects. We employ double asymptotics under which both the cross-sectional sample size and the length of time series tend to infinity and utilize the sieve AR approximation with its lag order increasing with the sample size. We establish the consistency and asymptotic normality of the fixed effects estimator and propose a bias-corrected fixed effects estimator based on a theoretical asymptotic bias term. Monte Carlo simulations demonstrate the usefulness of bias correction. As an illustration, the proposed methods are applied to dynamic panel estimation of the law of one price deviations among US cities.

Keywords: Autoregressive sieve estimation; Bias correction; Double asymptotics; Fixed effects estimator (search for similar items in EconPapers)
JEL-codes: C13 C23 C26 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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Related works:
Working Paper: Asymptotic Inference for Dynamic Panel Estimators of In nite Order Autoregressive Processes (2013)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:204:y:2018:i:2:p:147-158

DOI: 10.1016/j.jeconom.2017.04.005

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