Semi‐Parametric Estimation of Linear Cointegrating Models with Nonlinear Contemporaneous Endogeneity

25 Pages Posted: 27 Aug 2014

Date Written: September 2014

Abstract

This article considers linear cointegrating models with unknown nonlinear short‐run contemporaneous endogeneity. Two estimators are proposed to estimate the linear cointegrating parameter after the nonlinear endogenous component is estimated by local linear regression approach. Both the proposed estimators are shown to have the same mixed normal limiting distribution with zero mean and smaller asymptotic variance than the fully modified ordinary least squares and instrumental variables estimators. Monte Carlo simulations are used to evaluate the finite sample performance of our proposed estimators, and an empirical application is also included.

Keywords: Integrated time series, linear cointegrating models, local linear regression approach

Suggested Citation

Sun, Yiguo, Semi‐Parametric Estimation of Linear Cointegrating Models with Nonlinear Contemporaneous Endogeneity (September 2014). Journal of Time Series Analysis, Vol. 35, Issue 5, pp. 437-461, 2014, Available at SSRN: https://ssrn.com/abstract=2487581 or http://dx.doi.org/10.1111/jtsa.12075

Yiguo Sun (Contact Author)

University of Guelph ( email )

Guelph, Ontario
Canada

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