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Activity Number: 41
Type: Contributed
Date/Time: Sunday, August 4, 2013 : 2:00 PM to 3:50 PM
Sponsor: Section on Nonparametric Statistics
Abstract - #307652
Title: Semiparametrically Modified OLS and IV Estimators for Linear Cointegrating Models
Author(s): Yiguo Sun*+
Companies: University of Guelph
Keywords: Integrated time series ; Linear cointegrating models ; Kernel estimator ; Partially linear cointegrating models
Abstract:

This paper proposes a semiparametrically modified OLS (SM-OLS) estimator and a semiparametrically modified instrumental variable (SM-IV) estimator via kernel method for linear cointegrating models. Both the proposed estimators are shown to have a mixed normal limiting distribution with zero mean and have smaller asymptotic variance than Phillips and Hansen's (1991) fully modified OLS (FM-OLS) estimator and Marmol et al.'s (2002) fully modified instrumental variable (FM-IV) estimator if the first-differenced integrated regressor affects the cointegrating equilibrium errors in nonlinear way. Finite sample Monte Carlo simulations and an empirical application are given to illustrate the performance and usefulness of our proposed estimators.


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