Nonlinear Instrumental Variable Estimation of an Autoregression

31 Pages Posted: 14 Oct 2001

See all articles by Peter C. B. Phillips

Peter C. B. Phillips

University of Auckland Business School; Yale University - Cowles Foundation; Singapore Management University - School of Economics

Joon Park

Seoul National University

Yoosoon Chang

Indiana University Bloomington - Department of Economics

Date Written: September 2001

Abstract

Instrumental variable (IV) estimation methods that allow for certain nonlinear functions of the data as instruments are studied. The context of the discussion is the simple unit root model where certain advantages to the use of nonlinear instruments are revealed. In particular, certain classes of IV estimators and associated t-tests are shown to have simpler (standard) limit theory in contrast to the least squares estimator, providing an opportunity for the study of optimal estimation in certain IV classes and furnishing tests and confidence intervals that allow for unit root and stationary alternatives. The Cauchy estimator studied in recent work by So and Shin (1999) is shown to have such an optimality property in the class of certain IV procedures with bounded instruments.

Keywords: Cauchy Estimator, Instrumental Variable Autoregression, Nonlinear Instruments, Sojourn Time, Unit Root

JEL Classification: C22, C25

Suggested Citation

Phillips, Peter C. B. and Park, Joon and Chang, Yoosoon, Nonlinear Instrumental Variable Estimation of an Autoregression (September 2001). Available at SSRN: https://ssrn.com/abstract=285766

Peter C. B. Phillips (Contact Author)

University of Auckland Business School ( email )

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Singapore Management University - School of Economics

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Joon Park

Seoul National University ( email )

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Yoosoon Chang

Indiana University Bloomington - Department of Economics ( email )

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