Series Estimation of Stochastic Processes: Recent Developments and Econometric Applications

53 Pages Posted: 5 Sep 2012  

Peter C. B. Phillips

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

Zhipeng Liao

University of California, Los Angeles (UCLA) - Department of Economics

Date Written: September 4, 2012

Abstract

This paper overviews recent developments in series estimation of stochastic processes and some of their applications in econometrics. Underlying this approach is the idea that a stochastic process may under certain conditions be represented in terms of a set of orthonormal basis functions, giving a series representation that involves deterministic functions. Several applications of this series approximation method are discussed. The first shows how a continuous function can be approximated by a linear combination of Brownian motions (BMs), which is useful in the study of the spurious regressions. The second application utilizes the series representation of BM to investigate the effect of the presence of deterministic trends in a regression on traditional unit-root tests. The third uses basis functions in the series approximation as instrumental variables (IVs) to perform efficient estimation of the parameters in cointegrated systems. The fourth application proposes alternative estimators of long-run variances in some econometric models with dependent data, thereby providing autocorrelation robust inference methods in these models. We review some work related to these applications and some ongoing research involving series approximation methods.

Keywords: Cointegrated system, HAC estimation, Instrumental variables, Lasso regression, Karhunen-Loève representation, Long-run variance, Reproducing kernel Hilbert space, Oracle effciency, Orthonormal system, Trend basis

JEL Classification: C22

Suggested Citation

Phillips, Peter C. B. and Liao, Zhipeng, Series Estimation of Stochastic Processes: Recent Developments and Econometric Applications (September 4, 2012). Cowles Foundation Discussion Paper No. 1871. Available at SSRN: https://ssrn.com/abstract=2141299 or http://dx.doi.org/10.2139/ssrn.2141299

Peter C. B. Phillips (Contact Author)

Yale University - Cowles Foundation ( email )

Box 208281
New Haven, CT 06520-8281
United States
203-432-3695 (Phone)
203-432-5429 (Fax)

University of Auckland ( email )

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Auckland
New Zealand
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University of Southampton

Southampton, SO17 1BJ
United Kingdom

Singapore Management University - School of Economics

90 Stamford Road
178903
Singapore

Zhipeng Liao

University of California, Los Angeles (UCLA) - Department of Economics ( email )

8283 Bunche Hall
Los Angeles, CA 90095-1477
United States

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