Hostname: page-component-586b7cd67f-g8jcs Total loading time: 0 Render date: 2024-11-23T17:05:40.306Z Has data issue: false hasContentIssue false

PANEL COINTEGRATION: ASYMPTOTIC AND FINITE SAMPLE PROPERTIES OF POOLED TIME SERIES TESTS WITH AN APPLICATION TO THE PPP HYPOTHESIS

Published online by Cambridge University Press:  08 June 2004

Peter Pedroni
Affiliation:
Williams College

Abstract

We examine properties of residual-based tests for the null of no cointegration for dynamic panels in which both the short-run dynamics and the long-run slope coefficients are permitted to be heterogeneous across individual members of the panel. The tests also allow for individual heterogeneous fixed effects and trend terms, and we consider both pooled within dimension tests and group mean between dimension tests. We derive limiting distributions for these and show that they are normal and free of nuisance parameters. We also provide Monte Carlo evidence to demonstrate their small sample size and power performance, and we illustrate their use in testing purchasing power parity for the post–Bretton Woods period.I thank Rich Clarida, Bob Cumby, Mahmoud El-Gamal, Heejoon Kang, Chiwha Kao, Andy Levin, Klaus Neusser, Masao Ogaki, David Papell, Pierre Perron, Abdel Senhadji, Jean-Pierre Urbain, Alan Taylor, and three anonymous referees for helpful comments on various earlier versions of this paper. The paper has also benefited from presentations at the 1994 North American Econometric Society Summer Meetings in Quebec City, the 1994 European Econometric Society Summer Meetings in Maastricht, and workshop seminars at the Board of Governors of the Federal Reserve, INSEE-CREST Paris, IUPUI, Ohio State, Purdue, Queens University Belfast, Rice University–University of Houston, and Southern Methodist University. Finally, I thank the following students who provided assistance in the earlier stages of the project: Younghan Kim, Rasmus Ruffer, and Lining Wan.

Type
Research Article
Copyright
© 2004 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Bai, J. & S. Ng (2002) Determining the number of factors in approximate factor models. Econometrica 70, 191221.Google Scholar
Baltagi, B. & C. Kao (2000) Nonstationary panels, cointegration in panels, and dynamic panels: A survey. Advances in Econometrics 15, 752.Google Scholar
Banerjee, A. (1999) Panel data unit roots and cointegration: An overview. Oxford Bulletin of Economics and Statistics 61, 607630.Google Scholar
Chang, Y. (2000) Bootstrap Unit Root Tests in Panels with Cross-Sectional Dependency. Working paper, Rice University.
Haug, A. (1996) Tests for cointegration: A Monte Carlo comparison. Journal of Econometrics 71, 89115.Google Scholar
Holz-Eakon, D., W. Newey, & H. Rosen (1988) Estimating VARs with panel data. Econometrica 56, 13711395.Google Scholar
Im, K., H. Pesaran, & Y. Shin (2003) Testing for unit roots in heterogeneous panels. Journal of Econometrics 115, 5374.Google Scholar
Johansen, S. (1988) Statistical analysis of cointegration vectors. Journal of Economic Dynamics and Control 12, 231254.Google Scholar
Johansen, S. (1991) Estimation and hypothesis testing of cointegration vectors in Gaussian vector autoregressive models. Econometrica 59, 15511580.Google Scholar
Kao, C. (1999) Spurious regression and residual-based tests for cointegration in panel data when the cross-section and time series dimensions are comparable. Journal of Econometrics 90, 144.Google Scholar
Levin, A., C. Lin, & C. Chu (2002) Unit root tests in panel data: Asymptotic and finite-sample properties. Journal of Econometrics 108, 124.Google Scholar
Moon, H.R. & B. Perron (2003) Testing for a Unit Root in Panels with Dynamic Factors. Mimeo, University of California at Santa Barbara.
Newey, W. & K. West (1994) Autocovariance lag selection in covariance matrix estimation. Review of Economic Studies 61, 631653.Google Scholar
Ng, S. & P. Perron (1997) Estimation and inference in nearly unbalanced nearly cointegrated systems. Journal of Econometrics 79, 5381.Google Scholar
Park, J.Y. & P.C.B Phillips (1988) Statistical inference in regressions with integrated processes, part 1. Econometric Theory 4, 468497.Google Scholar
Pedroni, P. (1993) Panel Cointegration, Endogenous Growth and Business Cycles in Open Economies. Ph.D. Dissertation, Columbia University. UMI Publishers.
Pedroni, P. (1995) Panel Cointegration; Asymptotic and Finite Sample Properties of Pooled Time Series Tests, with an Application to the PPP Hypothesis. Indiana University working papers in economics 95-013.
Pedroni, P. (1996) Fully Modified OLS for Heterogeneous Cointegrated Panels and the Case of Purchasing Power Parity. Indiana University working papers in economics 96-020.
Pedroni, P. (1997a) Panel Cointegration; Asymptotic and Finite Sample Properties of Pooled Time Series Tests, with an Application to the PPP Hypothesis: New Results. Working paper, Indiana University.
Pedroni, P. (1997b) On the Role of Cross Sectional Dependency in Panel Unit Root and Panel Cointegration Exchange Rate Studies. Working paper, Indiana University.
Pedroni, P. (1999) Critical values for cointegration tests in heterogeneous panels with multiple regressors. Oxford Bulletin of Economics and Statistics 61, 653670.Google Scholar
Pedroni, P. (2000) Fully modified OLS for heterogeneous cointegrated panels. Advances in Econometrics 15, 93130.Google Scholar
Pedroni, P. (2001a) Panel Cointegration; Asymptotic and Finite Sample Properties of Pooled Time Series Tests, with an Application to the PPP Hypothesis. Revised working paper, Indiana University.
Pedroni, P. (2001b) Purchasing power parity tests in cointegrated panels. Review of Economics and Statistics 83, 727731.Google Scholar
Perron, P. (1989) Testing for a random walk: A simulation experiment of power when the sampling interval is varied. In B. Jaj (ed.), Advances in Econometrics and Modeling, pp. 4768. Kluwer Academic Publishers.
Perron, P. (1991) Test consistency with varying sampling frequency. Econometric Theory 7, 341368.Google Scholar
Phillips, P.C.B. (1986) Understanding spurious regressions. Journal of Econometrics 33, 311340.Google Scholar
Phillips, P.C.B. (1987) Time series regression with a unit root. Econometrica 55, 227301.Google Scholar
Phillips, P.C.B. & S. Durlauf (1986) Multiple time series regression with integrated processes. Review of Economic Studies 53, 473495.Google Scholar
Phillips, P.C.B. & H. Moon (1999) Linear regression limit theory for nonstationary panel data. Econometrica 67, 10571112.Google Scholar
Phillips, P.C.B. & H. Moon (2000) Nonstationary panel data analysis: An overview of some recent developments. Econometric Reviews 19, 263286.Google Scholar
Phillips, P.C.B. & S. Ouliaris (1990) Asymptotic properties of residual based tests for cointegration. Econometrica 58, 165193.Google Scholar
Phillips, P.C.B. & P. Perron (1988) Testing for a unit root in time series regressions. Biometrika 75, 335346.Google Scholar
Phillips, P.C.B. & V. Solo (1992) Asymptotics for linear processes. Annals of Statistics 20, 9711001.Google Scholar
Phillips, P.C.B. & D. Sul (2003) Dynamic panel estimation and homogeneity testing under cross section dependence. Econometrics Journal 6, 217259.Google Scholar
Pierce, R.G. & A.J. Snell (1995) Temporal aggregation and the power of tests for a unit root. Journal of Econometrics 65, 333345.Google Scholar
Quah, D. (1994) Exploiting cross-section variation for unit root inference in dynamic data. Economics Letters 44, 919.Google Scholar
Shiller, R. & P. Perron (1985) Testing the random walk hypothesis: Power versus frequency of observation. Economic Letters 18, 381386.Google Scholar