Hostname: page-component-cd9895bd7-lnqnp Total loading time: 0 Render date: 2024-12-27T18:31:01.888Z Has data issue: false hasContentIssue false

PETER C.B. PHILLIPS’S CONTRIBUTIONS TO PANEL DATA METHODS

Published online by Cambridge University Press:  24 February 2014

Hyungsik Roger Moon*
Affiliation:
University of Southern California, Yonsei University
Benoit Perron
Affiliation:
Université de Montréal, CIREQ, CIRANO
*
*Address correspondence and reprint requests to Hyungsik Roger Moon, Department of Economics, University of Southern California, 3620 South Vermont Ave, Los Angeles, CA 90089, U.S.A.; and Department of Economics, Yonsei University, Seoul, Korea.

Abstract

This paper discusses Peter Phillips’s contributions to panel data methods. These include contributions in the areas of seemingly unrelated regressions, nonstationary panel data, dynamic panels, and the development of multiple index asymptotic theory. We also discuss his empirical contributions in the area of economic growth and convergence that use macro panel data.

Type
ARTICLES
Copyright
Copyright © Cambridge University Press 2014 

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

Ahn, S. & Schmidt, P. (1995) Efficient estimation of models for dynamic panel data. Journal of Econometrics 68, 528.Google Scholar
Anderson, T.W. & Hsiao, C. (1982) Formulation and estimation of dynamic models using panel data. Journal of Econometrics 18, 4782,Google Scholar
Arellano, M. & Bond, S. (1991) Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. Review of Economic Studies 58, 277297.Google Scholar
Arellano, M. & Bover, O. (1991) Another look at the instrumental variable estimation of error-component models. Journal of Econometrics 68, 2951.Google Scholar
Bai, J. & Ng, S. (2004) A PANIC attack on unit roots and cointegration. Econometrica 72, 11271177.Google Scholar
Barro, R. & Sala-i-Martin, X. (1992) Convergence. Journal of Political Economy 100, 223251.Google Scholar
Breitung, J. (2000) The local power of some unit root tests for panel data. In Baltagi, B. (ed.), Nonstationary Panels, Panel Cointegration, and Dynamic Panels, Advances in Econometrics, Vol. 15, pp. 161178. JAI.CrossRefGoogle Scholar
Breitung, J. & Pesaran, M.H. (2008) Unit roots and cointegration in panels. In Matyas, L. & Sevestre, P. (eds.), The Econometrics of Panel Data, 3rd ed., Kluwer Academic Publishers.Google Scholar
Choi, I. (2001) Unit root tests for panel data. Journal of International Money and Finance 20,249272.CrossRefGoogle Scholar
Gourieroux, C., Phillips, P.C.B., & Yu, J. (2010) Indirect inference for dynamic panel models. Journal of Econometrics 157, 6877.Google Scholar
Granger, C.W.J. & Newbold, P. (1974) Spurious regressions in econometrics. Journal of Econometrics 2, 111120.CrossRefGoogle Scholar
Hahn, J. & Kuersteiner, G.M. (2002) Asymptotically unbiased inference for a dynamic panel model with fixed effects when both n and T are large. Econometrica 70, 16391657.Google Scholar
Han, C. & Phillips, P.C.B. (2010) GMM estimation for dynamic panels with fixed effects and strong instruments at unity. Econometric Theory 26, 119151.Google Scholar
Im, K., Pesaran, H., & Shin, Y. (2003) Testing for unit roots in heterogeneous panels. Journal of Econometrics 115, 5374.Google Scholar
Kao, C. (1999) Spurious regression and residual-based tests for cointegration in panel data. Journal of Econometrics 90, 144.Google Scholar
Levin, A. & Lin, F. (1993a) Unit Root Test in Panel Data: Asymptotic and Finite Sample Properties, University of California, San Diego Discussion Paper 93–23.Google Scholar
Levin, A. & Lin, F. (1993b) Unit Root Test in Panel Data: New Results, University of California, San Diego Discussion Paper 93–56.Google Scholar
Levin, A., Lin, F., & Chu, C. (2002) Unit root tests in panel data: Asymptotic and finite-sample properties. Journal of Econometrics 108, 124.CrossRefGoogle Scholar
Maddala, G.S. & Wu, S. (1999) A comparative study of unit root tests with panel data and a new simple test. Oxford Bulletin of Economics and Statistics 61, 631651.CrossRefGoogle Scholar
Mankiw, N., Romer, GD., & Weil, D. (1992) A contribution to the empirics of economic growth. Quarterly Journal of Economics 107, 407437.Google Scholar
Moon, H.R. & Perron, B. (2004) Testing for a unit root in panels with dynamic factors. Journal of Econometrics 122, 81126.Google Scholar
Moon, H.R. & Perron, B. (2008) Asymptotic local power of pooled t-ratio tests for unit roots in panels with fixed effects. Econometrics Journal 11, 80104.Google Scholar
Moon, H.R., Perron, B., & Phillips, P.C.B. (2006) On the Breitung test for panel unit roots and local asymptotic power. Econometric Theory 22, 11791190.Google Scholar
Moon, H.R., Perron, B., & Phillips, P.C.B. (2007) Incidental trends and the power of panel unit root tests. Journal of Econometrics 141, 416459.CrossRefGoogle Scholar
Moon, H.R. & Phillips, P.C.B. (1999) Maximum likelihood estimation in panels with incidental trends. Oxford Bulletin of Economics and Statistics 61, 711747.Google Scholar
Moon, H.R. & Phillips, P.C.B. (2000) Estimation of autoregressive roots near unity using panel data. Econometric Theory 16, 927997.Google Scholar
Moon, H.R. & Phillips, P.C.B. (2004) GMM estimation of autoregressive roots near unity with panel data. Econometrica 72, 467522.Google Scholar
Neyman, J., & Scott, E. (1948) Consistent estimates based on partially consistent observations. Econometrica 16, 131.Google Scholar
Nickell, S. (1981) Biases in dynamic models with fixed effects. Econometrica 49, 14171426.Google Scholar
Pedroni, P. (1995) Panel Cointegration: Asymptotic and Finite Sample Properties of Pooled Time Series with an Application to the PPP Hypothesis, Indiana University Working Paper in Economics, No 95–013.Google Scholar
Pesaran, H. & Smith, R. (1995) Estimating the long-run relationships from dynamic heterogeneous panels. Journal of Econometrics 68, 79113.Google Scholar
Phillips, P.C.B (1977) An approximation to the finite sample distribution of Zellner’s seemingly unrelated regression estimator. Journal of Econometrics 6(2), 147164.Google Scholar
Phillips, P.C.B (1985) The exact distribution of the SUR estimator. Econometrica 53(4), 745756.Google Scholar
Phillips, P.C.B. (1986) Understanding spurious regressions in econometrics. Journal of Econometrics 33, 311340.Google Scholar
Phillips, P.C.B. & Moon, H.R. (2000) Nonstationary panel data analysis: An overview of some recent developments. Econometric Reviews 19, 263286.Google Scholar
Phillips, P.C.B. & Moon, H.R. (1999) Linear regression limit theory for nonstationary panel data. Econometrica 67, 10571111.CrossRefGoogle Scholar
Phillips, P.C.B. & Sul, D. (2003) Dynamic panel estimation and homogeneity testing under cross section dependence. Econometrics Journal 6, 217259.Google Scholar
Phillips, P.C.B. & Sul, D. (2007a) Bias in dynamic panel estimation with fixed effects, incidental trends and cross section dependence. Journal of Econometrics 137, 162188.Google Scholar
Phillips, P.C.B. & Sul, D. (2007b) Some empirics on economic growth under heterogeneous technology. Journal of Macroeconomics 29, 455469.Google Scholar
Phillips, P.C.B. & Sul, D. (2007c) Transition modeling and econometric convergence tests. Econometrica 75, 17711855.Google Scholar
Ploberger, W. & Phillips, P.C.B. (2002) Optimal Testing for Unit Roots in Panel Data. Mimeo.Google Scholar
Quah, D., (1994) Exploiting cross-section variations for unit root inference in dynamic panels. Economics Letters 44, 919.Google Scholar
Zellner, A. (1962) An efficient method of estimating seemingly unrelated regression equations and tests of aggregation bias. Journal of the American Statistical Association 57, 500509.CrossRefGoogle Scholar