This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Robust Nonstationary Regression

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Peter C.B. Phillips () (Cowles Foundation, Yale University)

Additional information is available for the following registered author(s):

Abstract

This paper provides a robust statistical approach to nonstationary time series regression and inference. Fully modified extensions of traditional robust statistical procedures are developed which allow for endogeneities in the nonstationary regressors and serial dependence in the shocks that drive the regressors and the errors that appear in the equation being estimated. The suggested estimators involve semiparametric corrections to accommodate these possibilities and they belong to the same family as the fully modified least squares (FM-OLS) estimator of Phillips and Hansen (1990). Specific attention is given to fully modified least absolute deviation (FM-LAD) estimation and fully modified M (FM-M)-estimation. The criterion function for LAD and some M-estimators is not always smooth and the paper develops generalized function methods to cope with this difficulty in the asymptotics. The results given here include a strong law of large numbers and some weak convergence theory for partial sums of generalized functions of random variables. The limit distribution theory for FM-LAD and FM-M estimators that is developed includes the case of finite variance errors and the case of heavy-tailed (infinite variance) errors. Some simulations and a brief empirical illustration are reported.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://cowles.econ.yale.edu/P/cp/p09a/p0912.pdf
File Format: application/pdf
File Function:
Download Restriction: no
File URL: http://cowles.econ.yale.edu/P/cd/d10b/d1064.pdf
File Format: application/pdf
File Function:
Download Restriction: no

Publisher Info
Paper provided by Cowles Foundation, Yale University in its series Cowles Foundation Discussion Papers with number 1064.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length: 49 pages
Date of creation: Nov 1993
Date of revision:
Publication status: Published in Econometric Theory (1995), 11: 912-951
Handle: RePEc:cwl:cwldpp:1064

Note: CFP 912.
Contact details of provider:
Postal: Yale University, Box 208281, New Haven, CT 06520-8281 USA
Phone: (203) 432-3702
Fax: (203) 432-6167
Web page: http://cowles.econ.yale.edu/
More information through EDIRC

Order Information:
Postal: Cowles Foundation, Yale University, Box 208281, New Haven, CT 06520-8281 USA

For technical questions regarding this item, or to correct its listing, contact: (Glena Ames).

Related research
Keywords: FM-LAD estimator; FM-M estimator; generalized functions of random variables; laws of large numbers and weak convergence for generalized functions; non-Gaussian nonstationarity; regular sequence; robust estimation;

Other versions of this item:

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Peter C.B. Phillips & Victor Solo, 1989. "Asymptotics for Linear Processes," Cowles Foundation Discussion Papers 932, Cowles Foundation, Yale University. [Downloadable!]
  2. repec:cup:etheor:v:7:y:1991:i:4:p:450-63 is not listed on IDEAS
  3. repec:cup:etheor:v:8:y:1992:i:4:p:489-500 is not listed on IDEAS
  4. Peter C.B. Phillips & Joon Y. Park, 1986. "Statistical Inference in Regressions with Integrated Processes: Part 2," Cowles Foundation Discussion Papers 819R, Cowles Foundation, Yale University, revised Feb 1987. [Downloadable!]
    Other versions:
  5. Paulauskas, V. J., 1976. "Some remarks on multivariate stable distributions," Journal of Multivariate Analysis, Elsevier, vol. 6(3), pages 356-368, September. [Downloadable!] (restricted)
  6. Phillips, P C B, 1991. "Optimal Inference in Cointegrated Systems," Econometrica, Econometric Society, vol. 59(2), pages 283-306, March. [Downloadable!] (restricted)
    Other versions:
  7. Peter C.B. Phillips, 1987. "Weak Convergence of Sample Covariance Matrices to Stochastic Integrals via Martingale Approximations," Cowles Foundation Discussion Papers 846, Cowles Foundation, Yale University. [Downloadable!]
  8. Hunter, John, 1992. "Tests of cointegrating exogeneity for PPP and uncovered interest rate parity in the United Kingdom," Journal of Policy Modeling, Elsevier, vol. 14(4), pages 453-463, August. [Downloadable!] (restricted)
  9. Peter C.B. Phillips, 1993. "Fully Modified Least Squares and Vector Autoregression," Cowles Foundation Discussion Papers 1047, Cowles Foundation, Yale University. [Downloadable!]
    Other versions:
  10. Peter C.B. Phillips & Bruce E. Hansen, 1988. "Statistical Inference in Instrumental Variables," Cowles Foundation Discussion Papers 869R, Cowles Foundation, Yale University, revised Apr 1989. [Downloadable!]
  11. Phillips, P.C.B., 1991. "A Shortcut to LAD Estimator Asymptotics," Econometric Theory, Cambridge University Press, vol. 7(04), pages 450-463, December. [Downloadable!]
    Other versions:
  12. Resnick, Sidney & Greenwood, Priscilla, 1979. "A bivariate stable characterization and domains of attraction," Journal of Multivariate Analysis, Elsevier, vol. 9(2), pages 206-221, June. [Downloadable!] (restricted)
Full references

Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Douglas J. Hodgson & Oliver Linton & Keith Vorkink, 2004. "Testing forward exchange rate unbiasedness efficiently: a semiparametric approach," Journal of Applied Economics, Universidad del CEMA, vol. 0, pages 325-353, November. [Downloadable!]
  2. Serguei Zernov & Victoria Zindle-Walsh & John Galbraith, 2006. "Asymptotics For Estimation Of Truncated Infinite-Dimensional Quantile Regressions," Departmental Working Papers 2006-16, McGill University, Department of Economics. [Downloadable!]
  3. Peter C.B. Phillips & James W. McFarland & Patrick C. McMahon, 1994. "Robust Tests of Forward Exchange Market Efficiency with Empirical Evidence from the 1920's," Cowles Foundation Discussion Papers 1080, Cowles Foundation, Yale University. [Downloadable!]
    Other versions:
  4. Peter C.B. Phillips, 1994. "Nonstationary Time Series and Cointegration: Recent Books and Themes for the Future," Cowles Foundation Discussion Papers 1081, Cowles Foundation, Yale University. [Downloadable!]
  5. Michael T. K. Horvath & Mark W. Watson, 1994. "Testing for Cointegration When Some of the Contributing Vectors are Known," NBER Technical Working Papers 0171, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  6. John Galbraith & Victoria Zinde-Walsh, 2001. "Properties of Estimates of Daily GARCH Parameters Basaed on Intra-Day Observations," CIRANO Working Papers 2001s-15, CIRANO. [Downloadable!]
    Other versions:
  7. Ted Juhl & Zhijie Xiao, 2000. "N-Consistent Semiparametric Regression: Partially Linear Models with Unit Roots," Econometric Society World Congress 2000 Contributed Papers 1532, Econometric Society. [Downloadable!]
Statistics
Access and download statistics

Did you know? IDEAS also indexes books.

This page was last updated on 2009-12-22.

This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.