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Instrumental Variables Estimation of Stationaryand Nonstationary Cointegrating Regressions

  • M. Gerolimetto
  • Peter M Robinson

Instrumental variables estimation is classically employed to avoid simultaneousequations bias in a stable environment. Here we use it to improve upon ordinaryleast squares estimation of cointegrating regressions between nonstationaryand/or long memory stationary variables where the integration orders of regressorand disturbance sum to less than 1, as happens always for stationary regressors,and sometimes for mean-reverting nonstationary ones. Unlike in the classicalsituation, instruments can be correlated with disturbances and/or uncorrelated withregressors. The approach can also be used in traditional non-fractionalcointegrating relations. Various choices of instrument are proposed. Finite sampleperformance is examined.

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Paper provided by Suntory and Toyota International Centres for Economics and Related Disciplines, LSE in its series STICERD - Econometrics Paper Series with number /2006/500.

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Date of creation: Apr 2006
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Handle: RePEc:cep:stiecm:/2006/500
Contact details of provider: Web page: http://sticerd.lse.ac.uk/_new/publications/default.asp

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  1. Javier Hualde & Peter M Robinson, 2006. "Root-N-Consistent Estimation Of Weakfractional Cointegration," STICERD - Econometrics Paper Series /2006/499, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  2. Kitamura, Yuichi & Phillips, Peter C. B., 1997. "Fully modified IV, GIVE and GMM estimation with possibly non-stationary regressors and instruments," Journal of Econometrics, Elsevier, vol. 80(1), pages 85-123, September.
  3. Bent Jesper Christensen & Morten Ø. Nielsen, . "Semiparametric Analysis of Stationary Fractional Cointegration and the Implied-Realized Volatility Relation in High-Frequency Options Data," Economics Working Papers 2001-4, School of Economics and Management, University of Aarhus.
  4. Stock, James H, 1987. "Asymptotic Properties of Least Squares Estimators of Cointegrating Vectors," Econometrica, Econometric Society, vol. 55(5), pages 1035-56, September.
  5. Juan J. Dolado & Francisco Mármol, 1996. "Efficient Estimation of Cointegrating Relationships Among Higher Order and Fractionally Integrated Processes," Banco de Espa�a Working Papers 9617, Banco de Espa�a.
  6. Jeganathan, P., 1999. "On Asymptotic Inference In Cointegrated Time Series With Fractionally Integrated Errors," Econometric Theory, Cambridge University Press, vol. 15(04), pages 583-621, August.
  7. Cheung, Yin-Wong & Lai, Kon S, 1993. "A Fractional Cointegration Analysis of Purchasing Power Parity," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(1), pages 103-12, January.
  8. Marinucci, D. & Robinson, P. M., 2000. "Weak convergence of multivariate fractional processes," Stochastic Processes and their Applications, Elsevier, vol. 86(1), pages 103-120, March.
  9. Andrew Harvey (ed.), 1994. "Time Series," Books, Edward Elgar, volume 0, number 599.
  10. Javier Hualde & Peter M Robinson, 2003. "Cointegration in Fractional Systems with Unkown Integration Orders," STICERD - Econometrics Paper Series /2003/449, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  11. Marmol, Francesc & Escribano, Alvaro & Aparicio, Felipe M., 2002. "Instrumental Variable Interpretation Of Cointegration With Inference Results For Fractional Cointegration," Econometric Theory, Cambridge University Press, vol. 18(03), pages 646-672, June.
  12. repec:cup:etheor:v:11:y:1995:i:5:p:1095-1130 is not listed on IDEAS
  13. Kitamura, Yuichi & Phillips, Peter C.B., 1995. "Efficient IV Estimation in Nonstationary Regression," Econometric Theory, Cambridge University Press, vol. 11(05), pages 1095-1130, October.
  14. Phillips, P C B, 1991. "Optimal Inference in Cointegrated Systems," Econometrica, Econometric Society, vol. 59(2), pages 283-306, March.
  15. Tsay, Wen-Jen & Chung, Ching-Fan, 2000. "The spurious regression of fractionally integrated processes," Journal of Econometrics, Elsevier, vol. 96(1), pages 155-182, May.
  16. Javier Hualde & Peter M Robinson, 2006. "Semiparametric Estimation of Fractional Cointegration," STICERD - Econometrics Paper Series /2006/502, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  17. Federico M. Bandi & Benoit Perron, 2006. "Long Memory and the Relation Between Implied and Realized Volatility," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 4(4), pages 636-670.
  18. D Marinucci & Peter M Robinson, 2001. "Narrow-Band Analysis of Nonstationary Processes," STICERD - Econometrics Paper Series /2001/421, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  19. Peter C.B. Phillips & Bruce E. Hansen, 1988. "Statistical Inference in Instrumental Variables," Cowles Foundation Discussion Papers 869R, Cowles Foundation for Research in Economics, Yale University, revised Apr 1989.
  20. Robinson, Peter M. & Yajima, Yoshihiro, 2002. "Determination of cointegrating rank in fractional systems," Journal of Econometrics, Elsevier, vol. 106(2), pages 217-241, February.
  21. Phillips, P.C.B., 1986. "Understanding spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 33(3), pages 311-340, December.
  22. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-80, November.
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