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A Class of Robust Tests in Augmented Predictive Regressions

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  • Paulo M.M. Rodrigues
  • Antonio Rubia

Abstract

This paper focuses on the analytical discussion of a robust t-test for predictability and on the analysis of its finite-sample properties. Our analysis shows that the procedure proposed exhibits approximately correct size even in fairly small samples. Furthermore, the test is well-behaved under short-run dependence, and can exhibit improved power performance over alternative procedures. These appealing properties, together with the fact that the test can be applied in a simple and direct way in the linear regression context, suggests that the modified t-statistic introduced in this paper is well suited for addressing predictability in empirical applications.

Suggested Citation

  • Paulo M.M. Rodrigues & Antonio Rubia, 2011. "A Class of Robust Tests in Augmented Predictive Regressions," Working Papers w201126, Banco de Portugal, Economics and Research Department.
    • Handle: RePEc:ptu:wpaper:w201126
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    References listed on IDEAS

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    1. Amihud, Yakov & Hurvich, Clifford M., 2004. "Predictive Regressions: A Reduced-Bias Estimation Method," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 39(4), pages 813-841, December.
    2. Campbell, J.Y. & Shiller, R.J., 1988. "Stock Prices, Earnings And Expected Dividends," Papers 334, Princeton, Department of Economics - Econometric Research Program.
    3. Bunzel, Helle & Vogelsang, Timothy J., 2005. "Powerful Trend Function Tests That Are Robust to Strong Serial Correlation, With an Application to the Prebisch-Singer Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 381-394, October.
    4. Davidson, James, 1994. "Stochastic Limit Theory: An Introduction for Econometricians," OUP Catalogue, Oxford University Press, number 9780198774037.
    5. Markku Lanne, 2002. "Testing The Predictability Of Stock Returns," The Review of Economics and Statistics, MIT Press, vol. 84(3), pages 407-415, August.
    6. Maynard, Alex & Shimotsu, Katsumi, 2009. "Covariance-Based Orthogonality Tests For Regressors With Unknown Persistence," Econometric Theory, Cambridge University Press, vol. 25(1), pages 63-116, February.
    7. Dong Wan Shin & Beong Soo So, 2001. "recursive Mean Adjustment for Unit Root Tests," Journal of Time Series Analysis, Wiley Blackwell, vol. 22(5), pages 595-612, September.
    8. repec:bla:obuest:v:61:y:1999:i:4:p:583-95 is not listed on IDEAS
    9. John Y. Campbell, 2008. "Viewpoint: Estimating the equity premium," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 41(1), pages 1-21, February.
    10. Elliott, Graham & Stock, James H., 1994. "Inference in Time Series Regression When the Order of Integration of a Regressor is Unknown," Econometric Theory, Cambridge University Press, vol. 10(3-4), pages 672-700, August.
    11. Campbell, John Y. & Yogo, Motohiro, 2006. "Efficient tests of stock return predictability," Journal of Financial Economics, Elsevier, vol. 81(1), pages 27-60, July.
    12. Phillips, Peter C B, 1988. "Regression Theory for Near-Integrated Time Series," Econometrica, Econometric Society, vol. 56(5), pages 1021-1043, September.
    13. Gregory Mankiw, N. & Shapiro, Matthew D., 1986. "Do we reject too often? : Small sample properties of tests of rational expectations models," Economics Letters, Elsevier, vol. 20(2), pages 139-145.
    14. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
    15. Lewellen, Jonathan, 2004. "Predicting returns with financial ratios," Journal of Financial Economics, Elsevier, vol. 74(2), pages 209-235, November.
    16. John Y. Campbell, 2007. "Estimating the Equity Premium," NBER Working Papers 13423, National Bureau of Economic Research, Inc.
    17. Yakov Amihud & Clifford M. Hurvich & Yi Wang, 2009. "Multiple-Predictor Regressions: Hypothesis Testing," The Review of Financial Studies, Society for Financial Studies, vol. 22(1), pages 413-434, January.
    18. Hansen, Bruce E., 1995. "Rethinking the Univariate Approach to Unit Root Testing: Using Covariates to Increase Power," Econometric Theory, Cambridge University Press, vol. 11(5), pages 1148-1171, October.
    19. Guglielmo Maria Caporale & Nikitas Pittis, 1999. "Unit Root Testing Using Covariates: Some Theory and Evidence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 61(4), pages 583-595, November.
    20. Michael Jansson & Marcelo J. Moreira, 2006. "Optimal Inference in Regression Models with Nearly Integrated Regressors," Econometrica, Econometric Society, vol. 74(3), pages 681-714, May.
    21. Fama, Eugene F. & French, Kenneth R., 1988. "Dividend yields and expected stock returns," Journal of Financial Economics, Elsevier, vol. 22(1), pages 3-25, October.
    22. Stambaugh, Robert F., 1999. "Predictive regressions," Journal of Financial Economics, Elsevier, vol. 54(3), pages 375-421, December.
    23. Unknown, 1986. "Letters," Choices: The Magazine of Food, Farm, and Resource Issues, Agricultural and Applied Economics Association, vol. 1(4), pages 1-9.
    24. repec:bla:jfinan:v:43:y:1988:i:3:p:661-76 is not listed on IDEAS
    25. Harvey, David I. & Leybourne, Stephen J. & Taylor, A.M. Robert, 2006. "Modified tests for a change in persistence," Journal of Econometrics, Elsevier, vol. 134(2), pages 441-469, October.
    26. Valkanov, Rossen, 2003. "Long-horizon regressions: theoretical results and applications," Journal of Financial Economics, Elsevier, vol. 68(2), pages 201-232, May.
    27. Cavanagh, Christopher L. & Elliott, Graham & Stock, James H., 1995. "Inference in Models with Nearly Integrated Regressors," Econometric Theory, Cambridge University Press, vol. 11(5), pages 1131-1147, October.
    28. Timothy J. Vogelsang, 1998. "Trend Function Hypothesis Testing in the Presence of Serial Correlation," Econometrica, Econometric Society, vol. 66(1), pages 123-148, January.
    29. Breitung, Jorg, 2002. "Nonparametric tests for unit roots and cointegration," Journal of Econometrics, Elsevier, vol. 108(2), pages 343-363, June.
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