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Estimation And Inference In Predictive Regressions

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  • KUROZUMI, EIJI
  • AONO, KOHEI

Abstract

In this paper, we analyze feasible bias-reduced versions of point estimates for predictive regressions: The plug-in estimates, which are based on the augmented regressions proposed by Amihud and Hurvich (2004) and Amihud, Hurvich and Wang (2010), and the grouped jackknife estimate by Quenouille (1949, 1956).We also derive the correct standard errors associated with these point estimates.The methods thus allow for a unified inferential framework, where point estimates and statistical inference are based on the same methods. Using the new estimates, we investigate U.S. stock returns and find that some variables are able to predict stock returns.

Suggested Citation

  • Kurozumi, Eiji & Aono, Kohei, 2013. "Estimation And Inference In Predictive Regressions," Hitotsubashi Journal of Economics, Hitotsubashi University, vol. 54(2), pages 231-250, December.
  • Handle: RePEc:hit:hitjec:v:54:y:2013:i:2:p:231-250
    DOI: 10.15057/26018
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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. Walter Torous & Rossen Valkanov & Shu Yan, 2004. "On Predicting Stock Returns with Nearly Integrated Explanatory Variables," The Journal of Business, University of Chicago Press, vol. 77(4), pages 937-966, October.
    3. Campbell, John Y. & Yogo, Motohiro, 2006. "Efficient tests of stock return predictability," Journal of Financial Economics, Elsevier, vol. 81(1), pages 27-60, July.
    4. Toda, Hiro Y. & Yamamoto, Taku, 1995. "Statistical inference in vector autoregressions with possibly integrated processes," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 225-250.
    5. 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.
    6. Stambaugh, Robert F., 1999. "Predictive regressions," Journal of Financial Economics, Elsevier, vol. 54(3), pages 375-421, December.
    7. Amihud, Yakov & Hurvich, Clifford M. & Wang, Yi, 2010. "Predictive regression with order-p autoregressive predictors," Journal of Empirical Finance, Elsevier, vol. 17(3), pages 513-525, June.
    8. 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.
    9. Markku Lanne, 2002. "Testing The Predictability Of Stock Returns," The Review of Economics and Statistics, MIT Press, vol. 84(3), pages 407-415, August.
    10. 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.
    11. Andrews, Donald W K, 1993. "Exactly Median-Unbiased Estimation of First Order Autoregressive/Unit Root Models," Econometrica, Econometric Society, vol. 61(1), pages 139-165, January.
    12. Yamamoto, Taku & Kurozumi, Eiji, 2005. "Lag augmentation in regression models with possibly integrated regressors," Hitotsubashi Journal of Economics, Hitotsubashi University, vol. 46(2), pages 159-175, December.
    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. Lewellen, Jonathan, 2004. "Predicting returns with financial ratios," Journal of Financial Economics, Elsevier, vol. 74(2), pages 209-235, November.
    15. Eiji Kurozumi & Taku Yamamoto, 2000. "Modified lag augmented vector autoregressions," Econometric Reviews, Taylor & Francis Journals, vol. 19(2), pages 207-231.
    16. Unknown, 1986. "Letters," Choices: The Magazine of Food, Farm, and Resource Issues, Agricultural and Applied Economics Association, vol. 1(4), pages 1-9.
    17. Fama, Eugene F. & French, Kenneth R., 1989. "Business conditions and expected returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 25(1), pages 23-49, November.
    18. So, Beong Soo & Shin, Dong Wan, 1999. "Cauchy Estimators For Autoregressive Processes With Applications To Unit Root Tests And Confidence Intervals," Econometric Theory, Cambridge University Press, vol. 15(2), pages 165-176, April.
    19. Chen, Willa W. & Deo, Rohit S., 2009. "Bias Reduction And Likelihood-Based Almost Exactly Sized Hypothesis Testing In Predictive Regressions Using The Restricted Likelihood," Econometric Theory, Cambridge University Press, vol. 25(5), pages 1143-1179, October.
    20. Heon Jin Park & Wayne A. Fuller, 1995. "Alternative Estimators And Unit Root Tests For The Autoregressive Process," Journal of Time Series Analysis, Wiley Blackwell, vol. 16(4), pages 415-429, July.
    21. Choi, In, 1993. "Asymptotic Normality of the Least-Squares Estimates for Higher Order Autoregressive Integrated Processes with Some Applications," Econometric Theory, Cambridge University Press, vol. 9(2), pages 263-282, April.
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    More about this item

    Keywords

    near unit root; bias; stock return; jackknife;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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