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The Stambaugh bias in panel predictive regressions

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Abstract

This paper analyzes predictive regressions in a panel data setting. The standard fixed effects estimator suffers from a small sample bias, which is the analogue of the Stambaugh bias in time-series predictive regressions. Monte Carlo evidence shows that the bias and resulting size distortions can be severe. A new bias-corrected estimator is proposed, which is shown to work well in finite samples and to lead to approximately normally distributed t-statistics. Overall, the results show that the econometric issues associated with predictive regressions when using time-series data to a large extent also carry over to the panel case. The results are illustrated with an application to predictability in international stock indices.

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  • Erik Hjalmarsson, 2007. "The Stambaugh bias in panel predictive regressions," International Finance Discussion Papers 914, Board of Governors of the Federal Reserve System (U.S.).
    • Handle: RePEc:fip:fedgif:914
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    1. Randolph B. Cohen & Christopher Polk & Tuomo Vuolteenaho, 2003. "The Value Spread," Journal of Finance, American Finance Association, vol. 58(2), pages 609-641, April.
    2. Moon, Hyungsik R. & Phillips, Peter C.B., 2000. "Estimation Of Autoregressive Roots Near Unity Using Panel Data," Econometric Theory, Cambridge University Press, vol. 16(6), pages 927-997, December.
    3. Andrew Ang & Geert Bekaert, 2007. "Stock Return Predictability: Is it There?," The Review of Financial Studies, Society for Financial Studies, vol. 20(3), pages 651-707.
    4. repec:rus:hseeco:52003 is not listed on IDEAS
    5. Polk, Christopher & Thompson, Samuel & Vuolteenaho, Tuomo, 2006. "Cross-sectional forecasts of the equity premium," Journal of Financial Economics, Elsevier, vol. 81(1), pages 101-141, July.
    6. Campbell, John Y. & Yogo, Motohiro, 2006. "Efficient tests of stock return predictability," Journal of Financial Economics, Elsevier, vol. 81(1), pages 27-60, July.
    7. Stambaugh, Robert F., 1999. "Predictive regressions," Journal of Financial Economics, Elsevier, vol. 54(3), pages 375-421, December.
    8. Peter C. B. Phillips & Hyungsik R. Moon, 1999. "Linear Regression Limit Theory for Nonstationary Panel Data," Econometrica, Econometric Society, vol. 67(5), pages 1057-1112, September.
    9. Hjalmarsson, Erik, 2010. "Predicting Global Stock Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(1), pages 49-80, February.
    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. repec:cup:etheor:v:11:y:1995:i:5:p:1131-47 is not listed on IDEAS
    12. 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.
    13. Lewellen, Jonathan, 2004. "Predicting returns with financial ratios," Journal of Financial Economics, Elsevier, vol. 74(2), pages 209-235, November.
    14. Randolph B. Cohen & Christopher Polk & Tuomo Vuolteenaho, 2001. "The Value Spread," NBER Working Papers 8242, National Bureau of Economic Research, Inc.
    15. Unknown, 1986. "Letters," Choices: The Magazine of Food, Farm, and Resource Issues, Agricultural and Applied Economics Association, vol. 1(4), pages 1-9.
    16. Randolph B. Cohen & Christopher Polk & Tuomo Vuolteenaho, 2003. "The Value Spread," Journal of Finance, American Finance Association, vol. 58(2), pages 609-642, April.
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    Cited by:

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    2. Skintzi, Vasiliki D., 2019. "Determinants of stock-bond market comovement in the Eurozone under model uncertainty," International Review of Financial Analysis, Elsevier, vol. 61(C), pages 20-28.
    3. Ayelen Banegas, 2016. "Predictability of Growth in Emerging Markets: Information in Financial Aggregates," International Finance Discussion Papers 1174, Board of Governors of the Federal Reserve System (U.S.).
    4. Westerlund, Joakim & Narayan, Paresh Kumar & Zheng, Xinwei, 2015. "Testing for stock return predictability in a large Chinese panel," Emerging Markets Review, Elsevier, vol. 24(C), pages 81-100.
    5. Robin Greenwood & Samuel G. Hanson & Andrei Shleifer & Jakob Ahm Sørensen, 2022. "Predictable Financial Crises," Journal of Finance, American Finance Association, vol. 77(2), pages 863-921, April.
    6. Hagenhoff, Tim & Lustenhouwer, Joep, 2020. "The role of stickiness, extrapolation and past consensus forecasts in macroeconomic expectations," BERG Working Paper Series 163, Bamberg University, Bamberg Economic Research Group.
    7. Stephan Smeekes & Joakim Westerlund, 2019. "Robust block bootstrap panel predictability tests," Econometric Reviews, Taylor & Francis Journals, vol. 38(9), pages 1089-1107, October.
    8. Wang, Cindy S.H. & Chen, Yi-Chi & Lo, Hsin-Yu, 2021. "A fresh look at the risk-return tradeoff," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    9. Victor Troster & José Penalva & Abderrahim Taamouti & Dominik Wied, 2021. "Cointegration, information transmission, and the lead‐lag effect between industry portfolios and the stock market," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(7), pages 1291-1309, November.
    10. Hagenhoff, Tim & Lustenhouwer, Joep, 2020. "The role of stickiness, extrapolation and past consensus forecasts in macroeconomic expectations," Working Papers 0686, University of Heidelberg, Department of Economics.
    11. Karabiyik, Hande & Westerlund, Joakim & Narayan, Paresh, 2016. "On the estimation and testing of predictive panel regressions," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 45(C), pages 115-125.
    12. Lawrenz, Jochen & Zorn, Josef, 2018. "Decomposing the predictive power of local and global financial valuation ratios," The Quarterly Review of Economics and Finance, Elsevier, vol. 70(C), pages 137-149.
    13. Westerlund, Joakim & Narayan, Paresh, 2016. "Testing for predictability in panels of any time series dimension," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1162-1177.
    14. Devpura, Neluka & Narayan, Paresh Kumar & Sharma, Susan Sunila, 2018. "Is stock return predictability time-varying?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 52(C), pages 152-172.
    15. Malte Rengel, 2020. "Sustainability of European fiscal balances: Just a statistical artifact?," Empirical Economics, Springer, vol. 58(4), pages 1681-1712, April.

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    Keywords

    Panel analysis; Stocks;

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