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Predictive regressions with panel data

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  • Hjalmarsson, Erik

    () (Department of Economics)

Abstract

This paper analyzes econometric inference in predictive regressions in a panel data setting. In a traditional time-series framework, estimation and testing are often made difficult by the endogeneity and near persistence of many forecasting variables; tests of whether the dividend-price ratio predicts stock returns is a prototypical example. I show that, by pooling the data, these econometric issues can be dealt with more easily. When no individual intercepts are included in the pooled regression, the pooled estimator has an asymptotically normal distribution and standard tests can be performed. However, when fixed effects are included in the specification, a second order bias in the fixed effects estimator arises from the endogeneity and persistence of the regressors. A new estimator based on recursive demeaning is proposed and its asymptotic normality is derived; the procedure requires no knowledge of the degree of persistence in the regressors and thus sidesteps the main inferential problems in the time-series case. Since forecasting regressions are typically applied to financial or macroeconomic data, the traditional panel data assumption of cross-sectional independence is likely to be violated. New methods for dealing with common factors in the data are therefore also developed. The analytical results derived in the paper are supported by Monte Carlo evidence.

Suggested Citation

  • Hjalmarsson, Erik, 2005. "Predictive regressions with panel data," Working Papers in Economics 160, University of Gothenburg, Department of Economics.
  • Handle: RePEc:hhs:gunwpe:0160
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    File URL: http://hdl.handle.net/2077/2765
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    References listed on IDEAS

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    1. Moon, Hyungsik R. & Phillips, Peter C.B., 2000. "Estimation Of Autoregressive Roots Near Unity Using Panel Data," Econometric Theory, Cambridge University Press, vol. 16(06), pages 927-997, December.
    2. Goetzmann, William Nelson & Jorion, Philippe, 1993. " Testing the Predictive Power of Dividend Yields," Journal of Finance, American Finance Association, vol. 48(2), pages 663-679, June.
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    16. Erik Hjalmarsson, 2005. "Estimation of average local-to-unity roots in heterogenous panels," International Finance Discussion Papers 852, Board of Governors of the Federal Reserve System (U.S.).
    17. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, July.
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    Citations

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    Cited by:

    1. Hjalmarsson, Erik, 2005. "On the Predictability of Global Stock Returns," Working Papers in Economics 161, University of Gothenburg, Department of Economics.
    2. Badi H. Baltagi, 2008. "Forecasting with panel data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(2), pages 153-173.
    3. Baltagi, Badi H., 2013. "Panel Data Forecasting," Handbook of Economic Forecasting, Elsevier.
    4. Angelica Gonzalez, 2007. "Angelica Gonzalez," ESE Discussion Papers 168, Edinburgh School of Economics, University of Edinburgh.

    More about this item

    Keywords

    Predictive regression; panel data; pooled regression; cross-sectional dependence; stock return predictability; fully modified estimation; local-to-unity;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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