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Machine Learning and Forecast Combination in Incomplete Panels

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  • Kajal Lahiri
  • Huaming Peng
  • Yongchen Zhao

Abstract

This paper focuses on the newly proposed on-line forecast combination algorithms in Sancetta (2010), Yang (2004), and Wei and Yang (2012). We first establish the asymptotic relationship between these new algorithms and the Bates and Granger (1969) method. Then, we show that when implemented on unbalanced panels, different combination algorithms implicitly impute missing data differently, making results not comparable across methods. Using forecasts of a number of macroeconomic variables from the U.S. Survey of Professional Forecasters, we evaluate the performance of the new algorithms and contrast their inner mechanisms with that of Bates and Granger's method. Missing data in the SPF panels are specifically controlled for by explicit imputation. We find that even though equally weighted average is hard to beat, the new algorithms deliver superior performance especially during periods of volatility clustering and structural breaks.

Suggested Citation

  • Kajal Lahiri & Huaming Peng & Yongchen Zhao, 2013. "Machine Learning and Forecast Combination in Incomplete Panels," Discussion Papers 13-01, University at Albany, SUNY, Department of Economics.
  • Handle: RePEc:nya:albaec:13-01
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    File URL: http://www.albany.edu/economics/research/workingp/2013/lmz-comb.pdf
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    Cited by:

    1. Wei Qian & Craig A. Rolling & Gang Cheng & Yuhong Yang, 2015. "On the Forecast Combination Puzzle," Papers 1505.00475, arXiv.org.
    2. Cheng, Gang & Yang, Yuhong, 2015. "Forecast combination with outlier protection," International Journal of Forecasting, Elsevier, vol. 31(2), pages 223-237.
    3. Graham Elliott, 2017. "Forecast combination when outcomes are difficult to predict," Empirical Economics, Springer, vol. 53(1), pages 7-20, August.
    4. Constantin Burgi, 2016. "What Do We Lose When We Average Expectations?," Working Papers 2016-013, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    5. Wei Qian & Craig A. Rolling & Gang Cheng & Yuhong Yang, 2019. "On the Forecast Combination Puzzle," Econometrics, MDPI, Open Access Journal, vol. 7(3), pages 1-26, September.

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