To Bag is to Prune
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- Clements, Michael P. & Smith, Jeremy, 1997.
"The performance of alternative forecasting methods for SETAR models,"
International Journal of Forecasting, Elsevier, vol. 13(4), pages 463-475, December.
- Clements, Michael P & Smith, Jeremy, 1996. "Performance of Alternative Forecasting Methods for Setar Models," The Warwick Economics Research Paper Series (TWERPS) 467, University of Warwick, Department of Economics.
- Clements, Michael P. & Smith, Jeremy, 1996. "The Performance of Alternative Forecasting Methods for SETAR Models," Economic Research Papers 268737, University of Warwick - Department of Economics.
- Bergmeir, Christoph & Hyndman, Rob J. & Koo, Bonsoo, 2018. "A note on the validity of cross-validation for evaluating autoregressive time series prediction," Computational Statistics & Data Analysis, Elsevier, vol. 120(C), pages 70-83.
- Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2022.
"How is machine learning useful for macroeconomic forecasting?,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 920-964, August.
- Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2019. "How is Machine Learning Useful for Macroeconomic Forecasting?," CIRANO Working Papers 2019s-22, CIRANO.
- Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & St'ephane Surprenant, 2020. "How is Machine Learning Useful for Macroeconomic Forecasting?," Papers 2008.12477, arXiv.org.
- Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stephane Surprenant, 2020. "How is Machine Learning Useful for Macroeconomic Forecasting?," Working Papers 20-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Aug 2020.
- Maxime Leroux & Rachidi Kotchoni & Dalibor Stevanovic, 2017.
"Forecasting economic activity in data-rich environment,"
EconomiX Working Papers
2017-5, University of Paris Nanterre, EconomiX.
- Dalibor Stevanovic & Rachidi Kotchoni & Maxime Leroux, 2017. "Forecasting economic activity in data-rich environment," CIRANO Working Papers 2017s-05, CIRANO.
- Maxime Leroux & Rachidi Kotchoni & Dalibor Stevanovic, 2017. "Forecasting economic activity in data-rich environment," Working Papers hal-04141668, HAL.
- Goulet Coulombe, Philippe & Leroux, Maxime & Stevanovic, Dalibor & Surprenant, Stéphane, 2021.
"Macroeconomic data transformations matter,"
International Journal of Forecasting, Elsevier, vol. 37(4), pages 1338-1354.
- Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2020. "Macroeconomic Data Transformations Matter," CIRANO Working Papers 2020s-42, CIRANO.
- Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stephane Surprenant, 2020. "Macroeconomic Data Transformations Matter," Working Papers 20-17, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management, revised Mar 2021.
- Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & St'ephane Surprenant, 2020. "Macroeconomic Data Transformations Matter," Papers 2008.01714, arXiv.org, revised Mar 2021.
- Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
- Michael W. McCracken & Serena Ng, 2021.
"FRED-QD: A Quarterly Database for Macroeconomic Research,"
Review, Federal Reserve Bank of St. Louis, vol. 103(1), pages 1-44, January.
- Michael W. McCracken & Serena Ng, 2020. "FRED-QD: A Quarterly Database for Macroeconomic Research," Working Papers 2020-005, Federal Reserve Bank of St. Louis.
- Michael McCracken & Serena Ng, 2020. "FRED-QD: A Quarterly Database for Macroeconomic Research," NBER Working Papers 26872, National Bureau of Economic Research, Inc.
- Diebold, Francis X & Mariano, Roberto S, 2002.
"Comparing Predictive Accuracy,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
- Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-263, July.
- Francis X. Diebold & Roberto S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
- Friedman, Jerome H., 2002. "Stochastic gradient boosting," Computational Statistics & Data Analysis, Elsevier, vol. 38(4), pages 367-378, February.
- Stock, James H & Watson, Mark W, 2002. "Macroeconomic Forecasting Using Diffusion Indexes," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 147-162, April.
- Rapach, David & Zhou, Guofu, 2013. "Forecasting Stock Returns," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 328-383, Elsevier.
- Elliott, Graham & Gargano, Antonio & Timmermann, Allan, 2013.
"Complete subset regressions,"
Journal of Econometrics, Elsevier, vol. 177(2), pages 357-373.
- Elliott, Graham & Gargano, Antonio & Timmermann, Allan, 2013. "Complete subset regressions," University of California at San Diego, Economics Working Paper Series qt1st3n7z7, Department of Economics, UC San Diego.
- Klaus-Peter Hellwig, 2018. "Overfitting in Judgment-based Economic Forecasts: The Case of IMF Growth Projections," IMF Working Papers 2018/260, International Monetary Fund.
- G. Elliott & C. Granger & A. Timmermann (ed.), 2006. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 1, number 1.
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This paper has been announced in the following NEP Reports:- NEP-CMP-2020-09-07 (Computational Economics)
- NEP-ECM-2020-09-07 (Econometrics)
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