Online learning and forecast combination in unbalanced panels
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DOI: 10.1080/07474938.2015.1114550
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Citations
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Cited by:
- Kajal Lahiri & Huaming Peng & Xuguang Simon Sheng, 2022.
"Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity,"
Advances in Econometrics, in: Essays in Honor of M. Hashem Pesaran: Prediction and Macro Modeling, volume 43, pages 29-50,
Emerald Group Publishing Limited.
- Kajal Lahiri & Huaming Peng & Xuguang Sheng, 2015. "Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity," CESifo Working Paper Series 5468, CESifo.
- Kajal Lahiri & Huaming Peng & Xuguang Simon Sheng, 2021. "Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity," Working Papers 2021-005, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
- Kajal Lahiri & Huaming Peng & Xuguang Sheng, 2020. "Measuring Uncertainty of a Combined Forecast and Some Tests for Forecaster Heterogeneity," CESifo Working Paper Series 8810, CESifo.
- Meryem Duygun & Jiaqi Hao & Anders Isaksson & Robin C. Sickles, 2017.
"World Productivity Growth: A Model Averaging Approach,"
Pacific Economic Review, Wiley Blackwell, vol. 22(4), pages 587-619, October.
- Duygun, Meryem & Hao, Jiaqi & Isaksson, Anders & Sickles, Robin C., 2015. "World Productivity Growth: A Model Averaging Approach," Working Papers 15-011, Rice University, Department of Economics.
- Constantin Bürgi & Tara M. Sinclair, 2017.
"A nonparametric approach to identifying a subset of forecasters that outperforms the simple average,"
Empirical Economics, Springer, vol. 53(1), pages 101-115, August.
- Constantin Bürgi & Tara M. Sinclair, 2015. "A Nonparametric Approach to Identifying a Subset of Forecasters that Outperforms the Simple Average," Working Papers 2015-006, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
- Glas, Alexander & Hartmann, Matthias, 2016.
"Inflation uncertainty, disagreement and monetary policy: Evidence from the ECB Survey of Professional Forecasters,"
Journal of Empirical Finance, Elsevier, vol. 39(PB), pages 215-228.
- Glas, Alexander & Hartmann, Matthias, 2016. "Inflation uncertainty, disagreement and monetary policy: Evidence from the ECB Survey of Professional Forecasters," Working Papers 0612, University of Heidelberg, Department of Economics.
- Glas, Alexander & Hartmann, Matthias, 2016. "Inflation uncertainty, disagreement and monetary policy: Evidence from the ECB Survey of Professional Forecasters," VfS Annual Conference 2016 (Augsburg): Demographic Change 145888, Verein für Socialpolitik / German Economic Association.
- Yongchen Zhao, 2021.
"The robustness of forecast combination in unstable environments: a Monte Carlo study of advanced algorithms,"
Empirical Economics, Springer, vol. 61(1), pages 173-199, July.
- Yongchen Zhao, 2015. "Robustness of Forecast Combination in Unstable Environment: A Monte Carlo Study of Advanced Algorithms," Working Papers 2015-005, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
- Yongchen Zhao, 2015. "Robustness of Forecast Combination in Unstable Environment: A Monte Carlo Study of Advanced Algorithms," Working Papers 2015-04, Towson University, Department of Economics, revised Mar 2020.
- Constantin Rudolf Salomo Bürgi, 2023.
"How to deal with missing observations in surveys of professional forecasters,"
Journal of Applied Economics, Taylor & Francis Journals, vol. 26(1), pages 2185975-218, December.
- Constantin Bürgi, 2023. "How to Deal With Missing Observations in Surveys of Professional Forecasters," CESifo Working Paper Series 10203, CESifo.
- Wei Qian & Craig A. Rolling & Gang Cheng & Yuhong Yang, 2019. "On the Forecast Combination Puzzle," Econometrics, MDPI, vol. 7(3), pages 1-26, September.
- Qian, Wei & Rolling, Craig A. & Cheng, Gang & Yang, Yuhong, 2022. "Combining forecasts for universally optimal performance," International Journal of Forecasting, Elsevier, vol. 38(1), pages 193-208.
- Hounyo, Ulrich & Lahiri, Kajal, 2023.
"Estimating the variance of a combined forecast: Bootstrap-based approach,"
Journal of Econometrics, Elsevier, vol. 232(2), pages 445-468.
- Ulrich Hounyo & Kajal Lahiri, 2021. "Estimating the Variance of a Combined Forecast: Bootstrap-Based Approach," CREATES Research Papers 2021-14, Department of Economics and Business Economics, Aarhus University.
- Antonio Martin Arroyo & Aranzazu de Juan Fernandez, 2020. "Split-then-Combine simplex combination and selection of forecasters," Papers 2012.11935, arXiv.org.
- Valentina Corradi & Sainan Jin & Norman R. Swanson, 2023. "Robust forecast superiority testing with an application to assessing pools of expert forecasters," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 596-622, June.
- Ulrich Hounyo & Kajal Lahiri, 2023. "Are Some Forecasters Really Better than Others? A Note," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 55(2-3), pages 577-593, March.
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