Forecasting Macroeconomic Variables under Model Instability

Citations

Cited by:

1. Delle Monache, Davide & Petrella, Ivan, 2017. "Adaptive models and heavy tails with an application to inflation forecasting," International Journal of Forecasting, Elsevier, vol. 33(2), pages 482-501.
   • Delle Monache, Davide & Petrella, Ivan, 2016. "Adaptive models and heavy tails with an application to inflation forecasting," MPRA Paper 75424, University Library of Munich, Germany.
   • Davide Delle Monache & Ivan Petrella, 2016. "Adaptive models and heavy tails with an application to inflation forecasting," BCAM Working Papers 1603, Birkbeck Centre for Applied Macroeconomics.
2. Hillebrand, Eric & Lukas, Manuel & Wei, Wei, 2021. "Bagging weak predictors," International Journal of Forecasting, Elsevier, vol. 37(1), pages 237-254.
   • Manuel Lukas & Eric Hillebrand, 2014. "Bagging Weak Predictors," CREATES Research Papers 2014-01, Department of Economics and Business Economics, Aarhus University.
   • Eric Hillebrand & Manuel Lukas & Wei Wei, 2020. "Bagging Weak Predictors," Monash Econometrics and Business Statistics Working Papers 16/20, Monash University, Department of Econometrics and Business Statistics.
3. Chen, Qitong & Hong, Yongmiao & Li, Haiqi, 2024. "Time-varying forecast combination for factor-augmented regressions with smooth structural changes," Journal of Econometrics, Elsevier, vol. 240(1).
4. repec:rim:rimwps:18-20 is not listed on IDEAS
5. Gary Koop & Dimitris Korobilis, 2023. "Bayesian Dynamic Variable Selection In High Dimensions," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 64(3), pages 1047-1074, August.
   • Gary Koop & Dimitris Korobilis, 2018. "Bayesian dynamic variable selection in high dimensions," Papers 1809.03031, arXiv.org, revised May 2020.
   • Korobilis, Dimitris & Koop, Gary, 2020. "Bayesian dynamic variable selection in high dimensions," MPRA Paper 100164, University Library of Munich, Germany.
   • Gary Koop & Dimitris Korobilis, 2020. "Bayesian dynamic variable selection in high dimensions," Working Papers 2020_11, Business School - Economics, University of Glasgow.
6. Gary Koop & Dimitris Korobilis, 2019. "Forecasting with High‐Dimensional Panel VARs," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 81(5), pages 937-959, October.
7. Petropoulos, Fotios & Spiliotis, Evangelos & Panagiotelis, Anastasios, 2023. "Model combinations through revised base rates," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1477-1492.
8. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
9. Olena Rayevnyeva & Volodymyr Ponomarenko & Silvia Matusova & Kostyantyn Stryzhychenko & Stanislav Filip & Olha Brovko, 2024. "Models of the Impact of Socio-Economic Shocks on Higher Education Development," Administrative Sciences, MDPI, vol. 14(11), pages 1-28, October.
10. Emilian DOBRESCU, 2017. "Modelling an Emergent Economy and Parameter Instability Problem," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 5-28, June.
11. Alessandra Canepa, & Karanasos, Menelaos & Paraskevopoulos, Athanasios & Chini, Emilio Zanetti, 2022. "Forecasting Ination: A GARCH-in-Mean-Level Model with Time Varying Predictability," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202212, University of Turin.
12. Eraslan, Sercan & Schröder, Maximilian, 2019. "Nowcasting GDP with a large factor model space," Discussion Papers 41/2019, Deutsche Bundesbank.
13. Dimitris Korobilis, 2021. "High-Dimensional Macroeconomic Forecasting Using Message Passing Algorithms," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(2), pages 493-504, March.
14. , & Stein, Tobias, 2021. "Equity premium predictability over the business cycle," CEPR Discussion Papers 16357, C.E.P.R. Discussion Papers.
    • Mönch, Emanuel & Stein, Tobias, 2021. "Equity premium predictability over the business cycle," Discussion Papers 25/2021, Deutsche Bundesbank.
15. Rachidi Kotchoni & Maxime Leroux & Dalibor Stevanovic, 2019. "Macroeconomic forecast accuracy in a data‐rich environment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(7), pages 1050-1072, November.
    • Rachidi Kotchoni & Maxime Leroux & Dalibor Stevanovic, 2019. "Macroeconomic Forecast Accuracy in data-rich environment," Post-Print hal-02435757, HAL.
16. Eraslan, Sercan & Schröder, Maximilian, 2023. "Nowcasting GDP with a pool of factor models and a fast estimation algorithm," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1460-1476.
17. Korobilis, Dimitris, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," MPRA Paper 96079, University Library of Munich, Germany.
    • Dimitris Korobilis, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," Working Papers 2019-07, Business School - Economics, University of Glasgow.
    • Dimitris Korobilis, 2020. "High-dimensional macroeconomic forecasting using message passing algorithms," Papers 2004.11485, arXiv.org.
    • Dimitris Korobilis, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," Working Paper series 19-17, Rimini Centre for Economic Analysis.
18. Yousuf, Kashif & Ng, Serena, 2021. "Boosting high dimensional predictive regressions with time varying parameters," Journal of Econometrics, Elsevier, vol. 224(1), pages 60-87.
    • Kashif Yousuf & Serena Ng, 2019. "Boosting High Dimensional Predictive Regressions with Time Varying Parameters," Papers 1910.03109, arXiv.org.
19. Zhou, Weilun & Gao, Jiti & Harris, David & Kew, Hsein, 2024. "Semi-parametric single-index predictive regression models with cointegrated regressors," Journal of Econometrics, Elsevier, vol. 238(1).
20. Prüser, Jan, 2023. "Data-based priors for vector error correction models," International Journal of Forecasting, Elsevier, vol. 39(1), pages 209-227.
21. Daniel Borup & Jonas N. Eriksen & Mads M. Kjær & Martin Thyrsgaard, 2024. "Predicting Bond Return Predictability," Management Science, INFORMS, vol. 70(2), pages 931-951, February.
    • Daniel Borup & Jonas N. Eriksen & Mads M. Kjær & Martin Thyrsgaard, 2020. "Predicting bond return predictability," CREATES Research Papers 2020-09, Department of Economics and Business Economics, Aarhus University.
22. Markus Heinrich & Magnus Reif, 2020. "Real-Time Forecasting Using Mixed-Frequency VARS with Time-Varying Parameters," CESifo Working Paper Series 8054, CESifo.
23. Nguyen Duc Do, 2025. "Using a Wage–Price‐Setting Model to Forecast US Inflation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(2), pages 803-832, March.
24. Philippe Goulet Coulombe, 2020. "Time-Varying Parameters as Ridge Regressions," Papers 2009.00401, arXiv.org, revised Nov 2024.