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Using Entropic Tilting to Combine BVAR Forecasts with External Nowcasts

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Cited by:

  1. Marta Bañbura & Danilo Leiva-León & Jan-Oliver Menz, 2021. "Do inflation expectations improve model-based inflation Forecasts?," Working Papers 2138, Banco de España.
  2. Konstantinos Metaxoglou & Davide Pettenuzzo & Aaron Smith, 2019. "Option-Implied Equity Premium Predictions via Entropic Tilting," The Journal of Financial Econometrics, Society for Financial Econometrics, vol. 17(4), pages 559-586.
  3. Tallman, Ellis W. & Zaman, Saeed, 2020. "Combining survey long-run forecasts and nowcasts with BVAR forecasts using relative entropy," International Journal of Forecasting, Elsevier, vol. 36(2), pages 373-398.
  4. McDonald, Christopher & Thamotheram, Craig & Vahey, Shaun P. & Wakerly, Elizabeth C., 2015. "Assessing the Economic Value of Probabilistic Forecasts in the Presence of an Inflation Target," EMF Research Papers 09, Economic Modelling and Forecasting Group.
  5. Knotek, Edward S. & Zaman, Saeed, 2019. "Financial nowcasts and their usefulness in macroeconomic forecasting," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1708-1724.
  6. Richard K. Crump & Stefano Eusepi & Domenico Giannone & Eric Qian & Argia M. Sbordone, 2021. "A Large Bayesian VAR of the United States Economy," Staff Reports 976, Federal Reserve Bank of New York.
  7. Taeyoung Doh, 2017. "Trend and Uncertainty in the Long-Term Real Interest Rate: Bayesian Exponential Tilting with Survey Data," Research Working Paper RWP 17-8, Federal Reserve Bank of Kansas City.
  8. Galvão, Ana Beatriz & Garratt, Anthony & Mitchell, James, 2021. "Does judgment improve macroeconomic density forecasts?," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1247-1260.
  9. Knotek, Edward S. & Zaman, Saeed, 2023. "Real-time density nowcasts of US inflation: A model combination approach," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1736-1760.
  10. Richard Schnorrenberger & Aishameriane Schmidt & Guilherme Valle Moura, 2024. "Harnessing Machine Learning for Real-Time Inflation Nowcasting," Working Papers 806, DNB.
  11. Marta Baltar Moreira Areosa & Wagner Piazza Gaglianone, 2023. "Anchoring Long-term VAR Forecasts Based On Survey Data and State-space Models," Working Papers Series 574, Central Bank of Brazil, Research Department.
  12. Christiane Baumeister, 2021. "Measuring Market Expectations," Working Papers 202163, University of Pretoria, Department of Economics.
  13. Markus Heinrich & Magnus Reif, 2020. "Real-Time Forecasting Using Mixed-Frequency VARS with Time-Varying Parameters," CESifo Working Paper Series 8054, CESifo.
  14. Gary Koop & Stuart McIntyre & James Mitchell, 2018. "UK regional nowcasting using a mixed frequency vector autoregressive model," Working Papers 1805, University of Strathclyde Business School, Department of Economics.
  15. Hauber, Philipp, 2021. "How useful is external information from professional forecasters? Conditional forecasts in large factor models," EconStor Preprints 251469, ZBW - Leibniz Information Centre for Economics.
  16. Kenourgios, Dimitris & Papadamou, Stephanos & Dimitriou, Dimitrios & Zopounidis, Constantin, 2020. "Modelling the dynamics of unconventional monetary policies’ impact on professionals’ forecasts," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 64(C).
  17. Barbara Rossi, 2019. "Forecasting in the Presence of Instabilities: How Do We Know Whether Models Predict Well and How to Improve Them," Working Papers 1162, Barcelona School of Economics.
  18. Ganics, Gergely & Odendahl, Florens, 2021. "Bayesian VAR forecasts, survey information, and structural change in the euro area," International Journal of Forecasting, Elsevier, vol. 37(2), pages 971-999.
  19. Malte Knüppel & Fabian Krüger, 2022. "Forecast uncertainty, disagreement, and the linear pool," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 23-41, January.
  20. Todd E. Clark & Gergely Ganics & Elmar Mertens, 2022. "What is the Predictive Value of SPF Point and Density Forecasts?," Working Papers 22-37, Federal Reserve Bank of Cleveland.
  21. Maryam Movahedifar & Hossein Hassani & Masoud Yarmohammadi & Mahdi Kalantari & Rangan Gupta, 2021. "A robust approach for outlier imputation: Singular Spectrum Decomposition," Working Papers 202164, University of Pretoria, Department of Economics.
  22. Fabian Krüger, 2017. "Survey-based forecast distributions for Euro Area growth and inflation: ensembles versus histograms," Empirical Economics, Springer, vol. 53(1), pages 235-246, August.
  23. Pablo Guerróon‐Quintana & Molin Zhong, 2023. "Macroeconomic forecasting in times of crises," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(3), pages 295-320, April.
  24. Cem Cakmakli & Hamza Demircan, 2020. "Using Survey Information for Improving the Density Nowcasting of US GDP with a Focus on Predictive Performance during Covid-19 Pandemic," Koç University-TUSIAD Economic Research Forum Working Papers 2016, Koc University-TUSIAD Economic Research Forum.
  25. Nadiia Shapovalenko, 2021. "A BVAR Model for Forecasting Ukrainian Inflation," IHEID Working Papers 05-2021, Economics Section, The Graduate Institute of International Studies.
  26. Montes-Galdón, Carlos & Paredes, Joan & Wolf, Elias, 2022. "Conditional density forecasting: a tempered importance sampling approach," Working Paper Series 2754, European Central Bank.
  27. Yuliya Rychalovska & Sergey Slobodyan & Rafael Wouters, 2023. "Professional Survey Forecasts and Expectations in DSGE Models," CERGE-EI Working Papers wp766, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
  28. Gary Koop & Stuart McIntyre & James Mitchell, 2020. "UK regional nowcasting using a mixed frequency vector auto‐regressive model with entropic tilting," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(1), pages 91-119, January.
  29. Bańbura, Marta & Brenna, Federica & Paredes, Joan & Ravazzolo, Francesco, 2021. "Combining Bayesian VARs with survey density forecasts: does it pay off?," Working Paper Series 2543, European Central Bank.
  30. Fabian Krüger & Sebastian Lerch & Thordis Thorarinsdottir & Tilmann Gneiting, 2021. "Predictive Inference Based on Markov Chain Monte Carlo Output," International Statistical Review, International Statistical Institute, vol. 89(2), pages 274-301, August.
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