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Point and Density Forecasts for the Euro Area Using Many Predictors: Are Large BVARs Really Superior?

Citations

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Cited by:

  1. Maik H. Wolters, 2015. "Evaluating Point and Density Forecasts of DSGE Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(1), pages 74-96, January.
  2. 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.
  3. Berg Tim Oliver, 2017. "Forecast accuracy of a BVAR under alternative specifications of the zero lower bound," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(2), pages 1-29, April.
  4. Tim Oliver Berg, 2016. "Multivariate Forecasting with BVARs and DSGE Models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(8), pages 718-740, December.
  5. Justyna Wróblewska & Anna Pajor, 2019. "One-period joint forecasts of Polish inflation, unemployment and interest rate using Bayesian VEC-MSF models," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 11(1), pages 23-45, March.
  6. Pestova, Anna & Mamonov, Mikhail, 2019. "Should we care? : The economic effects of financial sanctions on the Russian economy," BOFIT Discussion Papers 13/2019, Bank of Finland, Institute for Economies in Transition.
  7. Christian Grimme & Steffen Henzel & Elisabeth Wieland, 2014. "Inflation uncertainty revisited: a proposal for robust measurement," Empirical Economics, Springer, vol. 47(4), pages 1497-1523, December.
  8. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
  9. Wolfgang Nierhaus & Timo Wollmershäuser, 2016. "ifo Konjunkturumfragen und Konjunkturanalyse: Band II," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 72.
  10. Pestova, Anna & Mamonov, Mikhail, 2019. "Should we care? The economic effects of financial sanctions on the Russian economy," BOFIT Discussion Papers 13/2019, Bank of Finland Institute for Emerging Economies (BOFIT).
  11. Timo Wollmershäuser & Wolfgang Nierhaus & Tim Oliver Berg & Christian Breuer & Johanna Garnitz & Christian Grimme & Atanas Hristov & Nikolay Hristov & Wolfgang Meister & Magnus Reif & Felix Schröter &, 2015. "Ifo Economic Forecast 2015/2017: Modest Upswing Continues," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 68(24), pages 23-66, December.
  12. Mandalinci, Zeyyad, 2017. "Forecasting inflation in emerging markets: An evaluation of alternative models," International Journal of Forecasting, Elsevier, vol. 33(4), pages 1082-1104.
  13. Kuo‐Hsuan Chin, 2022. "Forecast evaluation of DSGE models: Linear and nonlinear likelihood," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1099-1130, September.
  14. Pirschel, Inske & Wolters, Maik H., 2014. "Forecasting German key macroeconomic variables using large dataset methods," Kiel Working Papers 1925, Kiel Institute for the World Economy (IfW Kiel).
  15. Martin Feldkircher & Nico Hauzenberger, 2019. "How useful are time-varying parameter models for forecasting economic growth in CESEE?," Focus on European Economic Integration, Oesterreichische Nationalbank (Austrian Central Bank), issue Q1/19, pages 29-48.
  16. Robert Lehmann & Klaus Wohlrabe, 2016. "Boosting and Forecasting German Industrial Output: What Does a Closer Look at the Details Tell Us?," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 69(03), pages 30-33, February.
  17. Hauzenberger, Niko & Huber, Florian & Klieber, Karin, 2023. "Real-time inflation forecasting using non-linear dimension reduction techniques," International Journal of Forecasting, Elsevier, vol. 39(2), pages 901-921.
  18. Dimitrios P. Louzis, 2017. "Macroeconomic and credit forecasts during the Greek crisis using Bayesian VARs," Empirical Economics, Springer, vol. 53(2), pages 569-598, September.
  19. Szafranek, Karol, 2019. "Bagged neural networks for forecasting Polish (low) inflation," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1042-1059.
  20. Boris B. Demeshev & Oxana A. Malakhovskaya, 2015. "Forecasting Russian Macroeconomic Indicators with BVAR," HSE Working papers WP BRP 105/EC/2015, National Research University Higher School of Economics.
  21. Reif Magnus, 2021. "Macroeconomic uncertainty and forecasting macroeconomic aggregates," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(2), pages 1-20, April.
  22. Demeshev, Boris & Malakhovskaya, Oxana, 2016. "BVAR mapping," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 43, pages 118-141.
  23. Solikin M. Juhro & Bernard Njindan Iyke, 2019. "Forecasting Indonesian Inflation Within An Inflation-Targeting Framework: Do Large-Scale Models Pay Off?," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 22(4), pages 423-436, December.
  24. Steffen Henzel & Robert Lehmann & Klaus Wohlrabe, 2015. "Die Machbarkeit von Kurzfristprognosen für den Freistaat Sachsen," ifo Dresden berichtet, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 22(04), pages 21-25, August.
  25. repec:zbw:bofitp:2019_013 is not listed on IDEAS
  26. Swamy, Vighneswara, 2020. "Macroeconomic transmission of Eurozone shocks to India—A mean-adjusted Bayesian VAR approach," Economic Analysis and Policy, Elsevier, vol. 68(C), pages 126-150.
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