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Have economic models' forecasting performance for US output growth and inflation changed over time, and when?

Citations

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Cited by:

  1. Granziera, Eleonora & Sekhposyan, Tatevik, 2019. "Predicting relative forecasting performance: An empirical investigation," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1636-1657.
  2. Carlos Barros & Luis Gil-Alana, 2013. "Inflation Forecasting in Angola: A Fractional Approach," African Development Review, African Development Bank, vol. 25(1), pages 91-104.
  3. Bel, K. & Paap, R., 2013. "Modeling the impact of forecast-based regime switches on macroeconomic time series," Econometric Institute Research Papers EI 2013-25, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  4. González-Rivera, Gloria & Sun, Yingying, 2017. "Density forecast evaluation in unstable environments," International Journal of Forecasting, Elsevier, vol. 33(2), pages 416-432.
  5. Magdalena Grothe & Aidan Meyler, 2018. "Inflation Forecasts: Are Market-Based and Survey-Based Measures Informative?," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 9(1), pages 171-188, January.
  6. Brave, Scott A. & Butters, R. Andrew & Justiniano, Alejandro, 2019. "Forecasting economic activity with mixed frequency BVARs," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1692-1707.
  7. Mawuli Segnon & Rangan Gupta & Stelios Bekiros & Mark E. Wohar, 2018. "Forecasting US GNP growth: The role of uncertainty," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(5), pages 541-559, August.
  8. Plakandaras, Vasilios & Gogas, Periklis & Papadimitriou, Theophilos & Gupta, Rangan, 2019. "A re-evaluation of the term spread as a leading indicator," International Review of Economics & Finance, Elsevier, vol. 64(C), pages 476-492.
  9. Vasilios Plakandaras & Periklis Gogas & Theophilos Papadimitriou & Rangan Gupta, 2017. "The Informational Content of the Term Spread in Forecasting the US Inflation Rate: A Nonlinear Approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(2), pages 109-121, March.
  10. Martinez-Martin Jaime & Morris Richard & Onorante Luca & Piersanti Fabio Massimo, 2024. "Merging Structural and Reduced-Form Models for Forecasting," The B.E. Journal of Macroeconomics, De Gruyter, vol. 24(1), pages 399-437, January.
  11. Vasilios Plakandaras & Periklis Gogas & Theophilos Papadimitriou & Rangan Gupta, 2016. "The Term Premium as a Leading Macroeconomic Indicator," Working Papers 201613, University of Pretoria, Department of Economics.
  12. Niu, Linlin & Xu, Xiu & Chen, Ying, 2017. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," Economic Modelling, Elsevier, vol. 66(C), pages 201-213.
  13. Marta Crispino & Vincenzo Mariani, 2023. "A tool to nowcast tourist overnight stays with payment data and complementary indicators," Questioni di Economia e Finanza (Occasional Papers) 746, Bank of Italy, Economic Research and International Relations Area.
  14. Burgess, Matthew G. & Langendorf, Ryan E. & Ippolito, Tara & Pielke, Roger Jr, 2020. "Optimistically biased economic growth forecasts and negatively skewed annual variation," SocArXiv vndqr, Center for Open Science.
  15. Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2019. "Priors for the Long Run," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(526), pages 565-580, April.
  16. Faust, Jon & Wright, Jonathan H., 2013. "Forecasting Inflation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 2-56, Elsevier.
  17. Kihwan Kim & Hyun Hak Kim & Norman R. Swanson, 2023. "Mixing mixed frequency and diffusion indices in good times and in bad: an assessment based on historical data around the great recession of 2008," Empirical Economics, Springer, vol. 64(3), pages 1421-1469, March.
  18. Marcus P. A. Cobb, 2020. "Aggregate density forecasting from disaggregate components using Bayesian VARs," Empirical Economics, Springer, vol. 58(1), pages 287-312, January.
  19. Barbara Rossi, 2011. "Comment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 25-29, August.
  20. Barnett, Alina & Mumtaz, Haroon & Theodoridis, Konstantinos, 2014. "Forecasting UK GDP growth and inflation under structural change. A comparison of models with time-varying parameters," International Journal of Forecasting, Elsevier, vol. 30(1), pages 129-143.
  21. Carstensen Kai & Wohlrabe Klaus & Ziegler Christina, 2011. "Predictive Ability of Business Cycle Indicators under Test: A Case Study for the Euro Area Industrial Production," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 82-106, February.
  22. Benjamin Beckers & Konstantin A. Kholodilin & Dirk Ulbricht, 2017. "Reading between the Lines: Using Media to Improve German Inflation Forecasts," Discussion Papers of DIW Berlin 1665, DIW Berlin, German Institute for Economic Research.
  23. Anna Florio, 2016. "The central bank as shaper and observer of events: The case of the yield spread," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 49(1), pages 320-346, February.
  24. Raffaella Giacomini & Barbara Rossi, 2015. "Forecasting in Nonstationary Environments: What Works and What Doesn't in Reduced-Form and Structural Models," Annual Review of Economics, Annual Reviews, vol. 7(1), pages 207-229, August.
  25. Denis Shibitov & Mariam Mamedli, 2021. "Forecasting Russian Cpi With Data Vintages And Machine Learning Techniques," Bank of Russia Working Paper Series wps70, Bank of Russia.
  26. Joseph G. Haubrich, 2021. "Does the Yield Curve Predict Output?," Annual Review of Financial Economics, Annual Reviews, vol. 13(1), pages 341-362, November.
  27. Richard Ashley & Randal J. Verbrugge, 2019. "The Intermittent Phillips Curve: Finding a Stable (But Persistence-Dependent) Phillips Curve Model Specification," Working Papers 19-09R2, Federal Reserve Bank of Cleveland, revised 14 Feb 2023.
  28. Fossati, Sebastian, 2017. "Testing for State-Dependent Predictive Ability," Working Papers 2017-9, University of Alberta, Department of Economics.
  29. Rusnák, Marek, 2016. "Nowcasting Czech GDP in real time," Economic Modelling, Elsevier, vol. 54(C), pages 26-39.
  30. Sekkel, Rodrigo M., 2015. "Balance sheets of financial intermediaries: Do they forecast economic activity?," International Journal of Forecasting, Elsevier, vol. 31(2), pages 263-275.
  31. McKnight, Stephen & Mihailov, Alexander & Rumler, Fabio, 2020. "Inflation forecasting using the New Keynesian Phillips Curve with a time-varying trend," Economic Modelling, Elsevier, vol. 87(C), pages 383-393.
  32. Martínez-Martin, Jaime & Morris, Richard & Onorante, Luca & Piersanti, Fabio M., 2019. "Merging structural and reduced-form models for forecasting: opening the DSGE-VAR box," Working Paper Series 2335, European Central Bank.
  33. 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.
  34. Fabrizio Iacone & Luca Rossini & Andrea Viselli, 2024. "Comparing predictive ability in presence of instability over a very short time," Papers 2405.11954, arXiv.org.
  35. Jari Hännikäinen, 2015. "Zero lower bound, unconventional monetary policy and indicator properties of interest rate spreads," Review of Financial Economics, John Wiley & Sons, vol. 26(1), pages 47-54, September.
  36. repec:bof:bofitp:urn:nbn:fi:bof-201504131155 is not listed on IDEAS
  37. Rossi, Barbara & Sekhposyan, Tatevik, 2014. "Evaluating predictive densities of US output growth and inflation in a large macroeconomic data set," International Journal of Forecasting, Elsevier, vol. 30(3), pages 662-682.
  38. repec:zbw:bofitp:urn:nbn:fi:bof-201504131155 is not listed on IDEAS
  39. William A. Barnett & Sohee Park, 2023. "Forecasting inflation and output growth with credit‐card‐augmented Divisia monetary aggregates," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 331-346, March.
  40. David I. Harvey & Stephen J. Leybourne & Yang Zu, 2024. "Tests for equal forecast accuracy under heteroskedasticity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(5), pages 850-869, August.
  41. repec:zbw:bofrdp:2018_023 is not listed on IDEAS
  42. Serena Ng & Jonathan H. Wright, 2013. "Facts and Challenges from the Great Recession for Forecasting and Macroeconomic Modeling," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1120-1154, December.
  43. Bordo, Michael D. & Haubrich, Joseph G., 2022. "Some international evidence on the causal impact of the yield curve," Finance Research Letters, Elsevier, vol. 45(C).
  44. Granziera, Eleonora & Sekhposyan, Tatevik, 2019. "Predicting relative forecasting performance: An empirical investigation," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1636-1657.
  45. repec:hum:wpaper:sfb649dp2015-023 is not listed on IDEAS
  46. Koop, Gary, 2014. "Forecasting with dimension switching VARs," International Journal of Forecasting, Elsevier, vol. 30(2), pages 280-290.
  47. N. Kundan Kishor & Evan F. Koenig, 2022. "Finding a Role for Slack in Real-Time Inflation Forecasting," International Journal of Central Banking, International Journal of Central Banking, vol. 18(2), pages 245-282, June.
  48. Hännikäinen, Jari, 2015. "Zero lower bound, unconventional monetary policy and indicator properties of interest rate spreads," Review of Financial Economics, Elsevier, vol. 26(C), pages 47-54.
  49. Nonejad, Nima, 2023. "Conditional out-of-sample predictability of aggregate equity returns and aggregate equity return volatility using economic variables," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 91-122.
  50. Dur, Ayşe & Martínez García, Enrique, 2020. "Mind the gap!—A monetarist view of the open-economy Phillips curve," Journal of Economic Dynamics and Control, Elsevier, vol. 117(C).
  51. Li, You & Tay, Anthony, 2021. "The role of macroeconomic and policy uncertainty in density forecast dispersion," Journal of Macroeconomics, Elsevier, vol. 67(C).
  52. Liebermann, Joelle, 2012. "Real-time forecasting in a data-rich environment," MPRA Paper 39452, University Library of Munich, Germany.
  53. Yousuf, Kashif & Ng, Serena, 2021. "Boosting high dimensional predictive regressions with time varying parameters," Journal of Econometrics, Elsevier, vol. 224(1), pages 60-87.
  54. repec:zbw:bofitp:2015_012 is not listed on IDEAS
  55. Nonejad, Nima, 2020. "Crude oil price changes and the United Kingdom real gross domestic product growth rate: An out-of-sample investigation," The Journal of Economic Asymmetries, Elsevier, vol. 21(C).
  56. Bel, Koen & Paap, Richard, 2016. "Modeling the impact of forecast-based regime switches on US inflation," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1306-1316.
  57. Niu, Linlin & Xu, Xiu & Chen, Ying, 2017. "An adaptive approach to forecasting three key macroeconomic variables for transitional China," Economic Modelling, Elsevier, vol. 66(C), pages 201-213.
  58. Nima Nonejad, 2020. "A detailed look at crude oil price volatility prediction using macroeconomic variables," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1119-1141, November.
  59. Nonejad, Nima, 2020. "A comprehensive empirical analysis of the predictive impact of the price of crude oil on aggregate equity return volatility," Journal of Commodity Markets, Elsevier, vol. 20(C).
  60. Harun Özkan & M. Yazgan, 2015. "Is forecasting inflation easier under inflation targeting?," Empirical Economics, Springer, vol. 48(2), pages 609-626, March.
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