IDEAS home Printed from https://ideas.repec.org/r/duk/dukeec/10-16.html
   My bibliography  Save this item

Has Models' Forecasting Performance for US Output Growth and Inflation Changed over Time, and When?

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Juan Carlos Pérez-Velasco Pavón, 2009. "Determinantes de la demanda por la denominación promedio de billete: el caso de México," Monetaria, CEMLA, vol. 0(4), pages 523-548, octubre-d.
  2. 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.
  3. Galvão, Ana Beatriz, 2013. "Changes in predictive ability with mixed frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 395-410.
  4. Granziera, Eleonora & Sekhposyan, Tatevik, 2019. "Predicting relative forecasting performance: An empirical investigation," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1636-1657.
  5. 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.
  6. 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.
  7. Elena Andreou & Eric Ghysels & Andros Kourtellos, 2013. "Should Macroeconomic Forecasters Use Daily Financial Data and How?," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(2), pages 240-251, April.
  8. 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.
  9. Antonello D'Agostino & Luca Gambetti & Domenico Giannone, 2013. "Macroeconomic forecasting and structural change," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(1), pages 82-101, January.
  10. 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.
  11. González-Rivera, Gloria & Sun, Yingying, 2017. "Density forecast evaluation in unstable environments," International Journal of Forecasting, Elsevier, vol. 33(2), pages 416-432.
  12. 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.
  13. 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.
  14. Anna Florio, 2016. "The central bank as shaper and observer of events: The case of the yield spread," Canadian Journal of Economics, Canadian Economics Association, vol. 49(1), pages 320-346, February.
  15. 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.
  16. Rusnák, Marek, 2016. "Nowcasting Czech GDP in real time," Economic Modelling, Elsevier, vol. 54(C), pages 26-39.
  17. 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.
  18. Koop, Gary, 2014. "Forecasting with dimension switching VARs," International Journal of Forecasting, Elsevier, vol. 30(2), pages 280-290.
  19. 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.
  20. Kirdan Lees, 2009. "Overview of a recent Reserve Bank workshop: nowcasting with model combination," Reserve Bank of New Zealand Bulletin, Reserve Bank of New Zealand, vol. 72, pages 31-33, March.
  21. 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.
  22. 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.
  23. 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.
  24. Pierre Perron & Yohei Yamamoto, 2008. "Estimating and Testing Multiple Structural Changes in Models with Endogenous Regressors," Boston University - Department of Economics - Working Papers Series wp2008-017, Boston University - Department of Economics.
  25. Pierre Perron & Yohei Yamamoto, 2015. "Using OLS to Estimate and Test for Structural Changes in Models with Endogenous Regressors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(1), pages 119-144, January.
  26. 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.
  27. Juan Díaz Maureira & Gustavo Leyva Jiménez, 2009. "Proyección de la inflación chilena en tiempos difíciles," Monetaria, CEMLA, vol. 0(4), pages 491-522, octubre-d.
  28. 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.
  29. 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.
  30. Strauss, Jack, 2013. "Does housing drive state-level job growth? Building permits and consumer expectations forecast a state’s economic activity," Journal of Urban Economics, Elsevier, vol. 73(1), pages 77-93.
  31. 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.
  32. 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).
  33. Li, You & Tay, Anthony, 2021. "The role of macroeconomic and policy uncertainty in density forecast dispersion," Journal of Macroeconomics, Elsevier, vol. 67(C).
  34. Marcus P. A. Cobb, 2020. "Aggregate density forecasting from disaggregate components using Bayesian VARs," Empirical Economics, Springer, vol. 58(1), pages 287-312, January.
  35. 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.
  36. 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.
  37. Barbara Rossi, 2011. "Comment," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 25-29, August.
  38. 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.
  39. Liebermann, Joelle, 2012. "Real-time forecasting in a data-rich environment," MPRA Paper 39452, University Library of Munich, Germany.
  40. Yousuf, Kashif & Ng, Serena, 2021. "Boosting high dimensional predictive regressions with time varying parameters," Journal of Econometrics, Elsevier, vol. 224(1), pages 60-87.
  41. Manzan, Sebastiano & Zerom, Dawit, 2013. "Are macroeconomic variables useful for forecasting the distribution of U.S. inflation?," International Journal of Forecasting, Elsevier, vol. 29(3), pages 469-478.
  42. repec:zbw:bofitp:2015_012 is not listed on IDEAS
  43. 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.
  44. 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).
  45. Joseph G. Haubrich, 2021. "Does the Yield Curve Predict Output?," Annual Review of Financial Economics, Annual Reviews, vol. 13(1), pages 341-362, November.
  46. 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.
  47. 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.
  48. Fossati, Sebastian, 2017. "Testing for State-Dependent Predictive Ability," Working Papers 2017-9, University of Alberta, Department of Economics.
  49. 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.
  50. 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.
  51. 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.
  52. 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).
  53. Ricardo Gimeno & José Manuel Marqués-Sevillano, 2009. "Incertidumbre y el precio del riesgo en un proceso de convergencia nominal," Monetaria, CEMLA, vol. 0(4), pages 451-489, octubre-d.
  54. Andrés Schneider, 2009. "Regímenes de flotación administrada: un enfoque de cartera," Monetaria, CEMLA, vol. 0(4), pages 549-584, octubre-d.
  55. 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.
  56. 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.
  57. Harun Özkan & M. Yazgan, 2015. "Is forecasting inflation easier under inflation targeting?," Empirical Economics, Springer, vol. 48(2), pages 609-626, March.
  58. repec:bof:bofitp:urn:nbn:fi:bof-201504131155 is not listed on IDEAS
  59. repec:zbw:bofitp:urn:nbn:fi:bof-201504131155 is not listed on IDEAS
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.