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An evaluation of inflation forecasts from surveys using real-time data

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Cited by:

  1. Soojin Jo & Rodrigo Sekkel, 2019. "Macroeconomic Uncertainty Through the Lens of Professional Forecasters," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(3), pages 436-446, July.
  2. 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.
  3. James Yetman & Gregor W. Smith, 2007. "The Curse Of Irving Fisher (professional Forecasters' Version)," Working Paper 1144, Economics Department, Queen's University.
  4. Ahmed, M. Iqbal & Cassou, Steven P., 2021. "Asymmetries in the effects of unemployment expectation shocks as monetary policy shifts with economic conditions," Economic Modelling, Elsevier, vol. 100(C).
  5. Olivier Coibion & Yuriy Gorodnichenko & Rupal Kamdar, 2018. "The Formation of Expectations, Inflation, and the Phillips Curve," Journal of Economic Literature, American Economic Association, vol. 56(4), pages 1447-1491, December.
  6. James M. Nason & Gregor W. Smith, 2021. "Measuring the slowly evolving trend in US inflation with professional forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(1), pages 1-17, January.
  7. Katharina Glass & Ulrich Fritsche, 2015. "Real-time Macroeconomic Data and Uncertainty," Macroeconomics and Finance Series 201406, University of Hamburg, Department of Socioeconomics.
  8. Rubaszek, Michal & Skrzypczynski, Pawel, 2008. "On the forecasting performance of a small-scale DSGE model," International Journal of Forecasting, Elsevier, vol. 24(3), pages 498-512.
  9. Bedri Kamil Onur Taş, 2016. "Does the Federal Reserve have Private Information about its Future Actions?," Economica, London School of Economics and Political Science, vol. 83(331), pages 498-517, July.
  10. Charles Engel & John H Rogers, 2009. "Expected Consumption Growth from Cross-Country Surveys: Implications for Assessing International Capital Markets," IMF Staff Papers, Palgrave Macmillan, vol. 56(3), pages 543-573, August.
  11. Pablo Pincheira B. & Nicolás Fernández, 2011. "Jaque Mate a las Proyecciones de Consenso," Working Papers Central Bank of Chile 630, Central Bank of Chile.
  12. Barbara Rossi & Tatevik Sekhposyan, 2016. "Forecast Rationality Tests in the Presence of Instabilities, with Applications to Federal Reserve and Survey Forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(3), pages 507-532, April.
  13. Filip Novotný & Marie Raková, 2011. "Assessment of Consensus Forecasts Accuracy: The Czech National Bank Perspective," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 61(4), pages 348-366, August.
  14. Todd E. Clark & Michael W. McCracken & Elmar Mertens, 2020. "Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors," The Review of Economics and Statistics, MIT Press, vol. 102(1), pages 17-33, March.
  15. Dick Dijk & Siem Jan Koopman & Michel Wel & Jonathan H. Wright, 2014. "Forecasting interest rates with shifting endpoints," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(5), pages 693-712, August.
  16. Anthony Garratt & Gary Koop & ShaunP. Vahey, 2008. "Forecasting Substantial Data Revisions in the Presence of Model Uncertainty," Economic Journal, Royal Economic Society, vol. 118(530), pages 1128-1144, July.
  17. Michal Rubaszek & Pawel Skrzypczynski, 2007. "Can a simple DSGE model outperform Professional Forecasters?," Working Papers 5, Department of Applied Econometrics, Warsaw School of Economics.
  18. Josef C. Brada & Jan KubÃ­Ä ek & Ali M. Kutan & Vladimír Tomšík, 2015. "Inflation Targeting: Insights from Behavioral Economics," Eastern European Economics, Taylor & Francis Journals, vol. 53(5), pages 357-376, September.
  19. Croushore Dean, 2010. "An Evaluation of Inflation Forecasts from Surveys Using Real-Time Data," The B.E. Journal of Macroeconomics, De Gruyter, vol. 10(1), pages 1-32, May.
  20. 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.
  21. Fabiana Gomez & David Pacini, 2015. "Counting Biased Forecasters: An Application of Multiple Testing Techniques," Bristol Economics Discussion Papers 15/661, School of Economics, University of Bristol, UK.
  22. Devereux, Michael B. & Smith, Gregor W. & Yetman, James, 2012. "Consumption and real exchange rates in professional forecasts," Journal of International Economics, Elsevier, vol. 86(1), pages 33-42.
  23. Elmar Mertens & James M. Nason, 2020. "Inflation and professional forecast dynamics: An evaluation of stickiness, persistence, and volatility," Quantitative Economics, Econometric Society, vol. 11(4), pages 1485-1520, November.
  24. Matei Demetrescu & Christoph Hanck & Robinson Kruse‐Becher, 2022. "Robust inference under time‐varying volatility: A real‐time evaluation of professional forecasters," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 1010-1030, August.
  25. Nikolsko-Rzhevskyy, Alex, 2008. "Monetary Policy Evaluation in Real Time: Forward-Looking Taylor Rules Without Forward-Looking Data," MPRA Paper 11352, University Library of Munich, Germany.
  26. Dean Croushore & Katherine Marsten, 2014. "The continuing power of the yield spread in forecasting recessions," Working Papers 14-5, Federal Reserve Bank of Philadelphia.
  27. Pincheira, Pablo, 2013. "A Bunch of Models, a Bunch of Nulls and Inference about Predictive Ability," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 26-43, October.
  28. Nicolas Reigl, 2023. "Noise shocks and business cycle fluctuations in three major European Economies," Empirical Economics, Springer, vol. 64(2), pages 603-657, February.
  29. Chrystalleni Aristidou & Kevin Lee & Kalvinder Shields, 2015. "Real-Time Data should be used in Forecasting Output Growth and Recessionary Events in the US," Discussion Papers 2015/13, University of Nottingham, Centre for Finance, Credit and Macroeconomics (CFCM).
  30. Reifschneider, David & Tulip, Peter, 2019. "Gauging the uncertainty of the economic outlook using historical forecasting errors: The Federal Reserve’s approach," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1564-1582.
  31. Eric Eisenstat & Rodney W. Strachan, 2016. "Modelling Inflation Volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(5), pages 805-820, August.
  32. Marcin Kolasa & Michał Rubaszek & Paweł Skrzypczyński, 2012. "Putting the New Keynesian DSGE Model to the Real‐Time Forecasting Test," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(7), pages 1301-1324, October.
  33. Kurt Graden Lunsford & Kenneth D. West, 2023. "Random Walk Forecasts of Stationary Processes Have Low Bias," Working Papers 23-18, Federal Reserve Bank of Cleveland.
  34. Smith, Gregor W., 2009. "Pooling forecasts in linear rational expectations models," Journal of Economic Dynamics and Control, Elsevier, vol. 33(11), pages 1858-1866, November.
  35. Paul Hubert & Harun Mirza, 2019. "The role of forward‐ and backward‐looking information for inflation expectations formation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 38(8), pages 733-748, December.
  36. Gimeno, Ricardo & Ibáñez, Alfredo, 2018. "The eurozone (expected) inflation: An option's eyes view," Journal of International Money and Finance, Elsevier, vol. 86(C), pages 70-92.
  37. Todd E. Clark & Troy Davig, 2008. "An empirical assessment of the relationships among inflation and short- and long-term expectations," Research Working Paper RWP 08-05, Federal Reserve Bank of Kansas City.
  38. Olivier Coibion & Yuriy Gorodnichenko, 2015. "Information Rigidity and the Expectations Formation Process: A Simple Framework and New Facts," American Economic Review, American Economic Association, vol. 105(8), pages 2644-2678, August.
  39. Aparicio, Diego & Bertolotto, Manuel I., 2020. "Forecasting inflation with online prices," International Journal of Forecasting, Elsevier, vol. 36(2), pages 232-247.
  40. Dean Croushore, 2012. "Forecast bias in two dimensions," Working Papers 12-9, Federal Reserve Bank of Philadelphia.
  41. Wright, Jonathan H., 2019. "Some observations on forecasting and policy," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1186-1192.
  42. Richard K. Crump & Stefano Eusepi & Emanuel Moench, 2016. "The term structure of expectations and bond yields," Staff Reports 775, Federal Reserve Bank of New York.
  43. Pablo M. Pincheira & Carlos A. Medel, 2016. "Forecasting with a Random Walk," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 66(6), pages 539-564, December.
  44. Gomes, Orlando & Mendes, Diana A. & Mendes, Vivaldo M., 2008. "Bounded rational expectations and the stability of interest rate policy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(15), pages 3882-3890.
  45. Anmol Bhandari & Jaroslav Borovička & Paul Ho, 2016. "Identifying Ambiguity Shocks in Business Cycle Models Using Survey Data," NBER Working Papers 22225, National Bureau of Economic Research, Inc.
  46. Liu, Dandan & Smith, Julie K., 2014. "Inflation forecasts and core inflation measures: Where is the information on future inflation?," The Quarterly Review of Economics and Finance, Elsevier, vol. 54(1), pages 133-137.
  47. Unn Lindholm & Marcus Mossfeldt & Pär Stockhammar, 2020. "Forecasting inflation in Sweden," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 37(1), pages 39-68, April.
  48. Pablo Pincheira & Carlos A. Medel, 2012. "Forecasting Inflation with a Simple and Accurate Benchmark: a Cross-Country Analysis," Working Papers Central Bank of Chile 677, Central Bank of Chile.
  49. Kim, Insu & Kim, Young Se, 2019. "Inattentive agents and inflation forecast error dynamics: A Bayesian DSGE approach," Journal of Macroeconomics, Elsevier, vol. 62(C).
  50. Garratt, Anthony & Koop, Gary & Mise, Emi & Vahey, Shaun P., 2009. "Real-Time Prediction With U.K. Monetary Aggregates in the Presence of Model Uncertainty," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(4), pages 480-491.
  51. Zhang, Bo & Chan, Joshua C.C. & Cross, Jamie L., 2020. "Stochastic volatility models with ARMA innovations: An application to G7 inflation forecasts," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1318-1328.
  52. Berge, Travis J., 2018. "Understanding survey-based inflation expectations," International Journal of Forecasting, Elsevier, vol. 34(4), pages 788-801.
  53. Julie Bennett & Michael T. Owyang, 2022. "On the Relative Performance of Inflation Forecasts," Review, Federal Reserve Bank of St. Louis, vol. 104(2), pages 131-148.
  54. Wang, Yiyao & Lee, Tae-Hwy, 2014. "Asymmetric loss in the Greenbook and the Survey of Professional Forecasters," International Journal of Forecasting, Elsevier, vol. 30(2), pages 235-245.
  55. James M. Nason & Gregor W. Smith, 2013. "Reverse Kalman filtering U.S. inflation with sticky professional forecasts," Working Papers 13-34, Federal Reserve Bank of Philadelphia.
  56. 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.
  57. Todd E. Clark & Gergely Ganics & Elmar Mertens, 2022. "Constructing Fan Charts from the Ragged Edge of SPF Forecasts," Working Papers 22-36, Federal Reserve Bank of Cleveland.
  58. Geoff Kenny & Thomas Kostka & Federico Masera, 2015. "Can Macroeconomists Forecast Risk? Event-Based Evidence from the Euro-Area SPF," International Journal of Central Banking, International Journal of Central Banking, vol. 11(4), pages 1-46, December.
  59. repec:hal:spmain:info:hdl:2441/3v5mev848s8148gjqcbf4mva5q is not listed on IDEAS
  60. Gilberto Boaretto & Marcelo C. Medeiros, 2023. "Forecasting inflation using disaggregates and machine learning," Papers 2308.11173, arXiv.org.
  61. Florian Peters & Simas Kucinskas, 2018. "Measuring Biases in Expectation Formation," Tinbergen Institute Discussion Papers 18-058/IV, Tinbergen Institute.
  62. Dean Croushore, 2010. "Philadelphia Fed forecasting surveys: their value for research," Business Review, Federal Reserve Bank of Philadelphia, issue Q3, pages 1-11.
  63. Pablo Pincheira & Carlos Medel, 2012. "Forecasting Inflation With a Random Walk," Working Papers Central Bank of Chile 669, Central Bank of Chile.
  64. Liebermann, Joelle, 2012. "Real-time forecasting in a data-rich environment," MPRA Paper 39452, University Library of Munich, Germany.
  65. João Valle e Azevedo & João Tovar Jalles, 2011. "Rational vs. Professional Forecasts," Working Papers w201114, Banco de Portugal, Economics and Research Department.
  66. Pablo Pincheira, 2012. "A Joint Test of Superior Predictive Ability for Chilean Inflation Forecasts," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 15(3), pages 04-39, December.
  67. David Reifschneider & Peter Tulip, 2017. "Gauging the Uncertainty of the Economic Outlook Using Historical Forecasting Errors: The Federal Reserve's Approach," RBA Research Discussion Papers rdp2017-01, Reserve Bank of Australia.
  68. Pablo M. Pincheira & Carlos A. Medel, 2015. "Forecasting Inflation with a Simple and Accurate Benchmark: The Case of the US and a Set of Inflation Targeting Countries," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 65(1), pages 2-29, January.
  69. Víctor López-Pérez, 2017. "Do professional forecasters behave as if they believed in the New Keynesian Phillips Curve for the euro area?," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 44(1), pages 147-174, February.
  70. Kocięcki, Andrzej & Kolasa, Marcin & Rubaszek, Michał, 2012. "A Bayesian method of combining judgmental and model-based density forecasts," Economic Modelling, Elsevier, vol. 29(4), pages 1349-1355.
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