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Forecasting inflation gap persistence: Do financial sector professionals differ from nonfinancial sector ones?

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  • Huw Dixon
  • Joshy Easaw
  • Saeed Heravi

Abstract

The purpose of the present paper is to investigate forecasted inflation gap persistence using professionals' survey‐based data, differentiating between financial and nonfinancial sectors professionals. We derive the forecasted inflation gap persistence, and using a state‐dependent model, we estimate the nonlinear persistence coefficient of the inflation gap. We distinguish between the pre‐Great Moderation, Great Moderation, and Great Recession periods. Our main results indicate that although the estimates of persistence for gross domestic product inflation largely confirm the results obtained using a linear model, for consumer price index inflation, we find that there is strong evidence for state dependence and time variation. By and large, the results are consistent with the price stability policy pursued in the Great Moderation period and perceived disinflationary pressures during the Great Recession period.

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  • Huw Dixon & Joshy Easaw & Saeed Heravi, 2020. "Forecasting inflation gap persistence: Do financial sector professionals differ from nonfinancial sector ones?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 25(3), pages 461-474, July.
    • Handle: RePEc:wly:ijfiec:v:25:y:2020:i:3:p:461-474
    DOI: 10.1002/ijfe.1762
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    1. Monica Jain, 2019. "Perceived Inflation Persistence," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(1), pages 110-120, January.
    2. 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.
    3. N. Gregory Mankiw & Ricardo Reis & Justin Wolfers, 2004. "Disagreement about Inflation Expectations," NBER Chapters, in: NBER Macroeconomics Annual 2003, Volume 18, pages 209-270, National Bureau of Economic Research, Inc.
    4. Andrade, Philippe & Le Bihan, Hervé, 2013. "Inattentive professional forecasters," Journal of Monetary Economics, Elsevier, vol. 60(8), pages 967-982.
    5. N. Gregory Mankiw & Ricardo Reis, 2002. "Sticky Information versus Sticky Prices: A Proposal to Replace the New Keynesian Phillips Curve," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 117(4), pages 1295-1328.
    6. Andrew T. Levin & Jeremy M. Piger, 2003. "Is inflation persistence intrinsic in industrial economies?," Working Papers 2002-023, Federal Reserve Bank of St. Louis.
    7. 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.
    8. Jonathan H. Wright, 2013. "Evaluating Real‐Time Var Forecasts With An Informative Democratic Prior," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(5), pages 762-776, August.
    9. Jeffrey C. Fuhrer, 2015. "Expectations as a source of macroeconomic persistence: an exploration of firms' and households' expectation formation," Working Papers 15-5, Federal Reserve Bank of Boston.
    10. James H. Stock & Mark W. Watson, 2007. "Why Has U.S. Inflation Become Harder to Forecast?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, February.
    11. Fuhrer, Jeff, 2017. "Expectations as a source of macroeconomic persistence: Evidence from survey expectations in a dynamic macro model," Journal of Monetary Economics, Elsevier, vol. 86(C), pages 22-35.
    12. James H. Stock & Mark W. Watson, 2010. "Modeling inflation after the crisis," Proceedings - Economic Policy Symposium - Jackson Hole, Federal Reserve Bank of Kansas City, pages 173-220.
    13. 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.
    14. Sharon Kozicki & P. A. Tinsley, 2012. "Effective Use of Survey Information in Estimating the Evolution of Expected Inflation," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(1), pages 145-169, February.
    15. Easaw, Joshy & Golinelli, Roberto & Malgarini, Marco, 2013. "What determines households inflation expectations? Theory and evidence from a household survey," European Economic Review, Elsevier, vol. 61(C), pages 1-13.
    16. Elmar Mertens, 2016. "Measuring the Level and Uncertainty of Trend Inflation," The Review of Economics and Statistics, MIT Press, vol. 98(5), pages 950-967, December.
    17. Timothy Cogley & Giorgio E. Primiceri & Thomas J. Sargent, 2010. "Inflation-Gap Persistence in the US," American Economic Journal: Macroeconomics, American Economic Association, vol. 2(1), pages 43-69, January.
    18. Kajal Lahiri & Xuguang Sheng, 2010. "Measuring forecast uncertainty by disagreement: The missing link," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 514-538.
    19. EASAW, Joshy & MOSSAY, Pascal, 2015. "Households forming macroeconomic expectations: inattentive behavior with social learning," LIDAM Reprints CORE 2683, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    20. Berger, Tino & Everaert, Gerdie & Vierke, Hauke, 2016. "Testing for time variation in an unobserved components model for the U.S. economy," Journal of Economic Dynamics and Control, Elsevier, vol. 69(C), pages 179-208.
    21. Sims, Christopher A., 2003. "Implications of rational inattention," Journal of Monetary Economics, Elsevier, vol. 50(3), pages 665-690, April.
    22. Nordhaus, William D, 1987. "Forecasting Efficiency: Concepts and Applications," The Review of Economics and Statistics, MIT Press, vol. 69(4), pages 667-674, November.
    23. Stock, J.H. & Watson, M.W., 2016. "Dynamic Factor Models, Factor-Augmented Vector Autoregressions, and Structural Vector Autoregressions in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 415-525, Elsevier.
    24. Matějka, Filip & Mackowiak, Bartosz & Wiederholt, Mirko, 2018. "Survey: Rational Inattention, a Disciplined Behavioral Model," CEPR Discussion Papers 13243, C.E.P.R. Discussion Papers.
    25. Kozicki, Sharon & Tinsley, P. A., 2001. "Shifting endpoints in the term structure of interest rates," Journal of Monetary Economics, Elsevier, vol. 47(3), pages 613-652, June.
    26. Hedibert F. Lopes & Ruey S. Tsay, 2011. "Particle filters and Bayesian inference in financial econometrics," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 30(1), pages 168-209, January.
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