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Inflation and Real Activity over the Business Cycle

Author

Listed:
  • Francesco Bianchi
  • Giovanni Nicolò
  • Dongho Song
Abstract
We study the relation between inflation and real activity over the business cycle. We employ a Trend-Cycle VAR model to control for low-frequency movements in inflation, unemployment, and growth that are pervasive in the post-WWII period. We show that cyclical fluctuations of inflation are related to cyclical movements in real activity and unemployment, in line with what is implied by the New Keynesian framework. We then discuss the reasons for which our results relying on a Trend-Cycle VAR differ from the findings of previous studies based on VAR analysis. We explain empirically and theoretically how to reconcile these differences.

Suggested Citation

  • Francesco Bianchi & Giovanni Nicolò & Dongho Song, 2023. "Inflation and Real Activity over the Business Cycle," NBER Working Papers 31075, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:31075
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    References listed on IDEAS

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    1. Farmer, Roger E.A. & Nicolò, Giovanni, 2018. "Keynesian economics without the Phillips curve," Journal of Economic Dynamics and Control, Elsevier, vol. 89(C), pages 137-150.
    2. James H. Stock & Mark W. Watson, 2008. "Phillips curve inflation forecasts," Conference Series ; [Proceedings], Federal Reserve Bank of Boston.
    3. Del Negro, Marco & Giannone, Domenico & Giannoni, Marc P. & Tambalotti, Andrea, 2019. "Global trends in interest rates," Journal of International Economics, Elsevier, vol. 118(C), pages 248-262.
    4. Jesús Fernández-Villaverde & Juan F. Rubio-Ramírez & Thomas J. Sargent & Mark W. Watson, 2007. "ABCs (and Ds) of Understanding VARs," American Economic Review, American Economic Association, vol. 97(3), pages 1021-1026, June.
    5. George‐Marios Angeletos & Fabrice Collard & Harris Dellas, 2018. "Quantifying Confidence," Econometrica, Econometric Society, vol. 86(5), pages 1689-1726, September.
    6. Holston, Kathryn & Laubach, Thomas & Williams, John C., 2017. "Measuring the natural rate of interest: International trends and determinants," Journal of International Economics, Elsevier, vol. 108(S1), pages 59-75.
    7. Paul Beaudry & Dana Galizia & Franck Portier, 2020. "Putting the Cycle Back into Business Cycle Analysis," American Economic Review, American Economic Association, vol. 110(1), pages 1-47, January.
    8. Francesco Bianchi & Cosmin Ilut, 2017. "Monetary/Fiscal Policy Mix and Agent's Beliefs," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 26, pages 113-139, October.
    9. Giannone, Domenico & Reichlin, Lucrezia & Sala, Luca, 2006. "VARs, common factors and the empirical validation of equilibrium business cycle models," Journal of Econometrics, Elsevier, vol. 132(1), pages 257-279, May.
    10. Guido Ascari & Luca Fosso, 2021. "The Inflation Rate Disconnect Puzzle: On the International Component of Trend Inflation and the Flattening of the Phillips Curve," Working Paper 2021/17, Norges Bank.
    11. Burridge, Peter & Wallis, Kenneth F., 1983. "Signal Extraction In Nonstationary Series," Economic Research Papers 269177, University of Warwick - Department of Economics.
    12. Francesco Bianchi, 2013. "Regime Switches, Agents' Beliefs, and Post-World War II U.S. Macroeconomic Dynamics," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 80(2), pages 463-490.
    13. Alejandro Justiniano & Giorgio E. Primiceri & Andrea Tambalotti, 2013. "Is There a Trade-Off between Inflation and Output Stabilization?," American Economic Journal: Macroeconomics, American Economic Association, vol. 5(2), pages 1-31, April.
    14. Lawrence J. Christiano & Terry J. Fitzgerald, 2003. "The Band Pass Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(2), pages 435-465, May.
    15. Thomas Laubach & John C. Williams, 2003. "Measuring the Natural Rate of Interest," The Review of Economics and Statistics, MIT Press, vol. 85(4), pages 1063-1070, November.
    16. Stock, James H. & Watson, Mark, 2011. "Dynamic Factor Models," Scholarly Articles 28469541, Harvard University Department of Economics.
    17. Christopher Gust & Edward Herbst & David López-Salido, 2022. "Short-Term Planning, Monetary Policy, and Macroeconomic Persistence," American Economic Journal: Macroeconomics, American Economic Association, vol. 14(4), pages 174-209, October.
    18. Bańbura, Marta & Giannone, Domenico & Lenza, Michele, 2015. "Conditional forecasts and scenario analysis with vector autoregressions for large cross-sections," International Journal of Forecasting, Elsevier, vol. 31(3), pages 739-756.
    19. Domenico Giannone & Michele Lenza & Giorgio E. Primiceri, 2015. "Prior Selection for Vector Autoregressions," The Review of Economics and Statistics, MIT Press, vol. 97(2), pages 436-451, May.
    20. Roger E.A. Farmer & Giovanni Nicolò, 2021. "Some International Evidence for Keynesian Economics Without the Phillips Curve," Manchester School, University of Manchester, vol. 89(S1), pages 1-22, September.
    21. 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.
    22. Susanto Basu & Giacomo Candian & Ryan Chahrour & Rosen Valchev, 2021. "Risky Business Cycles," Boston College Working Papers in Economics 1029, Boston College Department of Economics, revised 17 Sep 2024.
    23. 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.
    24. 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.
    25. Paul Beaudry & Franck Portier, 2014. "Understanding Noninflationary Demand-Driven Business Cycles," NBER Macroeconomics Annual, University of Chicago Press, vol. 28(1), pages 69-130.
    26. Watson, Mark W., 1986. "Univariate detrending methods with stochastic trends," Journal of Monetary Economics, Elsevier, vol. 18(1), pages 49-75, July.
    27. Jonathon Hazell & Juan Herreño & Emi Nakamura & Jón Steinsson, 2022. "The Slope of the Phillips Curve: Evidence from U.S. States," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 137(3), pages 1299-1344.
    28. Kurt F. Lewis & Francisco Vazquez‐Grande, 2019. "Measuring the natural rate of interest: A note on transitory shocks," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(3), pages 425-436, April.
    29. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178.
    30. Masao Fukui & Emi Nakamura & Jón Steinsson, 2023. "Women, Wealth Effects, and Slow Recoveries," American Economic Journal: Macroeconomics, American Economic Association, vol. 15(1), pages 269-313, January.
    31. 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.
    32. Christopher A. Sims & Tao Zha, 2006. "Were There Regime Switches in U.S. Monetary Policy?," American Economic Review, American Economic Association, vol. 96(1), pages 54-81, March.
    33. Giannone, Domenico & Lenza, Michele & Momferatou, Daphne & Onorante, Luca, 2014. "Short-term inflation projections: A Bayesian vector autoregressive approach," International Journal of Forecasting, Elsevier, vol. 30(3), pages 635-644.
    34. James H. Stock & Mark W. Watson, 2007. "Erratum to "Why Has U.S. Inflation Become Harder to Forecast?"," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(7), pages 1849-1849, October.
    35. James H. Stock & Mark W. Watson, 2007. "Erratum to “Why Has U.S. Inflation Become Harder to Forecast?”," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(7), pages 1849-1849, October.
    36. Kadiyala, K Rao & Karlsson, Sune, 1997. "Numerical Methods for Estimation and Inference in Bayesian VAR-Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(2), pages 99-132, March-Apr.
    37. Lars Peter Hansen & Thomas J. Sargent, 2013. "Recursive Models of Dynamic Linear Economies," Economics Books, Princeton University Press, edition 1, number 10141.
    38. Mattias Villani, 2009. "Steady-state priors for vector autoregressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(4), pages 630-650.
    39. 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.
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    Cited by:

    1. Ascari, Guido & Fosso, Luca, 2024. "The international dimension of trend inflation," Journal of International Economics, Elsevier, vol. 148(C).
    2. Ángelo Gutiérrez-Daza, 2024. "Business Cycles when Consumers Learn by Shopping," Working Papers 2024-12, Banco de México.
    3. Leonardo Ciambezi & Mattia Guerini & Mauro Napoletano & Andrea Roventini, 2023. "Accounting for the Multiple Sources of Inflation: an Agent-Based Model Investigation," GREDEG Working Papers 2023-14, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France, revised Jun 2024.

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    More about this item

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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