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Measuring inflation persistence under time-varying inflation target and stochastic volatility with jumps

Author

Listed:
  • Cássio R. A. Alves

    (University of São Paulo)

  • Márcio P. Laurini

    (University of São Paulo)

Abstract

We analyze whether the presence of a time-varying inflation target and stochastic volatility affect inflation persistence. We estimated different autoregressive specifications for inflation with and without time-varying parameters. The results show that the inflation persistence diminishes when we consider time-varying inflation target and stochastic volatility with jumps. We conclude that neglecting the time variation in inflation target and inflation volatility results in an upward biased estimation of persistence.

Suggested Citation

  • Cássio R. A. Alves & Márcio P. Laurini, 2022. "Measuring inflation persistence under time-varying inflation target and stochastic volatility with jumps," Economics Bulletin, AccessEcon, vol. 42(2), pages 342-349.
    • Handle: RePEc:ebl:ecbull:eb-21-00688
    as

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    References listed on IDEAS

    as
    1. 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.
    2. Chaim, Pedro & Laurini, Márcio P., 2018. "Volatility and return jumps in bitcoin," Economics Letters, Elsevier, vol. 173(C), pages 158-163.
    3. Monica Jain, 2019. "Perceived Inflation Persistence," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(1), pages 110-120, January.
    4. Maarten Dossche & Gerdie Everaert, 2005. "Measuring Inflation Persistence: A Structural Time Series Approach," Computing in Economics and Finance 2005 459, Society for Computational Economics.
    5. 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.
    6. Kozicki, Sharon & Tinsley, P.A., 2005. "Permanent and transitory policy shocks in an empirical macro model with asymmetric information," Journal of Economic Dynamics and Control, Elsevier, vol. 29(11), pages 1985-2015, November.
    7. Perron, P, 1993. "Erratum [The Great Crash, the Oil Price Shock and the Unit Root Hypothesis]," Econometrica, Econometric Society, vol. 61(1), pages 248-249, January.
    8. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
    9. Antonakakis, Nikolaos & Cunado, Juncal & Gil-Alana, Luis A. & Gupta, Rangan, 2016. "Is inflation persistence different in reality?," Economics Letters, Elsevier, vol. 148(C), pages 55-58.
    10. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November.
    11. 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.
    12. 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.
    13. Luengo-Prado, María José & Rao, Nikhil & Sheremirov, Viacheslav, 2018. "Sectoral inflation and the Phillips curve: What has changed since the Great Recession?," Economics Letters, Elsevier, vol. 172(C), pages 63-68.
    14. Zhongjun Qu & Pierre Perron, 2013. "A stochastic volatility model with random level shifts and its applications to S&P 500 and NASDAQ return indices," Econometrics Journal, Royal Economic Society, vol. 16(3), pages 309-339, October.
    15. Spencer D. Krane, 2011. "Professional Forecasters' View of Permanent and Transitory Shocks to GDP," American Economic Journal: Macroeconomics, American Economic Association, vol. 3(1), pages 184-211, January.
    16. Márcio Laurini, 2013. "A Dynamic Econometric Model for Inflationary Inertia In Brazil," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 2(2), pages 1-6.
    17. 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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    More about this item

    Keywords

    Inflation persistence; Time-varying parameters; Stochastic volatility;
    All these keywords.

    JEL classification:

    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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