IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/126329.html
   My bibliography  Save this paper

Estimating the New Keynesian Phillips Curve (NKPC) with Fat-tailed Events

Author

Listed:
  • ., Kaustubh
  • Gopalakrishnan, Pawan Gopalakrishnan
  • Ranjan, Abhishek Ranjan

Abstract

This paper provides estimation of the New Keynesian Phillips curve accounting for the unexpected large shocks such as Covid-19. The recent pandemic distorted the estimates of the output gap derived using the regular trend cycle decomposition of GDP (HP Filter, BP Filter, Kalman Filter). We propose a modified unobserved components model (UCM) by introducing an additional Student-t distributed irregular component in the trend cycle decomposition of GDP, which successfully isolates transitory shocks like COVID-19 from trend and cycle estimates. We also construct a model-based measure of inflation expectations that captures adaptive learning from a long inflation history and real-time updating during the pandemic. For India, we find a stable linear NKPC. Our results demonstrate that accounting for fat-tailed events is crucial for obtaining reliable Phillips curve estimates in emerging markets.

Suggested Citation

  • ., Kaustubh & Gopalakrishnan, Pawan Gopalakrishnan & Ranjan, Abhishek Ranjan, 2025. "Estimating the New Keynesian Phillips Curve (NKPC) with Fat-tailed Events," MPRA Paper 126329, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:126329
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/126329/1/MPRA_paper_126322.pdf
    File Function: original version
    Download Restriction: no
    File URL: https://mpra.ub.uni-muenchen.de/126329/2/MPRA_paper_126329.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Harding, Martín & Lindé, Jesper & Trabandt, Mathias, 2023. "Understanding post-COVID inflation dynamics," Journal of Monetary Economics, Elsevier, vol. 140(S), pages 101-118.
    2. Laurence Ball & Sandeep Mazumder, 2019. "A Phillips Curve with Anchored Expectations and Short‐Term Unemployment," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 51(1), pages 111-137, February.
    3. Thomas Hale & Noam Angrist & Rafael Goldszmidt & Beatriz Kira & Anna Petherick & Toby Phillips & Samuel Webster & Emily Cameron-Blake & Laura Hallas & Saptarshi Majumdar & Helen Tatlow, 2021. "A global panel database of pandemic policies (Oxford COVID-19 Government Response Tracker)," Nature Human Behaviour, Nature, vol. 5(4), pages 529-538, April.
    4. Alexander Doser & Ricardo Nunes & Nikhil Rao & Viacheslav Sheremirov, 2023. "Inflation expectations and nonlinearities in the Phillips curve," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 453-471, June.
    5. Michele Lenza & Giorgio E. Primiceri, 2022. "How to estimate a vector autoregression after March 2020," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 688-699, June.
    6. Dietrich, Alexander M. & Kuester, Keith & Müller, Gernot J. & Schoenle, Raphael, 2022. "News and uncertainty about COVID-19: Survey evidence and short-run economic impact," Journal of Monetary Economics, Elsevier, vol. 129(S), pages 35-51.
    7. Shovon Sengupta & Bhanu Pratap & Amit Pawar, 2025. "Non-linear Phillips Curve for India: Evidence from Explainable Machine Learning," Papers 2504.05350, arXiv.org.
    8. Goyal, Ashima & Parab, Prashant, 2021. "What influences aggregate inflation expectations of households in India?," Journal of Asian Economics, Elsevier, vol. 72(C).
    9. 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.
    10. James C. Morley & Charles R. Nelson & Eric Zivot, 2003. "Why Are the Beveridge-Nelson and Unobserved-Components Decompositions of GDP So Different?," The Review of Economics and Statistics, MIT Press, vol. 85(2), pages 235-243, May.
    11. Annalisa Cristini & Piero Ferri, 2021. "Nonlinear models of the Phillips curve," Journal of Evolutionary Economics, Springer, vol. 31(4), pages 1129-1155, September.
    12. 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.
    13. Bhanu Pratap & Amit Pawar & Shovon Sengupta, 2025. "Non-linear Phillips Curve for India: Evidence from Explainable Machine Learning," Post-Print hal-05052296, HAL.
    14. Antolín-Díaz, Juan & Drechsel, Thomas & Petrella, Ivan, 2024. "Advances in nowcasting economic activity: The role of heterogeneous dynamics and fat tails," Journal of Econometrics, Elsevier, vol. 238(2).
    15. Kuttner, Kenneth N, 1994. "Estimating Potential Output as a Latent Variable," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 361-368, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Anis Foresto & Monique Reid & Jeffrey Rakgalakane, 2025. "State dependence of the Phillips curve what does this mean for monetary policy," Working Papers 11080, South African Reserve Bank.
    2. Haschka, Rouven E., 2024. "Examining the New Keynesian Phillips Curve in the U.S.: Why has the relationship between inflation and unemployment weakened?," Research in Economics, Elsevier, vol. 78(4).
    3. Shovon Sengupta & Tanujit Chakraborty & Sunny Kumar Singh, 2024. "Forecasting CPI inflation under economic policy and geopolitical uncertainties," Post-Print hal-05056934, HAL.
    4. Shovon Sengupta & Bhanu Pratap & Amit Pawar, 2025. "Non-linear Phillips Curve for India: Evidence from Explainable Machine Learning," Papers 2504.05350, arXiv.org.
    5. Crump, Richard K. & Eusepi, Stefano & Giannoni, Marc & Şahin, Ayşegül, 2024. "The unemployment–inflation trade-off revisited: The Phillips curve in COVID times," Journal of Monetary Economics, Elsevier, vol. 145(S).
    6. Luís Aguiar-Conraria & Manuel M. F. Martins & Maria Joana Soares, 2019. "The Phillips Curve at 60: time for time and frequency," CEF.UP Working Papers 1902, Universidade do Porto, Faculdade de Economia do Porto.
    7. Ferri, Piero & Cristini, Annalisa & Tramontana, Fabio, 2023. "Meta-models of the Phillips curve and income distribution," Journal of Economic Behavior & Organization, Elsevier, vol. 213(C), pages 215-232.
    8. Aguiar-Conraria, Luís & Martins, Manuel M.F. & Soares, Maria Joana, 2023. "The Phillips curve at 65: Time for time and frequency," Journal of Economic Dynamics and Control, Elsevier, vol. 151(C).
    9. repec:zbw:bofrdp:2019_012 is not listed on IDEAS
    10. Luís Aguiar-Conraria & Manuel M. F. Martins & Maria Joana Soares, 2019. "The Phillips Curve at 60: time for time and frequency," CEF.UP Working Papers 1902, Universidade do Porto, Faculdade de Economia do Porto.
    11. Kamber, Güneş & Morley, James & Wong, Benjamin, 2025. "Trend-cycle decomposition in the presence of large shocks," Journal of Economic Dynamics and Control, Elsevier, vol. 173(C).
    12. Guérin, Pierre & Maurin, Laurent & Mohr, Matthias, 2015. "Trend-Cycle Decomposition Of Output And Euro Area Inflation Forecasts: A Real-Time Approach Based On Model Combination," Macroeconomic Dynamics, Cambridge University Press, vol. 19(2), pages 363-393, March.
    13. Jonathon Hazell, 2024. "Comment on "The Dominant Role of Expectations and Broad-Based Supply Shocks in Driving Inflation"," NBER Chapters, in: NBER Macroeconomics Annual 2024, volume 39, pages 277-290, National Bureau of Economic Research, Inc.
    14. Marek Jarociński & Michele Lenza, 2018. "An Inflation‐Predicting Measure of the Output Gap in the Euro Area," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(6), pages 1189-1224, September.
    15. Marian Vavra, 2016. "Testing the Validity of Assumptions of UC-ARIMA Models for Trend-Cycle Decompositions," Working and Discussion Papers WP 4/2016, Research Department, National Bank of Slovakia.
    16. Michael Weber & Yuriy Gorodnichenko & Olivier Coibion, 2023. "The Expected, Perceived, and Realized Inflation of US Households Before and During the COVID19 Pandemic," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 71(1), pages 326-368, March.
    17. Blonigen, Bruce A. & Piger, Jeremy & Sly, Nicholas, 2014. "Comovement in GDP trends and cycles among trading partners," Journal of International Economics, Elsevier, vol. 94(2), pages 239-247.
    18. Tino Berger, 2011. "Estimating Europe’s natural rates," Empirical Economics, Springer, vol. 40(2), pages 521-536, April.
    19. Castillo, Luis & Florián, David, 2019. "Measuring the output gap, potential output growth and natural interest rate from a semi-structural dynamic model for Peru," Working Papers 2019-012, Banco Central de Reserva del Perú.
    20. Morley, James & Rodríguez-Palenzuela, Diego & Sun, Yiqiao & Wong, Benjamin, 2023. "Estimating the euro area output gap using multivariate information and addressing the COVID-19 pandemic," European Economic Review, Elsevier, vol. 153(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:126329. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.