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The Econometric Analysis of Recurrent Events in Macroeconomics and Finance

Author

Listed:
  • Don Harding

    (Victoria University)

  • Adrian Pagan

    (University of Melbourne)

Abstract

The global financial crisis highlighted the impact on macroeconomic outcomes of recurrent events like business and financial cycles, highs and lows in volatility, and crashes and recessions. At the most basic level, such recurrent events can be summarized using binary indicators showing if the event will occur or not. These indicators are constructed either directly from data or indirectly through models. Because they are constructed, they have different properties than those arising in microeconometrics, and how one is to use them depends a lot on the method of construction. This book presents the econometric methods necessary for the successful modeling of recurrent events, providing valuable insights for policymakers, empirical researchers, and theorists. It explains why it is inherently difficult to forecast the onset of a recession in a way that provides useful guidance for active stabilization policy, with the consequence that policymakers should place more emphasis on making the economy robust to recessions. The book offers a range of econometric tools and techniques that researchers can use to measure recurrent events, summarize their properties, and evaluate how effectively economic and statistical models capture them. These methods also offer insights for developing models that are consistent with observed financial and real cycles. This book is an essential resource for students, academics, and researchers at central banks and institutions such as the International Monetary Fund.

Suggested Citation

  • Don Harding & Adrian Pagan, 2016. "The Econometric Analysis of Recurrent Events in Macroeconomics and Finance," Economics Books, Princeton University Press, edition 1, number 10744.
  • Handle: RePEc:pup:pbooks:10744
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    Citations

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    Cited by:

    1. Marco Gallegati, 2019. "A system for dating long wave phases in economic development," Journal of Evolutionary Economics, Springer, vol. 29(3), pages 803-822, July.
    2. Kajal Lahiri & Cheng Yang, 2023. "A tale of two recession-derivative indicators," Empirical Economics, Springer, vol. 65(2), pages 925-947, August.
    3. Hall, Viv B & Thomson, Peter, 2022. "A boosted HP filter for business cycle analysis: evidence from New Zealand’s small open economy," Working Paper Series 9473, Victoria University of Wellington, School of Economics and Finance.
    4. M. Ayhan Kose & Naotaka Sugawara & Marco E. Terrones, 2020. "Global Recessions," Working Papers 162, Peruvian Economic Association.
    5. Ye Lu & Adrian Pagan, 2023. "To Boost or Not to Boost? That is the Question," CAMA Working Papers 2023-12, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    6. Barros, Geraldo Sant’Ana de Camargo & Carrara, Aniela Fagundes & Castro, Nicole Rennó & Silva, Adriana Ferreira, 2022. "Agriculture and inflation: Expected and unexpected shocks," The Quarterly Review of Economics and Finance, Elsevier, vol. 83(C), pages 178-188.
    7. Brandyn Bok & Daniele Caratelli & Domenico Giannone & Argia M. Sbordone & Andrea Tambalotti, 2018. "Macroeconomic Nowcasting and Forecasting with Big Data," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 615-643, August.
    8. Maximo Camacho & María Dolores Gadea & Ana Gómez-Loscos, 2021. "An Automatic Algorithm to Date the Reference Cycle of the Spanish Economy," Mathematics, MDPI, vol. 9(18), pages 1-17, September.
    9. Stijn Claessens & M Ayhan Kose, 2018. "Frontiers of macrofinancial linkages," BIS Papers, Bank for International Settlements, number 95.
    10. Palenzuela, Diego Rodriguez & Saiz, Lorena & Stoevsky, Grigor & Tóth, Máté & Warmedinger, Thomas & Grigoraș, Veaceslav, 2024. "The euro area business cycle and its drivers," Occasional Paper Series 354, European Central Bank.
    11. Stijn Claessens & M. Ayhan Kose, 2017. "Asset prices and macroeconomic outcomes: A survey," CAMA Working Papers 2017-76, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    12. Dutra, Tiago Mota & Dias, José Carlos & Teixeira, João C.A., 2022. "Measuring financial cycles: Empirical evidence for Germany, United Kingdom and United States of America," International Review of Economics & Finance, Elsevier, vol. 79(C), pages 599-630.
    13. Sean Langcake & Tim Robinson, 2018. "Forecasting the Australian economy with DSGE and BVAR models," Applied Economics, Taylor & Francis Journals, vol. 50(3), pages 251-267, January.
    14. Yunjong Eo & Chang-Jin Kim, 2016. "Markov-Switching Models with Evolving Regime-Specific Parameters: Are Postwar Booms or Recessions All Alike?," The Review of Economics and Statistics, MIT Press, vol. 98(5), pages 940-949, December.
    15. Mariano Kulish & Adrian Pagan, 2021. "Turning point and oscillatory cycles: Concepts, measurement, and use," Journal of Economic Surveys, Wiley Blackwell, vol. 35(4), pages 977-1006, September.
    16. Tara M. Sinclair, 2019. "Continuities and Discontinuities in Economic Forecasting," Working Papers 2019-003, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    17. Maximo Camacho & María Dolores Gadea & Ana Gómez Loscos, 2022. "A New Approach to Dating the Reference Cycle," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(1), pages 66-81, January.
    18. Viv B. Hall & Peter Thomson, 2022. "A boosted HP filter for business cycle analysis:evidence from New Zealand's small open economy," CAMA Working Papers 2022-45, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    19. Albers, Thilo Nils Hendrik, 2018. "The prelude and global impact of the Great Depression: Evidence from a new macroeconomic dataset," Explorations in Economic History, Elsevier, vol. 70(C), pages 150-163.
    20. Greg Farrell & Esti Kemp, 2020. "Measuring the Financial Cycle in South Africa," South African Journal of Economics, Economic Society of South Africa, vol. 88(2), pages 123-144, June.
    21. C. Colther & J. L. Rojo & R. Hornero, 2022. "A Wavelet Method for Detecting Turning Points in the Business Cycle," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 18(2), pages 171-187, July.
    22. Gunnar Bårdsen & Stan Hurn & Kenneth Lindsay, 2019. "Modelling and forecasting wind drought," Working Paper Series 18219, Department of Economics, Norwegian University of Science and Technology.
    23. Any Flore Djoumessi Djoukouo, 2023. "Recessions and recoveries in Central African countries: Lessons from the past," Journal of International Development, John Wiley & Sons, Ltd., vol. 35(6), pages 1121-1142, August.

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