IDEAS home Printed from https://ideas.repec.org/p/mtu/wpaper/26_02.html

On quantitative and graphical measures of the severity of New Zealand’s recessions and strength of its expansions

Author

Abstract

We develop three measures for the shape of business cycle phases, reflecting excess gains and losses relative to constant quarterly growth across the phase. These measures can be seen as representing better or worse economic outcomes during recession and expansion phases relative to constant growth rate paths and, as a consequence, provide summary evaluation measures for such economic outcomes. Using a phase’s constant quarterly growth rate as the benchmark, our methodology builds on Harding and Pagan (2016) by developing quantitative measures that have useful economic interpretations and which are amenable to informative graphical display and analysis. Empirical outcomes are provided for New Zealand’s recession and expansion phases.

Suggested Citation

  • Viv B. Hall & John McDermott & Peter Thomson, 2026. "On quantitative and graphical measures of the severity of New Zealand’s recessions and strength of its expansions," Motu Working Papers 26_02, Motu Economic and Public Policy Research.
  • Handle: RePEc:mtu:wpaper:26_02
    as

    Download full text from publisher

    File URL: https://motu-www.motu.org.nz/wpapers/26_02.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Don Harding & Adrian Pagan, 2016. "The Econometric Analysis of Recurrent Events in Macroeconomics and Finance," Economics Books, Princeton University Press, edition 1, number 10744, December.
    2. Viv B. Hall & C. John McDermott, 2011. "A quarterly post-Second World War real GDP series for New Zealand," New Zealand Economic Papers, Taylor & Francis Journals, vol. 45(3), pages 273-298, March.
    3. Viv B. Hall & C. John McDermott, 2016. "Recessions and recoveries in New Zealand's post-Second World War business cycles," New Zealand Economic Papers, Taylor & Francis Journals, vol. 50(3), pages 261-280, September.
    4. Harding, Don & Pagan, Adrian, 2002. "Dissecting the cycle: a methodological investigation," Journal of Monetary Economics, Elsevier, vol. 49(2), pages 365-381, March.
    5. Gerhard Bry & Charlotte Boschan, 1971. "Standard Business Cycle Analysis of Economic Time Series," NBER Chapters, in: Cyclical Analysis of Time Series: Selected Procedures and Computer Programs, pages 64-150, National Bureau of Economic Research, Inc.
    6. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178.
    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. 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.
    2. 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.
    3. Viv B. Hall & Peter Thomson, 2021. "Does Hamilton’s OLS Regression Provide a “better alternative” to the Hodrick-Prescott Filter? A New Zealand Business Cycle Perspective," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), vol. 17(2), pages 151-183, November.
    4. 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.
    5. 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.
    6. Guido Bulligan & Lorenzo Burlon & Davide Delle Monache & Andrea Silvestrini, 2019. "Real and financial cycles: estimates using unobserved component models for the Italian economy," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(3), pages 541-569, September.
    7. Arias, Maria A. & Gascon, Charles S. & Rapach, David E., 2016. "Metro business cycles," Journal of Urban Economics, Elsevier, vol. 94(C), pages 90-108.
    8. Jalali Naini, Ahmad Reza & Naderian, Mohammad Amin, 2017. "Oil Price Cycles, Fiscal Dominance and Counter-cyclical Monetary Policy in Iran," MPRA Paper 84480, University Library of Munich, Germany.
    9. Jasper de Winter & Siem Jan Koopman & Irma Hindrayanto, 2022. "Joint Decomposition of Business and Financial Cycles: Evidence from Eight Advanced Economies," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(1), pages 57-79, February.
    10. Michael Ryan, 2020. "An Anchor in Stormy Seas: Does Reforming Economic Institutions Reduce Uncertainty? Evidence from New Zealand," Working Papers in Economics 20/11, University of Waikato.
    11. 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.
    12. Matthieu Lemoine & Gian Luigi Mazzi & Paola Monperrus-Veroni & Frédéric Reynes, 2010. "A new production function estimate of the euro area output gap This paper is based on a report for Eurostat: 'Real time estimation of potential output, output gap, NAIRU and Phillips curve for Euro-zone', part of the Advanced statistical and economet," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(1-2), pages 29-53.
    13. Jorge David Quintero Otero & Alcides de Jesús Padilla Sierra, 2024. "Impacto de la sincronización sub-nacional sobre el comportamiento de los ciclos nacionales en economías emergentes con inflación objetivo," Documentos Departamento de Economía 54, Universidad del Norte.
    14. M. Ayhan Kose & Naotaka Sugawara & Marco E. Terrones, 2020. "Global Recessions," Working Papers 162, Peruvian Economic Association.
    15. Hall, Viv B. & McDermott, C. John, 2015. "Recessions and Recoveries in New Zealand’s Post-Second World War Business Cycles," Working Paper Series 4688, Victoria University of Wellington, School of Economics and Finance.
    16. Viv B. Hall & C. John McDermott, 2016. "Recessions and recoveries in New Zealand's post-Second World War business cycles," New Zealand Economic Papers, Taylor & Francis Journals, vol. 50(3), pages 261-280, September.
    17. 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.
    18. 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.
    19. Stijn Claessens & M Ayhan Kose, 2018. "Frontiers of macrofinancial linkages," BIS Papers, Bank for International Settlements, number 95.
    20. Giordani, Paolo & Kohn, Robert & van Dijk, Dick, 2007. "A unified approach to nonlinearity, structural change, and outliers," Journal of Econometrics, Elsevier, vol. 137(1), pages 112-133, March.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

    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:mtu:wpaper:26_02. 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: Emma Williams (email available below). General contact details of provider: https://edirc.repec.org/data/motuenz.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.