IDEAS home Printed from https://ideas.repec.org/a/bla/ausecp/v63y2024i1p36-58.html
   My bibliography  Save this article

How Australia's economy gained momentum because of Covid‐19

Author

Listed:
  • Pierre Rostan
  • Alexandra Rostan

Abstract

The objective of the paper is to assess the resilience of the economy of Australia following the Covid‐19 pandemic that hit the global economy in Q4 2019, in years 2020, 2021 and 2022. Quarterly growth rates (annualised) of the Real GDP of Australia and Canada are forecasted between Q2 2022 and Q4 2050. Two sets of forecasts are generated: forecasts using historical data including the pandemic (from Q1 1961 to Q1 2022) and excluding the pandemic (from Q1 1961 to Q3 2019). The computation of the difference of their averages is an indicator of the resilience of the economies during the pandemic, the greater the difference the greater the resilience. Used as a benchmark, Canada's economy shows a slightly lower resilience to the Covid‐19 pandemic (+0.37%) than Australia's economy (+0.39%) based on Q2 2022–2050 forecasts. However, driven by stronger growth than Canada, the average estimate of the Q2 2022–Q4 2050 quarterly (annualised) growth rate forecasts of Australia is expected to be +2.09% with the Q1 1961–Q1 2022 historical data while it should be +1.61% for Canada. Supported by higher growth, Australia's Real GDP is expected to overtake Canada's in Q1 2040.

Suggested Citation

  • Pierre Rostan & Alexandra Rostan, 2024. "How Australia's economy gained momentum because of Covid‐19," Australian Economic Papers, Wiley Blackwell, vol. 63(1), pages 36-58, March.
    • Handle: RePEc:bla:ausecp:v:63:y:2024:i:1:p:36-58
    DOI: 10.1111/1467-8454.12308
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/1467-8454.12308
    Download Restriction: no
    File URL: https://libkey.io/10.1111/1467-8454.12308?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Marco Gallegati & Mauro Gallegati & James B. Ramsey & Willi Semmler, 2017. "Long waves in prices: new evidence from wavelet analysis," Cliometrica, Springer;Cliometric Society (Association Francaise de Cliométrie), vol. 11(1), pages 127-151, January.
    2. Olaolu Richard Olayeni, 2016. "Causality in Continuous Wavelet Transform Without Spectral Matrix Factorization: Theory and Application," Computational Economics, Springer;Society for Computational Economics, vol. 47(3), pages 321-340, March.
    3. Pierre Rostan & Alexandra Rostan, 2018. "Will Saudi Arabia get older? Will its pension system be sustainable? Spectral answers," PSU Research Review, Emerald Group Publishing Limited, vol. 2(3), pages 189-205, April.
    4. Theo Berger, 2016. "Forecasting Based on Decomposed Financial Return Series: A Wavelet Analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 35(5), pages 419-433, August.
    5. Pierre Rostan & Rachid Belhachemi & François‐Eric Racicot, 2017. "Yield Curve Forecasting with the Burg Model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 36(1), pages 91-99, January.
    6. Harvey, A C & Jaeger, A, 1993. "Detrending, Stylized Facts and the Business Cycle," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(3), pages 231-247, July-Sept.
    7. Pierre Rostan & Alexandra Rostan, 2018. "The versatility of spectrum analysis for forecasting financial time series," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(3), pages 327-339, April.
    8. Muggenthaler, Philip & Schroth, Joachim & Sun, Yiqiao, 2021. "The heterogeneous economic impact of the pandemic across euro area countries," Economic Bulletin Boxes, European Central Bank, vol. 5.
    9. Kriechbaumer, Thomas & Angus, Andrew & Parsons, David & Rivas Casado, Monica, 2014. "An improved wavelet–ARIMA approach for forecasting metal prices," Resources Policy, Elsevier, vol. 39(C), pages 32-41.
    10. Tan, Zhongfu & Zhang, Jinliang & Wang, Jianhui & Xu, Jun, 2010. "Day-ahead electricity price forecasting using wavelet transform combined with ARIMA and GARCH models," Applied Energy, Elsevier, vol. 87(11), pages 3606-3610, November.
    11. Pierre Rostan & Alexandra Rostan, 2019. "When will European Muslim population be majority and in which country?," PSU Research Review, Emerald Group Publishing Limited, vol. 3(2), pages 123-144, August.
    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. Pierre Rostan & Alexandra Rostan, 2023. "The benefit of the Covid‐19 pandemic on global temperature projections," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 2079-2098, December.
    2. Pierre Rostan & Alexandra Rostan & John Wall, 2024. "Measuring the Resilience to the Covid-19 Pandemic of Eurozone Economies with Their 2050 Forecasts," Computational Economics, Springer;Society for Computational Economics, vol. 63(3), pages 1137-1157, March.
    3. Kim C. Raath & Katherine B. Ensor, 2023. "Wavelet-L2E Stochastic Volatility Models: an Application to the Water-Energy Nexus," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 150-176, May.
    4. Faria, Gonçalo & Verona, Fabio, 2020. "The yield curve and the stock market: Mind the long run," Journal of Financial Markets, Elsevier, vol. 50(C).
    5. Joanna Bruzda, 2020. "The wavelet scaling approach to forecasting: Verification on a large set of Noisy data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 353-367, April.
    6. Lars-H. R. Siemers, 2024. "On the Hamilton-HP Filter Controversy: Evidence from German Business Cycles," MAGKS Papers on Economics 202421, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    7. Perron, Pierre & Wada, Tatsuma, 2016. "Measuring business cycles with structural breaks and outliers: Applications to international data," Research in Economics, Elsevier, vol. 70(2), pages 281-303.
    8. Vitek, Francis, 2006. "Measuring the Stance of Monetary Policy in a Small Open Economy: A Dynamic Stochastic General Equilibrium Approach," MPRA Paper 802, University Library of Munich, Germany.
    9. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October.
    10. 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.
    11. Jesús Cuaresma & Ernest Gnan & Doris Ritzberger-Gruenwald, 2004. "Searching for the natural rate of interest: a euro area perspective," Economic Change and Restructuring, Springer, vol. 31(2), pages 185-204, June.
    12. Henriques, Irene & Sadorsky, Perry, 2023. "Forecasting rare earth stock prices with machine learning," Resources Policy, Elsevier, vol. 86(PA).
    13. Marco Gallegati & Mauro Gallegati, 2005. "Wavelet variance and correlation analyses of output in G7 countries," Macroeconomics 0512017, University Library of Munich, Germany.
    14. João T. Jalles, 2022. "Do credit rating agencies reward fiscal prudence?," International Finance, Wiley Blackwell, vol. 25(1), pages 2-22, April.
    15. Pin Li & Jinsuo Zhang, 2019. "Is China’s Energy Supply Sustainable? New Research Model Based on the Exponential Smoothing and GM(1,1) Methods," Energies, MDPI, vol. 12(2), pages 1-30, January.
    16. Javier J. Pérez & Jesús Rodríguez López & Carlos Usabiaga, 2002. "Análisis Dinámico de la Relación entre Ciclo Económico y Ciclo del Desempleo en Andalucía en Comparación con el Resto de España," Economic Working Papers at Centro de Estudios Andaluces E2002/07, Centro de Estudios Andaluces.
    17. Grintzalis, Ioannis & Lodge, David & Manu, Ana-Simona, 2017. "The implications of global and domestic credit cycles for emerging market economies: measures of finance-adjusted output gaps," Working Paper Series 2034, European Central Bank.
    18. Drew, Aaron & Hunt, Benjamin, 2000. "Efficient simple policy rules and the implications of potential output uncertainty," Journal of Economics and Business, Elsevier, vol. 52(1-2), pages 143-160.
    19. Tommaso Proietti, 2002. "Some Reflections on Trend-Cycle Decompositions with Correlated Components," Econometrics 0209002, University Library of Munich, Germany.
    20. Mark Knell & Simone Vannuccini, 2022. "Tools and concepts for understanding disruptive technological change after Schumpeter," Jena Economics Research Papers 2022-005, Friedrich-Schiller-University Jena.

    More about this item

    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:bla:ausecp:v:63:y:2024:i:1:p:36-58. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0004-900X .

    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.