IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i14p7474-d593527.html
   My bibliography  Save this article

Evaluation of COVID-19 Mitigation Policies in Australia Using Generalised Space-Time Autoregressive Intervention Models

Author

Listed:
  • Ryan H. L. Ip

    (School of Computing and Mathematics, Charles Sturt University, Wagga Wagga, NSW 2650, Australia
    These authors contributed equally to this work.)

  • Dmitry Demskoi

    (School of Computing and Mathematics, Charles Sturt University, Wagga Wagga, NSW 2650, Australia
    These authors contributed equally to this work.)

  • Azizur Rahman

    (School of Computing and Mathematics, Charles Sturt University, Wagga Wagga, NSW 2650, Australia
    These authors contributed equally to this work.)

  • Lihong Zheng

    (School of Computing and Mathematics, Charles Sturt University, Wagga Wagga, NSW 2650, Australia
    These authors contributed equally to this work.)

Abstract

In handling the COVID-19 pandemic, various mitigation policies aiming at slowing the spread and protecting all individuals, especially the vulnerable ones, were implemented. A careful evaluation of the effectiveness of these policies is necessary so that policy-makers can implement informed decisions if another wave of COVID-19 or another pandemic happens in the future. This paper reports an assessment of some policies introduced by the Australian governments using a generalised space-time autoregressive model which incorporates multiple exogenous variables and delay effects. Our results show that the number of daily new cases from the states and territories are influenced by both temporal and spatial aspects. Business and border restrictions are found helpful in reducing the number of new cases a few days after implementation while gathering restrictions may not be effective.

Suggested Citation

  • Ryan H. L. Ip & Dmitry Demskoi & Azizur Rahman & Lihong Zheng, 2021. "Evaluation of COVID-19 Mitigation Policies in Australia Using Generalised Space-Time Autoregressive Intervention Models," IJERPH, MDPI, vol. 18(14), pages 1-17, July.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:14:p:7474-:d:593527
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/14/7474/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/18/14/7474/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Svetlana Borovkova & Hendrik P. Lopuhaä & Budi Nurani Ruchjana, 2008. "Consistency and asymptotic normality of least squares estimators in generalized STAR models," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 62(4), pages 482-508, November.
    2. Nunung Nurhayati & Udjianna S. Pasaribu & Oki Neswan, 2012. "Application of Generalized Space-Time Autoregressive Model on GDP Data in West European Countries," Journal of Probability and Statistics, Hindawi, vol. 2012, pages 1-16, May.
    3. Hiroyasu Inoue & Yasuyuki Todo, 2020. "The propagation of the economic impact through supply chains: The case of a mega-city lockdown against the spread of COVID-19," Papers 2003.14002, arXiv.org.
    4. Hiroyasu Inoue & Yasuyuki Todo, 2020. "The propagation of economic impacts through supply chains: The case of a mega-city lockdown to prevent the spread of COVID-19," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-10, September.
    5. Valter Di Giacinto, 2006. "A Generalized Space-Time ARMA Model with an Application to Regional Unemployment Analysis in Italy," International Regional Science Review, , vol. 29(2), pages 159-198, April.
    6. Liu, Aiyi, 2002. "Efficient Estimation of Two Seemingly Unrelated Regression Equations," Journal of Multivariate Analysis, Elsevier, vol. 82(2), pages 445-456, August.
    7. Srivastava, V. K. & Dwivedi, T. D., 1979. "Estimation of seemingly unrelated regression equations : A brief survey," Journal of Econometrics, Elsevier, vol. 10(1), pages 15-32, April.
    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. Gehman, Andrew & Wei, William W.S., 2020. "Optimal spatial aggregation of space–time models and applications," Computational Statistics & Data Analysis, Elsevier, vol. 145(C).
    2. Souknilanh Keola & Kazunobu Hayakawa, 2021. "Do Lockdown Policies Reduce Economic and Social Activities? Evidence from NO2 Emissions," The Developing Economies, Institute of Developing Economies, vol. 59(2), pages 178-205, June.
    3. Keiichi Morimoto & Shiba Suzuki, 2022. "Ambiguity in a pandemic recession, asset prices, and lockdown policy," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 24(5), pages 1039-1070, October.
    4. Nano Prawoto & Eko Priyo Purnomo & Abitassha Az Zahra, 2020. "The Impacts of Covid-19 Pandemic on Socio-Economic Mobility in Indonesia," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(3), pages 57-71.
    5. Prol, Javier López & O, Sungmin, 2020. "Impact of COVID-19 Measures on Short-Term Electricity Consumption in the Most Affected EU Countries and USA States," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 23(10).
    6. INOUE Hiroyasu & MURASE Yohsuke & TODO Yasuyuki, 2022. "Lockdowns Require Geographic Coordination because of the Propagation of Economic Effects through Supply Chains," Discussion papers 22076, Research Institute of Economy, Trade and Industry (RIETI).
    7. Antoine Mandel & Vipin Veetil, 2020. "The Economic Cost of COVID Lockdowns: An Out-of-Equilibrium Analysis," Economics of Disasters and Climate Change, Springer, vol. 4(3), pages 431-451, October.
    8. Mohammadreza Akbari & John L. Hopkins, 2022. "Digital technologies as enablers of supply chain sustainability in an emerging economy," Operations Management Research, Springer, vol. 15(3), pages 689-710, December.
    9. Vijaya Bandyopadhyaya & Ranja Bandyopadhyaya, 2024. "Understanding the Impact of COVID-19 Pandemic Outbreak on Grocery Stocking Behaviour in India: A Pattern Mining Approach," Global Business Review, International Management Institute, vol. 25(3), pages 750-770, June.
    10. Kahn, Charles M. & Wagner, Wolf, 2021. "Liquidity provision during a pandemic," Journal of Banking & Finance, Elsevier, vol. 133(C).
    11. Mellacher, Patrick, 2020. "COVID-Town: An Integrated Economic-Epidemiological Agent-Based Model," MPRA Paper 103661, University Library of Munich, Germany.
    12. Trinh Q. Long, 2021. "Individual Subjective Well-Being during the COVID-19 Pandemic," Sustainability, MDPI, vol. 13(14), pages 1-18, July.
    13. Andrea Coveri & Claudio Cozza & Leopoldo Nascia & Antonello Zanfei, 2020. "Supply chain contagion and the role of industrial policy," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 47(3), pages 467-482, September.
    14. Hamermesh, Daniel S., 2020. "Lockdowns, Loneliness and Life Satisfaction," IZA Discussion Papers 13140, Institute of Labor Economics (IZA).
    15. Kazunobu Hayakawa & Hiroshi Mukunoki, 2021. "Impacts of COVID‐19 on Global Value Chains," The Developing Economies, Institute of Developing Economies, vol. 59(2), pages 154-177, June.
    16. Martin Forster & Emanuela Randon, 2020. "Epidemic policy under uncertainty and information," Discussion Papers 20/05, Department of Economics, University of York.
    17. INOUE Hiroyasu & TODO Yasuyuki, 2022. "Propagation of Overseas Economic Shocks through Global Supply Chains: Firm-level evidence," Discussion papers 22062, Research Institute of Economy, Trade and Industry (RIETI).
    18. Yuli Shan & Jiamin Ou & Daoping Wang & Zhao Zeng & Shaohui Zhang & Dabo Guan & Klaus Hubacek, 2021. "Impacts of COVID-19 and fiscal stimuli on global emissions and the Paris Agreement," Nature Climate Change, Nature, vol. 11(3), pages 200-206, March.
    19. Francesco Scotti & Andrea Flori & Giovanni Bonaccorsi & Fabio Pammolli, 2023. "Do We Learn From Errors? The Economic Impact of Differentiated Policy Restrictions in Italy," International Regional Science Review, , vol. 46(5-6), pages 613-648, September.
    20. Eduardo Rodrigues Sanguinet & Augusto Mussi Alvim & Miguel Atienza & Adelar Fochezatto, 2021. "The subnational supply chain and the COVID‐19 pandemic: Short‐term impacts on the Brazilian regional economy," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(S1), pages 158-186, November.

    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:gam:jijerp:v:18:y:2021:i:14:p:7474-:d:593527. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.