IDEAS home Printed from https://ideas.repec.org/p/ulp/sbbeta/2021-42.html
   My bibliography  Save this paper

Une analyse économétrique des déterminants des hospitalisations dues à la Covid-19

Author

Listed:
  • Francis Bismans

Abstract

Ce document de travail s’appuie sur des données journalières relatives aux personnes vaccinées, à celles infectées par le coronavirus et aux hospitalisations pour tenter d’établir une relation de cointégration entre ces différentes variables. Les séries utilisées concernent la Belgique et vont du 1er février 2021 au 20 septembre 2021. Cette relation s’obtient à l’aide d’un modèle économétrique dynamique ARDL à correction d’erreur. Les principaux résultats de l’analyse sont les suivants : lorsque le nombre de vaccinés s’accroit de 1%, le nombre de personnes hospitalisées diminue, lui, de 0,24% ; quand celui des contaminations s’accroît de 1 pourcent, les hospitalisations augmentent de 1,05%.

Suggested Citation

  • Francis Bismans, 2021. "Une analyse économétrique des déterminants des hospitalisations dues à la Covid-19," Working Papers of BETA 2021-42, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    • Handle: RePEc:ulp:sbbeta:2021-42
    as

    Download full text from publisher

    File URL: http://beta.u-strasbg.fr/WP/2021/2021-42.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zivot, Eric & Andrews, Donald W K, 2002. "Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 25-44, January.
    2. Stock, James H & Watson, Mark W, 1993. "A Simple Estimator of Cointegrating Vectors in Higher Order Integrated Systems," Econometrica, Econometric Society, vol. 61(4), pages 783-820, July.
    3. M. Hashem Pesaran & Yongcheol Shin & Richard J. Smith, 2001. "Bounds testing approaches to the analysis of level relationships," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 289-326.
    4. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    5. Bhaskar Bagchi & Susmita Chatterjee & Raktim Ghosh & Dhrubaranjan Dandapat, 2020. "Coronavirus Outbreak and the Great Lockdown," SpringerBriefs in Economics, Springer, number 978-981-15-7782-6, October.
    6. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    7. Perron, Pierre, 1997. "Further evidence on breaking trend functions in macroeconomic variables," Journal of Econometrics, Elsevier, vol. 80(2), pages 355-385, October.
    8. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November.
    9. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
    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. Ogali, Oscar I.O. & Okoro, Emeka E. & Olafuyi, Saburi G., 2023. "Assessing consensus on nexus between natural gas consumption and economic growth," Renewable and Sustainable Energy Reviews, Elsevier, vol. 187(C).
    2. Brittle, Shane, 2009. "Ricardian Equivalence and the Efficacy of Fiscal Policy in Australia," Economics Working Papers wp09-10, School of Economics, University of Wollongong, NSW, Australia.
    3. Jeng-Bau Lin & Chin-Chia Liang & Wei Tsai, 2019. "Nonlinear Relationships between Oil Prices and Implied Volatilities: Providing More Valuable Information," Sustainability, MDPI, vol. 11(14), pages 1-15, July.
    4. David Greasley & Les Oxley, 2010. "Cliometrics And Time Series Econometrics: Some Theory And Applications," Journal of Economic Surveys, Wiley Blackwell, vol. 24(5), pages 970-1042, December.
    5. Zou, Gao Lu, 2012. "The long-term relationships among China's energy consumption sources and adjustments to its renewable energy policy," Energy Policy, Elsevier, vol. 47(C), pages 456-467.
    6. Taha, Roshaiza & Colombage, Sisira R.N. & Maslyuk, Svetlana & Nanthakumar, Loganathan, 2013. "Does financial system activity affect tax revenue in Malaysia? Bounds testing and causality approach," Journal of Asian Economics, Elsevier, vol. 24(C), pages 147-157.
    7. Goh, Soo Khoon & McNown, Robert, 2015. "Examining the exchange rate regime–monetary policy autonomy nexus: Evidence from Malaysia," International Review of Economics & Finance, Elsevier, vol. 35(C), pages 292-303.
    8. Ciarreta Antuñano, Aitor & Zárraga Alonso, Ainhoa, 2007. "Electricity consumption and economic growth: evidence from Spain," BILTOKI 1134-8984, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística).
    9. Caner Demir & Raif Cergibozan & Adem Gök, 2019. "Income inequality and CO2 emissions: Empirical evidence from Turkey," Energy & Environment, , vol. 30(3), pages 444-461, May.
    10. Chun-Ping Chang & Chien-Chiang Lee, 2010. "A Re-examination of German Government Approval and Economic Performance: Is There a Stable Relationship between Them?," International Economic Journal, Taylor & Francis Journals, vol. 24(1), pages 25-43.
    11. John D. Levendis, 2018. "Time Series Econometrics," Springer Texts in Business and Economics, Springer, number 978-3-319-98282-3, April.
    12. Abdul Jalil & Samia Manan & Sundus Saleemi, 2016. "Estimating the growth effects of services sector: a cointegration analysis for Pakistan," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 5(1), pages 1-14, December.
    13. Yaya Keho, 2010. "Spending Cuts or Tax Adjustments: How Can UEMOA Countries Control Their Budget Deficits?," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 9(3), pages 233-252, December.
    14. Aliyu Alhaji Jibrilla, 2016. "Fiscal sustainability in the presence of structural breaks: Does overconfidence on resource exports hurt government’s ability to finance debt? Evidence from Nigeria," Cogent Economics & Finance, Taylor & Francis Journals, vol. 4(1), pages 1170317-117, December.
    15. Solarin, Sakiru Adebola & Shahbaz, Muhammad, 2013. "Trivariate causality between economic growth, urbanisation and electricity consumption in Angola: Cointegration and causality analysis," Energy Policy, Elsevier, vol. 60(C), pages 876-884.
    16. Chowdhury, Khorshed, 2012. "Modelling the dynamics, structural breaks and the determinants of the real exchange rate of Australia," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(2), pages 343-358.
    17. Akhand Akhtar Hossain, 2008. "Rural Labour Market Developments, Agricultural Productivity, and Real Wages in Bangladesh, 1950–2006," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 47(1), pages 89-114.
    18. Ahmad Zubaidi Baharumshah & Aliyu Alhaji Jibrilla & Abdalla Sirag & Hamisu Sadi Ali & Ibrahim Muye Muhammad, 2016. "Public Revenue-Expenditure Nexus in South Africa: Are there Asymmetries?," South African Journal of Economics, Economic Society of South Africa, vol. 84(4), pages 520-537, December.
    19. Makin, Anthony J. & Ratnasiri, Shyama, 2015. "Competitiveness and government expenditure: The Australian example," Economic Modelling, Elsevier, vol. 49(C), pages 154-161.

    More about this item

    Keywords

    Cointégration; Coronavirus; mécanisme à correction d’erreur; méthodologie GETS; modèle ARDL; pandémie; tests de racine unitaire.;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

    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:ulp:sbbeta:2021-42. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/bestrfr.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.