IDEAS home Printed from https://ideas.repec.org/p/cam/camdae/2065.html
   My bibliography  Save this paper

On Time Trend of COVID-19: A Panel Data Study

Author

Listed:
  • Dong, C.
  • Gao, J.
  • Linton, O.
  • Peng, B.

Abstract

In this paper, we study the trending behaviour of COVID-19 data at country level, and draw attention to some existing econometric tools which are potentially helpful to understand the trend better in future studies. In our empirical study, we find that European countries overall flatten the curves more effectively compared to the other regions, while Asia & Oceania also achieve some success, but the situations are not as optimistic as in Europe. Africa and America are still facing serious challenges in terms of managing the spread of the virus and reducing the death rate. In Africa, the rate of the spread of the virus is slower and the death rate is also lower than those of the other regions. By comparing the performances of different countries, our results on the performance of different countries in managing the speed of the virus agree with Gu et al. (2020). For example, both studies agree that countries such as USA, UK and Italy perform relatively poorly; on the other hand, Australia, China, Japan, Korea, and Singapore perform relatively better.

Suggested Citation

  • Dong, C. & Gao, J. & Linton, O. & Peng, B., 2020. "On Time Trend of COVID-19: A Panel Data Study," Cambridge Working Papers in Economics 2065, Faculty of Economics, University of Cambridge.
  • Handle: RePEc:cam:camdae:2065
    Note: obl20
    as

    Download full text from publisher

    File URL: http://www.econ.cam.ac.uk/research-files/repec/cam/pdf/cwpe2065.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Yongmiao Hong, 2005. "Nonparametric Specification Testing for Continuous-Time Models with Applications to Term Structure of Interest Rates," Review of Financial Studies, Society for Financial Studies, vol. 18(1), pages 37-84.
    2. Liu, Laura & Moon, Hyungsik Roger & Schorfheide, Frank, 2021. "Panel forecasts of country-level Covid-19 infections," Journal of Econometrics, Elsevier, vol. 220(1), pages 2-22.
    3. Qi Li & Jeffrey Scott Racine, 2006. "Density Estimation, from Nonparametric Econometrics: Theory and Practice," Introductory Chapters, in: Nonparametric Econometrics: Theory and Practice, Princeton University Press.
    4. Gao, Jiti & Linton, Oliver & Peng, Bin, 2020. "Inference On A Semiparametric Model With Global Power Law And Local Nonparametric Trends," Econometric Theory, Cambridge University Press, vol. 36(2), pages 223-249, April.
    5. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, number 8355, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    RePEc Biblio mentions

    As found on the RePEc Biblio, the curated bibliography for Economics:
    1. > Economics of Welfare > Health Economics > Economics of Pandemics > Specific pandemics > Covid-19 > Modelling > Statistical Modelling

    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. Walter Sosa-Escudero & Sergio Petralia, 2011. "Anatomy of Distributive Changes in Argentina," Chapters, in: Werner Baer & David Fleischer (ed.), The Economies of Argentina and Brazil, chapter 10, Edward Elgar Publishing.
    2. Eduardo Fé & Bruce Hollingsworth, 2016. "Short- and long-run estimates of the local effects of retirement on health," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(4), pages 1051-1067, October.
    3. Camelia Minoiu & Sanjay Reddy, 2014. "Kernel density estimation on grouped data: the case of poverty assessment," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 12(2), pages 163-189, June.
    4. Cornelius Christian & Lukas Hensel & Christopher Roth, 2019. "Income Shocks and Suicides: Causal Evidence From Indonesia," The Review of Economics and Statistics, MIT Press, vol. 101(5), pages 905-920, December.
    5. Manuel Hernandez & Maximo Torero, 2014. "Parametric versus nonparametric methods in risk scoring: an application to microcredit," Empirical Economics, Springer, vol. 46(3), pages 1057-1079, May.
    6. Damian Kozbur, 2013. "Inference in additively separable models with a high-dimensional set of conditioning variables," ECON - Working Papers 284, Department of Economics - University of Zurich, revised Apr 2018.
    7. Darolles, Serge & Florens, Jean-Pierre & Simon, Guillaume, 2010. "Nonparametric Analysis of Hedge Funds Lifetimes," IDEI Working Papers 620, Institut d'Économie Industrielle (IDEI), Toulouse.
    8. Christine Amsler & Yi Yi Chen & Peter Schmidt & Hung Jen Wang, 2021. "A hierarchical panel data stochastic frontier model for the estimation of stochastic metafrontiers," Empirical Economics, Springer, vol. 60(1), pages 353-363, January.
    9. Eduardo Fé Rodríguez, 2009. "Adaptive Instrumental Variable Estimation of Heteroskedastic Error Component Models," Economics Discussion Paper Series 0921, Economics, The University of Manchester.
    10. Quoc-Anh Do & Kieu-Trang Nguyen & Anh N. Tran, 2017. "One Mandarin Benefits the Whole Clan: Hometown Favoritism in an Authoritarian Regime," American Economic Journal: Applied Economics, American Economic Association, vol. 9(4), pages 1-29, October.
    11. Filipe R. Campante & Quoc-Anh Do & Bernardo Guimaraes, 2019. "Capital Cities, Conflict, and Misgovernance," American Economic Journal: Applied Economics, American Economic Association, vol. 11(3), pages 298-337, July.
    12. Richard Blundell & Dennis Kristensen & Rosa Matzkin, 2017. "Individual counterfactuals with multidimensional unobserved heterogeneity," CeMMAP working papers CWP60/17, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    13. Alberto Gude & Inmaculada Álvarez & Luis Orea, 2018. "Heterogeneous spillovers among Spanish provinces: a generalized spatial stochastic frontier model," Journal of Productivity Analysis, Springer, vol. 50(3), pages 155-173, December.
    14. Senay SOKULLU & Sami STOULI, 2017. "Cross-Validation Selection of Regularisation Parameter(s) for Semiparametric Transformation Models," Annals of Economics and Statistics, GENES, issue 128, pages 67-108.
    15. Hernandez, Manuel A. & Torero, Maximo, 2018. "A poverty-sensitive scorecard to prioritize lending and grant allocation: Evidence from Central America," Food Policy, Elsevier, vol. 77(C), pages 81-90.
    16. Daniel J. Henderson & Léopold Simar & Le Wang, 2017. "The three s of public schools: irrelevant inputs, insufficient resources and inefficiency," Applied Economics, Taylor & Francis Journals, vol. 49(12), pages 1164-1184, March.
    17. Meng-Shiuh Chang & Victoria Salin & Yanhong Jin, 2011. "Diversification effect of real estate investment trusts: Comparing copula functions with kernel methods," Journal of Property Research, Taylor & Francis Journals, vol. 28(3), pages 189-212, January.
    18. Barigozzi, Matteo & Brownlees, Christian & Gallo, Giampiero M. & Veredas, David, 2014. "Disentangling systematic and idiosyncratic dynamics in panels of volatility measures," Journal of Econometrics, Elsevier, vol. 182(2), pages 364-384.
    19. Chen, Xiaohong & Christensen, Timothy M., 2015. "Optimal uniform convergence rates and asymptotic normality for series estimators under weak dependence and weak conditions," Journal of Econometrics, Elsevier, vol. 188(2), pages 447-465.
    20. Boldron, François & Fève, Frédérique & Florens, Jean-Pierre & Panet-Amaro, C. & Valognes, C., 2010. "Econometric Models and the Evolution of Post-Offices Network," IDEI Working Papers 626, Institut d'Économie Industrielle (IDEI), Toulouse.

    More about this item

    Keywords

    COVID-19; Deterministic time trend; Panel data; Varying-coefficient;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling

    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:cam:camdae:2065. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://www.econ.cam.ac.uk/ .

    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: Jake Dyer (email available below). General contact details of provider: https://www.econ.cam.ac.uk/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.