Reasons for Some Countries Having More COVID-19 Cases Than Others: Evidence from 70 Most Affected Countries <i>sans</i> China

Mohammad Mokammel Karim Toufique

doi:doi:10.11648/j.jwer.20200902.13

| Peer-Reviewed

Reasons for Some Countries Having More COVID-19 Cases Than Others: Evidence from 70 Most Affected Countries sans China

Mohammad Mokammel Karim Toufique

Published in Journal of World Economic Research (Volume 9, Issue 2)

Received: 30 July 2020 Accepted: 2 September 2020 Published: 17 September 2020

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

Abstract

A look into the country-level data on the number of COVID-19 positive cases reveals considerable cross-country variations in the number of officially confirmed COVID-19 positive cases. Consequently, there exists a research gap in the relevant field of research. This paper attempts to explain the variations in the number of officially confirmed COVID-19 positive cases across countries around the world and thus fills in the research gap. The study develops a unique dataset of 70 of the most COVID-19 affected countries and employs multiple regression techniques. The findings indicate that regional characteristics play an essential role. Percent of people living in the urban area, number of tests, air passenger transport (an indicator of population mobility) also come out as determinants with substantial influence. Besides, the impacts of trade relationships with China (a proxy for the degree of interaction with the country) and per capita health expenditure appears to be noteworthy. Differences in temperature are found to have no appreciable impact. Also, factors such as the relative importance of health in national policy, the quality of life, and the quality of governance fail to register any vital influence. The study does not find any evidence of endogeneity of the total number of tests conducted.

Published in	Journal of World Economic Research (Volume 9, Issue 2)
DOI	10.11648/j.jwer.20200902.13
Page(s)	91-98
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2020. Published by Science Publishing Group

Keywords

COVID-19, Economics, Variation in Coronavirus Cases, Trade with China, Air Passenger Transport

References

[1]	World Health Organization (WHO) https://www.who.int/emergencies/diseases/novel-coronavirus-2019/(Accessed on July 11, 2020).
[2]	Baldwin, R. and B. Weder di Mauro, editors, Economics in the Time of COVID-19, CEPR Press, 2020.
[3]	Atkeson, Andrew. What Will Be the Economic Impact of COVID-19 in the US? Rough Estimates of Disease Scenarios. Working Paper 26867, National Bureau of Economic Research, March 2020.
[4]	Fetzer, Thiemo, Lukas Hensel, Johannes Hermle, and Chris Roth. 2020. Coronavirus Perceptions and Economic Anxiety. arXiv: 2003.03848.
[5]	Adams-Prassl, Abi; Boneva, Teodora; Golin, Marta; Rauh, Christopher (2020): Inequality in the Impact of the Coronavirus Shock: Evidence from Real-Time Surveys, IZA Discussion Papers, No. 13183, Institute of Labor Economics (IZA), Bonn
[6]	Wright, Austin L, Konstantin Sonin, Jesse Driscoll, and Jarnickae Wilson (2020). Poverty and economic dislocation reduce compliance with COVID-19 shelter-in-place protocols. The University of Chicago, Becker Friedman Institute for Economics Working Paper (2020-40).
[7]	Brzezinski, A., Kecht, V., Dijcke, D. V., and Wright, A. L. (2020). Belief in Science Influences Physical Distancing in Response to COVID-19 Lockdown Policies. The University of Chicago, Becker Friedman Institute for Economics Working Paper (2020-56).
[8]	Barro, Robert J., Jose F. Ursua, and Joanna Weng. 2020. The coronavirus and the great influenza epidemic: Lessons from the Spanish flu for the coronavirus potential effects on mortality and economic activity. AEI Economics Working Paper 2020-02, American Enterprise Institute.
[9]	Eichenbaum, Martin S., Sergio Rebelo, and Mathias Trabandtz. 2020. The Macroeconomics of Epidemics. Author's website, Northwestern University.
[10]	Hall, Robert E., Charles I. Jones, and Peter J. Klenow. 2020. Trading of Consumption and COVID-19 Deaths. Mimeo, Stanford University.
[11]	Dewatripont, Mathias, Michel Goldman, Eric Muraille, and Jean-Philippe Platteau. 2020.Rapid identification of workers immune to COVID-19 and virus-free: A priority to restart the economy. Discussion paper, Universit Libre de Bruxelles.
[12]	Piguillem, F. and Shi, L., 2020. The Optimal COVID-19 Quarantine and Testing Policies. Working paper 20/04, EIEF.
[13]	Jones, Callum, Thomas Philippon, and Venky Venkateswaran. 2020. Optimal Mitigation Policies in a Pandemic. Tech. Rep., NYU.
[14]	Alvarez, Fernando, David Argente, and Francesco Lippi, A Simple Planning Problem for COVID-19 Lockdown. March 2020. Mimeo.
[15]	Fang, Hanming, Long Wang, and Yang Yang (2020). Human mobility restrictions and the spread of the novel coronavirus (2019-nCoV) in China. Technical report, National Bureau of Economic Research.
[16]	Juranek, Steffen and Floris Zoutman (2020) The Effect of Social Distancing Measures on the Demand for Intensive Care: Evidence on COVID-19 in Scandinavia. Available at SSRN 3577213.
[17]	Qiu, Yun, Xi Chen, and Wei Shi (2020) Impacts of social and economic factors on the transmission of coronavirus disease (COVID-19) in China. medRxiv.
[18]	Alexander, D. and Karger, E. (2020). Do Stay-at-Home Orders Cause People to Stay at Home? Effects of Stay-at-Home Orders on Consumer Behavior.
[19]	Alé-Chilet, J., Atal, JP, Domínguez, P. 2020. Where are the missing emergencies? Lockdown and health risk during the pandemic. COVID Economics 14.
[20]	Dingel, Jonathan I., and Brent Neiman. 2020. How Many Jobs Can be Done at Home? CEPR. COVID Economics 1.
[21]	Saltiel, Fernando. 2020. Who Can Work From Home in Developing Countries?. CEPR. COVID Economics 6.
[22]	Delaporte, I., & Peña, W. (2020). Working From Home Under COVID-19: Who Is Affected? Evidence From Latin American and Caribbean Countries. CEPR. COVID Economics 14.
[23]	Fornaro, L., and M. Wolf. 2020. Covid-19 coronavirus and macroeconomic policy. CEPR working paper.
[24]	Chiou, L., and C. Tucker. Social distancing, internet access, and inequality. Working Paper 26982 National Bureau of Economic Research, April 2020. http://www.nber.org/papers/w26982.
[25]	Barrot, J.-N., B. Grassi, and J. Sauvagnat. 2020. Sectoral effects of social distancing. CEPR's COVID Economics Review No. 3.
[26]	Alon, T. M., M. Doepke, J. Olmstead-Rumsey, and M. Tertilt. 2020. The impact of COVID-19 on gender equality. CEPR's COVID Economics Review No. 4.
[27]	Glover, A., J. Heathcote, D. Krueger, and J.-V. Rios-Rull. 2020. Health versus wealth: On the distributional effects of controlling a pandemic. CEPR's COVID Economics Review No. 6.
[28]	Corsetti, G., M. Bodenstein, and L. Guerrieri. 2020. Social distancing and supply disruptions in a pandemic. CEPR Discussion Paper.
[29]	Caballero, R. J., and A. Simsek. 2020. A model of asset price spirals and aggregate demand amplification of a "COVID-19" shock. CEPR Discussion Paper.
[30]	Coven, J., and A. Gupta. 2020. Disparities in mobility response to COVID-19. Working paper.
[31]	Baker, S. R., N. Bloom, S. J. Davis, and S. J. Terry. COVID-induced economic uncertainty. Working Paper 26983 National Bureau of Economic Research April 2020.
[32]	Hassan, T. A., S. Hollander, L. van Lent, and A. Tahoun. Firm-level exposure to epidemic diseases: Covid-19, sars, and h1n1. Working Paper 26971 National Bureau of Economic Research, April 2020.
[33]	Bartik, A. W., M. Bertrand, Z. B. Cullen, E. L. Glaeser, M. Luca, and C. T. Stanton. How are small businesses adjusting to COVID-19? Early evidence from a survey. Working Paper 26989 National Bureau of Economic Research, April 2020.
[34]	Giglio, S., M. Maggiori, J. Stroebel, and S. Utkus. 2020. Inside the mind of a stock market crash. arXiv preprint arXiv: 2004.01831.
[35]	Lewis, D., K. Mertens, and J. H. Stock. 2020. U.s. Economic activity during the early weeks of the sars-cov-2 outbreak. CEPR's COVID Economics Review No. 6.
[36]	Kirigia JM, Muthuri RNDK, Muthuri NG: The net present value of human lives lost due to coronavirus disease (COVID-19) in the Islamic Republic of Iran. Research Square. 2020; Accessed June 11, 2020.
[37]	Worldometer. https://www.worldometers.info/(Accessed on July 02, 2020. 12: 43 am Bangladesh Time).
[38]	United Nations Development Program, Human Development Reports. http://hdr.undp.org/en/data (Accessed on July 06, 2020).
[39]	World Bank. https://data.worldbank.org/ (Accessed on July 06, 2020).
[40]	TradingEconomics. https://tradingeconomics.com/ (Accessed on July 06, 2020).
[41]	Transparency International (2019). Corruption Perception Index. https://www.transparency.org/en/cpi (Accessed on July 11, 2020).
[42]	Macrotrends.net https://www.macrotrends.net/ (Accessed on July 11, 2020).
[43]	Lloydsbanktrade.com https://www.lloydsbanktrade.com/en (Accessed on July 11, 2020).
[44]	CIA World Factbook and other Sources, 2020. https://www.cia.gov/library/publications/resources/the-world-factbook/ (accessed on July 11, 2020).
[45]	Kennedy, P. Oh No! I Got the Wrong Sign! What Should I Do? Department of Economics, Simon Fraser University, Discussions Paper, 02-3, 2002.
[46]	Economist Intelligence Unit, the (2019). Democracy Index. https://www.eiu.com/topic/democracy-index (accessed on July 07, 2020).

Cite This Article

Plain Text BibTeX RIS

APA Style

Mohammad Mokammel Karim Toufique. (2020). Reasons for Some Countries Having More COVID-19 Cases Than Others: Evidence from 70 Most Affected Countries sans China. Journal of World Economic Research, 9(2), 91-98. https://doi.org/10.11648/j.jwer.20200902.13

Copy | Download

ACS Style

Mohammad Mokammel Karim Toufique. Reasons for Some Countries Having More COVID-19 Cases Than Others: Evidence from 70 Most Affected Countries sans China. J. World Econ. Res. 2020, 9(2), 91-98. doi: 10.11648/j.jwer.20200902.13

Copy | Download

AMA Style

Mohammad Mokammel Karim Toufique. Reasons for Some Countries Having More COVID-19 Cases Than Others: Evidence from 70 Most Affected Countries sans China. J World Econ Res. 2020;9(2):91-98. doi: 10.11648/j.jwer.20200902.13

Copy | Download

@article{10.11648/j.jwer.20200902.13,
  author = {Mohammad Mokammel Karim Toufique},
  title = {Reasons for Some Countries Having More COVID-19 Cases Than Others: Evidence from 70 Most Affected Countries sans China},
  journal = {Journal of World Economic Research},
  volume = {9},
  number = {2},
  pages = {91-98},
  doi = {10.11648/j.jwer.20200902.13},
  url = {https://doi.org/10.11648/j.jwer.20200902.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jwer.20200902.13},
  abstract = {A look into the country-level data on the number of COVID-19 positive cases reveals considerable cross-country variations in the number of officially confirmed COVID-19 positive cases. Consequently, there exists a research gap in the relevant field of research. This paper attempts to explain the variations in the number of officially confirmed COVID-19 positive cases across countries around the world and thus fills in the research gap. The study develops a unique dataset of 70 of the most COVID-19 affected countries and employs multiple regression techniques. The findings indicate that regional characteristics play an essential role. Percent of people living in the urban area, number of tests, air passenger transport (an indicator of population mobility) also come out as determinants with substantial influence. Besides, the impacts of trade relationships with China (a proxy for the degree of interaction with the country) and per capita health expenditure appears to be noteworthy. Differences in temperature are found to have no appreciable impact. Also, factors such as the relative importance of health in national policy, the quality of life, and the quality of governance fail to register any vital influence. The study does not find any evidence of endogeneity of the total number of tests conducted.},
 year = {2020}
}

Copy | Download

TY - JOUR
T1 - Reasons for Some Countries Having More COVID-19 Cases Than Others: Evidence from 70 Most Affected Countries sans China
AU - Mohammad Mokammel Karim Toufique
Y1 - 2020/09/17
PY - 2020
N1 - https://doi.org/10.11648/j.jwer.20200902.13
DO - 10.11648/j.jwer.20200902.13
T2 - Journal of World Economic Research
JF - Journal of World Economic Research
JO - Journal of World Economic Research
SP - 91
EP - 98
PB - Science Publishing Group
SN - 2328-7748
UR - https://doi.org/10.11648/j.jwer.20200902.13
AB - A look into the country-level data on the number of COVID-19 positive cases reveals considerable cross-country variations in the number of officially confirmed COVID-19 positive cases. Consequently, there exists a research gap in the relevant field of research. This paper attempts to explain the variations in the number of officially confirmed COVID-19 positive cases across countries around the world and thus fills in the research gap. The study develops a unique dataset of 70 of the most COVID-19 affected countries and employs multiple regression techniques. The findings indicate that regional characteristics play an essential role. Percent of people living in the urban area, number of tests, air passenger transport (an indicator of population mobility) also come out as determinants with substantial influence. Besides, the impacts of trade relationships with China (a proxy for the degree of interaction with the country) and per capita health expenditure appears to be noteworthy. Differences in temperature are found to have no appreciable impact. Also, factors such as the relative importance of health in national policy, the quality of life, and the quality of governance fail to register any vital influence. The study does not find any evidence of endogeneity of the total number of tests conducted.
VL - 9
IS - 2
ER -

Copy | Download

Author Information

Mohammad Mokammel Karim Toufique

Department of Economics, Noakhali Science and Technology University, Noakhali, Bangladesh

Download PDF

Sections

Plain Text BibTeX RIS

APA Style

Mohammad Mokammel Karim Toufique. (2020). Reasons for Some Countries Having More COVID-19 Cases Than Others: Evidence from 70 Most Affected Countries sans China. Journal of World Economic Research, 9(2), 91-98. https://doi.org/10.11648/j.jwer.20200902.13

Copy | Download

ACS Style

Mohammad Mokammel Karim Toufique. Reasons for Some Countries Having More COVID-19 Cases Than Others: Evidence from 70 Most Affected Countries sans China. J. World Econ. Res. 2020, 9(2), 91-98. doi: 10.11648/j.jwer.20200902.13

Copy | Download

AMA Style

Mohammad Mokammel Karim Toufique. Reasons for Some Countries Having More COVID-19 Cases Than Others: Evidence from 70 Most Affected Countries sans China. J World Econ Res. 2020;9(2):91-98. doi: 10.11648/j.jwer.20200902.13

Copy | Download

@article{10.11648/j.jwer.20200902.13,
  author = {Mohammad Mokammel Karim Toufique},
  title = {Reasons for Some Countries Having More COVID-19 Cases Than Others: Evidence from 70 Most Affected Countries sans China},
  journal = {Journal of World Economic Research},
  volume = {9},
  number = {2},
  pages = {91-98},
  doi = {10.11648/j.jwer.20200902.13},
  url = {https://doi.org/10.11648/j.jwer.20200902.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.jwer.20200902.13},
  abstract = {A look into the country-level data on the number of COVID-19 positive cases reveals considerable cross-country variations in the number of officially confirmed COVID-19 positive cases. Consequently, there exists a research gap in the relevant field of research. This paper attempts to explain the variations in the number of officially confirmed COVID-19 positive cases across countries around the world and thus fills in the research gap. The study develops a unique dataset of 70 of the most COVID-19 affected countries and employs multiple regression techniques. The findings indicate that regional characteristics play an essential role. Percent of people living in the urban area, number of tests, air passenger transport (an indicator of population mobility) also come out as determinants with substantial influence. Besides, the impacts of trade relationships with China (a proxy for the degree of interaction with the country) and per capita health expenditure appears to be noteworthy. Differences in temperature are found to have no appreciable impact. Also, factors such as the relative importance of health in national policy, the quality of life, and the quality of governance fail to register any vital influence. The study does not find any evidence of endogeneity of the total number of tests conducted.},
 year = {2020}
}

Copy | Download