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The impact of state capacity on the cross-country variations in COVID-19 vaccination rates

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  • Dragan Tevdovski
  • Petar Jolakoski
  • Viktor Stojkoski

Abstract

The initial period of vaccination shows strong heterogeneity between countries' vaccinations rollout, both in the terms of the start of the vaccination process and in the dynamics of the number of people that are vaccinated. A predominant thesis in the ongoing debate on the drivers of this observed heterogeneity is that a key determinant of the swift and extensive vaccine rollout is state capacity. Here, we utilize two measures that quantify different aspects of the state capacity: i) the external capacity (measured through the soft power and the economic power of the country) and ii) the internal capacity (measured via the country's government effectiveness) and investigate their relationship with the coronavirus vaccination outcome in the initial period (up to 30th January 2021). By using data on 189 countries and a two-step Heckman approach, we find that the economic power of the country and its soft power are robust determinants of whether a country has started with the vaccination process. In addition, the government effectiveness is a key factor that determines vaccine roll-out. Altogether, our findings are in line with the hypothesis that state capacity determines the observed heterogeneity between countries in the initial period of COVID-19 vaccines rollout.

Suggested Citation

  • Dragan Tevdovski & Petar Jolakoski & Viktor Stojkoski, 2021. "The impact of state capacity on the cross-country variations in COVID-19 vaccination rates," Papers 2103.04981, arXiv.org.
  • Handle: RePEc:arx:papers:2103.04981
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    References listed on IDEAS

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    1. Cingolani, Luciana & Thomsson, Kaj & de Crombrugghe, Denis, 2015. "Minding Weber More Than Ever? The Impacts of State Capacity and Bureaucratic Autonomy on Development Goals," World Development, Elsevier, vol. 72(C), pages 191-207.
    2. Timothy Besley & Torsten Persson, 2010. "State Capacity, Conflict, and Development," Econometrica, Econometric Society, vol. 78(1), pages 1-34, January.
    3. Daron Acemoglu & Camilo García-Jimeno & James A. Robinson, 2015. "State Capacity and Economic Development: A Network Approach," American Economic Review, American Economic Association, vol. 105(8), pages 2364-2409, August.
    4. Heckman, James J, 1974. "Shadow Prices, Market Wages, and Labor Supply," Econometrica, Econometric Society, vol. 42(4), pages 679-694, July.
    5. Khemani,Stuti, 2019. "What Is State Capacity ?," Policy Research Working Paper Series 8734, The World Bank.
    6. Viktor Stojkoski & Zoran Utkovski & Petar Jolakoski & Dragan Tevdovski & Ljupco Kocarev, 2020. "Correlates of the country differences in the infection and mortality rates during the first wave of the COVID-19 pandemic: Evidence from Bayesian model averaging," Papers 2004.07947, arXiv.org, revised Jan 2022.
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    Cited by:

    1. Orhan Erdem & Sukran Erdem & Kelly Monson, 2023. "Children, vaccines, and financial incentives," International Journal of Health Economics and Management, Springer, vol. 23(4), pages 537-552, December.
    2. Chiara F. Del Bo, 2023. "Institutional quality and COVID-19 vaccination: does decentralization matter?," Letters in Spatial and Resource Sciences, Springer, vol. 16(1), pages 1-24, December.
    3. Dragan Tevdovski & Petar Jolakoski & Viktor Stojkoski, 2021. "Determinants of budget deficits: Focus on the effects from the COVID-19 crisis," Papers 2105.14959, arXiv.org.
    4. Dragan Tevdovski & Petar Jolakoski & Viktor Stojkoski, 2022. "Determinants Of Budget Deficits: The Effects Of The Covid-19 Crisis," Economic Annals, Faculty of Economics and Business, University of Belgrade, vol. 67(232), pages 105-126, January –.
    5. Ogundari, Kolawole, 2023. "Testing Club Convergence in COVID-19 Vaccine Doses Administered in the United States," MPRA Paper 116666, University Library of Munich, Germany.
    6. Saša Ranđelović & Svetozar Tanasković, 2024. "Socioeconomic determinants of COVID-19 vaccine acceptance," International Journal of Health Economics and Management, Springer, vol. 24(4), pages 537-553, December.

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    More about this item

    JEL classification:

    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling
    • F51 - International Economics - - International Relations, National Security, and International Political Economy - - - International Conflicts; Negotiations; Sanctions
    • F63 - International Economics - - Economic Impacts of Globalization - - - Economic Development

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