IDEAS home Printed from https://ideas.repec.org/a/eee/ecmode/v124y2023ics0264999323001116.html
   My bibliography  Save this article

Subnational governments and COVID management

Author

Listed:
  • Bandyopadhyay, Simanti
  • Kabiraj, Sujana
  • Majumder, Subrata

Abstract

In the backdrop of COVID, this paper is the first to investigate the role of different classes of indicators at the subnational (state) levels in managing the crisis, which would augment the role played by the central governments. Three distinct time periods are considered between August and November 2020. We sample three amongst the worst affected countries viz, India, Mexico and USA, belonging to three different stages of development. First, a meta frontier analysis with state level data is attempted to estimate the efficiency of COVID management using DEA. Country level efficiency scores increase over time indicating a positive role of experience in crisis management. The states in USA performed consistently better compared to states in other countries. An exploratory median analysis in the second stage shows that finance, development and governance indicators at the subnational levels prove to impact the performance in COVID management in varying degrees.

Suggested Citation

  • Bandyopadhyay, Simanti & Kabiraj, Sujana & Majumder, Subrata, 2023. "Subnational governments and COVID management," Economic Modelling, Elsevier, vol. 124(C).
  • Handle: RePEc:eee:ecmode:v:124:y:2023:i:c:s0264999323001116
    DOI: 10.1016/j.econmod.2023.106299
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0264999323001116
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.econmod.2023.106299?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Dergiades, Theologos & Milas, Costas & Panagiotidis, Theodore, 2022. "Unemployment claims during COVID-19 and economic support measures in the U.S," Economic Modelling, Elsevier, vol. 113(C).
    2. Simanti Bandyopadhyay & Sujana Kabiraj & Subrata Majumder, 2021. "Performances in COVID 19 Management Across Countries: Do Subnational Finances Matter?," International Center for Public Policy Working Paper Series, at AYSPS, GSU paper2110, International Center for Public Policy, Andrew Young School of Policy Studies, Georgia State University.
    3. Jelnov, Artyom & Jelnov, Pavel, 2022. "Vaccination policy and trust," Economic Modelling, Elsevier, vol. 108(C).
    4. Dutta, Anwesha & Fischer, Harry W., 2021. "The local governance of COVID-19: Disease prevention and social security in rural India," World Development, Elsevier, vol. 138(C).
    5. Teng, Bin & Wang, Sicong & Shi, Yufeng & Sun, Yunchuan & Wang, Wei & Hu, Wentao & Shi, Chaojun, 2022. "Economic recovery forecasts under impacts of COVID-19," Economic Modelling, Elsevier, vol. 110(C).
    6. Lewkowicz, Jacek & Woźniak, Michał & Wrzesiński, Michał, 2022. "COVID-19 and erosion of democracy," Economic Modelling, Elsevier, vol. 106(C).
    7. Juraj Nemec & David Špaček, 2020. "The Covid-19 pandemic and local government finance: Czechia and Slovakia," Journal of Public Budgeting, Accounting & Financial Management, Emerald Group Publishing Limited, vol. 32(5), pages 837-846, August.
    8. George Battese & D. Rao & Christopher O'Donnell, 2004. "A Metafrontier Production Function for Estimation of Technical Efficiencies and Technology Gaps for Firms Operating Under Different Technologies," Journal of Productivity Analysis, Springer, vol. 21(1), pages 91-103, January.
    9. Rajiv D. Banker & Ram Natarajan, 2008. "Evaluating Contextual Variables Affecting Productivity Using Data Envelopment Analysis," Operations Research, INFORMS, vol. 56(1), pages 48-58, February.
    10. George E. Battese & D. S. Prasada Rao, 2002. "Technology Gap, Efficiency, and a Stochastic Metafrontier Function," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 1(2), pages 87-93, August.
    11. Winkelmann, Juliane & Webb, Erin & Williams, Gemma A. & Hernández-Quevedo, Cristina & Maier, Claudia B. & Panteli, Dimitra, 2022. "European countries' responses in ensuring sufficient physical infrastructure and workforce capacity during the first COVID-19 wave," Health Policy, Elsevier, vol. 126(5), pages 362-372.
    12. Utteeyo Dasgupta & Chandan Kumar Jha & Sudipta Sarangi, 2021. "Persistent Patterns Of Behavior: Two Infectious Disease Outbreaks 350 Years Apart," Economic Inquiry, Western Economic Association International, vol. 59(2), pages 848-857, 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. J. David Cummins & María Rubio-Misas, 2022. "Integration and convergence in efficiency and technology gap of European life insurance markets," Annals of Operations Research, Springer, vol. 315(1), pages 93-119, August.
    2. Juan Piedra-Peña & Diego Prior, 2023. "Analyzing the effect of health reforms on the efficiency of Ecuadorian public hospitals," International Journal of Health Economics and Management, Springer, vol. 23(3), pages 361-392, September.
    3. Carlucci, Fabio & Corcione, Carlo & Mazzocchi, Paolo & Trincone, Barbara, 2021. "The role of logistics in promoting Italian agribusiness: The Belt and Road Initiative case study," Land Use Policy, Elsevier, vol. 108(C).
    4. Wirat Krasachat & Suthathip Yaisawarng, 2021. "Directional Distance Function Technical Efficiency of Chili Production in Thailand," Sustainability, MDPI, vol. 13(2), pages 1-18, January.
    5. Subal C. Kumbhakar & Christopher F. Parmeter & Valentin Zelenyuk, 2022. "Stochastic Frontier Analysis: Foundations and Advances I," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 8, pages 331-370, Springer.
    6. Yongqi Feng & Haolin Zhang & Yung-ho Chiu & Tzu-Han Chang, 2021. "Innovation efficiency and the impact of the institutional quality: a cross-country analysis using the two-stage meta-frontier dynamic network DEA model," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3091-3129, April.
    7. Inyoung Park & Jieon Lee & Jungwoo Nam & Yuri Jo & Daeho Lee, 2022. "Which networking strategy improves ICT startup companies' technical efficiency?," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(6), pages 2434-2443, September.
    8. Farnaz Pourzand & Mohammad Bakhshoodeh, 2014. "Technical effici ency and agricultural sustainability–technology gap of maize producers in Fars province of Iran," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 16(3), pages 671-688, June.
    9. Chin‐wei Huang & Hsiao‐Yin Chen, 2023. "Using nonradial metafrontier data envelopment analysis to evaluate the metatechnology and metafactor ratios for the Taiwanese hotel industry," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(4), pages 1904-1919, June.
    10. Afsharian, Mohsen & Ahn, Heinz & Harms, Sören Guntram, 2019. "Performance comparison of management groups under centralised management," European Journal of Operational Research, Elsevier, vol. 278(3), pages 845-854.
    11. Camanho, Ana S. & Stumbriene, Dovile & Barbosa, Flávia & Jakaitiene, Audrone, 2023. "The assessment of performance trends and convergence in education and training systems of European countries," European Journal of Operational Research, Elsevier, vol. 305(1), pages 356-372.
    12. Breustedt, Gunnar & Tiedemann, Torben & Latacz-Lohmann, Uwe, 2009. "What is my optimal technology? A metafrontier approach using Data Envelopment Analysis for the choice between conventional and organic farming," 2009 Conference, August 16-22, 2009, Beijing, China 51754, International Association of Agricultural Economists.
    13. Thanh Pham Thien Nguyen & Son Hong Nghiem & Eduardo Roca & Parmendra Sharma, 2016. "Efficiency, innovation and competition: evidence from Vietnam, China and India," Empirical Economics, Springer, vol. 51(3), pages 1235-1259, November.
    14. Lee, Kyoungsun & Park, Yuri & Lee, Daeho, 2018. "Measuring efficiency and ICT ecosystem impact: Hardware vs. software industry," Telecommunications Policy, Elsevier, vol. 42(2), pages 107-115.
    15. Latruffe, Laure & Fogarasi, József & Desjeux, Yann, 2012. "Efficiency, productivity and technology comparison for farms in Central and Western Europe: The case of field crop and dairy farming in Hungary and France," Economic Systems, Elsevier, vol. 36(2), pages 264-278.
    16. Saeid Hajihassaniasl & Recep Kök, 2016. "Scale effect in Turkish manufacturing industry: stochastic metafrontier analysis," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 5(1), pages 1-17, December.
    17. Sombat Singkharat & Aree Wiboonpongse & Yaovarate Chaovanapoonphol, 2012. "Efficiency of improved peeled longan drying technology in Thailand: A metafrontier approach," The Empirical Econometrics and Quantitative Economics Letters, Faculty of Economics, Chiang Mai University, vol. 1(3), pages 19-32, September.
    18. Torben Tiedemann & Tammo Francksen & Uwe Latacz-Lohmann, 2011. "Assessing the performance of German Bundesliga football players: a non-parametric metafrontier approach," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 19(4), pages 571-587, December.
    19. Yuri Jo & Won Young Chung & Daeho Lee, 2020. "The capability‐enhancing role of government‐driven industrial districts for new technology‐based firms in South Korea," Asia and the Pacific Policy Studies, Wiley Blackwell, vol. 7(3), pages 306-321, September.
    20. Koangsung Choi & Chung Choe & Daeho Lee, 2021. "The Effect of Employing Temporary Workers on Efficiency: Evidence From a Meta-Frontier Analysis," SAGE Open, , vol. 11(4), pages 21582440211, November.

    More about this item

    Keywords

    Subnational finance; Development indicators; COVID Management; Non-parametric methods; Meta frontier analysis;
    All these keywords.

    JEL classification:

    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • H70 - Public Economics - - State and Local Government; Intergovernmental Relations - - - General
    • H71 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Taxation, Subsidies, and Revenue
    • H72 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Budget and Expenditures
    • H75 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Government: Health, Education, and Welfare

    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:eee:ecmode:v:124:y:2023:i:c:s0264999323001116. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/30411 .

    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.