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An empirical investigation of country level efficiency and national systems of entrepreneurship using Data Envelopment Analysis (DEA) and the TOBIT model

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  • Nishat Tasnim

    (Shahjalal University of Science and Technology (SUST))

  • Munshi Naser Ibne Afzal

    (Shahjalal University of Science and Technology (SUST)
    University of Southern Queensland
    HBMSU)

Abstract

The goal of this paper is to investigate effects of national systems of entrepreneurship on the country level efficiency, on addition we find what macro factors affect efficiency as well. From a comprehensive database of 59 countries using GEM, WDI, WCI for 2018 using data envelopment analysis (DEA) we find the results support the theoretical grounding of Global Entrepreneurship Index (GEI) hypothesis. The GEI methodology has been designed to capture the core features of the National Systems of Entrepreneurship theory. It approaches country-level entrepreneurship as a systemic phenomenon, which is driven by the interaction between individual-level actions and country-level framework conditions. While discussing country level framework, we have depicted key macroeconomic indicators in the analysis along with GEI index. The DEA analysis followed this framework to assess the performance of the study countries. Though inefficiency widely varies across countries, while the group of factor-driven countries is the most inefficient while innovation-driven economies are the most efficient ones. Subsequently, we apply the Tobit model to explain efficiency. Based on the Tobit regression model, the DEA VRS technical efficient score could be improved through GDP per capita and social capital. From policy perspective, to promote economic growth policy makers should consider national systems of entrepreneurship as their priority so that entrepreneurs can allocate resources in the economy effectively.

Suggested Citation

  • Nishat Tasnim & Munshi Naser Ibne Afzal, 2018. "An empirical investigation of country level efficiency and national systems of entrepreneurship using Data Envelopment Analysis (DEA) and the TOBIT model," Journal of Global Entrepreneurship Research, Springer;UNESCO Chair in Entrepreneurship, vol. 8(1), pages 1-17, December.
    • Handle: RePEc:spr:jglont:v:8:y:2018:i:1:d:10.1186_s40497-018-0138-y
    DOI: 10.1186/s40497-018-0138-y
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    Cited by:

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    2. Svetlana V. Ratner & Svetlana A. Balashova & Andrey V. Lychev, 2022. "The Efficiency of National Innovation Systems in Post-Soviet Countries: DEA-Based Approach," Mathematics, MDPI, vol. 10(19), pages 1-23, October.
    3. Ebrahim Bonyadi & Lida Sarreshtehdari, 2021. "The Global Entrepreneurship Index (GEI): a critical review," Journal of Global Entrepreneurship Research, Springer;UNESCO Chair in Entrepreneurship, vol. 11(1), pages 469-488, December.
    4. Sehoon Kim, 2022. "A Global Entrepreneurship Efficiency Benchmarking and Comparison Study based on National Systems of Entrepreneurship and Early-Stage Business: A Data Envelopment Analysis Approach," SAGE Open, , vol. 12(3), pages 21582440221, September.
    5. Jorge Antunes & Goodness C. Aye & Rangan Gupta & Peter Wanke & Yong Tan, 2020. "Endogenous Long-Term Productivity Performance in Advanced Countries: A Novel Two-Dimensional Fuzzy-Monte Carlo Approach," Working Papers 2020111, University of Pretoria, Department of Economics.
    6. Mohamed Mehdi Jelassi & Ezzeddine Delhoumi, 2021. "What explains the technical efficiency of banks in Tunisia? Evidence from a two-stage data envelopment analysis," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-26, December.

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