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Measuring world governance: revisiting the institutions hypothesis

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  • Mehmet Pinar

Abstract

We consider the weighting scheme that results in a best-case scenario in the construction of the world governance indicators (WGIs), a proxy of institutional quality. To perform that, we use an approach that relies on consistent tests for stochastic dominance efficiency of a given index with respect to all possible indices constructed from a set of individual components. The test statistics and the estimators are computed using mixed integer programming methods. The results show that the equally weighted (fixed weights) composite WGI index is not the best-case scenario and that governance indicators at different years should be weighted differently. Furthermore, we revisit the institutions hypothesis in the empirical growth literature, where institutional quality is the main determinant of long-term development. We find that not only do institutions matter for economic development but also geography and macroeconomic policies do affect economic development directly. Copyright Springer-Verlag Berlin Heidelberg 2015

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  • Mehmet Pinar, 2015. "Measuring world governance: revisiting the institutions hypothesis," Empirical Economics, Springer, vol. 48(2), pages 747-778, March.
    • Handle: RePEc:spr:empeco:v:48:y:2015:i:2:p:747-778
    DOI: 10.1007/s00181-013-0796-0
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    Cited by:

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    2. Mohammad Salam Ibrahim AlShiab & Husam-Aldin N. Al-Malkawi & Abdelmounaim Lahrech, 2020. "Revisiting the Relationship between Governance Quality and Economic Growth," International Journal of Economics and Financial Issues, Econjournals, vol. 10(4), pages 54-63.
    3. Mehmet Pinar & Thanasis Stengos & Nikolas Topaloglou, 2022. "Stochastic dominance spanning and augmenting the human development index with institutional quality," Annals of Operations Research, Springer, vol. 315(1), pages 341-369, August.
    4. Tahsin Mehdi, 2019. "Stochastic Dominance Approach to OECD’s Better Life Index," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 143(3), pages 917-954, June.
    5. Asiedu, Edward & Sadekla, Sylvester S. & Bokpin, Godfred A., 2020. "Aid to Africa’s agriculture towards building physical capital: Empirical evidence and implications for post-COVID-19 food insecurity," World Development Perspectives, Elsevier, vol. 20(C).
    6. Jordi Pons-Novell & Montserrat Guillen, 2022. "The Autonomous Capacity of the Elderly Population in Spain for Shopping and Preparing Meals," IJERPH, MDPI, vol. 19(22), pages 1-16, November.
    7. Giovanni Bernardo & Irene Brunetti & Mehmet Pinar & Thanasis Stengos, 2021. "Measuring the presence of organized crime across Italian provinces: a sensitivity analysis," European Journal of Law and Economics, Springer, vol. 51(1), pages 31-95, February.
    8. Nicholas Apergis & Mehmet Pinar, 2023. "Corruption and partisan polarization: evidence from the European Union," Empirical Economics, Springer, vol. 64(1), pages 277-301, January.
    9. Zhang, Jianhong, 2022. "Liability of emergingness and EMNEs’ cross-border acquisition completion: A legitimacy perspective," International Business Review, Elsevier, vol. 31(2).
    10. Tahsin Mehdi, 2019. "Stochastic Dominance Approach to Measuring Child Development," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 12(5), pages 1567-1588, October.
    11. Pinar, Mehmet & Volkan, Engin, 2018. "Institutions and information flows, and their effect on capital flows," Information Economics and Policy, Elsevier, vol. 43(C), pages 34-47.
    12. He, Xinming & Zhang, Jianhong, 2018. "Emerging market MNCs' cross-border acquisition completion: Institutional image and strategies," Journal of Business Research, Elsevier, vol. 93(C), pages 139-150.

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    More about this item

    Keywords

    World governance indicators; Institutions; Geography; Openness; Nonparametric stochastic dominance; Mixed integer programming; C12; C13; C14; C15; O1; O57;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • O1 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development
    • O57 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Comparative Studies of Countries

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