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Institutions and Growth: a GMM/IV Panel VAR Approach

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  • Carlos Góes

Abstract

Both sides of the institutions and growth debate have resorted largely to microeconometric techniques in testing hypotheses. In this paper, I build a panel structural vector autoregression (SVAR) model for a short panel of 119 countries over 10 years and find support for the institutions hypothesis. Controlling for individual fixed effects, I find that exogenous shocks to a proxy for institutional quality have a positive and statistically significant effect on GDP per capita. On average, a 1 percent shock in institutional quality leads to a peak 1.7 percent increase in GDP per capita after six years. Results are robust to using a different proxy for institutional quality. There are different dynamics for advanced economies and developing countries. This suggests diminishing returns to institutional quality improvements.

Suggested Citation

  • Carlos Góes, 2015. "Institutions and Growth: a GMM/IV Panel VAR Approach," IMF Working Papers 2015/174, International Monetary Fund.
  • Handle: RePEc:imf:imfwpa:2015/174
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    Cited by:

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    2. Arvin, Mak B. & Pradhan, Rudra P. & Nair, Mahendhiran S., 2021. "Are there links between institutional quality, government expenditure, tax revenue and economic growth? Evidence from low-income and lower middle-income countries," Economic Analysis and Policy, Elsevier, vol. 70(C), pages 468-489.
    3. Mittal, Amit & Garg, Ajay Kumar, 2021. "Bank stocks inform higher growth—A System GMM analysis of ten emerging markets in Asia," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 210-220.
    4. James E. Payne & James W. Saunoris & Saban Nazlioglu & Cagin Karul, 2023. "The convergence dynamics of economic freedom across U.S. states," Southern Economic Journal, John Wiley & Sons, vol. 89(4), pages 1216-1241, April.
    5. Mittal, Amit & Garg, Ajay Kumar, 2018. "Bank stocks inform higher growth – A System GMM analysis of ten emerging markets in Asia," MPRA Paper 98253, University Library of Munich, Germany.
    6. Adams, Samuel & Klobodu, Edem Kwame Mensah & Opoku, Eric Evans Osei, 2016. "Energy consumption, political regime and economic growth in sub-Saharan Africa," Energy Policy, Elsevier, vol. 96(C), pages 36-44.
    7. Abdikarim Bashir Jama, 2020. "The Effect of Institutional Quality on Export performance of Middle East & North-Africa Region," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 4(1), pages 14-20, January.
    8. Steve Loris Gui-Diby & Saskia Mösle, 2017. "Governance and development outcomes: re-assessing the two-way causality," MPDD Working Paper Series WP/17/09, United Nations Economic and Social Commission for Asia and the Pacific (ESCAP).
    9. Alimov, Behzod, 2022. "The dynamic effects of debt and equity inflows: Evidence from emerging and developing countries," The Journal of Economic Asymmetries, Elsevier, vol. 26(C).
    10. Hao Liu & Weilun Huang, 2022. "Sustainable Financing and Financial Risk Management of Financial Institutions—Case Study on Chinese Banks," Sustainability, MDPI, vol. 14(15), pages 1-18, August.
    11. Dirks, Maximilian & Schmidt, Torsten, 2023. "The relationship between political instability and economic growth in advanced economies: Empirical evidence from a panel VAR and a dynamic panel FE-IV analysis," Ruhr Economic Papers 1000, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    12. Nana, Ibrahim & Tabe-Ojong, Martin Paul, 2023. "Evolution of Global Value Chains Participation and Economic Growth in Africa," Sustainable Global Supply Chains Discussion Papers 5, Research Network Sustainable Global Supply Chains.

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    More about this item

    Keywords

    WP; time series; Institutions; Panel VAR; Economic Development; EFW index; index AJR; estimation sample; expropriation index; endogenous variable; Estimation techniques; Vector autoregression; Structural vector autoregression; Personal income;
    All these keywords.

    JEL classification:

    • O43 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Institutions and Growth
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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