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Institutions and growth: A GMM/IV Panel VAR approach



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% shock in institutional quality leads to a peak 1.7% 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

  • Góes, Carlos, 2016. "Institutions and growth: A GMM/IV Panel VAR approach," Economics Letters, Elsevier, vol. 138(C), pages 85-91.
  • Handle: RePEc:eee:ecolet:v:138:y:2016:i:c:p:85-91 DOI: 10.1016/j.econlet.2015.11.024

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    References listed on IDEAS

    1. Nathan Nunn & Diego Puga, 2012. "Ruggedness: The Blessing of Bad Geography in Africa," The Review of Economics and Statistics, MIT Press, vol. 94(1), pages 20-36, February.
    2. Holtz-Eakin, Douglas & Newey, Whitney & Rosen, Harvey S, 1989. "The Revenues-Expenditures Nexus: Evidence from Local Government Data," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 30(2), pages 415-429, May.
    3. Canova, Fabio & Ciccarelli, Matteo, 2013. "Panel Vector Autoregressive Models: A Survey," CEPR Discussion Papers 9380, C.E.P.R. Discussion Papers.
    4. repec:spr:portec:v:1:y:2002:i:2:d:10.1007_s10258-002-0009-9 is not listed on IDEAS
    5. A. Chong & C. Calderón, 2000. "Causality and Feedback Between Institutional Measures and Economic Growth," Economics and Politics, Wiley Blackwell, vol. 12(1), pages 69-81, March.
    6. Jeffrey D. Sachs, 2003. "Institutions Don't Rule: Direct Effects of Geography on Per Capita Income," NBER Working Papers 9490, National Bureau of Economic Research, Inc.
    7. Daron Acemoglu & Simon Johnson & James A. Robinson, 2001. "The Colonial Origins of Comparative Development: An Empirical Investigation," American Economic Review, American Economic Association, vol. 91(5), pages 1369-1401, December.
    8. Stephen Bond, 2002. "Dynamic panel data models: a guide to microdata methods and practice," CeMMAP working papers CWP09/02, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    9. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Oxford University Press, vol. 58(2), pages 277-297.
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    Cited by:

    1. 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.
    2. Steve Loris Gui-Diby & Saskia Mösle, "undated". "Governance and development outcomes: re-assessing the two-way causality," MPDD Working Paper Series WP/17/06, United Nations Economic and Social Commission for Asia and the Pacific (ESCAP).

    More about this item


    Institutions; Panel VAR; Economic development;

    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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