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The economics of state fragmentation

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  • Jo Reynaerts
  • Jakob Vanschoonbeek

Abstract

This paper provides empirical evidence that declaring independence significantly lowers per capita GDP based on a large panel of countries covering the period 1950-2013. To do so, we rely on a semi-parametric identification strategy that controls for the confounding effects of past GDP dynamics, anticipation effects, unobserved heterogeneity, model uncertainty and effect heterogeneity. Our baseline results indicate that declaring independence reduces per capita GDP by around 20% in the long run. We subsequently propose a novel triple-differential procedure to demonstrate the stability of these results. Another methodological novelty consists of the development of a two-step estimator to shed some light on the primary channels driving our results. We find robust evidence that the adverse effects of independence increase in the extent of surface area loss, pointing to the presence of economies of scale, but that they are mitigated when newly independent states liberalize their trade regime or use their new-found political autonomy to democratize.

Suggested Citation

  • Jo Reynaerts & Jakob Vanschoonbeek, 2016. "The economics of state fragmentation," Working Papers of VIVES - Research Centre for Regional Economics 547244, KU Leuven, Faculty of Economics and Business (FEB), VIVES - Research Centre for Regional Economics.
  • Handle: RePEc:ete:vivwps:547244
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    File URL: https://lirias.kuleuven.be/retrieve/398341
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    Cited by:

    1. Dieppe,Alistair Matthew & Kilic Celik,Sinem & Okou,Cedric Iltis Finafa, 2020. "Implications of Major Adverse Events on Productivity," Policy Research Working Paper Series 9411, The World Bank.
    2. Vincenzo Galasso, 2020. "Market Reactions to Quest for Decentralization and Independence: Evidence from Catalonia," CESifo Working Paper Series 8254, CESifo.

    More about this item

    Keywords

    Independence dividend; panel data; dynamic model; synthetic control method; difference-in-difference; triple-difference; two-step approach;
    All these keywords.

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