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The Contribution of Economic Geography to GDP Per Capita

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  • Hervé Boulhol
  • Alain de Serres
  • Margit Molnár

Abstract

This paper examines how much of the dispersion in economic performance across OECD countries can be accounted for by economic geography factors. More specifically, two aspects of economic geography are examined, namely the proximity to areas of dense economic activity and endowments in natural resources. To do so, various indicators of distance to markets, transportation costs, and dependence on natural resources are added as determinants in an augmented Solow model, which serves as a benchmark. Three measures of distance to markets are found to have a statistically significant effect on GDP per capita: the sum of bilateral distances, market potential and the weighted sum of market access and supplier access. And the estimated economic impact is far from negligible. The reduced access to markets relative to the OECD average could contribute negatively to GDP per capita by as much as 10% in Australia and New Zealand. Conversely, a favourable impact of around 6-7% of GDP is found in the case of two centrally-located countries: Belgium and the Netherlands. Endowments in natural resources are also found to have a significant positive effect on GDP per capita, suggesting that OECD countries have, on average, escaped the natural resource curse or severe forms of the Dutch disease. The paper provides also some tentative evidence that spending on R&D and human capital might have a stronger effect on GDP per capita in countries with a higher degree of urban concentration. La contribution de l'économie géographique au PIB par tête Ce papier analyse la contribution des facteurs géographiques à la dispersion des performances économiques entre pays de l’OCDE. Plus particulièrement, deux aspects de l’économie géographique sont étudiés : la proximité de zones denses d’activités économiques et les dotations en ressources naturelles. Pour se faire, divers indicateurs de distance par rapport aux marchés, de coûts de transports, et de dépendance envers les ressources naturelles sont ajoutés comme déterminants dans un modèle de Solow augmenté, utilisé comme référence. Trois mesures de distance sont estimées avoir un effet significatif sur le PIB par habitant : la somme des distances bilatérales, le potentiel de marché et la somme pondérée de l’accès aux marchés et de l’accès aux fournisseurs. De plus, l’impact économique estimé est loin d’être négligeable. L’éloignement par rapport aux marchés pourrait pénaliser l’Australie et la Nouvelle Zélande, par rapport à la moyenne des pays de l’OCDE, à hauteur d’environ 10% de PIB. A l’inverse, la Belgique et les Pays Bas bénéficieraient de leur position centrale pour environ 6-7% de PIB. Les dotations en ressources naturelles sont estimées avoir un effet positif significatif sur le PIB par habitant, suggérant que les pays de l’OCDE ont, en moyenne, échappé au fléau des ressources naturelles ou aux formes sévères de la maladie hollandaise. Des premières indications suggèrent également que les dépenses en R&D et en capital humain peuvent avoir un effet plus fort sur le PIB par tête dans les pays ayant un fort degré de concentration urbaine.

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File URL: http://dx.doi.org/10.1787/242216186836
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Bibliographic Info

Paper provided by OECD Publishing in its series OECD Economics Department Working Papers with number 602.

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Date of creation: 14 Apr 2008
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Handle: RePEc:oec:ecoaaa:602-en

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Related research

Keywords: transport costs; GDP-per-capita; natural resources; distance; economic geography; distance; économie géographique; ressources naturelles; PIB par tête; coûts de transport;

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Cited by:
  1. Ahrend, Rüdiger, 2012. "Understanding Russian regions’ economic performance during periods of decline and growth—An extreme bound analysis approach," Economic Systems, Elsevier, vol. 36(3), pages 426-443.
  2. J.A. Bikker, 2009. "An extended gravity model with substitution applied to international trade," Working Papers 09-17, Utrecht School of Economics.
  3. Andrea Elekes, 2011. "Cohesion and/or Growth?," Public Finance Quarterly, State Audit Office of Hungary, vol. 56(1), pages 108-124.
  4. Romain Bouis & Romain Duval & Fabrice Murtin, 2011. "The Policy and Institutional Drivers of Economic Growth Across OECD and Non-OECD Economies: New Evidence from Growth Regressions," OECD Economics Department Working Papers 843, OECD Publishing.
  5. Christophe Gouel & Nina Kousnetzoff & Hassan Salman, 2008. "Commerce international et transports : tendances du passe et prospective 2020," Working Papers 2008-28, CEPII research center.
  6. Clovis Kerdrain & Isabell Koske & Isabelle Wanner, 2011. "Current Account Imbalances: can Structural Reforms Help to Reduce Them?," OECD Journal: Economic Studies, OECD Publishing, vol. 2011(1), pages 1-44.
  7. Clovis Kerdrain & Isabell Koske & Isabelle Wanner, 2010. "The Impact of Structural Policies on Saving, Investment and Current Accounts," OECD Economics Department Working Papers 815, OECD Publishing.
  8. Sebastian Barnes & Romain Bouis & Philippe Briard & Sean Dougherty & Mehmet Eris, 2013. "The GDP Impact of Reform: A Simple Simulation Framework," OECD Economics Department Working Papers 834, OECD Publishing.

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