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Development Accounting with Spatial Effects


  • Wilfried Koch


Abstract The aim of this paper is to show how the spatial autocorrelation phenomenon often observed in the world distribution of income per capita, can be introduced structurally as the outcome of spillovers effects into a development accounting equation. Neglecting spatial autocorrelation potentially biases our vision of the role played by physical capital in the development process. We show that the total contribution of physical capital accounts for almost 90% of the differences between developing countries and the richest countries.

Suggested Citation

  • Wilfried Koch, 2008. "Development Accounting with Spatial Effects," Spatial Economic Analysis, Taylor & Francis Journals, vol. 3(3), pages 321-342.
  • Handle: RePEc:taf:specan:v:3:y:2008:i:3:p:321-342 DOI: 10.1080/17421770802353733

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    References listed on IDEAS

    1. Törmä, Hannu & Rutherford, Thomas, 1993. "Integrating Finnish Agriculture into EC," Research Reports 13, VATT Institute for Economic Research.
    2. Jones, Rich & Whalley, John, 1989. "A Canadian regional general equilibrium model and some applications," Journal of Urban Economics, Elsevier, vol. 25(3), pages 368-404, May.
    3. Törmä Hannu, Rutherford Thomas, Vaittinen Risto, 1995. "What Will EU Membership and the Value-Added Tax Reform Do to Finnish Food Economy? - A Computable General Equilibrium Analysis," Discussion Papers 88, VATT Institute for Economic Research.
    4. Mark D. Partridge & Dan S. Rickman, 1998. "Regional Computable General Equilibrium Modeling: A Survey and Critical Appraisal," International Regional Science Review, , vol. 21(3), pages 205-248, December.
    5. Valkonen, Tarmo, 2002. "Demographic Uncertainty and Taxes," Discussion Papers 816, The Research Institute of the Finnish Economy.
    6. Vaittinen Risto, 2004. "Trade Policies and Integration - Evaluations with CGE Models," Research Reports 109, VATT Institute for Economic Research.
    7. Matthew W. Peter & Mark Horridge & G.A.Meagher & Fazana Naqvi & B.R.Parmenter, 1996. "The Theoretical Structure of MONASH-MRF," Centre of Policy Studies/IMPACT Centre Working Papers op-85, Victoria University, Centre of Policy Studies/IMPACT Centre.
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    Cited by:

    1. Badi H. Baltagi & Bernard Fingleton & Alain Pirotte, 2014. "Estimating and Forecasting with a Dynamic Spatial Panel Data Model," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(1), pages 112-138, February.
    2. Rosa Bernadini Papalia & Silvia Bertarelli, 2013. "Identification and Estimation of Club Convergence Models with Spatial Dependence," International Journal of Urban and Regional Research, Wiley Blackwell, vol. 37(6), pages 2094-2115, November.
    3. Glass, Anthony J. & Kenjegalieva, Karligash & Sickles, Robin C., 2016. "A spatial autoregressive stochastic frontier model for panel data with asymmetric efficiency spillovers," Journal of Econometrics, Elsevier, vol. 190(2), pages 289-300.
    4. Jan Ditzen, 2014. "Economic Growth and Migration," SEEC Discussion Papers 1406, Spatial Economics and Econometrics Centre, Heriot Watt University.

    More about this item


    Development accounting; total factor productivity; spatial autocorrelation; technological interdependence; C21; 033; 040;

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models


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