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Weak and Strong cross-sectional dependence: a panel data analysis of international technology diffusion

Author

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  • Cem Ertur

    (University of Orleans UMR 6221, CNRS Faculté de Droit d’Economie et de Gestion. Rue de Blois - B.P. 6739 45067 Orléans Cedex 2,France)

  • Antonio Musolesi

    (Department of Economics and Management (DEM), University of Ferrara, and SEEDS, Via Voltapaletto 11, 44100 Ferrara - Italy.)

Abstract

This paper provides an econometric examination of geographic R&D spillovers among countries by focusing on the issue of cross-sectional dependence, and in particular on the different ways – weak and strong – it may affect the model. A preliminary analysis based on the estimation of the exponent of cross-sectional correlation proposed by Bailey et al.(2013), a, provides a very clear-cut result with an estimate of a very close to unity, not only indicating the presence of strong cross-sectional correlation but also being consistent with the factor literature typically assuming that a = 1. Moreover, second generation unit roots tests suggest that while the unobserved idiosyncratic component of the variables under study may be stationary, the unobserved common factors appear to be nonstationary. Consequently, a factor structure appears to be preferable to a spatial error model and in particular the Correlated Common Effects approach is employed since, among other things, it is still valid in the more general case of nonstationary common factors. Finally, comparing the results with those obtained with a spatial model gives some insights on the possible bias occurring when allowing only for weak correlation while strong correlation is present in the data.

Suggested Citation

  • Cem Ertur & Antonio Musolesi, 2015. "Weak and Strong cross-sectional dependence: a panel data analysis of international technology diffusion," SEEDS Working Papers 1915, SEEDS, Sustainability Environmental Economics and Dynamics Studies, revised Dec 2015.
    • Handle: RePEc:srt:wpaper:1915
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    More about this item

    Keywords

    panel data; cross-sectional correlation; spatial models; factor models; unit root; international technology diffusion; geography.;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • F0 - International Economics - - General
    • O3 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights

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