Spatial autoregressive spillovers vs unobserved common factors models. A panel data analysis of international technology diffusion

Cem Ertur and Antonio Musolesi ()

No 2012/9, INRA UMR CESAER Working Papers from INRA UMR CESAER, Centre d'’Economie et Sociologie appliquées à l'’Agriculture et aux Espaces Ruraux

Abstract: This paper provides an econometric examination of geographic R&D spillovers among countries by focusing on the issue of cross-sectional dependence. By applying several unit root tests, we show that when the number of lags of the autoregressive component of augmented Dickey Fuller test-type speci…cations or the number of common factors is estimated in a model selection framework, the variables (total factor productivity and the R&D capital stocks) appear to be stationary. Then, we estimate the model using two complementary approaches, focusing on generalised spatial autoregression and unobserved common correlated factors. These approaches account for different types of cross-sectional dependence and are related to the notions of weak and strong cross-sectional dependence recently developed in the literature.

Keywords: Panel data; Cross-section correlation; Spatial models; Factor models; Unit root (search for similar items in EconPapers)
JEL-codes: C23 C5 F0 O3 (search for similar items in EconPapers)
Pages: 37
Date: 2012-12-19
New Economics Papers: this item is included in nep-geo, nep-ino and nep-ure
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Citations: View citations in EconPapers (2)

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