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

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 di erent ways { weak and strong { it may a ect 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 E ects 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.