This paper investigates the usefulness of the semi-parametric spatial vector autoregressive approach proposed by Chen and Conley (JE 2001) in modelling the growth rates of Total Factor Productivity (TFP) for a large cross-section of U.S. manufacturing industries. The magnitude of the interactions of TFP's across sectors is of great economic significance as it gives an indication of the importance of Marshallian externalities which are a necessary ingredients in many endogenous growth models. In the approach by Chen and Conley the magnitude of the effect of one sector has on the other sectors depends on the economic distance between them. Both the dependence of the coefficients of the VAR and of the covariances of the error terms on the distances between sectors is modelled in a semi-parametric way using cardinal B-splines. Irrespective whether distances are computed from factor shares or input-output tables, most of the interaction seems to be captured by the covariances whereas lagged TFP growth rates and/or lagged growth rates of capital intensities have only a negligible effect.
sectoral TFP, cross-section externalities, spatial VAR
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