Modelling smooth and uneven cross-sectoral growth patterns : An identification problem
Authors: Mauro Napoletano, Andrea Roventini and Sandro Sapio
Economics Bulletin (2006)
This paper shows that the available stylized facts on productivity dynamics, such as persistent cross-sectoral heterogeneity, do not allow to solve an identification problem regarding the impact of common drivers-such as General Purpose Technologies (GPTs)-on economic growth. The evidence of persistently heterogeneous productivity performances is consistent both with a GPT-driven model, and with a model characterized by purely independent and idiosyncratic sectoral dynamics. These results are obtained within a simple theoretical framework, and illustrated with reference to measures of concentration of the sectoral contributions to aggregate total factor productivity growth.