Mauro Napoletano () (Chair of Systems Design, ETH Zurich, 8092 Zurich, Switzerland, and Sant'Anna School of Advanced Studies, Pisa, Italy) Andrea Roventini () (University of Modena and Reggio Emilia, Italy, and Sant'Anna School of Advanced Studies, Pisa, Italy) Sandro Sapio () (Sant'Anna School of Advanced Studies, Pisa, Italy)
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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.
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Article provided by Economics Bulletin in its journal Economics Bulletin.
Find related papers by JEL classification: O4 - Economic Development, Technological Change, and Growth - - Economic Growth and Aggregate Productivity D2 - Microeconomics - - Production and Organizations
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