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EnglishThis paper shows that the available stylized facts on productivity dynamics, such aspersistent cross-sectoral heterogeneity, do not allow to solve an identification problemregarding the impact of common drivers - such as General Purpose Technologies (GPTs) - oneconomic growth. The evidence of persistently heterogeneous productivity performances isconsistent both with a GPT-driven model, and with a model characterized by purelyindependent and idiosyncratic sectoral dynamics. These results are obtained within a simpletheoretical framework, and illustrated with reference to measures of concentration of thesectoral contributions to aggregate total factor productivity growth.
| Titolo: | Modelling Smooth and Uneven Cross-Sectoral Growth Patterns: an Identification Problem | |
| Autori: | ||
| Data di pubblicazione: | 2006 | |
| Rivista: | ||
| Abstract: | This paper shows that the available stylized facts on productivity dynamics, such aspersistent cross-sectoral heterogeneity, do not allow to solve an identification problemregarding the impact of common drivers - such as General Purpose Technologies (GPTs) - oneconomic growth. The evidence of persistently heterogeneous productivity performances isconsistent both with a GPT-driven model, and with a model characterized by purelyindependent and idiosyncratic sectoral dynamics. These results are obtained within a simpletheoretical framework, and illustrated with reference to measures of concentration of thesectoral contributions to aggregate total factor productivity growth. | |
| Handle: | http://hdl.handle.net/11367/28914 | |
| Appare nelle tipologie: | 1.1 Articolo in rivista |
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