. In the present paper dynamic panel models for productivity analysis will be analyzed. Recent years have seen a relevant increase in studies on productivity. This is partly due to rising availability of longitudinal micro-level data. This paper is an attempt to give an answer to some questions about productivity dynamics and determinants, using the large data base of company accounts constructed by Research Center of Unioncamere. In our study we investigate the distribution of labor productivity in two important Italian manufacturing sectors. A new derivation of dynamic panel model starting from a Cobb-Douglas production function has been applied in this paper to discover the underlying generating process of productivity growth and to estimate the elasticities of productivity to personnel expenditure.

Panel Data Models for Productivity Analysis / L., Grossi; Gozzi, Giorgio. - (2010), pp. 1095-1102. (Intervento presentato al convegno 19th International Conference on Computational Statistics tenutosi a Paris - France nel August 22-27, 2010).

Panel Data Models for Productivity Analysis

L. Grossi;GOZZI, Giorgio
2010-01-01

Abstract

. In the present paper dynamic panel models for productivity analysis will be analyzed. Recent years have seen a relevant increase in studies on productivity. This is partly due to rising availability of longitudinal micro-level data. This paper is an attempt to give an answer to some questions about productivity dynamics and determinants, using the large data base of company accounts constructed by Research Center of Unioncamere. In our study we investigate the distribution of labor productivity in two important Italian manufacturing sectors. A new derivation of dynamic panel model starting from a Cobb-Douglas production function has been applied in this paper to discover the underlying generating process of productivity growth and to estimate the elasticities of productivity to personnel expenditure.
2010
9783790826043
Panel Data Models for Productivity Analysis / L., Grossi; Gozzi, Giorgio. - (2010), pp. 1095-1102. (Intervento presentato al convegno 19th International Conference on Computational Statistics tenutosi a Paris - France nel August 22-27, 2010).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11381/2318283
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