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Sectoral Differences in Labor Productivity Growth: Estimation and Modeling

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  • Roberto Roson

Abstract

This study provides some empirical evidence and quantification of differences in labor productivity among industries and countries. Using a recently available data base of value added per worker, country and time fixed effects are estimated first for various industries. Results are subsequently elaborated, to identify some time trends and sectoral profiles by country, which are in turn employed in a cluster analysis, summarizing some salient characteristics of industrial labor productivity in different economies. The empirical exercise is motivated by the possible employment of its findings in the construction of long-run economic growth scenarios, by means of Computable General Equilibrium (CGE) models. It is found that: (a) Manufacturing is normally the fastest growing sector and its performance is strongly correlated with the aggregate productivity growth; (b) differences in the rates of agricultural productivity gains are relatively minor; (c) slow-growing countries are characterized by slow-growing Services.

Suggested Citation

  • Roberto Roson, 2019. "Sectoral Differences in Labor Productivity Growth: Estimation and Modeling," Research in Applied Economics, Macrothink Institute, vol. 11(1), pages 1-8, March.
    • Handle: RePEc:mth:raee88:v:11:y:2019:i:1:p:1-8
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    File URL: http://www.macrothink.org/journal/index.php/rae/article/view/14074
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    References listed on IDEAS

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    Cited by:

    1. Wolfgang Britz & Roberto Roson, 2019. "G-RDEM: A GTAP-Based Recursive Dynamic CGE Model for Long-Term Baseline Generation and Analysis," Journal of Global Economic Analysis, Center for Global Trade Analysis, Department of Agricultural Economics, Purdue University, vol. 4(1), pages 50-96, June.

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