Learning-by-Doing and Productivity Dynamics in Manufacturing Industries
AbstractThis paper estimates a structural model of learning-by-doing. Treating production experience as a state variable, this paper provides estimates of the structural parameters obtained from the first order conditions arising from the plant’s maximization problem. Estimates are provided using data on 4-digit manufacturing industries and plant-level observations. Using aggregate industry data, the results indicate that estimated learning rates might be considerably lower than previous estimates. The results also reveal considerable variation in estimated learning rates, across broad industry groups, at both the plant-level and the 4-digit industry level. This implies that using results from existing studies that focus upon specific, narrowly defined industries or firms, may lead to misleading conclusions concerning the widespread importance of learning-by-doing for generating productivity dynamics within the manufacturing industry
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Bibliographic InfoPaper provided by The University of Melbourne in its series Department of Economics - Working Papers Series with number 1032.
Length: x pages
Date of creation: 2008
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More information through EDIRC
Production Experience; Learning-by-Doing; Structural Estimation;
Find related papers by JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
- L23 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Organization of Production
- L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2008-11-25 (All new papers)
- NEP-BEC-2008-11-25 (Business Economics)
- NEP-EFF-2008-11-25 (Efficiency & Productivity)
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