Learning-by-Doing and Productivity Dynamics in Manufacturing Industries

Andrew Clarke ()

No 1032, Department of Economics - Working Papers Series from The University of Melbourne

Abstract: This 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

Keywords: Production Experience; Learning-by-Doing; Structural Estimation (search for similar items in EconPapers)
JEL-codes: C13 D21 L23 L60 (search for similar items in EconPapers)
Pages: x pages
Date: 2008
New Economics Papers: this item is included in nep-bec and nep-eff
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:mlb:wpaper:1032

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