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Plant Life Cycle and Aggregate Employment Dynamics

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  • Min Ouyang

    (Department of Economics, University of California-Irvine)

Abstract

Past empirical studies have repeatedly found the link between plant life cycle and aggregate employment dynamics: cross-section aggregate employment dynamics differ significantly by plant age. Interestingly, the dynamics of plant-level productivity distribution also display a strong age pattern. This paper develops a model of plant life cycle with demand fluctuations, to capture both of these empirical regularities. We model plants to differ by vintage, and an idiosyncratic component that is not directly observable, but can be learned over time. We show that this model, developed to match the observed dynamics of plant-level productivity distribution, introduces two driving forces for job flows: learning and creative destruction. The resulting job flows can match, both qualitatively and quantitatively, the differences between young and old plants in their job-flow magnitude and cyclical responses observed in the U.S. manufacturing sector.

Suggested Citation

  • Min Ouyang, 2006. "Plant Life Cycle and Aggregate Employment Dynamics," Working Papers 050632, University of California-Irvine, Department of Economics.
    • Handle: RePEc:irv:wpaper:050632
    as

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    File URL: https://www.economics.uci.edu/files/docs/workingpapers/2005-06/Ouyang-32.pdf
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    References listed on IDEAS

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    More about this item

    Keywords

    Plant life cycle; Employment dynamics; Heterogeneous employers; Job creation; Job destruction; Productivity dynamics; Demand fluctuations;
    All these keywords.

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • L16 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Industrial Organization and Macroeconomics; Macroeconomic Industrial Structure
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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