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Nonlinear Firm Dynamics

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Abstract

This paper presents empirical evidence on the nature of idiosyncratic shocks to firms and discusses its role for firm behavior and aggregate fluctuations. We document that firm-level sales and productivity are hit by heavy-tailed shocks and follow a nonlinear stochastic process, thus departing from the canonical linear. We estimate a state-of-the-art model to flexibly capture the rich dynamics uncovered in the data and characterize the drivers of nonlinear persistence and non-Gaussian shocks. We show that these features are crucial to get empirically plausible volatility and persistence of micro-originated (granular) aggregate fluctuations.

Suggested Citation

  • Davide Melcangi & Silvia Sarpietro, 2024. "Nonlinear Firm Dynamics," Staff Reports 1088, Federal Reserve Bank of New York.
    • Handle: RePEc:fip:fednsr:97929
    DOI: 10.59576/sr.1088
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    References listed on IDEAS

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    1. Daniel Wilhelm, 2015. "Identification and estimation of nonparametric panel data regressions with measurement error," CeMMAP working papers CWP34/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. MaCurdy, Thomas E., 1982. "The use of time series processes to model the error structure of earnings in a longitudinal data analysis," Journal of Econometrics, Elsevier, vol. 18(1), pages 83-114, January.
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    Cited by:

    1. Giuseppe Berlingieri & Maarten De Ridder & Danial Lashkari & Davide Rigo, 2025. "Creative destruction through innovation bursts," CEP Discussion Papers dp2095, Centre for Economic Performance, LSE.

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    More about this item

    Keywords

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    JEL classification:

    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • E23 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Production
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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