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A Bayesian Latent Variable Mixture Model for Filtering Firm Profit Rate

Gregor Semieniuk and Ellis Scharfenaker

No 2014-1, SCEPA working paper series. SCEPA's main areas of research are macroeconomic policy, inequality and poverty, and globalization. from Schwartz Center for Economic Policy Analysis (SCEPA), The New School

Abstract: By using Bayesian Markov chain Monte Carlo methods we select the proper subset of competitive firms and find striking evidence for Laplace shaped firm profit rate distributions. Our approach enables us to extract more information from data than previous research. We filter US firm-level data into signal and noise distributions by Gibbs-sampling from a latent variable mixture distribution, extracting a sharply peaked, negatively skewed Laplace-type profit rate distribution. A Bayesian change point analysis yields the subset of large firms with symmetric and stationary Laplace distributed profit rates, adding to the evidence for statistical equilibrium at the economy wide and sectoral levels.

Keywords: Firm competition; Laplace distribution; Gibbs sampler; Profit rate; Statistical equilibrium (search for similar items in EconPapers)
JEL-codes: C15 D20 E10 L11 (search for similar items in EconPapers)
Pages: 36 pages
Date: 2014-02
New Economics Papers: this item is included in nep-ecm, nep-mac and nep-ore
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