We show that the volatility puzzle in labor economics (Shimer, 2005) stems from the inability of technology shocks to generate sufficient volatility of firm value. We introduce non-fundamental shocks to firm value, akin to bubbles, into an otherwise standard searchand-matching model. When calibrated to stock market data, stochastic bubbles significantly improve the ability of the matching model to quantitatively explain the volatility of the US labor market. An extension with multiple sectors improves the persistence of simulated labor market variables. (C) 2019 Published by Elsevier B.V.
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Univ Calif Riverside, Dept Econ, Sproul Hall 3132, Riverside, CA 92521 USAUniv Calif Riverside, Dept Econ, Sproul Hall 3132, Riverside, CA 92521 USA
机构:
George Mason Univ, Dept Computat & Data Sci, Fairfax, VA 22030 USA
Santa Fe Inst, Santa Fe, NM 87501 USAGeorge Mason Univ, Dept Computat & Data Sci, Fairfax, VA 22030 USA
Axtell, Robert L.
Guerrero, Omar A.
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UCL, Dept Econ, London, England
Alan Turing Inst, London, England
Aalto Univ, Dept Comp Sci, Espoo, FinlandGeorge Mason Univ, Dept Computat & Data Sci, Fairfax, VA 22030 USA
Guerrero, Omar A.
Lopez, Eduardo
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Santa Fe Inst, Santa Fe, NM 87501 USAGeorge Mason Univ, Dept Computat & Data Sci, Fairfax, VA 22030 USA