Identifying Ambiguity Shocks in Business Cycle Models Using Survey Data

Working Paper: NBER ID: w22225

Authors: Anmol Bhandari; Jaroslav Borovika; Paul Ho

Abstract: We develop a framework to analyze economies with agents facing time-varying concerns for model misspecification. These concerns lead agents to interpret economic outcomes and make decisions through the lens of a pessimistically biased 'worst-case' model. We combine survey data and implied theoretical restrictions on the relative magnitudes and comovement of forecast biases across macroeconomic variables to identify ambiguity shocks as exogenous fluctuations in the worst-case model. Our solution method delivers tractable linear approximations that preserve the effects of time-varying ambiguity concerns and permit estimation using standard Bayesian techniques. Applying our framework to an estimated New-Keynesian business cycle model with frictional labor markets, we find that ambiguity shocks explain a substantial portion of the variation in labor market quantities.

Keywords: ambiguity shocks; business cycle; survey data; labor market; expectations

JEL Codes: C11; C63; D81; D84; E24; E32


Causal Claims Network Graph

Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.


Causal Claims

CauseEffect
ambiguity shocks (D80)labor market quantities (J20)
ambiguity shocks (D80)unemployment (J64)
ambiguity shocks (D80)GDP growth (O49)
increased ambiguity (D80)pessimistic evaluation of future economic conditions (E66)
pessimistic evaluation of future economic conditions (E66)match creation in the labor market (J68)
match creation in the labor market (J68)unemployment (J64)
ambiguity concerns (D84)risky component of the stochastic discount factor (D15)
ambiguity concerns (D84)hiring and employment rates (J63)
ambiguity shocks (D80)contractionary effects (H31)

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