A New Approach to Identifying the Real Effects of Uncertainty Shocks

Minchul Shin and Molin Zhong

No 2016-040, Finance and Economics Discussion Series from Board of Governors of the Federal Reserve System (U.S.)

Abstract: This paper proposes a multivariate stochastic volatility-in-vector autoregression model called the conditional autoregressive inverse Wishart-in-VAR (CAIW-in-VAR) model as a framework for studying the real effects of uncertainty shocks. We make three contributions to the literature. First, the uncertainty shocks we analyze are estimated directly from macroeconomic data so they are associated with changes in the volatility of the shocks hitting the macroeconomy. Second, we advance a new approach to identify uncertainty shocks by placing limited economic restrictions on the first and second moment responses to these shocks. Third, we consider an extension of the sign restrictions methodology of Uhlig (2005) to uncertainty shocks. To illustrate our methods, we ask what is the role of financial markets in transmitting uncertainty shocks to the real economy? We find evidence that an increase in uncertainty leads to a decline in industrial production only if associated with a deterioration in financial conditions.

Keywords: Multivariate stochastic volatility; Uncertainty; Vector autoregression; Volatility-in-mean; Wishart process (search for similar items in EconPapers)
JEL-codes: C11 C32 E32 (search for similar items in EconPapers)
Pages: 55 pages
Date: 2016-04-25
New Economics Papers: this item is included in nep-ecm, nep-pr~ and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (20)

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Related works:
Journal Article: A New Approach to Identifying the Real Effects of Uncertainty Shocks (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:fip:fedgfe:2016-40

DOI: 10.17016/FEDS.2016.040

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