Estimating and accounting for the output gap with large Bayesian vector autoregressions

James Morley and Benjamin Wong

CAMA Working Papers from Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University

Abstract: We demonstrate how Bayesian shrinkage can address problems with utilizing large information sets to calculate trend and cycle via a multivariate Beveridge-Nelson (BN) decomposition. We illustrate our approach by estimating the U.S. output gap with large Bayesian vector autoregressions that include up to 138 variables. Because the BN trend and cycle are linear functions of historical forecast errors, we are also able to account for the estimated output gap in terms of different sources of information, as well as particular underlying structural shocks given identification restrictions. Our empirical analysis suggests that, in addition to output growth, the unemployment rate, CPI inflation, and, to a lesser extent, housing starts, consumption, stock prices, real M1, and the federal funds rate are important conditioning variables for estimating the U.S. output gap, with estimates largely robust to incorporating additional variables. Using standard identification restrictions, we find that the role of monetary policy shocks in driving the output gap is small, while oil price shocks explain about 10% of the variance over different horizons.

Keywords: Beveridge-Nelson decomposition; output gap; Bayesian estimation; multivariate information (search for similar items in EconPapers)
JEL-codes: C18 E17 E32 (search for similar items in EconPapers)
Pages: 43 pages
Date: 2017-07
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-mac and nep-ore
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Citations: View citations in EconPapers (2)

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Related works:
Journal Article: Estimating and accounting for the output gap with large Bayesian vector autoregressions (2020)
Working Paper: Estimating and Accounting for the Output Gap with Large Bayesian Vector Autoregressions (2019)
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Persistent link: https://EconPapers.repec.org/RePEc:een:camaaa:2017-46

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