Multivariate Filter Estimation of Potential Output for the United States: An Extension with Labor Market Hysteresis

Ali Alichi, Hayk Avetisyan, Douglas Laxton, Shalva Mkhatrishvili, Armen Nurbekyan, Lusine Torosyan and Hou Wang

No 2019/035, IMF Working Papers from International Monetary Fund

Abstract: This paper extends the multivariate filter approach of estimating potential output developed by Alichi and others (2018) to incorporate labor market hysteresis. This extension captures the idea that long and deep recessions (expansions) cause persistent damage (improvement) to the labor market, thereby reducing (increasing) potential output. Applying the model to U.S. data results in significantly smaller estimates of output gaps, and higher estimates of the NAIRU, after the global financial crisis, compared to estimates without hysteresis. The smaller output gaps partly explain the absence of persistent deflation despite the slow recovery during 2010-2017. Going forward, if strong growth performance continues well beyond 2018, hysteresis is expected to result in a structural improvement in growth and employment.

Keywords: WP; NAIRU; Macroeconomic Modeling; Potential Output; output gap shock; unemployment gap; output gap estimate; Volcker recession; inflation target shock; output gap in the with-hysteresis model; inflation expectation; Output gap; Labor markets; Unemployment rate; Inflation (search for similar items in EconPapers)
Pages: 35
Date: 2019-02-19
New Economics Papers: this item is included in nep-ets and nep-mac
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Citations: View citations in EconPapers (6)

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Working Paper: Multivariate Filter Estimation of Potential Output for the United States: An Extension with Labor Market Hysteresis (2019)
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