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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, Hou Wang

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
Language
eng
Literary Form
non fiction
Physical Description
1 online resource (35 p.)
Form Of Item
online
Isbn
9781498301350

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