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

Author/Editor:

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

Publication Date:

February 19, 2019

Electronic Access:

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Disclaimer: IMF Working Papers describe research in progress by the author(s) and are published to elicit comments and to encourage debate. The views expressed in IMF Working Papers are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management.

Summary:

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.

Series:

Working Paper No. 2019/035

Subject:

English

Publication Date:

February 19, 2019

ISBN/ISSN:

9781484398067/1018-5941

Stock No:

WPIEA2019035

Pages:

35

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