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

36 Pages Posted: 8 Apr 2019

See all articles by Ali Alichi

Ali Alichi

International Monetary Fund (IMF)

Douglas Laxton

International Monetary Fund (IMF) - Research Department

Shalva Mkhatrishvili

Independent

Armen Nurbekyan

CBA

Lusine Torosyan

Independent

Hou Wang

International Monetary Fund (IMF)

Date Written: February 2019

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: Business cycles, Unemployment, Potential output, Capacity utilization, Production growth, Macroeconomic Modeling, output gap, NAIRU, hysteresis, potential growth, Volcker

JEL Classification: C51, E31, E52, E01, E2, Z13, D4

Suggested Citation

Alichi, Ali and Laxton, Douglas and Mkhatrishvili, Shalva and Nurbekyan, Armen and Torosyan, Lusine and Wang, Hou, Multivariate Filter Estimation of Potential Output for the United States: An Extension with Labor Market Hysteresis (February 2019). IMF Working Paper No. 19/35, Available at SSRN: https://ssrn.com/abstract=3367420

Ali Alichi (Contact Author)

International Monetary Fund (IMF) ( email )

700 19th Street, N.W.
Washington, DC 20431
United States

Douglas Laxton

International Monetary Fund (IMF) - Research Department ( email )

700 19th Street NW
Washington, DC 20431
United States

Shalva Mkhatrishvili

Independent

Armen Nurbekyan

CBA ( email )

Vazgen Sargsyan 6
Armenia

Lusine Torosyan

Independent

Hou Wang

International Monetary Fund (IMF) ( email )

700 19th Street, N.W.
Washington, DC 20431
United States

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