Multivariate Filter Estimation of Potential Output for the United States : An Extension with Labor Market Hysteresis /
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, ther...
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| מחברים אחרים: | , , |
| פורמט: | כתב-עת |
| שפה: | English |
| יצא לאור: |
Washington, D.C. :
International Monetary Fund,
2019.
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| סדרה: | IMF Working Papers; Working Paper ;
No. 2019/035 |
| גישה מקוונת: | Full text available on IMF |
| סיכום: | 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. |
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| תאור פריט: | <strong>Off-Campus Access:</strong> No User ID or Password Required <strong>On-Campus Access:</strong> No User ID or Password Required |
| תיאור פיזי: | 1 online resource (35 pages) |
| פורמט: | Mode of access: Internet |
| ISSN: | 1018-5941 |
| גישה: | Electronic access restricted to authorized BRAC University faculty, staff and students |