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161223 ||| eng |
| 020 |
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|a 9781498348645
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| 100 |
1 |
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|a Laseen, Stefan
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| 245 |
0 |
0 |
|a Did the Global Financial Crisis Break the U.S. Phillips Curve?
|c Stefan Laseen, Marzie Taheri Sanjani
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| 260 |
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|a Washington, D.C.
|b International Monetary Fund
|c 2016
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| 300 |
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|a 42 pages
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| 651 |
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4 |
|a United States
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| 653 |
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|a Economic & financial crises & disasters
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| 653 |
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|a Inflation
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| 653 |
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|a Labour
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| 653 |
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|a Financial crises
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| 653 |
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|a Deflation
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| 653 |
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|a Unemployment: Models, Duration, Incidence, and Job Search
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| 653 |
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|a Cost
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| 653 |
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|a Capital and Total Factor Productivity
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| 653 |
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|a Production
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| 653 |
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|a Industrial productivity
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| 653 |
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|a Unemployment
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| 653 |
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|a Total factor productivity
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| 653 |
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|a Labor
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| 653 |
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|a Model Construction and Estimation
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| 653 |
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|a Global Financial Crisis, 2008-2009
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| 653 |
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|a Price Level
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| 653 |
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|a Cycles
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| 653 |
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|a Global financial crisis of 2008-2009
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| 653 |
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|a Prices
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| 653 |
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|a Macroeconomics
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| 653 |
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|a Business Fluctuations
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| 653 |
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|a Capacity
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| 653 |
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|a Unemployment rate
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| 653 |
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|a Monetary Policy
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| 653 |
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|a Income economics
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| 653 |
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|a Production and Operations Management
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| 653 |
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|a Financial Crises
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| 700 |
1 |
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|a Taheri Sanjani, Marzie
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b IMF
|a International Monetary Fund
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| 490 |
0 |
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|a IMF Working Papers
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| 028 |
5 |
0 |
|a 10.5089/9781498348645.001
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| 856 |
4 |
0 |
|u https://elibrary.imf.org/view/journals/001/2016/126/001.2016.issue-126-en.xml?cid=44049-com-dsp-marc
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 330
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| 520 |
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|a Inflation dynamics, as well as its interaction with unemployment, have been puzzling since the Global Financial Crisis (GFC). In this empirical paper, we use multivariate, possibly time-varying, time-series models and show that changes in shocks are a more salient feature of the data than changes in coefficients. Hence, the GFC did not break the Phillips curve. By estimating variations of a regime-switching model, we show that allowing for regime switching solely in coefficients of the policy rule would maximize the fit. Additionally, using a data-rich reduced-form model we compute conditional forecast scenarios. We show that financial and external variables have the highest forecasting power for inflation and unemployment, post-GFC.
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