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Hysteresis in Unemployment and Jobless Recoveries, Dmitry Plotnikov

Label
Hysteresis in Unemployment and Jobless Recoveries, Dmitry Plotnikov
Language
eng
Abstract
This paper develops and estimates a general equilibrium rational expectations model with search and multiple equilibria where aggregate shocks have a permanent effect on the unemployment rate. If agents' wealth decreases, the unemployment rate increases for a potentially indefinite period. This makes unemployment rate dynamics path dependent as in Blanchard and Summers (1987). I argue that this feature explains the persistence of the unemployment rate in the U.S. after the Great Recession and over the entire postwar period
Bibliography note
Includes bibliographical references
resource.governmentPublication
international or intergovernmental publication
Literary Form
non fiction
Main title
Hysteresis in Unemployment and Jobless Recoveries
Nature of contents
dictionaries
Responsibility statement
Dmitry Plotnikov
Series statement
IMF Working Papers
Table Of Contents
Cover; Contents; I. Introduction; Tables; Table 1. Wealth losses and joblessness of recoveries; Figures; Figure 1. Employment dynamics in all post-war recessions in the United States; Figure 2. Total nonfarm employment dynamics during Big Five financial crises; II. Model; A. The household; B. Firms; C. Search in the labor market; D. Equilibrium; III. Closing the model; A. Steady state vs. dynamic indeterminancy; IV. Estimation; A. Overview; B. Priors; C. Posterior estimates; Table 2. Prior distributions of parameters of the model; Table 3. Posterior distributions of parameters of the modelV. Taking the model to the dataFigure 3. Posterior distributions; A. Model performance; Table 4. Summary statistics of the simulated and the real data; B. The mechanism of the model; Figure 4. Simulated series and the actual data in wage units; C. Case study: the Great Recession; Figure 5. Simulated series with both shocks and simulated series with belief shocks only; Figure 6. Simulated series with both shocks and simulated series with TFP shocks only; Figure 7. RBC model generated series and the actual dataFigure 8. The benchmark model generated series using TFP shocks only and the actual dataD. Impulse response functions; Figure 9. The benchmark model generated series using both TFP shocks and belief shocks against the actual data; Figure 10. Impulse response functions to 1% negative TFP shock; VI. Conclusion; References
Classification
Content