What (really) accounts for the fall in hours after a technology shock? /

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Bibliographic Details
Author / Creator:Rebei, Nooman, 1972- author.
Imprint:[Washington, D.C.] : International Monetary Fund, ©2012.
Description:1 online resource (41 pages)
Language:English
Series:IMF working paper ; WP/12/211
IMF working paper ; WP/12/211.
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/11142013
Hidden Bibliographic Details
Other authors / contributors:International Monetary Fund. Institute for Capacity Development.
ISBN:1475580576
9781475580570
1475505612
9781475505610
147555236X
9781475552362
9781475505610
9781475552362
Digital file characteristics:data file
Notes:Title from PDF title page (IMF Web site, viewed August 29, 2012).
"Institute for Capacity Development Department."
"August 2012."
Includes bibliographical references.
Summary:The paper asks how state of the art DSGE models that account for the conditional response of hours following a positive neutral technology shock compare in a marginal likelihood race. To that end we construct and estimate several competing small-scale DSGE models that extend the standard real business cycle model. In particular, we identify from the literature six different hypotheses that generate the empirically observed decline in worked hours after a positive technology shock. These models alternatively exhibit (i) sticky prices; (ii) firm entry and exit with time to build; (iii) habit in consumption and costly adjustment of investment; (iv) persistence in the permanent technology shocks; (v) labor market friction with procyclical hiring costs; and (vi) Leontief production function with labor-saving technology shocks. In terms of model posterior probabilities, impulse responses, and autocorrelations, the model favored is the one that exhibits habit formation in consumption and investment adjustment costs. A robustness test shows that the sticky price model becomes as competitive as the habit formation and costly adjustment of investment model when sticky wages are included.

MARC

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245 1 0 |a What (really) accounts for the fall in hours after a technology shock? /  |c prepared by Nooman Rebei. 
260 |a [Washington, D.C.] :  |b International Monetary Fund,  |c ©2012. 
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490 1 |a IMF working paper ;  |v WP/12/211 
500 |a Title from PDF title page (IMF Web site, viewed August 29, 2012). 
520 |a The paper asks how state of the art DSGE models that account for the conditional response of hours following a positive neutral technology shock compare in a marginal likelihood race. To that end we construct and estimate several competing small-scale DSGE models that extend the standard real business cycle model. In particular, we identify from the literature six different hypotheses that generate the empirically observed decline in worked hours after a positive technology shock. These models alternatively exhibit (i) sticky prices; (ii) firm entry and exit with time to build; (iii) habit in consumption and costly adjustment of investment; (iv) persistence in the permanent technology shocks; (v) labor market friction with procyclical hiring costs; and (vi) Leontief production function with labor-saving technology shocks. In terms of model posterior probabilities, impulse responses, and autocorrelations, the model favored is the one that exhibits habit formation in consumption and investment adjustment costs. A robustness test shows that the sticky price model becomes as competitive as the habit formation and costly adjustment of investment model when sticky wages are included. 
504 |a Includes bibliographical references. 
500 |a "Institute for Capacity Development Department." 
500 |a "August 2012." 
505 0 |a Cover; Contents; I. Introduction; II. Stylized facts and the RBC model; A. Stylized facts; Figures; 1. SVAR IRFs following a technology shock; B. The benchmark RBC model; 1. Representative household's and firm's problems; 2. Impulse-response functions; III. Alternative models; A. The sticky price (SP) model; 2. Impulse-response functions: SVAR versus the standard RBC model; B. The entry-exit (EE) model; 3. Impulse-response functions: SVAR versus the SP model; C. The habit in consumption (HC) model; 4. Impulse-response functions: SVAR versus the EE model. 
505 8 |a 5. Impulse-response functions: SVAR versus the HC modelD. The persistent technology shock (PT) model; E. The labor friction (LF) model; 6. Impulse-response functions: SVAR versus the PT model; F. The Leontief production (LP) model; 7. Impulse-response functions: SVAR versus the LF model; IV. Full information estimation and model comparison; 8. Impulse-response functions: SVAR versus the LP model; A. Priors and data; Tables; 1. Prior distributions of parameters; B. Estimation results and model comparison; 2. Parameter Estimation Results; C. Impulse-response functions. 
505 8 |a 9. IRFs of the Alternative Estimated ModelsD. Autocorrelation functions; 10. Autocorrelations of the Alternative Models; 3. Autocorrelation statistics; V. Robustness; 4. Estimation results with sticky wages; 11. Autocorrelations: SP versus HC model; VI. Conclusion; References. 
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650 0 |a Business cycles  |x Econometric models. 
650 6 |a Prix  |x Modèles économétriques. 
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