LEADER 06778oam 22012974 450 001 9910786482103321 005 20230801225341.0 010 $a1-4755-2415-3 010 $a1-4755-5236-X 035 $a(CKB)2670000000278818 035 $a(EBL)1606955 035 $a(SSID)ssj0000944123 035 $a(PQKBManifestationID)11612517 035 $a(PQKBTitleCode)TC0000944123 035 $a(PQKBWorkID)10982501 035 $a(PQKB)11675520 035 $a(MiAaPQ)EBC1606955 035 $a(Au-PeEL)EBL1606955 035 $a(CaPaEBR)ebr10627039 035 $a(OCoLC)808636008 035 $a(IMF)WPIEE2012211 035 $a(IMF)WPIEA2012211 035 $a(EXLCZ)992670000000278818 100 $a20020129d2012 uf 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aWhat (Really) Accounts for the Fall in Hours After a Technology Shock? /$fNooman Rebei 210 1$aWashington, D.C. :$cInternational Monetary Fund,$d2012. 215 $a1 online resource (42 p.) 225 1 $aIMF Working Papers 300 $aDescription based upon print version of record. 311 $a1-4755-8057-6 311 $a1-4755-0561-2 320 $aIncludes bibliographical references. 327 $aCover; 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 327 $a5. 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 327 $a9. 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 330 3 $aThe paper asks how state of the art DSGE models that account for the conditional response of hours following a positive neutral technology shock compare in a marginal likelihood race. To that end we construct and estimate several competing small-scale DSGE models that extend the standard real business cycle model. In particular, we identify from the literature six different hypotheses that generate the empirically observed decline in worked hours after a positive technology shock. These models alternatively exhibit (i) sticky prices; (ii) firm entry and exit with time to build; (iii) habit in consumption and costly adjustment of investment; (iv) persistence in the permanent technology shocks; (v) labor market friction with procyclical hiring costs; and (vi) Leontief production function with labor-saving technology shocks. In terms of model posterior probabilities, impulse responses, and autocorrelations, the model favored is the one that exhibits habit formation in consumption and investment adjustment costs. A robustness test shows that the sticky price model becomes as competitive as the habit formation and costly adjustment of investment model when sticky wages are included. 410 0$aIMF Working Papers; Working Paper ;$vNo. 2012/211 606 $aLabor supply$xEffect of technological innovations on$xMathematical models 606 $aHours of labor$xEffect of technological innovations on$xEconometric models 606 $aEconometrics$2imf 606 $aLabor$2imf 606 $aMacroeconomics$2imf 606 $aInnovation$2imf 606 $aResearch and Development$2imf 606 $aTechnological Change$2imf 606 $aIntellectual Property Rights: General$2imf 606 $aLabor Economics: General$2imf 606 $aWages, Compensation, and Labor Costs: General$2imf 606 $aTime-Series Models$2imf 606 $aDynamic Quantile Regressions$2imf 606 $aDynamic Treatment Effect Models$2imf 606 $aDiffusion Processes$2imf 606 $aState Space Models$2imf 606 $aPrice Level$2imf 606 $aInflation$2imf 606 $aDeflation$2imf 606 $aLabour$2imf 606 $aincome economics$2imf 606 $aTechnology$2imf 606 $ageneral issues$2imf 606 $aEconometrics & economic statistics$2imf 606 $aReal wages$2imf 606 $aStructural vector autoregression$2imf 606 $aSticky prices$2imf 606 $aEconometric analysis$2imf 606 $aPrices$2imf 606 $aLabor economics$2imf 606 $aWages$2imf 607 $aUnited States$2imf 615 0$aLabor supply$xEffect of technological innovations on$xMathematical models. 615 0$aHours of labor$xEffect of technological innovations on$xEconometric models. 615 7$aEconometrics 615 7$aLabor 615 7$aMacroeconomics 615 7$aInnovation 615 7$aResearch and Development 615 7$aTechnological Change 615 7$aIntellectual Property Rights: General 615 7$aLabor Economics: General 615 7$aWages, Compensation, and Labor Costs: General 615 7$aTime-Series Models 615 7$aDynamic Quantile Regressions 615 7$aDynamic Treatment Effect Models 615 7$aDiffusion Processes 615 7$aState Space Models 615 7$aPrice Level 615 7$aInflation 615 7$aDeflation 615 7$aLabour 615 7$aincome economics 615 7$aTechnology 615 7$ageneral issues 615 7$aEconometrics & economic statistics 615 7$aReal wages 615 7$aStructural vector autoregression 615 7$aSticky prices 615 7$aEconometric analysis 615 7$aPrices 615 7$aLabor economics 615 7$aWages 700 $aRebei$b Nooman$01578635 801 0$bDcWaIMF 906 $aBOOK 912 $a9910786482103321 996 $aWhat (Really) Accounts for the Fall in Hours After a Technology Shock$93858208 997 $aUNINA