In this paper, we employ both calibration and modern (Bayesian) estimation methods to assess the role of neutral and investment-specific technology shocks in generating fluctuations in hours. Using a neoclassical stochastic growth model, we show how answers are shaped by the identification strategies and not by the statistical approaches. The crucial parameter is the labor supply elasticity. Both a calibration procedure that uses modern assessments of the Frisch elasticity and the estimation procedures result in technology shocks accounting for 2% to 9% of the variation in hours worked in the data. We infer that we should be talking more about identification and less about the choice of particular quantitative approaches.
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Length: Date of creation: Sep 2009 Date of revision: Handle: RePEc:nbr:nberwo:15375
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Find related papers by JEL classification: C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
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