Working Paper: NBER ID: w15375
Authors: Josvctor Rosrull; Frank Schorfheide; Cristina Fuentesalbero; Maxym Kryshko; Ral Santaeulliallopis
Abstract: 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.
Keywords: Technology Shocks; Labor Supply Elasticity; Bayesian Estimation; Calibration; Macroeconomics
JEL Codes: C1; C8; E3
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| technology shocks (D89) | hours worked (J22) |
| labor supply elasticity (J20) | estimated contribution of technology shocks to fluctuations in hours worked (O49) |
| Frisch elasticity (D11) | contribution of technology shocks (O49) |
| statistical methods (C89) | disparities in results (I24) |
| identification strategies (Z13) | different conclusions about the role of technology shocks (O33) |