Calibration and modern (Bayesian) estimation methods for a neoclassical stochastic growth model are applied to make the case that the identification of key parameters, rather than quantitative methodologies per se, is responsible for empirical findings. For concreteness, the model is used to...

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...

A productivity innovation reduces labor share at impact, making it countercyclical; it subsequently produces a long-lasting increase that peaks five years later at a level larger in absolute terms than the initial drop, before slowly returning to average, i.e., labor share overshoots. We...

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...

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...