Technology Shock and Employment under Catching up with the Joneses

Following a positive technology shock, a flexible price monetary model with catching up with the Joneses utility function can easily generate a negative and persistent decline in employment. When the effect of relative consumption is large, the model also produces a small short run response of output to a technology shock.

Identification of Technology Shocks in Structural VARs

The usefulness of SVARs for developing empirically plausible models is actually subject to many controversies in quantitative macroeconomics. In this paper, we propose a simple alternative two step SVARs based procedure which consistently identifies and estimates the effect of permanent technology shocks on aggregate variables. Simulation experiments from a standard business cycle model show that our approach outperforms standard SVARs. The two step procedure, when applied to actual data, predicts a significant short-run decrease of hours after a technology improvement followed by a delayed and hump-shaped positive response. Additionally, the rate of inflation and the nominal interest rate displays a significant decrease after a positive technology shock.SVARs, long-run restriction, technology shocks, consumption to output ratio, hours worked

The Response of Hours to a Technology Shock: a Two-Step Structural VAR Approach

The response of hours worked to a technology shock is an important and a controversial issue in macroeconomics. Unfortunately, the estimated response is generally sensitive to the specification of hours in SVARs. This paper uses a simple two-step approach in order to consistently estimate technology shocks from a SVAR model and the response of hours that follow this shock. The first step considers a SVAR model with a set of relevant stationary variables, but excluding hours. Given a consistent estimate of technology shocks in the first step, the response of hours to this shock is estimated in a second step. When applied to US data, the two-step approach predicts a short-run decrease of hours after a technology improvement followed by a hump-shaped positive response. This result is robust to the specification of hours, different sample periods, measures of hours and output and to the variables included in the VAR in the first step.SVARs, long-run restriction, technology shocks, consumption to output ratio, hours worked