In this study, I analyze the shock responses of macro variables in a shopping-time monetary
model, namely, the cash in advance (CIA) model, when the shock processes are calibrated by
Bayesian regression. Two external disturbances related to financial variables-that is, productivity
and monetary shocks-are introduced in the model. These shocks are then calibrated by a Markov
Chain Monte Carlo (MCMC) method to fit the shock evolutionary process of the US economy
during the period from 1947 through 2012. This calibration strategy outperforms the traditional
calibration style in (i) matching the variables’ correlation with the observed pattern in the analysis
of the amplification and (ii) demonstrating persistence of the variables’ impulse response to the
shocks. The results also show the dominant substitution effect, consistently suggesting that a
household elastically substitutes labor supply with leisure when an economy experiences a positive
shock.
주제어：Cash in Advance model, Markov Chain Monte Carlo method, Impulse Response,
Productivity shock, Monetary shock