The Variability of Velocity in Cash-in-Advance Models

Abstract

Monetary models based on cash-in-advance constraints make strong predictions about the stochastic properties of endogeneous variables such as the velocity of circulation of money, the rate of inflation, and real and nominal interest rates. We develop numerical methods to understand these predictions because the models cannot be characterized analytically. We calibrate some cash-in-advance models using driving processes estimated from U. S. time-series data to generate model predictions that are compared to sample statistics. Formulations of the models that generate variability in velocity corresponding to the U.S. data typically fail along other dimensions.