The Variability of Velocity in Cash-in-Advance Models
基于美国时间序列数据校准现金先行模型，通过数值方法分析货币流通速度、通胀率等变量的随机特性，发现能模拟流通速度波动的模型在其他方面往往与数据不符。
Monetary models based on cash-in-advance constraints make strong predictions about the stochastic properties of endogenous variables such as the velocity of circulation of money, the rate of inflation, and real and nominal interest rates. The authors develop numerical methods to understand these predictions because the models cannot be characterized analytically. They 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. Copyright 1991 by University of Chicago Press.