Money demand function estimation by nonlinear cointegration
提出一种结合对数设定与利率单位根假设的非线性协整方法，用于估计货币需求函数，该方法对误差序列相关稳健，对美国数据的估计系数更大且样本外预测更优。
Abstract Conventionally, the money demand function is estimated using a regression of the logarithm of money demand on either the interest rate or the logarithm of the interest rate. This equation is presumed to be a cointegrating regression. In this paper, we aim to combine the logarithmic specification, which models the liquidity trap better than a linear model, with the assumption that the interest rate itself is an integrated process. The proposed technique is robust to serial correlation in the errors. For the USA, our new technique results in larger coefficient estimates than previous research suggested, and produces superior out‐of‐sample prediction. Copyright © 2007 John Wiley & Sons, Ltd.