Adapting to instability in money demand: forecasting money growth with a time-varying parameter model

Conventional money demand models appear to be unstable, and this complicates the problem of conducting monetary policy. One way to deal with parameter instability is to learn how to adapt quickly when parameters shift. This paper applies a time-varying-parameter estimator to conventional money demand models and evaluates its usefulness as a forecasting tool. In relative terms, the time-varying-parameter estimator improves significantly on ordinary least squares. In absolute terms, we continue to have difficulty tracking money demand through turbulent periods.