Synopses & Reviews
The econometric consequences of nonstationary data have wide-ranging implications for empirical research in economics. Specifically, these issues have implications for the study of empirical relations such as a money demand function that links macroeconomic aggregates: real money balances, real income and a nominal interest rate. Traditional monetary theory predicts that these nonstationary series form a cointegrating relation and, accordingly, that the dynamics of a vector process comprising these variables generates distinct patterns. Recent econometric developments designed to cope with nonstationarities have changed the course of empirical research in the area, but many fundamental challenges, for example the issue of identification, remain. This book is an effort to determine the consequences that nonstationarity has for the study of aggregate money demand relations. The object of this book is to utilize the tools of modern time series analysis to determine the role of an aggregate demand for real balances in the generation of macroeconomic time series. A significant distinguishing characteristic of this research is the identification and estimation of this demand function in a multivariate framework, in contrast to most existing studies that concentrate on a single equation framework.
Table of Contents
1. Background. 2. The Development and Failures of the Empirical Literature on the Demand for Money. 3. Identification, Estimation, and Inference in Cointegrated Systems. 4. A Framework for Structural and Dynamic Analysis in Cointegrated Systems. 5. A Prototype Economic Model Characterized by Cointegration. 6. Analysis of Three Variable VECM Models Including Demand Functions for Real Balances. 7. Higher Dimensional VECM Models with Long-Run Money Demand Functions. 8. Combining Term Structure and Fisher Effects. Appendix. Bibliography. Author Index. Subject Index.