The econometric consequences of nonstationary data have wide ranging im-
plications for empirical research in economics. Specifically, these
issues have implications for the study of empirical relations such as a
money demand func- tion that links macroeconomic aggregates: real money
balances, real income and a nominal interest rate. Traditional monetary
theory predicts that these nonsta- tionary series form a cointegrating
relation and accordingly, that the dynamics of a vector process
comprised of these variables generates distinct patterns. Re- cent
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 represents the efforts undertaken by the authors in recent
years in an effort to determine the consequences that nonstationarity
has for the study of aggregate money demand relations. We have brought
together an empirical methodology that we find useful in conducting
empirical research. Some of the work was undertaken during the authors'
sabbatical periods and we wish to acknowledge the generous support of
Arizona State University and Michigan State University respectively.
Professor Hoffman wishes to acknowledge the support of the
Fulbright-Hays Foundation that supported sabbattical research in Europe
and separate support of the Council of 100 Summer Research Program at
Arizona State University.
