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."
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