Parameter constancy and a model's mean square forecast error are two commonly used measures of forecast performance. By explicit consideration of the information sets involved, this paper clarifies the roles that each plays in analyzing a model's forecast accuracy. Both criteria are necessary...

Virtually all previous narrow money demand studies for the United Kingdom have used seasonally adjusted data for money, prices, and expenditure. This paper develops a constant, data-coherent M1 demand equation for the United Kingdom with seasonally unadjusted data. For that model, we address...

This paper critically re-evaluates some of the fundamental empirical claims about monetary behavior in the United Kingdom made by Milton Friedman and Anna J. Schwartz in their 1982 book Monetary Trends in the United States and the United Kingdom. We focus on six aspects of their analysis: the...

This overview describes the concepts of cointegration and exogeneity, focusing on analytical structure, statistical inference, and implications for policy analysis. Examples help clarify the concepts. The remainder of the overview summarizes the articles in a special issue of the Journal of...

Argentina became highly "dollarized" during its hyperinflations of 1989 and early 1990. Although inflation has returned to very low rates, a high degree of dollarization has persisted during the early 1990s, counter to what the currency substitution hypothesis predicts. This paper provides new...

This paper develops an empirically constant, data-coherent, error correction model for inflation in Australia. The level of consumer prices is a mark-up over domestic and import costs, with adjustments for dynamics and relative aggregate demand. We address issues of cointegration, general to...

Hoover and Perez (1999) advocate a constructive approach to data mining. The current paper identifies four pejorative senses of data mining and shows how Hoover and Perez's approach counters each. To assess the benefits of constructive data mining, the current paper applies a data-mining...