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(S)he was not hurting anybody, just running away.
S. Endo
INTRODUCTION
Because Central Banks have abandoned the control of monetary aggregates and implemented inflation targeting rules directly or indirectly by means of aggressive Taylor rules, forecasting inflation rates, both unconditionally or conditionally, has become crucial for both policy makers and private agents who try to understand and react to Central Banks decisions. Several methods have been proposed but the overall performance has been, at best, mixed: the information provided by past inflation appears to suffice and very few variables add marginal predictive content to univariate specifications [see, e.g., Cecchetti, Chu, and Steindel (2001)].
Traditional forecasting models of inflation are motivated by a standard Phillips curve trade-off. Blinder (1997) attributes the popularity of this specification to the stability of the relationship and its reliability as forecasting tool. Stock and Watson (1999) criticized this conventional wisdom, showing that in the United States, the parameters of a standard Phillips curve have changed over time; that other measures of real activity forecast inflation better than the unemployment rate, and that combining forecasts produced by different specifications improves the performance of a model which only uses the unemployment rate. Atkeson and Ohanian (2001) also criticize this view by showing that Phillips curve forecast of U.S. inflation over a 15-year period are no better than those obtained from a random walk model. The instability of the forecasting relationships is not limited to traditional Phillips curve based models but extends to other theoretical or ad hoc empirical models used in the literature [see, e.g., models that include asset prices, for example, Stock and Watson (2000), Goodhart and Hoffman (2000), Marcellino (2002)]. Although forecasting specifications built adding one indicator of real activity at the time work poorly and tend to be unstable, some improvements have been documented by Cristadoro et al. (Forthcoming), Wright (2003), Granger and Yeon (2004), and Inoue and Kilian (2003), using methods that combine information obtained from many predictors.
In this paper, we explore the interaction between predictability and instability by comparing the forecasting performance of some leading models for inflation in G-7 countries. To narrow down the scope of the comparison, we focus attention on four different but interrelated questions. First, we would like to investigate how models...