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This paper evaluates the predictive power of different information sets for the European Central Bank (ECB) interest rate setting behavior. The authors employ an ordered probit model, i.e. a limited dependent variable framework, to take into account the discreteness displayed by policy rate changes. The results show that the forecasting ability of standard Taylor-type variables, such as inflation and output gap, is fairly low both insample and out-of-sample, and is comparable to the performance of the random walk model. Instead by using broader information sets that include measures of core inflation, exchange rates and monetary aggregates, the accuracy of the forecasts about ECB future actions substantially improves.
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