摘要：In this paper it is assessed the differences that emerge in Taylor rule estimations for the European Central Bank (ECB) when using ex-post data instead of real-time forecasts and vice versa. The authors argue that previous comparative studies in this field risk mixing up two separate effects. First,the differences resulting from the use of ex-post and real time data per se;and second,the differences emerging from the use of non-modified real-time data instead of real-time database forecasted values (and vice versa). Since both effects can influence the ECB reaction to inflation and the output gap in either way,it is used a more clear-cut approach to disentangle the partial effects. However,"good” forecasts have to be as close as possible to the forecasts the ECB governing council had at hand when taking its interest rate decision. Therefore,two approaches are used to generate the forecasts:first,forecasts generated relying on a pure AR process;and second,explicit ECB staff projections which are available only at a quarterly frequency. So,the authors found it indispensable to estimate all variants of the reaction function using also quarterly data. Our estimation results indicate that using real-time instead of ex-post data leads to higher estimated inflation coefficients while the opposite is true for the output gap coefficients. If real-time data forecasts based on AR processes for the current period are used (since actual data become available with a lag),this empirical pattern is even strengthened in the sense of even increasing the inflation response but lowering the reaction to the output gap while the reverse is true if "true” forecasts of real?time data for several periods are employed.
关键词：European Central Bank;monetary policy;real-time data;Taylor rule.
