Building Confidence Intervals for the Band-pass and Hodrick-prescott Filters: an Application Using Bootstrapping

نویسندگان

  • Francisco A. Gallego
  • Christian A. Johnson
  • Adolfo Ibáñez
چکیده

This article generates innovative confidence intervals for two of the most popular de-trending methods: the Hodrick-Prescott and Band-Pass filters. The confidence intervals are obtained using block-bootstrapping techniques for dependent data. As an example, we present GDP trend growth and output gap intervals for the G7 economies. This new concept can improve the utility and applications of these filters by overcoming on the most cited limitations: not having confidence intervals.

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تاریخ انتشار 2002