Forecasting Inflation with the New Keynesian Phillips Curve: Frequency Matters

M. M. Martins, Fabio Verona
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引用次数: 3

Abstract

We show that the New Keynesian Phillips Curve (NKPC) outperforms standard benchmarks in forecasting U.S. inflation once frequency-domain information is taken into account. We do so by decomposing the time series (of inflation and its predictors) into several frequency bands and forecasting separately each frequency component of inflation. The largest statistically significant forecasting gains are achieved with a model that forecasts the lowest frequency component of inflation (corresponding to cycles longer than 16 years) flexibly using information from all frequency components of the NKPC inflation predictors. Its performance is particularly good in the returning to recovery from the Great Recession.
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用新凯恩斯菲利普斯曲线预测通货膨胀:频率很重要
我们表明,一旦考虑到频域信息,新凯恩斯菲利普斯曲线(NKPC)在预测美国通货膨胀方面优于标准基准。我们通过将时间序列(通货膨胀及其预测者)分解为几个频带并分别预测通货膨胀的每个频率分量来做到这一点。通过灵活地利用NKPC通胀预测器的所有频率成分的信息来预测通胀的最低频率成分(对应于超过16年的周期),可以实现最大的统计显著预测收益。它在从大衰退中恢复的过程中表现得尤为出色。
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