Fitting survey expectations and uncertainty about trend inflation |
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Affiliation: | 1. National Research University Higher School of Economics, Nizhny Novgorod 603155, Russia;2. Department of Physical Electronics, School of Electrical Engineering, Faculty of Engineering, and Center for Light-Matter Interaction, Tel Aviv University, Tel Aviv 69978, Israel;1. Freddie Mac, 1551 Park Run Dr., McLean, VA 22102, USA;2. Department of Economics, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd., Daan Dist., Taipei City 106, Taiwan |
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Abstract: | Many studies document that the inflation rate is governed by persistent trend shifts and time-varying uncertainty about trend inflation. As both these quantities are unobserved, a forecaster has to learn about changes in trend inflation by a signal extraction procedure. I suggest that the forecaster uses a simple IMA(1, 1) model because it is well suited to forecast inflation and it provides an efficient way to solve the signal extraction problem. I test whether this model provides a good fit for expectations from the Survey of Professional Forecasters. The model appears to be well suited to model observed inflation expectations if we allow for stochastic volatility. When I estimate the implied learning rule, results are supportive for the trend learning hypothesis. Moreover, stochastic volatility seems to influence the way agents learn over time. It appears that survey participants systematically adapt their learning behavior when inflation uncertainty changes. |
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