Wednesday, January 13, 2016

15th January 2016: The Role of Inflation Expectations, Core Inflation, and Slack in Real-Time Inflation Forecasting

Kundan Kishor
University of Wisconsin - Milwaukee

Using a state-space approach, we extract information from surveys of long-term inflation expectations and multiple quarterly inflation series to undertake a real-time decomposition of quarterly PCE and GDP deflator inflation into a common long-term trend,cyclical components with common and idiosyncratic elements, and residualhigh- frequency noise components. We then explore alternative approaches to real-time forecasting of headline PCE and GDP inflation.We find that performance is enhanced if forecasting equations are estimated using inflation data that have been stripped of high-frequency noise. Performance can be further improved by including an unemployment-based measure of slack in the equations. The improvement is statistically significant relative to benchmark autoregressive models, and also relative to professional forecasters at all but the shortest horizons for headline PCE inflation. In contrast, introducing slack into models estimated using unfiltered PCE inflation data causes forecast performance to deteriorate. Finally,we demonstrate that forecasting models estimated using the Kishor-Koenig (JBES 2012) methodologywhich mandates that each forecasting VAR be augmented with a flexible state-space model of data revisions- consistently outperform the corresponding conventionally estimated forecasting models.

Date: January 15, 2016
Time: 11:30 A.M.

Seminar Room 2
Indian Statistical Institute Delhi Centre,
7, S. J. S. Sansanwal Marg,
New Delhi-110016 (INDIA)


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