Predictability of Output Growth and Inflation: A Multi-Horizon Survey Approach, Summary of Paper by Andrew Patton, Allan Timmermann

7 Pages Posted: 2 Jan 2016 Last revised: 13 Jan 2017

See all articles by Ravi Kashyap

Ravi Kashyap

Gain Knowledge Group; Estonian Business School; City University of Hong Kong (CityU) - Department of Economics & Finance

Date Written: November 16, 2015

Abstract

Patton and Timmermann (2011) develop an unobserved-components approach to study surveys of forecasts containing multiple forecast horizons. Under the assumption that forecasters optimally update their beliefs about past, current, and future state variables as new information arrives, their model extracts information on the degree of predictability of the state variable and the importance of measurement errors in the observables. The empirical results suggest that inflation exhibits greater persistence, and thus is predictable at longer horizons, than GDP growth and the persistent component of both variables is well approximated by a low-order autoregressive specification.

We choose this paper (henceforth, “the paper”) to summarize since it provides key insights into how the information that can be gleaned from the revised forecasts of forecasters can be a valuable source of improving forecasts and to understand the strength of agents beliefs.

Keywords: Predictability, Output Growth, Inflation, Measurement, Error

Suggested Citation

Kashyap, Ravi, Predictability of Output Growth and Inflation: A Multi-Horizon Survey Approach, Summary of Paper by Andrew Patton, Allan Timmermann (November 16, 2015). Available at SSRN: https://ssrn.com/abstract=2709890

Ravi Kashyap (Contact Author)

Gain Knowledge Group ( email )

1 Austin Road West
Kowloon
Hong Kong

HOME PAGE: http://www.gainknowledgegroup.com

Estonian Business School ( email )

City University of Hong Kong (CityU) - Department of Economics & Finance

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