Tails of Inflation Forecasts and Tales of Monetary Policy

Abstract

We introduce a new measure called Inflation-at-Risk (I@R) associated with (left and right) tail inflation risk. We estimate I@R using survey-based density forecasts. We show that it contains information not covered by usual inflation risk indicators which focus on inflation uncertainty and do not distinguish between the risks of low or high future inflation outcomes. Not only the extent but also the asymmetry of inflation risks evolve over time. Moreover, changes in this asymmetry have an impact on future inflation realizations as well as on the current interest rate central banks target.

The financial content of inflation risks in the euro area

“…The asymmetry of the distribution of inflation risks is also higher in periods where markets expect an monetary contraction either in 1M of in 1Y. This is consistent with the findings of Andrade, Ghysels, and Idier (2012) who emphasize that monetary authorities react to the asymmetry of the inflation risks as such.…”

“…to depart of the assumption that the risks are balanced. Moreover, Andrade, Ghysels, and Idier (2012) show that these indicators have some predictive power for future inflation realizations in addition to the usual MPF. I@R are defined for a certain risk level p, that is the a given risk to see inflation below a certain threshold.…”

“…The question is then how to measure extreme inflation risks. One answer is provided in Andrade, Ghysels, and Idier (2012) who develop such kind of measures, based on survey data. These inflation-at-risk indicators (I@R) complement the standard MPF indicator.…”

“…The estimation of the I@R, IQR, and ASY indicators relies on the subjective probability distributions provided by the survey. As described in Andrade, Ghysels, and Idier (2012), it first requires to fit continuous generalized beta density distributions over each individual probability distributions about future inflation, using the methodology of Engelberg, Manski, and Williams (2009). For a chosen level of risk, one can then recovers, individual quantiles out of these individual continuous distributions.…”

“…the average of professionals' mean point forecast of inflation, is indeed a very good predictor of future inflation realizations. More recently, Andrade, Ghysels, and Idier (2012) develop new surveybased inflation risk indicators which rely on quantiles extracted from individual subjective distributions of future inflation to measure the risk of extreme inflation realizations. They show that these measures are complementary to the usual consensus forecast extracted from surveys as they allow for a distinction between upside and downside inflation risks and as they also bring information about future inflation outcomes in addition to the usual consensus forecast.…”