Dallas Fed research seeks to improve real-time inflation forecasts
Filtering out noise can improve performance, researchers say
It is possible to improve real-time forecast performance by stripping noise out of data on inflation and inflation expectations, research published by the Federal Reserve Bank of Dallas has found.
The working paper by N Kundan Kishor and Evan Koenig begins by breaking survey data on expectations and inflation data into trend, cyclical and noise components. This allows them to filter the noise component out when using the data for real-time forecasting.
Forecasts based on their filtered inflation
Only users who have a paid subscription or are part of a corporate subscription are able to print or copy content.
To access these options, along with all other subscription benefits, please contact info@centralbanking.com or view our subscription options here: http://subscriptions.centralbanking.com/subscribe
You are currently unable to print this content. Please contact info@centralbanking.com to find out more.
You are currently unable to copy this content. Please contact info@centralbanking.com to find out more.
Copyright Infopro Digital Limited. All rights reserved.
As outlined in our terms and conditions, https://www.infopro-digital.com/terms-and-conditions/subscriptions/ (point 2.4), printing is limited to a single copy.
If you would like to purchase additional rights please email info@centralbanking.com
Copyright Infopro Digital Limited. All rights reserved.
You may share this content using our article tools. As outlined in our terms and conditions, https://www.infopro-digital.com/terms-and-conditions/subscriptions/ (clause 2.4), an Authorised User may only make one copy of the materials for their own personal use. You must also comply with the restrictions in clause 2.5.
If you would like to purchase additional rights please email info@centralbanking.com