A Root Mean Square Error Forecasting Model for Inflation: An Empirical Analysis, 2009-2021

Authors

Presenter(s)

Sydnee C. Haymore, John V. Ruma, Kristen N. Timko

Comments

Presentation: 9:00 a.m.-10:15 a.m., Kennedy Union Ballroom

Files

Description

The purpose of this study is to determine if Root Mean Square Error (RMSE) forecasting models for different inflation indexes (e.g. Personal Consumption Expenditure Price Index (PCEPI) are statistically reliable and efficient for one and two years out of sample. Our benchmark for success is a 12 month average forecast error of 2.5% or less. We use time trend regressions to develop our RMSE inflation forecasting models. Our trend regression time periods are 2009-2017 and 2009-2018. 2019, 2020, and 2021 are the out-of-sample forecasting years.

Publication Date

4-20-2022

Project Designation

Independent Research

Primary Advisor

Tony S. Caporale, Robert D. Dean

Primary Advisor's Department

Economics and Finance

Keywords

Stander Symposium project, School of Business Administration

United Nations Sustainable Development Goals

Quality Education

Recommended Citation

"A Root Mean Square Error Forecasting Model for Inflation: An Empirical Analysis, 2009-2021" (2022). Stander Symposium Projects. 2663.
https://ecommons.udayton.edu/stander_posters/2663