Abstract
We estimate a “hybrid expectations” version of the Smets and Wouters (2007) model in which a subset of agents employ simple moving-average forecast rules that place a significant weight on the most recent data observation. We show that the overall fit is improved relative to an otherwise similar version in which all agents have fully rational expectations. In-sample and out-of-sample analyses show the superiority of the hybrid expectations model in generating an expected inflation series that more closely tracks expected inflation from the Survey of Professional Forecasters.
Citation
@article{Iskrev2019258,
title = {Inflation dynamics and adaptive expectations in an estimated DSGE model},
journal = {Journal of Macroeconomics},
volume = {59},
pages = {258-277},
year = {2019},
issn = {0164-0704},
doi = {https://doi.org/10.1016/j.jmacro.2018.12.002},
url = {https://www.sciencedirect.com/science/article/pii/S0164070418302428},
author = {Paolo Gelain and Nikolay Iskrev and Kevin {J. Lansing} and Caterina Mendicino},
keywords = {Inflation expectations, Bayesian estimation, Local identification, Adaptive expectations, Survey of Professional Forecasters' expectations},
abstract = {We estimate a “hybrid expectations” version of the Smets and Wouters (2007) model in which a subset of agents employ simple moving-average forecast rules that place a significant weight on the most recent data observation. We show that the overall fit is improved relative to an otherwise similar version in which all agents have fully rational expectations. In-sample and out-of-sample analyses show the superiority of the hybrid expectations model in generating an expected inflation series that more closely tracks expected inflation from the Survey of Professional Forecasters.}
}