Browse by author
Lookup NU author(s): Dr Robert AndersonORCiD
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).
This paper extends standard single equation heteroskedasticity and autocorrelation (HAC) robust inference methods to allow consistent inference for a system of vector moving-average correlated equations also accommodating contemporaneous correlations. This is of particular relevance to the examination of inflation forecast errors, as forecasts for different groups are contemporaneously correlated, while any proposed forecasting model utilising a time-series of multi-period forward-looking expectations data will suffer from overlapping errors inducing a moving-average error structure. The proposed methodology is a generalisation of Newey & West (1987) and the SUR technique of Zellner (1962). Monte Carlo simulations confirm that the method performs well in large samples. Applications testing the rationality of male versus female inflation forecasts, and those of defined educated groups, are also included.
Author(s): Anderson RDJ, Becker R, Osborn DR
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: EcoSta 2017: 1st International Conference on Econometrics and Statistics
Year of Conference: 2017
Online publication date: 17/06/2017
Acceptance date: 01/01/2017
Date deposited: 05/09/2017