Testing for an Omitted Multiplicative Long-Term Component in GARCH Models

A-Tier
Journal: Journal of Business & Economic Statistics
Year: 2020
Volume: 38
Issue: 2
Pages: 229-242

Authors (2)

Score contribution per author:

2.018 = (α=2.02 / 2 authors) × 2.0x A-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

We consider the problem of testing for an omitted multiplicative long-term component in GARCH-type models. Under the alternative, there is a two-component model with a short-term GARCH component that fluctuates around a smoothly time-varying long-term component which is driven by the dynamics of an explanatory variable. We suggest a Lagrange multiplier statistic for testing the null hypothesis that the variable has no explanatory power. We derive the asymptotic theory for our test statistic and investigate its finite sample properties by Monte Carlo simulation. Our test also covers the mixed-frequency case in which the returns are observed at a higher frequency than the explanatory variable. The usefulness of our procedure is illustrated by empirical applications to S&P 500 return data. Supplementary materials for this article are available online.

Technical Details

RePEc Handle
repec:taf:jnlbes:v:38:y:2020:i:2:p:229-242
Journal Field
Econometrics
Author Count
2
Added to Database
2026-01-25