Mean Targeting Estimation for Negative Binomial INGARCH(1,1) Models

• Activity Number: 519 - Innovations in Time Series Modeling
• Type: Contributed
• Date/Time: Thursday, August 11, 2022 : 8:30 AM to 10:20 AM
• Sponsor: Business and Economic Statistics Section
• Author(s): Yunwei Cui* and Mackenzie McCracken
• Companies: Towson University and Towson University
• Keywords: variance targeting; mean targeting; negative binomial INGARCH(1,1) model

Abstract

In order to alleviate numerical difficulties in GARCH models, variance targeting estimation (VTE) was introduced to estimate parameters. Mean targeting estimation (MTE) was developed in a similar fashion to VTE, but is used for integer-valued generalized autoregressive conditional heteroskedastic (INGARCH) models. The asymptotic properties of MTE for the Poisson INGARCH(1, 1) model have been established in prior literature. This project applies MTE to the negative binomial INGARCH(1, 1) model. The strong consistency and asymptotic normality of MTE for the negative binomial INGARCH(1, 1) model are established. The performance of the proposed MTE is illustrated by simulation studies and an empirical example.