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Statistical Inference for Measurement Equation Selection in the log-RealGARCH Model (EC)

Friday 8 November 2019, 2.00PM to 3.00 pm

Speaker(s): Yuning Li (PhD)

Host: Econometric Theory Cluster

Abstract: This article investigates the statistical inference problem of whether a measurement equation is self-consistent in the logarithmic realized GARCH model (log-RealGARCH). First, we provide the sufficient and necessary conditions for the strict stationarity of both the log-RealGARCH model and the log-GARCH-X model. Under these conditions, strong consistency and asymptotic normality of the quasi-maximum likelihood estimators of these two models are obtained. Then, based on the asymptotic results, we propose a Hausman-type self-consistency test for diagnosing the suitability of the measurement equation in the log-RealGARCH model. Finally, the results of simulations and an empirical study are found to accord with the theoretical results.

Location: A/D271 ERC Meeting Room (above Alcuin Porters)

Admission: All welcome