Generalized Covariance Estimator under Misspecification

Aryan Manafi Neyazi

Papers from arXiv.org

Abstract: This paper investigates the properties of the Generalized Covariance (GCov) estimator under misspecification with application to processes with local explosive patterns, such as causal-noncausal processes. We show that GCov is consistent and has an asymptotically Normal distribution under misspecification. Then, we construct GCov-based Wald-type and score-type tests to test one specification against the other, all of which follow a $\chi^2$ distribution. We validate the finite-sample performance of the proposed estimators and tests in the context of causal-noncausal models. Finally, we provide applications of the noncausal model to the final energy demand commodity index.

Date: 2025-09, Revised 2026-09
New Economics Papers: this item is included in nep-ecm and nep-ets
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