In this article, consistency and asymptotic normality of the quasi-maximum likelihood estimator (QMLE) in the class of …

We study the strong consistency and asymptotic normality of the maximum likelihood estimator for a class of time series … processes. We formulate primitive conditions for global identification, invertibility, strong consistency, asymptotic normality …

application of theorems by Meyn and Tweedie [2009]. Under those conditions, the consistency and asymptotic normality of the QMLE …

robust filtering and forecasting. We provide sufficient conditions for the strong consistency and asymptotic normality of the …

consistency (which is a prerequisite for proving asymptotic normality) is challenging due to non-uniform convergence of the … components. In contrast, we establish consistency and asymptotic normality of parameter estimates related to the stochastic …

different forms of nonstationarity and noninvertibility. As in related settings, the proof of consistency (which is a … stochastic and deterministic components. We establish consistency and asymptotic normality under quite general circumstances …

dependent errors, are considered for observations over time, space or space-time. Consistency and asymptotic normality of … of many in which consistency of a vector of parameter estimates (which converge at different rates) cannot be established … present a generic consistency result. …

This paper proves consistency and asymptotic normality for the conditional-sum-of-squares (CSS) estimator in fractional … time series models. The models are parametric and quite general. The novelty of the consistency result is that it applies … uniform convergence fails is handled using a truncation argument. The only other consistency proof for such models that …