This article surveys estimation in stationary time series models using the approach of optimal instrumentation. We review tools that allow construction and implementation of optimal instrumental variables estimators in various circumstances - in single- and multi-period models, in the absence...

This short paper is a comment on "Testing for Nonlinear Structure and Chaos in Economic Time Series" by Catherine Kyrtsou and Apostolos Serletis. We summarize their main results and discuss some of their conclusions concerning the role of outliers and noisy chaos. In particular, we include some...

In the present paper we confine ourselves to proposing tests for smooth transition nonlinearity in the presence ou outliers. We consider outlier robust estimation techniques to modify the tests developed by Luukkonen et al

Infra-monthly time series have increasingly appeared on the radar of official statistics in recent years, mostly as a consequence of a general digital transformation process and the outbreak of the COVID-19 pandemic in 2020. Many of those series are seasonal and thus in need for seasonal...

NOTE: This is a description of the paper and not the actual abstract. In this paper it is argued that describing seasonal patterns as an evolving seasonals model in which the coefficients attached to seasonal trigonometric terms follow simple autoregressive processes can be very useful when one...

We propose a modification of kernel time series regression estimators that improves efficiency when the innovation process is autocorrelated. The procedure is based on a pre-whitening transformation of the dependent variable that has to be estimated from the data. We establish the asymptotic...

We argue that existing methods for the treatment of missing observations in observation-driven models lead to inconsistent inference. We provide a formal proof of this inconsistency for a Gaussian model with time-varying mean. A Monte Carlo simulation study supports this theoretical result and...

In this paper it is argued that describing seasonal patterns as an evolving seasonals model in which the coefficients attached to seasonal trigonometric terms follow simple autoregressive processes can be very useful when one is faced with the task of extending well known results obtained for...