Abstract Models characterized by autoregressive structure and random coefficients are
powerful tools for the analysis of high-frequency, high-dimensional and volatile time series …

Statistical Theories and Methods with Applications to Economics and Business highlights
recent advances in statistical theory and methods that benefit econometric practice. It deals …

Quantification of the dependence characteristics in hydrological time series is essential for
understanding hydrological variability and for managing water resources. However, how …

In this study, we propose a test for the coefficient randomness in autoregressive models
where the autoregressive coefficient is local to unity, which is empirically relevant given the …

Local‐to‐unity and moderate‐deviations specifications have been popular alternatives to
unit root modeling. This article considers another kind of departures from a unit root, of the …

In this article, we test for a bubble in a model with a random explosive autoregressive
coefficient. We consider two local alternatives and find that versions of recursive stochastic …

In this article, we develop the asymptotic theory of Hwang and Basawa (2005) for explosive
random coefficient autoregressive (ERCA) models. Applying the theory, we prove that a …

An agent based model (ABM), where each agent makes decisions by using the sum of two
signals, is proposed. The first is related to the fundamental information while the second …

The random coefficient autoregressive model has been utilized for modeling financial time
series because it possesses features that are often observed in financial time series. When …

Many studies have examined the power of Stochastic Unit Root (STUR) tests. However,
these studies assume that the two error processes of the underlying time series are …