Spatial–temporal linear models and the corresponding likelihood-based statistical inference are important tools for the analysis of spatial–temporal lattice data. In this paper, we study the asymptotic properties of maximum likelihood estimates under a general asymptotic framework for...

A Wald type test of the joint null hypothesis of linearity and nonstationarity within a threshold autoregressive process of order one with deterministic components is developed. Its limiting distribution is derived and its local power and finite sample properties investigated.

In a typical strategic asset allocation problem, the out-of-sample certainty equivalent returns for a long-horizon investor with constant relative risk aversion computed from a range of vector autoregressions (VARs) are compared with those from nonlinear models that account for bull and bear...

This paper deals with the presence of asymmetric effects of monetary policy on real activity in Tunisia, using a threshold vector autoregressive model. Two kinds of asymmetry are investigated: asymmetry related to the phase of the business cycle and asymmetry related to the direction of the...

In this paper, a Bayesian approach is suggested to compare unit root models with stationary models when both the level and the error variance are subject to structural changes (known as breaks) of an unknown date. The paper utilizes analytic and Monte Carlo integration techniques for calculating...

This paper proposes a simple testing procedure to distinguish a unit root process from a globally stationary three-regime self-exciting threshold autoregressive process. Following the threshold cointegration literature we assume that the process follows the random walk in the corridor regime,...