The paper presents a study of dependencies between the autocorrelation function and selected nonlinear transformations of time series. We examine parametric transformations and introduce an analysis of nonlinear canonical correlations. We also propose various methods of testing the...

We introduce nonlinear panel data models for individual risl management and control. Our approach extends traditional models by allowing for nonlinearities in input variables and unobserved individual heterogeneity with possible temporal dependence. This permits us to develop nonlineat models...

In a nonlinear framework the magnitude of temporal dependence may depend on the transformation applied to time series. The aim of this paper is to examine in detail various forms of persistence and the corresponding transformations. For multivariate series the persistence analysis is used to...

We consider truncated processes, both in discrete and continuous time, and study their dynamic properties. When the underlying process is a diffusion process, we derive the infinitesimal generator of its truncated counterpart. This result is the basis for the estimation of the drift and...

In this note, we propose a general testing procedure for parametric models based on Bartlett Identities. A well-known example is the Information Matrix Test, which is based on the Bartlett Identity of order 1. The Identities are shown to induce a sequence of testable restrictions on the data...

In order to obtain exact distributional results without imposing restrictive parametric assumptions, various rank counterparts of the Dickey-Fuller statistic are considered. In particular, a rank counterpart of the score statistic is suggested which appears to have attractive theoretical...

We consider a kernel based approach to nonlinear canonical correlation analysis and its implementation for time series. We deduce various diagnostics for reversible processes and gaussian processes. The method is first applied to a stimulated series satisfying a diffusion equation allowing us to...

This paper is interested in small sample properties of the indirect inference procedure which has been previously studied only from an asymptotic point of view. First, we highlight the fact that the Andrews(1993) median-bias correction procedure for autoregresssive parameter of an AR(1) process...