The recursive prediction and filtering formulas of the Kalman filter are difficult to implement in nonlinear state space models. For Gaussian linear state space models, or for models with qualitative state variables, the recursive formulas of the filter require the updating of a finite number of...

This paper deals with efficient estimation in exchangeable nonlinear dynamic panel models with common unobservable factor. The specification accounts for both micro- and macro-dynamics, induced by the lagged individual observation and the common stochastic factor, respectively. For large...

The aim of this paper is to characterize the one-dimensional stochastic differential equations, for which the eigenfunctions of the infinitesimal generator are polynomials in y. Affine transformations of the Ornstein-Uhlenbeck process, the Cox-Ingersoll-Ross process and the Jacobi process belong...

In this paper we propose causality measures based on the Kullback Information Criterion. These causality measures are applicable in a general context which contains, as special cases, the stationary autoregressive case, considered by GEWEKE, and qualitative models. Estimators of these measures...

In this paper we are interested in inference problems on the matrix of coefficients in a multivariate linear model; in particular we consider tests on the kernel, the range and the rank of this matrix. Various test procedures are explicited and compared: (pseudo) likelihood ratio, Wald (or...

The difficulties in estimating continuous time interest rate models stem in large parts from measurement problems. The observations are in discrete time and the infinitesimal rate is unobservable and replaced by an observed short term rate with non infinitesimal time-to-maturity. These two...

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 sequenceof testable restrictions on the data...

In this paper, we introduce the concept of covariance estimators. These estimators are obtained by solving the empirical counterpart of some noncorrelation conditions characterizing the interest parameters. The statistical properties of the covariance estimators are studied in a general...