We propose a nonparametric estimator and a nonparametric test for Granger causality measures that quantify linear and nonlinear Granger causality in distribution between random variables. We first show how to write the Granger causality measures in terms of copula densities. We suggest a...

We propose a nonparametric estimator and a nonparametric test for Granger causality measures that quantify linear and nonlinear Granger causality in distribution between random variables. We first show how to write the Granger causality measures in terms of copula densities. We suggest a...

We propose a nonparametric estimation and inference for conditional density based Granger causality measures that quantify linear and nonlinear Granger causalities. We first show how to write the causality measures in terms of copula densities. Thereafter, we suggest consistent estimators for...

Let X1,X2,...Xn be i.i.d. N-dimensional random variables having an unknown support of probability density denoted G; we suppose that G belongs to a functional class "g" of compact sets with smooth upper surface called boundary fragments. The problem consists in testing the hypotheses G=Go...

The paper deals with the problem of identifying stochastic unobserved two-component models, as in seasonal adjustment or trend-cycle decompositions. Solutions based on the properties of the unobserved component estimation error are considered, and analytical expressions for the variances and...

The simulation result of Nunes, Kuan, and Newbold suggests that it is possible to estimate a spurious break for a regression model with I(1) disturbances. In this note, we provide a rigorous proof for this phenomenon.

This paper puts forth a concept of Adptivety Rational Equilibrium (A.R.E) where agents base decisions upon predictions of future values of endogenous variables whose actual values are determined by equilibrium equations.