Parametric copulas are shown to be attractive devices for specifying quantile autoregressive models for nonlinear time-series. Estimation of local, quantile-specific copula-based time series models offers some salient advantages over classical global parametric approaches. Consistency and asymptotic normality of the proposed quantile estimators are established under mild conditions, allowing fo...

In this paper we consider general rst order autoregression, including the stationary, the explosive and the unstable case. It is well-known in the literature that the usual bootstrap method for the least squares parameter estimator is asymptotically consistent for the stationary and the explosive case, but does not work in the unstable case, where the parameter value is equal to + 1 or {1. We p...

The goal of this paper is to test and model nonlinearities in several monthly exchange rates time series. We apply two different nonlinear alternatives, namely: the artificial neural-network time series model estimated with Bayesian regularization; and a flexible smooth transition specification, called the neuro-coefficient smooth transition autoregression. The linearity test rejects the null h...

A nonparametric statistical model of small di€usion type is compared with its discretization by a stochastic Euler di€erence scheme. It is shown that the discrete and continuous models are asymptotically equivalent in the sense of Le Cam's de®ciency distance for statistical experiments, when the discretization step decreases with the noise intensity . Mathematics Subject Classi®cation (1991): P...

The study of the large-sample distribution of the canonical correlations and variates in cointegrated models is extended from the first-order autoregression model to autoregression of any (finite) order. The cointegrated process considered here is nonstationary in some dimensions and stationary in some other directions, but the first difference (the "error-correction form") is stationary. The a...

This paper investigates the effects of shocks to U.S. monetary policy on the dollar/yen exchange rate, using structural Vector Error Correction Model (VECM) methods. We compare our estimates of the impulse responses with those based on levels Vector Autoregression. We also compare results from short run and long run restrictions imposed on the structural VECM. We find evidence of overshooting b...