The Yule-Walker estimator is commonly used in time-series analysis, as a simple way to estimate the coefficients of an autoregressive process. Under strong assumptions on the noise process, this estimator possesses the same asymptotic properties as the Gaussian maximum likelihood estimator....

This paper considers GMM estimation of autoregressive processes. It is shown that, contrary to the case where the noise is independent (see Kim, Qian and Schmidt (1999)), using high-order moments can provide substantial efficiency gains for estimating the AR(p) model when the noise is only...

In this paper we study a new type of latent model in which only the rank statistics of the depen- dent variable is observed. This problem appears naturally in the microeconometric literature, in particular in the case of the parametric estimation of a production function when the output is...

[fre] Nous examinons les différentes possibilités d'estimation d'un des outils les plus utilisés en matière de gestion de risque de taux d'intérêt : la structure par terme des taux d'intérêt. Nous nous attachons plus particulièrement à la présenta­tion des méthodes fondées sur des...

We present an estimation procedure for continuous time models based on discrete sampled data with a fixed unit of time between two observations. Since in general the conditional likelihood of the model cannot be derived an indirect inference procedure based on simulations of a discretized model...

Exponential smoothing (ES) with ARCH (autoregressive conditionally heteroscedastic) and GARCH (generalized ARCH) errors are introduced. This is done for a large class of ES methods, those for which the forecasts are obtained using a set of additive updating formulas, and also those for which an...