The increasing works on parameter instability, structural changes and regime switches lead to the natural research question whether the assumption of stationarity is appropriate to model volatility processes. Early econometric studies have provided testing procedures of covariance stationarity...

Many time series in the applied sciences display a time-varying second order structure. In this article, we address the problem of how to forecast these nonstationary time series by means of non-decimated wavelets. Using the class of Locally Stationary Wavelet processes, we introduce a new...

We consider the semiparametric regression X t +(Z) where and (r and function, and where the variables (X, Z) are endogeneous. We propose necessary and sufficient conditions for the identification of the parameters in the presence of instrumental variables. We also focus on the estimation of . An...

We estimate the distribution of a real-valued random variable from contaminated observations. The additive error is supposed to be normally distributed, but with an unknown variance. The distribution is identifiable from the observations if we restrict the class of considered distributions by a...

The purpose of this work is to provide upper bounds on the stop-loss and total variation distances between random sums. The main theoretical argument consists in defining discrete analogs of the classical ideal metrics considered by Rachev and Rüschendorf (Adv. Appl. Probab. 22 (1990) 350). An...

The nonparametric estimation of a regression function from conditional moment restrictions involving instrumental variables is considered. The rate of convergence of penalized estimators is studied in the case where the regression function is not identified from the conditional moment...

This paper studies the estimation of a nonparametric function <italic>ϕ</italic> from the inverse problem <italic>r</italic> = <italic>Tϕ</italic> given estimates of the function <italic>r</italic> and of the linear transform <italic>T</italic>. We show that rates of convergence of the estimator are driven by two types of assumptions expressed in a single Hilbert scale. The...