This paper studies the limiting behavior of general functionals of order statistics and their multivariate concomitants for weakly dependent data. The asymptotic analysis is performed under a conditional moment-based notion of dependence for vector-valued time series. It is argued, through...

This paper develops the asymptotic theory for the estimation of smooth semiparametric generalized estimating equations models with weakly dependent data. The paper proposes new estimation methods based on smoothed two-step versions of the generalised method of moments and generalised empirical...

This paper proposes a new method to estimate dynamic panel data models with spatially dependent errors that allows for known/unknown group-specific patterns of slope heterogeneity. Analysis of this model is conducted in the framework of composite quasi-likelihood (CL) maximization. The proposed...

This paper proposes a novel method to estimate large panel data error-correction models with stationary/non-stationary covariates and spatially dependent errors, which allows for known/unknown group-specific patterns of slope heterogeneity. Analysis is based on composite quasi-likelihood (CQL)...

We propose a functional principal components method that accounts for stratified random sample weighting and time dependence in the observations to understand the evolution of distributions of monthly micro-level consumer prices for the United Kingdom (UK). We apply the method to publicly...

We develop a new method to approximate the asymmetric multivariate probability density function (pdf) of financial asset returns by using series expansions; a rate of convergence for the mean absolute error of this approximation is also provided. We then propose the method of maximum likelihood...

This paper considers the problem of estimating expected values of functions that are inversely weighted by an unknown density using the <italic>k</italic>-nearest neighbor (<italic>k</italic>-NN) method. It establishes the <inline-graphic> </inline-graphic>-consistency and the asymptotic normality of an estimator that allows for strictly stationary time-series...

type="main" <p>Permutation tests for serial independence using three different statistics based on empirical distributions are proposed. These tests are shown to be consistent under the alternative of m-dependence and are all simple to perform in practice. A small simulation study demonstrates that...</p>