Purpose - To discuss subcopula estimation for discrete models. Design/methodology/approach - The convergence of estimators is considered under the weak convergence of distribution functions and its equivalent properties known in prior works. Findings - The domain of the true subcopula associated...

Permutation techniques, where one recompute the test statistic over permutations of data, have a long history in statistics and have become increasingly useful as the availability of computational power has increased. Until now, no permutation tests for examining returns to scale assumptions,...

This paper (i) derives a number of properties of a newly specified multi-input-single-output (MISO) production function with a derived error term, and (ii) using iteratively rescaled generalized least squares, presents estimates of the cross-sectionally varying coefficients of a...

Statistical Analysis in surveys is often facing missing data. As case-wise deletion and single imputation prove to have undesired properties, multiple imputation remains as a measure to handle this problem. In a longitudinal study, where for some missing values past or future data points might...

We develop a method of testing linearity using power transforms of regressors, allowing for stationary processes and time trends. The linear model is a simplifying hypothesis that derives from the power transform model in three different ways, each producing its own identification problem. We...

When benchmarking production units by non-parametric methods like data envelopment analysis (DEA), an assumption has to be made about the returns to scale of the underlying technology. Moreover, it is often also relevant to compare the frontiers across samples of producers. Until now, no exact...

The estimation of the holding periods of financial products has to be done in a dynamic process in which the size of the observation time interval influences the result. Small intervals will produce smaller average holding periods than bigger ones. The approach developed in this paper offers the...

This paper studies the asymptotic normality for the kernel deconvolution estimator when the noise distribution is logarithmic chi-square; both identical and independently distributed observations and strong mixing observations are considered. The dependent case of the result is applied to obtain...

In this paper, we study the finite sample accuracy of confidence intervals for index functional built via parametric bootstrap, in the case of inequality indices. To estimate the parameters of the assumed parametric data generating distribution, we propose a Generalized Method of Moment...