We propose a novel nonparametric method for the structural identification of unobserved technological heterogeneity in production. We assume cost minimization as the firms' behavioral objective, and we model unobserved heterogeneity as an unobserved productivity factor on which firms condition...

Nonparametric unit-root tests are a useful addendum to the tool-box of time-series analysis. They tend to trade off power for enhanced robustness features. We consider combinations of the RURS (seasonal range unit roots) test statistic and a variant of the level-crossings count. This combination...

A test for serial independence is proposed which is related to the BDS test but focuses on tail event probabilities rather than probabilities near the center of the distribution. The motivation behind this approach is to obtain a test more suitable for detecting structure in the tails, such as...

We derive a nonparametric test for constant (continuous) beta over a fixed interval of time. Continuous beta is defined as the ratio of the continuous covariation between an asset and observable risk factor (e.g., the market return) and the continuous variation of the latter. Our test is based...

The transferable utility hypothesis underlies important theoretical results in household economics. We provide a revealed preference framework for bringing this (theoretically appealing) hypothesis to observational data. We establish revealed preference conditions that must be satisfied for...

Tests for serial independence and goodness-of-fit based on divergence notions between probability distributions, such as the Kullback-Leibler divergence or Hellinger distance, have recently received much interest in time series analysis. The aim of this paper is to introduce tests for serial...

This paper improves on the issues of extreme data points and heterogeneity found in the linear programming data envelopment analysis (DEA) by presenting a cluster-adjusted DEA model (DEA with cluster approach). This analysis, based on efficiency, determines the number of clusters via Gap...

The study investigates the stock market efficiency of selected OPEC member countries within the context of random walk hypothesis and volatility approaches using monthly data on stock market indices from January, 2005 to April, 2016. Parametric (variance ratio: homoskedastic and heteroskedastic...

Quantile regression (QR) is a principal regression method for analyzing the impact of covariates on outcomes. The impact is described by the conditional quantile function and its functionals. In this paper we develop the nonparametric QR series framework, covering many regressors as a special...