This paper is concerned with bootstrap hypothesis testing in high dimensional linear regression models. Using a theoretical framework recently introduced by Anatolyev (2012), we show that bootstrap F, LR and LM tests are asymptotically valid even when the numbers of estimated parameters and...

Determining whether a data set contains one or more outliers is a challenge commonly faced in applied statistics. This paper introduces a distribution-free test for multiple outliers in data drawn from an unknown data generating process. Besides, a sequential algorithm is proposed in order to...

In this paper, we propose a method of analyzing time series in the spatial domain. The analysis is based on the inference on the local time and its expectation. Both for the stationary and nonstationary time series, the spatial distributions are provided by the local time, and some of their...

This paper utilizes the bootstrap to construct tests using the measures for goodness-of-fit for nonnested regression models. The bootstrap enables us to compute the statistical significance of the differences in the measures and to formally test on nonnested regression models. The bootstrap...

In various fields of macroeconomic modelling, researchers often face the problem of decomposing time series into trend component and cycle fluctuations. While there are several potentially useful methods to perform the task in question, Hodrick-Prescott (HP) fi lter seems to have remained...

In this paper we use a two stage procedure, based on bias corrected DEA, to evaluate the impacts of regulatory reforms on technical efficiency of 28 Italian airports during the period 2000–2006. We employ two different DEA models: physical and monetary. The first relies on the aeronautical...

This paper examines the total factor productivity of 28 Italian airports during 2000–2006 using non-parametric estimation methods. Moreover, non-parametric inference and hypothesis test on the Malmquist index and its two main components, efficiency and technological change, have been carried...

The Johansen-Ledoit-Sornette (JLS) model of rational expectation bubbles with finite-time singular crash hazard rates has been developed to describe the dynamics of financial bubbles and crashes. It has been applied successfully to a large variety of financial bubbles in many different markets....

We analyse statistical inference for top income shares in finite samples. The asymptotic inference performs poorly even in large samples. The standard bootstrap tests give some improvement, but can be unreliable. Semi-parametric bootstrap approach is accurate in moderate and larger samples.