This paper studies linear time‐series regressions with many regressors. Weak exogeneity is the most used identifying assumption in time series. Weak exogeneity requires the structural error to have zero conditional expectation given present and past regressor values, allowing errors to...

This document summarizes the global process of designing geotechnical structures, as given in the 2nd Generation EN 1997, and highlights the step where the designer must determine representative values for limit state verifications based on ground investigation data. This guideline explains the...

How efficiently do scientific results make their way into the wider world? Applying multiple methods to the universe of hypothesis tests reported in three leading health journals between 2016 and 2022 we evidence the important role of statistical significance as a driver of popular attention to...

How efficiently do scientific results make their way into the wider world? Applying multiple methods to the universe of hypothesis tests reported in three leading health journals between 2016 and 2022 we evidence the important role of statistical significance as a driver of popular attention to...

Walter Andrew Shewhart is regarded as the founder of Statistical Quality Control (SQC), an approach to production inspection based on the application of statistical theory. He developed SQC in the 1920s while working at Bell Telephone Laboratories. During this period, he was tasked with training...

We propose a new way to obtain identification results using order statistics as finite mixtures with two key properties: i) the weights are known integer numbers; and ii) the elements of the mixture are the distributions of the maximum over a subset of the original random variables. We leverage...

This paper presents a distribution-free test, based on the permutation approach, on treatment effects with a multivariate categorical response variable. The motivating example is a typical case-control biomedical study, performed to investigate the effect of the treatment called "assisted motor...

In statistical analysis, evaluating the normality of large datasets is crucial for validating parametric tests, particularly in areas such as Global Navigation Satellite System (GNSS) measurements, where data often exhibit non-normal characteristics resulting from their variability and errors....

Model misspecification in multivariate econometric models can strongly influence estimates of quantities of interest such as structural parameters, forecast distributions or responses to structural shocks, even more so if higher-order forecasts or responses are considered, due to parameter...

Modeling loss data is a crucial aspect of actuarial science. In the insurance industry, small claims occur frequently, while large claims are rare. Traditional heavy-tail distributions, such as Weibull, Log-Normal, and Inverse Gaussian distributions, are not suitable for describing insurance...

The European Dactyloscopy Database (Eurodac) is the large-scale IT system used in the EU for managing asylum applications within the EU+2, as illustrated in Figure 1. The system allows fingerprint comparison and storage, and therefore supports the effective implementation of Regulation (EU) No...

Input-output multipliers are typically calculated as point estimates of the Leontief quantity model. From the previous literature, they can also be estimated (and their confidence intervals) directly from establishments'/industries' inputs and outputs data by running an appropriate econometric...

Economic data are often contaminated by measurement errors and truncated by ranking. This paper shows that the classical measurement error model with independent and additive measurement errors is identified nonparametrically using only two order statistics of repeated measurements. The...

Researchers may want to know whether an observed statistical relationship is either meaningfully negative, meaningfully positive, or small enough to be considered practically equivalent to zero. Such a question can not be addressed with standard null hypothesis significance testing, nor with...

Purpose - This paper aims mainly at introducing applied statisticians and econometricians to the current research methodology with non-Euclidean data sets. Specifically, it provides the basis and rationale for statistics in Wasserstein space, where the metric on probability measures is taken as...

We review tests of null hypotheses that consist of many subsidiary null hypotheses, including tests that have not received much attention in the econometrics literature. We study test performance in the context of specification testing for linear regressions based on a Monte Carlo study....

We forecast recessions in Canada using an autoregressive (AR) probit model. In this model, the presence of the lagged latent variable, which captures the autocorrelation in the recession binary variable, results in an intractable likelihood with a high dimensional integral. Therefore, we employ...

You want to run an experiment where you anticipate finding a treatment effect. How large should your sample size be to have a reasonable chance of detecting significant results? In this manuscript, I present and explain the Stata code I use to address this question. The code uses simulations to...

Bayes' theorem incorporates distinct types of information through the likelihood and prior. Direct observations of state variables enter the likelihood and modify posterior probabilities through consistent updating. Information in terms of expected values of state variables modify posterior...

This paper is inspired by medical studies in which the same patients with multiple sclerosis are examined at several successive visits (doctor's appointments) and described by fractional anisotropy tract profiles, which can be represented as f unctions. Since the observations for each patient...