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...

We propose a methodology to construct tests for the null hypothesis that the pricing errors of a panel of asset returns are jointly equal to zero in a linear factor asset pric- ing model - that is, the null of "zero alpha". We consider, as a leading example, a model with observable, tradable...

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...

Textbook theory predicts that t-ratios decline towards zero in regressions when there is increasing collinearity between two independent variables. This article shows that this rarely happens if the two variables are endogenous, and coefficients increase greatly with more collinearity. The...

In this paper, a beta transform of multivariate normal datasets is obtained. The phi divergence measure, DΦ(F,G) between two distributions F and G is used to obtain a goodnessof-fit test to multivariate normality (MVN) based on the theoretical density function of the beta transformed random...

Value-at-Risk (VaR) is a key metric widely applied in market risk assessment and regulatory compliance under the Basel III framework. This study compares two Monte Carlo-based VaR models using publicly available equity data: a return-based model calibrated to historical portfolio volatility, and...

Because finite sample inference for inequality indices based on asymptotic methods or the standard bootstrap does not perform well, Davidson and Flachaire (Journal of Econometrics, 2007) and Cowell and Flachaire (Journal of Econometrics, 2007) proposed inference based on semiparametric methods...

To address a key issue in functional time series analysis on testing the randomness of an observed series, we propose an IID test for functional time series by generalizing the Brock-Dechert-Scheinkman (BDS) test, which is commonly used for testing nonlinear independence. Similarly to the BDS...

We propose the double robust Lagrange multiplier (DRLM) statistic for testing hypotheses specified on the minimizer of the population continuous updating objective function. The (bounding) χ2 limiting distribution of the DRLM statistic is robust to both misspecification and weak identification,...

This paper focuses on the estimation and testing of multiple breaks that occur at unknown dates in multivariate long memory time series regression models, allowing for fractional cointegration. A likelihood-ratio based approach for estimating the breaks in the parameters and in the covariance of...

This paper studies the limiting behavior of the test for instrument exogeneity in linear models when there is uncertainty about the strength of the identification signal. We consider the test for conditional moment restrictions with an expanding set of constructed instruments. We establish the...

Spatial unit roots can lead to spurious regression results. We present a brief overview of the methods developed in Müller and Watson (2024) to test for and correct for spatial unit roots. We also introduce a suite of Stata commands (-spur-) implementing these techniques. Our commands exactly...

We develop a test for mean stationarity of latent volatility curves using high-frequency data. To derive the asymptotic test size and power, we establish a functional invariance principle for semimartingales under a strong mixing condition. The power properties are analyzed under alternatives...

Forecasting natural gas demand is critical for enhancing energy efficiency, optimizing infrastructure planning, and supporting Tunisia's transition toward sustainable energy. As the fastest-growing fossil fuel and one of the cleanest among non-renewable energy sources, natural gas plays a...

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....