Several process parameters affect product reliability. Traditional reliability improvement methods primarily focus on maximizing product lifetime, often overlooking the variation in product lifetime. Manufacturers, however, aim to produce products with minimal variations in their performance....

The presence of autocorrelated financial returns has major implications for investment decisions. Unsurprisingly, therefore, numerous studies have sought to shed light on whether returns are autocorrelated or not, to what extent, and when. Standard tests for autocorrelation rely on the...

We study the impact of a teacher strike on students still in compulsory school and about to choose their secondary education track. Using administrative data and a difference-in-differences approach, we estimate the effect of a regional strike in Finland on educational attainment and long-term...

The original study by Graham et al. (2024) investigated whether loneliness changes with age across the adult lifespan, synthesizing data from nine longitudinal studies via meta-analyses. The primary finding was that loneliness follows a U-shaped trajectory: decreasing from young adulthood to...

In this study, we address the ambiguity in portfolio optimization, particularly focusing on the uncertainty related to the statistical parameters governing asset returns. We propose a novel method that combines robust optimization with artificial neural networks (ANNs). Our approach effectively...

Cox et al. (2023) investigated the acoustic features of infant-directed speech. They used Bayesian meta-analyses to investigate five acoustic features with data from 88 studies. In the present robustness reproduction, we first check if the reported results are reproducible based on the data and...

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,...

The present note provides an initial theoretical explanation of the way norm regularizations may provide a means of controlling the non-asymptotic probability of False Dominance classification for empirically optimal portfolios satisfying empirical Stochastic Dominance restrictions in an iid...

In this paper, we propose a novel optimization model for portfolio selection that integrates the classical mean-variance criterion with a second-order Tsallis entropy term. This approach enables a trade-off between expected return, risk, and diversification, extending Markowitz's theory to...

How should researchers adjust for covariates? We show that if the propensity score is estimated using a specific covariate balancing approach, inverse probability weighting (IPW), augmented inverse probability weighting (AIPW), and inverse probability weighted regression adjustment (IPWRA)...

How should researchers adjust for covariates? We show that if the propensity score is estimated using a specific covariate balancing approach, inverse probability weighting (IPW), augmented inverse probability weighting (AIPW), and inverse probability weighted regression adjustment (IPWRA)...

Wage growth is a key indicator of labor market conditions, but common measures often conflate individual wage changes with shifts in workforce composition. This paper develops a composition-adjusted measure of wage growth using nonparametric decomposition and program evaluation methods. The...

Multi-Criteria Decision-Making (MCDM) methods, particularly TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and VIKOR (VIsekriterijumska optimizacija i KOmpromisno Resenje) (Multicriteria Optimization and Compromise Solution), are extensively used in logistics for...

Recent advances in healthcare technologies have led to the availability of large amounts of biological samples across several techniques and applications. In particular, in the last few years, Raman spectroscopy analysis of biological samples has been successfully applied for early-stage...

Uncertainty is critical in bulk terminals because it is inherent to many operations. In particular, the berth allocation problem (BAP) is greatly affected by the uncertain arrival times of the vessels. In this paper, we propose the first distributionally robust optimization (DRO) model for the...