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...

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....

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 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...

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...

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...

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...

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...

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...

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...

This paper introduces and analyses a setting with general heterogeneity in regression modelling. It shows that regression models with fixed or time-varying parameters can be estimated by OLS or time-varying OLS methods, respectively, for a very wide class of regressors and noises, not covered by...

Guinaudeau and Jankowski reassess our recent study on the use of strategic descriptive representation among political parties in Europe. The authors successfully replicate the vast majority of our findings and perform a number of additional robustness checks. They claim that one of our key...

This paper presents new results on the identification of heteroskedastic structural vector autoregressive (HSVAR) models. Point identification of HSVAR models fails when some shifts in the variances of the structural shocks are suspected to be statistically indistinguishable from each other....

Using data from the Panel Study of Income Dynamics, we estimate the impact of breastfeeding initiation and duration on multiple cognitive, health, and behavioral outcomes spanning early childhood through adolescence. To mitigate the potential bias from misspecification, we employ a doubly robust...