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...

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...

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....

Many structural econometric models include latent variables on whose probability distributions one may wish to place minimal restrictions. Leading examples in panel data models are individual-specific variables sometimes treated as "fixed effects" and, in dynamic models, initial conditions. This...

This paper studies covariate adjusted estimation of the average treatment effect in stratified experiments. We work in a general framework that includes matched tuples designs, coarse stratification, and complete randomization as special cases. Regression adjustment with treatment‐covariate...

We consider estimation and inference for a regression coefficient in panels with interactive fixed effects (i.e., with a factor structure). We demonstrate that existing estimators and confidence intervals (CIs) can be heavily biased and size-distorted when some of the factors are weak. We...

Numerous robust estimators exist as alternatives to the maximum likelihood estimator (MLE) when a completely observed ground-up loss severity sample dataset is available. However, the options for robust alternatives to a MLE become significantly limited when dealing with grouped loss severity...

Barro et al. (2022) investigate the quantity of safe assets held in the cross-section of developed countries and find that the average safe-asset ratio (ratio of safe assets to total assets) was 37% in 2015 and has remained relatively stable over time. They also document a crowding-out...

We estimate the robustness reproducibility of key results from 17 non-experimental AER papers published in 2013 (8 papers) and 2022/23 (9 papers). We find that many of the results are not robust, with no improvement over time. The fraction of significant robustness tests (p0.05) varies between...

Many structural econometric models include latent variables on whose probability distributions one may wish to place minimal restrictions. Leading examples in panel data models are individual-specific variables sometimes treated as "fixed effects" and, in dynamic models, initial conditions. This...

Ambuehl et al. (2022) explore ways to evaluate interventions designed to enhance decision-making quality when individuals misjudge the outcomes of their choices. The authors propose a novel outcome metric that can distinguish between interventions better than conventional metrics such as...

Alan et al. (2023) carry out a field experiment where they randomly allocate 20 corporations in Turkey to a treatment group or a control group. White-collar employees at the headquarters of the corporations are invited to participate in a training program to improve the workplace environment....

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...

In this study, we evaluate the reproducibility and replicability of Scott Orr's (2022) innovative approach for identifying within-plant productivity differences across product lines. Orr's methodology allows the estimation of plant-product level productivity, contingent upon a well-behaved...

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...

A principal provides incentives for independent agents. The principal cannot observe the agents' actions, nor does she know the entire set of actions available to them. It is shown that an anti-informativeness principle holds: very generally, robustly optimal contracts must link the incentive...