Structural estimation in economics often makes use of models formulated in terms of moment conditions. While these moment conditions are generally well-motivated, it is often unknown whether the moment restrictions hold exactly. We consider a framework where researchers model their belief about...

Difference-in-differences (DiD) is one of the most popular approaches for empirical research in economics, political science, and beyond. Identification in these models is based on the conditional parallel trends assumption: In the absence of treatment, the average outcome of the treated and...

Meningococcal meningitis is a deadly acute bacterial infection caused by the Neisseria meningitidis bacterium that affects the membrane covering the brain and spinal cord. The World Health Organization launched the "Defeating bacterial meningitis by 2030" initiative in 2018, which relies on...

We critically assess an almost universal Benefit-Cost Analysis (BCA) practice. In addition to the central Net Present Value (NPV), analysts frequently also report multiple additional values in what is commonly referred to as ‘NPV sensitivity analysis’. This practice is generally justified...

Building on a recently developed methodology for sensitivity analysis that parametrizes omitted variable bias in terms of partial R2 measures, I propose a simple statistic to capture the severity of omitted variable bias in any observational study: the probability of omitted variable bias...

Covariate benchmarking is an important part of sensitivity analysis about omitted variable bias and can be used to bound the strength of the unobserved confounder using information and judgments about observed covariates. It is common to carry out formal covariate benchmarking under the...

Covariate benchmarking is an important part of sensitivity analysis about omitted variable bias and can be used to bound the strength of the unobserved confounder using information and judgments about observed covariates. It is common to carry out formal covariate benchmarking after...

SimDec is a revolution in decision-making support. SimDec "teases out" inherent cause-and-effect relationships and reveals the intricacy of relationships between sets of input and output variables. At its core, SimDec is an amalgamation of uncertainty and global sensitivity analysis with an...

Structural estimation in economics often makes use of models formulated in terms of moment conditions. While these moment conditions are generally well-motivated, it is often unknown whether the moment restrictions hold exactly. We consider a framework where researchers model their belief about...

This study develops a holistic framework for assessing risks in sustainable supply chain innovation (SSCI) within Jordan's garment, textile, and leather (GTL) industry, addressing critical challenges posed by demand volatility, customer concentration, and price competition. Using multi-criteria...

Prevailing methods for measuring sensitive outcomes confront researchers with an inherent bias-variance trade-off: direct questioning is prone to a sensitivity bias, while indirect methods such as list experiments are substantially less precise. We introduce the ballot-bag, a novel technique...

Difference-in-differences (DiD) is one of the most popular approaches for empirical research in economics, political science, and beyond. Identification in these models is based on the conditional parallel trends assumption: In the absence of treatment, the average outcome of the treated and...

Signed supply chain networks are essential for representing relationships between entities in commercial activities. Imbalances in these relationships can lead to significant consequences, including financial losses and reputational damage. This paper presents a two-layer analytical framework...

"SimDec is a revolution in decision-making support. SimDec "teases out" inherent cause-and-effect relationships and reveals the intricacy of relationships between sets of input and output variables. At its core, SimDec is an amalgamation of uncertainty and global sensitivity analysis with an...

The adverse effects of carbon emissions have garnered significant attention from the international community. Against this backdrop, China has set the dual carbon target and taken concrete actions to achieve it. This study integrates Shared Socioeconomic Pathways with machine-learning...

This study aims to design and optimize a Photovoltaic/Diesel/Battery hybrid energy system to provide a stable and sustainable electricity supply for the University Institute of Technology Fotso Victor in Bandjoun, Cameroon, which currently suffers from frequent power outages. The main objective...

Uncertainty about the choice of identifying assumptions is common in causal studies, but is often ignored in empirical practice. This paper considers uncertainty over models that impose different identifying assumptions, which can lead to a mix of point‐ and set‐identified models. We propose...

We propose a framework for estimation and inference when the model may be misspecified. We rely on a local asymptotic approach where the degree of misspecification is indexed by the sample size. We construct estimators whose mean squared error is minimax in a neighborhood of the reference model,...

The study aims to present from a technical-economic point of view aspects related to the cost behaviour, according to the cost-volume-profit analysis model and the sensitivity analysis, of cereal products (maize and wheat) grown in conventional and organic farming systems. In Romania, according...

We critically assess an almost universal Benefit-Cost Analysis (BCA) practice. In addition to the central Net Present Value (NPV), analysts frequently also report multiple additional values in what is commonly referred to as 'NPV sensitivity analysis'. This practice is generally justified with...

Building on a recently developed methodology for sensitivity analysis that parametrizes omitted variable bias in terms of partial R2 measures, I propose a simple statistic to capture the severity of omitted variable bias in any observational study: the probability of omitted variable bias...

Aim: The study examined the behavior of exchange rate in ASEAN countries. This was highly necessitated in order to account for the structural break in the data set occasioned by global financial crisis. Research method: The quantile regression sensitivity analysis was performed on daily series...

Chlamydiosis remains a major public health concern in both developed and developing countries due to its effects on the human reproductive system. While limited modeling studies have been conducted on the transmission dynamics of the disease, none of them have examined the impacts of the...

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...

Vaccine boosters have been recommended to mitigate the spread of the coronavirus disease 2019 (COVID-19) pandemic. A mathematical model with three vaccine doses and susceptibility is formulated. The model is calibrated using the cumulative number of hospitalized cases from Alberta, Canada....