Averaging Quantiles, Variance Shrinkage, and Overconfidence
Averaging quantiles as a way of combining experts' judgments is studied both mathematically and empirically.
Averaging quantiles as a way of combining experts' judgments is studied both mathematically and empirically. Quantile averaging is equivalent to taking the harmonic mean of densities evaluated at quantile points. A variance shrinkage law is established between equal and harmonic weighting. Data from 49 post‐2006 studies are extended to include harmonic weighting in addition to equal and performance‐based weighting. It emerges that harmonic weighting has the highest average information and degraded statistical accuracy. The hypothesis that the quantile average is statistically accurate would be rejected at the 5% level in 28 studies and at the 0.1% level in 15 studies. For performance weighting, these numbers are 3 and 1, for equal weighting 2 and 1.
Journal Article — Oct 19, 2022
A Retrospective Assessment of COVID-19 Model Performance in the USA
This study presents a worthwhile method for appropriately assessing the performance of probabilistic forecasts and can potentially improve both public health decision-making and COVID-19 modeling.
Journal Article — Oct 3, 2022
Ice Sheet and Climate Processes Driving the Uncertainty in Projections of Future Sea Level Rise
The authors' findings identify key processes and factors that need to be addressed in future modeling and observational studies in order to reduce uncertainties in ice sheet projections.
Journal Article — Jun 27, 2022
Price-Responsive Allowance Supply in Emissions Markets
This paper proposes an efficient, effective way to determine the true cost of environmental goods: "price-responsive supply," which sets pollution allowances by assessing price and quantity together.
Journal Article — Apr 20, 2022
Mortality Attributable to Long-Term Exposure to Ambient Fine Particulate Matter: Insights from the Epidemiologic Evidence for Understudied Locations
This review discusses the association between long-term exposure to ambient fine particles (PM2.5) and mortality in understudied locations.