Project Grant 2341730

This Project Grant award of $194,675 from the National Science Foundation's (NSF) Social, Behavioral, and Economic Sciences (CFDA 47.075) program supports research to develop new econometric and statistical methods that allow researchers to draw valid conclusions from complex data in a variety of social, behavioral, and medical science settings. The key products and services to be delivered include:

• Developing a generally applicable reparameterization procedure for informative identification-robust subvector inference, allowing researchers to plug in estimates of nuisance parameters rather than projecting over them
• Creating new methods for producing valid confidence intervals on the performance of treatments or policies chosen by estimating the identified set of best-performing options
• Producing statistical software to implement the new inference methods, enabling their use by applied researchers
• Advancing theoretical insights for economists, statisticians, and other social/medical scientists
• Improving the efficiency, productivity, and well-being impacts of decision-making in these disciplines, both in the U.S. and globally.

The award has a performance period from July 1, 2024 to June 30, 2027 and will be carried out by the University of Colorado, a U.S. state government institution of higher learning.