Project Grant 2520365
- The National Science Foundation awarded a $101,598 project grant under the Social, Behavioral, and Economic Sciences (CFDA 47.075) program to the University of Chicago. The grant funds the development of new statistical methods to help researchers, analysts, and policymakers isolate the effects of changes in business and government policies using observational data and natural experiments. Key objectives include: (a) creating computationally simple methods to precisely identify causal...
- 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...
- This $285,000 federal Project Grant award from the National Science Foundation (NSF) Social, Behavioral, and Economic Sciences (SBE) program (CFDA 47.075) will fund research to develop new statistical methods to guide economic and public policy decisions in rapidly changing environments. The research aims to build on recent advances in statistical decision theory, causal inference, and machine learning to create econometric models that can effectively inform evidence-based policymaking while...
- This $350,000 federal Project Grant award from the National Science Foundation's (NSF) Social, Behavioral, and Economic Sciences (CFDA 47.075) program will support the development of new theory and methods for assessing the sensitivity of causal inferences to violations of underlying assumptions in quasi-experimental research designs. The research project aims to create a comprehensive suite of sensitivity analysis tools for popular causal inference techniques such as instrumental variables,...
- This $140,482 Project Grant awarded by the National Science Foundation's Social, Behavioral, and Economic Sciences (CFDA 47.075) program funds research to develop a new methodology that can distinguish between research findings that are generalizable across populations, places, and time, versus those that are context-specific. The research aims to address the fundamental challenge of determining which experimental or observational results can be reliably generalized, in order to improve the...
- This $279,983 National Science Foundation project grant supports research at Brown University to develop hybrid statistical and econometric modeling methods. Funded under the NSF Social, Behavioral, and Economic Sciences program, the three-year award beginning August 2022 aims to advance modeling approaches that account for imperfect data measurement and the reality that models approximate rather than perfectly represent the world. The research will modify method-of-moments techniques to...
- This $309,960 federal Project Grant award from the National Science Foundation's (NSF) Social, Behavioral, and Economic Sciences (CFDA 47.075) program will fund a research project at the University of Chicago to improve the methodology for testing coefficients in linear regressions. The project will develop new test methods that are robust to assumptions about error term distributions and sample size, allowing for more precise coefficient estimates. This research aims to enhance decision-making,...
- This NSF Social, Behavioral, and Economic Sciences (CFDA 47.075) Project Grant award of $572,000 to the National Bureau of Economic Research (NBER) will fund research to develop advanced computational methods for solving heterogeneous-agent macroeconomic models. The research will focus on expanding the capabilities of sequence-space methods to enable the analysis of models with diverse types of heterogeneity, such as location choice and firm-level differences. Key deliverables include new...
- The National Science Foundation (NSF) awarded a $108,000 Project Grant under the Mathematical and Physical Sciences Federal Grant Program (CFDA 47.049) to the University of Illinois for the collaborative research project "Distributional Balancing Methods for Advancing Causal Inference in Complex Settings". The project aims to develop advanced statistical methodologies that improve the reliability of causal conclusions from complex, observational data. Specifically, it will enhance...
- This $175,000 Project Grant award from the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049) will support research on the problem of external validity in causal inference under interference. The project aims to understand how causal conclusions from a sample can be generalized to a broader population, when treatment and outcome spillover effects exist. Key deliverables include software for public use and workshops for high school students, in addition to...
This Project Grant award of $217,250 from the National Science Foundation's Social, Behavioral, and Economic Sciences (CFDA 47.075) program to Trustees of Boston University supports a collaborative research project to develop new statistical methods for isolating the effects of changes in business and government policies and regulations. The key products and services to be delivered under this award include: (a) computationally simple methods for sharp identification of causal parameters, (b) improved estimators for partially identified parameters, (c) computationally reliable methods to derive identifying restrictions, and (d) a publicly available code library that implements these new statistical methods and makes them accessible to researchers, business analysts, and policy analysts conducting program evaluations. The research aims to advance knowledge by developing a unified framework for identification, counterfactual prediction, and specification analyses for potential outcome models. This will be achieved through two main sub-projects, one focused on bounding counterfactuals using random set theory, and the other on deriving sharp testable implications of modeling assumptions in potential outcome models. The award period runs from September 1, 2025 to August 31, 2027.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $217.3k | 8/25/25 |