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Economics

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Designing Accountable Software Systems

he Designing Accountable Software Systems (DASS) program solicits foundational research aimed towards a deeper understanding and formalization of the bi-directional relationship between software systems and the complex social and legal contexts within which software systems must be designed and operate.

Deadline: 

Monday, April 19, 2021

Economic Institutions, Behavior, & Performance

To support rigorous and objective research projects on U.S. economic structure, behavior, and performance whose findings inform and strengthen decision-making by regulators, policymakers, and the public.

Williams Institute’s LGBTQ & Racial Justice Small Grants Program

The Williams Institute’s LGBTQ & Racial Justice Small Grants Program aims to encourage new research on LGBTQ populations, with a particular focus on emerging issues at the intersections of race, sexual orientation, and gender identity. The Program is designed to support work that will have a direct impact on law and policy.

Deadline: 

Friday, March 19, 2021

U.S. Household Food Security Measurement

To mark the 25th anniversary of U.S. household food security measurement, the U.S. Department of Agriculture’s Economic Research Service (USDA ERS) will fund a suite of competitive grants on food security measurement methods, data, and future research needs. The selection and coordination of the projects will be managed by an external cooperator, a collaboration between Tufts University (Dr. Parke Wilde) and the University of Missouri (Dr. Irma Arteaga).

Deadline: 

Friday, February 19, 2021

Mid-Career Advancement

An academic career often does not provide the uninterrupted stretches of time necessary for acquiring and building new skills to enhance and advance one’s research program. Mid-career scientists in particular are at a critical career stage where they need to advance their research programs to ensure long-term productivity and creativity but are often constrained by service, teaching, or other activities that limit the amount of time devoted to research.

Deadline: 

Monday, February 7, 2022
Monday, February 6, 2023
Monday, February 5, 2024
Monday, February 3, 2025

Pipeline Grants Competition

The Russell Sage Foundation, in partnership with the Economic Mobility and Opportunity program at the Bill & Melinda Gates Foundation, seeks to advance innovative research on economic mobility and access to opportunity in the United States. We are interested in research focused on structural barriers to economic mobility and how individuals, communities, and governments have come to understand, navigate, and challenge the existence of systemic inequalities.

Deadline: 

Thursday, November 4, 2021

Doctoral Dissertation Research in Economics: The Social Dimension of Quality

Why do consumers willingly pay more for brand name products compared to non-branded products even though the two have the same attributes. This doctoral dissertation research in economics (DDRIE) research project will use economic theory and experimental methods to investigate the social network source of value for a product. The researchers argue that people pay more for a product to signal prestige or because people they look up to consume that product. The researchers will collect data on a number imported and domestically produced consumer goods to test this theory.

Collaborative Research: Veto Bargaining: Delegation and Non-Coasian Dynamics

This award funds research on the topic of veto bargaining. Veto bargaining concerns situations in which one agent or group can make proposals but another must approve them. Applications can be found in many areas of the social sciences: legislatures (e.g., U.S.

Factor Based Imputation of Missing Data

Missing observations occur in physical and social science research; Missing observations may arise from people not responding to question,; changes in data definitions, technology of data collection, and natural disasters and wars, among others. Many methods have been proposed to impute the missing observations; these methods often impose restrictive assumptions about the nature of the missing values, with missing at random being the most common. Though they work well in practice, the theoretical properties of the imputed data are not well understood.

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