Kevin D. Dayaratna, PhD is an applied statistician whose work lies at the intersection of public policy, economics, and advanced statistical modeling. He serves as the Vice President of the Center for Statistical Modeling and Scientific Analysis in Policy at Advancing American Freedom, where he leads research applying rigorous quantitative methods to some of the most consequential policy debates facing the United States.
Prior to joining AAF, Dr. Dayaratna served as Director of the Center for Data Analysis and Chief Statistician at The Heritage Foundation, where he built and applied high-powered quantitative models to evaluate major policy questions across energy, climate, health care, taxation, and social policy. In that role, he oversaw the development and use of a wide array of policy models, including tax, entitlement, energy, climate, and economic simulation frameworks.
Dr. Dayaratna specializes in modern statistical and econometric methods—including Bayesian modeling, simulation techniques, and large-scale policy models—to assess real-world outcomes and tradeoffs. His research – published both as policy papers as well as in the peer-reviewed literature – has been recognized at the highest levels of government, including by the U.S. Congress, the White House, and the Supreme Court of the United States, and has been cited by policymakers, courts, and major media outlets. He has testified at both the federal and state levels, regularly briefs lawmakers in Congress and state legislatures, and has provided policy briefings to senior officials across the executive branch, including at the White House.
A central focus of Dr. Dayaratna’s work has been energy and climate policy. During the Obama administration, he identified significant flaws in federal climate modeling frameworks, contributing to increased transparency and public accountability in how these models were developed and used. His research on the Social Cost of Carbon (SCC) became a centerpiece of the conservative pushback against its use in regulatory policy, emphasizing model uncertainty, embedded assumptions, and the risks of treating the SCC as a precise and policy-ready metric. This work culminated in, among other efforts, a formal public comment to the Office of Management and Budget co-signed by more than fifteen state attorneys general, which drew heavily on and extensively referenced Dr. Dayaratna’s SCC research, underscoring the national and legal significance of the issue.
Beyond energy and climate, Dr. Dayaratna has conducted research across a wide range of policy areas, including health care, taxation, Social Security, labor markets, public health, election integrity, criminal justice reform, and counterterrorism. He began his career at The Heritage Foundation as a Graduate Fellow in health policy, publishing research comparing outcomes under Medicaid and private insurance and examining the role of market-based reforms in health care, before expanding his work to other domains unified by a common analytical approach: rigorous statistical evaluation of how policies function in practice rather than how they are described in theory.
Dr. Dayaratna is a recognized speaker both domestically and internationally, and he regularly presents his work to policymakers, academics, and public audiences. He also serves as an Associate Editor of the peer-reviewed journal Statistics and Public Policy, contributing to the advancement of rigorous quantitative standards in policy-relevant research. In addition to his policy work, Dr. Dayaratna has taught mathematics, statistics, data science, and economics at the University of Maryland, Georgetown University, and The George Washington University, with an emphasis on applied modeling, computational methods, and data-driven analysis. He has mentored dozens of students and early-career researchers, many of whom have gone on to careers in policy analysis, academia, and data science. Interested students are encouraged to apply to AAF’s internship program to work directly on quantitative policy research.
Dr. Dayaratna earned his PhD in
Mathematical Statistics from the University of Maryland, with concentrations in
Bayesian modeling and statistical computing. He also holds two master’s degrees
from the University of Maryland—in Mathematical Statistics and in Business and
Management—and a bachelor’s degree in Applied Mathematics from the University
of California, Berkeley, with a specialization in mathematical physics. Outside
of his professional work, Dr. Dayaratna is an avid lifelong tennis player and has
recently also taken up swimming. He also enjoys cooking international cuisines,
exploring mathematical ideas, analyzing data from many other fields, and
following professional sports.