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| David N. MacKinnon | |
|---|---|
| Name | David N. MacKinnon |
| Birth date | 1949 |
| Birth place | Boston, Massachusetts |
| Nationality | American |
| Occupation | Economist |
| Alma mater | Harvard University; Massachusetts Institute of Technology |
| Employer | Dartmouth College; National Bureau of Economic Research |
David N. MacKinnon is an American economist noted for contributions to econometrics, statistical inference, and empirical methods in applied economics. He has held faculty positions at prominent institutions and collaborated with leading scholars on methodology that bridges theoretical statistics and empirical practice. His work influenced policy analysis, labor studies, and macroeconomic measurement through improved testing procedures and robust inference techniques.
MacKinnon was born in Boston and raised in the New England region, where he attended preparatory schools before matriculating at Harvard University for undergraduate studies. He pursued graduate work at the Massachusetts Institute of Technology and completed doctoral research that engaged with the statistical traditions of scholars at Cowles Commission-influenced departments and the methodological currents from Econometric Society meetings. During his formative years he interacted with faculty and graduate students associated with Kenneth Arrow, Paul Samuelson, James Tobin, Robert Solow, and visiting researchers from University of Chicago seminars, situating his training amid debates over identification and testing in econometrics.
MacKinnon's academic appointments included tenure-track and visiting roles at major research universities, culminating in a long-term professorship at Dartmouth College. He participated in research networks such as the National Bureau of Economic Research and presented papers at gatherings sponsored by the American Economic Association, Royal Economic Society, and the European Economic Association. MacKinnon also held visiting scholar positions at institutions including Princeton University, Stanford University, University of California, Berkeley, and international centers such as the London School of Economics and the Centre for Economic Policy Research. He served on editorial boards of leading journals associated with the Econometric Society, Journal of Econometrics, and the Review of Economic Studies.
MacKinnon’s research focused on finite-sample properties of estimators, bootstrap methods, and the construction of robust hypothesis tests, engaging with traditions established by John Tukey, Jerzy Neyman, Egon Pearson, and later refinements from Bradley Efron and Donald Rubin. He developed testing procedures that addressed size distortions in small samples, building on work by Clive Granger, Christopher Sims, and Robert Engle on time-series inference. His advances in bootstrap techniques connected to practical applications in studies by scholars at National Bureau of Economic Research programs on business cycles, and informed empirical work by researchers at Brookings Institution and Federal Reserve Board staff.
MacKinnon produced influential results on cointegration testing and inference that interacted with the literature of Robert F. Engle and Clive W.J. Granger and methods used in applied macroeconomics at institutions like International Monetary Fund and World Bank. He contributed to the theoretical underpinnings of hypothesis testing under weak identification, aligning with innovations by James Stock and Mark Watson on inference in instrumental variable settings. His methodological contributions have been used by labor economists analyzing data from Bureau of Labor Statistics surveys and by public policy analysts working with datasets from Organisation for Economic Co-operation and Development and national statistical agencies.
MacKinnon authored and coauthored numerous articles in journals affiliated with the Econometric Society, American Economic Association, and specialized outlets in statistics and econometrics. His textbook and monographs on econometric methods and hypothesis testing integrated mathematical rigor with applied examples familiar to scholars at Harvard University, MIT, and Dartmouth College. He collaborated with prominent coauthors connected to the National Bureau of Economic Research and contributed chapters to volumes edited by figures from the Institute of Mathematical Statistics and the Royal Statistical Society. His work appears in compendia alongside contributions from G. S. Maddala, Tom Sargent, Halbert White, and Whitney Newey.
MacKinnon received recognition from professional societies including fellowships and awards associated with the Econometric Society, the American Statistical Association, and research grants from organizations such as the National Science Foundation and foundations that fund social science methods. He gave invited lectures at venues like the Cowles Foundation workshop, the Institute for Advanced Study, and plenary sessions of the Royal Economic Society. His methodological papers were cited in award-winning empirical studies from think tanks such as Brookings Institution and policy departments at the Federal Reserve Bank of New York.
Outside academia, MacKinnon engaged with community institutions in the New England area and contributed to outreach linking universities such as Dartmouth College to regional economic development organizations and historical societies. His legacy is reflected in the adoption of his testing protocols in graduate curricula at Princeton University, Yale University, Columbia University, and in applied work at agencies including the U.S. Census Bureau. Students and collaborators who trained under him went on to positions at University of Chicago, London School of Economics, University of California, Los Angeles, and international policy institutions, perpetuating his influence on empirical practice and methodological standards.
Category:American economists Category:Econometricians