Kevin D. Hoover
- 203-D West Duke Building
- Campus Box 90097
- Phone: +1 919.660.2425 or +1 919.660.1876
- Fax: 919.660.3060
- Office Hours: No office hours Fall 2006 semester.
Macroeconomics, Monetary Economics;
Philosophy and Methodology of Empirical Economics;
History of Economic Thought.
The structure of vector autoregression models; causality in macroeconomics, specification search methodologies; the history of 20th century macroeconomics.
History of Economic Thought
Associate Editor, Journal of Economic Methodology
Editor, Journal of Economic Methodology (1996-2005)
Associate Editor, Journal of Economic Surveys
Editorial Board, Economics and Philosophy
Board of Editors, Review of Political Economy
Board of Editors, American Economic Review (1990-1994)
President, History of Economics Society (2002-2003)
Chairman, International Network for Economic Method (1999-2001)
International Network for Economic Method (Founding Member)
American Economics Association
History of Economics Society
British Society for the Philosophy of Science
Professor Hoover's research interests include macroeconomics, monetary economics, the history of economics, and the philosophy and methodology of empirical economics. His recent work in economics has focused on the application of causal search methodologies for structural vector autoregression, the history of microfoundational programs in macroeconomics, and Roy Harrod's early work on dynamic macroeconomics. In philosophy, he has concentrated on issues related to causality, especially in economics, and on reductionism -- the philosophical counterpart to microfoundations. Recently published papers include: He has conducted studies to investigate the history of twentieth century macroeconomics, the structure of vector auto-regression models, and causality in macroeconomics examined via specification search methodologies. Recent working papers include: “Still Puzzling: Evaluating the Price Puzzle in an Empirically Identified Structural Vector Autoregression,” “Was Harrod Right?” "Identity, Structure, and Causal Representation in Scientific Models."