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Dr. Matthew Higgins is an associate professor in the Department of Economics 51¸£ÀûÉç Michigan University.

He teaches a wide range of courses in statistics and econometrics at the undergraduate, master's and Ph.D. level. His courses emphasize the use of statistical theory to understand contemporary economic issues. His primary course is a Ph.D. field class in econometric theory focusing on time-series analysis. He also teaches a graduate level economic computing class covering the SAS System and the use of the Internet as a research tool.

Higgins also supervises graduate student research. Higgins' research focuses on econometric methods for understanding how uncertainty about the future affects the economy. He has written extensively on the theory of empirical models for asset price volatility and has proposed procedures estimating and testing statistical models of how agents formulate their expectations. He is also interested in developing methods for detecting nonlinear dynamics in equity, and foreign exchange and insurance markets. His most recent research deals with economic forecasting. Higgins has found methods for optimal forecasting when forecast errors have asymmetric costs. He is studying how professional economic forecasters, who use heterogeneous information and models, arrive at a consensus view of the future.