Debasri Mukherjee
Â鶹´«Ã½
1903 W Michigan Ave
Kalamazoo MI 49008-5330 USA
- Ph.D., University of California-Riverside, 2002
- Theoretical and Applied Econometrics
- Nonparametric and semiparametric data-mining and Machine Learning methods, panel data techniques
- Applications of econometric and statistical tools in economic development, international economics and public policy issues related to health, education, environment and immigration
Dr. Debasri Mukherjee is a professor in the Department of Economics at Â鶹´«Ã½.
Mukherjee teaches a broad set of courses in econometrics, statistics and applied economics at the undergraduate, Master’s and Ph.D. level at Â鶹´«Ã½. She teaches advanced Ph.D. level course on panel data, nonparametric econometrics and applied Machine Learning methods. She also teaches undergraduate econometrics (a capstone course for economics majors) and a data exploration and visualization course at the undergraduate level. Mukherjee teaches many statistical aspects of economic data and several computing tools in her courses that can help Â鶹´«Ã½s learn how to analyze real-world economic data. Her teaching also includes economic development and Principles of Microeconomics and Principles of Macroeconomics at the undergraduate level.
Mukherjee is a theoretical and applied econometrician. Her research interest includes nonparametric data mining, applied Machine Learning and Longitudinal data analysis. She has published many articles in peer-reviewed journals including in Journal of Econometrics, Journal of Multivariate Analysis, Journal of Quantitative Economics, Southern Economic Journal, Applied Economics, and Applied Economics Letters. Her theoretical contributions include finding new techniques in nonparametric longitudinal data analysis using kernel smoothing. In her applications Mukherjee has analyzed both macro level longitudinal data and micro level large survey data. The applications include a wide range of topics on poverty and economic development, international economics and public policy issues such as health, education, immigration and environment. The theme of her applied research is examining economic policy questions using advanced data-mining tools. She has supervised several Ph.D. dissertations and published with many Â鶹´«Ã½s.