Jeffrey Wooldridge
University Distinguished Professor of Economics | Michigan State University
East Lansing, MI, UNITED STATES
Expert in education financing, econometrics, and longitudinal data analysis
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Biography
Jeffrey Marc Wooldridge (born 1960) is an American econometrician at Michigan State University. He is known for his theoretical contributions to analysis of cross-sectional and panel data.
After graduating in computer science and economics from the University of California, Berkeley in 1982, Wooldridge earned a Ph.D. in economics from the University of California, San Diego in 1986. He spent five years as an assistant professor of economics at the Massachusetts Institute of Technology, before joining faculty at Michigan State University, where he became a professor in 1993. He was designated University Distinguished Professor in 2001.[1]
Wooldridge is a Fellow of the Econometric Society and of the Journal of Econometrics. He is also known as the author of the popular econometrics textbooks Introductory Econometrics: A Modern Approach (6th edition, 2016) and Econometric Analysis of Cross Section and Panel Data (2nd edition, 2010).
Areas of Expertise (3)
Longitudinal Data Analysis
Educational Financing
Econometrics
Accomplishments (3)
Founding Fellow , IAAE, (professional)
January 2018
ournal of Business and Economic Statistics Invited Paper (professional)
2017
President - elect, Midwest Economics Association (professional)
2009-2010
Education (2)
University of California: Ph.D., Economics 1986
University of California: B.A., Computer Science, Economics 1982
Affiliations (3)
- American Economic Association
- Econometric Society
- Midwest Economics Association
Journal Articles (3)
Understanding error structures and exploiting panel data in meta-analytic benefit transfers
Environmental and Resource EconomicsKevin J Boyle, Jeffrey M Wooldridge
2018 A regression meta-analysis is a statistical summary of results from a set of empirical studies. While, a meta-analysis is typically used to drawn inferences regarding the collective insights from an empirical literature, a regression meta-analysis can also be used to predict outcomes as a substitute for the conduct of a new study. Within the nonmarket-valuation literature benefit transfers are a special case of prediction where value estimates collected for one purpose are used as a basis for predicting value for unstudied applications...
Binary response panel data models with sample selection and self‐selection
Journal of Applied EconometricsAnastasia Semykina, Jeffrey M Wooldridge
2018 We consider estimating binary response models on an unbalanced panel, where the outcome of the dependent variable may be missing due to nonrandom selection, or there is self‐selection into a treatment. In the present paper, we first consider estimation of sample selection models and treatment effects using a fully parametric approach, where the error distribution is assumed to be normal in both primary and selection equations. Arbitrary time dependence in errors is permitted.
Does the precision and stability of value-added estimates of teacher performance depend on the types of students they serve?
Economics of Education ReviewBrian Stacy, Cassandra Guarino, Jeffrey Wooldridge
2018 In this paper, we investigate how the precision and year-to-year stability of a teacher's value-added estimate relate to student characteristics. We find that teachers serving initially higher performing students have more precise value-added estimates and in most cases have higher year-to-year stability levels than teachers with lower performing students. We also decompose the variation in value-added estimates into components that reflect persistent and transitory variation in true teacher performance as well as variation caused by imprecision in the estimates...
