Econometrics

Lectures: 2 sessions / week, 1.5 hours / session

Recitations: 1 session / week, 1 hour / session

This course covers the statistical tools needed to understand empirical economic research and to plan and execute independent research projects. Topics include statistical inference, regression, generalized least squares, instrumental variables, simultaneous equations models, and evaluation of government policies and programs.

The prerequisite courses include Introduction to Statistical Methods in Economics (14.30) or equivalent. Students should be familiar with basic concepts in probability theory and statistical inference. The course includes a brief statistics review.

Each week there are two lectures and a weekly recitation.

In addition to the readings, there are 6 graded problem sets and ungraded review problem sets at the beginning and end of the course. The problem sets have both analytical and computer-exercise components. The statistical analysis will be done using Stata or SAS on PCs or MIT workstations. Help for new Stata users will be given in recitation.

Wooldridge, Jeffrey M. Introductory Econometrics: A Modern Approach. 3rd ed. Mason, OH: Thomson/South-Western, 2006. ISBN: 9780324289787.

Goldberger, Arthur S. A Course in Econometrics. Cambridge, MA: Harvard University Press, 1991. ISBN: 9780674175440.

DeGroot, Morris H., and Mark J. Schervish. Probability and Statistics. 3rd ed. Boston, MA: Addison-Wesley, 2001. ISBN: 9780201524888.

Wooldridge is the main text. The material in Goldberger is more advanced and optional. DeGroot and Schervish is a recommended text for statistics review. Each unit also has readings from published journal articles.

Each review problem set is worth 1 bonus percentage point.

Graded problem sets are mandatory and solutions should be submitted on time to receive credit. Stata or SAS logs should be submitted with solution sets. A grade of 50% or better on at least 5 problem sets is required in order to be eligible to take the final. Consult with classmates on problem sets if you get stuck, but written solution sets should be your own work.

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