Econometrics

3-0-3 units · Graduate

Covers key models as well as identification and estimation methods used in modern econometrics. Presents modern ways to set up problems and do better estimation and inference than the current empirical practice. Introduces generalized method of moments and the method of M-estimators in addition to more modern versions of these methods dealing with important issues, such as weak identification. Also discusses the bootstrap. Students gain practical experience by applying the methods to real data sets. Enrollment limited.

Spring 2017

The course will cover several key models as well as identification and estimation methods used in modern econometrics. We shall being with exploring some leading models of econometrics, then seeing structures, then providing methods of identification, estimation, and inference. You will get lots of hands-on experience with using the methods on real data sets.

Readings

There is no particular text that we shall follow. For each theme, we will post readings. There is a free online version of Bruce Hanse’s Econometrics text. Other nice texts include Wooldridge’s grad text, Econometric Analysis of Cross Section and Panel Data , 2nd edition; Hayashi’s Econometrics , and Cameron and Trivedi’s Microeconometrics . I can’t really say which one you should buy. We also highly recommend Van der Vaart’s text called Asymptotic Statistics to those planning to specialize in econometrics. ↗
Listed reading

Prerequisites & course information

Prereq: 14.381 or permission of instructor G (Spring; first half of term) 3-0-3 units

Sources

Course catalogue ↗2026–2027
MIT OpenCourseWare ↗Spring 2017
MIT OCW syllabus ↗
Historical MIT OpenCourseWare offering. Named reading entries and schedule topics are automatically extracted from the linked source pages.