Regression analysis, focusing on departures from the standard Gauss-Markov assumptions, and simultaneous equations. Regression topics include heteroskedasticity, serial correlation, and errors in variables, generalized least squares, nonlinear regression, and limited dependent variable models. Covers identification and estimation of linear and nonlinear simultaneous equations models. Economic applications are discussed. Enrollment limited.
This class has 14.381 as a prerequisite.
14.382 will be offered this semester (Spring 2017). It is instructed by V. Chernozhukov.
Lecture occurs 2:30 PM to 4:00 PM on Mondays and Wednesdays in E51-149.
This class counts for a total of 12 credits.
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