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Introduction to Econometrics
Course: Economics 421/521
Professor: Mark Thoma
Office/Hours: PLC 471 on M/W 3:304:30 p.m.
Phone/Email: (541) 3464673, mthoma@uoregon.edu
Web Page: http://economistsview.typepad.com/economics421/
Course Description: This course is a continuation of the econometrics sequence. The first course, EC 420/520, introduces the linear regression model and discusses estimation and testing under (mostly) ideal conditions. This course looks at what happens when the conditions are less than ideal due to departures from the assumptions necessary for ordinary least squares to be the best linear unbiased estimator, and then provides alternative regression techniques that address problems arising from the violations of the basic assumptions.
Text: Dougherty, Christopher, Introduction to Econometrics, 3rd ed. (Oxford: University Press, 2007)
Prerequisites: Economics 420 or the equivalent.
GTFs, Office Hours, Location, and Email Address:
Matt Cole  Hours: W 1011 
PLC 520  mcole@uoregon.edu 
Lab Times:
Lab  21820  16001720  Thu  442 MCK 
Lab  21821  18001920  Thu  442 MCK 
Tests and Grading: There will be a midterm exam and a final. The midterm will be given Monday, February 9th. The final will be given on Tuesday, March 17th at 3:15 p.m. No makeup exams will be given. The midterm is worth 30% and the final is worth 40%. Grades will be assigned according to your relative standing in the class.
Empirical Project: There will be an empirical paper that will comprise 15% of your grade. The paper is due no later than Wednesday, March 11 at the beginning of class. Details will be given during lecture.
Computer Labs: The statistical software package EViews will be used for estimation and testing. Labs will consist of instruction and examples helpful in completing the homework assignments, and other activities. The homework is worth 15% of your grade.
*Tentative* Course Outline:
We will cover the following chapters: 

Review of Multiple Regression and Hypothesis Testing  
Heteroscedasticity  Ch. 7 
Autocorrelation  Ch.12 
Stochastic regressors and measurement errors  Ch. 8 
Simultaneous Equations Estimation  Ch. 9 
And, as time permits: 

Binary Choice Models and Maximum Likelihood Estimation  Ch. 10 
Models Using Time Series Data  Ch. 11 
More details on the readings, homework, homework due dates, etc. will be posted here on an ongoing basis, so please check back regularly.