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EC 200: Econometrics
This course focuses on the use of econometric techniques in economic research. Students should have completed introductory statistics, intermediate micro and macroeconomics. These prerequisites are essential given that econometrics is primarily designed to identify and evaluate causal relationships derived from economic theory. Econometrics can also be used to forecast correlated variables when policy intervention is not the objective. Econometric models also involve the application of basic statistical concepts such as sample spaces, probability and hypothesis testing, typically covered in introductory statistics. The course covers the design of econometric models, data collection, estimation, and interpretation of results with the goal of understanding how economists use econometric methods to adduce evidence in support of hypotheses. This course will not cover time series econometrics, which is currently offered and can be taken concurrently.
Stata : is the software required for the course. Any version of the program is acceptable, so if you already own a copy or get it from some other source this is fine. The cheapest is Small Stata (the student version) but you may have some issues with this since it will not handle some of our homework assignments. Library computers at UVM have the full version of Stata so you might be able to use Small Stata and do the large assignments in the library. If you prefer, order Stata/IC 12 which will handle everything we will do but is a bit more expensive. Students are able to order online with the Grad Plan ID using code BG200. See below for recommended texts for using Stata.
Paper: The paper is an original research project that begins with the replication of an existing study. Students are assigned articles for which data is available for replication. Once replicated the next step is to extend the data set to most recent data available. The value added of the paper is the to determine whether the author's conclusion remain valid when updated. Papers will be graded on how well the research is presented, relevance of the model, the adequacy of the data set and how possible objections are anticipated and dealt with. A good paper need not be at the frontiers of econometric sophistication, but will be well researched, documented and formatted according to instructions given in class. See below for dates for first and final drafts of the paper. No late papers accepted. Papers must have an abstract (of 150) words, an introduction (250 words), a brief literature review (250 words), a discussion of the relevant economic theory (250 words), a data summary, (250 words) an in-depth econometric analysis (1000 words), interpretation and evaluation (1000 words) conclusions (250 words) and references. The paper should be prepared in LaTeX (highly advisable) or Word (less advisable but acceptable).Homework assignments: will be done in Excel and submitted electronically using the format: student_number.xls. The homework you submit must be your own. If two spreadsheets are found to be identical, both students will get zeros for the assignment.
Grading: Midterm exam, final exam, original research paper, homework. All worth 25 percent of the final grade.
Part 1: Classical Linear Regression ModelJan 15-29 Reading: Chapters 4-5. Stock and Watson, Chapter 4.
Part 2: Linear regressors with multiple regressors, hypothesis testing and nonlinear regressionFeb 5-26: Reading: Chapter 6-9.
MidtermThurs 28 Feb, covering all readings and class material to date.
Part 3: Panel Data, Binary Dependent Variable and Instrumental VariablesMar 9-Apr 15. Reading: Chapters 10-13.
Paper due22 Apr midnight, submitted as student_number.docx
Final ExamTUE 05/07/2013 04:30 - 05:45pm Gibson Comprehensive--1 hr and 15 minutes.
UVM Final exam schedule-Spring 2013
Office Hours: 1:00-2:00pm TTh and by appt.