Prof. Bryan Caplan

http://www.gmu.edu/departments/economics/bcaplan

Econ 637

Fall, 1998

Econometrics Syllabus

Course Focus:

Econometrics lies at the intersection of statistics, economics, and computer science. Essentially, it uses computers to apply statistics to study economics. The primary goal of this course is to introduce you to econometrics and thereby help you become an intelligent consumer of statistics and its application to economics. Throughout the course, there will be a strong effort to keep a good balance between statistics, computing, and economics - but the first part of the course will be weighted more towards statistics, and the second towards economics.

The first part of the course reviews basic statistics, then works out the theory of the most widely used econometric technique, known as *multiple regression analysis*. The second part of the course turns to applications, with four weeks devoted to applying econometrics to four different substantive economic questions.

Prerequisites

You __must__ have competence in basic statistics to succeed in this course. In the first class, you will be provided with a take-home pre-test to see if your preparation is adequate. You will also need to be reasonably familiar with basic micro and macroeconomics.

This class will make extensive use of PC computing using Eviews. I do not assume familiarity with computer programming, but you __must__ know (or be willing to teach yourself) the basics of using the World Wide Web (e.g., how to go to a website, and how to save files from a webpage).

Texts:

The main text is a reader copying selections from T. Dudley Wallace and J. Lew Silver, *Econometrics: An Introductio*. For homework and supplemental reading, you will also need David Freedman and David Love, *Mathematical Methods in Statistics: A Workbook*.

In addition, you __must__ purchase a copy of Eviews; the best place to do so is surely online at http://www.eviews.com/general/prices.html. The price is $65 for the Student version; once you are sure you will be in the class, order it immediately.

Other materials will be provided on my webpage or in lecture.

Grading and Exams:

There will be one midterm and a final exam - essentially, an exam for each Part of the course. The midterm counts 30%; the final exam is 40%; homework counts for the remaining 30%. These weights are __fixed__ - improvement on later exams will not retroactively raise your grades on earlier exams.

There is no formal grade for participation, but if you are one of the students who (in my judgment) contributes most to the quality of class discussion your grade will be raised if you are on the border between two grades.

Homework:

There will be approximately six homework assignments during the semester. You will probably find the class very hard to follow if you fail to spend sufficient time on all of the homeworks. Depending upon how good a job you do, your homework will receive a check-plus (4 points), a check (3 points), or a check-minus (2 points) if you turn it in; otherwise you receive 0 points. Late homework loses one point. *Late homework is no longer accepted after I pass out my suggested answers for a given assignment.*

Office Hours

The best way to contact me is by email at bcaplan@gmu.edu. Many questions and requests can be satisfied by going to my homepage at http://www.gmu.edu/departments/economics/bcaplan. My office is in 326 Enterprise Hall; my office number is 3-1124. My official office hours are MWF 1:30-2:30, but you can also schedule an appointment or just drop by and see if I’m available.

Tentative Schedule:

My proposed schedule for the semester follows. If it proves too ambitious, I will try to *simply say less about each topic* rather than cut the topics for the final weeks.

PART I: Econometric Theory

Weeks 1-2: __Brief__ Review of Basic Statistics

- What is econometrics?
- Probability density functions
- Expected values
- Variance and standard deviation
- Covariance and correlation
- Estimating population mean and population variance
- Standard errors, confidence intervals, and hypothesis testing

__Readings:__

Wallace and Silver, *Econometrics*, pp.1-24; 47-59.

Weeks 3-4: Regression with One Variable

- Curve-fitting
- Least-squares estimator
- Derivation of the slope and intercept terms
- R
^{2} - Correlation vs. causation

__Readings:__

Wallace and Silver, *Econometrics*, pp.74-91

Handout: Introduction to Eviews

Week 5: Choice of Functional Forms

- Taking logs of a variable
- Squaring a variable
- First differences
- Percentage changes

__Readings:__

Wallace and Silver, *Econometrics*, pp.114-122.

Weeks 6-7: Multiple Regression

- Intuition (no math) behind multiple regression
- Controlling for other variables
- R
^{2}and multiple regression - Omitted Variable Bias
- Correlation vs. causation, again

__Readings:__

none

MIDTERM

PART II: Econometric Practice

Week 8: Types of Data

- Cross sections
- Time series
- Pooled time series

__Readings:__

none

Week 9: Dummy and Trend Variables

- Dummy variables - right-hand side
- Dummy variables - left-hand side
- Trend variables

__Readings:__

Wallace and Silver, *Econometrics*, pp.210-224.

Week 10: Endogenous vs. Exogenous Variables

- Intuition (no math) - endogenous vs. exogenous
- Illustration of the problem
- Picking exogenous variables
- Resolving the problem of correlation vs. causation

__Readings:__

Wallace and Silver, *Econometrics*, pp.336-339.

Week 11: Simple Econometrics and the Phillips Curve

- Economic theory of the Phillips curve
- Simple empirical analysis
- More complicated empirical analysis

__Readings:__

Steven Landsburg, "New, Improved Football: How Economists Go Wrong"

Week 12: Simple Econometrics and Monetarism

- Economic theory of monetarism
- Simple empirical analysis
- More complicated empirical analysis

__Readings:__

none

Week 13: Simple Econometrics and the Random Walk Hypothesis

- Economic theory of the random walk
- Simple empirical analysis
- More complicated empirical analysis

__Readings:__

Steven Landsburg, "Random Walks and Stock Market Prices: A Primer for Investors"

Week 14: Simple Econometrics and Indices of Economic Freedom

- What is the effect of economic freedom on economic prosperity?
- Measuring economic freedom
- Simple empirical analysis
- More complicated empirical analysis

__Readings:__

*The Economic Freedom of the World* at:

http://192.197.214.46/cgi-bin/foliocgi.exe/fraser.nfo/query=*/doc/{@81350}?

Week 15: Being an Intelligent Consumer of Econometrics

- Econometrics
__one__tool of empirical research - Evaluating evidence
- Economic theory and econometrics

__Readings:__

none

FINAL EXAM