Syllabus
Introduction to Econometrics - Economics
4818-001 - Fall 2004
TR 11-12:15 - ECON 117
Robert McNown. Office: Economics 109
Hours:
Tuesday 9-11; Thursday
Phone: 492-8295
Email: mcnownr@colorado.edu
Introduction
Economics 4818 is a course in introductory econometrics, designed to provide you with the theoretical tools and practical experience necessary to do applied econometric research. The prerequisite for this course is a previous course in economic statistics such as Economics 3818. The essential background in probability and statistics is also reviewed in Chapter 2 of our text.
You will be actively involved with computer exercises in this course using the Eviews econometrics program, available in the Economics Computer Lab. Throughout the course you will use Eviews to implement a series of econometrics exercises designed to provide experience with various tests and estimation procedures. The instructions for these exercises and the data required for their implementation are posted on our WebCT site. In addition to these exercises, you will complete your own applied econometrics project as described below. It is not required that you use Eviews if you prefer another program. However, Eviews is extremely easy to use, yet relatively powerful in terms of the variety of econometrics tests and procedures it can perform. It is also possible to purchase a student version of Eviews that is capable of implementing most of the assignments in this course (see www.eviews.com for more information).
Evaluation and Administrative Issues
Your grade in this course will be based on three components. There will be two hourly exams and a final exam, each counting towards 20% of the course grade. The individual econometrics project counts towards 30% of your final grade. The remaining 10% of the grade is based on the econometrics lab exercises. You may work on these exercises in teams and submit one set of results and answers for the group. Late or seriously incomplete exercises will only receive half credit. I will also encourage you to work problems throughout the course, although these will not be submitted for evaluation. However, working problems and doing the computer exercises are both essential to learning econometrics and to succeeding on the examinations.
If you qualify for accommodations because of a disability, please submit to me a letter from Disability Services (DS) early in the semester so that your needs may be addressed. DS determines accommodations based on documented disabilities (303-492-8671, Willard 322, http://www.colorado.edu/sacs/disabilityservices).
I shall make every effort to accommodate all students who, because of religious obligations, have conflicts with scheduled exams, assignments, or other required attendance, provided I am notified well in advance of the scheduled conflict. Please notify me at least two weeks in advance of the conflict to request special accommodation. The campus policy concerning religious observances can be viewed at http://www.colorado.edu/policies/index.html.
The new Student Honor Code system has now been implemented in all schools and colleges. Please see http://www.colorado.edu/academics/honorcode/. If you have any specific questions about what constitutes plagiarism with respect to the assignments in this course, please raise them with me.
Individual Econometrics Projects
Throughout your training in economics you have been presented with theoretical or empirical relations among economic variables. A fundamental example is a demand function, which expresses the quantity of a good demanded as a function of its price, the price of alternatives, and consumer incomes. If we have data on these four variables over time, then regression analysis can be used to estimate the elasticities of this demand function. The regression model can also be used to perform statistical tests on the elasticities (e.g., is demand inelastic?), or to project future levels of demand conditional on assumed levels of the explanatory variables. There are numerous statistical problems that can arise in the estimation of a model such as this, and the field of econometrics is concerned with procedures for testing whether such problems exist and developing treatments for these problems.
Your assignment is to construct an econometric model of a functional relation that is interesting to you, collect the relevant data, and estimate the model dealing with possible statistical problems that might arise. You can find ideas for possible projects from examples in our text or in the econometrics lab projects, from questions that are raised in other economics classes, or from economics journals that publish applied econometric research, such as The Review of Economics and Statistics, Applied Economics, The Journal of Applied Econometrics, and various journals in the applied fields of economics. See the Project Aids module on our WebCT site for further ideas, sample student papers from previous semesters, and links to electronic sources.
I
will impose very few restriction on the nature of this
project; the application does not necessarily have to be an economic relation.
However, there are some projects that are likely to be less suitable than
others, because of unavailable data or lack of interesting testable hypotheses.
Therefore, to guarantee that you are on the right track with a project, you are
required to submit a one or two page project proposal on or before October 7.
Your proposal should (1) identify the topic you will investigate and general
questions to be addressed, (2) sketch a tentative model to be estimated,
including the relevant variables in the model, (3) cite at least two papers
that present a similar econometric model, and (4) identify your data sources,
the nature of the sample (time series or cross section), and the number of
observations. In your proposal be clear what your units of measurement will be.
For example, if you were to propose a model of wage determination, would you
observe wages of individuals at a point in time, or would you model average
wages in the
I realize that some of the pieces of the proposal may be incomplete or tentative, but you should submit your proposal on October 7 in any case. Failure to submit a proposal by October 7 will result in a five point deduction from your final project score. I will try to respond to all proposals indicating whether your idea is reasonable and to make any suggestions that I can.
Once we have agreed on a project, you should collect the data and begin estimation. You will probably want to try several alternative specifications of your model, and you will undoubtedly encounter various statistical problems. An important part of the project is the testing and treatment of these various econometric problems, using procedures presented in the course. You should document your use of these procedures by submitting the relevant computer output with your paper.
The write-up summarizing your project should follow the format of empirical articles in economics journals. Typically, these papers include:
1. Overview of the research question; statement of objectives, hypotheses to test.
2. Presentation of theory and review of relevant theoretical work.
3. Discussion of related empirical work in the area; critique of this work and statement of how your research is a contribution.
4. Specification of model to be estimated; variable definitions; data sources.
5. Presentation of estimation results; estimated equations and summary statistics; diagnostic test statistics; discussion of tests and procedures for dealing with econometric problems
6. Substantive conclusions; implication of your results for theory and policy; comparison with other empirical results.
Your final paper is due on Tuesday, December 7. Be sure to include supporting computer output, guiding me through this morass of paper in the text. Late papers will be penalized by 10 percentage points if I receive it by December 13, and by 20 percentage points if it is any later.
Text. Ramanathan, Ramu, Introductory Econometrics with Applications. (Fifth edition) Harcourt, 2002.
I. Introduction to regression and Eviews.
Computer exercise 1: (Introduction to Eviews). Due 9/2
II. Classical two-variable regression model; properties of estimators; hypothesis testing..
Exercises 3.5, 3.16, 3.22, 3.23, and Practice Exercises on Expectation (on WebCT under Exercises module).
Computer exercise 2: (Industrial Profits: Basic Regression). Due 9/9
III. Multiple regression: estimation, hypothesis testing.
Exercises 4.1, 4.8, 4.12, 4.16
Computer exercise 3 (Production Function). Due 9/21
First hourly examination: September 23
IV. Multicollinearity; Specification error.
Exercises 5.1, 5.2, 5.4, 5.9
V. Alternative functional forms.
Exercises 6.2, 6.8, 6.15
Project Proposals Due: October 7
VI. Dummy variables.
Computer Exercise 4 (Dummy variables). Due 10/14
Second hourly examination: October 21
VII. Single equation problems of regression: heteroscedasticity, autocorrelation.
Exercises 8.4, 8.6, 8.9, 8.11, 8.22; 9.2, 9.8,
Computer exercise 5 (Education expenditures: heteroscedasticity). Due 11/2
Computer exercise 6 (Female labor supply: autocorrelation). Due 11/11
VIII. Simultaneous equations models
Simultaneous equations exercises (on WebCT under Exercises module).
Computer exercise 7 (Two-stage least squares) Due11/30
IX. Qualitative choice and limited dependent variable models
Computer exercise 8 (Discrete choice). Optional
X. Dynamic models, unit roots, and cointegration; Pooling (Panel data)
Computer exercise 9 (unit root testing). Optional
Computer exercise 10 (pooling). Optional
Projects Due: December 7
Final examination: Saturday December 11,