Note: I have not taught this course in many years.

· Monday October 28: In class test I -- approx. 1:20 in length

· Monday December 2: In class test II -- approx. 1:20 in length

· Monday October 14: Assignment 1 outlined in class.

· Monday October 21: Assignment 1 is due in class.

· Monday November 18: Assignment 2 outlined in class.

· Monday November 25: Assignment 2 (i.e. the final project) is due on the last day of classes (Monday December 9).

· Monday December 9: Last Class!!

·

· **Course Syllabus**

· Economics 506 Course Syllabus, Fall 2002. PDF Version.

· **Practice and Text Problems and Solutions**

· Economics 506 Practice Problems I. PDF Version.

· Economics 506 Practice Problems I - solutions. Document.

· Economics 506 Practice Problems II. PDF Version.

· Economics 506 Practice Problems II - solutions. Document.

· Economics 506 Text Practice Problem Solutions - Sections 3 and 4 of Syllabus. Document.

· Economics 506 Text Practice Problem Solutions - Section 5 of Syllabus. Document.

**SOFTWARE AND PROGRAMS **

· Gauss -- in class demo (Monday October 7)

· Eviews - in class demo (Monday October 28)

**EXAMPLES OF GAUSS PROGRAMS
and 673**

· Gauss Monte Carlo Experiment Example

**USEFUL GAUSS WEBSITES
and 673**

**·
Mark Watson's Gauss Tutorial **

**·
Eric Zivot's Gauss Resources **

**·
Paul Söderlind's Software Page **

**GRADES FOR ECMT506 (when available) **

· Grades by last 4 digits of SSN

**ASSIGNMENTS: (These are the assignments for Fall 2002)
ASSIGNMENT 1:
I would like each of you to collect an economic dataset from any source
of your choosing (there is a link at the end of this page
to many data links). Your dataset should have at least 3-4 variables in it, and each variable should
have at least 100 observations. I would like you to examine your data and do the following:
1. Graph the data and discuss economic episodes in the data, apparent structural breaks, possible outliers, etc.
2. Construct basic statistics for all series, including mean, variance, covariances, and correlations. Discuss these, and
construct confidence intervals when possible, etc.
3. Given your findings in 1 and 2 above, hypothesize, both based on economic intuition and based on
your statistical calculations what the relationship(s) between the variables might be. Discuss the possibility of
fitting linear and nonlinear models, and then proceed using least squares estimation to
fit at least 3 different models to your data, choosing a ``target variable" that you wish to explain via
use of the other variables (and/or lags of the ``target" and other variables). Discuss the results of your regressions via
examination of t- and F-tests, as well as correlations, etc.
Particulars: I do not wish to receive from you great collections of computer
output. Rather, please
interpret your own computer output, and hand in a summary of your results and
findings to me, including garphs of the data, tables of statistical output, etc.
ASSIGNMENT 2:
I would like you to carry out a Monte Carlo assessment of the finite sample properties of a statistical
test. This should inlcude examination of the empirical level and power of a test for
various sample sizes, model parameterizations, and nominal test sizes. You should form a basic parameter set with which to
calibrate your data generating processes via empirical (regression) analysis of your dataset from Assignment 1. Additionally,
the test that you examine should be one that has been of use to you in your analysis of your dataset, and
you should finalize with me the details concerning which test you wish to examine. For those of
you who want to do something more advanced, you may instead compare the performance of a bootstrap procedure
for calculating test critical values with tests constructed using critical values derived from the usual
asymptotic approximations. Again, please discuss with me first.
Particulars: Monte Carlo results should be presented in tabulated form, along with detailed explanation of which
models were fitted, what parameterizations were used when generating data, the properties (asymptotic) of the
test being examined, etc.
FINAL PROJECT:
Assignment 2 serves as the final project for this class.
HANDOUTS **

**· Summary of Various Discrete and
Continuous Distributions. **

**· Gauss example program - Monte Carlo, Basic Regression, and Statistic Calculation. **

**· Eviews overview. **

**· papers as they
are discussed in class **

WEB SITES WORTH LOOKING AT

**· Data Links, Econ Dept's,
Conferences, and Economists **

** **

**· Any queries or
comments? Please click here ---> ---
nswanson@econ.rutgers.edu **