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POLS 6482 ADVANCED MULTIVARIATE STATISTICS
Due 8 October 2001
The aim of this problem is to learn how do coefficient tests
in EVIEWS and
STATA using the Refrigerator data
discussed in Epple Notes IV pp.15-19. Download the data and bring it
up in EVIEWS.
Replicate the analyses performed in Epple Notes IV pp.15-19.
This problem is a continuation of 1.c of the 3rd homework and
2 of the 4th homework. I made some corrections in the file so download
the new version:
Answer questions 4.3 and 4.4 on page IV-22. With respect to question 4.4,
generate an appropriate variable in EVIEWS
and run the regression.
Paste the dataset into STATA, insert the
appropriate names and labels, do the d and
summ commands and report the results.
In STATA run the regression shown on
In STATA perform the Wald Test discussed
on page IV-19:
105th Elections Data by Congressional
Bring up the HDMG105Y.DTA in STATA.
Do the d and
summ commands and report the results.
there are three types of variables: personal characteristics of the representative
demographics of the congressional district
and election results
The variable dwnom1 is a measure of the
economic liberalism/conservatism of the member of Congress and it ranges from
approximately -1 (liberal) to +1 (conservative). The variable
dwnom2 is a measure of the social
liberalism/conservatism of the member of Congress and it ranges from
approximately -1 (social-liberal) to +1 (social-conservative).
Paste HDMG105Y.DTA into EVIEWS.
Run the regression:
ls clint96 c black south hisp income dwnom1 dwnom2 female aamer himem
Do the results make sense to you? Specifically, should the personal characteristics of the
representative have any effect upon the Clinton vote in the congressional district? Justify
If we believe that the personal characteristics of the member of the House should
have no effect upon the presidential vote, then this is tantamount to testing the following
bhimem = 0
We can test this null hypothesis using the method discussed in Epple Notes V.
The method is a more elaborate version of the simple Wald test done on the
refrigerator data. Follow the same steps discussed on page IV-19. For
example, if the variable female is
C(3) in the Estimation Equation and
C(5) respectively, in the Estimation
Equation, then the command in
(WARNING! Note that
tests whether or not the coefficients have the same value! This is
different from testing whether or not they all are equal to zero!)
to perform the Wald test first run the regression and
test female aamer himem
bhimem = 0
An alternative way to perform the test that sometimes is very convenient is to first
test aamer=0, accumulate
baamer = 0. Then if you
test himem=0, accumulate
You get the full test
bhimem = 0.
The keyword "accumulate" causes
STATA to test the joint restriction that the
then aamer, and
then himem are all equal to zero.
(Note that, to test
you would use the commands:
test female=himem, accumulate)
In EVIEWS run the above regression without
the personal characteristics of the representative; namely:
ls clint96 c black south hisp income dwnom1 dwnom2
The sum of squared error should be larger for this regression (Sum squared
resid in the EVIEWS regression table). How much larger
is it? Compute the difference and divide by 3 ("3" is the number of restrictions -- see
Epple notes V pp.1-7 -- the formula is (SSER - SSEUR)/number of restrictions
). This number is the numerator of the formula shown in Epple notes V-1. Now,
take the sum of squared error from the full regression with the
personal characteristics (this is SSEUR in Epple notes V) and divide it
by 425. This is the denominator of the formula shown in Epple notes V-1. Compute the
resulting number and compare it to the value shown in the Wald tests (show all of your
work). The two numbers
should be the same. This is the F-Statistic for the Wald test.
Take the above result and calculate the P-Value using
EVIEWS. Suppose the F value
is .55. In EVIEWS enter the command:
"pval" will now appear in the
EVIEWS workfile. Double-Click on "pval" and
the probability, .648389482496, will appear at the bottom of the window. The
"3,425" in the fdist argument gives the degrees of freedom for the numerator
and denominator, respectively.
To calculate the P-Value using
STATA enter the command:
and the probability, .64838948, will appear in the
"Stata Results" window.