ECON 4706 XXXXXXXXXXSim
ECON 4706 B Winter 2022 XXXXXXXXXXSimon Powe
Assignment 3: Due April 6
BEFORE BEGINNING THIS ASSIGNMENT, PLEASE BE SURE TO READ THE
DOCUMENT ENTITLED “GENERAL ASSIGNMENT GUIDELINES”. ALL REFERENCES
TO PAGE NUMBERS, EQUATIONS, TABLES, AND SO ON ARE TO THE 5th EDITION OF
DOUGHERTY. USE A 5% SIGNIFICANCE LEVEL FOR ALL TESTS UNLESS
INDICATED OTHERWISE.
1. Answer Question 6.15 on p. 288.
2. A researcher suggests that the following model might be useful for analyzing earnings
????????? = ?1 + ?2?? + ?3???? + ?4??????? + ?5????? + ?6?????????
+ ?7???????? + ?? ? = 1, 2, … , 500
where the variables are as defined in Appendix B (pp XXXXXXXXXX).
Using the EAWE17.dta dataset:
a) Estimate the model, and then copy and paste your output into your assignment.
) Another researcher now comes along and wonders whether work experience with previous
employer(s) is of equal value to a worker as work experience with cu
ent employer. In order to
investigate this issue, estimate a new version of the model in which work experience, EXP, is
divided into two parts, namely, work experience with previous employer(s), PREVEXP, and
work experience with cu
ent employer, TENURE, where PREVEXP = EXP – TENURE. Copy
and paste your output into your assignment.
NOTE: For parts c), d), and e), you may NOT use the STATA “test” or “lincom” commands.
c) Test to see whether the impact of work experience with previous employer(s) is equal to that of
work experience with cu
ent employer, that is, test the null hypothesis ?0: ?1 = ?2 against the
alternative ?1: ?1 ≠ ?2, using the basic t-test approach, which involves the use of information from
the estimated variance covariance matrix. (See, for example, the discussion in the text around
equation XXXXXXXXXXon p XXXXXXXXXXNOTE: Assume that ?1 is the parameter associated with PREVEXP
and that ?2 is the parameter associated with TENURE.
d) Repeat part c) using the t-test reparameterization approach, described on the bottom half of p.
283. Explain.
e) Repeat part c) using the general F-test approach, described on pp XXXXXXXXXX.
2
f) Check your answer to part e) by using the STATA “test” command. Copy and paste your output
into your assignment.
g) Using your STATA output from part f), check your answers to parts c) and d). Explain.
h) A third researcher now comes along and argues that the important issue is not whether work
experience with previous employer(s) is of equal value to a worker as work experience with cu
ent
employer, rather it is whether work experience with previous employer(s) is of less value to a
worker than work experience with cu
ent employer. Explain how the third researcher’s concern
could be addressed, that is, tested, using a simple adaptation of the t-test reparameterization
approach from part d), and then do it.
3. Consider the following variation on a wage equation model:
????????? = ?1 + ?2?? + ?3???? + ?4????? + ?? ? = 1, 2, … , ?
where the variables are as defined in Appendix B (pp XXXXXXXXXX).
Using the EAWE17.dta dataset:
NOTE: You may NOT use the STATA “estat imtest, white” command for part a).
a) Test for heteroskedasticity using the (regular) White test. (Be sure to include a clear statement
of the appropriate null and alternative hypotheses, the formula for the test statistic, and the
necessary calculations for your test in your answer.) Explain.
) Repeat part a), but this time use the variation of the White test in which the auxiliary regression
consists in a regression of the squared residuals (from the original regression) on just a constant,
the predictions (from the original regression), and the squared predictions (from the original
egression). (Be sure to include a clear statement of the appropriate null and alternative hypotheses,
the formula for the test statistic, and the necessary calculations for your test in your answer.)
Explain.
c) Test for heteroskedasticity using the Goldfeld-Quandt test, assuming that the heteroskedasticity,
if any, is positively related to the value of the variable ?. (Omit the middle 132 observations.) (Be
sure to include a clear statement of the appropriate null and alternative hypotheses, the formula for
the test statistic, and the necessary calculations for your test in your answer.) Explain.
NOTE: For parts d) and e), do NOT include the MALE variable in your wage equation model.
d) Use the Chow test, as described on pp XXXXXXXXXX, to test the “parameter stability” of this cross-
sectional model. Divide the sample into two halves, so that the first half consists of the first 250
observations and the second half consists of the remaining 250 observations. (Be sure to include a
clear statement of the appropriate null and alternative hypotheses, the formula for the test statistic,
3
and the necessary calculations for your test in your answer.) Explain. NOTE: Be very careful that
you have the observations in the co
ect order, that is, the same order in which they appeared in
the original data set.
HINT: One way to estimate a model in STATA using only the first 250 observations would be to
use the following STATA code:
gen Z = _n
eg Y X2 X3 X4 if Z <= 250
This code creates a new variable, Z, which is equal to the observation number, and then estimates
a (general) model using only the first 250 observations in the sample. You can adapt this code, as
necessary, for the present problem.
NOTE: You may NOT use the STATA “test” command for part e).
e) Redo this Chow test, using the alternative dummy variable framework, described on pp. 252-
253. (Be sure to include a clear statement of the appropriate null and alternative hypotheses, the
formula for the test statistic, and the necessary calculations for your test in your answer.) Do you
get the same result? Explain.