PROBLEM 3

A study wishes to estimate the following wage equation

where the Dummy variable METRO =1 (for Urban) and =0 (for Rural). Two sets of estimated output from EViews are presented below:

Dependent Variable: WAGE
Method: Least Squares
Date: 06/09/22 Time: 11:05
Sample: 1 500 IF METRO=1
Included observations: 392
Variable	Coefficient	Std. Error	t-Statistic	Prob.
C	3.385291	0.470793	7.190612	0.0000
EDUC	0.171925	0.034638	4.963548	0.0000
EXPER	0.014662	0.006352	2.308150	0.0215
R-squared	0.063342	Mean dependent var	5.767883
Adjusted R-squared	0.058527	S.D. dependent var	1.544253
S.E. of regression	1.498382	Akaike info criterion	3.654272
Sum squared resid	873.3626	Schwarz criterion	3.684664
Log likelihood	-713.2373	Hannan-Quinn criter.	3.666317
F-statistic	13.15325	Durbin-Watson stat	0.122998
Prob(F-statistic)	0.000003

Dependent Variable: WAGE
Method: Least Squares
Date: 06/09/22 Time: 11:07
Sample: 1 500 IF METRO=0
Included observations: 108
Variable	Coefficient	Std. Error	t-Statistic	Prob.
C	2.132689	1.021757	2.087276	0.0393
EDUC	0.236026	0.076179	3.098306	0.0025
EXPER	0.030514	0.012261	2.488672	0.0144
R-squared	0.107898	Mean dependent var	5.563333
Adjusted R-squared	0.090906	S.D. dependent var	1.493970
S.E. of regression	1.424447	Akaike info criterion	3.572830
Sum squared resid	213.0503	Schwarz criterion	3.647333
Log likelihood	-189.9328	Hannan-Quinn criter.	3.603038
F-statistic	6.349790	Durbin-Watson stat	0.214528
Prob(F-statistic)	0.002493

Answer questions Q21 and Q22 based on the above estimation results:

Q21. The purpose of estimating the above two regressions is (select the best answer)

1. to investigate proportional heteroscedasticity
2. to investigate portioned heteroscedasticity
3. to investigate proportional heteroscedasticity using Goldfeld-Quandt test
4. to investigate partitioned heteroscedasticity using Goldfeld-Quandt test

Q22. To perform the Goldfeld-Quandt test, if we test

,

With a F-critical value of 0.269 at the 5 percent level of significance, the correct values usable for this test and the conclusion are as follows:

1. the conclusion is reject Ho and conclude that there is no heteroscedasticity
2. the conclusion is reject Ho and conclude that there is heteroscedasticity
3. ; the conclusion is do not reject Ho and conclude that there is no heteroscedasticity
4. ; the conclusion is reject Ho and conclude that there is heteroscedasticity

PROBLEM 4

The following is the EViews estimation results for the following model,

where A = Area planted; and P =Output price. Answer the following questions based on the given EVIEWS output.

Dependent Variable: LOG(A)
Method: Least Squares
Date: 06/09/22 Time: 11:36
Sample: 1 34
Included observations: 34
Variable	Coefficient	Std. Error	t-Statistic	Prob.
C	3.893256	0.061345	63.46486	0.0000
LOG(P)	0.776119	0.277467	2.797154	0.0087
R-squared	0.196466	Mean dependent var	3.980680
Adjusted R-squared	0.171355	S.D. dependent var	0.338123
S.E. of regression	0.307793	Akaike info criterion	0.538245
Sum squared resid	3.031571	Schwarz criterion	0.628031
Log likelihood	-7.150159	Hannan-Quinn criter.	0.568864
F-statistic	7.824072	Durbin-Watson stat	1.168987
Prob(F-statistic)	0.008653

Answer questions Q23-Q25 based on the above estimation results:

Q23. From the estimation results, we can find and conclude the following (select the best answer):

1. Intercept = 3.893 and Slope = 0.776; there is no serial correlation and price significantly influences area cultivated.
2. Intercept = 0.776 and Slope = 3.893; there is positive serial correlation and price significantly influences area cultivated.
3. Intercept = 0.776 and Slope = 3.893; there is serial correlation and price significantly influence area cultivated.
4. Intercept = 3.893 and Slope = 0.776; there is positive serial correlation and price significantly influence area cultivated.

Q24. For the above estimation results, If you graph the two plots (1) e_tagainst time and (2) e_t against e_{t-1 ,}for the above estimation results, the two plots would reveal that the errors are (select the best answer)

1. Serially correlated
2. Negatively Serially correlated
3. Serially uncorrelated
4. Positively Serially correlated

Q25. From the above estimation results, if you use Durbin-Watson test for serial correlation at the 5% level of significant, the value of the D-W statistic, the critical values for the test and the conclusion for the test are (select the best answer)

1. DW=1.169, D_L=1.39, D_U=1.51, support for no serial correlation
2. DW=1.169, D_L=1.33, D_U=1.58, support for positive serial correlation
3. DW=1.169, D_L=1.39, D_U=1.51, support for negative serial correlation
4. DW=1.169, D_L=1.39, D_U=1.51, support for positive serial correlation

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