Download 2/2002

Mid-term Exam (December 6, 2002, 0900-1200hr)
2940603 Advanced Econometrics (Assoc. Prof. Pongsa Pornchaiwiseskul)
Instructions:
a) Textbooks, lecture notes and calculators are allowed.
b) Each must work alone. Cheating will not be tolerated.
c) There are four tests. You don’t need the knowledge of
time series analysis. Attempt all the tests. Use only the
provided test-books.
d) All the hypothesis testing will use 0.05 as the level of
significance.
TEST#1 (20 points)
Using data for 40 inexperienced employees from each of
Firm A and Firm B, a labor economist estimated the
following model.
lnE_Ai =  + S_Ai + ui for Firm A
lnE_Bi =  +  S_Bi + vi for Firm B
where
lnE_fi = the natural logarithm of earnings of employee
S_fi = the number of years of schooling
f = A,B
ui,vi = IID normal error terms
Var(ui) = [A]2 for Firm A’s employees
Var(vi) = [B]2 for Firm B’s employees
Based upon printouts (1.1)-(1.3),
1.1) provide the best estimates for the model parameters
(,,,A,B). Explain in details.
1.2) test whether both firms can give the same model
parameters. That is, test for
H0:  = , A = B 
H1:   , A  B 
TEST#2 (20 points)
It is postulated that IT expenditure of a car service center
is related to satisfaction of its customers, especially, the
female customers. A customer satisfaction survey has been
conducted for ten (10) service centers. Eight (8) male and
eight (8) female customers have been selected at each
service center. The LOGIT model has been used:
Pr(CSij=1) = 1/(1+exp(Zij))
Zij = 1 + 2ITEXPi + 3ITEXPi FEMALEij
where
ij = the jth customer at center i
CSij = dummy variable for customer satisfaction
= 1 if the jth customer at center i is satisfied
= 0, otherwise
ITEXPi = IT expenditure of center i
FEMALEij = dummy variable for gender of customer ij
= 1 if the jth customer at center i is female
= 0, otherwise
Based on EViews printout(2.1), answer the following
questions in details:
2.1) Write down the best estimate for the above model.
2.2) Test whether the IT expenditure will have effect on
the customer satisfaction.
2.3) Test whether the effect of IT expenditure on male
customer is different from that on female customers.
2.4) If the 16 customers are randomly selected from each
service center without pre-determining the number of
female customers, how the model will be modified
and how will the hypothesis in Question 2.3 be tested?
TEST#3 (20 points)
Five stocks are to be used in weekly return analysis. The
following model has been used to fit the observed data:
Rit = 1 + 2i(RMt - RFt) + it
where
Rit = weekly return of stock i in week t
RMt = weekly return of the whole market in week t
RFt = weekly return of risk-free asset in week t
it = IID error term for stock i in week t
V(it) = 2 for all i,t
3.1) If the five stocks are pre-selected, explain how to
estimate the parameters 1, 21, 22, 23, 24, 25, 2
3.2) If the five stocks are to be randomly selected, explain
how to estimate the parameters. 
Note: Do not refer to EViews or any other software.
TEST#4 (20 points)
Determine the shaded figures in EViews printouts (4.14.2). Explain in details how you do it.
************PRINTOUT 1.1
============================================================
Dependent Variable: LNE?
Method: Pooled Least Squares
Date: 12/05/02
Time: 16:03
Sample: 1 40
Included observations: 40
Number of cross-sections used: 2
Total panel (balanced) observations: 80
============================================================
Variable
CoefficientStd. Errort-Statistic Prob.
============================================================
C
13.48166
2.449696
5.503400
0.0000
S?
0.209602
0.216780
0.966890
0.3366
============================================================
R-squared
0.011844
Mean dependent var 15.78544
Adjusted R-squared -0.000825
S.D. dependent var 5.088289
S.E. of regression
5.090388
Sum squared resid 2021.140
Log likelihood
-242.6907
F-statistic
0.934877
Durbin-Watson stat
0.264905
Prob(F-statistic) 0.336587
============================================================
Residual Covariance Matrix
====================================
_A
_B
====================================
_A
26.25038
-22.05547
_B
-22.05547
24.27811
====================================
************PRINTOUT 1.2
============================================================
Dependent Variable: LNE?
MEcon Thai Program, Faculty of Economics, Chulalongkorn University
Page 1/2
Mid-term Exam (December 6, 2002, 0900-1200hr)
2940603 Advanced Econometrics (Assoc. Prof. Pongsa Pornchaiwiseskul)
Method: Pooled Least Squares
Date: 12/05/02
Time: 16:10
Sample: 1 40
Included observations: 40
Number of cross-sections used: 2
Total panel (balanced) observations: 80
============================================================
Variable
CoefficientStd. Errort-Statistic Prob.
============================================================
S?
0.454514
0.072371
6.280358
0.0000
Fixed Effects
_A--C
15.58021
_B--C
5.999372
============================================================
R-squared
0.893239
Mean dependent var 15.78544
Adjusted R-squared
0.890466
S.D. dependent var 5.088289
S.E. of regression
1.684019
Sum squared resid 218.3659
Log likelihood
-153.6809
Durbin-Watson stat 2.232289
============================================================
Residual Covariance Matrix
====================================
_A
_B
====================================
_A
2.550235
-0.061847
_B
-0.061847
2.908912
====================================
************PRINTOUT 1.3
============================================================
Dependent Variable: LNE?
Method: GLS (Cross Section Weights)
Date: 12/05/02
Time: 16:10
Sample: 1 40
Included observations: 40
Number of cross-sections used: 2
Total panel (balanced) observations: 80
Convergence achieved after 13 iteration(s)
============================================================
Variable
CoefficientStd. Errort-Statistic Prob.
============================================================
S?
0.537362
0.072473
7.414611
0.0000
Fixed Effects
_A--C
14.69880
_B--C
5.059579
============================================================
Weighted Statistics
============================================================
R-squared
0.940496
Mean dependent var 16.58745
Adjusted R-squared
0.938950
S.D. dependent var 6.872830
S.E. of regression
1.698156
Sum squared resid 222.0476
Log likelihood
-153.3926
Durbin-Watson stat 2.224463
============================================================
Unweighted Statistics
============================================================
R-squared
0.891422
Mean dependent var 15.78544
Adjusted R-squared
0.888601
S.D. dependent var 5.088289
S.E. of regression
1.698289
Sum squared resid 222.0824
Durbin-Watson stat
2.249709
============================================================
Residual Covariance Matrix
====================================
_A
_B
====================================
_A
2.174040
-0.132839
_B
-0.132839
3.378019
====================================
Covariance matrix computed using second derivatives
============================================================
Variable
CoefficientStd. Errorz-Statistic Prob.
============================================================
C
-1.644284
0.448629 -3.665129
0.0002
ITEXP
0.037119
0.008532
4.350553
0.0000
ITEXP*FEMALE
0.001928
0.006306
0.305651
0.7599
============================================================
Mean dependent var
0.600000
S.D. dependent var 0.491436
S.E. of regression
0.453367
Akaike info criteri1.214856
Sum squared resid
32.27002
Schwarz criterion 1.272515
Log likelihood
-94.18845
Hannan-Quinn criter1.238269
Restr. log likelihoo-107.6819
Avg. log likelihoo-0.588678
LR statistic (2 df) 26.98683
McFadden R-squared 0.125308
Probability(LR stat) 1.38E-06
============================================================
Obs with Dep=0
64
Total obs
160
Obs with Dep=1
96
************PRINTOUT 4.1
============================================================
Dependent Variable: Y
Method: Least Squares
Date: 12/05/02
Time: 21:49
Sample: 1 38
Included observations: 38
============================================================
Variable
CoefficientStd. Errort-Statistic Prob.
============================================================
C
5.668538
2.258747
2.509594
0.0172
X2
0.335393
0.108774
3.083397
0.0041
X3
0.401936
0.311425
1.290633
0.2058
Z1
0.139932
0.218411
0.640683
0.5262
Z2
-0.948379
0.935091 -1.014210
0.3179
============================================================
R-squared
0.407902
Mean dependent var 9.013614
Adjusted R-squared
0.336133
S.D. dependent var 1.852037
S.E. of regression
1.509003
Akaike info criteri3.782855
Sum squared resid
75.14399
Schwarz criterion 3.998327
Log likelihood
-66.87424
F-statistic
5.683514
Durbin-Watson stat
2.095295
Prob(F-statistic) 0.001357
============================================================
************PRINTOUT 4.2
============================================================
Redundant Variables: Z1 Z2
============================================================
F-statistic
0.532482
Probability
Log likelihood ratio 1.206951
Probability
============================================================
Test Equation:
Dependent Variable: Y
Method: Least Squares
Date: 12/05/02
Time: 21:50
Sample: 1 38
Included observations: 38
============================================================
Variable
CoefficientStd. Errort-Statistic Prob.
============================================================
C
4.634257
1.845062
2.511708
0.0168
X2
0.394092
0.086650
4.548067
0.0001
X3
0.349698
0.278859
1.254031
0.2181
============================================================
R-squared
0.388794
Mean dependent var 9.013614
Adjusted R-squared
0.353868
S.D. dependent var 1.852037
S.E. of regression
1.488710
Akaike info criteri
Sum squared resid
77.56901
Schwarz criterion
Log likelihood
-67.47772
F-statistic
Durbin-Watson stat
2.101511
Prob(F-statistic)
============================================================
End of Exam
************PRINTOUT 2.1
============================================================
Dependent Variable: CS
Method: ML - Binary Logit
Date: 12/05/02
Time: 21:17
Sample: 1 160
Included observations: 160
Convergence achieved after 3 iterations
MEcon Thai Program, Faculty of Economics, Chulalongkorn University
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