The above presents the result of regression of interest rate against unemployment rate, with the SACF of residuals. Which statement is correct about the regression? Select one: O a. The model shows strong evidence of autocorrelation of error term O b. The model shows no evidence of heteroskedasticity of error term O C. The model shows strong evidence of heteroskedasticity of error term O d. The model shows no evidence of autocorrelation of error term
The above presents the result of regression of interest rate against unemployment rate, with the SACF of residuals. Which statement is correct about the regression? Select one: O a. The model shows strong evidence of autocorrelation of error term O b. The model shows no evidence of heteroskedasticity of error term O C. The model shows strong evidence of heteroskedasticity of error term O d. The model shows no evidence of autocorrelation of error term
Chapter1: Making Economics Decisions
Section: Chapter Questions
Problem 1QTC
Related questions
Question
q11-
![Dependent Variable: INTEREST
Method: Least Squares
Date: 09/10/20 Time: 20:54
Sample: 2010M01 2019M12
Included observations: 120
Variable
с
UNEMP
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
-‒‒‒‒‒‒‒ -
I
Coefficient
Date: 09/10/20 Time: 20:54
Sample: 2010M01 2019M12
Included observations: 120
Autocorrelation Partial Correlation
I
1
Ⓒ Equation: UNTITLED Workfile: TEMP::Untitled\
View Proc Object Print Name Freeze Estimate Forecast Stats Resids
Correlogram of Residuals
9.586787 1.478492
-1.232859
0.152135 Mean dependent var
0.144949 S.D. dependent var
1.105708 Akaike info criterion
144.2656 Schwarz criterion
I
I
I
I
I
I
t-Statistic Prob.
0.0000
6.484167
0.267930 -4.601419 0.0000
I
Std. Error
I
I
I
I
I
T
I
II
I I
2.799500
1.195761
3.055375
3.101833
AC PAC Q-Stat Prob
1 0.961 0.961 113.60 0.00
2 0.926 0.033 219.96 0.00
3 0.893 0.010 319.72 0.00
4 0.853 -0.101 411.61 0.00
5 0.814 -0.019 496.06 0.00
6 0.783 0.067 574.71 0.00
7 0.745 -0.072 646.70 0.00
8 0.716 0.077 713.69 0.00
9 0.690 0.029 776.55 0.00
10 0.661 -0.048 834.71 0.00
The above presents the result of regression of interest rate against unemployment rate, with the SACF of residuals.
Which statement is correct about the regression?
Select one:
O a. The model shows strong evidence of autocorrelation of error term
O b.
The model shows no evidence of heteroskedasticity of error term
O C.
The model shows strong evidence of heteroskedasticity of error term
O d. The model shows no evidence of autocorrelation of error term](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fb923f7e1-4c04-439d-a0ca-b2619e836082%2Fb60d583f-309d-47f1-9205-b02513c59341%2Fmbzmwwn_processed.png&w=3840&q=75)
Transcribed Image Text:Dependent Variable: INTEREST
Method: Least Squares
Date: 09/10/20 Time: 20:54
Sample: 2010M01 2019M12
Included observations: 120
Variable
с
UNEMP
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
-‒‒‒‒‒‒‒ -
I
Coefficient
Date: 09/10/20 Time: 20:54
Sample: 2010M01 2019M12
Included observations: 120
Autocorrelation Partial Correlation
I
1
Ⓒ Equation: UNTITLED Workfile: TEMP::Untitled\
View Proc Object Print Name Freeze Estimate Forecast Stats Resids
Correlogram of Residuals
9.586787 1.478492
-1.232859
0.152135 Mean dependent var
0.144949 S.D. dependent var
1.105708 Akaike info criterion
144.2656 Schwarz criterion
I
I
I
I
I
I
t-Statistic Prob.
0.0000
6.484167
0.267930 -4.601419 0.0000
I
Std. Error
I
I
I
I
I
T
I
II
I I
2.799500
1.195761
3.055375
3.101833
AC PAC Q-Stat Prob
1 0.961 0.961 113.60 0.00
2 0.926 0.033 219.96 0.00
3 0.893 0.010 319.72 0.00
4 0.853 -0.101 411.61 0.00
5 0.814 -0.019 496.06 0.00
6 0.783 0.067 574.71 0.00
7 0.745 -0.072 646.70 0.00
8 0.716 0.077 713.69 0.00
9 0.690 0.029 776.55 0.00
10 0.661 -0.048 834.71 0.00
The above presents the result of regression of interest rate against unemployment rate, with the SACF of residuals.
Which statement is correct about the regression?
Select one:
O a. The model shows strong evidence of autocorrelation of error term
O b.
The model shows no evidence of heteroskedasticity of error term
O C.
The model shows strong evidence of heteroskedasticity of error term
O d. The model shows no evidence of autocorrelation of error term
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