Consider the regression output below and answer each question.
The frequency is quarterly,and the variables are defined at annual
rates as follows: INT_RATE_3M is the 3-Month Treasury Bill,
INF_RATE is the inflation rate, UNRATE is the unemployment rate,
and EMP_GROWTH corresponds to the employment growth rate.
a)How is the goodness of fit? How can you tell?
b)For each of the 3 independent variables in the regression, state if their coefficient is statistically significant at 5% level.
c)For the same variables in (b), construct 90% confidence intervals.
d)What do you learn from Akaike and Schwarz criteria?
Homework Answers
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Consider the regression output below and answer each question.
The frequency is quarterly,and the variables are...
1. Propose any one interaction hypothesis among the set of independent variables for each of the ...
1. Propose any one interaction hypothesis among the set of
independent variables for each of the two models and provide
rationales for your proposition.
2. Test whether your proposition is supported by the data
ependent Variable SALARY Method: Least Squares Date: 03/28/19 Time: 17:11 Sample: 1 447 Included observations: 447 Variable Coefficient Std. Error t-Statistic Prob TOTCOMP_MEYU TENURE_MEYU AGE_MEYU SALES_MEYU PROFITS_MEYU ASSETS_MEYU 857.5376 596.2939 1.438112 0.1511 0.014302 0.002179 6.564320 0.0000 27.40055 9.066757 3.022090 0.0027 7.034349 10.952730.642246 0.521 0.013978 0.006320 2.211800...
The following show the results of regression: Housing Sold = b0 + b1 permit +b2 price...
The following show the results of regression: Housing Sold = b0 + b1 permit +b2 price + b3 employment Dependent Variable: SOLD , Method: Least Squares Date: 03/15/20 Time: 14:59 Included observations: 108 Variable Coefficient Std. Error t-Statistic Prob. C -61520.76 167763.0 -0.366712 0.7146 PERMIT 15.98282 .280962 12.47721 0.0000 PRICE ...
Predict the value of a traditional style house with 2500 square feet of area, that is 20 years old, with 3 bedrooms and two bathrooms, which is owner occupied at the time of sale, with a fireplace, an...
Predict the value of a traditional style house with 2500 square
feet of area, that is 20 years old, with 3 bedrooms and two
bathrooms, which is owner occupied at the time of sale, with a
fireplace, and not on the waterfront. Provide the “corrected
predictor”. (Prediction in the log-linear model.) need help with
the corrected predictor.
Sample: 1 1080 Included observations: 1080 Variable Coefficient Std. Error t-Statistic Prob 3.971283 0.045870 86.57653 0.0000 0.030016 0.001388 21.62198 0.0000 0.031281 0.016548 1.890282...
An interpretation is needed for the below picture E Equation: UNTITLED Workfile: DATA ECONOMETRICS::Data_e.. X View...
An interpretation is needed for the below picture
E Equation: UNTITLED Workfile: DATA ECONOMETRICS::Data_e.. X View Proc Object Print Name Freeze Estimate Forecast Stats Resids Dependent Variable: GDPPERCAPITA Method: Least Squares Date: 01/19/19 Time: 21:40 Sample (adjusted): 2 264 Included observations: 142 after adjustments Variable Coefficient Std. Error t-Statistic Prob EDUEXPENSES FDINFLOWS GSAVING UNEMPR 3430.904 984.1997 3.485983 0.0007 285.7443 54.60948 5.232504 0.0000 321.8211 135.3456 2.377772 0.0188 557.7184 296.6160 1.880271 0.0622 VALUEADDAGRI 898.3994 133.3089 6.739232 0.0000 4784.332 7670.051 0.623768 0.5338 R-squared...
1.Which variables are statistically significant at the 5% level? 2.Which variables are statistically significant at the...
1.Which variables are statistically significant at the 5%
level?
2.Which variables are statistically significant at the 10%
level?
3.Which variables are insignificant?
4.Please present the correlation matrix of the independent
variables.
5.Please run the White test for heteroskedasticity, with
cross-products AND PRESENT YOUR RESULTS. Please explain whether the
test is significant or not.
6.If the White test is significant, please present the
heteroskedasticity-consistent White regression results.
7.Can you test this model for autocorrelation? Why of why not?
If you do,...
Attached are the results of a diagnostic test on an estimated model, autocorrelation, heteoskedasticity and non-normal...
Attached are the results of a diagnostic test on an estimated
model, autocorrelation, heteoskedasticity and non-normality
respectivey, can you please comment on the results and state the
conclusion for each test using a 5% significance level
Breusch-Godfrey Serial Correlation LM Test F-statistic Obs R-squared 0.7659 0.7612 0.458959 Prob. F(4,438) 1.861565 Prob. Chi-Square(4) Test Equation: Dependent Variable: RESID Method: Least Squares Date: 05/22/19 Time: 22:02 Sample: 1982M01 2019M02 Included observations: 446 Presample missing value lagged residuals set to zero. Coefficient Std....
An interpretation is needed for the below E Equation: UNTITLED Workfile: DATA ECONOMETRICS::Data_e.. X View Proc...
An interpretation is needed for the below
E Equation: UNTITLED Workfile: DATA ECONOMETRICS::Data_e.. X View Proc Object Print Name Freeze Estimate Forecast Stats Resids Dependent Variable: GDPPERCAPITA Method: Least Squares Date: 01/19/19 Time: 21:27 Sample (adjusted): 2 264 Included observations: 142 after adjustments Variable Coefficient Std. Error t-Statistic Prob EDUEXPENSES 3409.799982.7287 3.469726 0.0007 60.62503 50.33194 1.204504 0.2305 248.8894 62.51844 3.981056 0.0001 299.3805 136.4002 2.194869 0.0299 529.2544297.0670 1.781599 0.0771 VALUEADDAGRI 840.2738 141.5672 -5.935512 0.0000 2227.235 7946.208 0.280289 0.7797 EXPORTS FDINFLOWS GSAVING...
The information of data 1 Question Consider the following table that relates earning per hour (WAGE)...
The information of data 1
Question
Consider the following table that relates earning per hour (WAGE) to years of education (EDUC): Dependent Variable: WAGE Method Least Squares Date: 03/09/20 Time 1330 Sample: 11200 Included observations: 1200 Variable Coefficient Std. Error -Statistic tbl) 1770148 Prob. 0.0000 0.0000 1962400 se(b2) EDUC - 10 39996 2 396761 R-squared Adjusted R-squared SE of regression Sum squared resid Log likelihood F-statistic Prob(F statistic) 0 207327 Mean dependent var 0 206666 SD dependent var 13.55328 Akake...
Consider time series yt , defined as the daily percentage change in SP500 index. A researcher...
Consider time series yt , defined as the daily
percentage change in SP500 index. A researcher estimated the
following model:
(a) There is one partial
autocorrelation coefficient that you can find from the estimation
result. What is the value of it? What is order (k ) of
it?
(b) Test the null hypothesis that the partial autocorrelation
coefficient that you have is zero against the alternative that it
is not zero.
Dependent Variable: GROWTH Method: Least Squares Date: 03/08/15 Time:...
1. Calculate the values of A, B, C and D 2. Interpret the coefficient of P...
1. Calculate the values of A, B, C and D
2. Interpret the coefficient of P
e. Fill in the missing values in the table below Dependent Variable: M2 Method: Least Squares Date Sample: 2000M01 2015M03 Included observations: 183 Coefficient Std. Erro t-Statistic Prob. A 0.050558 26.05699 0.0000 В 16.90617 0.0000 С 0.8836 D 0.172778 -13.78765 0.0000 0.975830 0.005616 0.038297 2 R-squared Adjusted R-suared 0.996077 S.D. dependent var S.E. of regression Sum squared resid Log likelihood F-statistic 0.996142 Mean dependent...
1. Propose any one interaction hypothesis among the set of
independent variables for each of the two models and provide
rationales for your proposition.
2. Test whether your proposition is supported by the data
ependent Variable SALARY Method: Least Squares Date: 03/28/19 Time: 17:11 Sample: 1 447 Included observations: 447 Variable Coefficient Std. Error t-Statistic Prob TOTCOMP_MEYU TENURE_MEYU AGE_MEYU SALES_MEYU PROFITS_MEYU ASSETS_MEYU 857.5376 596.2939 1.438112 0.1511 0.014302 0.002179 6.564320 0.0000 27.40055 9.066757 3.022090 0.0027 7.034349 10.952730.642246 0.521 0.013978 0.006320 2.211800...
Predict the value of a traditional style house with 2500 square
feet of area, that is 20 years old, with 3 bedrooms and two
bathrooms, which is owner occupied at the time of sale, with a
fireplace, and not on the waterfront. Provide the “corrected
predictor”. (Prediction in the log-linear model.) need help with
the corrected predictor.
Sample: 1 1080 Included observations: 1080 Variable Coefficient Std. Error t-Statistic Prob 3.971283 0.045870 86.57653 0.0000 0.030016 0.001388 21.62198 0.0000 0.031281 0.016548 1.890282...
An interpretation is needed for the below picture
E Equation: UNTITLED Workfile: DATA ECONOMETRICS::Data_e.. X View Proc Object Print Name Freeze Estimate Forecast Stats Resids Dependent Variable: GDPPERCAPITA Method: Least Squares Date: 01/19/19 Time: 21:40 Sample (adjusted): 2 264 Included observations: 142 after adjustments Variable Coefficient Std. Error t-Statistic Prob EDUEXPENSES FDINFLOWS GSAVING UNEMPR 3430.904 984.1997 3.485983 0.0007 285.7443 54.60948 5.232504 0.0000 321.8211 135.3456 2.377772 0.0188 557.7184 296.6160 1.880271 0.0622 VALUEADDAGRI 898.3994 133.3089 6.739232 0.0000 4784.332 7670.051 0.623768 0.5338 R-squared...
1.Which variables are statistically significant at the 5%
level?
2.Which variables are statistically significant at the 10%
level?
3.Which variables are insignificant?
4.Please present the correlation matrix of the independent
variables.
5.Please run the White test for heteroskedasticity, with
cross-products AND PRESENT YOUR RESULTS. Please explain whether the
test is significant or not.
6.If the White test is significant, please present the
heteroskedasticity-consistent White regression results.
7.Can you test this model for autocorrelation? Why of why not?
If you do,...
Attached are the results of a diagnostic test on an estimated
model, autocorrelation, heteoskedasticity and non-normality
respectivey, can you please comment on the results and state the
conclusion for each test using a 5% significance level
Breusch-Godfrey Serial Correlation LM Test F-statistic Obs R-squared 0.7659 0.7612 0.458959 Prob. F(4,438) 1.861565 Prob. Chi-Square(4) Test Equation: Dependent Variable: RESID Method: Least Squares Date: 05/22/19 Time: 22:02 Sample: 1982M01 2019M02 Included observations: 446 Presample missing value lagged residuals set to zero. Coefficient Std....
An interpretation is needed for the below
E Equation: UNTITLED Workfile: DATA ECONOMETRICS::Data_e.. X View Proc Object Print Name Freeze Estimate Forecast Stats Resids Dependent Variable: GDPPERCAPITA Method: Least Squares Date: 01/19/19 Time: 21:27 Sample (adjusted): 2 264 Included observations: 142 after adjustments Variable Coefficient Std. Error t-Statistic Prob EDUEXPENSES 3409.799982.7287 3.469726 0.0007 60.62503 50.33194 1.204504 0.2305 248.8894 62.51844 3.981056 0.0001 299.3805 136.4002 2.194869 0.0299 529.2544297.0670 1.781599 0.0771 VALUEADDAGRI 840.2738 141.5672 -5.935512 0.0000 2227.235 7946.208 0.280289 0.7797 EXPORTS FDINFLOWS GSAVING...
The information of data 1
Question
Consider the following table that relates earning per hour (WAGE) to years of education (EDUC): Dependent Variable: WAGE Method Least Squares Date: 03/09/20 Time 1330 Sample: 11200 Included observations: 1200 Variable Coefficient Std. Error -Statistic tbl) 1770148 Prob. 0.0000 0.0000 1962400 se(b2) EDUC - 10 39996 2 396761 R-squared Adjusted R-squared SE of regression Sum squared resid Log likelihood F-statistic Prob(F statistic) 0 207327 Mean dependent var 0 206666 SD dependent var 13.55328 Akake...
Consider time series yt , defined as the daily
percentage change in SP500 index. A researcher estimated the
following model:
(a) There is one partial
autocorrelation coefficient that you can find from the estimation
result. What is the value of it? What is order (k ) of
it?
(b) Test the null hypothesis that the partial autocorrelation
coefficient that you have is zero against the alternative that it
is not zero.
Dependent Variable: GROWTH Method: Least Squares Date: 03/08/15 Time:...
1. Calculate the values of A, B, C and D
2. Interpret the coefficient of P
e. Fill in the missing values in the table below Dependent Variable: M2 Method: Least Squares Date Sample: 2000M01 2015M03 Included observations: 183 Coefficient Std. Erro t-Statistic Prob. A 0.050558 26.05699 0.0000 В 16.90617 0.0000 С 0.8836 D 0.172778 -13.78765 0.0000 0.975830 0.005616 0.038297 2 R-squared Adjusted R-suared 0.996077 S.D. dependent var S.E. of regression Sum squared resid Log likelihood F-statistic 0.996142 Mean dependent...
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