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Question 1 (100 Marks) The following table is the regression...
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...
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 ...
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...
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...
Consider the regression output below and answer each question. The frequency is quarterly,and the variables are...
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...
OP Please help me with the question above. Take Home Assignment 4 (***Round all the answers...
OP
Please help me with the question above.
Take Home Assignment 4 (***Round all the answers and intermediate calculations to two decimal places**) Question 1 (100 Marks) The following table is the regression results from the econometric mixtel: LOG(SALES) = 8. + S_LOG (PRICE) + ADVERT +e For a sample of 66 observations SALES: Monthly Sales of product A (S1000) PRICE: A price Index of product (51) ADVERT: Adverting Expenditure on product A (S1000) Dependent Variable: LOGSALES Method: Least Squares...
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...
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 for Heteroskedasticity for below picture E Equation: UNTITLED Workfile: DATA ECONOMETRICS::Data_e.. View Proc Object...
An interpretation for Heteroskedasticity for below picture
E Equation: UNTITLED Workfile: DATA ECONOMETRICS::Data_e.. View Proc Object Print Name Freeze Estimate Forecast Stats Resids Heteroskedasticity Test: Breusch-Pagan-Godfrey X F-statistic Obs R-squared Scaled explained SS 5.112724 Prob. F(4,137) 18.44402 Prob. Chi-Square(4) 37.67378 0.0007 0.0010 0.0000 Prob. Chi-Square(4) Test Equation: Dependent Variable: RESID 2 Method: Least Squares Date: 01/19/19 Time: 22:00 Sample: 2 264 Included observations: 142 Variable Coefficient Std. Error t-Statistic Prob 4.54E+08 2.09E+08 2.170543 0.0317 EDUEXPENSES 85458316 30075552 2.841455 0.0052 805579.71666856....
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) 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...
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...
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...
OP
Please help me with the question above.
Take Home Assignment 4 (***Round all the answers and intermediate calculations to two decimal places**) Question 1 (100 Marks) The following table is the regression results from the econometric mixtel: LOG(SALES) = 8. + S_LOG (PRICE) + ADVERT +e For a sample of 66 observations SALES: Monthly Sales of product A (S1000) PRICE: A price Index of product (51) ADVERT: Adverting Expenditure on product A (S1000) Dependent Variable: LOGSALES Method: Least Squares...
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...
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 for Heteroskedasticity for below picture
E Equation: UNTITLED Workfile: DATA ECONOMETRICS::Data_e.. View Proc Object Print Name Freeze Estimate Forecast Stats Resids Heteroskedasticity Test: Breusch-Pagan-Godfrey X F-statistic Obs R-squared Scaled explained SS 5.112724 Prob. F(4,137) 18.44402 Prob. Chi-Square(4) 37.67378 0.0007 0.0010 0.0000 Prob. Chi-Square(4) Test Equation: Dependent Variable: RESID 2 Method: Least Squares Date: 01/19/19 Time: 22:00 Sample: 2 264 Included observations: 142 Variable Coefficient Std. Error t-Statistic Prob 4.54E+08 2.09E+08 2.170543 0.0317 EDUEXPENSES 85458316 30075552 2.841455 0.0052 805579.71666856....
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...
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