Just need these questions answered please!!
- From the output, did the model use the incorrect functional form or suffer from omitted variables? Conduct the test at 5% and show the process in the answer, including the conclusion reached.
- From the output did, the model suffer from heteroskedasticity? Conduct each test at 5% and show the process in the answer, including the conclusion reached.
- Using the output and the statistical tables, did the model suffer from autocorrelation? Conduct the test at 5% and show the process in the answer, including the conclusion reached.
- Based on parts e to h, what are the problems with the model? How will they affect the model's reliability?
- Based on the problems mentioned in part i, what measures should be taken to address them?
pcwagen = Bo + Bipcwaget-1 + B2pcmwage + B3cpi+ ut = The variables, the name as it appears on the STATA output and the definition are below. Variable Per STATA Definition The percentage change in wage from the previous month in the pcwage furnishing industry. For example, if the current month's salary increased by 5% from the last month, then pcwage= 5.00. pcwager The previous month's change in the wage for the furnishing industry. pcwage-1 pcwage1 The percentage change in the minimum wage of the whole United States from the previous month. For example, if the minimum wage rose by 10% from the last month, pcmwage = 10.00. pcmwage pcmwage The consumer price index of the whole United States for the current month. . The STATA output starts from below. STATA OUTPUT . regress pcwage pcwage1 pcmwage cpi Source SS df MS = Model Residual 72.1014541 174.66602 3 196 24.033818 .891153163 Number of obs F(3, 196) Prob > F R-squared Adj R-squared Root MSE 200 26.97 0.0000 0.2922 0.2813 .94401 Total 246.767474 199 1.24003756 pcwage 1 Coef. Std. Err. t P>ti [95% Conf. Interval] pcwage11 pcmwage 1 | cons -.0885828 .0890592 -.0022905 3108802 .0602018 .0100117 .028482 .7768035 -1.47 8.90 -0.08 0.40 0.143 0.000 0.936 0.689 -.2073092 .0693147 -.0584611 -1.221086 .0301437 . 1088037 .0538801 1.842846 estat vif Variable ! VIE 1/VIF pcmwage 1 cpil pcwage1 1.01 1.01 1.00 0.991876 0.992140 0.996681 Mean VIF 1.01 estat ovtest Ramsey RESET test using powers of the fitted values of pcwage Ho: model has no omitted variables F(3, 193) = 26.76 Prob > F= 0.0000 estat hettest, rhs Breusch-Pagan / Cook-Weisberg test for heteroskedasticity Ho: Constant variance Variables: pcwage1 pcmwage cpi = chi2 (3) Prob > chi2 141.37 0.0000 . estat imtest, white White's test for Ho: homoskedasticity against Ha: unrestricted heteroskedasticity chi2 (9) 145.80 Prob > chi2 0.0000 Cameron & Trivedi's decomposition of IM-test Source chi2 df Heteroskedasticity Skewness Kurtosis 145.80 16.69 2.42 9 3 1 0.0000 0.0008 0.1197 Total 1 164.91 13 0.0000 estat dwatson Durbin-Watson d-statistici 4, 200) 2.072422 pcwagen = Bo + Bipcwaget-1 + B2pcmwage + B3cpi+ ut = The variables, the name as it appears on the STATA output and the definition are below. Variable Per STATA Definition The percentage change in wage from the previous month in the pcwage furnishing industry. For example, if the current month's salary increased by 5% from the last month, then pcwage= 5.00. pcwager The previous month's change in the wage for the furnishing industry. pcwage-1 pcwage1 The percentage change in the minimum wage of the whole United States from the previous month. For example, if the minimum wage rose by 10% from the last month, pcmwage = 10.00. pcmwage pcmwage The consumer price index of the whole United States for the current month. . The STATA output starts from below. STATA OUTPUT . regress pcwage pcwage1 pcmwage cpi Source SS df MS = Model Residual 72.1014541 174.66602 3 196 24.033818 .891153163 Number of obs F(3, 196) Prob > F R-squared Adj R-squared Root MSE 200 26.97 0.0000 0.2922 0.2813 .94401 Total 246.767474 199 1.24003756 pcwage 1 Coef. Std. Err. t P>ti [95% Conf. Interval] pcwage11 pcmwage 1 | cons -.0885828 .0890592 -.0022905 3108802 .0602018 .0100117 .028482 .7768035 -1.47 8.90 -0.08 0.40 0.143 0.000 0.936 0.689 -.2073092 .0693147 -.0584611 -1.221086 .0301437 . 1088037 .0538801 1.842846 estat vif Variable ! VIE 1/VIF pcmwage 1 cpil pcwage1 1.01 1.01 1.00 0.991876 0.992140 0.996681 Mean VIF 1.01 estat ovtest Ramsey RESET test using powers of the fitted values of pcwage Ho: model has no omitted variables F(3, 193) = 26.76 Prob > F= 0.0000 estat hettest, rhs Breusch-Pagan / Cook-Weisberg test for heteroskedasticity Ho: Constant variance Variables: pcwage1 pcmwage cpi = chi2 (3) Prob > chi2 141.37 0.0000 . estat imtest, white White's test for Ho: homoskedasticity against Ha: unrestricted heteroskedasticity chi2 (9) 145.80 Prob > chi2 0.0000 Cameron & Trivedi's decomposition of IM-test Source chi2 df Heteroskedasticity Skewness Kurtosis 145.80 16.69 2.42 9 3 1 0.0000 0.0008 0.1197 Total 1 164.91 13 0.0000 estat dwatson Durbin-Watson d-statistici 4, 200) 2.072422
