We are trying to estimate the impact of income on soda consumption per week and find that low-income people have a lot more variation in the amount of sodas they consume, as compared to high income people. The estimators from this regression model under this situation will _________. A. be BLUE because all OLS assumptions are met B. not be BLUE because there is clustering C. not be BLUE because of heteroskedasticity D. not be BLUE because there is autocorrelation E. be BLUE because of heteroskedasticity F. be BLUE because of homoskedasticity G. not be BLUE because of homoskedasticity H. none of the options are correct When x is a dummy variable, there will be a difference in b1 and b2 between linear and quadratic regression models. A. True B. False When x is a dummy variable, there will be no difference in OLS estimators between quadratic and cubic regression models. A. True B. False
Ans all otherwise don't ans
We are trying to estimate the impact of income on soda consumption per week and find that low-income people have a lot more variation in the amount of sodas they consume, as compared to high income people. The estimators from this regression model under this situation will _________.
| A. |
be BLUE because all OLS assumptions are met |
|
| B. |
not be BLUE because there is clustering |
|
| C. |
not be BLUE because of heteroskedasticity |
|
| D. |
not be BLUE because there is autocorrelation |
|
| E. |
be BLUE because of heteroskedasticity |
|
| F. |
be BLUE because of homoskedasticity |
|
| G. |
not be BLUE because of homoskedasticity |
|
| H. |
none of the options are correct |
When x is a dummy variable, there will be a difference in b1 and b2 between linear and quadratic regression models.
| A. |
True |
|
| B. |
False |
When x is a dummy variable, there will be no difference in OLS estimators between quadratic and cubic regression models.
| A. |
True |
|
| B. |
False |
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