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| Observations with different . You are less certain how a change in a High variability. determinant will affect the variable. (Rich people in the food expenditure example) |
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| Observations with same variances. Low variability.You are more sure of how a change in a determinant will affect the variable. (Poor people in the food expenditure variable) |
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| How to determine Heteroskedasticity |
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Definition
| If there are a shit ton variab les far away from the line of regression. The least squares assumption is violated. |
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| tests whether random effects estimation would be almost as good. In a fixed-effects kind of case, the Hausman test is a test of H0: that random effects would be consistent and efficient, versus H1: that random effects would be inconsistent. |
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Definition
method for estimating the unknown parameters in a linear regression model
--minimizes the sum of squared vertical distances between the observed responses in the dataset and the responses predicted by the linear approximation |
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| Multicollinearity is a statistical phenomenon in which two or more predictor variables in a multiple regression model are highly correlated, |
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the Wald test can be used to test the true value of the parameter based on the sample estimate.
-suppose smoking multiplies the risk of lung cancer by some number R: then the Wald test can be used to test whether R = 1 (i.e. there is no effect of smoking) or is greater (or less) than 1 (i.e. smoking alters risk).
Wald test uses two approximations (that we know the standard error, and that the distribution is chi-squared), |
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is a test for a unit root in a time series sample.
The more negative it is, the stronger the rejection of the hypothesis that there is a unit root at some level of confidence |
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Definition
| a loop of causality between the independent and dependent variables of a model leads to endogeneity. |
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| error of an observed value is the deviation of the observed value from the (unobservable) true function value |
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| residual of an observed value is the difference between the observed value and the estimated function value. |
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| test to see if you got rid of endogeniety. |
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Definition
| Observations with different variances. High variability. determinant will affect the variable greatly.(Rich people in the food expenditure example) |
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| Observations with similiar variances. Low variability.You are more sure of how a change in a determinant will affect the variable. (Poor people in the food expenditure variable) |
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| How to determine Heteroskedasticity |
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Definition
| If there are a shit ton variables located far from the line of regression. The least squares assumption is violated. |
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Term
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Definition
| Tests whether random effects estimation would be almost as good. In a fixed-effects kind of case, the Hausman test is a test of H0: that random effects would be consistent and efficient, versus H1: that random effects would be inconsistent. |
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Definition
| A variable is said to be endogenous when there is a correlation between the parameter or variable and the error term. |
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Outline
Endogeneity and Instrumental Variables Regression
Existence of Endogeneity and Evaluating IV's
Panel Data and Fixed E ects
What is Endogeneity?
What To Do About It?
Instruments
What is Endogeneity?
I
Endogeneity can be caused by three circumstances
1.
Omitted Variables
2.
Measurement Error
3.
Simultaneity |
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Term
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Definition
| Observations with different . You are less certain how a change in a High variability. determinant will affect the variable. (Rich people in the food expenditure example) |
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Term
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Definition
| Observations with same variances. Low variability.You are more sure of how a change in a determinant will affect the variable. (Poor people in the food expenditure variable) |
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Term
| How to determine Heteroskedasticity |
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Definition
| If there are a shit ton variab les far away from the line of regression. The least squares assumption is violated. |
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Term
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Definition
| tests whether random effects estimation would be almost as good. In a fixed-effects kind of case, the Hausman test is a test of H0: that random effects would be consistent and efficient, versus H1: that random effects would be inconsistent. |
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Term
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Definition
| A variable is said to be endogenous when there is a correlation between the parameter or variable and the error term. |
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Definition
| used to determine causal relationships |
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| Observed differentiating from (Unobserved)expected value. (does not equal 0 indicating independence) |
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| The difference between the height of each man in the sample and the observable sample mean is a residual |
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Definition
| rejecting a null hypothesis that is infact true |
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