1What is the point to learning to choose ones independent va

1.What is the point to learning to choose ones independent variables correctly for RA?

2. What damage can an irrelevant variable cause to one’s regression outcomes?

3. What is a Specification Error? Give an example of how it could occur.

4. What are the four Specification Criterion to help decide whether a given variable belongs in an equation or not?

5. What is the Omitted Variable Bias?

Solution

In statistics, omitted-variable bias (OVB) occurs when a model is created which incorrectly leaves out one or more important factors. The \"bias\" is created when the model compensates for the missing factor by over- or underestimating the effect of one of the other factors.

More specifically, OVB is the bias that appears in the estimates of parameters in a regression analysis, when the assumed specification is incorrect in that it omits an independent variable that is correlated with both the dependent variable and one or more included independent variables.

Specification error is actually a nice way of saying that the “wrong model” has been estimated. More precisely, we assume that in the population there is a specific way in which some set of independent variables, X l to X k , influence a dependent variable, Y. Specification error can result in two ways. First, we may have the proper variables in the model but specify the functional form of the relationship improperly. The regression model assumes that the relationships between the independent variables and the dependent variable are both linear and additive. If these assumptions are violated, the least squares estimators will be biased. The second form of specification error occurs when one estimates a model with the wrong independent variables

Specification error occurs when an independent variable is correlated with the error term. There are several different causes of specification error: