# 6.) Specification: Choosing the Independent Variables Flashcards

1
Q

Specifying an econometric equation consists of three parts…

A
1. ) Choosing the correct independent variables
2. ) Choosing the correct functional form
3. ) Choosing the correct form of the stochastic error term
2
Q

A specification error results when…

A

any one of three parts of specifying an econometric equation made incorrectly

3
Q

The strength of researchers being able to pick the independent variables for regression equations is…

A

the equations can be formulated to fit individual needs

4
Q

The weakness of researchers being able to pick which independent variables to include is…

A

that researchers can estimate many different specifications until they find the one that “proves” their point

5
Q

The primary consideration in deciding whether an independent variable belongs in an equation is whether

A

the variable is essential the regression on the basis of theory

6
Q

The major consequence of omitting a relevant independent variable from..

A

an equation is to cause bias in the regression coefficients that remain in the equation

7
Q

Omitted Variable is defined as..

A

an important explanatory variable that has been left out of a regression equation

8
Q

The bias caused by leaving a variable out of an is called…

A

omitted variable bias

9
Q

In an equation with more than one independent variable, the coefficient beta K represents…

A

the change I the dependent variable Y caused by a one-unit increase in the independent variable Xk, holding constant the other independent variables in the equation

10
Q

If a variable is omitted, then …

A

it is not included as an independent variable, and it is not held constant for the calculation and interpretation of beta hat K.

11
Q

The major consequence of omitting a relevant independent variable from an equation is…

A

to cause bias in the regression coefficients that remain in the equation

12
Q

The term Bomf(rin,om) is …

A

the amount of specification bias introduced into the estimate of the coefficient of the included variable by leaving out the omitted variable.

13
Q

When a relevant variable is omitted than r squared barred is likely to…

A

drop

14
Q

What two factors are key to understand if a relevant variable is left out of a regression equation?

A
1. ) There is no longer an estimate of the coefficient of that variable in the equation.
2. ) The coefficients of the remaining variables are likely to be biased.
15
Q

Reasons that including omitted variable is easier said than done

A
1. ) Omitted variable bias is hard to detect
2. ) The problem of choosing which variable to add to an equation once you decide that it is suffering from omitted variable bias.
16
Q

Expected bias is…

A

the likely bias that omitting a particular variable would have caused in the estimated coefficient of one of the included variables.

17
Q

The best indicators of an omitted relevant variable are

A

the theoretical underpinnings of the model itself

18
Q

Irrelevant variables are..

A

the converse of omitted variables, it’s when you include a variable in an equation that doesn’t belong there.

19
Q

Although the irrelevant variables no bias…

A

it causes problems for the regression because it reduces the t-scores and the R squared barred

20
Q

In terms of bias and variance on coefficient estimates an omitted variable causes…

A

Bias and the variance decreases

21
Q

In terms of bias and variance on coefficient estimates an irrelevant variable causes

A

No bias but increases the variance

22
Q

4 part test to be worked through every time a variable is added

A
1. ) Theory: is the variable’s place in the equation unambiguous and theoretically sound?
2. ) t-Test: Is the variable’s estimated coefficient significant in the expected direction?
3. ) R squared bar: Does the overall fit of the equation (adjusted for degrees of freedom) improve when the variable is added to the equation?
4. ) Bias: Do other variables’ coefficients change significantly when the variable is added to the equation?
23
Q

If an irreleveant variable is included…

A

it will reduce r squared bar, have an insignificant t-score, and have little impact on the other variables’ coefficients.

24
Q

Since economic theory is the most important test for including a variable…

A

a variable need not be dropped from an equation simply because it has an insignificant t-score.

25
Q

Theoretical considerations should never be discarded…

A

even in the face of statistical insignificance

26
Q

Three prescriptions for best practices in specification searches…

A
1. ) rely on theory rather than statistical fit as much as possible when choosing variables, functional forms, and the like.
2. ) minimize the number of equations estimated
3. ) Reveal, in a footnote or appendix, all alternative specifications estimated.