Question 1

In the equation,   is a(n) _____.

Accepted Answer

A) independent variable 
B) dependent variable 
C) slope parameter 
D) intercept parameter 
A) independent variable 
B) dependent variable 
C) slope parameter 
D) intercept parameter

Question 2

High (but not perfect) correlation between two or more independent variables is called _____.

Accepted Answer

A) heteroskedasticty 
B) homoskedasticty 
C) multicollinearity 
D) micronumerosity 
A) heteroskedasticty 
B) homoskedasticty 
C) multicollinearity 
D) micronumerosity

Question 3

Suppose the relationship between wage, years of education (educ), years of experience (exper), and participation in a job training program (train) is modeled as: log (   ) =   +     +   +     . Which of the following is the most accurate interpretation of the coefficient,   ?

Accepted Answer

A) Holding education and experience constant, participating in the training program increases the wage by $   . 
B) Holding education and experience constant, participating in the training program is predicted to increase the wage by   
C) Participating in the training program is predicted to increase the wage by   % . 
D) Participating in the training program increases the wage by $   . 
A) Holding education and experience constant, participating in the training program increases the wage by $   . 
B) Holding education and experience constant, participating in the training program is predicted to increase the wage by   
C) Participating in the training program is predicted to increase the wage by   % . 
D) Participating in the training program increases the wage by $   .

Question 4

The key assumption for the general multiple regression model is that all factors in the unobserved error term be correlated with the explanatory variables.

Accepted Answer

A) True 
 B)False

Question 5

The value of R2 always _____.

Accepted Answer

A) lies below 0 
B) lies above 1 
C) lies between 0 and 1 
D) lies between 1 and 1.5 
A) lies below 0 
B) lies above 1 
C) lies between 0 and 1 
D) lies between 1 and 1.5

Question 6

Which of the following is true of R2?

Accepted Answer

A) R2 is also called the standard error of regression. 
B) A low R2 indicates that the Ordinary Least Squares line fits the data well. 
C) R2 usually decreases with an increase in the number of independent variables in a regression. 
D) R2 shows what percentage of the total variation in the dependent variable, Y, is explained by the explanatory variables. 
A) R2 is also called the standard error of regression. 
B) A low R2 indicates that the Ordinary Least Squares line fits the data well. 
C) R2 usually decreases with an increase in the number of independent variables in a regression. 
D) R2 shows what percentage of the total variation in the dependent variable, Y, is explained by the explanatory variables.

Question 7

If an independent variable in a multiple linear regression model is an exact linear combination of other independent variables, the model suffers from the problem of _____.

Accepted Answer

A) perfect collinearity 
B) homoskedasticity 
C) heteroskedasticty 
D) omitted variable bias 
A) perfect collinearity 
B) homoskedasticity 
C) heteroskedasticty 
D) omitted variable bias

Question 8

The coefficient of determination (R2) decreases when an independent variable is added to a multiple regression model.

Accepted Answer

A) True 
 B)False

In the equation, is a(n) _____.

High (but not perfect) correlation between two or more independent variables is called _____.

Suppose the relationship between wage, years of education (educ), years of experience (exper), and participation in a job training program (train) is modeled as: log ( ) = + + + . Which of the following is the most accurate interpretation of the coefficient, ?

The key assumption for the general multiple regression model is that all factors in the unobserved error term be correlated with the explanatory variables.

The value of R² always _____.

Which of the following is true of R²?

If an independent variable in a multiple linear regression model is an exact linear combination of other independent variables, the model suffers from the problem of _____.

The coefficient of determination (R²) decreases when an independent variable is added to a multiple regression model.

The Nature of Econometrics and Economic Data

The Simple Regression Model

Multiple Regression Analysis Inference

Multiple Regression Analysis Ols Asymptotics

Multiple Regression Analysis Further Issues

Multiple Regression Analysis With Qualitative Information

Heteroskedasticity

More on Specification and Data Issues

Basic Regression Analysis With Time Series Data

Further Issues in Using Ols With Time Sries Data

Serial Correlation and Heteroskedasticity in Time Series Regressions

Pooling Cross Sections Across Time Simple Panel Data Methods

Advanced Panel Data Methods

Instrumental Variables Estimation and Two Strage Least Squares

Simultaneous Equations Models

Limited Dependent Variable Models and Sample Selection Correctons

Advanced Time Series Topics

Carrying Out an Empirical Project

Filters

Exam 3: Multiple Regression Analysis Estimation

In the equation, is a(n) _____.

High (but not perfect) correlation between two or more independent variables is called _____.

Suppose the relationship between wage, years of education (educ), years of experience (exper), and participation in a job training program (train) is modeled as: log ( ) = + + + . Which of the following is the most accurate interpretation of the coefficient, ?

The key assumption for the general multiple regression model is that all factors in the unobserved error term be correlated with the explanatory variables.

The value of R2 always _____.

Which of the following is true of R2?

If an independent variable in a multiple linear regression model is an exact linear combination of other independent variables, the model suffers from the problem of _____.

The coefficient of determination (R2) decreases when an independent variable is added to a multiple regression model.

The Nature of Econometrics and Economic Data

The Simple Regression Model

Multiple Regression Analysis Inference

Multiple Regression Analysis Ols Asymptotics

Multiple Regression Analysis Further Issues

Multiple Regression Analysis With Qualitative Information

Heteroskedasticity

More on Specification and Data Issues

Basic Regression Analysis With Time Series Data

Further Issues in Using Ols With Time Sries Data

Serial Correlation and Heteroskedasticity in Time Series Regressions

Pooling Cross Sections Across Time Simple Panel Data Methods

Advanced Panel Data Methods

Instrumental Variables Estimation and Two Strage Least Squares

Simultaneous Equations Models

Limited Dependent Variable Models and Sample Selection Correctons

Advanced Time Series Topics

Carrying Out an Empirical Project

Filters

The value of R² always _____.

Which of the following is true of R²?

The coefficient of determination (R²) decreases when an independent variable is added to a multiple regression model.