Question 1

A larger error variance makes it difficult to estimate the partial effect of any of the independent variables on the dependent variable.

Accepted Answer

A) True 
 B)False  True

Question 2

Find the degrees of freedom in a regression model that has 10 observations and 7 independent variables.

Accepted Answer

A) 17 
B) 2 
C) 3 
D) 4 
A) 17 
B) 2 
C) 3 
D) 4 B

Question 3

The term _____ refers to the problem of small sample size.

Accepted Answer

A) micronumerosity 
B) multicollinearity 
C) homoskedasticity 
D) heteroskedasticity 
A) micronumerosity 
B) multicollinearity 
C) homoskedasticity 
D) heteroskedasticity A

Question 4

Exclusion of a relevant variable from a multiple linear regression model leads to the problem of _____.

Accepted Answer

A) misspecification of the model 
B) multicollinearity 
C) perfect collinearity 
D) homoskedasticity 
A) misspecification of the model 
B) multicollinearity 
C) perfect collinearity 
D) homoskedasticity

Question 5

If the explained sum of squares is 35 and the total sum of squares is 49,what is the residual sum of squares?

Accepted Answer

A) 10 
B) 12 
C) 18 
D) 14 
A) 10 
B) 12 
C) 18 
D) 14

Question 6

Suppose the variable x2 has been omitted from the following regression equation,   .   is the estimator obtained when x2 is omitted from the equation.The bias in   is negative if _____.

Accepted Answer

A)    >0 and x 1 and x 2 are positively correlated 
B)     1 and x 2 are positively correlated 
C)    =0 and x 1 and x 2 are negatively correlated 
D)    =0 and x 1 and x 2 are negatively correlated 
A)    >0 and x 1 and x 2 are positively correlated 
B)     1 and x 2 are positively correlated 
C)    =0 and x 1 and x 2 are negatively correlated 
D)    =0 and x 1 and x 2 are negatively correlated

Question 7

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 8

The assumption that there are no exact linear relationships among the independent variables in a multiple linear regression model fails if _____,where n is the sample size and k is the number of parameters.

Accepted Answer

A) n>2 B) n=k+1 C) n>k D) n2 B) n=k+1 C) n>k D) n

Question 9

An explanatory variable is said to be exogenous if it is correlated with the error term.

Accepted Answer

A) True 
 B)False

Question 10

Suppose the variable x2 has been omitted from the following regression equation,   .   is the estimator obtained when x2 is omitted from the equation.If E(   )>β1,   is said to _____.

Accepted Answer

A) have an upward bias 
B) have a downward bias 
C) be unbiased 
D) be biased toward zero 
A) have an upward bias 
B) have a downward bias 
C) be unbiased 
D) be biased toward zero

Question 11

The term "linear" in a multiple linear regression model means that the equation is linear in parameters.

Accepted Answer

A) True 
 B)False

Question 12

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 13

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 14

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 15

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

Accepted Answer

A) True 
 B)False

Question 16

The Gauss-Markov theorem will not hold if _____.

Accepted Answer

A) the error term has the same variance given any values of the explanatory variables 
B) the error term has an expected value of zero given any values of the independent variables 
C) the independent variables have exact linear relationships among them 
D) the regression model relies on the method of random sampling for collection of data 
A) the error term has the same variance given any values of the explanatory variables 
B) the error term has an expected value of zero given any values of the independent variables 
C) the independent variables have exact linear relationships among them 
D) the regression model relies on the method of random sampling for collection of data

Question 17

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 18

Suppose the variable x2 has been omitted from the following regression equation,   .   is the estimator obtained when x2 is omitted from the equation.The bias in   is positive if _____.

Accepted Answer

A)    >0 and x 1 and x 2 are positively correlated 
B)     1 and x 2 are positively correlated 
C)    >0 and x 1 and x 2 are negatively correlated 
D)    = 0 and x 1 and x 2 are negatively correlated 
A)    >0 and x 1 and x 2 are positively correlated 
B)     1 and x 2 are positively correlated 
C)    >0 and x 1 and x 2 are negatively correlated 
D)    = 0 and x 1 and x 2 are negatively correlated

Question 19

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 20

Consider the following regression equation:   .What does β1 imply?

Accepted Answer

A)    measures the ceteris paribus effect of   on
  . 
B)    measures the ceteris paribus effect of   on
  . 
C)    measures the ceteris paribus effect of   on
  . 
D)    measures the ceteris paribus effect of   on
  . 
A)    measures the ceteris paribus effect of   on
  . 
B)    measures the ceteris paribus effect of   on
  . 
C)    measures the ceteris paribus effect of   on
  . 
D)    measures the ceteris paribus effect of   on
  .

A larger error variance makes it difficult to estimate the partial effect of any of the independent variables on the dependent variable.

Find the degrees of freedom in a regression model that has 10 observations and 7 independent variables.

The term _____ refers to the problem of small sample size.

Exclusion of a relevant variable from a multiple linear regression model leads to the problem of _____.

If the explained sum of squares is 35 and the total sum of squares is 49,what is the residual sum of squares?

Suppose the variable x₂ has been omitted from the following regression equation, . is the estimator obtained when x₂ is omitted from the equation.The bias in is negative if _____.

The value of R² always _____.

The assumption that there are no exact linear relationships among the independent variables in a multiple linear regression model fails if _____,where n is the sample size and k is the number of parameters.

An explanatory variable is said to be exogenous if it is correlated with the error term.

Suppose the variable x₂ has been omitted from the following regression equation, . is the estimator obtained when x₂ is omitted from the equation.If E( )>β₁, is said to _____.

The term "linear" in a multiple linear regression model means that the equation is linear in parameters.

In the equation, , is a(n)_____.

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 _____.

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.

The Gauss-Markov theorem will not hold if _____.

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

Suppose the variable x₂ has been omitted from the following regression equation, . is the estimator obtained when x₂ is omitted from the equation.The bias in is positive if _____.

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

Consider the following regression equation: .What does β₁ imply?

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: Binary or Dummy Variables

Heteroskedasticity

More on Specification and Data Problems

Basic Regression Analysis With Time Series Data

Further Issues in Using Ols With Time Series 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 Stage Least Squares

Simultaneous Equations Models

Limited Dependent Variable Models and Sample Selection Corrections

Advanced Time Series Topics

Carrying Out an Empirical Project

Filters

Exam 3: Multiple Regression Analysis: Estimation

A larger error variance makes it difficult to estimate the partial effect of any of the independent variables on the dependent variable.

Find the degrees of freedom in a regression model that has 10 observations and 7 independent variables.

The term _____ refers to the problem of small sample size.

Exclusion of a relevant variable from a multiple linear regression model leads to the problem of _____.

If the explained sum of squares is 35 and the total sum of squares is 49,what is the residual sum of squares?

Suppose the variable x2 has been omitted from the following regression equation, . is the estimator obtained when x2 is omitted from the equation.The bias in is negative if _____.

The value of R2 always _____.

The assumption that there are no exact linear relationships among the independent variables in a multiple linear regression model fails if _____,where n is the sample size and k is the number of parameters.

An explanatory variable is said to be exogenous if it is correlated with the error term.

Suppose the variable x2 has been omitted from the following regression equation, . is the estimator obtained when x2 is omitted from the equation.If E( )>β1, is said to _____.

The term "linear" in a multiple linear regression model means that the equation is linear in parameters.

In the equation, , is a(n)_____.

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 _____.

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.

The Gauss-Markov theorem will not hold if _____.

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

Suppose the variable x2 has been omitted from the following regression equation, . is the estimator obtained when x2 is omitted from the equation.The bias in is positive if _____.

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

Consider the following regression equation: .What does β1 imply?

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: Binary or Dummy Variables

Heteroskedasticity

More on Specification and Data Problems

Basic Regression Analysis With Time Series Data

Further Issues in Using Ols With Time Series 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 Stage Least Squares

Simultaneous Equations Models

Limited Dependent Variable Models and Sample Selection Corrections

Advanced Time Series Topics

Carrying Out an Empirical Project

Filters

Suppose the variable x₂ has been omitted from the following regression equation, . is the estimator obtained when x₂ is omitted from the equation.The bias in is negative if _____.

The value of R² always _____.

Suppose the variable x₂ has been omitted from the following regression equation, . is the estimator obtained when x₂ is omitted from the equation.If E( )>β₁, is said to _____.

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.

Suppose the variable x₂ has been omitted from the following regression equation, . is the estimator obtained when x₂ is omitted from the equation.The bias in is positive if _____.

Consider the following regression equation: .What does β₁ imply?