Question 1

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 A

Question 2

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

Accepted Answer

A) True 
 B)False  False

Question 3

​When one randomly samples from a population, the total sample variation in xj decreases without bound as the sample size increases.

Accepted Answer

A) True 
 B)False  False

Question 4

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

Question 5

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

Accepted Answer

A) >0 and and are positively correlated B) <0 and and are positively correlated C) =0 and and are negatively correlated D) =0 and and are negatively correlated A) >0 and and are positively correlated B) <0 and and are positively correlated C) =0 and and are negatively correlated D) =0 and and are negatively correlated

Question 6

Suppose the variable   has been omitted from the following regression equation,     is the estimator obtained when   is omitted from the equation. If   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 7

Suppose that you are interested in estimating the average impact a job training program has on wages. However, you recognize that there are some observed factors that influence wage, participation on the training program, or both. You may still get the unbiased estimate for the program effectiveness by:

Accepted Answer

A) Excluding those observed factors from your model and running a simple linear regression 
B) Including only the factors that predict wage but not participation as controls and running a multiple linear regression 
C) Including only the factors that predict participation but not wage as controls and running a multiple linear regression 
D) ​ Including factors that predict both wage and participation as controls and running a multiple linear regression
​
​ 
A) Excluding those observed factors from your model and running a simple linear regression 
B) Including only the factors that predict wage but not participation as controls and running a multiple linear regression 
C) Including only the factors that predict participation but not wage as controls and running a multiple linear regression 
D) ​ Including factors that predict both wage and participation as controls and running a multiple linear regression
​
​

Question 8

In econometrics, the general partialling out result is usually called the _____.​

Accepted Answer

A) ​Gauss-Markov assumption 
B) ​Best linear unbiased estimator 
C) ​Frisch-Waugh theorem 
D) ​Gauss-Markov theorem 
A) ​Gauss-Markov assumption 
B) ​Best linear unbiased estimator 
C) ​Frisch-Waugh theorem 
D) ​Gauss-Markov theorem

Question 9

Consider the following regression equation:   . What does   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   .

Question 10

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

Question 11

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 12

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

Accepted Answer

A)    >0 and   and    are positively correlated 
B)    0 and   and   are negatively correlated 
D)    = 0 and   and   are negatively correlated 
A)    >0 and   and    are positively correlated 
B)    0 and   and   are negatively correlated 
D)    = 0 and   and   are negatively correlated

Question 13

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 14

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

Question 15

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

Question 16

Which of the following is true of BLUE?​

Accepted Answer

A) ​It is a rule that can be applied to any one value of the data to produce an estimate. 
B) ​An estimator   is an unbiased estimator of   if   for any   . 
C) ​An estimator is linear if and only if it can be expressed as a linear function of the data on the dependent variable. 
D) ​It is the best linear uniform estimator. 
A) ​It is a rule that can be applied to any one value of the data to produce an estimate. 
B) ​An estimator   is an unbiased estimator of   if   for any   . 
C) ​An estimator is linear if and only if it can be expressed as a linear function of the data on the dependent variable. 
D) ​It is the best linear uniform estimator.

Question 17

Which of the following often implies that a single variable acts as a 'sufficient statistic' for predicting the outcome variable, y?

Accepted Answer

A) Ceteris paribus 
B) Conditional independence assumption 
C) Efficient markets theories 
D) Gauss-Markov theorem 
A) Ceteris paribus 
B) Conditional independence assumption 
C) Efficient markets theories 
D) Gauss-Markov theorem

Question 18

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

Accepted Answer

A) True 
 B)False

Question 19

In a multiple linear regression model, , where is a binary variable and is the years of experience, is the difference in the average wage between males and non-males, after accounting for experience.

Accepted Answer

A) True 
 B)False

Question 20

If two regressions use different sets of observations, then we can tell how the R-squareds will compare, even if one regression uses a subset of regressors.​

Accepted Answer

A) True 
 B)False

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

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

When one randomly samples from a population, the total sample variation in x_j decreases without bound as the sample size increases.

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

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

Suppose the variable has been omitted from the following regression equation, is the estimator obtained when is omitted from the equation. If is said to _____.

In econometrics, the general partialling out result is usually called the _____.

Consider the following regression equation: . What does imply?

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

The Gauss-Markov theorem will not hold if _____.

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

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

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

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.

Which of the following is true of BLUE?

Which of the following often implies that a single variable acts as a 'sufficient statistic' for predicting the outcome variable, y?

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

In a multiple linear regression model, , where is a binary variable and is the years of experience, is the difference in the average wage between males and non-males, after accounting for experience.

If two regressions use different sets of observations, then we can tell how the R-squareds will compare, even if one regression uses a subset of regressors.

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

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

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

​When one randomly samples from a population, the total sample variation in xj decreases without bound as the sample size increases.

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

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

Suppose the variable has been omitted from the following regression equation, is the estimator obtained when is omitted from the equation. If is said to _____.

In econometrics, the general partialling out result is usually called the _____.​

Consider the following regression equation: . What does imply?

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

The Gauss-Markov theorem will not hold if _____.

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

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

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

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.

Which of the following is true of BLUE?​

Which of the following often implies that a single variable acts as a 'sufficient statistic' for predicting the outcome variable, y?

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

In a multiple linear regression model, , where is a binary variable and is the years of experience, is the difference in the average wage between males and non-males, after accounting for experience.

If two regressions use different sets of observations, then we can tell how the R-squareds will compare, even if one regression uses a subset of regressors.​

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

When one randomly samples from a population, the total sample variation in x_j decreases without bound as the sample size increases.

In econometrics, the general partialling out result is usually called the _____.

Which of the following is true of BLUE?

If two regressions use different sets of observations, then we can tell how the R-squareds will compare, even if one regression uses a subset of regressors.