Question 1

An auxiliary regression refers to a regression that is used:

Accepted Answer

A) when the dependent variables are qualitative in nature. 
B) when the independent variables are qualitative in nature. 
C) to compute a test statistic but whose coefficients are not of direct interest. 
D) to compute coefficients which are of direct interest in the analysis. 
A) when the dependent variables are qualitative in nature. 
B) when the independent variables are qualitative in nature. 
C) to compute a test statistic but whose coefficients are not of direct interest. 
D) to compute coefficients which are of direct interest in the analysis. C

Question 2

In a multiple regression model,the OLS estimator is consistent if:

Accepted Answer

A) there is no correlation between the dependent variables and the error term. 
B) there is a perfect correlation between the dependent variables and the error term. 
C) the sample size is less than the number of parameters in the model. 
D) there is no correlation between the independent variables and the error term. 
A) there is no correlation between the dependent variables and the error term. 
B) there is a perfect correlation between the dependent variables and the error term. 
C) the sample size is less than the number of parameters in the model. 
D) there is no correlation between the independent variables and the error term. D

Question 3

A useful rule of thumb is that standard errors are expected to shrink at a rate that is the inverse of the:

Accepted Answer

A) square root of the sample size. 
B) product of the sample size and the number of parameters in the model. 
C) square of the sample size. 
D) sum of the sample size and the number of parameters in the model. 
A) square root of the sample size. 
B) product of the sample size and the number of parameters in the model. 
C) square of the sample size. 
D) sum of the sample size and the number of parameters in the model. A

Question 4

If variance of an independent variable in a regression model,say x1,is greater than 0,or Var(x1)> 0,the inconsistency in   1(estimator associated with x1)is negative,if x1 and the error term are positively related.

Accepted Answer

A) True 
 B)False

Question 5

The n-R-squared statistic also refers to the:

Accepted Answer

A) F statistic. 
B) t statistic. 
C) z statistic. 
D) LM statistic. 
A) F statistic. 
B) t statistic. 
C) z statistic. 
D) LM statistic.

Question 6

If OLS estimators satisfy asymptotic normality,it implies that:

Accepted Answer

A) they are approximately normally distributed in large enough sample sizes. 
B) they are approximately normally distributed in samples with less than 10 observations. 
C) they have a constant mean equal to zero and variance equal to σ2. 
D) they have a constant mean equal to one and variance equal to σ. 
A) they are approximately normally distributed in large enough sample sizes. 
B) they are approximately normally distributed in samples with less than 10 observations. 
C) they have a constant mean equal to zero and variance equal to σ2. 
D) they have a constant mean equal to one and variance equal to σ.

Question 7

In a regression model,if variance of the dependent variable,y,conditional on an explanatory variable,x,or Var(y|x),is not constant,_____.

Accepted Answer

A) the t statistics are invalid and confidence intervals are valid for small sample sizes 
B) the t statistics are valid and confidence intervals are invalid for small sample sizes 
C) the t statistics and confidence intervals are both invalid no matter how large the sample size is 
D) the t statistics confidence intervals are valid no matter how large the sample size is 
A) the t statistics are invalid and confidence intervals are valid for small sample sizes 
B) the t statistics are valid and confidence intervals are invalid for small sample sizes 
C) the t statistics and confidence intervals are both invalid no matter how large the sample size is 
D) the t statistics confidence intervals are valid no matter how large the sample size is

Question 8

If the error term is correlated with any of the independent variables,the OLS estimators are:

Accepted Answer

A) biased and consistent. 
B) unbiased and inconsistent. 
C) biased and inconsistent. 
D) unbiased and consistent. 
A) biased and consistent. 
B) unbiased and inconsistent. 
C) biased and inconsistent. 
D) unbiased and consistent.

Question 9

If δ1 = Cov(x1/x2)/ Var(x1)where x1 and x2 are two independent variables in a regression equation,which of the following statements is true?

Accepted Answer

A) If x2 has a positive partial effect on the dependent variable,and δ1 > 0,then the inconsistency in the simple regression slope estimator associated with x1is negative. 
B) If x2 has a positive partial effect on the dependent variable,and δ1 > 0,then the inconsistency in the simple regression slope estimator associated with x1is positive. 
C) If x1 has a positive partial effect on the dependent variable,and δ1 > 0,then the inconsistency in the simple regression slope estimator associated with x1is negative. 
D) If x1 has a positive partial effect on the dependent variable,and δ1 > 0,then the inconsistency in the simple regression slope estimator associated with x1is positive. 
A) If x2 has a positive partial effect on the dependent variable,and δ1 > 0,then the inconsistency in the simple regression slope estimator associated with x1is negative. 
B) If x2 has a positive partial effect on the dependent variable,and δ1 > 0,then the inconsistency in the simple regression slope estimator associated with x1is positive. 
C) If x1 has a positive partial effect on the dependent variable,and δ1 > 0,then the inconsistency in the simple regression slope estimator associated with x1is negative. 
D) If x1 has a positive partial effect on the dependent variable,and δ1 > 0,then the inconsistency in the simple regression slope estimator associated with x1is positive.

Question 10

Which of the following statements is true?

Accepted Answer

A) The standard error of a regression,   ,is not an unbiased estimator for
  ,the standard deviation of the error,u,in a multiple regression model. 
B) In time series regressions,OLS estimators are always unbiased. 
C) Almost all economists agree that unbiasedness is a minimal requirement for an estimator in regression analysis. 
D) All estimators in a regression model that are consistent are also unbiased. 
A) The standard error of a regression,   ,is not an unbiased estimator for
  ,the standard deviation of the error,u,in a multiple regression model. 
B) In time series regressions,OLS estimators are always unbiased. 
C) Almost all economists agree that unbiasedness is a minimal requirement for an estimator in regression analysis. 
D) All estimators in a regression model that are consistent are also unbiased.

Question 11

The LM statistic follows a:

Accepted Answer

A) t distribution. 
B) f distribution. 
C)    2 distribution. 
D) binomial distribution. 
A) t distribution. 
B) f distribution. 
C)    2 distribution. 
D) binomial distribution.

Question 12

Even if the error terms in a regression equation,u1,u2,….. ,un,are not normally distributed,the estimated coefficients can be normally distributed.

Accepted Answer

A) True 
 B)False

Question 13

Which of the following statements is true?

Accepted Answer

A) In large samples there are not many discrepancies between the outcomes of the F test and the LM test. 
B) Degrees of freedom of the unrestricted model are necessary for using the LM test. 
C) The LM test can be used to test hypotheses with single restrictions only and provides inefficient results for multiple restrictions. 
D) The LM statistic is derived on the basis of the normality assumption. 
A) In large samples there are not many discrepancies between the outcomes of the F test and the LM test. 
B) Degrees of freedom of the unrestricted model are necessary for using the LM test. 
C) The LM test can be used to test hypotheses with single restrictions only and provides inefficient results for multiple restrictions. 
D) The LM statistic is derived on the basis of the normality assumption.

Question 14

If   j,an unbiased estimator of   j,is also a consistent estimator of   j,then when the sample size tends to infinity:

Accepted Answer

A) the distribution of   jcollapses to a single value of zero. 
B) the distribution of   jdiverges away from a single value of zero. 
C) the distribution of   jcollapses to the single point
  j. 
D) the distribution of   jdiverges away from
  j. 
A) the distribution of   jcollapses to a single value of zero. 
B) the distribution of   jdiverges away from a single value of zero. 
C) the distribution of   jcollapses to the single point
  j. 
D) the distribution of   jdiverges away from
  j.

Question 15

The F statistic is also referred to as the score statistic.

Accepted Answer

A) True 
 B)False

Question 16

The LM statistic requires estimation of the unrestricted model only.

Accepted Answer

A) True 
 B)False

Question 17

A normally distributed random variable is symmetrically distributed about its mean,it can take on any positive or negative value (but with zero probability),and more than 95% of the area under the distribution is within two standard deviations.

Accepted Answer

A) True 
 B)False

Question 18

If   jis an OLS estimator of a regression coefficient associated with one of the explanatory variables,such that j= 1,2,…. ,n,asymptotic standard error of   j will refer to the:

Accepted Answer

A) estimated variance of   jwhen the error term is normally distributed. 
B) estimated variance of a given coefficient when the error term is not normally distributed. 
C) square root of the estimated variance of   j when the error term is normally distributed. 
D) square root of the estimated variance of   j when the error term is not normally distributed. 
A) estimated variance of   jwhen the error term is normally distributed. 
B) estimated variance of a given coefficient when the error term is not normally distributed. 
C) square root of the estimated variance of   j when the error term is normally distributed. 
D) square root of the estimated variance of   j when the error term is not normally distributed.

Question 19

Which of the following statements is true under the Gauss-Markov assumptions?

Accepted Answer

A) Among a certain class of estimators,OLS estimators are best linear unbiased,but are asymptotically inefficient. 
B) Among a certain class of estimators,OLS estimators are biased but asymptotically efficient. 
C) Among a certain class of estimators,OLS estimators are best linear unbiased and asymptotically efficient. 
D) The LM test is independent of the Gauss-Markov assumptions. 
A) Among a certain class of estimators,OLS estimators are best linear unbiased,but are asymptotically inefficient. 
B) Among a certain class of estimators,OLS estimators are biased but asymptotically efficient. 
C) Among a certain class of estimators,OLS estimators are best linear unbiased and asymptotically efficient. 
D) The LM test is independent of the Gauss-Markov assumptions.

Question 20

If   j,an unbiased estimator of   j,is consistent,then the:

Accepted Answer

A) distribution of   jbecomes more and more loosely distributed around
  jas the sample size grows. 
B) distribution of   jbecomes more and more tightly distributed around
  jas the sample size grows. 
C) distribution of   jtends toward a standard normal distribution as the sample size grows. 
D) distribution of   jremains unaffected as the sample size grows. 
A) distribution of   jbecomes more and more loosely distributed around
  jas the sample size grows. 
B) distribution of   jbecomes more and more tightly distributed around
  jas the sample size grows. 
C) distribution of   jtends toward a standard normal distribution as the sample size grows. 
D) distribution of   jremains unaffected as the sample size grows.

An auxiliary regression refers to a regression that is used:

In a multiple regression model,the OLS estimator is consistent if:

A useful rule of thumb is that standard errors are expected to shrink at a rate that is the inverse of the:

If variance of an independent variable in a regression model,say x₁,is greater than 0,or Var(x₁)> 0,the inconsistency in ₁(estimator associated with x₁)is negative,if x₁ and the error term are positively related.

The n-R-squared statistic also refers to the:

If OLS estimators satisfy asymptotic normality,it implies that:

In a regression model,if variance of the dependent variable,y,conditional on an explanatory variable,x,or Var(y|x),is not constant,_____.

If the error term is correlated with any of the independent variables,the OLS estimators are:

If δ₁ = Cov(x₁/x₂)/ Var(x₁)where x₁ and x₂ are two independent variables in a regression equation,which of the following statements is true?

Which of the following statements is true?

The LM statistic follows a:

Even if the error terms in a regression equation,u₁,u₂,….. ,u_n,are not normally distributed,the estimated coefficients can be normally distributed.

Which of the following statements is true?

If _j,an unbiased estimator of _j,is also a consistent estimator of _j,then when the sample size tends to infinity:

The F statistic is also referred to as the score statistic.

The LM statistic requires estimation of the unrestricted model only.

A normally distributed random variable is symmetrically distributed about its mean,it can take on any positive or negative value (but with zero probability),and more than 95% of the area under the distribution is within two standard deviations.

If _jis an OLS estimator of a regression coefficient associated with one of the explanatory variables,such that j= 1,2,…. ,n,asymptotic standard error of _j will refer to the:

Which of the following statements is true under the Gauss-Markov assumptions?

If _j,an unbiased estimator of _j,is consistent,then the:

The Nature of Econometrics and Economic Data

The Simple Regression Model

Multiple Regression Analysis: Estimation

Multiple Regression Analysis: Inference

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 5: Multiple Regression Analysis: Ols Asymptotics

An auxiliary regression refers to a regression that is used:

In a multiple regression model,the OLS estimator is consistent if:

A useful rule of thumb is that standard errors are expected to shrink at a rate that is the inverse of the:

If variance of an independent variable in a regression model,say x1,is greater than 0,or Var(x1)> 0,the inconsistency in 1(estimator associated with x1)is negative,if x1 and the error term are positively related.

The n-R-squared statistic also refers to the:

If OLS estimators satisfy asymptotic normality,it implies that:

In a regression model,if variance of the dependent variable,y,conditional on an explanatory variable,x,or Var(y|x),is not constant,_____.

If the error term is correlated with any of the independent variables,the OLS estimators are:

If δ1 = Cov(x1/x2)/ Var(x1)where x1 and x2 are two independent variables in a regression equation,which of the following statements is true?

Which of the following statements is true?

The LM statistic follows a:

Even if the error terms in a regression equation,u1,u2,….. ,un,are not normally distributed,the estimated coefficients can be normally distributed.

Which of the following statements is true?

If j,an unbiased estimator of j,is also a consistent estimator of j,then when the sample size tends to infinity:

The F statistic is also referred to as the score statistic.

The LM statistic requires estimation of the unrestricted model only.

A normally distributed random variable is symmetrically distributed about its mean,it can take on any positive or negative value (but with zero probability),and more than 95% of the area under the distribution is within two standard deviations.

If jis an OLS estimator of a regression coefficient associated with one of the explanatory variables,such that j= 1,2,…. ,n,asymptotic standard error of j will refer to the:

Which of the following statements is true under the Gauss-Markov assumptions?

If j,an unbiased estimator of j,is consistent,then the:

The Nature of Econometrics and Economic Data

The Simple Regression Model

Multiple Regression Analysis: Estimation

Multiple Regression Analysis: Inference

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

If variance of an independent variable in a regression model,say x₁,is greater than 0,or Var(x₁)> 0,the inconsistency in ₁(estimator associated with x₁)is negative,if x₁ and the error term are positively related.

If δ₁ = Cov(x₁/x₂)/ Var(x₁)where x₁ and x₂ are two independent variables in a regression equation,which of the following statements is true?

Even if the error terms in a regression equation,u₁,u₂,….. ,u_n,are not normally distributed,the estimated coefficients can be normally distributed.

If _j,an unbiased estimator of _j,is also a consistent estimator of _j,then when the sample size tends to infinity:

If _jis an OLS estimator of a regression coefficient associated with one of the explanatory variables,such that j= 1,2,…. ,n,asymptotic standard error of _j will refer to the:

If _j,an unbiased estimator of _j,is consistent,then the: