Question 1

The statistic used to test for serial correlation is the:

Accepted Answer

A)  R-squared statistic. 
B)  t-statistic. 
C)  Durbin-Watson statistic. 
D)  F-test statistic. 
E)  standard error of the estimate. 
A)  R-squared statistic. 
B)  t-statistic. 
C)  Durbin-Watson statistic. 
D)  F-test statistic. 
E)  standard error of the estimate.

Question 2

The 1991 exports and imports by industry code are given in the following table.What is the approximate slope coefficient estimate b of the regression of exports as a function of imports?

Accepted Answer

A)  -0.5. 
B)  -5.0. 
C)  -0.3. 
D)  -3.0. 
E)  0.4. 
A)  -0.5. 
B)  -5.0. 
C)  -0.3. 
D)  -3.0. 
E)  0.4.

Question 3

When the coefficient of determination is near 1 but the t-statistics are all insignificant,the regression likely suffers from:

Accepted Answer

A)  nonconstant variance of the error terms. 
B)  multicollinearity. 
C)  serial correlation. 
D)  randomness. 
E)  nonidentifiability. 
A)  nonconstant variance of the error terms. 
B)  multicollinearity. 
C)  serial correlation. 
D)  randomness. 
E)  nonidentifiability.

Question 4

Suppose the labor force and unemployment rate in 2001 are given in the following table.What is the slope coefficient estimate b of the regression of the unemployment rate as a function of the labor force?

Accepted Answer

A)  -0.20. 
B)  -0.020. 
C)  -0.0020. 
D)  -2.0. 
E)  0.020. 
A)  -0.20. 
B)  -0.020. 
C)  -0.0020. 
D)  -2.0. 
E)  0.020.

Question 5

The vacancy rates for commercial office space in 2001 for selected cities are given in the following table.What is the slope coefficient estimate b of the regression of the vacancy rate downtown as a function of the vacancy rate in the suburbs?

Accepted Answer

A)  1.0. 
B)  0.5. 
C)  2.5. 
D)  1.5. 
E)  0.0. 
A)  1.0. 
B)  0.5. 
C)  2.5. 
D)  1.5. 
E)  0.0.

Question 6

Multiple regression differs from simple regression in that:

Accepted Answer

A)  there can be multiple dependent variables. 
B)  the time periods over which observations are taken are multiplied to increase explanatory power. 
C)  a simple regression is done multiple times to increase explanatory power. 
D)  the computational requirements are less. 
E)  there are multiple independent variables. 
A)  there can be multiple dependent variables. 
B)  the time periods over which observations are taken are multiplied to increase explanatory power. 
C)  a simple regression is done multiple times to increase explanatory power. 
D)  the computational requirements are less. 
E)  there are multiple independent variables.

Question 7

The vacancy rates for commercial office space in 2001 for selected cities are given in the following table.What is the R-squared of the regression of the vacancy rate downtown as a function of the vacancy rate in the suburbs?

Accepted Answer

A)  1.0. 
B)  0.5. 
C)  0.25. 
D)  0.75. 
E)  0. 
A)  1.0. 
B)  0.5. 
C)  0.25. 
D)  0.75. 
E)  0.

Question 8

The annual mean daily high and low temperatures by selected cities are given in the following table.What is the estimate of the intercept coefficient a for the regression of the mean daily high temperature as a function of the mean daily low temperature?

Accepted Answer

A)  50.0. 
B)  45.0. 
C)  47.5. 
D)  -47.50. 
E)  -50.0. 
A)  50.0. 
B)  45.0. 
C)  47.5. 
D)  -47.50. 
E)  -50.0.

Question 9

The total variation in the dependent variable Y is:

Accepted Answer

A) $\Sigma$ (Yi - Ymean)2. 
B) $\Sigma$ (Yi - Yestimated)2. 
C)  $\Sigma$(Yi - Ymean)2 / $\Sigma$ (Yi - Yestimated)2. 
D) $\Sigma$(Yi - Yestimated)2 / $\Sigma$ (Yi - Ymean)2. 
E)  1 - $\Sigma$ (Yi - Yestimated)2 / $\Sigma$(Yi - Ymean)2. 
A) $\Sigma$ (Yi - Ymean)2. 
B) $\Sigma$ (Yi - Yestimated)2. 
C)  $\Sigma$(Yi - Ymean)2 / $\Sigma$ (Yi - Yestimated)2. 
D) $\Sigma$(Yi - Yestimated)2 / $\Sigma$ (Yi - Ymean)2. 
E)  1 - $\Sigma$ (Yi - Yestimated)2 / $\Sigma$(Yi - Ymean)2.

Question 10

When the t-ratio statistics on individual coefficients are all near 0 but the F-test statistic is greater than 20:

Accepted Answer

A)  multicollinearity is suggested. 
B)  nonconstant variance of the error terms is suggested. 
C)  serial correlation is suggested. 
D)  the root-mean-squared error will be large. 
E)  the Durbin-Watson statistic will be near 0. 
A)  multicollinearity is suggested. 
B)  nonconstant variance of the error terms is suggested. 
C)  serial correlation is suggested. 
D)  the root-mean-squared error will be large. 
E)  the Durbin-Watson statistic will be near 0.

Question 11

If the Durbin-Watson statistic is near 0,we can conclude that there is:

Accepted Answer

A)  positive serial correlation. 
B)  negative serial correlation. 
C)  no serial correlation. 
D)  a multicollinearity problem. 
E)  not enough data to estimate the regression. 
A)  positive serial correlation. 
B)  negative serial correlation. 
C)  no serial correlation. 
D)  a multicollinearity problem. 
E)  not enough data to estimate the regression.

Question 12

The use of consumer interviews to estimate demand functions has been criticized by economists primarily because:

Accepted Answer

A)  answering surveys takes too much time. 
B)  the answers collected cannot be easily quantified. 
C)  respondents don't have strong incentives to answer accurately. 
D)  interviewers are often belligerent. 
E)  survey questions are difficult to word clearly. 
A)  answering surveys takes too much time. 
B)  the answers collected cannot be easily quantified. 
C)  respondents don't have strong incentives to answer accurately. 
D)  interviewers are often belligerent. 
E)  survey questions are difficult to word clearly.

Question 13

The estimated mathematical relationship between dependent and independent variables derived using ordinary least squares is called the:

Accepted Answer

A)  covariance. 
B)  sample regression line. 
C)  residual demand curve. 
D)  goodness of fit. 
E)  coefficient of determination. 
A)  covariance. 
B)  sample regression line. 
C)  residual demand curve. 
D)  goodness of fit. 
E)  coefficient of determination.

Question 14

The first step in multiple regression analysis is to:

Accepted Answer

A)  procure a powerful computer. 
B)  identify the important variables. 
C)  specify a functional form to be estimated. 
D)  gather all available data. 
E)  select an estimation procedure. 
A)  procure a powerful computer. 
B)  identify the important variables. 
C)  specify a functional form to be estimated. 
D)  gather all available data. 
E)  select an estimation procedure.

Question 15

The annual mean daily high and low temperatures by selected cities are given in the following table.What is the R-squared of the regression of the mean daily high temperature as a function of the mean daily low temperature?

Accepted Answer

A)  0.67. 
B)  0.25. 
C)  0.75. 
D)  0.50. 
E)  0.85. 
A)  0.67. 
B)  0.25. 
C)  0.75. 
D)  0.50. 
E)  0.85.

Question 16

In simple regression analysis (Y = a + bX),the estimate of the slope coefficient b is equal to

Accepted Answer

A)  [$\Sigma$[(Xi - Xmean)(Yi - Ymean)] / $\Sigma$(Xi - Xmean)]2. 
B)  $\Sigma${[(Xi - Xmean)(Yi - Ymean)] / $\Sigma$(Xi - Xmean)}2. 
C)  $\Sigma$ [(Xi - Xmean)(Yi - Ymean)] / $\Sigma$(Xi - Xmean)2. 
D)  $\Sigma$ [(Xi + Xmean)(Yi + Ymean)] / $\Sigma$ (Xi + Xmean)2. 
E)  $\Sigma$ [(Xi - Xmean)(Yi - Ymean)] / $\Sigma$(Xi - Xmean). 
A)  [$\Sigma$[(Xi - Xmean)(Yi - Ymean)] / $\Sigma$(Xi - Xmean)]2. 
B)  $\Sigma${[(Xi - Xmean)(Yi - Ymean)] / $\Sigma$(Xi - Xmean)}2. 
C)  $\Sigma$ [(Xi - Xmean)(Yi - Ymean)] / $\Sigma$(Xi - Xmean)2. 
D)  $\Sigma$ [(Xi + Xmean)(Yi + Ymean)] / $\Sigma$ (Xi + Xmean)2. 
E)  $\Sigma$ [(Xi - Xmean)(Yi - Ymean)] / $\Sigma$(Xi - Xmean).

Question 17

If the Durbin-Watson statistic is near 4,we can conclude that there is:

Accepted Answer

A)  positive serial correlation. 
B)  negative serial correlation. 
C)  no serial correlation. 
D)  a multicollinearity problem. 
E)  not enough data to estimate the regression. 
A)  positive serial correlation. 
B)  negative serial correlation. 
C)  no serial correlation. 
D)  a multicollinearity problem. 
E)  not enough data to estimate the regression.

Question 18

The coefficient of determination from a regression represents the:

Accepted Answer

A)  proportion of variation in the dependent variable explained by variation in the independent variables. 
B)  proportion of variation in the independent variables explained by variation in the dependent variable. 
C)  variation in the dependent variable. 
D)  proportion of the variation in the dependent variable. 
E)  proportion of the variation in the independent variable. 
A)  proportion of variation in the dependent variable explained by variation in the independent variables. 
B)  proportion of variation in the independent variables explained by variation in the dependent variable. 
C)  variation in the dependent variable. 
D)  proportion of the variation in the dependent variable. 
E)  proportion of the variation in the independent variable.

Question 19

The difference between the observed value of a dependent variable and the value we estimate using regression analysis is known as a(n):

Accepted Answer

A)  aberration. 
B)  correlation. 
C)  dependent variable. 
D)  mistake. 
E)  residual. 
A)  aberration. 
B)  correlation. 
C)  dependent variable. 
D)  mistake. 
E)  residual.

Question 20

A regression of exports as a function of imports in 1991 across industry types yielded exports = 68 - 0.3(imports),R2 = .25,Prob > F = .26,and RMSE = 30.If imports by an industry equal 60,what is the estimate of exports from this industry,and how confident are you of your estimate?

Accepted Answer

A)  Exportsestimated = 50, variation in imports explains 25% of variation in exports, and the F-test statistic is high, so we are confident in our estimate of exports. 
B)  Exportsestimated = 86, variation in imports explains 25% of variation in exports, and the F-test statistic is high, so we are confident in our estimate of exports. 
C)  Exportsestimated = 50, variation in exports explains 25% of variation in imports, and the F-test statistic is high, so we are confident in our estimate of exports. 
D)  Exportsestimated = 86, variation in exports explains 25% of variation in imports, and the F-test statistic is high, so we are confident in our estimate of exports. 
E)  Exportsestimated = 50, but the F-test statistic fails standard significance tests and the RMSE is large relative to estimated exports, so we are not confident in our estimate. 
A)  Exportsestimated = 50, variation in imports explains 25% of variation in exports, and the F-test statistic is high, so we are confident in our estimate of exports. 
B)  Exportsestimated = 86, variation in imports explains 25% of variation in exports, and the F-test statistic is high, so we are confident in our estimate of exports. 
C)  Exportsestimated = 50, variation in exports explains 25% of variation in imports, and the F-test statistic is high, so we are confident in our estimate of exports. 
D)  Exportsestimated = 86, variation in exports explains 25% of variation in imports, and the F-test statistic is high, so we are confident in our estimate of exports. 
E)  Exportsestimated = 50, but the F-test statistic fails standard significance tests and the RMSE is large relative to estimated exports, so we are not confident in our estimate.

The statistic used to test for serial correlation is the:

The 1991 exports and imports by industry code are given in the following table.What is the approximate slope coefficient estimate b of the regression of exports as a function of imports?

When the coefficient of determination is near 1 but the t-statistics are all insignificant,the regression likely suffers from:

Suppose the labor force and unemployment rate in 2001 are given in the following table.What is the slope coefficient estimate b of the regression of the unemployment rate as a function of the labor force?

The vacancy rates for commercial office space in 2001 for selected cities are given in the following table.What is the slope coefficient estimate b of the regression of the vacancy rate downtown as a function of the vacancy rate in the suburbs?

Multiple regression differs from simple regression in that:

The vacancy rates for commercial office space in 2001 for selected cities are given in the following table.What is the R-squared of the regression of the vacancy rate downtown as a function of the vacancy rate in the suburbs?

The annual mean daily high and low temperatures by selected cities are given in the following table.What is the estimate of the intercept coefficient a for the regression of the mean daily high temperature as a function of the mean daily low temperature?

The total variation in the dependent variable Y is:

When the t-ratio statistics on individual coefficients are all near 0 but the F-test statistic is greater than 20:

If the Durbin-Watson statistic is near 0,we can conclude that there is:

The use of consumer interviews to estimate demand functions has been criticized by economists primarily because:

The estimated mathematical relationship between dependent and independent variables derived using ordinary least squares is called the:

The first step in multiple regression analysis is to:

The annual mean daily high and low temperatures by selected cities are given in the following table.What is the R-squared of the regression of the mean daily high temperature as a function of the mean daily low temperature?

In simple regression analysis (Y = a + bX),the estimate of the slope coefficient b is equal to

If the Durbin-Watson statistic is near 4,we can conclude that there is:

The coefficient of determination from a regression represents the:

The difference between the observed value of a dependent variable and the value we estimate using regression analysis is known as a(n):

A regression of exports as a function of imports in 1991 across industry types yielded exports = 68 - 0.3(imports),R² = .25,Prob > F = .26,and RMSE = 30.If imports by an industry equal 60,what is the estimate of exports from this industry,and how confident are you of your estimate?

Introduction

Demand Theory

Consumer Behavior and Rational Choice

Production Theory

The Analysis of Costs

Perfect Competition

Monopoly and Monopolistic Competition

Managerial Use of Price Discrimination

Bundling and Intrafirm Pricing

Oligopoly

Game Theory

Auctions

Risk Analysis

Principalagent Issues and Managerial Compensation

Adverse Selection

Government and Business

Optimization Techniques

Appendix Problems

Filters

Exam 4: Estimating Demand Functions

The statistic used to test for serial correlation is the:

The 1991 exports and imports by industry code are given in the following table.What is the approximate slope coefficient estimate b of the regression of exports as a function of imports?

When the coefficient of determination is near 1 but the t-statistics are all insignificant,the regression likely suffers from:

Suppose the labor force and unemployment rate in 2001 are given in the following table.What is the slope coefficient estimate b of the regression of the unemployment rate as a function of the labor force?

The vacancy rates for commercial office space in 2001 for selected cities are given in the following table.What is the slope coefficient estimate b of the regression of the vacancy rate downtown as a function of the vacancy rate in the suburbs?

Multiple regression differs from simple regression in that:

The vacancy rates for commercial office space in 2001 for selected cities are given in the following table.What is the R-squared of the regression of the vacancy rate downtown as a function of the vacancy rate in the suburbs?

The annual mean daily high and low temperatures by selected cities are given in the following table.What is the estimate of the intercept coefficient a for the regression of the mean daily high temperature as a function of the mean daily low temperature?

The total variation in the dependent variable Y is:

When the t-ratio statistics on individual coefficients are all near 0 but the F-test statistic is greater than 20:

If the Durbin-Watson statistic is near 0,we can conclude that there is:

The use of consumer interviews to estimate demand functions has been criticized by economists primarily because:

The estimated mathematical relationship between dependent and independent variables derived using ordinary least squares is called the:

The first step in multiple regression analysis is to:

The annual mean daily high and low temperatures by selected cities are given in the following table.What is the R-squared of the regression of the mean daily high temperature as a function of the mean daily low temperature?

In simple regression analysis (Y = a + bX),the estimate of the slope coefficient b is equal to

If the Durbin-Watson statistic is near 4,we can conclude that there is:

The coefficient of determination from a regression represents the:

The difference between the observed value of a dependent variable and the value we estimate using regression analysis is known as a(n):

A regression of exports as a function of imports in 1991 across industry types yielded exports = 68 - 0.3(imports),R2 = .25,Prob > F = .26,and RMSE = 30.If imports by an industry equal 60,what is the estimate of exports from this industry,and how confident are you of your estimate?

Introduction

Demand Theory

Consumer Behavior and Rational Choice

Production Theory

The Analysis of Costs

Perfect Competition

Monopoly and Monopolistic Competition

Managerial Use of Price Discrimination

Bundling and Intrafirm Pricing

Oligopoly

Game Theory

Auctions

Risk Analysis

Principalagent Issues and Managerial Compensation

Adverse Selection

Government and Business

Optimization Techniques

Appendix Problems

Filters

A regression of exports as a function of imports in 1991 across industry types yielded exports = 68 - 0.3(imports),R² = .25,Prob > F = .26,and RMSE = 30.If imports by an industry equal 60,what is the estimate of exports from this industry,and how confident are you of your estimate?