经济统计计量模型Chapter 2

Chapter 21. A dependent variable is also known as a(n) _.a. explanatory variableb. control variablec. predictor variabled. response variableAnswer: dDifficulty: EasyBlooms: KnowledgeA-Head: Definition of the Simple Regression ModelBUSPROG: Feedback: A dependent variable is known as a response variable.2. If a change in variable x causes a change in variable y, variable x is called the _. a. dependent variableb. explained variablec. explanatory variabled. response variableAnswer: cDifficulty: EasyBlooms: ComprehensionA-Head: Definition of the Simple Regression ModelBUSPROG: Feedback: If a change in variable x causes a change in variable y, variable x is called the independent variable or the explanatory variable.3. In the equation y = 0 + 1x + u, 0 is the _.a. dependent variableb. independent variablec. slope parameterd. intercept parameterAnswer: dDifficulty: EasyBlooms: KnowledgeA-Head: Definition of the Simple Regression ModelBUSPROG: Feedback: In the equation y = 0 + 1x + u, 0 is the intercept parameter.4. In the equation y = 0 + 1x + u, what is the estimated value of 0?a. y- 1 xb. y+1xc. i=1n(xi-x)(yi-y)i=1n(xi)2d. i=1nxyAnswer: aDifficulty: EasyBlooms: KnowledgeA-Head: Deriving the Ordinary Least Squares EstimatesBUSPROG: Feedback: The estimated value of 0 is y- 1 x.5. In the equation c = 0 + 1i + u, c denotes consumption and i denotes income. What is the residual for the 5th observation if c5=$500 and c5=$475?a. $975b. $300c. $25d. $50Answer: cDifficulty: EasyBlooms: KnowledgeA-Head: Deriving the Ordinary Least Squares EstimatesBUSPROG: Feedback: The formula for calculating the residual for the ith observation is ui=yi-yi. In this case, the residual is u5=c5-c5 =$500 -$475= $25.6. What does the equation y=0+1x denote if the regression equation is y = 0 + 1x1 + u?a. The explained sum of squaresb. The total sum of squaresc. The sample regression functiond. The population regression functionAnswer: cDifficulty: EasyBlooms: KnowledgeA-Head: Deriving the Ordinary Least Squares EstimatesBUSPROG: Feedback: The equation y=0+1x denotes the sample regression function of the given regression model.7. Consider the following regression model: y = 0 + 1x1 + u. Which of the following is a property of Ordinary Least Square (OLS) estimates of this model and their associated statistics?a. The sum, and therefore the sample average of the OLS residuals, is positive.b. The sum of the OLS residuals is negative.c. The sample covariance between the regressors and the OLS residuals is positive.d. The point (x, y) always lies on the OLS regression line.Answer: dDifficulty: EasyBlooms: KnowledgeA-Head: Properties of OLS on Any Sample of DataBUSPROG: Feedback: An important property of the OLS estimates is that the point (x, y) always lies on the OLS regression line. In other words, if x=x, the predicted value of y is y.8. The explained sum of squares for the regression function, yi=0+1x1+u1, is defined as _.a. i=1n(yi-y)2b. i=1n(yi-y)2c. i=1 nuid.i=1n(ui)2Answer: bDifficulty: EasyBlooms: KnowledgeA-Head: Properties of OLS on Any Sample of DataBUSPROG: Feedback: The explained sum of squares is defined as i=1n(yi-y)29. If the total sum of squares (SST) in a regression equation is 81, and the residual sum of squares (SSR) is 25, what is the explained sum of squares (SSE)?a. 64b. 56c. 32d. 18Answer: bDifficulty: ModerateBlooms: ApplicationA-Head: Properties of OLS on Any Sample of DataBUSPROG: AnalyticFeedback: Total sum of squares (SST) is given by the sum of explained sum of squares (SSE) and residual sum of squares (SSR). Therefore, in this case, SSE=81-25=56.10. If the residual sum of squares (SSR) in a regression analysis is 66 and the total sum of squares (SST) is equal to 90, what is the value of the coefficient of determination?a. 0.73b. 0.55c. 0.27d. 1.2Answer: cDifficulty: ModerateBlooms: ApplicationA-Head: Properties of OLS on Any Sample of DataBUSPROG: AnalyticFeedback: The formula for calculating the coefficient of determination is R2=1-SSRSST . In this case, R2=1- 6690=0.2711. Which of the following is a nonlinear regression model?a. y = 0 + 1x1/2 + ub. log y = 0 + 1log x +uc. y = 1 / (0 + 1x) + ud. y = 0 + 1x + uAnswer: cDifficulty: ModerateBlooms: ComprehensionA-Head: Properties of OLS on Any Sample of DataBUSPROG: Feedback: A regression model is nonlinear if the equation is nonlinear in the parameters. In this case, y=1 / (0 + 1x) + u is nonlinear as it is nonlinear in its parameters.12. Which of the following is assumed for establishing the unbiasedness of Ordinary Least Square (OLS) estimates?a. The error term has an expected value of 1 given any value of the explanatory variable.b. The regression equation is linear in the explained and explanatory variables.c. The sample outcomes on the explanatory variable are all the same value.d. The error term has the same variance given any value of the explanatory variable.Answer: dDifficulty: EasyBlooms: KnowledgeA-Head: Expected Values and Variances of the OLS EstimatorsBUSPROG: Feedback: The error u has the same variance given any value of the explanatory variable.13. The error term in a regression equation is said to exhibit homoskedasticty if _.a. it has zero conditional meanb. it has the same variance for all values of the explanatory variable.c. it has the same value for all values of the explanatory variabled. if the error term has a value of one given any value of the explanatory variable.Answer: bDifficulty: EasyBlooms: KnowledgeA-Head: Expected Values and Variances of the OLS EstimatorsBUSPROG: Feedback: The error term in a regression equation is said to exhibit homoskedasticty if it has the same variance for all values of the explanatory variable.14. In the regression of y on x, the error term exhibits heteroskedasticity if _.a. it has a constant varianceb. Var(y|x) is a function of xc. x is a function of yd. y is a function of xAnswer: bDifficulty: EasyBlooms: KnowledgeA-Head: Expected Values and Variances of the OLS EstimatorsBUSPROG: Feedback: Heteroskedasticity is present whenever Var(y|x) is a function of x because Var(u|x) = Var(y|x).15. What is the estimated value of the slope parameter when the regression equation, y = 0 + 1x1 + u passes through the origin?a.i=1nyib.i=1n(yi-y)c. i=1nxiyii=1nxi2d. i=1n(yi-y)2Answer: cDifficulty: EasyBlooms: KnowledgeA-Head: Regression through the Origin and Regression on a ConstantBUSPROG: Feedback: The estimated value of the slope parameter when the regression equation passes through the origin is i=1nxiyii=1nxi2 .16. A natural measure of the association between two random variables is the correlation coefficient.Answer: TrueDifficulty: EasyBlooms: KnowledgeA-Head: Definition of the Simple Regression ModelBUSPROG: Feedback: A natural measure of the association between two random variables is the correlation coefficient.17. The sample covariance between the regressors and the Ordinary Least Square (OLS) residuals is always positive.Answer: FalseDifficulty: EasyBlooms: KnowledgeA-Head: Properties of OLS on Any Sample of DataBUSPROG: Feedback: The sample covariance between the regressors and the Ordinary Least Square (OLS) residuals is zero.18. R2 is the ratio of the explained va