经济统计计量模型-2

Chapter

21.A dependentvariable is also known as an.a.explanatory variableb.control variablec.predictor variabled.response variableAnswer:dDifficulty:EasyBlooms:KnowledgeA-Head:Definition of the SimpleRegression ModelBUSPROG:Feedback:A dependentvariable isknownasa responsevariable.

2.If achange invariable xcauses achange invariable y,variable x is calledthe.a.dependent variableb.explained variablec.explanatory variabled.response variableAnswer:cDifficulty:EasyBlooms:ComprehensionA-Head:Definition of the SimpleRegression ModelBUSPROG:Feedback:If achange invariable xcauses achange invariable y,variable x is calledthe independentvariableor the explanatory variable.

3.In the equation y=[3++u,p is the.00a.dependent variableb.independent variablec.slope parameterd.intercept parameterAnswer:dDifficulty:EasyBlooms:KnowledgeA-Head:Definition of the SimpleRegression ModelBUSPROG:Feedback:In the equation y=Bo+Pix+u,[3the interceptparameter.

04.In theequation y=p+Pix+u,what is the estimatedvalue ofp00a.y-的天b.y+PixEC=［（Xi-幻（力一力-E-i（Xi）2d.SiLixyAnswer:aDifficulty:EasyBlooms:KnowledgeA-Head:Deriving theOrdinary Least Squares EstimatesBUSPROG:Feedback:The estimatedvalue ofp is y—01x.

05.In theequation c=0°++u,c denotesconsumption andi denotesincome.What is the residualforthe5th observationif c=$500and c^=$4755a.$975b.$300c.$25d.$50Answer:cDifficulty:EasyBlooms:KnowledgeA-Head:Deriving theOrdinary Least Squares EstimatesBUSPROG:Feedback:The formulafor calculatingthe residualfor theith observationis（^=yj—yj.In thiscase,theresidual is=$500-$475=$

25.砾=一心

6.What doestheequationy=Po+BiX denoteif the regression equation isy=po+piXi+ua.The explainedsum of squaresb.The total sum of squaresc.The sampleregression functiond.The populationregression functionAnswer:cDifficulty:EasyBlooms:KnowledgeA-Head:Deriving theOrdinary LeastSquares EstimatesBUSPROG:Feedback:The equationy=p+Pix denotesthe sampleregression functionof thegiven regressionmodel.

07.Consider the following regressionmodel:y=po+piXi+u.Which of the followingis aproperty ofOrdinary LeastSquare OLS estimatesof thismodel and their associatedstatisticsa.The sum,and thereforethe sampleaverage of the OLS residuals,is positive.b.The sum of the OLS residualsis negative.c.The samplecovariance betweenthe regressorsand the OLSresidualsis positive.d.The point x,y alwayslies ontheOLSregression line.Answer:dDifficulty:EasyBlooms:KnowledgeA-Head:Properties ofOLS onAny Sampleof DataBUSPROG:Feedback:An importantproperty of theOLSestimates isthat thepointx,y alwayslies onthe OLSregressionline.In otherwords,if x=x,the predictedvalue ofy isy.

8.The explainedsum of squares forthe regressionfunction,yj=p++u isdefined as.01,a.XiliC/i-y2b.£%%一夕¥c.£2%d.£ki%2Answer:bDifficulty:EasyBlooms:KnowledgeA-Head:Properties ofOLS onAny Sampleof DataBUSPROG:Feedback:The explainedsum of squares isdefined as£1^y2式%—

9.If thetotal sum of squaresSST ina regressionequation is81,and theresidual sumof squaresSSR is25,what isthe explainedsumofsquares SSEa.64b.56c.32d.18Answer:bDifficulty:ModerateBlooms:ApplicationA-Head:Properties ofOLS onAny Sampleof DataBUSPROG:AnalyticFeedback:Total sumofsquaresSST isgiven bythe sumof explainedsumofsquares SSEand residualsumofsquaresSSR.Therefore,in thiscase,SSE=81-25=

56.

10.If theresidual sumofsquaresSSR ina regression analysis is66and thetotalsumofsquaresSST isequalto90,what isthe value of the coefficient of determinationa.

0.73b.

0.55c.

0.27d.

1.2Answer:cDifficulty:ModerateBlooms:ApplicationA-Head:Properties ofOLS onAny Sampleof DataBUSPROG:AnalyticSSRFeedback:The formulafor calculatingthecoefficientofdeterminationis R2=1——-.In thiscase,•DOIR2=1--=

0.

279011.Which of the followingisanonlinear regressionmodela.y=Po+Pix1/2+ub.logy=p+Pilogx+u0c.y=l/Po+Pix+ud.y=p+Pix+u0Answer:cDifficulty:ModerateBlooms:ComprehensionA-Head:Properties ofOLS onAny Sampleof DataBUSPROG:Feedback:A regressionmodel is nonlinear if theequation isnonlinear in theparameters.In thiscase,y=l/Po+pix+u isnonlinear asit isnonlinear inits parameters.

12.Which of thefollowingis assumedfor establishingthe unbiasednessof Ordinary LeastSquare OLSestimatesa.The error term has an expectedvalue of1given any value of the explanatory variable.b.The regressionequation islinearinthe explainedand explanatory variables.c.The sampleoutcomes ontheexplanatory variable areall the same value.d.The errorterm has the samevariance givenany value of theexplanatory variable.Blooms:KnowledgeA-Head:Expected Valuesand Variancesof theOLS EstimatorsBUSPROG:Feedback:The erroru hasthe samevariance givenany value of theexplanatory variable.

13.The errorterm ina regressionequationissaid toexhibit homoskedastictyif.a.it haszero conditionalmeanb.it hasthe samevariance forall valuesof theexplanatoryvariable.c.it hasthesamevalue forall valuesoftheexplanatory variabled.ifthe errortermhasavalueofone givenanyvalueoftheexplanatoryvariable.Answer:bDifficulty:EasyBlooms:KnowledgeA-Head:Expected Valuesand VariancesoftheOLS EstimatorsBUSPROG:Feedback:The errorterm ina regressionequationissaid toexhibit homoskedastictyif it hasthesamevariance forall valuesoftheexplanatoryvariable.

14.In the regression ofy onx,the errorterm exhibitsheteroskedasticity if.a.ithasa constantvarianceb.Vary|x isa functionof xc.xisa functionof yd.y isa functionof xAnswer:bDifficulty:EasyBlooms:KnowledgeA-Head:Expected Valuesand VariancesoftheOLS EstimatorsBUSPROG:Feedback:Heteroskedasticity ispresent wheneverVary|xisa functionof xbecause Varu|x=Vary|x.

15.What isthe estimatedvalueofthe slopeparameter whentheregressionequation,y=p+piXi+u0passes throughthe origin一历下£%%-9Blooms:KnowledgeA-Head:Regression throughthe Originand RegressiononaConstantBUSPROG:Feedback:The estimatedvalueofthe slopeparameter whentheregressionequation passesthrough theoriginis.2乙i=i xi

16.A naturalmeasure ofthe associationbetween tworandom variablesisthecorrelation coefficient.Answer:TrueDifficulty:EasyBlooms:KnowledgeA-Head:Definition ofthe SimpleRegression ModelBUSPROG:Feedback:A naturalmeasure ofthe associationbetween tworandom variablesisthecorrelationcoefficient.

17.The samplecovariance betweenthe regressorsand theOrdinary LeastSquare OLSresiduals isalwayspositive.Answer:FalseDifficulty:EasyBlooms:KnowledgeA-Head:Properties ofOLS onAny Sampleof DataBUSPROG:Feedback:The samplecovariance betweenthe regressorsand theOrdinary LeastSquareOLSresiduals iszero.

18.R2istheratio ofthe explainedvariation comparedto thetotal variation.Answer:TrueDifficulty:EasyBlooms:KnowledgeA-Head:Properties ofOLS onAny Sampleof DataBUSPROG:Feedback:The samplecovariance betweenthe regressorsandtheOrdinary LeastSquareOLSresiduals iszero.

19.There aren-1degrees offreedom inOrdinaryLeastSquare residuals.Blooms:KnowledgeA-Head:Expected Valuesand VariancesoftheOLS EstimatorsBUSPROG:Feedback:There aren-2degrees offreedom inOrdinaryLeastSquare residuals.

20.The varianceoftheslope estimatorincreases asthe errorvariance decreases.Answer:FalseDifficulty:EasyBlooms:KnowledgeA-Head:Expected Valuesand VariancesoftheOLS EstimatorsBUSPROG:Feedback:The varianceoftheslope estimatorincreases astheerrorvariance increases.。