计量经济学英文重点知识点考试必备Word格式文档下载.docx
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计量经济学英文重点知识点考试必备Word格式文档下载.docx
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收集数据Threetypesofdata三类可用于分析的数据1)Timeseries(时间序列数据):
Collectedoveraperiodoftime,arecollectedatregularintervals.按时间跨度收集得到2)Cross-sectional截面数据:
Collectedoveraperiodoftime,arecollectedatregularintervals.按时间跨度收集得到3)Pooleddata合并数据(上两种的结合)Step3:
设定数学模型1.plotscatterdiagramorscattergram2.writethemathematicalmodelStep4:
设立统计或经济计量模型CLFPRisdependentvariable应变量CUNRisindependentorexplanatoryvariable独立或解释变量(自变量)WegiveacatchallvariableUtostandforalltheseneglectedfactorsInlinearregressionanalysisourprimaryobjectiveistoexplainthebehaviorofthedependentvariableinrelationtothebehaviorofoneormoreothervariables,allowingforthedatathattherelationshipbetweenthemisinexact.线性回归分析的主要目标就是解释一个变量(应变量)与其他一个或多个变量(自变量)只见的行为关系,当然这种关系并非完全正确Step5:
估计经济计量模型参数Inshort,theestimatedregressionlinegivestherelationshipbetweenaverageCLFPRandCUNR简言之,估计的回归直线给出了平均应变量和自变量之间的关系Thatis,onaverage,howthedependentvariablerespondstoaunitchangeintheindependentvariable.单位因变量的变化引起的自变量平均变化量的多少。
Step6:
核查模型的适用性:
模型设定检验Thepurposeofdevelopinganeconometricmodelisnottocapturetotalreality,butjustitssalientfeatures.Step7:
检验自模型的假设WhydoweperformhypothesistestingWewanttofindourwhethertheestimatedmodelmakeseconomicsenseandwhethertheresultsobtainsconformwiththeunderlyingeconomictheory.第二章1.Themeaningofregression(回归)Regressionanalysisisconcernedwiththestudyoftherelationshipbetweenonevariablecalledthedependentorexplainedvariable,andoneormoreothervariablescalledindependentorexplanatoryvariables.2.Objectivesofregression1)Estimatethemean,oraverage,andthedependentvaluesgiventheindependentvalues2)Testhypothesesaboutthenatureofthedependence-hypothesessuggestedbytheunderlyingeconomictheory3)Predictorforecastthemeanvalueofthedependentvariablegiventhevaluesoftheindependents4)Oneormoreoftheprecedingobjectivescombined3.PopulationRegressionLine(PRL)Inshort,thePRLtellsushowthemean,oraverage,valueofYisrelatedtoeachvalueofXinthewholepopulation4.ThedependenceofYonX,technicallycalledtheregressionofYonX.5.HowdoweexplainitAstudentsscore,say,theithindividual,correspondingtoaspecificfamilyincomecanbeexpressedasthesumoftwocomponents1)Thecomponentcanbecalledthesystematic,ordeterministic,component.2)Maybecalledthenonsystematicorrandomcomponent6.WhatisthenatureofU(stochasticerror)term1)Theerrortermmayrepresenttheinfluenceofthosevariablesthatarenotexplicitlyincludedinthemodel.误差项代表了未纳入模型变量的影响2)Someintrinsicrandomnessinthemathscoreisboundtooccurthatcannotbeexplainedevenweincludeallrelevantvariables.即使模型包括了决定性数学分数的所有变量,内在随机性也不可避免,这是做任何努力都无法解释的。
3)Umayalsorepresenterrorsofmeasurement.U还代表了度量误差4)TheprincipleofOckhamsrazor-thedescriptionbekeptassimpleaspossibleuntilprovedinadequate-wouldsuggestthatwekeepourregressionmodelassimpleaspossible.“奥卡姆剃刀原则”,描述应该尽可能简单,只要不遗漏重要信息。
这表明回归模型应尽可能简单。
7.HowdoweestimatethePRF(populationregressionfunction)Unfortunately,inpractice,Werarelyhavetheentirepopulationinourdisposal,oftenwehaveonlyasamplefromthispopulation.8.GrantedthattheSRFisonlyanapproximationofPRF.CanwefindamethodoraprocedurethatwillmakethisapproximationascloseaspossibleSRF仅仅是PRF的近似,那么能不能找到一种方法使这种近似尽可能接近真实呢9.Specialmeaningof“linear”1)Linearityinthevariables变量线性Theconditionalmeanvalueofthedependentvariableisalinearfunctionoftheindependentvariables2)LinearityintheParameters参数线性Theconditionalmeanofthedependentvariableisalinearfunctionoftheparameters,theBs;
itmayormaynotbelinearinthevariables.第三章1.UnlesswearewillingtoassumehowthestochasticUtermsaregenerated,wewillnotbeabletotellhowgoodanSRFisasanestimateofthetruePRF.只有假定了随机误差的生成过程,才能判定SRF对PRF拟合的是好是坏。
2.ClassicalLinearRegressionModel1)Assumption1:
Theregressionmodelislinearintheparameters.Itmayormaynotbelinearinthevariables.回归模型是参数线性的,但不一定是变量线性的。
2)Assumption2:
TheexplanatoryvariablesXisuncorrelatedwiththedisturbancetermU.Xsarenonstochastic,Uisstochastic.解释变量X与扰动误差项u不相关.X是非随机的,U是随机的。
3)Assumption3:
GiventhevalueofXi,theexpected,ormeanvalueofthedisturbancetermUiszero.给定Xi,扰动项的期望或均值为零。
DisturbanceUrepresentallthosefactorsthatarenotspecificallyintroducedinthemodel干扰项U代表了所有未纳入模型的影响因素。
4)Assumption4:
ThevarianceofeachUiisconstant,orhomoscedastic.U的方差为常数,或同方差。
Homoscedasticity(同方差):
a.ThisassumptionsimplymeansthattheconditionaldistributionofeachYpopulationcorrespondingtothegivenvalueofXhasthesamevariance.该假定表明,与给定的X相对应的每个Y的条件分布具有同方差。
b.TheindividualYvaluesarespreadaroundtheirmeanvalueswiththesamevariance.即每个Y值以相同的方差分布在其均值周围。
5)Assumption5:
Thereisnocorrelationbetweentwoerrorterms,thisistheassumptionofno-autocorrelation.无自相关假定,即两个误差项之间不相关。
6)Assumption6:
Theregressionmodeliscorrectlyspecified.回归模型是正确假定的。
Thereisnospecificationbiasorspecificationerrorinthemodel.实证分析的模型不存在设定偏差或设定误差。
Thisassumptioncanbeexplainedinformallyasfollows.Aneconometricinvestigationbeginswiththespecificationoftheeconometricmodelunderlyingthephenomenonofinterest.andStandarderrorsofOLSestimators普通最小二乘估计量的方差与标准误:
OneimmediateresultoftheassumptionsintroducedisthattheyenableustoestimatethevariancesandstandarderrorsoftheOLSestimatorsgiveninEq.and.shouldknow:
VariancesoftheestimatorsStandarderrorsoftheestimatorsisthevalueofThehomoscedasticisestimatedfromformulaErroroftheRegression(SER)回归标准误IssimplythestandarddeviationoftheYvaluesabouttheestimatedregressionline.Y值偏离估计回归的标准差。
ofmathfunction1)InterpretationThestandarddeviation,orstandarderror,is,isameasureofvariabilityofb2fromsampletosample.Ifwecansaythatourcomputedb2lieswithinacertainnumberofstandarddeviationunitsfromthetrueB2,wecanstatewithsomeconfidencehowgoodthecomputedSRFisasanestimatorofthetruePRF.2)SamplingDistribution抽样分布Oncewedeterminethesamplingdistributionofourtwoestimators,thetaskofhypothesistestingbecomesstraightforward.一旦确定了两个估计量的抽样分布,那么假设检验就是举手之劳的事情。
doweuseOLSThepropertiesofOLSestimatorsThemethodofOLSisusedpopularlynotonlybecauseitiseasytousebutalsobecauseithassomestrongtheoreticalproperties.OLS法得到广泛使用,不仅是因为它简单易行,还因为它具有很强的理论性质。
theorem高斯-马尔科夫定理Giventheassumptionsoftheclassicallinearregressionmodel(CLRM),theOLSestimatorshaveminimumvarianceintheclassoflinearOLSestimatorsareBLUE(bestlinearunbiasedestimators)满足古典线性模型的基本假定,则在所有线性据计量中,OLS估计两具有最小方差性,即OLS是最优线性无偏估计量(BLUE)10.BLUEproperty最优线性无偏估计量的性质1)B1andB2arelinearestimators.B1和B2是线性估计量2)Theyareunbiased,thatisE(b1)=B1,E(b2)=B2.B1和B2是无偏估计两3)TheOLSestimatoroftheerrorvarianceisunbiased.误差方差的OLS估计量是无偏的4)b1andb2areefficient和B2是有效估计量Var(b1)islessthanthevarianceofanyotherlinearunbiasedestimatorofB1Var(b2)islessthanthevarianceofanyotherlinearunbiasedestimatorofB211.MonteCarlosimulation蒙特卡洛模拟DotheexperimentatlabDoitbyExcell.=NORMINV(RAND(),0,2)Doitbymatlab.=NORMINV(uniform(),MU,SIGMA)DoitbyStata.=invnorm(uniform()12.CentralLimitTheorems中心极限定理Ifthereisalargenumberofindependentandidenticallydistributed(iid)randomvariables,then,withafewexceptions,thedistributionoftheirsumtendstobeanormaldistributionasthenumberofsuchvariablesincreasesindefinitely.随着变量个数的无限增加,独立同分布随机变量近似服从正态分布13.RecallU,theerrortermrepresentstheinfluenceofallthoseforcesthataffectYbutarenotspecificallyincludedintheregressionmodelbecausetherearesomanyofthemandtheindividualeffectofanyonesuchforceonYmaybetoominor.误差项代表了未纳入回归模型的其他所有因素的影响。
因为在这些影响中,每种因素对Y的影响都很微弱Ifalltheseforcesarerandom,ifweletUrepresentthesumofalltheseforces,thenbyinvokingtheCLT,wecanassumethattheerrortermUfollowsthenormaldistribution.如果所有这些影响因素都是随机的,用U代表所有这些影响因素之和,那么根据中心极限定理,可以假定误差项服从正态分布。
14.Anotherpropertyofnormaldistribution另一个正态分布的性质Anylinearfunctionofanormallydistributedvariableisitselfnormallydistributed.正态变量的性质函数仍服从正态分布。
15.Hypothesistesting假设检验HavingknownthedistributionofOLSestimatorsb1andb2,wecanproceedthetopicofhypothesistesting.16.Nullhypothesis零假设“zero”nullhypothesisisdeliberatelychosentofindoutwhetherYisrelatedtoXalall,whichisalsocalledstrawmanhypothesis.之所以选择这样一个假设是为了确定Y是否与X有关,也称为稻草人假设。
17.Weneedsomeformaltestingproceduretorejectorreceivethenullhypothesisandmaketheskepticalguysshutup.需要正规的检验过程拒绝或接受零假设18.IfournullhypothesisisB2=0andthecomputedb2=,wecanfindouttheprobabilityof
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