面板數(shù)據(jù)分析：英文版

定　價(jià)：￥48.00

作　者：	（美）Cheng Hsiao著
出版社：	北京大學(xué)出版社
叢編項(xiàng)：	經(jīng)濟(jì)學(xué)前沿影印叢書
標(biāo)　簽：	暫缺

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ISBN：	9787301092187	出版時(shí)間：	2005-09-01	包裝：	平裝
開(kāi)本：	24cm	頁(yè)數(shù)：	366	字?jǐn)?shù)：

內(nèi)容簡(jiǎn)介

　　《面板數(shù)據(jù)分析》（第2版）是面板數(shù)據(jù)分析這一領(lǐng)域的經(jīng)典之作，《面板數(shù)據(jù)分析》（第2版）系統(tǒng)地介紹了有關(guān)面板數(shù)據(jù)的基本理論，尤其是對(duì)面板數(shù)據(jù)在控制未觀察到的個(gè)體或時(shí)間偏差，以避免設(shè)定誤差，改善估計(jì)效率方面的應(yīng)用；并且，《面板數(shù)據(jù)分析》（第2版）審慎地使用了實(shí)證研究的案例，這使得《面板數(shù)據(jù)分析》（第2版）對(duì)經(jīng)濟(jì)學(xué)、商學(xué)、社會(huì)學(xué)和政治科學(xué)的研究生和研究人員非常有用。在1986年第一版的成功基礎(chǔ)上，《面板數(shù)據(jù)分析》（第2版）第二版對(duì)第一版進(jìn)行了豐富的修改，以一種嚴(yán)謹(jǐn)易讀的方式將有關(guān)面板數(shù)據(jù)研究的近期進(jìn)展加入到書中，并且使這部分內(nèi)容與原有的內(nèi)容融為一體。第二版特別的修改包括：介紹了貝葉斯方法以及在廣義矩方法框架下的估計(jì)量的嚴(yán)格外生性的概念，使得各種模型的識(shí)別聯(lián)系起來(lái)；對(duì)估計(jì)離散選擇模型的半?yún)?shù)方法提出了直覺(jué)解釋；以及介紹了面板樣本選擇模型的估計(jì)的成對(duì)整理方法（methods of pairwise trimming）等。

作者簡(jiǎn)介

　　蕭政，是南加州大學(xué)經(jīng)濟(jì)學(xué)教授。本書的第1版已經(jīng)成為經(jīng)濟(jì)學(xué)文獻(xiàn)中有關(guān)面板數(shù)據(jù)的標(biāo)準(zhǔn)介紹。他還是《經(jīng)濟(jì)計(jì)量模型、技術(shù)與應(yīng)用》一書的合作者，并與他人共同主編了《面板模型和受限因變量模型分析》及《非線性統(tǒng)計(jì)推斷》等著作。他是計(jì)量經(jīng)濟(jì)學(xué)會(huì)的成員以及《計(jì)量經(jīng)濟(jì)學(xué)雜志》的主編和會(huì)員。

圖書目錄

PrefacetotheSecondEdition
PrefacetotheFirstEdition
Chapter1.Introduction
1.1AdvantagesofPanelData
1.2IssuesInvolvedinUtilizingPanelData
1.2.1HeterogeneityBias
1.2.2SelectivityBias
1.3OutlineoftheMonograph
Chapter2.AnalysisofCovariance
2.1Introduction
2.2AnalysisofCovariance
2.3AnExample
Chapter3.SimpleRegressionwithVariableIntercepts
3.1Introduction
3.2Fixed-EffectsModels:Least-SquaresDummy-VariableApproach
3.3Random-EffectsModels:EstimationofVariance-ComponentsModels
3.3.1CovarianceEstimation
3.3.2Generalized-Least-SquaresEstimation
3.3.3MaximumLikelihoodEstimation
3.4FixedEffectsorRandomEffects
3.4.1AnExample
3.4.2ConditionalInferenceorUnconditional(Marginal)Inference
3.4.2.aMundlak'sFormulation
3.4.2.bConditionalandUnconditionalInferencesinthePresenceorAbsenceofCorrelationbetweenIndividualEffectsandAttributes
3.5TestsforMisspecification
3.6ModelswithSpecificVariablesandBothIndividual-andTime-SpecificEffects
3.6.1EstimationofModelswithIndividual-SpecificVariables
3.6.2EstimationofModelswithBothIndividualandTimeEffects
3.7Heteroscedasticity
3.8ModelswithSeriallyCorrelatedErrors
3.9ModelswithArbitraryErrorStructure-ChamberlainπApproach
Appendix3A:ConsistencyandAsymptoticNormalityofthe
Minimum-DistanceEstimator
Appendix3B:CharacteristicVectorsandtheInverseofthe
Variance-CovarianceMatrixofa
Three-ComponentModel
Chapter4.DynamicModelswithVariableIntercepts
4.1Introduction
4.2TheCovarianceEstimator
4.3Random-EffectsModels
4.3.1BiasintheOLSEstimator
4.3.2ModelFormulation
4.3.3EstimationofRandom-EffectsModels
4.3.3.aMaximumLikelihoodEstimator
4.3.3.bGeneralized-Least-SquaresEstimator
4.3.3.cInstrumental-VariableEstimator
4.3.3.dGEneralizedMethodofMomentsEstimator
4.3.4TestingSomeMaintainedHypothesesonInitialConditions
4.3.5SimulationEvidence
4.4AnExample
4.5Fixed-EffectsModels
4.5.1TransformedLikelihoodApproach
4.5.2Minimum-DistanceEstimator
4.5.3RelationsbetweentheLikelihood-BasedEstimatorandtheGeneralizedMethodofMomentsEstimator(GMM)
4.5.4Random-versusFixed-EffectsSpecification
4.6EstimationofDynamicModelswithArbitaryCorrelationsintheResiduals
4.7Fixed-EffectsVectorAutoregressiveModels
4.7.1ModelFormulation
4.7.2GeneralizedMethodofMoments(GMM)Estimation
4.7.3(Transformed)MaximumLikelihoodEstimator
4.7.4Minimum-DistanceEstimator
Appendix4A:DerivationoftheAsymptoticCovarianceMatrixoftheFeasibleIVIDE
Chapter5.Simultaneous-EquationsModels
5.1Introduction
5.2JointGeneralized-Least-SquaresEstimationTechnique
5.3EstimationofStructuralEquations
5.3.1EstimationofaSingleEquationintheStructuralModel
5.3.2EstimationoftheCompleteStructuralSystem
5.4TriangularSystem
5.4.1Identification
5.4.2Estimation
5.4.2.aInstrumental-VariableMethod
5.4.2.bMaximum-LikelihoodMethod
5.4.3AnExample
Appendix5A
Chapter6.Variable-CoefficientModels
6.1Introduction
6.2CoefficientsThatVaryoverCross-SectionalUnits
6.2.1Fixed-CoefficientModel
6.2.2Random-CoefficientModel
6.2.2.aTheModel
6.2.2.bEstimation
6.2.2.cPredictingIndividualCoefficients
6.2.2.dTestingforCoefficientVariation
6.2.2.eFixedorRandomCoefficients
6.2.2.fAnExample
6.3CoefficientsThatVaryoverTimeandCross-SectionalUnits
6.3.1TheModel
6.3.2Fixed-CoefficientModel
6.3.3Random-CoefficientModel
6.4CoefficientsThatEvolveoverTime
6.4.1TheModel
6.4.2PredictingβtbytheKalmanFilter
6.4.3MaximumLikelihoodEstimation
6.4.4TestsforParameterConstancy
6.5CoefficientsThatAreFunctionsofOtherExogenousVariables
6.6AMixedFixed-andRandom-CoefficientsModel
6.6.1ModelFormulation
6.6.2ABayesSolution
6.6.3AnExample
6.6.4RandomorFixedParameters
6.6.4.aAnExample
6.6.4.bModelSelection
6.7Dy.namicRandom-CoefficientModels
6.8AnExample-LiquidityConstraintsandFirmInvestmentExpenditure
Appendix6A:CombinationofTwoNormalDistributions
Chapter7.DiscreteData
7.1Introduction
7.2SomeDiscrete-ResponseModels
7.3ParametricApproachtoStaticModelswithHeterogeneity
7.3.1Fixed-EffectsModels
7.3.1.aMaximumLikelihoodEstimator
7.3.1.bConditionsfortheExistenceofaConsistentEstimator
7.3.1.cSomeMonteCarloEvidence
7.3.2Random-EffectsModels
7.4SemiparametricApproachtoStaticModels
7.4.1MaximumScoreEstimator
7.4.2ARoot-NConsistentSemiparametricEstimator
7.5DynamicModels
7.5.1TheGeneralModel
7.5.2InitialConditions
7.5.3AConditionalApproach
7.5.4StateDependenceversusHeterogeneity
7.5.5TwoExamples
7.5.5.aFemaleEmployment
7.5.5.bHouSeholdBrandChoices
Chapter8.TruncatedandCensoredData
8.1Introduction
8.2AnExample-NonrandomlyMissingData
8.2.1Introduction
8.2.2AProbabilityModelofAttritionandSelectionBias
8.2.3AttritionintheGaryIncome-MaintenanceExperiment
8.3TobitModelswithRandomIndividualEffects
8.4Fixed-EffectsEstimator
8.4.1PairwiseTrimmedLeast-Squaresand
Least-Absolute-DeviationEstimatorsfor
TruncatedandCensoredRegressions
8.4.1.aTruncatedRegression
8.4.1.bCensoredRegressions
8.4.2ASemiparametricTwo-StepEstimatorfortheEndogenouslyDeterminedSampleSelectionModel
8.5AnExample:HousingExpenditure
8.6DynamicTobitModels
8.6.1DynamicCensoredModels
8.6.2DynamicSampleSelectionModels
Chapter9.IncompletePanelData
9.1EstimatingDistributedLagsinShortPanels
9.1.1Introduction
9.1.2CommonAssumptions
9.1.3IdentificationUsingPriorStructureoftheProcessoftheExogenousVariable
9.1.4IdentificationUsingPriorStructureoftheLagCoefficients
9.1.5EstimationandTesting
9.2RotatingorRandomlyMissingData
9.3Pseudopanels(orRepeatedCross-SectionalData)
9.4PoolingofaSingleCross-SectionalandaSingleTime-SeriesDataSet
9.4.1Introduction
9.4.2TheLikelihoodApproachtoPoolingCross-SectionalandTime-SeriesData
9.4.3AnExample
Chapter10.MiscellaneousTopics
10.1SimulationMethods
10.2PanelswithLargeNandT
10.3Unit-RootTests
10.4DatawithMultilevelStructures
10.5ErrorsofMeasurement
10.6ModelingCross-SectionalDependence
Chapter11.ASummaryView
11.1Introduction
11.2BenefitsandLimitationsofPanelData
11.2.1IncreasingDegreesofFreedomandLesseningtheProblemofMulticollinearity
11.2.2IdentificationandDiscriminationbetweenCompetingHypotheses
11.2.3ReducingEstimationBias
11.2.3.aOmitted-VariableBias
11.2.3.bBiasInducedbytheDynamicStructureofaModel
11.2.3.cSimultaneityBias
11.2.3.dBiasInducedbyMeasurementErrors
11.2.4ProvidingMicroFoundationsforAggregateDataAnalysis
11.3EfficiencyoftheEstimates
Notes
References
AuthorIndex
SubjectIndex