計量經(jīng)濟學教學大綱

課程編號：150143A課程類型：學科基礎課總學時：48講課學時：48實驗（上機）學時：0學分：3適用對象：金融學（數(shù)據(jù)與計量分析）先修課程：微觀經(jīng)濟學、宏觀經(jīng)濟學、概率與統(tǒng)計、線性代數(shù)、微積分CourseCode:150143ACourseType:DisciplinebasiccoursePeriods:48Lecture:48Experiment(Computer):0Credits:3ApplicableSubjects:FinancePreparatoryCourses:Microeconomics,Macroeconomics,ProbabilityandStatistics,LinearAlgebra,MathematicalAnalysis一、課程的教學目標本課程是面向經(jīng)濟學、管理學及金融學專業(yè)本科學生開設的計量經(jīng)濟學入門課程。計量經(jīng)濟學是經(jīng)濟學科中的核心必修課程，它為經(jīng)濟研究者提供了在分析經(jīng)濟數(shù)據(jù)、歸納經(jīng)濟現(xiàn)象、和總結(jié)經(jīng)濟規(guī)律時所必需的實證研究工具。作為計量經(jīng)濟學入門課程，我們希望學生通過課堂學習與實際操作，掌握計量經(jīng)濟學的基礎理論和基本分析方法，能夠利用統(tǒng)計軟件處理經(jīng)濟數(shù)據(jù)，建立線性回歸模型，估計模型并進行假設檢驗。本課程將為學習中級計量經(jīng)濟學、金融計量經(jīng)濟學、和學生從事獨立實證研究奠定扎實的基礎。本課程可以使學生對我國的經(jīng)濟發(fā)展有更清晰的了解，對我國發(fā)展教育事業(yè)的重要意義有進一步的認識，增強學生的愛國情懷，幫助學生提高對社會正能量價值觀的認同感。ThiscourseisanintroductiontoEconometrics,tailoredforundergraduatestudentswhosemajorisEconomics,Management,orFinance.EconometricsisacoresubjectinEconomics,equippingresearcherswithessentialtoolsforanalyzingeconomicdata,anddiscoveringtheregularitiesunderlyingtheseeminglyperplexingeconomicphenomena.Asanintroductorycourse,weexpectstudentstobeabletocomprehendbasicconceptsandmasterbasicmethodsinEconometrics.Throughlearninginclassandpracticingusingcomputersoftware,studentsshouldbecapableofhandlingeconomicdata,constructingalinearregressionmodel,estimatingthemodel,andperforminghypothesistesting.Thiscoursewillprovidesolidfoundationsforfurtherstudyinthecourses,suchasIntermediateEconometricsandFinancialEconometrics,andforstudents’ownempiricalresearch.ThiscoursewillleadstudentstohaveaclearerunderstandingofeconomicdevelopmentinChinaandbetterrecognizethegreatimportanceofeducationaldevelopmentinChina.Inaddition,thiscoursewillstrengthenthepatrioticfeelingsofstudents,andhelpstudentshaveabetterrecognitionofpositivevalues.二、教學基本要求本課程教學的基本要求是，對計量經(jīng)濟學要理論學習與實際應用并重。作為入門課程，理論學習強調(diào)對計量經(jīng)濟學理論的整體把握，對基礎概念與原理的準確理解，和對基本估計與檢驗方法的精通掌握。理論學習涵蓋以下內(nèi)容：一元線性回歸模型的估計與假設檢驗，多元線性回歸模型的估計和假設檢驗，以及對模型設定的評價。在時間允許的情況下，本課程還將介紹面板數(shù)據(jù)回歸與工具變量法的基本原理與方法。本課程將圍繞如何判斷自變量與因變量之間的因果關系這一核心問題展開，重點講解如何利用多元線性回歸模型分析橫截面數(shù)據(jù)中的因果關系。計量經(jīng)濟學理論學習必須結(jié)合實際應用。本課程將結(jié)合課本中各章節(jié)的實例，利用相關數(shù)據(jù)，講授如何使用計算機軟件（如STATA，EViews或者R語言）實現(xiàn)模型估計與檢驗。本課程教學方法將以課堂講授為主。由于課程內(nèi)容難度相對較大，我們鼓勵學生課前預習，課上積極參與討論，并課后復習和獨立完成作業(yè)。計算機語言的學習以課堂展示和學生上機實際操作的方式完成。我們將結(jié)合教學實例，為學生提供完整的計算機語言操作說明，并安排上機作業(yè)。課程考核由一般作業(yè)、上機作業(yè)、隨堂測驗、期中和期末考試組成?？己顺煽?yōu)榘俜种?，各項分?shù)分配見表（一）。隨堂測驗、期中和期末考試均為閉卷考試。為了減少“死記硬背”，我們允許學生在期中和期末考試中攜帶一張“小抄”用來記憶定理與公式。為了鼓勵學生參與課堂討論，我們將給予表現(xiàn)積極的學生最高5%的獎勵分。表（一）：分數(shù)分配方式一般作業(yè)15%上機作業(yè)5%隨堂測試10%期中考試30%期末考試40%Thiscourseemphasizesonboththeoreticallearningandrealapplications.Atanintroductorylevel,thecourseexpectsthatstudentswillcomprehendthegeneralframeworkofEconometrics,accuratelyunderstandthebasicconceptsandtheories,andmasterthefundamentalmethodsofestimationandinference.Servingfortheseends,thecontentsofthiscoursecover,butnotlimitedto,thesingleandmultipleordinaryleastsquares(OLS)regressionestimation,hypothesistesting,modelspecificationassessment,paneldataregression,andinstrumentalvariablesregression.Thecoresubjectofthiscourseishowtouseamultipleregressionmodeltoanalyzethecausalrelationshipbetweenthedependentvariableandtheindependentvariableswhenusingcross-sectionaldata.Moreover,thecoursestressestheimportanceofrealapplicationsalongwiththeoreticallearning.Studentswilllearnhowtousecomputersoftware(suchasSTATA，EviewsorRprogramminglanguage)toimplementestimationandinferenceofmultipleregressionmodelsusingtherealdataoftheapplicationsineachchapterinthetextbook.Thebasicteachingstrategyofthiscoursemainlyinvolvesin-classlectures.Duetothedifficultyofthecourse,weencouragestudentstobrowsetheassignedreadingmaterialsbeforeclass,toproactivelyparticipatediscussionsinclass,andtoperuselecturenotesandindependentlycompletehomeworkafterclass.Studentswilllearnprogramminglanguagethroughin-classinstructionsandpractice.Withthedataofrealapplicationsinthetextbook,wewillprovidestudentswithcompletetutorialsandassignempiricalexercisesforpractice.Themethodsofthecourseevaluationincludegeneralhomework,practicalexercises,quiz,mid-termandfinalexams.ThegradedistributionofeachcomponentwithinonehundredpercentagepointsispresentedinTable1.Thequiz,mid-termandfinalexamsareallclosed-bookexams.Topreventstudentsfromcrammingfortheexams,weallowstudentstobringacheat-sheetforremindingthemselvesofimportanttheoremsandformulawhentakingthemid-termandfinalexams.Finally,topromoteclassparticipation,wewillawardthestudentsengagingfrequentin-classdiscussionsforashighas5%bonuspoints.Table1:ThegradedistributionHomework15%PracticalExercises5%Quiz10%Midtermexam30%Finalexam40%三、各教學環(huán)節(jié)學時分配教學課時分配(Theassignmentofhoursofinstruction)序號(No.)章節(jié)內(nèi)容(Content)講課(Lecture)實驗(Experiment)其他(Others)合計(Total)1導論(Introduction)112概率論回顧(ReviewofProbability)223數(shù)理統(tǒng)計回顧(ReviewofStatistics)224線性代數(shù)回顧與計算機語言初步(ReviewofLinearAlgebraandIntroductiontoprogramminglanguage)1125隨堂測試(Quiz)116一元線性回歸模型(LinearRegressionwithOneRegressor)2247一元線性回歸模型假設檢驗(HypothesisTestofLinearRegressionwithaSingleRegressor)2248期中考試(Mid-termexam)229多元線性回歸模型(LinearRegressionwithMultipleRegressors)33610多元線性回歸模型假設檢驗(HypothesisTestsinMultipleRegression)33611非線性回歸方程(NonlinearRegressionFunctions)32512回歸模型評價(AssessingStudiesBasedonMultipleRegression)4413面板數(shù)據(jù)回歸(RegressionwithPanelData)22414工具變量法(InstrumentalVariablesRegression)31415回顧與總結(jié)(ReviewandSummary)11合計(Total)321648四、教學內(nèi)容（黑體，小四號字）第一講導論第一節(jié)什么是計量經(jīng)濟學第二節(jié)計量經(jīng)濟學中的研究問題第三節(jié)因果關系與實驗方法因果關系估計隨機控制實驗第四節(jié)數(shù)據(jù)來源與類型實驗數(shù)據(jù)與觀測數(shù)據(jù)數(shù)據(jù)類型教學重點、難點：了解計量經(jīng)濟學在經(jīng)濟學科中的地位和作用，理解如何通過隨機實驗推斷變量間因果關系。課程的考核要求：課后閱讀第二講概率論回顧第一節(jié)隨機變量與概率分布概率、樣本空間與隨機變量離散隨機變量的概率分布連續(xù)隨機變量的概率分布第二節(jié)隨機變量的期望與方差隨機變量的期望標準差與方差第三節(jié)兩個隨機變量的聯(lián)合分布與協(xié)方差聯(lián)合分布與邊際分布條件分布獨立、協(xié)方差與相關性第四節(jié)正態(tài)分布、開方分布、t分布與F分布正態(tài)分布開方分布t分布F分布第五節(jié)隨機樣本與樣本均值的抽樣分布隨機抽樣樣本均值的抽樣分布第六節(jié)大樣本的漸進分布大數(shù)定律與一致性中心極限定理教學重點、難點：掌握計算隨機變量期望、方差、條件期望和協(xié)方差的公式，了解樣本均值的大樣本特征。課程的考核要求：課后閱讀、完成作業(yè)第三講數(shù)理統(tǒng)計回顧第一節(jié)總體均值的估計估計量及其特征隨機抽樣的重要性第二節(jié)關于總體均值的假設檢驗零假設與備擇假設t統(tǒng)計量及其大樣本分布顯著性水平、臨界值和p值第三節(jié)總體均值的置信區(qū)間第四節(jié)散點圖、樣本協(xié)方差和相關系數(shù)教學重點、難點：理解假設檢驗的基本原理，掌握p值、臨界值和置信區(qū)間的計算。課程的考核要求：課后閱讀、完成作業(yè)第四講線性代數(shù)回顧與R語言初步第一節(jié)向量與矩陣第二節(jié)矩陣的運算第三節(jié)逆矩陣第四節(jié)線性獨立第五節(jié)特征值與正定性第六節(jié)R語言初步教學重點、難點：熟練掌握用向量和矩陣表示一組變量的樣本值，掌握矩陣的基本運算。課程的考核要求：課后閱讀、完成作業(yè)、完成上機練習第五講一元線性回歸模型第一節(jié)線性回歸模型第二節(jié)估計線性回歸模型中的參數(shù)最小二乘估計量估計參數(shù)的解釋第三節(jié)模型擬合的衡量擬合優(yōu)度(R2)回歸標準差(SER)第四節(jié)最小二乘估計的假設第五節(jié)最小二乘估計量的抽樣分布教學重點、難點：熟練掌握最小二乘估計法，掌握最小二乘估計量的推導與公式，理解最小二乘估計的假設課程的考核要求：課后閱讀、完成作業(yè)、完成上機練習第六講一元線性回歸模型假設檢驗第一節(jié)單系數(shù)的假設檢驗關于斜率的雙邊與單邊檢驗關于截距的檢驗第二節(jié)回歸系數(shù)的置信區(qū)間第三節(jié)虛擬變量回歸系數(shù)的解釋第四節(jié)異方差與同方差異方差與同方差的定義同方差的數(shù)學含義第五節(jié)最小二乘法的理論基礎高斯-馬科夫定理教學重點、難點：熟練掌握單參數(shù)假設檢驗的方法，掌握虛擬變量在回歸模型中的作用，理解異方差和高斯-馬科夫定理課程的考核要求：課后閱讀、完成作業(yè)、完成上機練習第七講多元線性回歸模型第一節(jié)多元回歸模型總體回歸線總體多元回歸模型多元回歸模型的矩陣表示第二節(jié)多元回歸模型的最小二乘估計量最小二乘估計量估計系數(shù)的解釋第三節(jié)多元回歸模型擬合的衡量回歸標準差(SER)擬合優(yōu)度(R2)調(diào)整擬合優(yōu)度(AdjustedR2)第四節(jié)多元回歸的最小二乘假設第五節(jié)多元回歸最小二乘估計量的統(tǒng)計特性第六節(jié)缺失變量誤差第七節(jié)多重共線性第八節(jié)我國地區(qū)經(jīng)濟發(fā)展和地區(qū)教育支出和教育消費的關系教學重點、難點：熟練掌握多元回歸模型的最小二乘估計法，掌握運用矩陣表示回歸模型與估計量，理解估計量的統(tǒng)計特性、缺失變量誤差和多重共線性。通過學習我國地區(qū)經(jīng)濟發(fā)展和地區(qū)教育支出和教育消費的關系，學生會對我國經(jīng)濟發(fā)展會有更清晰的了解，對我國發(fā)展教育事業(yè)的重要意義有進一步的認識。課程的考核要求：課后閱讀、完成作業(yè)、完成上機練習第八講多元線性回歸模型假設檢驗第一節(jié)單系數(shù)的假設檢驗和置信區(qū)間最小二乘估計量的標準差單系數(shù)的假設檢驗單系數(shù)的置信區(qū)間第二節(jié)聯(lián)合假設的檢驗聯(lián)合假設的形式F統(tǒng)計量同方差下的F統(tǒng)計量第三節(jié)多系數(shù)的置信集合第四節(jié)我國地區(qū)經(jīng)濟發(fā)展和地區(qū)教育支出和教育消費的關系的假設檢驗教學重點、難點：熟練掌握運用F統(tǒng)計量推斷聯(lián)合假設，掌握聯(lián)合假設的形式，和理解F統(tǒng)計量的含義。通過學習我國地區(qū)經(jīng)濟發(fā)展和地區(qū)教育支出和教育消費的關系的假設檢驗，學生會對我國經(jīng)濟發(fā)展有清晰的了解，對我國發(fā)展教育事業(yè)的重要意義有進一步的認識。課程的考核要求：課后閱讀、完成作業(yè)、完成上機練習第九講非線性回歸方程第一節(jié)非線性回歸方程的一般形式第二節(jié)單自變量的非線性方程變換多項式對數(shù)函數(shù)第三節(jié)自變量的交互效應虛擬變量的交互效應虛擬變量與連續(xù)變量的交互效應連續(xù)變量的交互效應教學重點、難點：熟練掌握非線性回歸模型的基本形式，掌握回歸系數(shù)的正確解釋方法課程的考核要求：課后閱讀、完成作業(yè)、完成上機練習第十講評價回歸模型第一節(jié)內(nèi)部和外部有效性對內(nèi)部有效性的威脅對外部有效性的威脅第二節(jié)回歸模型的內(nèi)部有效性問題缺失變量誤差模型形式的錯誤設定測量誤差及其估計偏差缺失數(shù)據(jù)與樣本選擇性雙向因果關系教學重點、難點：理解內(nèi)部和外部有效性的定義，掌握影響回歸模型內(nèi)部有效性的因素課程的考核要求：課后閱讀、完成作業(yè)第十一講面板數(shù)據(jù)回歸第一節(jié)面板數(shù)據(jù)第二節(jié)兩時期面板數(shù)據(jù)：事前事后比較法第三節(jié)固定效應回歸模型固定效應回歸模型的估計與推斷第四節(jié)加入時間固定效應教學重點、難點：掌握固定效應面板數(shù)據(jù)回歸的基本估計方法課程的考核要求：課后閱讀、完成作業(yè)、完成上機練習第十二講工具變量法第一節(jié)單自變量與單工具變量的回歸模型工具變量與假設二階段最小二乘法第二節(jié)一般回歸模型的工具變量估計法多元回歸模型中的二階段最小二乘法工具變量的相關性和外生性工具變量回歸模型的假設與二階段最小二乘估計量的抽樣分布工具變量回歸模型的假設檢驗第三節(jié)檢驗工具變量的有效性教學重點、難點：理解工具變量法的基本原理，掌握二階段最小二乘法課程的考核要求：課后閱讀、完成作業(yè)、完成上機練習Lecture1IntroductionSection1.1WhatisEconometricsAbout?Section1.2EconomicQuestionsWeExamineSection1.3CausalEffectsandIdealizedExperimentsEstimationofCausalEffectsRandomizedControlledExperimentsSection1.4DataSourcesandTypesExperimentalVersusObservationalDataDataTypesKeyandDifficultPoints:KnowtherolesandstatusofEconometricsinthesubjectofEconomics,andunderstandhowtouserandomizedcontrolledexperimentstoassessthecausalrelationshipamongvariables.EvaluationRequirements:ReadingrelevantmaterialsLecture2ReviewofProbabilitySection2.1RandomVariablesandProbabilityDistributionsProbabilities,theSampleSpace,andRandomVariablesProbabilityDistributionofaDiscreteRandomVariableProbabilityDistributionofaContinuousRandomVariableSection2.2TheExpectedValueandtheVarianceofaRandomVariableTheExpectedValueofaRandomVariableTheStandardDeviationandVarianceSection2.3TwoRandomVariablesJointandMarginalDistributionsConditionalDistributionsIndependence,Covariance,andCorrelationSection2.4TheNormal,Chi-Squared,Studentt,andFDistributionsTheNormalDistributionTheChi-SquaredDistributionTheStudenttDistributionTheFDistributionSection2.5RandomSamplingandtheDistributionoftheSampleAverageRandomSamplingTheSamplingDistributionoftheSampleAverageSection2.6Large-SampleApproximationstoSamplingDistributionsTheLawofLargeNumbersandConsistencyTheCentralLimitTheoremKeyandDifficultPoints:Masterthecalculationoftheexpectedvalue,variance,covariance,andconditionalmean,andunderstandthelarge-samplepropertiesofthesampleaverage.EvaluationRequirements:Readingmaterials,andfinishinghomeworkLecture3ReviewofStatisticsSection3.1EstimationofthePopulationMeanEstimatorsandTheirPropertiesTheImportanceofRandomSamplingSection3.2HypothesisTestingConcerningthePopulationMeanNullandAlternativeHypothesesThet-StatisticanditsSamplingDistributionwithLargeSamplesTheSignificanceLevel,theCriticalValue,andthep-ValueSection3.3ConfidenceIntervalsforthePopulationMeanSection3.4Scatterplots,theSampleCovariance,andtheSampleCorrelationKeyandDifficultPoints:Understandthebasicphilosophyofhypothesistesting,andmasterthecalculationofthep-value,thecriticalvalue,andtheconfidenceintervalconcerningthepopulationmean.EvaluationRequirements:Readingmaterials,andfinishinghomeworkLecture4ReviewofLinearAlgebraandanIntroductiontoRSection4.1VectorsandMatricesSection4.2MatrixOperationsSection4.3InverseMatrixSection4.4LinearIndependenceSection4.5EigenvaluesandPositive-DefinitenessSection4.6IntroductiontoRKeyandDifficultPoints:Masterthemethodofrepresentingtheobservationsofagroupofvariablesusingvectorsandmatrices,andgraspbasicmatrixoperations.EvaluationRequirements:Readingmaterials,finishinghomework,completingthepracticalexercisesLecture5LinearRegressionwithOneRegressorSection5.1TheLinearRegressionModelSection5.2EstimatingtheCoefficientsoftheLinearRegressionModelTheOLSestimatorsInterpretationoftheestimatedcoefficientsSection5.3MeasuresofFitR2TheStandardErrorofRegression(SER)Section5.4TheLeastSquaresAssumptionsSection5.5SamplingDistributionoftheOLSEstimatorsKeyandDifficultPoints:MastertheOLSestimationmethod,graspthederivationoftheformulaoftheOLSestimators,andunderstandtheleastsquaresassumptionsEvaluationRequirements:Readingmaterials,finishinghomework,andcompletingpracticalexercisesLecture6HypothesisTestofLinearRegressionwithaSingleRegressorSection6.1TestingHypothesesaboutOneoftheRegressionCoefficientsTwo-SidedandOne-SidedHypothesesConcerningtheSlopeHypothesesConcerningtheInterceptSection6.2ConfidenceIntervalsforaRegressionCoefficientSection6.3RegressionWhenXisaBinaryVariableInterpretationoftheRegressionCoefficientsonaBinaryVariableSection6.4HeteroskedasticityandHomoskedasticityWhatareheteroskedasticityandhomoskedasticity?MathematicalImplicationsofHeteroskedasticitySection6.5TheTheoreticalFoundationsofOrdinaryLeastSquaresTheGauss-MarkovTheoremKeyandDifficultPoints:Mastertheapproachtohypothesistestingconcerningonecoefficient,grasptheuseofabinaryvariableinregression,andunderstandheteroskedasticityandtheGauss-Markovtheorem.EvaluationRequirements:Readingmaterials,finishinghomework,andcompletingpracticalexercisesLecture7LinearRegressionwithMultipleRegressorsSection7.1TheMultipleRegressionModelThePopulationRegressionLineThePopulationRegressionModelMatrixNotationoftheMultipleRegressionModelSection7.2TheOLSEstimatorinMultipleRegressionTheOLSEstimatorsInterpretationoftheEstimatedCoefficientsSection7.3MeasuresofFitinMultipleRegressionTheStandarderrorsoftheregression(SER)R2TheAdjustedR2Section7.4TheLeastSquaresAssumptionsinMultipleRegressionSection7.5TheStatisticalPropertiesoftheOLSEstimatorsinMultipleRegressionSection7.6TheOmittedVariableBiasSection7.7MulticollinearitySection7.8TheRelationshipBetweenRegionalEconomicDevelopmentinChinaandTwoFactors:RegionalEducationalExpensesandEducationalConsumption.KeyandDifficultPoints:MastertheOLSestimationmethodinmultipleregression,graspthewaytorepresentthemultipleregressionmodelandtheOLSestimatorsusingmatrices,andunderstandthestatisticalpropertiesoftheOLSestimators,andtheconceptsoftheomittedvariablebiasandmulticollinearity.BystudyingtherelationshipbetweenregionaleconomicdevelopmentinChinaandtwofactors(i.e.regionaleducationalexpensesandeducationalconsumption),thestudentswillhaveaclearerunderstandingofeconomicdevelopmentinChinaandbetterrecognizethegreatimportanceofeducationaldevelopmentinChina.EvaluationRequirements:Readingmaterials,finishinghomework,andcompletingpracticalexercisesLecture8HypothesisTestsinMultipleRegressionSection8.1HypothesistestsandconfidenceintervalsforasinglecoefficientStandarderrorsfortheOLSestimatorsHypothesisTestsforaSingleCoefficientConfidenceIntervalsforaSingleCoefficientSection8.2TestsofjointhypothesesTheFormsofJointhypothesisTheF-StatisticTheHomoskedasticity-OnlyF-StatisticSection8.3ConfidenceSetsforMultipleCoefficientsSection8.4TestingHypothesesontheRelationshipBetweenRegionalEconomicDevelopmentinChinaandTwoFactors:RegionalEducationalExpensesandEducationalConsumption.KeyandDifficultPoints:MastertheapproachtousingtheF-statisticforjointhypothesistesting,graspthevariousformsofjointhypotheses,andunderstandtheimplicationoftheF-statistic.BytestinghypothesesontherelationshipbetweenregionaleconomicdevelopmentinChinaandtwofactors(i.e.regionaleducationalexpensesandeducationalconsumption),thestudentswillhaveaclearerunderstandingofeconomicdevelopmentinChinaandbetterrecognizethegreatimportanceofeducationaldevelopmentinChina.EvaluationRequirements:Readingmaterials,finishinghomework,andcompletingpracticalexercisesLecture9NonlinearRegressionFunctionsSection9.1AGeneralStrategyforModelingNonlinearRegressionFunctionsSection9.2NonlinearfunctionsofasingleindependentvariablePolynomialsLogarithmsSection9.3InteractionsbetweenindependentvariablesInteractionsbetweentwobinaryvariablesInteractionsbetweenacontinuousandabinaryvariableInteractionsbetweentwocontinuousvariablesKeyandDifficultPoints:Masterthebasicformsofnonlinearregressionfunctions,andmasterthecorrectinterpretationofcoefficientsinnonlinearregressionfunctions.EvaluationRequirements:Readingmaterials,finishinghomework,andcompletingpracticalexercisesLecture10AssessingStudiesBasedonMultipleRegressionSection10.1InternalandexternalvalidityThreatstoInternalValidityThreatstoExternalValiditySection10.2ThreatstointernalvalidityofmultipleregressionanalysisOmittedVariableBiasMisspecificationoftheFunctionalFo