Handbook of Empirical Economics and Finance STATISTICS: Textbooks and Monographs D. B. Owen Founding Editor, 1972–1991 Editors N. Balakrishnan William R. Schucany McMaster University Southern Methodist University Editorial Board Thomas B. Barker Nicholas Jewell Rochester Institute of Technology University of California, Berkeley Paul R. Garvey Sastry G. Pantula The MITRE Corporation North Carolina State University Subir Ghos h University of California, Riverside Daryl S. Paulson Biosciences Laboratories, Inc. David E. A. Giles University of Victoria Aman Ullah University of California, Arjun K. Gupta Riverside Bowling Green State University Brian E. White The MITRE Corporation STATISTICS: Textbooks and Monographs Recent Titles The EM Algorithm and Related Statistical Models, edited by Michiko Watanabe and Kazunori Yamaguchi Multivariate Statistical Analysis, Second Edition, Revised and Expanded, Narayan C. 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Visit the Taylor & Francis Web site at http://www.taylorandfrancis.com and the CRC Press Web site at http://www.crcpress.com P1:BINAYAKUMARDASH November12,2010 19:1 C7035 C7035˙C000 Contents Preface..................................................................ix AbouttheEditors.......................................................xv ListofContributors....................................................xvii 1 RobustInferencewithClusteredData................................1 A.ColinCameronandDouglasL.Miller 2 EfficientInferencewithPoorInstruments: AGeneralFramework...............................................29 BertilleAntoineandEricRenault 3 AnInformationTheoreticEstimatorfortheMixedDiscrete ChoiceModel........................................................71 AmosGolanandWilliamH.Greene 4 RecentDevelopmentsinCrossSectionandPanelCountModels....87 PravinK.TrivediandMuratK.Munkin 5 AnIntroductiontoTextualEconometrics...........................133 StephenFaganandRamazanGenc¸ay 6 LargeDeviationsTheoryandEconometric InformationRecovery..............................................155 MarianGrenda´randGeorgeJudge 7 NonparametricKernelMethodsforQualitative andQuantitativeData..............................................183 JeffreyS.Racine 8 TheUnconventionalDynamicsofEconomic andFinancialAggregates...........................................205 KarimM.AbadirandGabrielTalmain 9 StructuralMacroeconometricModeling inaPolicyEnvironment............................................215 MartinFukacˇandAdrianPagan vii P1:BINAYAKUMARDASH November12,2010 19:1 C7035 C7035˙C000 viii Contents 10 ForecastingwithIntervalandHistogramData:Some FinancialApplications............................................247 JavierArroyo,GloriaGonza´lez-Rivera,andCarlosMate´ 11 PredictabilityofAssetReturnsandtheEfficient MarketHypothesis................................................281 M.HashemPesaran 12 AFactorAnalysisofBondRiskPremia...........................313 SydneyC.LudvigsonandSerenaNg 13 DynamicPanelDataModels......................................373 ChengHsiao 14 AUnifiedEstimationApproachforSpatialDynamicPanelData Models:Stability,SpatialCo-integration,andExplosiveRoots....397 Lung-feiLeeandJihaiYu 15 SpatialPanels.....................................................435 BadiH.Baltagi 16 NonparametricandSemiparametricPanelEconometric Models:EstimationandTesting...................................455 LiangjunSuandAmanUllah Index..................................................................499 P1:BINAYAKUMARDASH November12,2010 19:1 C7035 C7035˙C000 Preface Econometricsoriginatedasabranchoftheclassicaldisciplineofmathemat- ical statistics. At the same time it has its foundation in economics where it beganasasubjectofquantitativeeconomics.Whilethehistoryofthequanti- tativeanalysisofbothmicroeconomicandmacroeconomicbehaviorislong, theformalofthesub-disciplineofeconometricspersecamewiththeestab- lishment of the Econometric Society in 1932, at a time when many of the mostsignificantadvancesinmodernstatisticalinferenceweremadebyJerzy Neyman,EgonPearson,SirRonaldFisher,andtheircontemporaries.Allof this led to dramatic and swift developments in the theoretical foundations of econometrics, followed by commensurate changes that took place in the applicationofeconometricmethodsovertheensuingdecades.Fromtimeto time these developments have been documented in various ways, includ- ingvarious“handbooks.”Amongtheotherhandbooksthathavebeenpro- duced, The Handbook of Applied Economic Statistics (1998), edited by Aman Ullah and David. E. A. Giles, and The Handbook of Applied Econometrics and StatisticalInference(2002),editedbyAmanUllah,AlanT.K.Wan,andAnoop Chaturvedi(bothpublishedbyMarcelDekker),tookastheirgeneraltheme theover-archingimportanceoftheinterfacebetweenmoderneconometrics andmathematicalstatistics. However,thedatathatareencounteredineconomicsoftenhaveunusual propertiesandcharacteristics.Thesedatacanbeintheformofmicro(cross- section), macro (time-series), and panel data (time-series of cross-sections). While cross-section data are more prevalent in the applied areas of micro- economics, such as development and labor economics, time-series data are commoninfinanceandmacroeconomics.Paneldatahavebeenusedexten- sivelyinrecentyearsforpolicyanalysisinconnectionwithmicroeconomic, macroeconomicandfinancialissues.Associatedwitheachofthesetypesof dataarevariouschallengingproblemsrelatingtomodelspecification,estima- tion,andtesting.Theseinclude,forexample,issuesrelatingtosimultaneity andendogeneity,weakinstruments,averagetreatment,censoring,functional form, nonstationarity, volatility and correlations, cointegration, varying co- efficients, and spatial data correlations, among others. All these complex- ities have led to several developments in the econometrics methods and applications to deal with the special models arising. In fact many advances have taken place in financial econometrics using time series, in labor eco- nomicsusingcrosssection,andinpolicyevaluationsusingpaneldata.Inthe faceofallthesedevelopmentsintheeconomicsandfinancialeconometrics, themotivationbehindthisHandbookistotakestockofthesubjectmatterof empirical economics and finance, and where this research field is likely to head in the near future. Given this objective, various econometricians who ix P1:BINAYAKUMARDASH November12,2010 19:1 C7035 C7035˙C000 x Preface are acknowledged international experts in their particular fields were com- missionedtoguideusaboutthefast,recentgrowingresearchineconomics and finance. The contributions in this Handbook should prove to be useful forresearchers,teachers,andgraduatestudentsineconomics,finance,soci- ology,psychology,politicalscience,econometrics,statistics,engineering,and themedicalsciences. The Handbook contains sixteen chapters that can be divided broadly into thefollowingthreeparts: 1. Micro(Cross-Section)Models 2. MacroandFinancial(Time-Series)Models 3. PanelDataModels PartIoftheHandbookconsistsofchaptersdealingwiththestatisticalissues intheanalysisofeconometricmodelsanalysiswiththecross-sectionaldata oftenarisinginmicroeconomics.ThechapterbyCameronandMillerreviews methodstocontrolforregressionmodelerrorthatiscorrelatedwithingroups orclusters,butisuncorrelatedacrossgroupsorclusters.Theimportanceof thisstemsfromthefactthatfailuretocontrolforsuchclusteringcanleadto anunderstatementofstandarderrors,andhenceanoverstatementofstatisti- calsignificance,asemphasizedmostnotablyinempiricalstudiesbyMoulton andothers.Thesemayleadtomisleadingconclusionsinempiricalandpolicy work.CameronandMilleremphasizeOLSestimationwithstatisticalinfer- encebasedonminimalassumptionsregardingtheerrorcorrelationprocess, buttheyalsoreviewmoreefficientfeasibleGLSestimation,andtheadaptation tononlinearandinstrumentalvariablesestimators.TrivediandMunkinhave preparedachapterontheregressionanalysisofempiricaleconomicmodels wheretheoutcomevariableisintheformofnon-negativecountdata.Count regressions have been extensively used for analyzing event count data that are common in fertility analysis, health care utilization, accident modeling, insurance,andrecreationaldemandstudies,forexample.Severalspecialfea- turesofcountregressionmodelsareintimatelyconnectedtodiscretenessand nonlinearity,asinthecaseofbinaryoutcomemodelssuchasthelogitandpro- bitmodels.Thepresentsurveygoessignificantlybeyondtheprevioussuch surveys,anditconcentratesonnewerdevelopments,coveringboththeprob- abilitymodelsandthemethodsofestimatingtheparametersofthesemodels. It also discusses noteworthy applications or extensions of older topics. An- otherchapterisbyFaganandGenc¸aydealingwithtextualdataeconometrics. Mostoftheempiricalworkineconomicsandfinanceisundertakenusingcat- egoricalornumericaldata,althoughnearlyalloftheinformationavailableto decision-makersiscommunicatedinalinguisticformat,eitherthroughspo- kenorwrittenlanguage.Whilethequantitativetoolsforanalyzingnumerical andcategoricaldataareverywelldeveloped,toolsforthequantitativeanal- ysis of textual data are quite new and in an early stage of development. Of course,theproblemsinvolvedintheanalysisoftextualdataaremuchgreater than those associated with other forms of data. Recently, however, research has shown that even at a coarse level of sophistication, automated textual