THE RELATIONSHIP BETWEEN FINANCIAL LIBERALIZATION AND STOCK MARKET EFFICIENCY: A STUDY OF EMERGING MARKETS NAVAZ NAGHAVI FACULTY OF ECONOMICS AND ADMINISTRATION UNIVERSITY OF MALAYA KUALA LUMPUR 2014THE RELATIONSHIP BETWEEN FINANCIAL LIBERALIZATION AND STOCK MARKET EFFICIENCY: A STUDY OF EMERGING MARKETS NAVAZ NAGHAVI THESIS SUBMITTED IN FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY FACULTY OF ECONOMICS AND ADMINISTRATION UNIVERSITY OF MALAYA KUALA LUMPUR 2014UNIVERSITI MALAYA ORIGINAL LITERARY WORK DECLARATION NameofCandidate:Navaz Naghavi(I.C/PassportNo:L95235659)Registration/MatricNo:EHA100010NameofDegree:Doctor of Philosophy TitleofProjectPaper/ResearchReport/Dissertation/Thesis(thisWork):The relationship between financial liberalization and stock market efficiency: A study of emerging markets FieldofStudy:Capital MarketsIdosolemnlyandsincerelydeclarethat:1.Iamthesoleauthor/writerofthisWork;2.ThisWorkisoriginal;3.Anyuseofanyworkinwhichcopyrightexistswasdonebywayoffairdealingandforpermittedpurposesandanyexcerptorextractfrom,orreferencetoorreproductionofanycopyrightworkhasbeendisclosedexpresslyandsufficientlyandthetitleoftheWorkanditsauthorshiphavebeenacknowledgedinthisWork;4.IdonothaveanyactualknowledgenordoIoughtreasonablytoknowthatthemakingofthisworkconstitutesaninfringementofanycopyrightwork;5.IherebyassignallandeveryrightsinthecopyrighttothisWorktotheUniversityofMalaya(UM),whohenceforthshallbeownerofthecopyrightinthisWorkandthatanyreproductionoruseinanyformorbyanymeanswhatsoeverisprohibitedwithoutthewrittenconsentofUMhavingbeenfirsthadandobtained;6.IamfullyawarethatifinthecourseofmakingthisWorkIhaveinfringedanycopyrightwhetherintentionallyorotherwise,ImaybesubjecttolegalactionoranyotheractionasmaybedeterminedbyUM.CandidatesSignature DateSubscribedandsolemnlydeclaredbefore,WitnesssSignature DateName:Designation:iiABSTRACT The process of neoliberal globalization has been associated with successive financialcrisesduringthe1990s. Mexican andTurkish crisesof1994have culminatedwiththewidespread Asian crisis of 1997; the Russian crisis of 1998, and the possibility of animpending crisis in Brazil during the early months of 1999 have raised serious doubtsabout the success of uncontrolled movements of capital. Moreover, global financialmeltdown in 2008, which can be interpreted as the main challenge of neoliberalglobalization,emergedasthemostdebatableissueofthecentury.Someeconomistsandpolicymakershaveopinedthatcurrentfinancialcrisisheraldsthefailurenotonlyofaneconomicsystem,butalsooftheideologyoffreemarketandneoliberalism.On the other side, in contrast to classical pessimistic view of freedom, modernpsychologists assume that freedom has a positive influence on subjective wellbeing.Residentsofcountrieswithopeneconomiesareexperiencingthepositiveconsequencesofmoreeconomicandfinancialfreedom.In consideration of the aforementioned concerns, it is investigated whether the globalfinancialandeconomiccrisisisacrisisofneoliberalism.Moreover,thedivergingresultsofempiricalliteratureabouttheliberalizationeffectsisjustifiedbasedonthepre-requisiteeconomicconditions.Specifically,panelunitroottest,panelcointegration,panelGrangercausality, General Methods of Moment (GMM) modeling, as well as threshold panelregressions,arethemaineconometrictechniquesappliedtoexploretheaforementionedissues.iiiPrincipally,theseanalysescanbecategorizedintothreemajorparts.First,thisresearchexaminesthecausaldirectionbetweenfinancialliberalizationandemergingstockmarketefficiency in short- and long-term. Second, the effect of financial openness on stockmarket efficiency has been examined with respect to trade openness and quality ofinstitution as pre-requisite conditions for benefiting from financial liberalization. Oncethepresenceofqualityofinstitutionsandtradeopennessareconfirmedasessentialandimperativefactors,thethirdanalyticalsectionfocusesonmeasuringthecriticallevelofinstitutions above which an economy can enjoy the beneficial effects of financialliberalization.Similarly,itispositedthat,belowthethresholdlevel,thecountrymaybeindangerofexperiencingcrisis.Severalkeyfindingsareworthmentioninghere.Theempiricalevidenceontheeffectsoffinancialmarketopennessimpliesthelikelihoodofadeterioratingimpactonstockmarketefficiencyintheshortterm,astheriskandcostaspectofliberalizationinitiallyimpedestockmarketefficiency.However,inthelongterm,asthestockmarketparticipantshadtime to adjust to the external shocks, they would move to produce more disclosures.Moreover,thestudyfindingslendempiricalsupporttotheexistenceofasignificantlinkbetween financial openness and stock market efficiency in countries with highinstitutionalquality.Itisshownthatthesuccessandfailureoffinancialliberalizationareassumed to be dependent on country characteristics. This premise implies non-linearrelationship(U-shaped)betweenfinancialliberalizationandstockmarketefficiency.ThisU-shaped relationship reveals that, below a certain level of institutions, financialliberalization may lead the market to experience more stock autocorrelation andconsequentlystartmovingtowardscrisis.Ontheotherhand,oncethethresholdlevelisreached,financialliberalizationhastheabilitytoboostupstockmarketefficiency.ivABSTRAK Prosesglobalisasineoliberaltelahdikaitkandenganbeberapakrisiskewanganyangtelahberlakusejaktahun1990an.Contohnya,krisisdiMexicodanTurkeypadatahun1994yang disusuli dengan krisis di Asia pada 1997; krisis di Rusia pada 1998 dan krisis diBrazilpadaawaltahun1999telahmenimbulkanpersoalantentangkeupayaanpergerakanmodal yang tidak terkawal. Tambahan pula, krisis kewangan global pada 2008 telahditafsirkansebagaicabaranutamadalamglobalisasineoliberalyangseringdiperdebatkandalamkurunini.Sesetengahahli-ahliekonomidanpengubal-pengubaldasarberpendapatbahawa krisis kewangan bukan sahaja menunjukkan kegagalan dalam sistem ekonomitetapijugamenonjolkankegagalanideologipasaranbebasdanneoliberalisme.Sebalik daripada pandangan klasikal yang pesimistik itu, ahli-ahli psikologi modenmengandaikan bahawa kebebasan mempunyai kesan positif ke atas kesejahteraansubjektif (subjectivewellbeing). Tambahan pula, penduduk di negara-negara yangmengamalkansistemekonomiterbukamempunyaipengalaman yangbaikdalamaspekkebebasanekonomidanjugakewangan.Ekorandaripadapercangahaanpendapattersebut,tesisiniinginmengkajisamaadakrisisekonomidankewanganglobalmerupakankrisisneoliberalisme.Seperkaralagi,tesisinijuga ingin menerangkan penemuan kajian empirikal lepas yang bercanggah terhadapkesan liberalisasi itu adalah akibat daripada prasyarat keadaan ekonomi. Lebih khususlagi,ujianpanelpuncaunit,ujianpanelkointegrasi,ujianpanelsebab-penyebabGranger,kaedahgeneralisedmethod of moment (GMM)danregresi-regresipanel paras ambang(thresholdpanelregressions) adalah teknik utama ekonometrik yang digunakan untukmenerokaiisu-isuyangdinyatakandiatas.vSecaraumumnya,analisisinibolehdikategorikankepadatigabahagianutama.Bahagianpertama akan mengkaji hubungan sebab-penyebab jangka pendek dan panjang antaraliberalisasikewangandankecekapanpasaransahambaru.Bahagiankeduaakanmengkajikesan keterbukaan pasaran kewangan kepada kecekapan pasaran saham denganmengambilkira keterbukaan perdagangan dan kualiti institusi sebagai prasyarat yangdiperlukan untuk memperoleh manfaat daripada liberalisasi kewangan. Setelahmengenalpasti kepentingan kualiti institusi dan keterbukaan perdagangan dalamliberalisasi kewangan, bahagian ketiga tesis ini akan memberi tumpuan kepadapengukurantahapkritikalinstitusi-institusitersebutyangmembolehkansesebuahnegaraitu menikmati kesan-kesan positif daripada liberalisasi kewangan. Begitu juga, jikasesebuah negara berada dibawah paras ambang (thresholdlevel), krisis yang dialamiberkemungkinanmemudaratkannegara-negaratersebut.Beberapahasilkajianyangpentingakandinyatakandisini.Kajianinimendapatibahawakesan-kesanketerbukaanpasarankewanganbesarkemungkinanmenjejaskankecekapanpasaransahamterutamanyadalamjangkapendekkeranaaspekrisikodankosliberalisasiseringkali menghalang kecekapan pasaran saham. Akan tetapi, dalam jangka panjangpelabur-pelabur di pasaran saham mempunyai masa yang mencukupi untuk membuatpelarasan terhadap kejutan-kejutan luaran dan selanjutnya mampu menghasilkan lebihbanyak peluang. Di samping itu, hasil kajian ini juga membuktikan bahawa terdapathubungan yangsignifikanantaraketerbukaankewangandankecekapan pasaransahamdi negara-negara yang mempunyai institusi-institusi berkualiti tinggi. Tambahan pula,kajian ini juga menemui bahawa kejayaan dan kegagalan liberalisasi kewangan adalahbergantung kepada ciri-ciri sesebuah negara. Idea ini menunjukkan bahawa hubunganantara liberalisasi kewangan dan kecekapan pasaran saham adalah tidak linear (bentukviU).HubunganyangberbentukUinimenunjukkanbahawapadaparaskebawahinstitusi-institusiyangtertentu,liberalisasikewanganakanmenyebabkanpasaransahammenjadilebihbersifatautokorelasidanseterusnyamenujukearahkrisis.Sebaliknya,apabilaparasambangdicapai,liberalisasikewanganakanmempunyaikeupayaanuntukmeningkatkankecekapanpasaransaham.viiACKNOWLEDGMENTS Thisthesisrepresentsnotonlymyworkatthekeyboard,itisamilestoneinmyfirst31yearsofmylife.Thebestandworstmomentofmydoctoraljourneyhavebeensharedwith many people. It has been a great privilege to spend four years in the Faculty ofEconomic and Administration at University of Malaya and its members will alwaysremaindeartome.My first debt of gratitude must go to my supervisor, Dr. Lau Wee Yeap. He patientlyprovided the vision, motives and advice to proceed throughout the doctoral program. Iremember all his positive and encouraging words in every meeting and email. He hassupportedmenotonlyacademicallyoveralmostfouryears,butalsoemotionallytroughtheroughroadtofinishthisthesis.Icannotexpressmyappreciationintowordsforthemoralsupportandfreedomhegavemetomoveon.Second, I would also like to thank academic and administrative staff of the Faculty ofEconomicandAdministrative,UniversityofMalaya.Specifically,IamverygratefultoProfessorDr.GohKimLeng,ProfessorDr.RajahRasiah,AssociateProfessorDr.VGRChandranGovindaraju,AssociateProfessorDr.YapSuFeiandDr.CheongKeeCheok,Mr. Suhaidi Kamarudin and Madam Azura Aziz for helping me in so many differentways. My sincerest appreciation to all them because of wonderful kindness andunderstandings.ThegenuinefriendsIgottoknowinMalaysiawereanothersourceofsupport.Mysinceregratitude is extended to Dr. Seeku Jaabi, who used to call me his closest friend inMalaysia.Iwouldalsoliketogiveaheartfelt,specialthankstoMs.AyeshaShoukat,Dr.Tang Chor Foon, Dr. Cheah Yong Kang, Dr. Sarala Aikanathan, Mr. Hamid Ghorbaniand Mr. Mehdi Memar without whom I could not pave this arduous journey. I am soviiipleasedthatinmanycases,myfriendshipswiththemhavebeenextendedwellbeyondPhDlife.Ihavebeenblessedwithaverylovingandsupportivefamily.Myfather,JalalNaghavi,hasalwaysstressedtheimportanceofeducation.Hehasbeenmyfinancialsponsoroverthesefouryearsandhisfinancialsupportshasopenedanewstageinmylife.Mymother,Khadijeh Irani Tehrani, has been a source of constant and unconditional love. Herexhortingwordseverymorninghavebeenactingasmypowersourcetoendureonthisroad.MySister,Nahal,whoseenergyisexemplary,hasbeencontributingimmeasurablyinthisthesis.Last,butcertainlynottheleast,Imustacknowledgetremendousanddeepthankstomyhusband, Seyed Hossein Mohsenian, whom I married in Malaysia just a few monthsbeforestartingmyPhD.Hewentthrougheveryexcruciatingstepandmoodchangeswithme.Hehastakencareofwhateverneededwithoutcomplaining,justsoIcouldfocusoncompletingmydissertation.Hosseinhasbeencentraltomycompletionofthisstudyashehasgivenmeconfidenceandmotivatedmeinsomanyways.Therearenowordsthatcanexpressmygratitudeandappreciationforallyouvedoneandbeenforme.ixTABLE OF CONTENTS ABSTRACT ..........................................................................................................ii ABSTRAK .........................................................................................................iv ACKNOWLEDGMENTS............................................................................................vii LIST OF FIGURES.....................................................................................................xiii LIST OF TABLES.......................................................................................................xiv CHAPTER 1: INTRODUCTION 1.1Introduction...........................................................................................................1 1.2Statementoftheproblem......................................................................................6 1.2.1Paradigmsinrespondtoseriesofrecentcrises.......................................8 1.3Objectiveofthestudy.........................................................................................10 1.4Researchquestions..............................................................................................11 1.5Significanceofthestudy.....................................................................................11 1.6Scopeofthestudy...............................................................................................13 1.7Organizationofthestudy....................................................................................16 CHAPTER 2: LITERATURE REVIEW 2.1Introduction.........................................................................................................18 2.2Definitionofstockmarketefficiency..................................................................18 2.2.1Serialcorrelationandmarketinefficiency............................................21 2.2.2EvolutionofEMH.................................................................................24 2.2.3Adaptivemarkethypothesis..................................................................26 2.2.4Applicationofadaptivemarkethypothesis...........................................29 2.3Definitionofliberalism.......................................................................................30 2.4Definitionofneoliberalism.................................................................................32 2.4.1Neoliberalismandcrises.......................................................................33 2.4.2Twoschoolofthoughtonglobalcrisis.................................................36 2.5Basictheoreticalframework................................................................................37 2.6Evolutiononthenexusbetweenfinancialliberalizationandefficiency.............40 2.6.1Newproposedtheoreticalmodel...........................................................44 2.7Institutions...........................................................................................................46 2.7.1Governanceindicators...........................................................................51 x2.8Datadescription...................................................................................................53 2.9Identificationofresearchgap..............................................................................53 CHAPTER 3: METHODOLOGY 3.1Introduction.........................................................................................................59 3.2Efficiencyandrandomwalk...............................................................................59 3.3Measurement.......................................................................................................60 3.3.1Generalconceptofmeasuringstockmarketefficiency........................60 3.3.2Efficientmarkethypothesis(EMH)......................................................61 3.3.3Adaptivemarkethypothesis..................................................................69 3.3.4Financialliberalizationdefinitionandmeasurement............................72 3.4Conceptualframework........................................................................................76 3.5Theoreticalbackground.......................................................................................79 3.5.1TheoreticalmodelofBasu&Morey....................................................79 3.5.2BasuandMoreylinkofopennessandefficiency.................................82 3.6Econometricmethodologyandestimationtechniques........................................83 3.6.1Unitroottest..........................................................................................83 3.6.2Panelcointegrationtests........................................................................89 3.6.3ErrorCorrectionModel.........................................................................92 3.6.4Testofcrosssectionaldependence.......................................................99 3.6.5SystemGMMandfirst-differenceGMM...........................................101 3.6.6Thresholdpaneldata...........................................................................105 3.7Dataandscopeofthestudy...............................................................................109 xiCHAPTER 4: CAUSALITY RELATIONSHIP BETWEEN FINANCIAL LIBERALIZATION AND STOCK MARKET EFFICIENCY 4.1Introduction.......................................................................................................112 4.2Contradictoryresults.........................................................................................112 4.3Modelspecificationanddata.............................................................................115 4.4Panelunitroottest.............................................................................................121 4.5Panelleveleffect...............................................................................................125 4.6Panelcointegration............................................................................................128 4.7Long-termandshort-termpanelGrangercausalityresults...............................129 CHAPTER 5: LONG TERM RELATIONSHIP 5.1Introduction.......................................................................................................141 5.2Dataandmodelspecification............................................................................142 5.2.1Variablescorrelations..........................................................................144 5.3Long-termestimation........................................................................................148 5.3.1High-governancecountries(Individualgovernanceindicators).........148 5.3.2Low-governancecountries(Individualgovernanceindicators)..........154 5.4Factoranalysis...................................................................................................157 5.4.1High-governancecountries(Re-shapingthegovernanceindicators).162 5.4.2Low-governancecountries(Re-shapingtheinstitutiongovernance)..165 5.5Conclusion.........................................................................................................168 CHAPTER 6: THRESHOLD PANEL 6.1Introduction.......................................................................................................171 6.2Econometricframeworkandmodelspecification.............................................172 6.3Thresholdlevelofinstitutionalvariables..........................................................174 6.4Thresholdlevelforeachdimension........................................................................179 6.5Conclusion.........................................................................................................186 CHAPTER 7: CONCLUSION 7.1Generalconclusionrelatedtotheobjectives.....................................................187 7.2Theoreticalconclusion......................................................................................192 7.3Contributionofthestudy...................................................................................194 xiiREFERENCES ......................................................................................................197 APPENDICES AppendixA:Figuresoftime-varyingefficiency(Hurstexponent)..............................212 xiiiLIST OF FIGURES Figure3.1: Conceptualframework.....................................................................77 Figure3.2: Econometricframework...................................................................77 Figure3.3: Econometricframeworkforgrangercausality.................................78 Figure3.4: Econometricframeworkforlong-termrelationshipandinstitutionoptimallevel.....................................................................................78 xivLIST OF TABLES Table3.1: Summaryofallliberalizationmeasures...........................................76 Table4.1: Summarystatisticsofstockreturninformationalefficiency(EMHapproach)fromJanuary1996toDecember2011derivedfromRpackage...........................................................................................119 Table4.2: Summarystatisticsofstockreturninformationalefficiency(AMHapproach)fromJanuary1996toDecember2011derivedfromMatlabpackage...............................................................................120 Table4.3: Panelunitroottest-LLCandIPStest.............................................122 Table4.4: CDteststatisticofADF( )regression.......................................123 Table4.5: PesaransCIPSpanelunitroottest................................................125 Table4.6: Estimationresultsforthe1996-2011period(Dependentvariable:Autcor)............................................................................................127 Table4.7: Estimationresultsforthe1996-2011period(Dependent variable: HE).................................................................................................127 Table4.8: Panelcointegrationtestresults(dependentvariable:Autcor)........128 Table4.9: Panelcointegrationtestresults(dependentvariable:HE)..............128 Table4.10: PanelGrangerCausality(EMHapproach).....................................134 Table4.11: PanelGrangercausality(AMHapproach).....................................135 Table4.12: Panelerrorcorrectionestimatesforthe1996-2011period(EMHapproach)........................................................................................138 Table4.13: Panelerrorcorrectionestimatesforthe1996-2011period(AMHapproach)........................................................................................139 xvTable5.1: CorrelationsbetweenCorrelationbetweenstockmarketefficiencyproxies,financialliberalization,tradeopennessandeachofgovernanceindicatorsfrom1996to2011......................................146 Table5.2: Correlationsbetweengovernanceindicatorsfrom1996to2011...147 Table5.3: Descriptivestatisticsfrom1996to2011........................................148 Table5.4: High-Gcountries,EMHapproachofefficiency-Individualgovernanceindicators(1996-2011)................................................150 Table5.5: High-Gcountries,AMHapproachofefficiency-Individualgovernanceindicators(1996-2011)................................................151 Table5.6: Low-Gcountries,EMHapproachofefficiency-Individualgovernanceindicators(1996-2011)................................................155 Table5.7: Low-Gcountries,AMHapproachofefficiency-Individualgovernanceindicators(1996-2011)................................................157 Table5.8: Factoranalysisofgovernanceindicators.......................................161 Table5.9: HighG-countries,EMHapproach,Institutionsaggregation(1996-2011)...............................................................................................164 Table5.10: High-Gcountries,AMHapproach,Institutionsaggregation(1996-2011).............................................................................................1655 Table5.11: Low-Gcountries,EMHapproach,Institutionsaggregation(1996-2011)...............................................................................................167 Table5.12: Low-Gcountries,AMHapproach,Institutionsaggregation(1996-2011)...............................................................................................168 Table6.1: TheresultsforthresholdvalueofVandaandEFF(EMHapproach)thresholdvariablelessthanthreshold............................................174 xviTable6.2: TheresultsforthresholdvalueofVandaandEFF(AMHapproach)thresholdvariablelessthanthreshold............................................175 Table6.3: TheresultsforthresholdvalueofVandaandEFF(EMHapproach)thresholdvariableabovethanthreshold.........................................176 Table6.4: TheresultsforthresholdvalueofVandaandEFF(AMHapproach)........................................................................................177 Table6.5: TheresultsforthresholdvalueofG1,G2andG3.........................180 Table6.6: TheresultsforthresholdlevelofG4,G5andG6..........................181 Table6.7: Thresholdestimation:Abovesinglethresholdlevel......................183 Table6.8: Thresholdestimation:Belowsinglethresholdlevel......................185 1CHAPTER 1: INTRODUCTION 1.1Introduction The term financial liberalization originated three decades ago, when several OECDcountriesandsomedevelopingnationsstartedmovingfromfinancialrepressiontowardsfinancialliberalizationbyrelaxingcontrolsontheirnationalcapitalaccounts.Financialrepressionischaracterizedbyafixedexchangerateregime,highreserverequirements,interestrateceilings,andcontroloncapitalflowsallofwhichareintroducedinanefforttomaintainfinancialstability(Abbott,AndersenandTarp,2010).A financially repressed system is also described as one in which the governmentdetermineswhogetsandgivescreditandatwhatprice.Sucheconomiesdonotallowforefficientcapitalallocation,inwhichhighercapitalflowsaredirectedtowardscountrieswithhigherinterestrateregimes.Industrializednationsreliedoncapitalaccountcontrolsforsignificantperiodsoftheireconomicdevelopment,andrelaxationsofcapitalaccountrestrictions are perceived as an integral aspect of economic development. As a result,many of these countries experienced low growth, macroeconomic instability, and highcoststomaintainregulation.Prior to the 1980s, governments in developing countries faced increasing difficulty inraising capital for development projects due to insufficient savings and a populationexpansion.Moreover,duetothepersistentdebtcrisesinthesecountriesandtherecentglobalfinancialcrisis,whichwasmostseverelyfeltinindustrializedcountries,theflowofpublicandprivatecapitaltodevelopingcountrieshaddeclined(Kanu,2011).2Therefore,economistsadvocatedfortheremovalofcapitalcontrols,asastabilizingfactorofthedevelopmentprocess,aimedatimprovingefficiencyandexpectedtoreturntheseeconomies from distorted factor prices to production frontiers. According to Bagehot(1999) possession of large quantities of borrowable funds is at the root of a countryseconomicprogress.Asthisconditionwasnotmetduringthe1980s,theworldeconomywasundergoingstartlingchange,wherebyalmosteverycountrystartedmovingtowardfreer markets and extensions of the private enterprise capitalist system. Most of thedeveloped nations have since privatized state-owned industries as de-regulated privateindustry,andhavefreedtheinternationaltradeandcapitalmovement,andseemintentonfurther liberalization. Developing countries also initiated reforms to liberalize theirfinancial markets in the late 1980s, to access the abundant resources available ininternationalfinancialmarkets.According to the definition adopted in the pertinent literature, liberalization can becharacterized as the process of allowing the market to determine credit allocation.Financialliberalization,firstmentionedbyMcKinnon(1973)andShaw(1973)advocatesreduceddirectinterventionofthestate.Inotherwords,itisachievedthroughamarket-oriented economy, whereby price mechanisms are used to allocate resources. Thereasoningbehindfinancialliberalizationisdrivenbytheneedtoreducecostsrelatingtomaintainingfixedexchangerateandpromotingproperallocationofsavingstoproductiveinvestments,thusdecreasingtheeffectofexternalitiescausedbytherepressionregime.Asraisingfinancialresourcesandaccumulatingcapitalaredrivingtheeconomicgrowth,theseweretheforemostgoalsofthecountriesaimingtoachievefinancialliberalization.To summarize, developing an efficient financial system is the essence of financialliberalization.3Theavailableempiricalevidenceontheeffectsofcapitalliberalizationpolicyismixed.Whilesomesourcessuggestthattheinflowofinternationalcapitalstimulatesinvestmentandleadstoeconomicgrowth,someauthorspositthatcapitalflightandcashoutflowmaycause instability and in some cases even financial crisis (Huang and Huang, 2008).Financialliberalizationshavebecomeassociatedwithcapitalflowreversals,whereinitialcapitalinflowsattheonsetaresubsequentlyoffsetbycapitaloutflowsresultinginhigherlevelsofaccumulatedindebtedness.Thissuggeststhatfinancialcontrol removalmighthaveafragileinfluenceonstockmarket.Whileitcanbringlowcostcapitalforfinancingnewinvestmentopportunities,itmayputtheeconomyatriskofsinkinginfinancialcrisis.Agrowingbodyofliteraturedefinesefficiencygainsfromcapitalaccountliberalizationin developed countries in terms of economic growth, financial development, portfoliodiversification,andreductionofthecostofcapital.Thebenefitsofcapitalmobilityareclear, as it results in a more efficient allocation of resources, including an additionalsourceoffundingfordomesticinvestmentprojectsinpoorercountrieswithlowsavings,possibilitiesforriskdiversification,andthepromotionoffinancialdevelopment.However, there is empirical support for a converse effect, whereby emerging marketeconomies experienced increased macroeconomic volatility and unbalanced currentaccount due to increased capital mobility. According to the opposing view ofglobalization,theopeningofdomesticcapitalmarketsofemergingeconomiestoforeigninvestorsinflictsconsiderablecostandgeneratesverylimitedbenefitstothesenations.Accordingtothisview,sinceemergingmarketslackmodernfinancialinstitutions,theyareparticularlyvulnerabletothevolatilityofglobalfinancialmarkets.Thisvulnerabilitywill be higher in countries with more open financial markets. Similarly, many global-skepticshavearguedthatthereisnoevidencesupportingtheviewthatahigherdegreeof4capitalmobilityhasapositiveimpactongrowthintheemergingeconomies(Edwards,2001).Therefore,someemergingcountriesreversethetrendtowardtheliberalizationandimposecontrolsoncapitalaccounts.Inthisvein,itisalsoclaimedthateconomictheoryinmanycasesdiffersfromeconomictruth,especiallyindevelopingcountries. Inthisregard,Corley etal.(1996)elaboratedthat, after the fall of the Soviet Union in 1989, Russia pushed towards a free marketapproach to expedite economic growth. Surprisingly, while many economists expectedtheRussianeconomytomakeasignificantprogress,itdeclinedoveronlysevenyears.According to Corley et al. (1996), the missing factor in the Russian endeavor was theabsenceoftheruleoflaw,whichleadstoeffectivefunctioningofeconomicinstitutions.Theruleoflaw,asreflectedbythelegalsystem,holdsalltheinstitutionsandresidentsof a particular country accountable under the law, the governments of the developingcountriesbeingnoexception(Corleyetal.,1996).Thequalityofcountrygovernanceisknowntoaffecttheoperationoffinancialandcapitalmarketsthroughitsinfluencesontheavailabilityofexternalfinancing,costoffunding,marketvaluations,andqualityofinvestments(Low,KewandTee,2011).Forthesereasons,theresearchinthisfieldhasmovedtowardconditioningtheeffectofliberalization on the quality of institutions (Honig, 2008). A number of interactionvariableshavebeenusedtomeasuretheoptimalcircumstancesforachievingimprovedefficiencythroughfinancialliberalization.Althoughcapitalmarketdevelopmenthasbeenadoptedbymanydevelopingcountriesasastrategyforachievingeconomicgrowth,theestablishmentofadequateinstitutionalfactors,suchaslegalsystem,ruleoflaw,propertyrights, administrative policy, and investors protection, might be even more critical tomaking these markets more efficient. In the discussion on why some nations are5prosperouswhileothersarepoor,Reedetal.(2006)identifiedtheabsenceofadequateinstitutional factors as the main impediment to viable capital markets and economicgrowth.Anumberofstudieshavebeenconducted,wherebytheauthorsexaminedtheeffectsofstockmarketliberalizationoneconomicfactors,especiallyinemergingeconomies.Mostof these researchers focused on changes in return behavior, volatility, and increase ineconomicgrowth,whileveryfewattemptedtoanalyzetheinfluenceofliberalizationonstock market efficiency. Recognition that an efficient stock market can provide usefulinputtomarket regulatorshaspromptednumerousauthorstotaketheirinvestigation astepfurtherbyconsideringtheimpactofsomepostulatedfactorsonthedegreeofmarketefficiency.While most of the empirical studies were carried out under the rubric of the EfficientMarketHypothesis(EMH),thereisevidentpaucityoftheoreticalworksontheeffectoffinancial liberalization on stock market efficiency. Market efficiency has beenemphasizedbecauseitcanleadtotheimprovementofeconomicperformance,andthuseconomicgrowth.Theefficientmarkethypothesisinfinancesuggeststhatequitypricesare reflected faster in new information. In addition, stocks and equities will be moreefficientlypricedwhentheequitymarketisliberalizedandmoreopentodomesticandforeignerinvestors(KawakatsuandMorey,1999).Inthecurrentresearch,therelationshipbetweenfinancialliberalizationandstockmarketefficiencyhasbeeninvestigatedwithregardtothethresholdeffectsofinstitutionsandthenecessityoftradeliberalizationasapreconditionforfinancialliberalization.61.2Statement of the problem Within the context of the recent financial crisis, it is increasingly questioned whetherstock market efficiency is improved through liberalization. Although numerousresearchershavestudiedtheempiricaleffectsoffinancialliberalizationonstockmarketefficiency,aconsistentconclusionremainselusive.Ononehand,theprocessofneoliberalglobalizationhasbeenassociatedwithsuccessivefinancialcrisesduringthe1990sMexicanandTurkishcrisesof1994culminatingwiththewidespreadAsiancrisisof1997,theRussiancrisisof1998,andthepossibilityofanimpendingcrisisinBrazilduringtheearlymonthsof1999raisingseriousdoubtsaboutsuccessofuncontrolledmovementsofcapitalinshortterm.Ontheotherhand,residentsof countries with open economies are experiencing the positive consequences of moreeconomicandfinancialfreedom.Apartfromthepossiblepositiveeffectofliberalizationoneconomicgrowth,whichhasbeenextensivelydiscussedinthepertinentliterature,incontrasttoclassicalpessimisticviewoffreedom,modernpsychologistsassumethatfreedomhasapositiveinfluenceonsubjective wellbeing (Gehring, 2013). In free countries, people not only experienceprivatepropertyrights,butalsoenjoywidercivilandpoliticalliberties(Kasper,2004).It is also evident that free countries facilitate more competition. Kasper and Analysis(2004)suggestedthatcompetitivecapitalismcultivatesacan-dooptimismamongpeople.Ascompetitionproducesmorewinnersthanlosers,lossescanbeovercomebyarenewedeffortthatemergesfromcompetition.Moreover,widespreadcorruptionismoreprevalentin countries with poor economic freedom than in open economies. Empirical evidenceindicatesthat,whentheeconomyfostersinternationalcompetition,thecostofcorruption7increases, making it less likely to take place. Consequently, corruption declines, ascountriesopenupeconomically.Despitetheincreasedinterestandparticipationofemergingmarketsintheliberalizationphenomenon,thusfar,onlylimitedworkexaminingtheirefficiencyhasbeenconducted.In addition, skepticism regarding their ability to value investment opportunitiesaccurately is evident. Hence, extant literature reveals conflicting views of thisrelationship, even after conditioning for the liberalization. Liberalization literature hasevolvedsignificantlysincethetermwasfirstintroduced;however,theempiricalliteratureontheeffectofliberalizationisstillmixed.In addition to the aforementioned contradictions, global financial meltdown in 2008,whichcanbeinterpretedasthemainchallengeofneoliberalglobalization,emergedasthe most debated issue of the century. In the wake of the fall of Lehman Brothers onSeptember 15th, 2008 and the subsequent near-total collapse of the global financialsystem,manypredictedtheendoftheworldofliberalcapitalism,oratleastannouncedthedeathofneoliberalideology.The Economist (2008) didwarnatthetimethateconomicliberty was under attack and capitalism was at bay. Around the world, economists andpolicymakers have opined that excessive reliance on unfettered markets was the rootcause of the current worldwide financial crisis. Free financial markets have collapsedacross the world, with far-reaching consequences for the world economy as a whole.Sincethelate2008,emergingmarketshadbeenmostlyhitbythefalloutofthefinancialmeltdown and experienced common symptoms, such as partly dramatic stock marketvolatility, currency depreciation, capital flight, and sharp declines in foreign directinvestment.8Now, the main problem of the era is to investigate whether the global financial andeconomiccrisisisacrisisofneoliberalism.Thecurrentfinancialcrisisheraldsthefailurenot only of an economic system, but also of an ideologythat of free market andneoliberalism.However,itwouldbeprematuretodeclaretheideologyofneoliberalismdeadandunderestimateitsremnantpower(Aalbers,2013).Thus, this study firstly seeks to justify the diverging results of empirical test about theeffectsofliberalizationandinvestigatewhichstrandofliteraturerepresentsthepatternthat can be observed in the real world. Investigating the veracity of each strand alsoenablesmeetingthestudyobjectives.Secondly,thestudywillaimtoestablishwhetherthespreadingoftheglobalfinancialturbulencetothedevelopingworldisasymptomoftheneoliberalismideologyfailure,orisrelatedtoneoliberalisminpractice.1.2.1Paradigms in respond to series of recent crises Inresponsetotheseriesofcrisesnotedabove,twogroupsofparadigmshaveemerged:1.Scholarswhoaresuspiciousabouttherelevanceofneoliberalismideology.Theybelievethatcurrentcrisismayunderminethefreemarketideologyandcanevenbeasymptomfordemiseofneoliberalideology.Advocatesofthisviewclaimthattherecentcrisisnotonlyspelledouttheendofneoliberalism,butalsoofferedprospectsforamoreequitable world (Overbeek and van Apeldoorn, 2012). They further posit that new-Keynesianismorpostneoliberalismisthesolution.Thisistobeexpected,giventhatthecurrentworldwidecrisishaspromptedresurgenceinKeynesianthoughts.9The standard reading is that Keynesian economics advocates government interventionand demand-side management of the economy to get as close to full employment aspossible.InKeynesianthinking,governmentdeficitspendingandfiscalstimulusareneededatthetimeofadownturn,asfreemarketsdonotautomaticallyleadtooptimaloutcomes,butmay rather result in a spiral of downward developments. Consequently, free financialmarketshavecollapsedacrosstheworld.2.Scholarsinthismindsetbelievethatcurrentcrisisreferstoneoliberalpractices,ratherthanneoliberalideology.Underthisparadigm,theresponsetothecrisisispossiblethroughgreaterorintensifiedneoliberalism. Thus, the challenge to neoliberal ideology was quickly turned intoneoliberal solutions, as the scholars in this group pointed to the distinction betweenneoliberal ideology and neoliberal practice. Thus, they claimed that, while neoliberalpractice can be declared dead, neoliberal ideology was very much alive. Thus, even ifmacroeconomicKeynesianismisassumedtobebackforgood(ithasneverbeenentirelyabsent),thisdoesnotimplythattheneoliberaleraisover.Theauthorssubscribingtothisschoolofthoughtdiscussedbroadlythatneoliberalismnotonlyremainsdominant,butalsoseemstocontinuouslycomeupwithnewideasonhowtosaveandrevampthesystem.Aspointedout,theyclaimthattheneoliberalspiritisverymuchalive;ithasdifferentformsandismoreflexiblethanmostofuswouldliketothink.Itissometimesarguedthatdiscussionsofperceivedneoliberalismarefalse,sincetherearenocompletelyneoliberalsystems.Neoliberalismwasneverabouttotalwithdrawalofthe state, but rather about its qualitative restructuring. In fact, corporate welfare is a10centraltenetofactualneoliberalism.AccordingtoAalbers(2012).neoliberalismpracticehideswhatrealneoliberalismwantsanddoes.According to the prevailing interpretation that has been expressed, for instance, in theG20meetings,thecrisiswascausedbyalackofadequategovernanceandregulationoffinance,notbecauseofanyinherenttendenciesoffinancialmarkets,orcapitalismmoregenerally. From this point of view, once the regulatory lacks and biases have beencorrected, and the economic situation otherwise normalized, the world is expected toreturntheneoliberalbusinessasusual.Thus,new-Keynesianismorpost-neoliberalismisnotasolution,butratherintensifiedneoliberalism.1.3Objective of the study The first objective of the study is to investigate the directional relationshipbetween the efficiency of emerging stock market and financial liberalization inthe short and long term. In another words, the aim is to investigate whetherliberalization-led-to-efficiencyhypothesiscanbeproveninshortandlongterm,basedonempiricaldata.Thesecondobjectiveistoinvestigatewhetheralegalframeworkandsufficientinstitutions,aswellastradeopenness,iscrucialforacountrytoreapthebenefitsoffinancialliberalizationinemergingmarkets.Thethirdobjectiveisderivedfromabove,andis:To acquire the optimum level of institutional development, which is crucial tobenefittedfromfinancialliberalization,asitcouldhelpfinancingpolicymakersintakingpreventiveactiontoavoidfinancialcrisisduetofinancialliberalization.111.4Research questions What is the causality relationship between financial liberalization and stockmarketefficiency?Inotherwords,doesfinancialliberalizationcausestockmarketefficiencytoadheremorestronglytointernationalnormsofcorporategovernance,or is an efficient stock market more willing to receive abundant money at lowpriceandpushtheeconomytoopenup?Doesfinancialliberalizationitselfleadtothestockmarketefficiency,ordoesitneed trade openness and institutional development as auxiliary preconditions tobeeffectiveintheeconomy?Whatistheoptimallevelofinstitutionaldevelopmentforemergingmarketstobenefitfromfinancialliberalization?1.5Significance of the studyIninvestigatingtheeffectoffinancialliberalizationonstockmarketefficiency,oneimportantquestionthatneedstobeaddressediswhyinformationalefficiencyisimportantwhenacountryproceedstoopenup.Theimportanceoftransparencyofeconomicactivityhasbeenincreasinglyrecognizedineconomicresearchsincetheonsetoftherecentfinancialcrisis.Theeffectoftransparencyisconsideredatboththemicrolevelfirmsbehaviorandatthemacrolevel,i.e.,ontheagents response to unobserved monetary or fiscal policies (Mehrez and Kaufmann,2000).Atthemacrolevel,whichisthefocusofthisresearch,recentattentionhasbeengiventotherelationshipbetweenthebehaviorofinternationalcommonlendersandpoor12transparency. Lack of information and uncertainty are inherent features of finance(VishwanathandKaufmann,2001).Poor transparency may lead to informational overshooting in the stock market.Moreover,whencombinedwithfinancialliberalization,poortransparencyincreasestheprobabilityofacrisis.However,thisdoesnotimplythatcountriesshouldnotliberalizetheir financial system, or that financial liberalization always results in a crisis. It onlyimplies that countries that liberalize their financial sector should make every effort toprovideapreconditiontoincreasetransparency(MehrezandKaufmann,2000).AlthoughinhisempiricalworkCaprio(1999)doesnotproposethatthelackoftransparencycausesafinancialcrisis,hedoessuggestthataitmayexacerbateacrisis(Caprio,1998).Furthermore, many experts on development economies and finance, including Levine(1997),Baumol(1965)andRousseauandSylla(2003)demonstratestrongevidenceofapositiverelationshipbetweenstockmarketsandeconomicgrowth.Thereasonbehindthedrive to establish and augment the stock market in developing countries is the need tospeeduptheeconomicgrowthbyprovidingastimulustodomesticsavingandfacilitatequality and quantity of investment. Stock markets can accelerate economic growth bymaking it possible for growing companies to raise capital at low cost. Thus, thedevelopingcountriesthathave embarkeduponthedevelopmentofstock marketshopethat these markets would play an important role in supporting social change througheconomicgrowth,astheycouldfacilitatetheexchangeofgoodsandservices,mobilizedomestic and international resources, diversify risk, and improve efficiency in theallocationoffactorsofproduction,therebyraisingthestandardofliving(Kanu,2011).131.6Scope of the study The designation emerging market is associated with the nomenclature adopted byWorldBank,wherebyacountryisdeemedemergingifitspercapitaGDPfallsbelowa certain level, which changes over time. Emerging Global Advisors uses criteriaestablished by the International Monetary Fund (IMF) which states that an emergingmarketisdefinedbyaGDP-per-capitaratiothatrangesbetween$2,000and$12,000.Ofcourse, the basic idea behind the term is that these countries emerge from lessdevelopedstatusandjointhegroupofdevelopedcountries.Emergingmarketsarethusused to describe the nations with social or business activities in the process of rapidgrowthandindustrialization.However,rankingtheworldseconomiesbypercapitagrossdomesticproductwould suggestthattheUnitedArabEmirates, forexample,isamongtheworldsmostdevelopedeconomies,butitisanemergingmarketnonethelessbecauseof its market structure. Intuitively, managers know that operating a business in anemerging market is different from doing so in a developed economy. It is tempting tochalk up these differences simply to country context. Indeed, market structures are theproductsofidiosyncratichistorical,political,legal,economicandculturalforceswithinanycountry.The economies of China and India are currently considered the largest. Similarly,emergingmarketsarethosedevelopingcountriesthatshowsignsofadvancementintheirfinancialstructuresbanks,stockmarkets, andregulatory bodiesandhavereachedacertainlevelofmaturityintermsofdepth,breadth,andliquidityinthefinancialstructureandeconomyasawhole. Thebestandmostdefinitivelistsofemergingmarketsarecompiledbyinvestmentbanks,andincludeMSCIandFTSEindex,orthelistbyIFC(InternationalFinanceCorporation,14partoftheWorldBankGroup).However,inthiscontext,thetermdevelopingcountriesrefers to entirely different groups of countries1. Developing countries are struggling incomparison and still need help from trade partners around the world. The fundamentaldifferencebetweentheemerginganddevelopingnationsisthattheformeraregrowingrapidlyandbecomingmoreimportantontheworldeconomicstage.The literature review suggests that most of the pertinent studies have been conductedusingdataondevelopingcountries,andincludethosebyVelenchik(2001);White(2001);Kose et al. (2009); Orok-Duke, Akpan Ekott and Edu Enya (2009); Kose, Prasad andTaylor(2011);tonameafew.Kimetal.(2012)recentlyattemptedtochangethistrendbyconsideringtheeffectsoftradeandfinancialopennessoninformationalefficiencyinemerging markets. In line with this initiative, the present study provides a relativelydetailedinvestigationoftheliberalization-efficiencyrelationshipinemergingmarkets.Moreover,therearesomeuniquespecificationforemergingmarketswhichdifferentiateitfromdevelopingmarketsandmakesitinterestingtostudy.Emergingmarketscarryamuchhigherriskbecausetheirstockscanbequitevolatile.Anythingfrominflationarypressurestorisinginterestratestosignsofaglobaleconomiccool-downcouldsendthemtumbling. Emerging markets investing carries other unique risks, such as politicalupheaval,regulatorychanges,andcurrencyfluctuations.While emerging markets (and thus emerging markets funds) carry higher risk than theaverageinvestment,thepotentialforrapideconomicgrowthinemergingcountriesmeansahigherreturnpotential.MatureeconomieslikeEnglandandtheUnitesStatesareoftenexpectedtogrow around3%annually, whileemergingeconomies withampleroomto1www.emergingeconomyreport.com[accessedon30thDecember2011]15grow have the potential to expand much faster. Going forward, this growth shouldtranslateintosuperiorcorporateprofitabilityandimpressivegainsforinvestors.2ThepresentworkadoptstheFTSEcategorizationofemergingmarkets,accordingtothethreelevelsAdvancedEmerging,SecondEmerging,andFrontierEmergingmarketswhichinclude10,12,and26countries,respectively.Asthestockmarketinmostofthesecountries is newly established, the stock price data is only available for recent years,whichreducesthescopeofthecurrentinvestigationtoasamplecomprising27emergingmarkets.Furthermore,inapaneldataset,whichhasthetimeseriescomponentinitself,a longer dataset generates more accurate results. Nevertheless, one of the principalvariablesofthecurrentresearch,namelytheWorldGovernanceIndicatorbyKaufmannand Kraay (2008), has been produced since 1996. This is considered as one of thelimitationsofthestudy,asitrestrictstheinitialtimedimension.Thedatausedinthisstudyincludesactualvaluesofdailyindicesoftheaforementioned27emergingstockmarkets.Theclosingpricesforthemajorstockindexineachmarketwere collected from Datastream. Due to the availability of all sample countries, thesample period spans from January 1st, 1996 to December 30th, 2011. The countriesincludedintheanalysisareCzechRepublic,Hungary,Malaysia,Mexico,SouthAfrica,Thailand, Turkey, Chile, China, Colombia, Egypt, India, Indonesia, Pakistan, Peru,Philippines,Russia,Argentina,Bangladesh,Croatia,Estonia,Kenya,Mauritius,Oman,Romania,SriLanka,andTunisia.Thesecountrieswerechosenbasedonthelatestversion(September2011)oftheFTSEgroupforemergingstockmarkets.2http://www.forbes.com,[accessedon4thAugust2014]161.7Organization of the studyChapter1providesageneralintroductiontothestudy,bybrieflyoutliningtheimportanceofthefinancialmarketanditsrelationtoliberalization.Thisisfollowedbythestatementoftheproblemthestudyaimstoinvestigate,thestudyobjectives,theresearchquestionsthatthestudyaimstoanswer,aswellassignificanceandscopeofthestudy.Chapter2reviewsthedefinitionsofstockmarketefficiencyprovidedbydifferentschoolsof thoughts, and presents most relevant theoretical literature on neoliberalism and itsantagonistandpropagandists.Thesereviewsprovidethebasisfortheconflictsregardingthe advantages and disadvantages of financial liberalization. In the next section of thischapter, the evolution on the nexus between financial liberalization and stock marketefficiencyisdiscussed.Chapter3containsthemethodologicalframeworkformeasuringtheefficiencythroughvarianceratiotest,aswellasHurstExponentmethod,differentpanelunitroottesttypes,cointegrationtest,andpanelcausalitytest.Italsoincludesacomprehensiveexplanationof the system GMM estimator, which provides long-term coefficients related to thevariables.Thechapterendswithaneconometricdescriptionofthethresholdpanelandprovidessomerecommendationsonhowtorectifyitsdrawbacks.Chapter 4 presents model specification and estimation results of the first objective onGrangercausality.Theresultsofthepanelunitroottest,cointegrationtest,andshort-andlong-termcausality.Italsoidentifiestheconditionsunderwhichfinancialliberalizationwouldenhancestockmarketefficiencyinemergingmarkets.Themodelspecificationandempiricalresultsofthelong-termrelationshipbetweenfinancialliberalizationandstockmarketefficiency,obtainedbyapplyingsystemGMM,arepresentedinChapter5.17Estimation of the threshold panel model, aimed at obtaining the critical level of thethresholdvariable,whichjustifiestheconflictsintheliterature,ispresentedinChapter6.Finally, Chapter 7 summarizes the results of allthe models developed inthis study, aswell as highlights the key policy implications and recommendations for authorities, inhopetoenablethemtobenefitfromfinancialliberalization.18CHAPTER 2: LITERATURE REVIEW 2.1Introduction The inter-relationship of share returns and the macroeconomic variables has been asubjectofconsiderableinterest,judgingfromtheabundantliteratureonthetopic.Sincethelate1980s,manydevelopingcountrieshaveactivelypursuedfinancialliberalizationpolicies,withtheanticipationthattheopeningofcapitalaccountwilldeliverhigherratesof economic growth. Their broad liberalization packages also included the removal ofstatutoryrestrictionsonforeignownershipofdomesticequitysecuritiesforstockmarketopenings(seeBekaertandHarvey(2000)andHenry(2000)).Asaresult,mostemergingmarketeconomiesexperiencedsurgesinthevolumeofinternationalcapitalflowsoverthenexttwodecades.However,aseriesoffinancialcrisesinthe1990sandtherecentglobalfinancialturmoilhavetriggeredanintensedebateinboththeacademicandpolicycirclesonthedesirabilityoffullliberalizationofcapitalflows.2.2Definition of stock market efficiency Thebehaviorofstockpricesindeveloped,aswellasinlessdevelopedmarkets,isakeytopicinthe financeliterature.Stockmarketsare supposedtohavetheabilitytoattractportfolioinvestments,enhancedomesticsavings,andimprovethepricingandavailabilityof capital for domestic investment. However, the achievement of these requirementsdepends upon the efficiency of stock markets. Whenever stock markets facilitate theoperationofthecapitalmarket,theyplayadecisiveroleinthepricingofrisk,aswellasthepricingandallocationofassets.19ThetermmarketefficiencywasfirstformalizedintheseminalreviewofFama(1970)and has since been generally referred to as the informational efficiency of financialmarketsthatemphasizestheroleofinformationinsettingprices(LimandBrooks,2011).AccordingtoFama'sEfficientMarketHypothesis(EMH),atanygiventime,themarketprices already reflect all known information, and change fast in response to any newinformationthatbecomesavailable.Accordingtothispremise,nomarketparticipantcanoutperformthemarketbyusingtheinformationalreadyavailabletoallinvestors,exceptbysheerchance(Fama,1998):Fama(1970)distinguishedbetweenthreeformsofmarketefficiency,withregardtotherelevantinformationsubset:1.Amarketisweaklyefficientifpricesfullyreflectallinformationcontainedinthehistoricalpriceseries.Therefore,ifstocksfollowarandomwalk,itisimpossibletopredictfuturereturnsbyusinginformationinthepatternofstockpricesbasedontechnicalanalysis.2.Thesemi-strong-formofEMHexpandstherelevantinformationsettoallpubliclyavailable information that might influence the value of a given company. Suchefficiency implies that a fundamental analysis of a firm and the economy ingeneralwillnotenableinvestorstoearnexcessreturns.3.Amarketinwhichanyinvestorhasmonopolisticaccesstoallinformationrelevantforpriceformation,includingprivate(insider)knowledge,iscalledstronglyefficient.Thus,thereisnopossibilityformarketparticipantstomakeexcessreturns.20Sinceverifyingtheefficiencyofastockexchangeinastrong-formisdependentonthestock exchange having already been efficient in semi-strong-form, and verifying theefficiencyinasemi-strong-formisdependentonthestockexchangehavingalreadybeenefficientinweak-form,itisnecessarythattheefficiencyofastockexchangeinaweak-form be studied and verified first. Thus, the existence of significant stock returnautocorrelations would imply investors mis-reaction to information. Thisinterpretation has strong theoretical grounds and is widely adopted in the existingempirical literature, which offers strong support for the view that short-horizon stockreturnsarepredictable.We can broadly divide the prevailing views on the meaning of these correlations intothree schools of thoughts. The first school, the loyalist, posits that markets rationallyprocess information. They argue that large autocorrelation at short horizons is due tomarketfrictions.Similartotheloyalists,thesecondschoolofthought,therevisionist,believesthatmarketsare efficient. However, even in frictionless market, short-horizon stock returns can beauto-correlated.The third school of thought, the heretic, takes a different approach, suggesting thatmarketsarenotrational,andthatprofitabletradingstrategiesdoexist.Hereticsarguethattimeseriespatternsinreturnsoccurbecauseinvestorseitheroverreactoronlypartiallyadjust to information arriving to the market. Thus, astute investors can achieve excessprofits, even if financial markets are functioning well. Based on the statistical analysisconductedbyBoudoukh,RichardsonandWhitelaw(1994)themarketsreactquicklytoinformation,suchasannouncementsofearnings,dividends,andtakeovers.Thisplaces21somedoubtonthehereticsviewduetodelayedreactionanddeathofmarketefficiency.The present study is based on Boudoukh, Richardson and Whitelaw (1994) work thatsupports the loyalist and revisionist3 point of view, and seeks to measure stock returnautocorrelation,usingitasanindicatorofstockmarketefficiency.Figure2.1:ReactionofstockpricetonewinformationinefficientandinefficientmarketsSource:http://www.rhsmith.umd.edu/faculty/gphillips/courses/Bmgt640/Effic.pdf(accessedon2Jan2014)2.2.1Serial correlation and market inefficiency Inthissection,twoissuesrelatedtomarketefficiencyarediscussed,thefirstofwhichis:1.Doesthepresenceofsignificantserialcorrelationsinstockreturnsindicatemarketinefficiency?3LoyalistdefinitionofmarketefficiencyimpliesmarketrationalityandRevisionistdefinitionofmarketefficiencyisbasedonlackofprofitability(seeRubinstein(2001)andJensen(1978))StockPriceEfficientmarketresponsetoBadnewsDelayedresponsetoBadnewsOverreactiontoBadnewswithreversionDaysbefore(-)andafter(+)announcement-30-20-100102022Marketefficiencyhasbeendefinedinmanydifferentways(forreferences,seeLimandBrooks (2011)), and an agreed-upon standard definition is still lacking. Hence, it isimportant for researchers to clarify how they define and measure such informationalefficiency.Inthisstudy,thepricereflectivity-baseddefinitiongivenbyMalkielandFama(1970), is adopted, whereby a stock market is efficient if new information is fullyreflected in its current stock price and the resulting price changes are completelyunpredictable. Thus, the existence of significant stock return autocorrelations wouldimplyinvestors'mis-reactiontoinformation.Thisinterpretationhasstrongtheoreticalgroundsandiswidely adoptedintheexistingempiricalliterature(FrootandPerold,1995).Manyresearchershaveattemptedtoexplainhow asset prices adjust to the release of new information. According to the marketefficiency theory developed by Malkiel and Fama (1970) and Fama (1998) the semi-strongefficientmarketistheoneinwhichpricesquickly,andinanunbiasedway,reflectthepublicinformation(Acharya,2010).Differentframeworkshavesincebeendevelopedtoanalyzethebehaviorofassetpricesin response to the arrival of new information. Brown and Jennings (1989) and Grundyand McNichols (1989) have developed models to explain the price adjustment processbasedontherationalexpectationsframework.Accordingtothisview,whentradersareheterogeneously informed, spot prices and volume contain private information, andtraders have rational expectations about the relationship between prices and signals.Debondt and Thaler (1985 and 1987) advanced the overreactions hypothesis based onempiricalfindings,whichshowedaweakformofinefficiency.Intheirstudysample,pastlosers outperformed past winners within 36 months after portfolio formation, and the23losing stocks earned about 25% morethan the winning stocks. The authors interpretedthisfindingasconfirmingthebehavioralhypothesisofinvestoroverreaction.The empirical findings supporting the underreaction hypothesis were documented byBernardandThomas(1990),andMichaely,ThalerandWomack(1995).Thesestudiessuggested that market behaved differently to different news, underreacting to earningsannouncements,andoverreactingtodividendomissions.JegadeeshandTitman(1993),(2001)reportedsomeanomaliesinstockmarketpricebehavior,astheirfindingsindicatedthatbuyingpastwinnersandsellingpastlosersgeneratedsignificantpositivereturnsover3-12 month holding periods. These types of contradictory findings have led to thedevelopment of alternative theoretical frameworks that aimed to explain the priceadjustmentprocess.Tosummarize,whendataonpastreturnsisavailable,thecross-sectionofstockreturnsispredictableduetotwokeyexplanations.ThefirsttypeofargumentsbasedonDebondtandThaler(1985and1987)contrarianstrategy,suggeststhatlong-termhistoricallosersoutperformlong-termwinnersoverthesubsequentthreetofiveyears,implyingnegativeautocorrelationintheholding.Secondly,alternativecompetinghypothesestendtofocusonthepredictabilityofacontrarianstrategybasedonthepremisethatmarketsrespondtonewinformationgradually.Theempiricalevidencesuggeststhatastockwithlowpastreturns would, on average, experience low subsequent returns, thus indicating positiveautocorrelation.From an efficient market perspective, the speed of adjustment can be assessed bycheckingfortheevidenceofunder-orover-reactioninsecurityprices,whileadjustingtotheir intrinsic values when new information is released. The intrinsic value series that24emergesisassumedtofollowrandomwalk(Acharya,2010),wherebyindividualintrinsicvalues are serially uncorrelated in efficient markets with adjustment coefficient = 1,whereascoefficient>1indicatesover-reaction,andcoefficient\ . (3.47)( )it i it ity x o | c ' = + + (3.48)The observations are divided into two regimes depending on whether the thresholdvariablei tq isaboveorbelowthethreshold.Theregimesaredistinguishedbydifferingregressionslopes1| and2| .Fortheidentificationof1| and2| ,itisrequiredthattheelementsofitx arenottimeinvariant.Itisfurtherassumedthatthethresholdvariablei tq isnottimeinvariant.Caselli,EsquivelandLefort(1996)arguedthatestimatescouldbeinconsistentincross-countrygrowthregressionsdueto:(i)country-specificfixedeffects,and(ii)theinclusionofendogenousvariablesamongexplanatoryregressorsinthemodel.In the current model design, these two issues are appropriately addressed, yieldingconsistentestimates.3.6.6.1Elimination of fixed effect Inthefirststage,thecountry-specificfixedeffectsio areeliminatedfromthemodeltoestimate the slope coefficients and the potential threshold point. According to Nickell(1981)andBond(2002),within-grouptransformationdoesnoteliminatedynamicpanelbiasbecausethetransformedlaggeddependentvariable(1*itx )negativelycorrelateswiththe transformed error term*itc . Thus, in the present study, another commontransformation method called forward orthogonal deviationproposed by ArellanoandBover(1995)isused.Thus,forwardorthogonaldeviationtransformationisappliedto eliminate individual fixed effects. Therefore, for the error term, the requiredtransformationisgivenby107*( 1)1[ ( ... )]( )it t it i t iTcT tc c c c+= + + (3.49)where1tT tcT t= +and2var( )it TI c o = isnotseriallycorrelatedand* 2-1var( )it TI c o = hasnoserialcorrelationeither.Applyingthisproceduretoequation(3.45)yields:* * * * *0 1 2( ) (1 [ ]) ,it it it it it it ity d d x | | t t | t t u c ' = + s + > + + (3.50)where 1, , 1 t T = . andsuperscript*denotesdataafterthetransformation.3.6.6.2Dealing with endogeneity Structuralequation(3.39)requiresasetofsuitableinstrumentstoaddresstheproblemofendogeneity. Thus, the lags of dependent variable are used as instruments for thepredetermined regressor. For the transformed lag of the dependent variable ) (* 1itx , theuntransformed value1itx is used. As there are no clear guidelines regarding theidentification restrictions, following the collapsed-form instrument method Roodman(2006), the following (T-1) moment conditions are adopted, thus employing the entireavailablesetoflagsasinstruments:1 *wher ( , ) 0 e 2, , 1it itE x t T c = . = (3.51)Next,theinstrumentalvariableparameter,or2SLSestimator,isestimatedthroughatwo-stepprocedure.Inthefirststep,areduced-formregressionfortheendogenousvariable1*( )itx isconstructedasafunctionoftheinstrumentsi tz andallexogenousvariables:1081* * * 2 *0 1 , 2 31( ) (1 [ ]) ( )Tit i t j it it it it it itjx z d d x t t t t u u=' ' = + + s + > + + (3.52)where( , ) 0it itE z u =.Next,thereduced-formparameteriscomputedbytheleast-squaremethod,aswellasthefittedvalueoftheendogenousvariable1*itx .Followingthat,1*itx isreplacedbyitsfittedvalue1*itx inequation(3.45),whichcanbewrittenas:* 1* * * 2* *0 1 ( ) 2 (1 [ ])it it it it it it it ity x d d x | | t t | t t u c ' = + + s + > + + (3.53)In the second step, the instrumental variable parameteriv| is estimated from equation(3.47)foranygiventhreshold.Then,theresidualsumofsquare(RSS)canbefound,asafunctionof ,asshownbelowi IVY X c | =(3.54) ( ) *i iS c c ' = (3.55)whereSistheresidualsumofsquare.3.6.6.3Computation of threshold value Inthethirdstep,thethresholdlevelofinstitutioniscalculatedbyusingtheconditionalleast square method. To estimate the threshold , the procedure described above isrepeated,changingthethresholdlevelofinstitutionrangingfromto withadecimalvalueofincrement.Finally,thethresholdvalue isselectedasthevalueassociatedwiththesmallestRSS.Theminimizationsearchtakesthefollowingform:109() argminnS =(3.56)Oncethethresholdvalueof isdetermined,inthesecondstage,theslopecoefficients(1| and2| )areestimatedandtheimpactofothercontrolvariablesondependentvariable(stock market efficiency) is determined using GMM. In this case, the previously usedinstruments and the previous estimated threshold are used. Finally, a test can beconducted in order to establish whetherthe threshold level is significant by testing theequality1 2| | =,whichisequivalenttotestingthefollowingnullhypothesis:0 1 2: H | | =3.7Data and scope of the study Inthisstudy,theactualvaluesofdailyindicesof27emergingstockmarketsareused.The closing prices for the major stock index in each market, denominated in theirrespectivelocalcurrencyunits,arecollectedfromDatastream.Duetotheavailabilityofallsamplecountries,thesampleperiodspansfromJanuary1st1996toDecember30th,2011.Astheestablishmentofstockmarketisanewphenomenoninemergingmarkets,thedataavailabilityforalongperiodisonetheseriouslimitationofthestudy.Formostofthecountriesstockpricewereavailableonlyforthelast3yearswhichisinsufficienttoconductapaneldataanalysis.Therefore,thecountrysampleshasautomaticallyshrink.Calculating the stock market efficiency, first, the log return ( )1/t t tr ln p p= iscalculated,wheretp istheclosingpriceoftheindexondayt.Secondly,twodifferentmodelsfromtwoschoolofthoughtshavebeenappliedtodefineinformationalefficiencyofstockmarkets.110As it is discussed in 3.2, there is a broad spectrum of test to measure stock marketefficiencyfromstaticanddynamicaspect.ForStaticaspectofefficiency,basedon(Jae(2009);Kim,ShamsuddinandLim(2011))whenthereturnsaresubjecttoanunknownformofconditionalheteroskedasticity,theuseofwildbootstrappedautomaticvarianceratiotestisstronglyrecommended.AsAVR( k)testisanasymptotictestthatmayexhibitdeficientsmallsampleproperties,thewildbootstraptestcanbeemployedtomitigatethiseffect.Fordynamicaspectofefficiency,anewlyintroducedmeasureinfinanceliteratureisappliedwhichconsidersthelongtermcorrelationmemory. The study sample comprises of Czech Republic, Hungary, Malaysia, Mexico, SouthAfrica, Thailand, Turkey, Chile, China, Colombia, Egypt, India, Indonesia, Pakistan,Peru, Philippines, Russia, Argentina, Bangladesh, Croatia, Estonia, Kenya, Mauritius,Oman,Romania,SriLanka,andTunisia.Thesecountrieswerechosenbasedonthelatestversion(September2011)oftheFTSElistofemergingstockmarkets.Indevelopingcountries,therearegapsbetweende jureannouncementdateofliberalizingandde factoimplementationdate.AccordingtoKimandLim(2011),althoughgreaterlevel of de facto trade openness is associated with a higher degree of stock marketefficiency, this positive relationship does not hold when dejure measure is used. Thisimpliesthatofficialtradereformsareinsufficienttotakeadvantageofreturnstoscaleiftheyarenotaccompaniedbyacorrespondingincreaseintheactualleveloftradeflows.Hence,inthecurrentmodel,de factotradeopenness,definedbythetradevolume/GDPratio, is used. For financial openness, as mentioned above, calculating net capitalflows/GDPratioforselectedcountriesallowscapturingthede factofinancialopennessindex.Intheworkpresentedhere,thestockmarketopeningisofinterest,whichcanbe111representedinnetequityflowstoGDP,fortwomainreasonstherequireddataisfreelyaccessibleandcanbeusedtoinfertheintensityoffinancialopenness.As highlighted by Kaufmann, Kraay and Mastruzzi (2005) in the World Banks WGIresearch report, precision of the governance estimates has been boosted due to theincreasednumberofindependentdatasources.ThekeyadvantagesoftheWGIstemfromthe time-varying characteristic, as the effect of time invariant characteristic cannototherwisebedistinguishedfromthecountry-specificeffects.Anumberofinteractionvariableshavebeenusedtomeasuretherightcircumstancesinwhich financial liberalization can lead to improve efficiency. Many authors haveattempted to analyze institution effect by employing variables that measure generalinstitutional quality, such as indicators of corruption, law and order, and bureaucracyquality, extracted from International Country Risk Guide. However, following thecomprehensive work by Kaufmann, Kraay and Mastruzzi (2005), which aimed toestablish new generation institutional variables referred to as Governance Indicator,theresearchfocushasshiftedtorecruitingthem.112CHAPTER 4: CAUSALITY RELATIONSHIP BETWEEN FINANCIAL LIBERALIZATION AND STOCK MARKET EFFICIENCY 4.1IntroductionTheon-goingdebateonthedirectionofthecausalitybetweenfinancialliberalizationandstock price behavior has prompted this research, the aim of which is to empiricallyinvestigate the direction of causality between financial liberalization and stock marketefficiency using recently developed approaches. Based on the widely adopted theory,financial liberalization stimulates stock market efficiency. On the other hand, manyauthorsindicatethatcountrieswithmoreefficientmarketstendtobemoreopentowardsforeign investment. These arguments suggest that, if financial openness enhancesefficiency,efficiencymayreciprocallystimulatefurtherliberalization.Duetothepaucityof empirical evidence of the positive relationship between financial liberalization andefficiency,thecausallinkhasnotyetbeenestablished.Themainobjectiveofthispartofthestudyistoinvestigatethedirectionalrelationshipbetweenefficiencyofemergingstockmarketandfinancialliberalizationintheshortandlongterm.4.2Contradictory results Althoughnumerousresearchershavestudiedempiricaleffectsoffinancialliberalizationonstockmarketefficiency,thereisnoconsistentconclusion.ForexampleKimandSingal(2000); Ciner and Karagozoglu (2008), and Cajueiro, Gogas and Tabak (2009) haveshownthatstockmarketseemstobelessautocorrelatedsubsequenttomarketopening,113rendering it more efficient. On the other hand, Kawakatsu and Morey (1999) andNikiforos(2004),LimandKim(2011)positedthatthereisnoevidenceofimprovingtheefficiency after liberalization. A part from the contradictory result in the pertinentliterature,thereisalsoanothertypeofargumentthatrapidliberalizationofthefinancialsystemwasapreconditionforfinancialcrisisinSouthEastAsia.Thiswouldimplythatcountriesaremorelikelytoexperiencefinancialcriseswhentheirfinancialmarketsareopentoforeigncapital(MehrezandKaufmann,2000).Asdiscussedearlier,thiseffectmight,however,bemitigatedifinstitutionalsupportiscapableofensuringthatcountriesenjoythebenefitsoffinancialglobalization.As a result, the research in this field has shifted toward conditioning the effect ofliberalizationonthequalityofinstitutions.Despitethisjointeffort,thefindingspertainingtotheconditioningtheliberalizationarestillmixed.AccordingtoCarrieri,ChaiebandErrunza (2013), improvements in corporate governance and institutions complementmarket liberalization policies and help in further integrating of emerging markets. BenNaceur,GhazouaniandOmran(2008)foundthatamoredevelopedfinancialmarketpriorto liberalization reinforced the positive impact of liberalization on stock marketdevelopment.Ontheotherhand,Edisonetal.(2002)providednoevidenceofagrowtheffect,evenwhencontrollingforinstitutionalcharacteristicsorthefinancialdevelopmentlevel.Similarly,Honig(2008)foundlittleevidenceofastrongereffectincountrieswithbetterinstitutionalcontrol.Hence,thereviewofextantliteraturerevealsconflictingviewofthisrelationship,evenafterconditioningfortheliberalization.Based on economic theories, foreign investors typically require local firms to produceaccurateandtimelydisclosuresandshowevidenceofstrongadherencetointernationalnormsofcorporategovernance.Thispractice,inturn,improvesthequalityofinformation114availabletothedomesticmarketparticipants,leadingtoagreaterdegreeofinformationalefficiency(LimandKim,2011).However,theinconsistencyinthereportedfindingmaygiverisetotheefficiency-letto-liberalizationhypothesiswhichisnotcompatiblewitheconomictheories.Assuming that removing capital market restrictions should promote financialdevelopment, reverse causality from development to capital account openness is apossibleexplanationfortheweakresultspublishedinpertinentliterature.Itispossiblethat countries characterized by low efficiency opt for liberalization because of theassumed efficiency-enhancing effects, resulting in a weaker correlation fromliberalizationtowardshigherefficiency;orperhapsmoreefficientmarketsaremoreeagertoliberalizetheircapitalaccounts,whilelessefficientmarketsaremorepronetoadoptmorestringentcapitalcontrols.Accordingtoanotherdescription,amoreefficientstockmarket may be a proxy for the extent of information asymmetries that may causevolatility,leadingthecountrytowardsliberalization(Lietal.,2004).Basedontheworkby Shin (2012), it can be posited that more developed stock market in which sounddomesticfinancialinstitutionsparticipatewouldleadtheeconomytowardsliberalization.Therefore, the causality relationship between financial liberalization and stock marketefficiency is going to be investigated in this chapter to see if the empirical result isconsistentwithefficiency-lettoliberalizationhypothesis.Additionally, testing the efficiency-led to-liberalization hypothesis provides theopportunitytoconsidertherelationshipoveratimehorizon.Discussingthenecessityofinstitutionsaspre-requisitetoreaptobenefitsofliberalization,thetimehorizoninwhichinstitutions act is also another crucial factor to be considered. As institutions are deepfactorswhichmoveslowly,theyappearedtoworkoverareasonablylonghorizon.The115likelihoodofcontradictoryeffectsofliberalizationoverdifferenttimehorizonsleadsustoinvestigatetheveracityofJcurvehypothesis.J-curvehypothesisseekstoanalyzeifshort-term deterioration is consistent with long-term improvements on stock marketefficiencywhileliberalizingthedomesticcapitalmarket.TheJ-curvehypothesiswasfirstintroducedintheseminalworkofMagee(1973)andSincethenhasbeenappliedmostlywithaggregateorbilateraltradedata.ThecurrentstudythustakestheinitiativetoanalyzeJ-curve in a new concept that links it to the short- and long-term effects of financialliberalization.Consequently,thefollowingchaptersaregoingtoelaboratewhen,how,andunderwhatcircumstanceseconomiesshouldliberalize.4.3Model specification and data In order to examine whether financial liberalization can improve the stock marketefficiency,themodelspecificationsdescribedbelowareutilizedinthiswork.To investigate whether the methods of measuring stock market efficiency affect theresults,thesamemodelwillbeexecuted,whileapplyingtwodifferentformsofdependentvariable. In equation (4.1), the dependent variable was calculated based on the EMHapproach,whichconsidersthestaticformofefficiency.TheAutomaticVarianceRatiotestwasappliedforthisapproach.Inordertocapturethedynamicformatofefficiency,equation(4.2)hastakenHurstExponentmethodtomeasurethedependentvariable.1 2 3| 1|it i i it i i it itVR FO TO INST o | | | c = + + + + (4.1)1 2 3 it i i it i i it itHE FO TO INST o | | | c = + + + + (4.2)116The dependent variable 1itVR is an inverse measure of informational efficiency forcountryiinyeartfromEMHapproach,HEisanothermeasureofinformationalefficiencyfrom AMH hypothesis, anditFO is the proxy for financial openness followed by twocontrol variables, namely trade openness (itTO ) and institution (itINST). INST is theaverageofthesixGovernanceIndicatorcomponentsforeachyear.Finally,thesubscripti denoteseachofthe27countriesincludedintheanalysisoftheannualdataforthe1996-2011period.Tocheckthecausalrelationshipbetweenfinancialliberalizationandstockmarketefficiencytheinstitutionvariableisconsideredasamediatoryvariable.Therefore,alldimensionshavebeencombinedtogeneratearepresentativeforinstitutionconcept.Underthenullhypothesisofarandomwalkwithuncorrelatedincrements,varianceratios(VRs)shouldbeequaltooneatalllags.VRssignificantly aboveoneindicatepositiveserialcorrelation,whereasvaluesbelowoneindicatenegativeautocorrelations.Becausebothnegativeandpositiveautocorrelationrepresentdeparturesfromarandomwalk,theabsolute value of the VR statistic minus one ( 1 VR) is used as a measure of relativeefficiency.Thisapproachisadvantageousinthat,ifamarketconsistsofstockssubjecttobothover-andunder-reactiontopastreturns,bothwouldbecaptured.Hence,thepanelregressionanalysisemploys( )1 VR k isusedasthedependentvariabletoexaminetheempiricalrelationshipbetweenopennessandthedegreeofinformationalefficiency.Table4.1showsthesummarystatisticofEMHstockreturnefficiencybasedondailydatafrom02/01/1996to29/12/2011foratotalof4176observations,wherebythestockpricedata are provided by Datastream. Table 4.2 represents stock return efficiency derivedfromtime-varyingHEmethod,whichisrepresentativefortheAMHperspective.117The estimation of the Hurst exponent for time windows with 1040 observations each,thousands of times is performed. To calculate rolling Hurst exponent, the first 1040observations is selected, rolled the sample one point forward to eliminate the firstobservationandincludethenextoneforthenewtimewindow,andrepeatthisprocedureuntiltheendoftheseries,inarollingsampleapproach.Applyingmovingmethodtothedata,showsthatthedegreeofmarketefficiencyvariesthroughtime.ItmeanstherollingHurstExponent(HE)togetaspecificdataforthedependentvariableforeachyear.Table4.2presentsthedescriptivestatisticsforHurstExponentforshuffledequityreturns.As we can see these Hurst Exponents- representative for AMH perspective- are highrangingfrom0.4128forEgyptto0.9098forSriLanka.4Themutualinteractionsoffinancialliberalizationandstockmarketautocorrelationareofparticular interest in the current estimation model. Within the existing econometricsliterature, recently developed panel error-correction model (panel ECM) allowsexamining the long- and short-term effects of financial liberalization on stock marketefficiency. However, the prerequisite for implementing the estimations is to clarifywhetherthereisalong-termrelationship,whichiscontingentonthetestingofpanelunitrootandexistenceofpanelcointegration.The LLC statistics developed by Levin, Lin and Chu (2002), IPS developed by Im,PesaranandShin(2003),andtheCIPSdevelopedbyPesaran(2007)arethethreemostwidelyadoptedtoolsfortestingtheexistenceofpanelunitroot.Ifthenullhypothesisthatapanelunitrootexistsisnotrejected,thecointegrationrelationshipamongthevariablespresentedinequations(4.1)and(4.2)shouldbeinvestigatedfurthertoascertainthatthis4FiguresintheAppendixApresenttime-varyingHurstExponentforeachcountry(withandwithoutshuffling)118expressionyieldsarenotspurious.Inthiswork,theresidualsitc ,obtainedbyestimatingequations(4.1)and(4.2),areusedtotestthenullhypothesisofnocointegrationbetweenthe variables. It is clear from the econometric specification slope that coefficients( )1 2 3, ,i i i i| || | = are allowedtobeheterogeneousacrossthe countriesincludedinthestudysample.119Table4.1:Summarystatisticsofstockreturninformationalefficiency(EMHapproach)fromJanuary1996toDecember2011derivedfromRpackageCountries MeanStandardDeviationMedian Minimum MaximumArgentina 0.0982 0.0659 0.0837 0.0005 0.3074Bangladesh 0.1337 0.2004 0.0691 0.0008 0.8424Chile 0.5699 0.3964 0.4145 0.0000 1.3212China 0.0426 0.0598 0.0155 0.0008 0.2116Colombia 0.1773 0.2226 0.0535 0.0000 0.6387CzechRepublic 0.2035 0.2289 0.1181 0.0181 0.8307Croatia 0.1961 0.2053 0.0797 0.0000 0.6359Egypt 0.3222 0.2735 0.2940 0.0008 0.9887Estonia 0.3306 0.2167 0.2551 0.0000 0.7981Hungary 0.1300 0.1921 0.0816 0.0004 0.8291India 0.0921 0.0995 0.0497 0.0004 0.3518Indonesia 0.2017 0.1589 0.1688 0.0012 0.5493Kenya 1.0480 0.7843 0.8727 0.0016 2.2965Mauritius 0.6975 0.3903 0.6946 0.0063 1.4161Malaysia 0.2597 0.1523 0.2407 0.0002 0.4734Mexico 0.1084 0.0820 0.1400 0.0017 0.2262Oman 0.3844 0.3790 0.3215 0.0000 1.7012Philippines 0.2637 0.1180 0.3119 0.0026 0.3771Pakistan 0.1490 0.2428 0.0821 0.0032 1.0565Peru 0.4015 0.2212 0.3849 0.0810 0.8937Romania 0.2745 0.2948 0.2229 0.0000 1.2615Russia 0.1719 0.1285 0.1570 0.0052 0.4733SouthAfrica 0.1511 0.1589 0.1233 0.0009 0.5193SriLanka 0.6955 0.8088 0.4392 0.0552 3.5205Thailand 0.1735 0.1518 0.1531 0.0004 0.4417Turkey 0.0817 0.0859 0.0446 0.0001 0.3034Tunisia 0.6196 0.5710 0.4826 0.0000 1.8193120Table4.2:Summarystatisticsofstockreturninformationalefficiency(AMHapproach)fromJanuary1996toDecember2011derivedfromMatlabpackageCountries MeanStandardDeviationMedian Minimum MaximumArgentina 0.6318 0.0495 0.6372 0.5533 0.7428Bangladesh 0.6507 0.0552 0.6551 0.5488 0.7304Chile 0.6919 0.0608 0.6756 0.6053 0.8068China 0.6264 0.0507 0.6182 0.5258 0.7300Colombia 0.5979 0.3367 0.6889 0.5944 0.7803CzechRepublic 0.6454 0.1675 0.6446 0.5639 0.7773Croatia 0.6289 0.1592 0.6372 0.5359 0.7267Egypt 0.6272 0.0703 0.6330 0.4128 0.7420Estonia 0.6900 0.1742 0.6814 0.5773 0.7951Hungary 0.6263 0.0303 0.6324 0.6869 0.6869India 0.6305 0.0462 0.6351 0.5472 0.7077Indonesia 0.6493 0.0511 0.6533 0.5061 0.7206Kenya 0.6844 0.0774 0.6953 0.5465 0.8594Mauritius 0.7243 0.0632 0.7230 0.5771 0.8397Mexico 0.6194 0.0501 0.6142 0.5351 0.6884Oman 0.6586 0.1728 0.6647 0.5231 0.7732Philippines 0.6604 0.0484 0.6695 0.5674 0.7287Pakistan 0.5635 0.0337 0.6514 0.5716 0.7301Peru 0.6854 0.0489 0.6864 0.5925 0.7889Romania 0.6591 0.2227 0.6621 0.5547 0.7379Russia 0.6434 0.0440 0.6489 0.6533 0.7124SouthAfrica 0.6211 0.0571 0.6218 0.7523 0.5414SriLanka 0.7056 0.0804 0.6896 0.5710 0.9098Thailand 0.6379 0.0410 0.6447 0.5313 0.7038Turkey 0.6325 0.0302 0.6332 0.5743 0.7089Tunisia 0.6891 0.2326 0.7101 0.5681 0.7803Note:Theblocksizeischosentobe10forshufflingdata.1214.4Panel unit root test Cointegration analysis is an appropriate technique for investigating the long-termrelationshipamongstockreturnautocorrelation,financialopenness,tradeopenness,andinstitutions.Beforeapplyingthislong-termrelationshipbyusingthepanelcointegrationprocedure,thestationaritypropertiesofthevariablesneedtobeinvestigated.Therefore,itisnecessarytotesttheorderinwhichthevariablesareintegratedinthemodel.Itshouldbenoted,however,thatthepowerofstandardtime-seriesunitroottestmaybelow,giventhesamplesizeandtimespans.Therefore,inthiswork,therecentlydevelopedpanelunitroottestsareadopted.Fortestingtheorderofintegrationforeachvariable,thepanelunitroottestsdevelopedbyLevin,LinandChu(2002)[LLC],Im,PesaranandShin(2003)[IPS],andPesaran(2007)[CIPS].Table4.3showstheresultsoftheLLCandIPStests,bothofwhichsuggestthatthenullhypothesisofnon-stationarityshouldberejectedforAutcor andHEseries.However,theresultsoftheorderofintegrationforFO,TO,andINSTseriesarenotconsistent,likelydue to violating the assumption of cross-section independence. As it is discussed inchapter three, an important assumption underlying the IPS test is that of the cross-sectionalindependenceacrosstheindividualtimeseriesinthepanel.Since the panel unit root tests, the results of which are shown in Table 4.3, have beencriticizedduetobeingbasedoncross-sectionalindependence,itisnecessarytotestforcross-sectionaldependenceoftheerrorsandtore-considertheunitrootpropertiesofthevariables included in the model. It is importantto ensure that, if a mixture of differentorders of integrated variables is employed, a sensible interpretation of the long-termrelationshipislikelytoemerge.122Table4.3:Panelunitroottest-LLCandIPStestSeries LLC IPSInterceptonly Interceptandtrend Interceptonly InterceptandtrendAutcor-14.12(0.00)*** -6.69(0.00)*** -8.73(0.00)*** -9.28(0.00)***HE -10.17(0.00)*** -7.34(0.00)*** -14.47(0.00)*** -15.19(0.00)***FO-0.46(0.32) -5.02(0.00)*** 0.81(0.079)* -1.12(0.13)FO A -14.50(0.00)*** -4.30(0.00)*** -11.71(0.00)*** -8.15(0.00)***TO-0.78(0.21) -11.38(0.00)*** -2.42(0.008)*** -3.05(0.001)***TO A -22.29(0.00)*** -19.63(0.00)*** -13.39(0.00)*** -8.12(0.00)***INST -11.64(0.00)*** -13.36(0.01)** -0.3416(0.64) -3.52(0.00)***INST A -6.32(0.00)*** -59.25(0.00)*** -16.11(0.00)*** -13.52(0.00)***Note: Probability values are in brackets. *** denotes statistical significance at the 1% level. ** denotesstatistical significance at 5% level and * denotes statistical significance at 10% level. Numbers in theparenthesisarep-value.ThisprocessstartsbylookingattheCD(cross-sectionaldependence)testdevelopedbyPesaran(2004),whichapproachesanormaldistributionasthenumberofcountriestendstoinfinity,andisbasedontheaverageofthepairwisecorrelationoftheOLSresidualsfromindividualpanelregressionsgivenbyequations(4.1)and(4.2).Table 4.4 reports the cross-sectional dependence of the residuals from the ) ( ADF regressionsofthestockautocorrelation,financialopenness,tradeopenness,androleofinstitutions,aswellastheirdifferencesoverthe1996-2011periodacrossthe27countriesincludedinthesample.Foreach (i.e.,1,2,and3),thereportedCDstatisticsarehighlysignificant. The presence of the cross-sectional dependence implies that the use of thestandardpanelunitroottests,suchasLLCandIPS,isnotvalidinthiscase.Inpractice,errorsectiondependencemayariseforvariousreasons; forexample,itmaybeduetothepresenceofspatialcorrelations specifiedonthebasisofeconomicandsocialdistance(Conley,1999)orrelativelocation, aswellasduetothepresenceofunobserved123components that give rise to a common factor specification in the disturbanceswith afixednumberoffactors(eg.JoreskogandGoldberger(1975)). Table4.4:CDteststatisticofADF( )regressionVariable ADF(0) ADF(1) ADF(2)a)WithaninterceptAutcor 36.15 16.35 7.61HE24.16 12.55 5.78FO5.72 3.41 -2.66TO -4.59 -3.37 -3.28INST 8.35 8.91 3.56Autcor A 21.68 38.18 21.68FO A 43.88 17.27 5.30TO A 26.13 17.58 3.39INST A 57.94 19.99 9.47b)WithandinterceptandalinertrendAutcor 27.00 9.97 6.92HE24.60 6.54 5.24FO4.55 3.33 2.60TO 4.52 3.95 3.60INST 6.40 5.30 2.60Notes: istheth-orderAugmentedDickey-Fullerteststatistics, () ADF ,forAutcor,FO, TO,andINST,andiscomputedforeachcross-sectionunitseparatelyintwocases,namely(a)withaninterceptonly,and(b)withaninterceptandlineartimetrend.11 1 2 / ( 1)J Jjkj k jCD T J J = = += ,with jk beingthecorrelationcoefficient of the () ADF regression residuals between jth and kth cross-section units, tends to N(0, 1)underthenullhypothesisofnocross-sectionalerrordependence.Thus, given the above results, the panel unit root tests are performed by applying thecross-sectionallyaugmentedIPS(CIPS)testproposedbyPesaran(2004),eventhoughitisrelativelynewandthuslessusedintheappliedeconomicsliterature.Asexplainedinthe previous chapter, the test was developed by augmenting the Augmented DickeyFuller (ADF) regression with cross-sectional averages of lagged levels and the first124differencesoftheindividualseries,andisthusknownasthecross-sectionallyaugmentedADF(CADF)test.TheCADFstatisticsarereportedinTable4.5fordifferentlagorders,indicatingthat,theresultoftheorderofintegrationforFO, TOandINSTturnsouttobeconsistent.Asitisshown, the unit root test hypothesis cannot be rejected at the 5% significance level.Additionally, the unit root tests for Autcor and HE as dependent variables which wereclearlyrejectedinprevioustests,cannotberejectedatlevel(thetrendiseitherincludedorexcludedfromthetest).Thus,theunitroottestforthefirstdifferenceofAutcor,HE ,FO, TO,andINSTvariablesissignificantlyrejectedandallvariablesaredenotedasI(1).Consequently,ourmodelincludesonlyI(1)variables.In order to check if there is danger of spurious regression, we will check the order ofintegrationoftheresidualsoftheestimatedmodel.125Table4.5:PesaransCIPSpanelunitroottestVariable CADF(0) CADF(1) CADF(2)a)WithaninterceptAutcor -3.81*** -2.86*** -2.18*FO-1.62 -1.27 -1.31TO -1.43 -1.55 -1.44INST -1.54 -1.03 -1.43FO A -3.89*** -2.22*** -2.14*TO A -3.35*** -2.24*** -2.39***INST A -3.48*** -3.03*** -2.90***b)WithandinterceptandalinertrendAutcor -3.89*** -2.98*** -2.70**FO-2.46 -2.19 -2.15TO -2.16 -2.17 -1.73INST -2.10 -2.63* -1.62FO A -4.03*** -2.73*** -2.97***TO A -3.42*** -3.37*** -2.84***INST A -3.71*** -2.97*** -2.76***Notes:Thereportedvaluesare () CIPS statistics,whicharecross-sectionalaveragesofcross-sectionallyAugmentedDickey-Fuller( ( ) CADF )teststatistic.4.5Panel level effect Inordertoobtaintheresidualsofthemodel,itisnecessarytofirstestimatetheequationsrepresentedinthebeginningofthechapter.(equations(4.1)and(4.2)).Theresultsforthethree estimation types for equations (4.1) and (4.2) are shown in Table 4.6. and 4.7.respectively.Cross-sectionindependencyassumptionamongtheunitsofthepaneldatacanberarelyfoundinempiricaleconomicanalyses.Cross-sectiondependenceappearsnaturallywhendealing with economic data due to, for instance, market integration processes,globalization of economic activity, offshoring processes or because of presence ofcommonshocks.Therefore,recenteconometrictoolshavedevotedconsiderableattention126to devising procedures, relaxing the assumption of cross-section independency. Theremay be different sources of cross-section dependency. The pervasive cross-sectiondependency is due to the notion of neighbors. However, neighbor does notnecessarilyneedtobedefinedintermsofphysicalcontiguity,suchasneighborregionsorcities,butmayalsobedefinedinter aliaintermsofeconomicdistance,usually,tradepartnerships(Chudik,PesaranandTosetti,2011).Toeliminatecross-sectionaldependence(CD)asymptotically,commoncorrelatedeffects(CCE) type estimators developed by Pesaran (2006) have been applied. One of theestimatorspoolsobservationsovercross-sectionalunitsandiscalledCCEpooled(CCEP)estimator. The other estimator, CCE mean group (CCEMG) estimator, is just a simpleaverageoftheindividualcountriescoefficients.TheCCEmethodsareshowntoberobusttodifferenttypesofcross-sectiondependenceoferrors,possibleunitrootsinthefactorsandslopeheterogeneity.TocompareCCEestimatorswithcommonestimators,inwhicherrorsareconsideredcrosssectionallyindependent,themeangroup(MG)estimatoralsohasbeenapplied.ThefirstcolumnreportstheMeanGroup(MG)estimates,assumingthaterrorsarecross-sectionally independent. The second and third column represent the coefficients ofCommonCorrelatedEffectMeanGroupand(CCEMG)(seePesaranandTosetti(2011))andCommonCorrelatedEffectPooled(CCEP),respective