Table Of ContentJournal of
Nonparametric
Econometric
Methods and
Application
Edited by
Thanasis Stengos
Printed Edition of the Special Issue Published in
Journal of Risk and Financial Management
www.mdpi.com/journal/jrfm
Nonparametric Econometric Methods
and Application
Nonparametric Econometric Methods
and Application
SpecialIssueEditor
ThanasisStengos
MDPI•Basel•Beijing•Wuhan•Barcelona•Belgrade
SpecialIssueEditor
ThanasisStengos
UniversityofGuelph
Canada
EditorialOffice
MDPI
St.Alban-Anlage66
4052Basel,Switzerland
This is a reprint of articles from the Special Issue published online in the open access journal
JournalofRiskandFinancialManagement (ISSN 1911-8074) from 2018 to 2019 (available at: https://
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Contents
AbouttheSpecialIssueEditor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii
Prefaceto”NonparametricEconometricMethodsandApplication” . . . . . . . . . . . . . . . . ix
YiguoSunandXimingWu
LeverageandVolatilityFeedbackEffectsandConditionalDependenceIndex:ANonparametric
Study
Reprintedfrom:JRFM2018,11,29,doi:10.3390/jrfm11020029 . . . . . . . . . . . . . . . . . . . . 1
PantelisKalaitzidakis,TheofanisP.MamuneasandThanasisStengos
GreenhouseEmissionsandProductivityGrowth
Reprintedfrom:JRFM2018,11,38,doi:10.3390/jrfm11030038 . . . . . . . . . . . . . . . . . . . . 21
KarenX.YanandQiLi
Nonparametric Estimation of a Conditional Quantile Function in a Fixed Effects Panel Data
Model
Reprintedfrom:JRFM2018,11,44,doi:10.3390/jrfm11030044 . . . . . . . . . . . . . . . . . . . . 35
NickolaosG.Tzeremes
FinancialDevelopmentandCountries’ProductionEfficiency:ANonparametricAnalysis
Reprintedfrom:JRFM2018,11,46,doi:10.3390/jrfm11030046 . . . . . . . . . . . . . . . . . . . . 45
BurakAlparslanErog˜luandBarıs¸Soybilgen
OnthePerformanceofWaveletBasedUnitRootTests
Reprintedfrom:JRFM2018,11,47,doi:10.3390/jrfm11030047 . . . . . . . . . . . . . . . . . . . . 58
ChaoyiChenandYiguoSun
MonteCarloComparisonforNonparametricThresholdEstimators
Reprintedfrom:JRFM2018,11,49,doi:10.3390/jrfm11030049 . . . . . . . . . . . . . . . . . . . . 80
MarkJ.JensenandJohnM.Maheu
Risk,ReturnandVolatilityFeedback:ABayesianNonparametricAnalysis
Reprintedfrom:JRFM2018,11,52,doi:10.3390/jrfm11030052 . . . . . . . . . . . . . . . . . . . . 95
ChuongLuongandNikolaiDokuchaev
ForecastingofRealisedVolatilitywiththeRandomForestsAlgorithm
Reprintedfrom:JRFM2018,11,61,doi:10.3390/jrfm11040061 . . . . . . . . . . . . . . . . . . . . 124
MustafaKoroglu
GrowthandDebt:AnEndogenousSmoothCoefficientApproach
Reprintedfrom:JRFM2019,12,23,doi:10.3390/jrfm12010023 . . . . . . . . . . . . . . . . . . . . 139
SadatRezaandPaulRilstone
SmoothedMaximumScoreEstimationofDiscreteDurationModels
Reprintedfrom:JRFM2019,12,64,doi:10.3390/jrfm12020064 . . . . . . . . . . . . . . . . . . . . 161
Luka´sˇMelecky´,MichaelaStan´ıcˇkova´andJanaHancˇlova´
Nonparametric Approach to Evaluation of Economic and Social Development in the EU28
MemberStatesbyDEAEfficiency
Reprintedfrom:JRFM2019,12,72,doi:10.3390/jrfm12020072 . . . . . . . . . . . . . . . . . . . . 177
v
About the Special Issue Editor
ThanasisStengosisamemberoftheDepartmentofEconomicsandFinanceoftheUniversityof
Guelph,Canada,wherehehasheldaUniversityResearchChairpositionsince2004. Hereceived
his B.Sc. and M.Sc. in Economics from the London School of Economics and his Ph.D. from
Queen’sUniversity,Canada. HecurrentlyservesasanAssociateEditoroftheJournalofApplied
Econometrics,EmpiricalEconomics,andEconomicsLetters,heisamemberoftheeditorialboardof
theJournalofRiskandFinancialManagement,andheiscoeditoroftheReviewofEconomicAnalysis.
His research has been published in journals including the Review of Economic Studies, European
EconomicReview,InternationalEconomicReview,EconomicJournal,JournalofMonetaryEconomics,Journal
ofEconometrics,EconometricTheory,TheReviewofEconomicandStatistics,JournalofAppliedEconometrics,
JournalofBusinessandEconomicStatistics,andtheJournalofEconomicGrowth.
vii
Preface to ”Nonparametric Econometric Methods and
Application”
An area of very active research in econometrics over the last 30 years has been that of non-
andsemiparametricmethods. Thesemethodshaveprovidedwaystocomplementmoretraditional
parametricapproachesintermsofrobustalternativesaswellaspreliminarydataanalysis.Thefield
hasexpandedwithimportantadvancesbothintimeseriesandcross-sectionalframeworksandmore
recently in panel data settings, allowing for data-driven flexibility that has proved invaluable in
appliedresearch. Themethodologyhasbeenenhancedbysoftwaredevelopmentsthathavemade
thesemethodseasytoapply,whichhasopenedupavarietyofpotentiallyimportantandrelevant
applicationsinallareasofeconomics:microeconomics,macroeconomics,economicgrowth,finance,
andlabor,etc.ThepresentSpecialIssuecollectsanumberofnewcontributionsbothatthetheoretical
levelandintermsofapplications.
The papers in the collection cover a number of different topics. Sun and Wu study the
contemporaneous relationship between S&P 500 index returns and log increments of the market
volatility index (VIX) via a nonparametric copula method, where they propose a conditional
dependenceindextoinvestigatehowthedependencebetweenthetwoseriesvariesacrossdifferent
segments of the market return distribution. Kalaitzidakis, Mamuneas and Stengos use a smooth
coefficientsemiparametricmodeltoexaminetheeffectofemissions,asmeasuredbycarbondioxide
(CO2), on economic growth among a set of OECD countries during the period 1981–1998 and
directly estimate the output elasticity of emissions. Yan and Li develop a nonparametric method
to estimate a conditional quantile function for a panel data model with an additive individual
fixed effects, a model that can be applied to a variety of circumstances. Tzeremes examines
theeffectoffinancialdevelopmentoncountries’productionefficiencylevelsanddevelopsrobust
(order-m) time-dependent conditional nonparametric frontier estimators in order to measure 87
countries’ production efficiency levels over the period 1970–2014. Eroglu and Soybilgen apply
wavelet methods in the popular augmented Dickey–Fuller and M types of unit root tests, and
they perform an extensive comparison of the wavelet-based unit root tests, which also includes
the recent contributions in the literature. Chen and Sun compare the finite sample performance
of three nonparametric threshold estimators via the Monte Carlo method, and they find that the
finite sample performance of the three estimators is not robust to the position of the threshold
levelalongthedistributionofthethresholdvariable,especiallywhenastructuralchangeoccursat
thetailpartofthedistribution. JensenandMaheuexaminethepresenceofvolatilityfeedbackin
theoften-debatedrisk–returnrelationshipbymodelingthecontemporaneousrelationshipbetween
marketexcessreturnsandlog-realizedvarianceswithanonparametric,infinitelyordered,mixture
representationoftheobservables’jointdistribution. LuongandDokuchaevaddresstheforecasting
ofrealizedvolatilityforfinancialtimeseriesusingtheheterogeneousautoregressivemodel(HAR)
and machine learning techniques, and they find that their proposed model offers improvements
whenappliedtohistoricalhigh-frequencydata. Korogluinvestigatesthepublicdebtandeconomic
growthrelationshipusingthesemiparametricsmoothcoefficientapproachthatallowsdemocracy
to influence this relationship and parameter heterogeneity in the unknown functional form and
addressestheendogeneityofvariables. RezaandRilstoneextendHorowitz’ssmoothedmaximum
score estimator to discrete-time duration models. They derive both asymptotic properties and
examinefinitesampleperformancethroughMonteCarlosimulations. Finally,Melecky,Stanickova
ix
