The Econometric Analysis of Recurrent Events in Macroeconomics and Finance

233 Pages·2016·2.707 MB·English

by  Don Harding, Adrian Pagan

The Econometric Analysis of Recurrent Events
in Macroeconomics and Finance
THE ECONOMETRIC AND TINBERGEN
INSTITUTES LECTURES
SeriesEditors
HermanK.vanDijkandPhilipHansFranses
TheEconometricInstitute,
ErasmusUniversityRotterdam
TheEconometricandTinbergenInstitutesLecturesseriesisa
jointprojectofPrincetonUniversityPressandtheEconometric
Institute at Erasmus University Rotterdam. This series col-
lectsthelecturesofleadingresearcherswhichtheyhavegiven
at the Econometric Institute for an audience of academics
and students. The lectures are at a high academic level and
deal with topics that have important policy implications. The
series covers a wide range of topics in econometrics. It is not
confined to any one area or sub-discipline. The Econometric
Institute is the leading research center in econometrics and
management science in the Netherlands. The Institute was
foundedin1956byJanTinbergenandHenriTheil,withTheil
being its first director. The Institute has received worldwide
recognition with an advanced training program for various
degreesineconometrics.
Otherbooksinthisseriesinclude
Anticipating Correlations: A New Paradigm for Risk Manage-
mentbyRobertEngle
CompleteandIncompleteEconometricModelsbyJohnGeweke
Social Choice with Partial Knowledge of Treatment Response
byCharlesF.Manski
Yield Curve Modeling and Forecasting: The Dynamic Nelson-
Siegel Approach by Francis X. Diebold and Glenn D. Rude-
busch
BayesianNon-andSemi-parametricMethodsandApplications
byPeterE.Rossi
BayesianEstimationofDSGEModelsbyEdwardP.Herbstand
FrankSchorfheide
The Econometric Analysis
of Recurrent Events in
Macroeconomics and
Finance
Don Harding and Adrian Pagan
PrincetonUniversityPress
PrincetonandOxford
Copyright(cid:2)c 2016byPrincetonUniversityPress
PublishedbyPrincetonUniversityPress,41WilliamStreet,
Princeton,NewJersey08540
IntheUnitedKingdom:PrincetonUniversityPress,
6OxfordStreet,Woodstock,OxfordshireOX201TW
press.princeton.edu
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JacketdesignbyRosalindFlower
AllRightsReserved
ISBN:978-0-691-16708-4
LibraryofCongressControlNumber:2015958412
BritishLibraryCataloging-in-PublicationDataisavailable
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Printedonacid-freepaper.∞
TypesetbyNovaTechsetPvtLtd,Bangalore,India
PrintedintheUnitedStatesofAmerica
10 9 8 7 6 5 4 3 2 1
Contents
Series Editors’ Introduction ix
Preface xi
1 Overview 1
1.1 Introduction 1
1.2 DescribingtheEvents 2
1.3 UsingtheEventIndicators(“States”) 10
1.4 PredictionofRecurrentEvents 12
1.5 Conclusion 13
2 Methods for Describing Oscillations,
Fluctuations, and Cycles in Univariate Series 15
2.1 Introduction 15
2.2 TypesofMovementsinRealandFinancial
Series 16
2.3 PrescribedRulesforDatingBusiness
Cycles 26
2.4 PrescribedRulesforDatingOtherTypesof
RealCycles 38
2.5 PrescribedRulesforDatingFinancial
Cycles 40
2.6 RelationsbetweenCyclesandOscillations 41
2.7 TheNatureofS andItsModeling 45
t
2.8 Conclusion 50
vi (cid:127) Contents
3 Constructing Reference Cycles with
Multivariate Information 51
3.1 Introduction 51
3.2 DeterminingtheReferenceCycleviaPhases 52
3.3 CombiningSpecificCycleTurningPoints 54
3.4 FindingTurningPointsbySeries
Aggregation 60
3.5 Conclusion 61
4 Model-Based Rules for Describing Recurrent
Events 62
4.1 Introduction 62
4.2 DatingCycleswithUnivariateSeries 63
4.3 Model-BasedRulesforDatingEventswith
MultivariateSeries 82
4.4 Conclusion 85
5 Measuring Recurrent Event Features in
Univariate Data 86
5.1 Introduction 86
5.2 TheFractionofTimeSpentinExpansions 87
5.3 RepresentingtheFeaturesofPhases 89
5.4 AmplitudesandDurationsofPhases 90
5.5 TheShapesofPhases 94
5.6 TheDiversityofPhases 99
5.7 PluckingEffectsandRecoveryTimes 100
5.8 DurationDependenceinPhases 101
5.9 Conclusion 106
6 Measuring Synchronization of Recurrent
Events in Multivariate Data 107
6.1 Introduction 107
6.2 Moment-BasedMeasures 108
6.3 OtherApproachestoMeasuring
Synchronization 115
6.4 SynchronizationandModel-BasedRules 116
Contents (cid:127) vii
6.5 ApplicationtoSynchronizationofIndustrial
ProductionCycles 116
6.6 MultivariateSynchronization 118
6.7 ComovementofCycles 119
6.8 Conclusion 121
7 Accounting for Observed Cycle Features with
a Range of Statistical Models 122
7.1 Introduction 122
7.2 U.S.CyclesasaBenchmark 123
7.3 TheBusinessCycleinaRangeofCountries 129
7.4 CanU.S.BusinessCyclesBeGeneratedby
LinearModels? 129
7.5 WhatDoNon-LinearModelsAdd? 132
7.6 TwoMarkovSwitchingModels 137
7.7 UsingtheBinaryIndicatorsinMultivariate
Systems 138
7.8 Conclusion 142
8 Using the Recurrent Event Binary States to
Examine Economic Modeling Issues 143
8.1 Introduction 143
8.2 EstimatingUnivariateModelswith
ConstructedBinaryData 145
8.3 WhatDoVarianceDecompositionsTellUs
AbouttheCycle? 150
8.4 TheRoleofStructuralShocksin
DeterminingCycleFeatures 152
8.5 FinancialEffectsandtheBusinessCycle 154
8.6 Conclusion 161
9 Predicting Turning Points and Recessions 163
9.1 Introduction 163
9.2 BoundingtheProbabilityoftheOccurrence
ofaPeak 166
9.3 PredictingRecessionswithaRangeof
Variables 168
viii (cid:127) Contents
9.4 ChangingtheEventDefiningRecessions
andTurningPoints 182
9.5 Conclusion 184
References 187
Index 205
Series Editors’ Introduction
The Econometric and Tinbergen Institutes Lectures series
deals with topics in econometrics with important policy
implications. The lectures cover a wide range of topics and
are not confined to any one area or sub-discipline. Leading
international scientists in the fields of econometrics in which
applications play a major role are invited to give three-
day lectures on a topic to which they have contributed
significantly.
Recurrent events come in many forms ranging from busi-
ness and financial cycles to crises, and they occur in almost
all economic systems whether they are capitalist or more
centrally planned or whether they are developed or less de-
veloped.Datingbusiness-cyclefeaturesiscrucialforaccurate
forecastingandoptimalpolicyanalysis.
ThepresentbookwrittenbyDonHardingandAdrianPagan
aims and succeeds at such a description. At the most basic
level, recurrent events are summarized by binary indicators
that are constructed either directly from data or indirectly by
models. The book is fully transparent in both analytical and
descriptive approaches to these topics. It provides excellent
tools for detailed empirical analysis of many business cycle
featureswhichusersthemselvescanexplore.
All results presented are novel and unquestionably useful
for academic researchers as well as professionals in the
internationalbankingandgovernmentsectors.
The editors of the series are indebted to the Tinbergen
Instituteforcontinuedsupport.
HermanK.vanDijkandPhilipHansFranses
EconometricandTinbergenInstitutes
ErasmusSchoolofEconomics