Table Of ContentAPPLICATIONSOFSIMULATION METHODS IN
ENVIRONMENTALAND RESOURCE ECONOMICS
THE ECONOMICSOF NON-MARKETGOODS AND RESOURCES
VOLUME6
Series Editor: Dr. Ian J. Bateman
Dr. Ian J. Bateman is Professor of Environmental Economics at the School of
Environmental Sciences, University of East Anglia (UEA) and directs the research
theme Innovation in Decision Support (Tools and Methods) within the Programme on
Environmental Decision Making (PEDM) at the Centre for Social and Economic
Research on the Global Environment (CSERGE), UEA. The PEDM is funded by the UK
Economic and Social Research Council. Professor Bateman is also a member of the
Centre for the Economic and Behavioural Analysis of Risk and Decision (CEBARD) at
UEAand Executive Editor of Environmental and Resource Economics, an international
journal published in cooperation with the European Association of Environmental and
Resource Economists. (EAERE).
Aims and Scope
The volumes which comprise The Economics of Non-Market Goods and Resources
series have been specially commissioned to bring a new perspective to the greatest
st
economic challenge facing society in the 21 Century; the successful incorporation of
non-market goods within economic decision making. Only by addressing the
complexity of the underlying issues raised by such a task can society hope to redirect
global economies onto paths of sustainable development. To this end the series
combines and contrasts perspectives from environmental, ecological and resource
economics and contains a variety of volumes which will appeal to students, researchers,
and decision makers at a range of expertise levels. The series will initially address two
themes, the first examining the ways in which economists assess the value of non-
market goods, the second looking at approaches to the sustainable use and management
of such goods. These will be supplemented with further texts examining the
fundamental theoretical and applied problems raised by public good decision making.
For further information about the series and how to order, please visit our Website
www.springeronline.com
Applications of Simulation
Methods in Environmental and
Resource Economics
Edited by
Riccardo Scarpa
University of York, U.K.,
and University of Waikato,
New Zealand
and
Anna Alberini
University of Maryland, U.S.A.
AC.I.P. Catalogue record for this book is available from the Library of Congress.
ISBN-10 1-4020-3683-3 (HB)
ISBN-13 978-1-4020-3683-5 (HB)
ISBN-10 1-4020-3684-1 (e-book)
ISBN-13 978-1-4020-3684-2 (e-book)
Published by Springer,
P.O. Box 17, 3300 AADordrecht, The Netherlands.
www.springeronline.com
Printed on acid-free paper
All Rights Reserved
© 2005 Springer
No part of this work may be reproduced, stored in a retrieval system, or transmitted
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Printed in the Netherlands.
Thisvolumeisdedicatedto
ourrespectivepartnersand
immediatefamily.
Contents
Dedication v
ListofFigures xv
ListofTables xvii
ContributingAuthors xxi
Foreword xxv
Acknowledgments xxvii
Introduction xxix
AnnaAlberiniandRiccardoScarpa
1. Backgroundandmotivation xxix
2. Heterogeneityindiscretechoicemodels xxx
3. Bayesianapplications xxxii
4. Simulationmethodsindynamicmodels xxxiii
5. MonteCarloexperiments xxxiv
6. Computationalaspects xxxv
7. Terminology xxxvi
1
Discrete Choice ModelsinPreferenceSpaceandWilling-to-paySpace 1
KennethTrainandMelvynWeeks
1. Introduction 2
2. Specification 4
3. Data 6
4. Estimation 7
4.1 Uncorrelatedcoefficientsinpreferencespace 7
4.2 UncorrelatedWTP’sinWTPspace 11
4.3 CorrelatedcoefficientsandWTP 14
5. Conclusions 16
2
Using Classical Simulation-Based Estimators to Estimate Individual WTP Values 17
WilliamH.Greene,DavidA.HensherandJohnM.Rose
1. Introduction 18
vii
viii APPLICATIONSOFSIMULATIONMETHODS
2. TheBayesianapproach 19
3. TheMixedLogitModel 21
4. AnEmpiricalExample 24
4.1 StatedChoiceExperimentalDesign 25
4.2 Findings 27
4.3 WTPDerivedfromIndividualParameters 30
4.4 WTPDerivedfromPopulationMoments 31
5. Conclusions 32
3
IntheCostofPowerOutages to Heterogeneous Households 35
DavidF.LaytonandKlausMoeltner
1. Introduction 36
2. ApproachestoEstimatingResidentialOutageCosts 37
3. TheEconometricModel 39
4. EmpiricalAnalysis 42
4.1 Data 42
4.2 ModelEstimation 43
4.3 OutageAttributes 45
4.4 HouseholdCharacteristics 48
4.5 PastOutageHistory 48
4.6 CovarianceParameters 51
4.7 ComparisonwithPreviousEstimates 51
5. DiscussionandConclusion 53
4
CapturingCorrelationandTasteHeterogeneitywithMixedGEVModels 55
StephaneHess,MichelBierlaire,JohnW.Polak
1. Introduction 56
2. Methodology 57
2.1 Closed-formGEVmodels 58
2.2 MixedGEVmodels 59
3. Empiricalanalysis 62
3.1 Multinomiallogitmodel 65
3.2 NestedLogitmodel 65
3.3 Cross-NestedLogitmodel 65
3.4 MixedMultinomialLogitmodel 68
3.5 MixedNestedLogitmodel 71
3.6 MixedCross-NestedLogitmodel 72
4. SummaryandConclusions 73
5
AnalysisofAgri-EnvironmentalPaymentPrograms 77
JosephCooper
1. Introduction 77
2. TheTheoreticalModel 79
3. EconometricModel 80
Contents ix
4. NumericalIllustration 84
5. Conclusion 94
6
A Comparison between MultinomialLogitandProbitModels 97
AndreasZiegler
1. Introduction 98
2. MethodologicalApproachandVariables 99
2.1 BackgroundonDeterminantsofEnvironmentalPerformance 99
2.2 MultinomialDiscreteChoiceModels 100
2.3 DependentandExplanatoryVariables 103
3. Data 105
4. Results 106
4.1 MultinomialLogitandIndependentProbitAnalysis 106
4.2 FlexibleMultinomialProbitAnalysis 108
5. Conclusions 115
7
MixedLogitwithBoundedDistributionsofCorrelatedPartworths 117
KennethTrainandGarrettSonnier
1. Introduction 118
2. Mixedlogitwithnormallydistributedpartworths 121
3. Transformationofnormals 124
4. Application 125
4.1 Choiceexperiments 126
4.2 Models 127
8
Kuhn-TuckerDemandSystemApproachestoNon-MarketValuation 135
RogerH.vonHaefen,DanielJ.Phaneuf
1. Introduction 136
2. Modelingframeworkandchallenges 137
vi 3. Empiricalspecificationsandimplementationstrategies 140
3.1 Fixedandrandomparameterclassicalestimationapproaches 141
3.2 RandomparameterBayesianestimationapproaches 144
3.3 Welfareanalysis 146
3.4 Simulatingtheunobservedheterogeneity 147
3.5 CalculatingCSH 148
3.6 Ourwelfarecalculationapproach: arestatement 151
4. Empiricalillustration 151
5. Results 153
5.1 Parameterestimates 153
5.2 Welfareestimates 155
6. Discussion 156
9
HierarchicalAnalysisofProductionEfficiency 159
in a Coastal Trawl Fishery
x APPLICATIONSOFSIMULATIONMETHODS
GarthHolloway,DavidTomberlin,XavierIrz
1. Introduction 160
2. Coastalfisheriesefficiencymeasurement 163
2.1 Whymeasuretechnicalefficiencyinfisheries? 163
2.2 ModellingTechnicalEfficiency 163
2.3 Whathavewelearned? 166
3. Bayesiancomposederrormodeldevelopment 168
3.1 Composed Error Frontier Model With Exponential Ineffi-
ciency 169
3.2 Gibbssamplingthecomposederrormodel 171
3.3 Composed-errormodelscomparison 175
3.4 Truncated-normal,paneldataestimation 177
3.5 Estimationinatwo-layerhierarchy 179
4. EmpiricalevidencefromthePacificCoastGroundfishFishery 180
5. Data 182
6. Results 183
7. ConclusionsandExtensions 184
10
BayesianApproachestoModelingStatedPreffferenceData 187
DavidF.LaytonandRichardA.Levine
1. Introduction 188
2. TheEconometricModelandBayesianEstimationApproach 189
2.1 ModelSpecification 190
2.2 BayesianEstimation 191
2.3 ModelComparisonandMarginalLikelihoodComputation 194
3. TheStatedPreferenceDataSets 196
4. Results 197
5. Conclusion 203
6. AppendixA 204
7. AppendixB 205
11
Bayesian Estimation of Dichotomous Choice Contingent Valuation with Follow-up 209
JJJorrgeE.Arrran˜a,CarmeloJJJ.Leo´n
1. Introduction 210
2. Modeling 211
3. Applicationandresults 215
4. Conclusions 220
5. Appendix 221
12
ModelingElicitationEffffectsinContingentVVValuationStudies 223
MargaritaGeniusandElisabettaStrazzera
1. Introduction 223
