Advanced robust and nonparametric methods in efficiency analysis: methodology and applications

260 Pages·2007·3.551 MB·English

by  Cinzia Daraio

A R
DVANCED OBUST
N M
AND ONPARAMETRIC ETHODS
E A
IN FFICIENCY NALYSIS
METHODOLOGY AND APPLICATIONS
Studies in Productivity and Efficiency

Series Editors:

Rolf Färe
Shawna Grosskopf
Oregon State University
R. Robert Russell
University of California, Riverside

Books in the series:

Fox, Kevin J.:
Efficiency in the Public Sector
Ball, V. Eldon and Norton, George W.:
Agricultural Productivity:
Measurement and Sources of Growth
Färe, Rolf and Grosskopf, Shawna:
New Directions:
Efficiency and Productivity
Daraio, C. and Simar, L.:
Advanced Robust and Nonparametric Methods in Efficiency Analysis:
Methodology and Applications
A R
DVANCED OBUST
N M
AND ONPARAMETRIC ETHODS
E A
IN FFICIENCY NALYSIS
METHODOLOGY AND APPLICATIONS
by
Cinzia Daraio
Institute of Informatics and Telematics (CNR), Pisa
and
Department of Electrical Systems and Automation,
School of Engineering, University of Pisa

Léopold Simar
Institute of Statistics
Université Catholique de Lovain, Louvain la Neuve, Belgium
123
Library of Congress Control Number: 2006927067
ISBN-10: 0-387-35155-8 e-ISBN 0-387-35231-7
ISBN-13: 978-0387-35155-1 e-ISBN-13: 978-0387-35231-1
Printed on acid-free paper.
© 2007 Springer Science+Business Media, LLC
All rights reserved. This work may not be translated or copied in whole or in part without the written
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Printed in the United States of America.
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Contents
v
Dedication
xi
ListofFigures
xv
ListofTables
Preface xvii
Acknowledgments xxi
1. INTRODUCTION 1
1.1 Whatthisworkisabout 1
1.2 Improvingthenonparametricapproachinfrontieranalysis 4
1.3 Anoutlineofthework 8
PartI Methodology
2. THEMEASUREMENTOFEFFICIENCY 13
2.1 ProductivityandEfficiency 13
2.2 Ashorthistoryofthought 16
2.3 Theeconomicmodel 19
2.4 Ataxonomyofefficientfrontiermodels 25
2.5 Thenonparametricfrontierapproach 30
2.5.1 DataEnvelopmentAnalysis(DEA) 31
2.5.2 FreeDisposalHull(FDH) 33
2.6 Recentdevelopmentsinnonparametricefficiencyanalysis 39
3. STATISTICALINFERENCEINNONPARAMETRIC
FRONTIERESTIMATION 43
3.1 Statisticalfoundation 43
3.2 Introducingstochasticnoiseinthemodel 45
viii Contents
3.3 Asymptoticresults 47
3.3.1 Consistency 47
3.3.2 Samplingdistributions 49
3.4 Bootstraptechniquesandapplications 50
3.4.1 Bootstrapinfrontiermodels 52
3.4.2 Correctingthebias 54
3.4.3 Bootstrapconfidenceintervals 55
3.4.4 Isthebootstrapconsistent? 56
3.4.5 Applicationsofthebootstrap 63
3.4.6 BootstrappingFDHestimators 64
4. NONPARAMETRICROBUSTESTIMATORS:
PARTIALFRONTIERS 65
4.1 Are-formulationbasedontheprobabilityofbeingdominated 66
4.2 Order-mfrontiersandefficiencyscores 68
4.3 Order-αquantile-typefrontiers 72
4.4 Propertiesofpartialfrontierestimators 77
4.4.1 Statisticalproperties 77
4.4.2 Robustestimatorsofthefullfrontier 77
4.4.3 Advantagesofusingpartialfrontiers 78
4.4.4 Detectionofoutliers 79
4.5 Summaryoftheresultsfortheoutputorientedcase 81
4.6 Parametricapproximationsofrobustnonparametricfrontiers 85
4.6.1 Twostagemethods 87
4.6.2 Thebootstrapalgorithms 89
4.7 Multivariateparametricapproximations 90
4.7.1 GeneralizedCobb-Douglasparametricmodel 91
4.7.2 Translogparametricmodel 93
5. CONDITIONALMEASURESOFEFFICIENCY 95
5.1 Explainingefficiencyintheliterature 96
5.2 Introducingexternal-environmentalvariables 100
5.2.1 Conditionalfullfrontiermeasures 100
5.2.2 Conditionalorder-mmeasures 101
5.2.3 Conditionalorder-αmeasures 103
5.2.4 Summaryfortheoutputorientedcase 105
5.3 Bandwidthselection 108
5.3.1 Univariatecase 109
5.3.2 Multivariatecase 110
Contents ix
5.4 Aneconometricmethodology 113
5.4.1 GlobaleffectofZ ontheproductionprocess 113
5.4.2 Adecompositionofconditionalefficiency 119
5.5 Simulatedillustrations 121
5.5.1 UnivariateZ 122
5.5.2 MultivariateZ 124
PartII Applications
6. ECONOMIES OF SCALE, SCOPE AND EXPERIENCE
IN THEITALIANMOTOR-VEHICLESECTOR 135
6.1 Introduction 135
6.2 Datadescription 139
6.2.1 Definitionofoutputsandinputs 142
6.2.2 Anexploratoryinvestigation 145
6.2.3 Aggregationofinputsandoutputs 148
6.3 Testingreturnstoscaleandbootstrappingefficiencyscores 151
6.4 Economiesofscale 157
6.5 Economiesofscope 160
6.6 Economiesofexperience 163
6.7 Conclusions 164
7. AGE, SCALE AND CONCENTRATION EFFECTS
IN A PUBLICRESEARCHSYSTEM 167
7.1 Introduction 167
7.2 Datadescription 176
7.3 Scaleandconcentrationeffects 178
7.4 AgeeffectsonCNRscientificproductivity 181
7.5 Robustparametricapproximationofmultioutput
distancefunction 186
7.6 Conclusions 191
8. EXPLORINGTHEEFFECTSOFMANAGERTENURE,FUND
AGEANDTHEIRINTERACTION 193
8.1 Introduction 193
8.2 Datadescription 196
8.3 Impactofmutualfundmanagertenureonperformance 199
8.4 Interactionbetweenmanagertenureandfundage 208
x Contents
8.5 Conclusions 216
9. CONCLUSIONS 217
References 221
TopicIndex 243
AuthorIndex 245
List of Figures
2.1 Anoverviewoftheliteratureonefficientfrontierestimation. 27
2.2 InputandOutputslacks. 33
2.3 FDHandDEAestimationofC(y)and∂C(y). 36
2.4 FDHandDEAestimationofP(x)and∂P(x). 36
2.5 Influenceofoutliers. 38
4.1 Inputorder-mfrontierinthebivariatecase. 69
4.2 Inputorder-αfrontierinthebivariatecase. 73
input
4.3 An illustration of α measure of efficiency in the
bivariatecase. 76
4.4 Illustrationoffullandpartialfrontiersintheinputorientation. 76
4.5 Illustrationoffullandpartialfrontiersintheoutputorientation. 85
5.1 TheBoilercase. Z favorable. 116
5.2 TheFridgecase. Z unfavorable. 118
5.3 TheFridgecasewithoutliers. Fullfrontiercase 119
5.4 TheFridgecasewithoutliers. Partialfrontierscase 119
5.5 Simulated example with univariate Z. Likelihood CV
criterion. 123
5.6 SimulatedexamplewithunivariateZ. Plotsofthepercentages.123
5.7 Simulated example with univariate Z. Smoothed non-
parametricplots. 125
5.8 Simulated example with multivariate Z. Likelihood
crossvalidationplot. 126
5.9 DensityofZ anditsContourplot. 127
5.10 Simulated example with multivariate Z. Plots of the
percentageofpointsoutsidepartialfrontiers. 128