Security of Supply and Greenhouse Gas Abatement

198 Pages·2013·2.5 MB·English

Essays on the Economics of
Energy Markets
-
Security of Supply and Greenhouse Gas Abatement
Inauguraldissertation
zur
Erlangung des Doktorgrades
der
Wirtschafts- und Sozialwissenschaftlichen Fakult¨at
der
Universita¨t zu Ko¨ln
2012
vorgelegt
von
Diplom-Volkswirtin, CEMS-MIM Caroline Dieckho¨ner
aus
Langenfeld (Rhld.)

Referent: Prof. Dr. Felix H¨offler
Korreferent: PD. Dr. Christian Growitsch
Tag der Promotion: 01.02.2013

Contents
List of Figures ix
List of Tables xi
Abbreviations xiii
1 Introduction 1
1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Some conceptual foundations . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2.1 Normative security of supply analyses . . . . . . . . . . . . . . . . 3
1.2.1.1 The TIGER model . . . . . . . . . . . . . . . . . . . . . . 4
1.2.1.2 Assumptions and caveats of TIGER . . . . . . . . . . . . 7
1.2.2 Positive analyses of consumer choices using microsimulation and
econometrics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
1.2.2.1 Discrete Choice Heat Market Simulation Model . . . . . 9
1.2.2.2 Assumptions and caveats of DIscrHEat . . . . . . . . . . 13
1.2.2.3 Differences-in-differences-in-differences approach (DDD) . 14
1.2.2.4 Assumptions and caveats of DDD . . . . . . . . . . . . . 17
1.3 Thesis outline and contributions . . . . . . . . . . . . . . . . . . . . . . . 18
1.3.1 Security of supply effects of the Nabucco and
South Stream projects . . . . . . . . . . . . . . . . . . . . . . . . . 18
1.3.2 Civil unrests in North Africa – Risks for natural gas supply? . . . 19
1.3.3 Greenhouse gas abatement curves of the residential
heating market . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
1.3.4 Subsidizing investments in energy efficiency . . . . . . . . . . . . . 20
I Model-based Analyses of Security of Supply in Natural Gas Mar-
kets 21
2 SimulatingsecurityofsupplyoftheNabuccoandSouthStreamprojects
for the European natural gas market 23
2.1 Introduction and Background . . . . . . . . . . . . . . . . . . . . . . . . . 23
2.2 Security of natural gas supply and the Nabucco and the South Stream
pipeline projects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
2.2.1 Security of natural gas supply . . . . . . . . . . . . . . . . . . . . . 25
2.2.2 The Nabucco project . . . . . . . . . . . . . . . . . . . . . . . . . . 26
v
vi CONTENTS
2.2.3 The South Stream project . . . . . . . . . . . . . . . . . . . . . . . 27
2.3 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
2.3.1 The TIGER-model . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
2.3.2 Data assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
2.3.3 Scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
2.4 Results of no-crisis simulation for 2020 . . . . . . . . . . . . . . . . . . . . 34
2.4.1 Baseline Scenario results of no-crisis simulation . . . . . . . . . . . 34
2.4.2 Nabucco and South Stream Scenario results of no-crisis simulation 37
2.5 Results of Ukraine crisis simulation for 2020 . . . . . . . . . . . . . . . . . 38
2.5.1 Baseline Scenario results of Ukraine crisis simulation . . . . . . . . 38
2.5.2 Nabucco and South Stream Scenario results of Ukraine crisis sim-
ulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
2.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
3 Civil unrest in North Africa – Risks for natural gas supply? 47
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
3.2 Security of European natural gas supply and political stability of supplier
countries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
3.3 Libyan gas export disruption in 2011 . . . . . . . . . . . . . . . . . . . . . 52
3.4 Model-based analysis of potential future disruptions . . . . . . . . . . . . 55
3.5 Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
3.5.1 Diversion of gas flows . . . . . . . . . . . . . . . . . . . . . . . . . 57
3.5.2 Demand curtailment . . . . . . . . . . . . . . . . . . . . . . . . . . 60
3.5.3 Price effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
3.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
II ConsumerChoices, EnergyEfficiencyandGreenhouseGasAbate-
ment Policies 67
4 Greenhouse gas abatement curves of the residential heating market –
a microeconomic approach 69
4.1 Introduction and Background . . . . . . . . . . . . . . . . . . . . . . . . . 69
4.2 Previous research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
4.3 Theoretical approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
4.4 Data and Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
4.4.1 Microsimulation using DIscrHEat . . . . . . . . . . . . . . . . . . . 84
4.4.2 Policy scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
4.5 Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
4.5.1 Greenhouse gas abatement policies and diffusion of heating systems 86
4.5.2 Welfare analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
4.5.3 Welfare-based greenhouse gas abatement curves . . . . . . . . . . . 93
4.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
5 Does subsidizing investments in energy efficiency reduce energy con-
sumption? Evidence from Germany 97
5.1 Introduction and Background . . . . . . . . . . . . . . . . . . . . . . . . . 97
5.2 Literature overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
CONTENTS vii
5.3 Hypotheses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
5.4 Data and descriptive statistics. . . . . . . . . . . . . . . . . . . . . . . . . 105
5.4.1 Sources and variables . . . . . . . . . . . . . . . . . . . . . . . . . 105
5.4.2 Heating expenditure and dwelling modernization . . . . . . . . . . 109
5.5 Estimation Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
5.5.1 Number of investments in energy efficiency . . . . . . . . . . . . . 114
5.5.2 Heating energy expenditures . . . . . . . . . . . . . . . . . . . . . 115
5.6 Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117
5.6.1 Impacts on dwelling modernizations . . . . . . . . . . . . . . . . . 117
5.6.1.1 Impacts of socio-economic and dwelling characteristics . . 118
5.6.1.2 Impacts of subsidies and ownership status . . . . . . . . . 119
5.6.2 Impacts on heating energy consumption . . . . . . . . . . . . . . . 120
5.6.2.1 Impacts of socio-economic and dwelling characteristics . . 121
5.6.2.2 Impacts of ownership status and modernizations during
subsidy periods. . . . . . . . . . . . . . . . . . . . . . . . 125
5.7 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128
A Supplementary Material to Chapters 2 and 3 131
A.1 Main equations of the TIGER model . . . . . . . . . . . . . . . . . . . . . 131
A.2 Model versions applied in Chapters 2 and 3 . . . . . . . . . . . . . . . . . 135
A.3 Parameterization and data sources . . . . . . . . . . . . . . . . . . . . . . 135
B Supplementary Material to Chapter 4 137
B.1 Assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137
B.1.1 Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137
B.2 Discrete choice model - welfare measurement and tests . . . . . . . . . . . 146
C Supplementary Material to Chapter 5 155
C.1 Theoretical framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155
C.1.1 The energy efficiency gap . . . . . . . . . . . . . . . . . . . . . . . 158
C.1.2 Lump-sum subsidies for investments in energy efficiency . . . . . . 158
C.1.3 Subsidies on interest rates of investments in energy efficiency . . . 159
C.1.4 Investment barriers in tenant-occupied dwellings . . . . . . . . . . 161
C.1.5 Subsidies, the heterogeneity of households and information as-
symetries of policy makers . . . . . . . . . . . . . . . . . . . . . . . 162
C.2 Summary statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164
C.3 Subsidy programs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165
Bibliography 167

List of Figures
1.1 TIGER model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.2 Duality and cost minimization . . . . . . . . . . . . . . . . . . . . . . . . 5
1.3 DIscrHEat model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
1.4 Compensating variation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.1 TIGER-model composition . . . . . . . . . . . . . . . . . . . . . . . . . . 31
2.2 Supply mix in 2020 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
2.3 Withdrawal of gas volumes along the route . . . . . . . . . . . . . . . . . 38
2.4 Differencesregardingsupplyvolumesbetweencrisis-andno-crisissimulation 43
3.1 Worldwide Governance Indicators . . . . . . . . . . . . . . . . . . . . . . . 50
3.2 Italian pipeline imports January to April 2011. . . . . . . . . . . . . . . . 54
3.3 Modeled infrastructure elements in Europe . . . . . . . . . . . . . . . . . 56
3.4 Gas flow changes Maghreb 1 year disruption vs. Reference Scenario. . . . 60
3.5 Modeled price effects in selected countries from pipeline disruptions . . . 64
4.1 Tax rate, subsidy level and resulting greenhouse gas abatement . . . . . . 87
4.2 Tax revenue and subsidy expenditure . . . . . . . . . . . . . . . . . . . . . 88
4.3 Installed heating systems in 2030 depending on CO reduction and policy
2
measures. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
4.4 Tax, subsidy and excess burdens depending on CO reduction based . . . 91
2
4.5 Marginal and average cost of public funds per CO abatement level . . . . 92
2
4.6 Marginal excess burden of greenhouse gas reduction . . . . . . . . . . . . 93
5.1 Average subsidies per state . . . . . . . . . . . . . . . . . . . . . . . . . . 109
5.2 Percentage of households with owners or tenants in Western Germany . . 110
5.3 Heating expenditure and gas price development . . . . . . . . . . . . . . . 111
5.4 Averagesubsidypaymentsfordifferenttreatmentperiodsandrealheating
expenditure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
5.5 BoxplotsofdisposablemonthlyincomeinEurosforhouseholdswithown-
ers or tenants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
5.6 Estimation strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
5.7 Treatment effect on real heating expenditures in Euros per m2 . . . . . . 128
B.1 Data: Costsandfrequencyofenergycarriersinstalledindifferentdwellings
in 2010 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146
ix