Regulation and Energy Supply Security

Michael Schmidthaler

Johannes Kepler University Linz

July 12, 2012

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Table of Contents - Structure of the presentation

1 Introduction, Research Questions and MethodologyResearch Motivation on Energy Supply Security / RegulationComparison of Regulatory Regimes’ EffectivenessEconomic Valuation of uninterrupted Power Supply

2 Results, Policy Recommendation and SummaryRegulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

3 Appendix (if time allows)Outage Case Study in Austria assessed with APOSTELEconometric Modeling of WTPData Availability - Analysis of Regulation’s Effectiveness

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 1

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Research Motivation on Energy Supply Security / RegulationComparison of Regulatory Regimes’ EffectivenessEconomic Valuation of uninterrupted Power Supply

Research Goals and Methodology

Goal I: Investigation of regulatory effectiveness with regard toelectricity supply security (ESS) ⇒ fixed effect/random effectmodel (Cross-country time series using data augmentation)

Goal II: Elicitation of firms’ outage costs (value-addedmodel) and households’ WTP to avoid power cuts (CVM).Energy policy ⇒ Assessment Model APOSTEL

Goal III: Understanding the interdependence of

ValueESS - LevelESS - Regulatory Regimes

Providing an evidence for benefit-cost analyses,regulatory decision and macroeconomic valuations ofESS,...

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 2

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Research Motivation on Energy Supply Security / RegulationComparison of Regulatory Regimes’ EffectivenessEconomic Valuation of uninterrupted Power Supply

Research Goals and Methodology

Goal I: Investigation of regulatory effectiveness with regard toelectricity supply security (ESS) ⇒ fixed effect/random effectmodel (Cross-country time series using data augmentation)

Goal II: Elicitation of firms’ outage costs (value-addedmodel) and households’ WTP to avoid power cuts (CVM).Energy policy ⇒ Assessment Model APOSTEL

Goal III: Understanding the interdependence of

ValueESS - LevelESS - Regulatory Regimes

Providing an evidence for benefit-cost analyses,regulatory decision and macroeconomic valuations ofESS,...

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 2

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Research Motivation on Energy Supply Security / RegulationComparison of Regulatory Regimes’ EffectivenessEconomic Valuation of uninterrupted Power Supply

Research Goals and Methodology

Goal I: Investigation of regulatory effectiveness with regard toelectricity supply security (ESS) ⇒ fixed effect/random effectmodel (Cross-country time series using data augmentation)

Goal II: Elicitation of firms’ outage costs (value-addedmodel) and households’ WTP to avoid power cuts (CVM).Energy policy ⇒ Assessment Model APOSTEL

Goal III: Understanding the interdependence of

ValueESS - LevelESS - Regulatory Regimes

Providing an evidence for benefit-cost analyses,regulatory decision and macroeconomic valuations ofESS,...

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 2

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Research Motivation on Energy Supply Security / RegulationComparison of Regulatory Regimes’ EffectivenessEconomic Valuation of uninterrupted Power Supply

Research Goals and Methodology

Goal I: Investigation of regulatory effectiveness with regard toelectricity supply security (ESS) ⇒ fixed effect/random effectmodel (Cross-country time series using data augmentation)

Goal II: Elicitation of firms’ outage costs (value-addedmodel) and households’ WTP to avoid power cuts (CVM).Energy policy ⇒ Assessment Model APOSTEL

Goal III: Understanding the interdependence of

ValueESS - LevelESS - Regulatory Regimes

Providing an evidence for benefit-cost analyses,regulatory decision and macroeconomic valuations ofESS,...

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 2

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Research Motivation on Energy Supply Security / RegulationComparison of Regulatory Regimes’ EffectivenessEconomic Valuation of uninterrupted Power Supply

Approach to assess Regulation in Terms of Reliability

Stepwise process (Categorization of regulatory regimes⇒Inclusion of control variables⇒Estimation of effectiveness)

ex ante: Choice of analytical methods is essential

- Cross-country for best-practise evaluation- Time series in order to account for system inertia

Effects on ESS: Regulation’s welfare implications

⇒ Aiming at providing efficient level of ESS

Policy Recommendation for future regulatory regimes ⇒E.g EU-wide implementation of quality standards in electricitymarket regulation if macroeconomically efficient

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 3

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Research Motivation on Energy Supply Security / RegulationComparison of Regulatory Regimes’ EffectivenessEconomic Valuation of uninterrupted Power Supply

Approach to assess Regulation in Terms of Reliability

Stepwise process (Categorization of regulatory regimes⇒Inclusion of control variables⇒Estimation of effectiveness)

ex ante: Choice of analytical methods is essential

- Cross-country for best-practise evaluation- Time series in order to account for system inertia

Effects on ESS: Regulation’s welfare implications

⇒ Aiming at providing efficient level of ESS

Policy Recommendation for future regulatory regimes ⇒E.g EU-wide implementation of quality standards in electricitymarket regulation if macroeconomically efficient

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 3

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Research Motivation on Energy Supply Security / RegulationComparison of Regulatory Regimes’ EffectivenessEconomic Valuation of uninterrupted Power Supply

Approach to assess Regulation in Terms of Reliability

Stepwise process (Categorization of regulatory regimes⇒Inclusion of control variables⇒Estimation of effectiveness)

ex ante: Choice of analytical methods is essential

- Cross-country for best-practise evaluation- Time series in order to account for system inertia

Effects on ESS: Regulation’s welfare implications

⇒ Aiming at providing efficient level of ESS

Policy Recommendation for future regulatory regimes ⇒E.g EU-wide implementation of quality standards in electricitymarket regulation if macroeconomically efficient

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 3

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Research Motivation on Energy Supply Security / RegulationComparison of Regulatory Regimes’ EffectivenessEconomic Valuation of uninterrupted Power Supply

Approach to assess Regulation in Terms of Reliability

Stepwise process (Categorization of regulatory regimes⇒Inclusion of control variables⇒Estimation of effectiveness)

ex ante: Choice of analytical methods is essential

- Cross-country for best-practise evaluation- Time series in order to account for system inertia

Effects on ESS: Regulation’s welfare implications

⇒ Aiming at providing efficient level of ESS

Policy Recommendation for future regulatory regimes ⇒E.g EU-wide implementation of quality standards in electricitymarket regulation if macroeconomically efficient

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 3

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Research Motivation on Energy Supply Security / RegulationComparison of Regulatory Regimes’ EffectivenessEconomic Valuation of uninterrupted Power Supply

Approach to assess Regulation in Terms of Reliability

Stepwise process (Categorization of regulatory regimes⇒Inclusion of control variables⇒Estimation of effectiveness)

ex ante: Choice of analytical methods is essential

- Cross-country for best-practise evaluation- Time series in order to account for system inertia

Effects on ESS: Regulation’s welfare implications

⇒ Aiming at providing efficient level of ESS

Policy Recommendation for future regulatory regimes ⇒E.g EU-wide implementation of quality standards in electricitymarket regulation if macroeconomically efficient

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 3

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Research Motivation on Energy Supply Security / RegulationComparison of Regulatory Regimes’ EffectivenessEconomic Valuation of uninterrupted Power Supply

Approach to assess Regulation in Terms of Reliability

Stepwise process (Categorization of regulatory regimes⇒Inclusion of control variables⇒Estimation of effectiveness)

ex ante: Choice of analytical methods is essential

- Cross-country for best-practise evaluation- Time series in order to account for system inertia

Effects on ESS: Regulation’s welfare implications

⇒ Aiming at providing efficient level of ESS

Policy Recommendation for future regulatory regimes ⇒E.g EU-wide implementation of quality standards in electricitymarket regulation if macroeconomically efficient

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 3

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Research Motivation on Energy Supply Security / RegulationComparison of Regulatory Regimes’ EffectivenessEconomic Valuation of uninterrupted Power Supply

Approach to assess Regulation in Terms of Reliability

Stepwise process (Categorization of regulatory regimes⇒Inclusion of control variables⇒Estimation of effectiveness)

ex ante: Choice of analytical methods is essential

- Cross-country for best-practise evaluation- Time series in order to account for system inertia

Effects on ESS: Regulation’s welfare implications

⇒ Aiming at providing efficient level of ESS

Policy Recommendation for future regulatory regimes ⇒E.g EU-wide implementation of quality standards in electricitymarket regulation if macroeconomically efficient

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 3

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Research Motivation on Energy Supply Security / RegulationComparison of Regulatory Regimes’ EffectivenessEconomic Valuation of uninterrupted Power Supply

Macroeconomic Assessment of ESS’ Value

Combined approach and macroeconomic aggregation

Non-Households (businesses, public institutions & entities)

- Assessment of outage costs (OC) based on disaggregatedadded-value data and synthetic demand load profiles

- Online survey (n ≈ 300) to assess businesses’ productionprocesses, dependencies, time aspects and vulnerabilities

Households: Utility-based Model

- WTP elicitation (n ≈ 1, 300) using discrete choice model- Contingent valuation (CVM): WTP to avoid power outages

⇒ Aggregating the social costs of power cuts: APOSTEL- Austrian Power Outage Simulation Tool of Economic Losses- VBA-based outage assessment GUI (available at EI website))

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 4

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Research Motivation on Energy Supply Security / RegulationComparison of Regulatory Regimes’ EffectivenessEconomic Valuation of uninterrupted Power Supply

Macroeconomic Assessment of ESS’ Value

Combined approach and macroeconomic aggregation

Non-Households (businesses, public institutions & entities)

- Assessment of outage costs (OC) based on disaggregatedadded-value data and synthetic demand load profiles

- Online survey (n ≈ 300) to assess businesses’ productionprocesses, dependencies, time aspects and vulnerabilities

Households: Utility-based Model

- WTP elicitation (n ≈ 1, 300) using discrete choice model- Contingent valuation (CVM): WTP to avoid power outages

⇒ Aggregating the social costs of power cuts: APOSTEL- Austrian Power Outage Simulation Tool of Economic Losses- VBA-based outage assessment GUI (available at EI website))

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 4

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Research Motivation on Energy Supply Security / RegulationComparison of Regulatory Regimes’ EffectivenessEconomic Valuation of uninterrupted Power Supply

Macroeconomic Assessment of ESS’ Value

Combined approach and macroeconomic aggregation

Non-Households (businesses, public institutions & entities)

- Assessment of outage costs (OC) based on disaggregatedadded-value data and synthetic demand load profiles

- Online survey (n ≈ 300) to assess businesses’ productionprocesses, dependencies, time aspects and vulnerabilities

Households: Utility-based Model

- WTP elicitation (n ≈ 1, 300) using discrete choice model- Contingent valuation (CVM): WTP to avoid power outages

⇒ Aggregating the social costs of power cuts: APOSTEL- Austrian Power Outage Simulation Tool of Economic Losses- VBA-based outage assessment GUI (available at EI website))

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 4

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Research Motivation on Energy Supply Security / RegulationComparison of Regulatory Regimes’ EffectivenessEconomic Valuation of uninterrupted Power Supply

Macroeconomic Assessment of ESS’ Value

Combined approach and macroeconomic aggregation

Non-Households (businesses, public institutions & entities)

- Assessment of outage costs (OC) based on disaggregatedadded-value data and synthetic demand load profiles

- Online survey (n ≈ 300) to assess businesses’ productionprocesses, dependencies, time aspects and vulnerabilities

Households: Utility-based Model

- WTP elicitation (n ≈ 1, 300) using discrete choice model- Contingent valuation (CVM): WTP to avoid power outages

⇒ Aggregating the social costs of power cuts: APOSTEL- Austrian Power Outage Simulation Tool of Economic Losses- VBA-based outage assessment GUI (available at EI website))

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 4

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Research Motivation on Energy Supply Security / RegulationComparison of Regulatory Regimes’ EffectivenessEconomic Valuation of uninterrupted Power Supply

Macroeconomic Assessment of ESS’ Value

Combined approach and macroeconomic aggregation

Non-Households (businesses, public institutions & entities)

- Assessment of outage costs (OC) based on disaggregatedadded-value data and synthetic demand load profiles

- Online survey (n ≈ 300) to assess businesses’ productionprocesses, dependencies, time aspects and vulnerabilities

Households: Utility-based Model

- WTP elicitation (n ≈ 1, 300) using discrete choice model- Contingent valuation (CVM): WTP to avoid power outages

⇒ Aggregating the social costs of power cuts: APOSTEL- Austrian Power Outage Simulation Tool of Economic Losses- VBA-based outage assessment GUI (available at EI website))

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 4

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Research Motivation on Energy Supply Security / RegulationComparison of Regulatory Regimes’ EffectivenessEconomic Valuation of uninterrupted Power Supply

Macroeconomic Assessment of ESS’ Value

Combined approach and macroeconomic aggregation

Non-Households (businesses, public institutions & entities)

- Assessment of outage costs (OC) based on disaggregatedadded-value data and synthetic demand load profiles

- Online survey (n ≈ 300) to assess businesses’ productionprocesses, dependencies, time aspects and vulnerabilities

Households: Utility-based Model

- WTP elicitation (n ≈ 1, 300) using discrete choice model- Contingent valuation (CVM): WTP to avoid power outages

⇒ Aggregating the social costs of power cuts: APOSTEL- Austrian Power Outage Simulation Tool of Economic Losses- VBA-based outage assessment GUI (available at EI website))

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 4

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Research Motivation on Energy Supply Security / RegulationComparison of Regulatory Regimes’ EffectivenessEconomic Valuation of uninterrupted Power Supply

Macroeconomic Assessment of ESS’ Value

Combined approach and macroeconomic aggregation

Non-Households (businesses, public institutions & entities)

- Assessment of outage costs (OC) based on disaggregatedadded-value data and synthetic demand load profiles

- Online survey (n ≈ 300) to assess businesses’ productionprocesses, dependencies, time aspects and vulnerabilities

Households: Utility-based Model

- WTP elicitation (n ≈ 1, 300) using discrete choice model- Contingent valuation (CVM): WTP to avoid power outages

⇒ Aggregating the social costs of power cuts: APOSTEL- Austrian Power Outage Simulation Tool of Economic Losses- VBA-based outage assessment GUI (available at EI website))

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 4

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Research Motivation on Energy Supply Security / RegulationComparison of Regulatory Regimes’ EffectivenessEconomic Valuation of uninterrupted Power Supply

Macroeconomic Assessment of ESS’ Value

Combined approach and macroeconomic aggregation

Non-Households (businesses, public institutions & entities)

- Assessment of outage costs (OC) based on disaggregatedadded-value data and synthetic demand load profiles

- Online survey (n ≈ 300) to assess businesses’ productionprocesses, dependencies, time aspects and vulnerabilities

Households: Utility-based Model

- WTP elicitation (n ≈ 1, 300) using discrete choice model- Contingent valuation (CVM): WTP to avoid power outages

⇒ Aggregating the social costs of power cuts: APOSTEL- Austrian Power Outage Simulation Tool of Economic Losses- VBA-based outage assessment GUI (available at EI website))

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 4

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Research Motivation on Energy Supply Security / RegulationComparison of Regulatory Regimes’ EffectivenessEconomic Valuation of uninterrupted Power Supply

Macroeconomic Assessment of ESS’ Value

Combined approach and macroeconomic aggregation

Non-Households (businesses, public institutions & entities)

- Assessment of outage costs (OC) based on disaggregatedadded-value data and synthetic demand load profiles

- Online survey (n ≈ 300) to assess businesses’ productionprocesses, dependencies, time aspects and vulnerabilities

Households: Utility-based Model

- WTP elicitation (n ≈ 1, 300) using discrete choice model- Contingent valuation (CVM): WTP to avoid power outages

⇒ Aggregating the social costs of power cuts: APOSTEL- Austrian Power Outage Simulation Tool of Economic Losses- VBA-based outage assessment GUI (available at EI website))

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 4

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Results of ESS and Regulation Assessment

This section contains:

Presentation of Regulatory Regression approach

Comparison of different regression models - Coefficients forWTP to avoid power outages

Summary, Policy recommendation and Synthesis

Power outage case study with APOSTEL, if time allows

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 5

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Results of ESS and Regulation Assessment

This section contains:

Presentation of Regulatory Regression approach

Comparison of different regression models - Coefficients forWTP to avoid power outages

Summary, Policy recommendation and Synthesis

Power outage case study with APOSTEL, if time allows

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 5

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Results of ESS and Regulation Assessment

This section contains:

Presentation of Regulatory Regression approach

Comparison of different regression models - Coefficients forWTP to avoid power outages

Summary, Policy recommendation and Synthesis

Power outage case study with APOSTEL, if time allows

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 5

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Results of ESS and Regulation Assessment

This section contains:

Presentation of Regulatory Regression approach

Comparison of different regression models - Coefficients forWTP to avoid power outages

Summary, Policy recommendation and Synthesis

Power outage case study with APOSTEL, if time allows

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 5

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Presentation of Work in Progress: Basic Ideas

We estimate the effects of regulatory regimes on reliabilitystandards (SAIDI, CAIDI, SAIFI)

We do so by applying RE and FE estimation methods

Utilizing panel data accounts for different regulatory regimesand market structures

Crucial: Categorization and inclusion of control variables

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 6

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Presentation of Work in Progress: Basic Ideas

We estimate the effects of regulatory regimes on reliabilitystandards (SAIDI, CAIDI, SAIFI)

We do so by applying RE and FE estimation methods

Utilizing panel data accounts for different regulatory regimesand market structures

Crucial: Categorization and inclusion of control variables

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 6

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Presentation of Work in Progress: Basic Ideas

We estimate the effects of regulatory regimes on reliabilitystandards (SAIDI, CAIDI, SAIFI)

We do so by applying RE and FE estimation methods

Utilizing panel data accounts for different regulatory regimesand market structures

Crucial: Categorization and inclusion of control variables

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 6

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Presentation of Work in Progress: Research

First evidence indicates higher reliability in the presence ofquality regulation (basic OLS w/o data augmentation)

Model choice appropriate in terms of exogenous factors

Currently: Categorization of regulatory regimes in EU 27

No regulationRate-of-Return regulationCost based regulation (without any kind of quality regulation)

Yardstick/benchmarking regulationPrice cap regulationProfit sharing, banded rate-of-return and menus

Incentive regulation incl. quality measures or integratedincentive quality regulation

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 7

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Presentation of Work in Progress: Research

First evidence indicates higher reliability in the presence ofquality regulation (basic OLS w/o data augmentation)

Model choice appropriate in terms of exogenous factors

Currently: Categorization of regulatory regimes in EU 27

No regulationRate-of-Return regulationCost based regulation (without any kind of quality regulation)

Yardstick/benchmarking regulationPrice cap regulationProfit sharing, banded rate-of-return and menus

Incentive regulation incl. quality measures or integratedincentive quality regulation

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 7

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Presentation of Work in Progress: Research

First evidence indicates higher reliability in the presence ofquality regulation (basic OLS w/o data augmentation)

Model choice appropriate in terms of exogenous factors

Currently: Categorization of regulatory regimes in EU 27

No regulationRate-of-Return regulationCost based regulation (without any kind of quality regulation)

Yardstick/benchmarking regulationPrice cap regulationProfit sharing, banded rate-of-return and menus

Incentive regulation incl. quality measures or integratedincentive quality regulation

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 7

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Presentation of Work in Progress: Research

First evidence indicates higher reliability in the presence ofquality regulation (basic OLS w/o data augmentation)

Model choice appropriate in terms of exogenous factors

Currently: Categorization of regulatory regimes in EU 27

No regulationRate-of-Return regulationCost based regulation (without any kind of quality regulation)

Yardstick/benchmarking regulationPrice cap regulationProfit sharing, banded rate-of-return and menus

Incentive regulation incl. quality measures or integratedincentive quality regulation

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 7

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Presentation of Work in Progress: Research

First evidence indicates higher reliability in the presence ofquality regulation (basic OLS w/o data augmentation)

Model choice appropriate in terms of exogenous factors

Currently: Categorization of regulatory regimes in EU 27

No regulationRate-of-Return regulationCost based regulation (without any kind of quality regulation)

Yardstick/benchmarking regulationPrice cap regulationProfit sharing, banded rate-of-return and menus

Incentive regulation incl. quality measures or integratedincentive quality regulation

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 7

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Presentation of Work in Progress: Research

First evidence indicates higher reliability in the presence ofquality regulation (basic OLS w/o data augmentation)

Model choice appropriate in terms of exogenous factors

Currently: Categorization of regulatory regimes in EU 27

No regulationRate-of-Return regulationCost based regulation (without any kind of quality regulation)

Yardstick/benchmarking regulationPrice cap regulationProfit sharing, banded rate-of-return and menus

Incentive regulation incl. quality measures or integratedincentive quality regulation

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 7

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Presentation of Work in Progress: Research

First evidence indicates higher reliability in the presence ofquality regulation (basic OLS w/o data augmentation)

Model choice appropriate in terms of exogenous factors

Currently: Categorization of regulatory regimes in EU 27

No regulationRate-of-Return regulationCost based regulation (without any kind of quality regulation)

Yardstick/benchmarking regulationPrice cap regulationProfit sharing, banded rate-of-return and menus

Incentive regulation incl. quality measures or integratedincentive quality regulation

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 7

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Presentation of Work in Progress: Research

First evidence indicates higher reliability in the presence ofquality regulation (basic OLS w/o data augmentation)

Model choice appropriate in terms of exogenous factors

Currently: Categorization of regulatory regimes in EU 27

No regulationRate-of-Return regulationCost based regulation (without any kind of quality regulation)

Yardstick/benchmarking regulationPrice cap regulationProfit sharing, banded rate-of-return and menus

Incentive regulation incl. quality measures or integratedincentive quality regulation

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 7

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Presentation of Work in Progress: Research

First evidence indicates higher reliability in the presence ofquality regulation (basic OLS w/o data augmentation)

Model choice appropriate in terms of exogenous factors

Currently: Categorization of regulatory regimes in EU 27

No regulationRate-of-Return regulationCost based regulation (without any kind of quality regulation)

Yardstick/benchmarking regulationPrice cap regulationProfit sharing, banded rate-of-return and menus

Incentive regulation incl. quality measures or integratedincentive quality regulation

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 7

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Presentation of Work in Progress: Research

First evidence indicates higher reliability in the presence ofquality regulation (basic OLS w/o data augmentation)

Model choice appropriate in terms of exogenous factors

Currently: Categorization of regulatory regimes in EU 27

No regulationRate-of-Return regulationCost based regulation (without any kind of quality regulation)

Yardstick/benchmarking regulationPrice cap regulationProfit sharing, banded rate-of-return and menus

Incentive regulation incl. quality measures or integratedincentive quality regulation

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 7

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Economic theory for the quantification of WTP

Goal: Elicitation of Maximum WTP (≥ 0) i is willing to pay

Observable in utility differences between scenarios O and NO

Utility differences: depend on the state of power supply

UNO

= XdNOβdNO

+ XbNOβbNO

+ Xuβbu (1)

UO

= XdOβdO + XbOβbO + Xuβbu (2)

Abbreviation Description Changes (NO vs O) i ’s choice

NO. . . Scenario ,,No Outage” UNOi,,1”

O. . . Scenario ,,Outage” UOi,,0”

βb. . . Marginal Utility of Income (Xb) Changes –βd . . . Marginal Utility of Outage (Xd ) Changes –βbu . . . MU of other goods (Xu) Constant –

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 8

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Economic theory for the quantification of WTP

Goal: Elicitation of Maximum WTP (≥ 0) i is willing to pay

Observable in utility differences between scenarios O and NO

Utility differences: depend on the state of power supply

UNO

= XdNOβdNO

+ XbNOβbNO

+ Xuβbu (1)

UO

= XdOβdO + XbOβbO + Xuβbu (2)

Abbreviation Description Changes (NO vs O) i ’s choice

NO. . . Scenario ,,No Outage” UNOi,,1”

O. . . Scenario ,,Outage” UOi,,0”

βb. . . Marginal Utility of Income (Xb) Changes –βd . . . Marginal Utility of Outage (Xd ) Changes –βbu . . . MU of other goods (Xu) Constant –

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 8

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Economic theory for the quantification of WTP

Goal: Elicitation of Maximum WTP (≥ 0) i is willing to pay

Observable in utility differences between scenarios O and NO

Utility differences: depend on the state of power supply

UNO

= XdNOβdNO

+ XbNOβbNO

+ Xuβbu (1)

UO

= XdOβdO + XbOβbO + Xuβbu (2)

Abbreviation Description Changes (NO vs O) i ’s choice

NO. . . Scenario ,,No Outage” UNOi,,1”

O. . . Scenario ,,Outage” UOi,,0”

βb. . . Marginal Utility of Income (Xb) Changes –βd . . . Marginal Utility of Outage (Xd ) Changes –βbu . . . MU of other goods (Xu) Constant –

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 8

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Economic theory for the quantification of WTP

Goal: Elicitation of Maximum WTP (≥ 0) i is willing to pay

Observable in utility differences between scenarios O and NO

Utility differences: depend on the state of power supply

UNO

= XdNOβdNO

+ XbNOβbNO

+ Xuβbu (1)

UO

= XdOβdO + XbOβbO + Xuβbu (2)

Abbreviation Description Changes (NO vs O) i ’s choice

NO. . . Scenario ,,No Outage” UNOi,,1”

O. . . Scenario ,,Outage” UOi,,0”

βb. . . Marginal Utility of Income (Xb) Changes –βd . . . Marginal Utility of Outage (Xd ) Changes –βbu . . . MU of other goods (Xu) Constant –

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 8

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Economic theory for the quantification of WTP

Goal: Elicitation of Maximum WTP (≥ 0) i is willing to pay

Observable in utility differences between scenarios O and NO

Utility differences: depend on the state of power supply

UNO

= XdNOβdNO

+ XbNOβbNO

+ Xuβbu (1)

UO

= XdOβdO + XbOβbO + Xuβbu (2)

Abbreviation Description Changes (NO vs O) i ’s choice

NO. . . Scenario ,,No Outage” UNOi,,1”

O. . . Scenario ,,Outage” UOi,,0”

βb. . . Marginal Utility of Income (Xb) Changes –βd . . . Marginal Utility of Outage (Xd ) Changes –βbu . . . MU of other goods (Xu) Constant –

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 8

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Households’ WTP Elicitation in the Utility Model

Scenario, If choice=,,1”: i chooses to pay WTP instead ofexperiencing a defined blackout with properties XdO⇒WTP to prevent outages reduces income by ∆YWTP

Inserting in (1) yields precondition for choice to be ,,1”:

UNO−∆UYWTP

≥ UO

(3)

boundary solution in : UNO−∆UYWTP

= UO

∆UYWTP. . . Utility change of income effect (↓) since WTP≥0

XdNOβdNO + (XbNO−WTP)βbNO = XdOβdO + XbOβbO

XdNOβdNO + XbNOβbNO −WTPβbNO = (·) + (·)(4)

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 9

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Households’ WTP Elicitation in the Utility Model

Scenario, If choice=,,1”: i chooses to pay WTP instead ofexperiencing a defined blackout with properties XdO⇒WTP to prevent outages reduces income by ∆YWTP

Inserting in (1) yields precondition for choice to be ,,1”:

UNO−∆UYWTP

≥ UO

(3)

boundary solution in : UNO−∆UYWTP

= UO

∆UYWTP. . . Utility change of income effect (↓) since WTP≥0

XdNOβdNO + (XbNO−WTP)βbNO = XdOβdO + XbOβbO

XdNOβdNO + XbNOβbNO −WTPβbNO = (·) + (·)(4)

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 9

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Households’ WTP Elicitation in the Utility Model

Scenario, If choice=,,1”: i chooses to pay WTP instead ofexperiencing a defined blackout with properties XdO⇒WTP to prevent outages reduces income by ∆YWTP

Inserting in (1) yields precondition for choice to be ,,1”:

UNO−∆UYWTP

≥ UO

(3)

boundary solution in : UNO−∆UYWTP

= UO

∆UYWTP. . . Utility change of income effect (↓) since WTP≥0

XdNOβdNO + (XbNO−WTP)βbNO = XdOβdO + XbOβbO

XdNOβdNO + XbNOβbNO −WTPβbNO = (·) + (·)(4)

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 9

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Households’ WTP Elicitation in the Utility Model

Scenario, If choice=,,1”: i chooses to pay WTP instead ofexperiencing a defined blackout with properties XdO⇒WTP to prevent outages reduces income by ∆YWTP

Inserting in (1) yields precondition for choice to be ,,1”:

UNO−∆UYWTP

≥ UO

(3)

boundary solution in : UNO−∆UYWTP

= UO

∆UYWTP. . . Utility change of income effect (↓) since WTP≥0

XdNOβdNO + (XbNO−WTP)βbNO = XdOβdO + XbOβbO

XdNOβdNO + XbNOβbNO −WTPβbNO = (·) + (·)(4)

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 9

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Households’ WTP Elicitation in the Utility Model

Scenario, If choice=,,1”: i chooses to pay WTP instead ofexperiencing a defined blackout with properties XdO⇒WTP to prevent outages reduces income by ∆YWTP

Inserting in (1) yields precondition for choice to be ,,1”:

UNO−∆UYWTP

≥ UO

(3)

boundary solution in : UNO−∆UYWTP

= UO

∆UYWTP. . . Utility change of income effect (↓) since WTP≥0

XdNOβdNO + (XbNO −WTP)βbNO= XdOβdO + XbOβbO

XdNOβdNO + XbNOβbNO −WTPβbNO = (·) + (·)(4)

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 9

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Households’ WTP Elicitation in the Utility Model

Scenario, If choice=,,1”: i chooses to pay WTP instead ofexperiencing a defined blackout with properties XdO⇒WTP to prevent outages reduces income by ∆YWTP

Inserting in (1) yields precondition for choice to be ,,1”:

UNO−∆UYWTP

≥ UO

(3)

boundary solution in : UNO−∆UYWTP

= UO

∆UYWTP. . . Utility change of income effect (↓) since WTP≥0

XdNOβdNO + (XbNO −WTP)βbNO= XdOβdO + XbOβbO

XdNOβdNO + XbNOβbNO −WTPβbNO = (·) + (·)(4)

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 9

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

CVM Empiric Evidence: Variables and Distribution inSample

Coefficient Coding Description of binary and metric coefficients Mean

natural 1 if the outage cause is a natural event, 0 if terrorism 0.49f2f 1 if the interview was done face-to-face, 0 if online 0.54

incent 1 if the respondent was promised 10 EUR for 0.68– the participation of the survey (already in recruiting) –

extent 1 if the power outage affects 3 province, 0 if neighborhood 0.50premo 1 if outage was announced (3 days), 0 if spontaneous 0.50winter 1 if the scenario takes place in winter, 0 if in summer 0.50laborT 1 if the failure is in the labor-leisure affected only if 0 0.50

sex 1 if male person answering, 0 if female 0.58experience 1 if participant has experienced power outages (≥ 4h) 0.28education 1 if the participant graduated from high school (Matura) 0.60

children 1 if children under 14 reside in the household 0.22age – the age of the survey participant (metric) 40.54city 1 if the household lies in a municipality with more 0.47

– than 10,000 inhabitants, household in urban area –income – household income in 100 EUR (metric) 23.11

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 10

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

RE Probit Coefficient Estimate Std. error t value Pr(> t) Sign

Intercept -1.42638382 0.19001276 -7.5068 0.00 ***f2f 0.10057017 0.10936286 0.9196 0.36

natural 0.07021704 0.06880141 1.0206 0.31incent -0.15095134 0.11752698 -1.2844 0.20extent 0.28916645 0.02951186 9.7983 < 2.2e-16 ***premo -0.10496562 0.02841273 -3.6943 0.00 ***winter 0.26149553 0.02899686 9.0181 < 2.2e-16 ***laborT 0.00867449 0.02852292 0.3041 0.76

h24 0.56945631 0.03050187 18.6696 < 2.2e-16 ***h12 0.29317765 0.0298255 9.8298 < 2.2e-16 ***

h4 0.14384599 0.03042072 4.7286 0.00 ***h1 0.04191215 0.03336475 1.2562 0.21

bid -0.01946734 0.00099969 -19.4734 < 2.2e-16 ***sex 0.00547088 0.00731818 0.7476 0.45

experience 0.04311205 0.07734068 0.5574 0.58education 0.02852567 0.08409955 0.3392 0.73

children -0.04701296 0.08687405 -0.5412 0.59age 0.00107608 0.00288677 0.3728 0.71city 0.16433608 0.07239785 2.2699 0.02 *

income 0.01018531 0.00341052 2.9864 0.00 **

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 11

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Interpretation of Results: Random Effect - Probit II

Model Quality: Random Effect Probit

Estimation using probit including intercept, 11 iteration

log-likelihood: -7532.70

AIC: 15089.4

⇒ Exclusion of insignificant variables does NOT improvemodel quality

⇒ Utilization of R-E Probitoriginal for WTP quantification

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 12

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Interpretation of Results: Random Effect - Probit II

Model Quality: Random Effect Probit

Estimation using probit including intercept, 11 iteration

log-likelihood: -7532.70

AIC: 15089.4

⇒ Exclusion of insignificant variables does NOT improvemodel quality

⇒ Utilization of R-E Probitoriginal for WTP quantification

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 12

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Interpretation of Results: Random Effect - Probit II

Model Quality: Random Effect Probit

Estimation using probit including intercept, 11 iteration

log-likelihood: -7532.70

AIC: 15089.4

⇒ Exclusion of insignificant variables does NOT improvemodel quality

⇒ Utilization of R-E Probitoriginal for WTP quantification

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 12

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Interpretation of Results: Random Effect - Probit II

Model Quality: Random Effect Probit

Estimation using probit including intercept, 11 iteration

log-likelihood: -7532.70

AIC: 15089.4

⇒ Exclusion of insignificant variables does NOT improvemodel quality

⇒ Utilization of R-E Probitoriginal for WTP quantification

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 12

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Interpretation of Results: Random Effect - Probit II

Model Quality: Random Effect Probit

Estimation using probit including intercept, 11 iteration

log-likelihood: -7532.70

AIC: 15089.4

⇒ Exclusion of insignificant variables does NOT improvemodel quality

⇒ Utilization of R-E Probitoriginal for WTP quantification

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 12

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Interpretation of Results: Random Effect - Probit II

Model Quality: Random Effect Probit

Estimation using probit including intercept, 11 iteration

log-likelihood: -7532.70

AIC: 15089.4

⇒ Exclusion of insignificant variables does NOT improvemodel quality

⇒ Utilization of R-E Probitoriginal for WTP quantification

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 12

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Interpretation of WTP Results - Random Effect Probit

Households’ WTP for outage prevention (24h, 12h, 4h & 1h)Following (7) (McFadden,19961), we get:

Random Effect Probit Quotient WTP in EURO

-h24/bid 29.25-h12/bid 15.06

-h4/bid 7.39-h1/bid 2.15

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 13

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Comparison of WTP Results with International Approaches

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� Austria, WTAopen

× Woo, USA1991� Sweden, planned

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Bliem, 2007

Figure: Comparison of different ESS valuation approachesMichael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 14

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Implementation of WTP and outage cost assessment inAPOSTEL

Economic evaluation of simulated outages on the sector andprovince level

Possible to identify especially vulnerable sectors

Valuation of the non-market good ESS important forregulation.

Next steps: Assessment of all 27 EU countries in FP7 project(6,750 households)

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 15

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Implementation of WTP and outage cost assessment inAPOSTEL

Economic evaluation of simulated outages on the sector andprovince level

Possible to identify especially vulnerable sectors

Valuation of the non-market good ESS important forregulation.

Next steps: Assessment of all 27 EU countries in FP7 project(6,750 households)

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 15

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Implementation of WTP and outage cost assessment inAPOSTEL

Economic evaluation of simulated outages on the sector andprovince level

Possible to identify especially vulnerable sectors

Valuation of the non-market good ESS important forregulation.

Next steps: Assessment of all 27 EU countries in FP7 project(6,750 households)

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 15

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Implementation of WTP and outage cost assessment inAPOSTEL

Economic evaluation of simulated outages on the sector andprovince level

Possible to identify especially vulnerable sectors

Valuation of the non-market good ESS important forregulation.

Next steps: Assessment of all 27 EU countries in FP7 project(6,750 households)

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 15

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Synthesis, Summary of main Findings

Different ESS valuation models applied ⇒ Similar Results!!

Regulatory science benefits from ESS research and vice versa.⇒ Exchange and Discussion highly appreciated

Depending on the outage attributes, total costs of a 10hBlackout in Austria are calculated to be ∼ ¿500 Mio.

Value Of Lost Load (VOLL) for a power cut of 1h on asummer workday morning is EUR 17.1/kWh.

Future: Cross-country assessments in the EU needed

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 16

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Synthesis, Summary of main Findings

Different ESS valuation models applied ⇒ Similar Results!!

Regulatory science benefits from ESS research and vice versa.⇒ Exchange and Discussion highly appreciated

Depending on the outage attributes, total costs of a 10hBlackout in Austria are calculated to be ∼ ¿500 Mio.

Value Of Lost Load (VOLL) for a power cut of 1h on asummer workday morning is EUR 17.1/kWh.

Future: Cross-country assessments in the EU needed

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 16

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Synthesis, Summary of main Findings

Different ESS valuation models applied ⇒ Similar Results!!

Regulatory science benefits from ESS research and vice versa.⇒ Exchange and Discussion highly appreciated

Depending on the outage attributes, total costs of a 10hBlackout in Austria are calculated to be ∼ ¿500 Mio.

Value Of Lost Load (VOLL) for a power cut of 1h on asummer workday morning is EUR 17.1/kWh.

Future: Cross-country assessments in the EU needed

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 16

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Synthesis, Summary of main Findings

Different ESS valuation models applied ⇒ Similar Results!!

Regulatory science benefits from ESS research and vice versa.⇒ Exchange and Discussion highly appreciated

Depending on the outage attributes, total costs of a 10hBlackout in Austria are calculated to be ∼ ¿500 Mio.

Value Of Lost Load (VOLL) for a power cut of 1h on asummer workday morning is EUR 17.1/kWh.

Future: Cross-country assessments in the EU needed

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 16

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Synthesis, Summary of main Findings

Different ESS valuation models applied ⇒ Similar Results!!

Regulatory science benefits from ESS research and vice versa.⇒ Exchange and Discussion highly appreciated

Depending on the outage attributes, total costs of a 10hBlackout in Austria are calculated to be ∼ ¿500 Mio.

Value Of Lost Load (VOLL) for a power cut of 1h on asummer workday morning is EUR 17.1/kWh.

Future: Cross-country assessments in the EU needed

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 16

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Regulatory Effectiveness - Cross-country Time SeriesHouseholds’ WTP-Estimation - Econometric ESS ModelSummary and Conclusion

Thank you for your attention

Case Study with APOSTEL? Time?

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 17

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Outage Case Study in Austria assessed with APOSTELEconometric Modeling of WTPData Availability - Analysis of Regulation’s Effectiveness

APOSTEL entry page: provision of outage details

APOSTEL allows to simulate power outage scenarios inAustria

Table 1: Properties of the analyzed power supply interruptions

The day the power outage occurs is a workday..

Upper Austria

5

10:00

Date check

Duration of power supply interruption (in hours)

Regional scale of the power outage (state level)

Date of outage start

Starting time of power supply interruption

23.01.2012

Figure: APOSTEL entry page - Information

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 18

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Outage Case Study in Austria assessed with APOSTELEconometric Modeling of WTPData Availability - Analysis of Regulation’s Effectiveness

Table 2a: Sector Assessment of Supply Security for a power outage with the previously defined attributes

Sector Code according to ÖNACE 2008

Sector

Number of adversely or very adversely affected companies

Number of employees in adversely or very adversely affected companies

Energy not supplied (in MWh)

A Agriculture, hunting and forestry 34,930 99,121 159 792

B Mining and quarrying 60 982 106 75

C Manufacturing 5,151 154,470 5,191 23,471

D Electricity, gas, steam and air conditioning supply 265 3,290 1,029 959

E Water supply; sewerage; waste managment and remediation activities 381 3,220 15 278

F Construction 4,467 46,911 59 4,507

G Wholesale and retail trade; repair of motor vehicles and motorcycles 11,115 97,136 262 14,301

H Transporting and storage 1,845 21,727 340 2,104

I Accommodation and food service activities 4,960 25,375 36 927

J Information and communication 1,666 8,544 33 756

K Financial and insurance activities 890 13,084 99 1,631

L Real estate activities 1,781 5,545 59 1,095

M Professional, scientific and technical activities 6,500 27,052 120 2,545

N Administrative and support service activities 1,350 32,440 90 1,635

OPQRSTU

Public administration and defence; compulsory social security, Education, Human health and

social work activities , Arts, entertainment and recreation, Other services activities.

* 128,878 488 5,231

Sum 75,360 ** 667,775 ** 8,085 ** 60,307 **

Table 2b: Sector Assessment of Supply Security for a power outage with the previously defined attributes

Sector Code according to ÖNACE 2008

Sector Value of Lost Load (in €/kWh)

Hourly damage (in 1,000 €)

A Agriculture, hunting and forestry 5.0 158

B Mining and quarrying 0.7 15

C Manufacturing 4.5 4,694

D Electricity, gas, steam and air conditioning supply 0.9 192

E Water supply; sewerage; waste managment and remediation activities 18.7 56

F Construction 76.6 901

G Wholesale and retail trade; repair of motor vehicles and motorcycles 54.7 2,860

H Transporting and storage 6.2 421

I Accommodation and food service activities 25.6 185

J Information and communication 23.2 151

K Financial and insurance activities 16.4 326

L Real estate activities 18.4 219

M Professional, scientific and technical activities 21.2 509

N Administrative and support service activities 18.1 327

OPQRSTU

Public administration and defence; compulsory social security, Education, Human health and

social work activities , Arts, entertainment and recreation, Other services activities

10.7 1,046

Sum 7.5 *** 12,061 ** ***

*** Weighted average of columns

24.9

* In the public sector it is impossible to quantify the number of entities affected using the same nomenclature as in the private sector.

Total damage (in 1,000 €)

1.6

** Sum of Columns

17.3

7.3

15.2

30.4

58.3

8.1

39.5

17.7

Hourly damage per employee in €

19.2

29.4

19.4

18.1

18.8

10.1

** Sum of Columns

2 / 4

Figure: APOSTEL - affected sectors

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 19

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Outage Case Study in Austria assessed with APOSTELEconometric Modeling of WTPData Availability - Analysis of Regulation’s Effectiveness

Table 2a: Sector Assessment of Supply Security for a power outage with the previously defined attributes

Sector Code according to ÖNACE 2008

Sector

Number of adversely or very adversely affected companies

Number of employees in adversely or very adversely affected companies

Energy not supplied (in MWh)

A Agriculture, hunting and forestry 34,930 99,121 159 792

B Mining and quarrying 60 982 106 75

C Manufacturing 5,151 154,470 5,191 23,471

D Electricity, gas, steam and air conditioning supply 265 3,290 1,029 959

E Water supply; sewerage; waste managment and remediation activities 381 3,220 15 278

F Construction 4,467 46,911 59 4,507

G Wholesale and retail trade; repair of motor vehicles and motorcycles 11,115 97,136 262 14,301

H Transporting and storage 1,845 21,727 340 2,104

I Accommodation and food service activities 4,960 25,375 36 927

J Information and communication 1,666 8,544 33 756

K Financial and insurance activities 890 13,084 99 1,631

L Real estate activities 1,781 5,545 59 1,095

M Professional, scientific and technical activities 6,500 27,052 120 2,545

N Administrative and support service activities 1,350 32,440 90 1,635

OPQRSTU

Public administration and defence; compulsory social security, Education, Human health and

social work activities , Arts, entertainment and recreation, Other services activities.

* 128,878 488 5,231

Sum 75,360 ** 667,775 ** 8,085 ** 60,307 **

Table 2b: Sector Assessment of Supply Security for a power outage with the previously defined attributes

Sector Code according to ÖNACE 2008

Sector Value of Lost Load (in €/kWh)

Hourly damage (in 1,000 €)

A Agriculture, hunting and forestry 5.0 158

B Mining and quarrying 0.7 15

C Manufacturing 4.5 4,694

D Electricity, gas, steam and air conditioning supply 0.9 192

E Water supply; sewerage; waste managment and remediation activities 18.7 56

F Construction 76.6 901

G Wholesale and retail trade; repair of motor vehicles and motorcycles 54.7 2,860

H Transporting and storage 6.2 421

I Accommodation and food service activities 25.6 185

J Information and communication 23.2 151

K Financial and insurance activities 16.4 326

L Real estate activities 18.4 219

M Professional, scientific and technical activities 21.2 509

N Administrative and support service activities 18.1 327

OPQRSTU

Public administration and defence; compulsory social security, Education, Human health and

social work activities , Arts, entertainment and recreation, Other services activities

10.7 1,046

Sum 7.5 *** 12,061 ** ***

*** Weighted average of columns

24.9

* In the public sector it is impossible to quantify the number of entities affected using the same nomenclature as in the private sector.

Total damage (in 1,000 €)

1.6

** Sum of Columns

17.3

7.3

15.2

30.4

58.3

8.1

39.5

17.7

Hourly damage per employee in €

19.2

29.4

19.4

18.1

18.8

10.1

** Sum of Columns

2 / 4

Figure: Computation of outage characteristics - Non-households

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 20

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Outage Case Study in Austria assessed with APOSTELEconometric Modeling of WTPData Availability - Analysis of Regulation’s Effectiveness

Damage per hour of outage and employee

New definition of classification figure aimed at overcomingsome drawbacks of the ,,Value of Lost Load” figure (VOLL)

Hourly damage per employ

Graph 1: The hourly damage per employee is depicted.

Table 3: Damages in the main economic sectorsSector Code according to ÖNACE 2008

Primary sector A, B

Secondary sector C, D, E, F

Tertiary sector G,H,I,J,K,L,M,N,O,P,Q,R,S,T,U

Sum

Energy not supplied to the main economic sectors Total monetary damage of the main economic sectors

Damage Assessment II : Households

Table 4: Assessments of households

583,981

1,819

Number of adversely or strongly adversely affected inhabitants

582,070

1,390,432

1.63

Energy not supplied (in MWh)

VOLL (in €/kWh)

WTP to avoid the outage (in 1,000 €) 2,968

244,469

Number of Inhabitants in the area of the outage

Number of adversely or strongly adversely affected households

6,293

867

30,225

60,307

Energy not supplied (in MwH)

Number of households in the area of the outage

8,085

Graph 3: Total monetary damage according to economic sectors

Total damage (in 1,000 Euro)

1,527

The assessment of damage occuring to households due to power outages is more difficult than for non-households. The majority of damages tohouseholds is indirect and not material or monetary as it is in the case of businesses and public administration. An adequate assessment musttherefore also incorporate the negative consequences to a household, such as diminished value of leisure and the mental stress that occurs whenthe household does not know when it will be able to receive power again. (See also the definitions in the Annex). The following values wereobtained using a willingness to pay analysis method (WTP) of roughly 1300 households. The damage assessment (including the mentionedintangible damages) was thus provided by the households themselves. Some literature sources point out that households tend to underestimatetheir willingness to pay to avoid power outages. These values are therefore to be considered a lower boundary of the actual damage.

Graph 2: Energy not supplied according to economic sectors

29,215

264

Primary sector 3.27%

Secondary sector 77.84%

Tertiary sector 18.89%

Energy not supplied to the main economic sectors

Primary sector 1.44%

Secondary sector 48.44%

Tertiary sector 50.12%

Total monetary damage of the main economic sectors

.00

10.00

20.00

30.00

40.00

50.00

60.00

70.00

A B C D E F G H I J K L M N OPQRSTU

Hourly damage per employee in EURO

3 / 4

Figure: Damage per hour of outage and employee

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 21

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Outage Case Study in Austria assessed with APOSTELEconometric Modeling of WTPData Availability - Analysis of Regulation’s Effectiveness

Distribution of monetary damages to economic sectors

Hourly damage per employ

Graph 1: The hourly damage per employee is depicted.

Table 3: Damages in the main economic sectorsSector Code according to ÖNACE 2008

Primary sector A, B

Secondary sector C, D, E, F

Tertiary sector G,H,I,J,K,L,M,N,O,P,Q,R,S,T,U

Sum

Energy not supplied to the main economic sectors Total monetary damage of the main economic sectors

Damage Assessment II : Households

Table 4: Assessments of households

583,981

1,819

Number of adversely or strongly adversely affected inhabitants

582,070

1,390,432

1.63

Energy not supplied (in MWh)

VOLL (in €/kWh)

WTP to avoid the outage (in 1,000 €) 2,968

244,469

Number of Inhabitants in the area of the outage

Number of adversely or strongly adversely affected households

6,293

867

30,225

60,307

Energy not supplied (in MwH)

Number of households in the area of the outage

8,085

Graph 3: Total monetary damage according to economic sectors

Total damage (in 1,000 Euro)

1,527

The assessment of damage occuring to households due to power outages is more difficult than for non-households. The majority of damages tohouseholds is indirect and not material or monetary as it is in the case of businesses and public administration. An adequate assessment musttherefore also incorporate the negative consequences to a household, such as diminished value of leisure and the mental stress that occurs whenthe household does not know when it will be able to receive power again. (See also the definitions in the Annex). The following values wereobtained using a willingness to pay analysis method (WTP) of roughly 1300 households. The damage assessment (including the mentionedintangible damages) was thus provided by the households themselves. Some literature sources point out that households tend to underestimatetheir willingness to pay to avoid power outages. These values are therefore to be considered a lower boundary of the actual damage.

Graph 2: Energy not supplied according to economic sectors

29,215

264

Primary sector 3.27%

Secondary sector 77.84%

Tertiary sector 18.89%

Energy not supplied to the main economic sectors

Primary sector 1.44%

Secondary sector 48.44%

Tertiary sector 50.12%

Total monetary damage of the main economic sectors

.00

10.00

20.00

30.00

40.00

50.00

60.00

70.00

A B C D E F G H I J K L M N OPQRSTU

Hourly damage per employee in EURO

3 / 4

Figure: Distribution of monetary damages to economic sectors

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 22

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Outage Case Study in Austria assessed with APOSTELEconometric Modeling of WTPData Availability - Analysis of Regulation’s Effectiveness

Assessments of households

Summary of affected households, unsupplied energy andWilligness to pay to avoid the specified outage scenario

Hourly damage per employ

Graph 1: The hourly damage per employee is depicted.

Table 3: Damages in the main economic sectorsSector Code according to ÖNACE 2008

Primary sector A, B

Secondary sector C, D, E, F

Tertiary sector G,H,I,J,K,L,M,N,O,P,Q,R,S,T,U

Sum

Energy not supplied to the main economic sectors Total monetary damage of the main economic sectors

Damage Assessment II : Households

Table 4: Assessments of households

583,981

1,819

Number of adversely or strongly adversely affected inhabitants

582,070

1,390,432

1.63

Energy not supplied (in MWh)

VOLL (in €/kWh)

WTP to avoid the outage (in 1,000 €) 2,968

244,469

Number of Inhabitants in the area of the outage

Number of adversely or strongly adversely affected households

6,293

867

30,225

60,307

Energy not supplied (in MwH)

Number of households in the area of the outage

8,085

Graph 3: Total monetary damage according to economic sectors

Total damage (in 1,000 Euro)

1,527

The assessment of damage occuring to households due to power outages is more difficult than for non-households. The majority of damages tohouseholds is indirect and not material or monetary as it is in the case of businesses and public administration. An adequate assessment musttherefore also incorporate the negative consequences to a household, such as diminished value of leisure and the mental stress that occurs whenthe household does not know when it will be able to receive power again. (See also the definitions in the Annex). The following values wereobtained using a willingness to pay analysis method (WTP) of roughly 1300 households. The damage assessment (including the mentionedintangible damages) was thus provided by the households themselves. Some literature sources point out that households tend to underestimatetheir willingness to pay to avoid power outages. These values are therefore to be considered a lower boundary of the actual damage.

Graph 2: Energy not supplied according to economic sectors

29,215

264

Primary sector 3.27%

Secondary sector 77.84%

Tertiary sector 18.89%

Energy not supplied to the main economic sectors

Primary sector 1.44%

Secondary sector 48.44%

Tertiary sector 50.12%

Total monetary damage of the main economic sectors

.00

10.00

20.00

30.00

40.00

50.00

60.00

70.00

A B C D E F G H I J K L M N OPQRSTU

Hourly damage per employee in EURO

3 / 4

Figure: Assessments of affected households

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 23

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Outage Case Study in Austria assessed with APOSTELEconometric Modeling of WTPData Availability - Analysis of Regulation’s Effectiveness

Households’ WTP Elicitation in the Utility Model II

WTP =−XdOβdO − XbOβbO + XdNO

βdNO+ XbNOβbNO

βbNO

(5)

The marginal change O to NO is of interest ⇒ XdO − XdNO = 1

Income in both states: XbNO= XbO

WTP =XdNOβdNO

− (1 + XdNO)βbO + Xb · (βbNO − βbO )

βbNO

(6)

Marginal Utility of Income in both states: βbNO = βbO2

WTP = − βdOβbNO

=̂−MUoutage

MUincome=̂−

coeffoutageempiric

coeffbidempiric

(7)

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 24

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Outage Case Study in Austria assessed with APOSTELEconometric Modeling of WTPData Availability - Analysis of Regulation’s Effectiveness

Households’ WTP Elicitation in the Utility Model II

WTP =−XdOβdO − XbOβbO + XdNO

βdNO+ XbNOβbNO

βbNO

(5)

The marginal change O to NO is of interest ⇒ XdO − XdNO = 1

Income in both states: XbNO= XbO

WTP =XdNOβdNO

− (1 + XdNO)βbO + Xb · (βbNO

− βbO )

βbNO

(6)

Marginal Utility of Income in both states: βbNO = βbO2

WTP = − βdOβbNO

=̂−MUoutage

MUincome=̂−

coeffoutageempiric

coeffbidempiric

(7)

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 24

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Outage Case Study in Austria assessed with APOSTELEconometric Modeling of WTPData Availability - Analysis of Regulation’s Effectiveness

Households’ WTP Elicitation in the Utility Model II

WTP =−XdOβdO − XbOβbO + XdNO

βdNO+ XbNOβbNO

βbNO

(5)

The marginal change O to NO is of interest ⇒ XdO − XdNO = 1

Income in both states: XbNO= XbO

WTP =XdNOβdNO − (1 + XdNO )βbO + Xb · (βbNO

− βbO )

βbNO

(6)

Marginal Utility of Income in both states: βbNO = βbO2

WTP = − βdOβbNO

=̂−MUoutage

MUincome=̂−

coeffoutageempiric

coeffbidempiric

(7)

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 24

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Outage Case Study in Austria assessed with APOSTELEconometric Modeling of WTPData Availability - Analysis of Regulation’s Effectiveness

Households’ WTP Elicitation in the Utility Model II

WTP =−XdOβdO − XbOβbO + XdNO

βdNO+ XbNOβbNO

βbNO

(5)

The marginal change O to NO is of interest ⇒ XdO − XdNO = 1

Income in both states: XbNO= XbO

WTP =XdNOβdNO − (1 + XdNO )βbO + Xb · (βbNO

− βbO )

βbNO

(6)

Marginal Utility of Income in both states: βbNO = βbO2

WTP = − βdOβbNO

=̂−MUoutage

MUincome=̂−

coeffoutageempiric

coeffbidempiric

(7)

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 24

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Outage Case Study in Austria assessed with APOSTELEconometric Modeling of WTPData Availability - Analysis of Regulation’s Effectiveness

Households’ WTP Elicitation in the Utility Model II

WTP =−XdOβdO − XbOβbO + XdNO

βdNO+ XbNOβbNO

βbNO

(5)

The marginal change O to NO is of interest ⇒ XdO − XdNO = 1

Income in both states: XbNO= XbO

WTP =XdNOβdNO − (1 + XdNO )βbO + Xb · (βbNO

− βbO )

βbNO

(6)

Marginal Utility of Income in both states: βbNO = βbO2

WTP = − βdOβbNO

=̂−MUoutage

MUincome=̂−

coeffoutageempiric

coeffbidempiric

(7)

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 24

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Outage Case Study in Austria assessed with APOSTELEconometric Modeling of WTPData Availability - Analysis of Regulation’s Effectiveness

Households’ WTP Elicitation in the Utility Model II

WTP =−XdOβdO − XbOβbO + XdNO

βdNO+ XbNOβbNO

βbNO

(5)

The marginal change O to NO is of interest ⇒ XdO − XdNO = 1

Income in both states: XbNO= XbO

WTP =XdNOβdNO − (1 + XdNO )βbO + Xb · (βbNO

− βbO )

βbNO

(6)

Marginal Utility of Income in both states: βbNO = βbO2

WTP = − βdOβbNO

=̂−MUoutage

MUincome=̂−

coeffoutageempiric

coeffbidempiric

(7)

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 24

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Outage Case Study in Austria assessed with APOSTELEconometric Modeling of WTPData Availability - Analysis of Regulation’s Effectiveness

Discrete Choice Model - Questionnaire Implementation

Scenario 1: Overnight winter power outage in three states in Austria with prior warning

Outage area: Upper Austria, Lower Austria, Salzburg

Advance warning: Yes, 3 days in advance

Time of year: from December to February

The power cut listed here will be avoided if you agree to pay the one time-fee Costs for the next 2

years

Willing to pay?

Begins: 7 p.m.

Ends: 7 p.m. 

0:00 24:00

WED THU

18:00 24:00 18:006:00 12:006:00 12:00

 

17 €

YES

NO

 

Figure: Questionnaire implementation of discrete choice options

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 25

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Outage Case Study in Austria assessed with APOSTELEconometric Modeling of WTPData Availability - Analysis of Regulation’s Effectiveness

RE Logit Coefficient Estimate Std. error t value Pr(> t) Sign

Intercept -2.2823699 0.3277952 -6.9628 3.34e − 12 ***f2f 0.1521533 0.1884263 0.8075 0.4193811

natural 0.1110282 0.1210584 0.9171 0.3590663incent -0.239923 0.2034472 -1.1793 0.2382832extent 0.471857 0.0501554 9.4079 < 2.2e − 16 ***premo -0.1794508 0.0484051 -3.7073 0.0002095 ***winter 0.4256245 0.0494761 8.6026 < 2.2e − 16 ***laborT 0.0117107 0.0486768 0.2406 0.8098806

h24 0.9315508 0.0525502 17.7269 < 2.2e − 16 ***h12 0.4776204 0.0510446 9.3569 < 2.2e − 16 ***

h4 0.2297066 0.0518396 4.4311 9.38e − 06 ***h1 0.0610742 0.0568813 1.0737 0.2829514

bid -0.0386914 0.0020765 -18.6333 < 2.2e − 16 ***sex 0.0090612 0.0146794 0.6173 0.5370558

experience 0.0699495 0.135536 0.5161 0.6057877education 0.0504243 0.148362 0.3399 0.7339521

children -0.0770311 0.1513918 -0.5088 0.6108786age -0.0022639 0.005004 -0.4524 0.6509707city 0.2683437 0.1256739 2.1352 0.0327415 *

income 0.0145896 0.0059 2.4728 0.0134055 *

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 26

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Outage Case Study in Austria assessed with APOSTELEconometric Modeling of WTPData Availability - Analysis of Regulation’s Effectiveness

Interpretation of results: Random Effect Logit

Model Quality Random Effect Logit

Estimation using R-E Logit with intercept, 10 iterations

log-likelihood: -5677.373

AIC:11396.75

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 27

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Outage Case Study in Austria assessed with APOSTELEconometric Modeling of WTPData Availability - Analysis of Regulation’s Effectiveness

Interpretation of results: Random Effect Logit

Model Quality Random Effect Logit

Estimation using R-E Logit with intercept, 10 iterations

log-likelihood: -5677.373

AIC:11396.75

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 27

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Outage Case Study in Austria assessed with APOSTELEconometric Modeling of WTPData Availability - Analysis of Regulation’s Effectiveness

Interpretation of results: Random Effect Logit

Model Quality Random Effect Logit

Estimation using R-E Logit with intercept, 10 iterations

log-likelihood: -5677.373

AIC:11396.75

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 27

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Outage Case Study in Austria assessed with APOSTELEconometric Modeling of WTPData Availability - Analysis of Regulation’s Effectiveness

Interpretation of WTP Estimation

Households’ WTP for outage prevention (24h, 12h, 4h & 1h)Following Equation (7) (see McFadden,1996), we get:

Random Effect Logit Quotient WTP in EURO (Logit)

-h24/bid 24.08-h12/bid 12.34

-h4/bid 5.94-h1/bid 1.58

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 28

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Outage Case Study in Austria assessed with APOSTELEconometric Modeling of WTPData Availability - Analysis of Regulation’s Effectiveness

Choice of Survey Format: Open-ended vs. Closed-ended

Open-ended format Closed-ended discrete choice

Advantages Easy to draft and to interpret Reduction of variationEasy to interpret (descriptive) Reduction of scope effects

helps rationalize quantitiesDisadvantages Protest/Nonsense answers Considerable effort to design

Utilization here WTP for long (48h) outages Scenario part of the studyWTA for 4h and 10h outages Discrete choice (accept/decline)

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 29

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Outage Case Study in Austria assessed with APOSTELEconometric Modeling of WTPData Availability - Analysis of Regulation’s Effectiveness

WTP Estimation using Discrete CHOICE Models (Panel)

Chosen model: Max Likelihood Estimation - Random Effect

If heterogeneity of individual exists (exogen, time constant)

Used for panel data analysis (here: well applicable!)Correlation b/w i ’s heterogeneity & explanatory variables

Option II: Bayes (comparison with Reichl, 2011)Advantage of Bayesian models (among others): relativeinterpretability of coefficient (vs. absolute changes in utility3)

Option III: Fixed effect model (Probit/Logit)⇒plannedConsistent estimators if individuals’ heterogeneity is endogenIssues with the model implementation in R (No Convergence)

Here: Random effect models (Probit & Logit)

Steps: Data prep, implementation in R, pglm-package

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 30

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Outage Case Study in Austria assessed with APOSTELEconometric Modeling of WTPData Availability - Analysis of Regulation’s Effectiveness

WTP Estimation using Discrete CHOICE Models (Panel)

Chosen model: Max Likelihood Estimation - Random Effect

If heterogeneity of individual exists (exogen, time constant)

Used for panel data analysis (here: well applicable!)Correlation b/w i ’s heterogeneity & explanatory variables

Option II: Bayes (comparison with Reichl, 2011)Advantage of Bayesian models (among others): relativeinterpretability of coefficient (vs. absolute changes in utility3)

Option III: Fixed effect model (Probit/Logit)⇒plannedConsistent estimators if individuals’ heterogeneity is endogenIssues with the model implementation in R (No Convergence)

Here: Random effect models (Probit & Logit)

Steps: Data prep, implementation in R, pglm-package

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 30

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Outage Case Study in Austria assessed with APOSTELEconometric Modeling of WTPData Availability - Analysis of Regulation’s Effectiveness

WTP Estimation using Discrete CHOICE Models (Panel)

Chosen model: Max Likelihood Estimation - Random Effect

If heterogeneity of individual exists (exogen, time constant)

Used for panel data analysis (here: well applicable!)Correlation b/w i ’s heterogeneity & explanatory variables

Option II: Bayes (comparison with Reichl, 2011)Advantage of Bayesian models (among others): relativeinterpretability of coefficient (vs. absolute changes in utility3)

Option III: Fixed effect model (Probit/Logit)⇒plannedConsistent estimators if individuals’ heterogeneity is endogenIssues with the model implementation in R (No Convergence)

Here: Random effect models (Probit & Logit)

Steps: Data prep, implementation in R, pglm-package

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 30

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Outage Case Study in Austria assessed with APOSTELEconometric Modeling of WTPData Availability - Analysis of Regulation’s Effectiveness

WTP Estimation using Discrete CHOICE Models (Panel)

Chosen model: Max Likelihood Estimation - Random Effect

If heterogeneity of individual exists (exogen, time constant)

Used for panel data analysis (here: well applicable!)Correlation b/w i ’s heterogeneity & explanatory variables

Option II: Bayes (comparison with Reichl, 2011)Advantage of Bayesian models (among others): relativeinterpretability of coefficient (vs. absolute changes in utility3)

Option III: Fixed effect model (Probit/Logit)⇒plannedConsistent estimators if individuals’ heterogeneity is endogenIssues with the model implementation in R (No Convergence)

Here: Random effect models (Probit & Logit)

Steps: Data prep, implementation in R, pglm-package

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 30

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Outage Case Study in Austria assessed with APOSTELEconometric Modeling of WTPData Availability - Analysis of Regulation’s Effectiveness

WTP Estimation using Discrete CHOICE Models (Panel)

Chosen model: Max Likelihood Estimation - Random Effect

If heterogeneity of individual exists (exogen, time constant)

Used for panel data analysis (here: well applicable!)Correlation b/w i ’s heterogeneity & explanatory variables

Option II: Bayes (comparison with Reichl, 2011)Advantage of Bayesian models (among others): relativeinterpretability of coefficient (vs. absolute changes in utility3)

Option III: Fixed effect model (Probit/Logit)⇒plannedConsistent estimators if individuals’ heterogeneity is endogenIssues with the model implementation in R (No Convergence)

Here: Random effect models (Probit & Logit)

Steps: Data prep, implementation in R, pglm-package

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 30

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Outage Case Study in Austria assessed with APOSTELEconometric Modeling of WTPData Availability - Analysis of Regulation’s Effectiveness

WTP Estimation using Discrete CHOICE Models (Panel)

Chosen model: Max Likelihood Estimation - Random Effect

If heterogeneity of individual exists (exogen, time constant)

Used for panel data analysis (here: well applicable!)Correlation b/w i ’s heterogeneity & explanatory variables

Option II: Bayes (comparison with Reichl, 2011)Advantage of Bayesian models (among others): relativeinterpretability of coefficient (vs. absolute changes in utility3)

Option III: Fixed effect model (Probit/Logit)⇒plannedConsistent estimators if individuals’ heterogeneity is endogenIssues with the model implementation in R (No Convergence)

Here: Random effect models (Probit & Logit)

Steps: Data prep, implementation in R, pglm-package

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 30

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Outage Case Study in Austria assessed with APOSTELEconometric Modeling of WTPData Availability - Analysis of Regulation’s Effectiveness

Summary of Model Comparison

Research Question Results of Model Comparison

Which model is better? AICRE−Logit > AICRE−Probit

LogLikeRE−Logit < LogLikeRE−Probit

⇒Choice Probit fits better to data (distribution)Exclusion of insign. Variables Not improving the model

Advantages of RE Probit If data is distributed evenlyAdvantages of RE Logit Applicable if outliers exist

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 31

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Outage Case Study in Austria assessed with APOSTELEconometric Modeling of WTPData Availability - Analysis of Regulation’s Effectiveness

Electricity consumption per capita the EU (in kWh)

0.00

1000.00

2000.00

3000.00

4000.00

5000.00

6000.00

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

kWh per capita

Electricity consumption per capita in kWh(based on households' overall consumption) 

BE

BG

CZ

DK

DE

EE

IE

GR

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 32

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Outage Case Study in Austria assessed with APOSTELEconometric Modeling of WTPData Availability - Analysis of Regulation’s Effectiveness

Electricity consumption per capita the EU (in kWh)

0

200

400

600

800

1000

1200

1400

1600

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

KG OE per 1000 €of GDP

Energy Intensity of GDP in kg oe / 1000 €BE

BG

CZ

DK

DE

EE

IE

GR

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 33

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Outage Case Study in Austria assessed with APOSTELEconometric Modeling of WTPData Availability - Analysis of Regulation’s Effectiveness

Electricity consumption per capita the EU (in kWh)

‐55

‐35

‐15

5

25

45

65

85

105

1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

In  %

 of  final energy consumption

Energy Import Dependence

geo\time

Belgium

Bulgaria

Czech Republic

Denmark

Germany

Estonia

Ireland

Greece

Spain

France

Italy

Cyprus

Latvia

Lithuania

Luxembourg

Hungary

Malta

Netherlands

Austria

Poland

Portugal

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 34

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Outage Case Study in Austria assessed with APOSTELEconometric Modeling of WTPData Availability - Analysis of Regulation’s Effectiveness

Electricity Consumption per Capita the EU (in kWh)

0.00

20.00

40.00

60.00

80.00

100.00

120.00

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

in %

Market share of the largest electriciety supplier in each countryBE

BG

CZ

DK

DE

EE

IE

GR

ES

FR

IT

CY

LV

LT

LU

HU

MT

NL

AT

PL

PT

RO

SI

SK

FI

SE

UK

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 35

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Outage Case Study in Austria assessed with APOSTELEconometric Modeling of WTPData Availability - Analysis of Regulation’s Effectiveness

Electricity consumption per capita the EU (in kWh)

00,000

00,000

00,000

00,000

00,000

00,000

00,000

00,000

00,000

00,000

00,000

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Ach

sent

itel

Electricity Price- domestic consumers

GR

DK

IE

NL

FR

LU

UK

PT

BE

ES

DE

IT

HU

SI

AT

BG

CY

CZ

EE

LV

LT

PL

RO

SK

SE

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 36

Introduction, Research Questions and MethodologyResults, Policy Recommendation and Summary

Appendix (if time allows)

Outage Case Study in Austria assessed with APOSTELEconometric Modeling of WTPData Availability - Analysis of Regulation’s Effectiveness

Thank you for your attention

Michael Schmidthaler Regulation and Energy Supply Security 12th July 2012 Slide 37