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This is the 4th chapter of the book "Understanding Risks and Uncertainties in Energy and Climate Policy - Multidisciplinary Methods and Tools for a Low Carbon Society" published in Springer. Abstract Ambitious emission reduction targets are challenging the status quo on designing effective strategies for electricity generation portfolios. In this chapter, we consider the role of low-carbon technologies and determine the cost-benefits of policy strategies to mitigate greenhouse gas emissions in the EU. In particular, we look into how long-term scenarios for transmission expansion and decarbonisation policies influence the evolution of the EU power system infrastructure. We use an EU electricity investment model to determine the optimal portfolio of electricity generation technologies and compute their respective costs and emissions achieved towards 2050. Based on the investment model's results (strategies and suggested portfolios), we investigate how these portfolios perform under divergent policy or geopolitical developments. For this purpose, we apply a robust optimisation tool based on the min-max and the min-max regret criteria, which selects ideal portfolios by stress testing a particular scenario or policy choice under uncertainty of input parameters. Results show that pursuing a strong transmission expansion strategy under the EU PRIMES reference case leads to the maximum regret, while relying on EU scenarios with strong prospects for decarbonisation, either with possibilities or with limitation on transmission expansion, leads to portfolios that exhibit the least variance. However, applying regret analysis on investment costs and total emissions indicates a limited transmission investment case as the more robust one, also noting that a high carbon price will accelerate the energy transition.

Ambitious emission reduction targets are challenging the status quo on designing effective strategies for electricity generation portfolios. In this chapter, we consider the role of low-carbon technologies and determine the cost-benefits of policy strategies to mitigate greenhouse gas emissions in the EU. In particular, we look into how long-term scenarios for transmission expansion and decarbonisation policies influence the evolution of the EU power system infrastructure. We use an EU electricity investment model to determine the optimal portfolio of electricity generation technologies and compute their respective costs and emissions achieved towards 2050. Based on the investment model's results (strategies and suggested portfolios), we investigate how these portfolios perform under divergent policy or geopolitical developments. For this purpose, we apply a robust optimisation tool based on the min-max and the min-max regret criteria, which selects ideal portfolios by stress testing a particular scenario or policy choice under uncertainty of input parameters. Results show that pursuing a strong transmission expansion strategy under the EU PRIMES reference case leads to the maximum regret, while relying on EU scenarios with strong prospects for decarbonisation, either with possibilities or with limitation on transmission expansion, leads to portfolios that exhibit the least variance. However, applying regret analysis on investment costs and total emissions indicates a limited transmission investment case as the more robust one, also noting that a high carbon price will accelerate the energy transition. ; publishedVersion ; © The Author(s) 2019 Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

Mestrado em Finanças ; A presente investigação analisa a vulnerabilidade financeira das famílias portuguesas e o impacto de choques macroeconómicos nessa vulnerabilidade. A análise empírica tem como base essencial o European Union Statistics on Income and Living Conditions (EU ? SILC 2010) para Portugal (5.182 famílias). Adoptando o teste de stress como metodologia procede-se à identificação do stress financeiro das famílias, através da adopção de medidas de diferentes níveis de vulnerabilidade baseadas nas margens financeiras. São realizados três tipos de cenários para avaliar o impacto na vulnerabilidade das famílias de três tipos de choques: um aumento da taxa de juro, um aumento da taxa de desemprego e um decréscimo do rendimento. Os resultados empíricos demonstram que a vulnerabilidade das famílias é afectada de modo insignificante por uma subida da taxa de juro. Por contrapartida, um aumento do desemprego e uma redução no nível de rendimento das famílias tem um impacto elevado. Estes resultados convergem com estudos empíricos recentemente realizados em outros países da Europa. A comparação da situação das famílias antes e depois da crise económica e financeira sugere uma degradação significativa da vulnerabilidade financeira das famílias, em particular daquelas pertencentes ao quartil de rendimento inferior e famílias monoparentais ou compostas por dois adultos com filhos menores. ; This research investigates the financial vulnerability of Portuguese households and the impact of macroeconomic shocks on it. The empirical analysis is mainly based on European Union Statistics on Income and Living Conditions (EU - SILC 2010) for Portugal (5,182 households). Using stress test methodologies, the financial stress of households is identified, adopting measures of different levels of vulnerability based on financial margins. Three types of scenario are constructed to assess the impact on family vulnerability of three different types of shocks: an increase in the interest rate, an increase in the unemployment rate and a decrease on income. The empirical results show that the vulnerability of households is weakly affected by rises in the interest rate. By contrast, the rise in unemployment and the decline in the level of household income have a high impact. These computed effects converge with other empirical studies recently conducted in other European countries. The comparison between the households' situation before and after the economic and financial crisis suggests a dramatic worsening of the financial vulnerability of households, particularly those in the lowest quartile of income and households composed by a single parent or couples with dependent children.

Die Firma Use-Lab testet medizintechnische Geräte für Hersteller. Dafür lädt Use-Lab Pflegepersonal ein, setzt es unter Druck und schaut, wie es unter Stress mit einem Gerät zurechtkommt. Solche Tests seien auch für Kliniken und Einkaufsgemeinschaften von Interesse, sagt der Use-Lab-Geschäftsführer.

Reverse stress tests are a relatively new stress test instrument that aims at finding exactly those scenarios that cause a bank to cross the frontier between survival and default. Afterward, the scenario which is most probable has to be identified. This paper sketches a framework for a quantitative reverse stress test for maturity-transforming banks that are exposed to credit and interest rate risk and demonstrates how the model can be calibrated empirically. The main features of the proposed framework are: 1) The necessary steps of a reverse stress test (solving an inversion problem and computing the scenario probabilities) can be performed within one model, 2) Scenarios are characterized by realizations of macroeconomic risk factors, 3) Principal component analysis helps to reduce the dimensionality of the space of systematic risk factors, 4) Due to data limitations, the results of reverse stress tests are exposed to considerable model and estimation risk, which makes numerous robustness checks necessary.