Die Anwendung eines Mikrosimulationsmodells als Instrument der wirtschaftswissenschaftlichen Forschung erfreut sich großer Beliebtheit. Die Verwendung dieses Modelltyps hat vor allem zwei Gründe. Zum einen sind die in den letzten Jahren extrem gesunkenen Kosten der Informationsverarbeitung ursächlich für die mittlerweile häufige Verwendung. Zum anderen besitzt diese Analyseform Eigenschaften, die kein anderes Instrument aufweist. Insbesondere für die Abschätzung der Verteilungswirkungen von Steuer- und Transferreformen ist die Mikrosimulation eine nahezu ideale Methode. Durch die Einbindung eines Nachfragesystems kann sowohl das Anwendungsgebiet eines Mikrosimulationsmodells erweitert als auch dessen potentielle Leistungsfähigkeit gesteigert werden. Die Arbeit hat im Wesentlichen die Beantwortung der Fragestellungen aus den folgenden zwei Fragenkomplexen zum Ziel: - Wann ist die Einbindung eines Nachfragesystems in Mikrosimulationsmodelle sinnvoll und wie kann ein solches System in das eigentliche Mikrosimulationsmodell integriert werden? - Welche Nachfragesysteme können aus den in Deutschland in Querschnittsform vorhandenen Mikrodatensätzen geschätzt werden und welche theoretischen Eigenschaften besitzen diese Systeme bzw. deren in einem zweistufigen Budgetierungsprozess einsetzbare Kombinationen? / The application of a microsimulation model as an instrument for economic research enjoys great popularity. The use of this type of model primarily has two reasons. In the first place the decreasing costs of data processing led to the frequent usage. Furthermore this type of analysis has unique characteristics compared to other instruments. Particularly microsimulation is an almost ideal method for the estimation of the impact of tax and allocative transfer reforms. With the integration of a demand system the field of application of a microsimulation model can be enlarged as well as its potential capacity increased. This paper has the aim to answer basically two batteries of questions: - In what case the integration of a demand system in a microsimulation model is reasonable and how can such a system be integrated in the model? - Which demand systems can be estimated from the microdata available in Germany and which characteristic properties do such systems offer, especially the combinations applicable in a two-stage budgeting environment?

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This thesis uses innovative approaches to analyse energy policy interventions aimed at enhancing the environmental sustainability of energy use as well as its consequential welfare implications. First, we examine the relationship between energy efficiency improvement and CO2 emissions at the macro level. We use the Index Decomposition Analysis to derive energy efficiency by separating out the impact of shifts in economic activity on energy intensity. We then employ econometric models to relate energy efficiency and CO2 emissions accounting for non-economic factors such as consumers lifestyle and attitudes. The applications for 13 OPEC and 30 OECD countries show that at the country-group and individual country level, increase in energy intensity for OPEC is associated with both deteriorations in energy efficiency and shifts towards energy-intensive activities. The model results suggest that the reduction in energy efficiency in general go in tandem with substantial increases in CO2 emissions. The decline in energy intensity for OECD can be attributed mainly to improvements in energy efficiency which is found to compensate for the impact on CO2 emissions of income changes. The results confirm the empirical relevance of energy efficiency improvements for the mitigation of CO2 emissions. The method developed in this chapter further enables the separate assessment of non-economic behavioural factors which according to the results exert a non-trivial influence on CO2 emissions. Secondly, having empirically confirmed the relationship between energy efficiency improvements and CO2 emission at the macro level in Chapter 2, we investigate potential underlying drivers of energy efficiency improvements taking into account potential asymmetric effects of energy price change in Chapter 3. This is crucial for designing effective and efficient policy measures that can promote energy efficiency. In addition to the Index Decomposition Analysis used to estimate the economy-wide energy efficiency in Chapter 2, we also use Stochastic Frontier Analysis and Data Envelop Analysis as alternative methods. The driving factors are examined using static and dynamic panel model methods that account for both observed and unobserved country heterogeneity. The application for 32 OECD countries shows that none of the three methods leads to correspondence in term of ranking between energy efficiency estimates and energy intensity at the country level corroborating the criticism that energy intensity is a poor proxy for energy efficiency. The panel-data regression results using the results of the three methods show similarities in the impacts of the determinants on the energy efficiency levels. Also, we find insignificant evidence of asymmetric effects of total energy price but there is proof of asymmetry using energy specific prices. Thirdly, in Chapter 4 we offer an improved understanding of the impacts to expect of abolishing fuel price subsidy on fuel consumption, and also of the welfare and distributional impacts at the household level. We develop a two-step approach for this purpose. Key aspect of the first step is a two-stage budgeting model to estimate various fuel types elasticities using micro-data. Relying on these estimates and the information on households expenditure shares for different commodities, the second step estimates the welfare (direct and indirect) and distributional impacts. The application for Nigeria emphasises the relevance of this approach. We find heterogeneous elasticities of fuel demand among household groups. The distributional impact of abolishing the kerosene subsidy shows a regressive welfare loss. Although we find a progressive loss for petrol, the loss gap between the low- and high-income groups is small relative to the loss gap from stopping kerosene subsidy, making the low-income groups to suffer a higher total welfare loss. Finally, from the highlighted results, we draw the following concluding remarks in chapter 5. Energy efficiency appears a key option to mitigate CO2 emissions but there is also a need for additional policies aiming for behavioural change; energy specific prices and allowing for asymmetry in analysing the changes in energy efficiency is more appropriate and informative in formulating reliable energy policies; the hypothesis that only the rich would be worse-off from fuel subsidy removal is rejected and the results further suggest that timing of the fuel subsidy removal would be crucial as a higher international oil price will lead to higher deregulated fuel price and consequently, larger welfare loss.