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This thesis analyses decision modelling and behaviour on a household level regarding energy consumption in housing and transportation, fleet choice in the case of high fuel prices and household expenditures. For this research three different data sets were used: A) A data set about total energy consumption from a survey including Stated Preference experiments about long term investment decisions in energy saving technology and a Priority Evaluator experiment about total energy consumption ,conducted among home-owners in the canton of Zurich. B) A data set about fleet choice from a survey including Stated Preference experiments for high fuel prices, conducted among car owners in Switzerland. C) The Swiss National Income and Expenditure Survey reporting all incomes and expenditures for a representative sample of Swiss households for the duration of one month. This data set covers the years between 2001 and 2008. The methodologies used were, next to standard descriptive statistics, Multinomial Logit Models (MNL) to model long term investment decisions, Multiple Discrete-Continuous Extreme Value model (MDCEV) to model total energy consumption and fleet choice and linear last square regressions to model household expenditure categories. In addition to the modelling, the results from the MDCEV models were analysed regarding residuals and accuracy of model implementation. Results of the analyses showed that total energy consumption was very difficult to model and produced unreliable results. Long term investments in energy saving technology as well as the change to cleaner, less fuel consuming cars, are preferred over a change in energy consuming behaviour when fuel prices are substantially higher. Linear regression models showed that household budget expenditures are very individual and reveal very few interdependencies. The categories which are most predictable are savings and food while the least pre- dictable are public transportation and housing rent and mortgage interest payments.