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.

Decision Modelling on Household Level for Energy, Fleet Choice and Expenditure

Kebutuhan perumahan di Provinsi DIY semakin meningkat sejalan dengan meningkatnya jumlah penduduk dan rumah tangga. Permasalahan yang masih menjadi fokus pemerintah saat ini adalah masih banyaknya masyarakat yang tinggal di lingkungan permukiman kumuh yang tidak sehat. Kondisi ini diakibatkan karena tingginya angka urbanisasi yang mendorong peningkatan permintaan rumah namun tidak diimbangi dengan ketersediaan lahan yang memadai sehingga berdampak pada semakin mahalnya harga rumah. Tujuan dari penelitian ini adalah untuk menganalisis faktor-faktor yang mempengaruhi permintaan perumahan khususnya Perum Perumnas di Provinsi DIY. Variabel yang diamati dalam penelitian ini meliputi ketersediaan rumah Perum Perumnas Provinsi DIY, migrasi, pengeluaran konsumsi masyarakat, dan pendapatan per kapita. Teknik analisis yang digunakan dalam penelitian ini adalah regresi linier berganda dengan pendekatan kuantitatif. Temuan empiris membuktikan bahwa migrasi dan pengeluaran konsumsi masyarakat secara signifikan tidak berpengaruh terhadap permintaan rumah Perum Perumnas Provinsi DIY. Hasil penelitian juga membuktikan bahwa pendapatan per kapita memiliki pengaruh positif dan signifikan terhadap permintaan rumah Perum Perumnas Provinsi DIY. 

pdf/dampak-migrasi-pengeluaran-konsumsi-dan-pendapatan-per-3r3ul77qkh.pdf

Dampak migrasi, pengeluaran konsumsi, dan pendapatan per kapita terhadap permintaan rumah perum perumnas provinsi daerah istimewa yogyakarta

With aggregate data from the U.S. Consumer Expenditure Survey for 19 years, 1984 through 2002, this study analyzes relationships between expenditures on transportation and communications. Several classification schemes for expenditure categories were used, from the most aggregate [two categories (transportation and communications)] to the most disaggregate [nine transportation categories (new vehicle purchases, used vehicle purchases, vehicle finance charges, gasoline and motor oil, vehicle maintenance and repairs, vehicle insurance, public transportation, out-of-town lodging, and other entertainment including bikes and recreational vehicles) and five communications categories (telephone service; miscellaneous household equipment including phones and computers; television, radio, and sound equipment; postage and stationery; and reading)]. Aggregate demand system modeling (in particular, the linear approximate almost ideal demand system) was then used to determine the relationships between expenditures on transportation and those on communications, again for several different classifications. The model results indicate that transportation and communications categories have substitution and complementarity relationships, often not symmetric. However, a dominant effect of complementarity can be found in the influence of communications on transportation.

Do Transportation and Communications Tend to Be Substitutes, Complements, or Neither? U.S. Consumer Expenditures Perspective, 1984–2002

The Swiss National Income and Expenditure Survey tracks household budgets of one month for 3000 households every year, in a representative sample for Switzerland. In this paper, the expenditures of households in the years between 2001 and 2008 were analyzed, with a focus on transportation expenditures. The expenditures were categorized in 10 categories: Savings and Durable Goods (SaDG), Food (F), Eating Out, Alcohol and Tobacco (EAT), Housing: Rent and Interest (HRI), Housing: Energy (HE), Entertainment (E), Consumer Goods (CG), Communication (C), Public Transportation (PuT), Private Transportation (PrT). The correlations between these categories were analysed for different subgroups of the population. For every category, a linear least square regression model for the whole data was estimated. The results of the analysis of covariance of the expenditure categories showed that the spending categories are independent from each other and only show very weak interdependencies, but without clear patterns. The results of the linear regressions are very different for every category. Savings are mainly determined by income and household type. Richer households can save considerably more than poorer ones. Food is determined by the no. of persons in the household and by household type. Both categories could be explained considerably well. The other categories had lower explanatory power. Eating out, Alcohol and Tobacco is weakly dependent on income and on age. The finance aspect of housing costs is determined by household type, age (older tenants have lower costs) and geography, but surprisingly almost independent of income. The entertainment spending category is determined by income and household type, as are consumer goods. Communication expenditures are virtually independent of income and almost solely determined by the no. of mobile phone devices in the household. The two transportation categories show a very distinct patterns. While public transportation expenses are almost independent of income and very random (lowest explanatory power of all categories), private transportation is determined mostly through car ownership and household type. Income of course influences car ownership in the first place, but once a household is already a car owner, it does not spend substantially more on fuel, reparations, parking etc. when with higher income.

Interdependencies and Modelling of Swiss Household Expenditure Categories

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Interdependencies and Modelling of Swiss Household Expenditure Categories