Decision Modelling on Household Level for Energy, Fleet Choice and Expenditure
dc.contributor.author
Jäggi, Boris
dc.contributor.supervisor
Jara-Díaz, Sergio R.
dc.contributor.supervisor
Axhausen, Kay W.
dc.date.accessioned
2017-12-06T17:19:02Z
dc.date.available
2017-06-11T20:57:39Z
dc.date.available
2017-12-06T17:19:02Z
dc.date.issued
2015
dc.identifier.uri
http://hdl.handle.net/20.500.11850/106737
dc.identifier.doi
10.3929/ethz-a-010594497
dc.description.abstract
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.
en_US
dc.format
application/pdf
dc.language.iso
en
en_US
dc.publisher
ETH Zurich
dc.rights.uri
http://rightsstatements.org/page/InC-NC/1.0/
dc.subject
ENERGY REQUIREMENT
en_US
dc.subject
10.3929/ethz-a-010594497
en_US
dc.subject
VERKEHRSMITTELWAHL (WIRTSCHAFTSWISSENSCHAFTEN)
en_US
dc.subject
ENTSCHEIDUNGSMODELLE + SPIELTHEORETISCHE MODELLE + THEORETISCHE SIMULATION (SOZIALWISSENSCHAFTEN)
en_US
dc.subject
RESEARCH INTO DEMAND + RESEARCH INTO CONSUMPTION
en_US
dc.subject
CHOICE OF MEANS OF TRANSPORTATION (ECONOMICS)
en_US
dc.subject
DECISION MODEL + GAMING-THEORY MODEL + THEORETICAL SIMULATION (SOCIAL SCIENCES)
en_US
dc.subject
HAUSHALTBUDGET + HAUSHALTSAUSGABEN (HAUSWIRTSCHAFT)
en_US
dc.subject
NACHFRAGEFORSCHUNG + KONSUMFORSCHUNG
en_US
dc.subject
SWITZERLAND (CENTRAL EUROPE). SWISS CONFEDERATION
en_US
dc.subject
SCHWEIZ (MITTELEUROPA). SCHWEIZERISCHE EIDGENOSSENSCHAFT
en_US
dc.subject
ENERGIEBEDARF + ENERGIENACHFRAGE
en_US
dc.subject
HOUSEHOLD BUDGET + HOUSEHOLD EXPENSES (HOME ECONOMICS)
en_US
dc.subject
STATISTICAL DATA HANDLING (MATHEMATICAL STATISTICS)
en_US
dc.subject
VERARBEITUNG UND AUSWERTUNG STATISTISCHER DATEN (MATHEMATISCHE STATISTIK)
en_US
dc.title
Decision Modelling on Household Level for Energy, Fleet Choice and Expenditure
en_US
dc.type
Doctoral Thesis
dc.rights.license
In Copyright - Non-Commercial Use Permitted
dc.date.published
2016
ethz.size
1 Band
en_US
ethz.code.ddc
DDC - DDC::3 - Social sciences::300 - Social sciences
en_US
ethz.code.ddc
DDC - DDC::3 - Social sciences::330 - Economics
en_US
ethz.identifier.diss
22880
en_US
ethz.identifier.nebis
010594497
ethz.publication.place
Zurich
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02115 - Dep. Bau, Umwelt und Geomatik / Dep. of Civil, Env. and Geomatic Eng.
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02115 - Dep. Bau, Umwelt und Geomatik / Dep. of Civil, Env. and Geomatic Eng.::02610 - Inst. f. Verkehrspl. u. Transportsyst. / Inst. Transport Planning and Systems::03521 - Axhausen, Kay W. (emeritus) / Axhausen, Kay W. (emeritus)
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02100 - Dep. Architektur / Dep. of Architecture::02655 - Netzwerk Stadt und Landschaft D-ARCH::02226 - NSL - Netzwerk Stadt und Landschaft / NSL - Network City and Landscape
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02100 - Dep. Architektur / Dep. of Architecture::02655 - Netzwerk Stadt u. Landschaft ARCH u BAUG / Network City and Landscape ARCH and BAUG
*
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02115 - Dep. Bau, Umwelt und Geomatik / Dep. of Civil, Env. and Geomatic Eng.::02610 - Inst. f. Verkehrspl. u. Transportsyst. / Inst. Transport Planning and Systems::03521 - Axhausen, Kay W. (emeritus) / Axhausen, Kay W. (emeritus)
ethz.date.deposited
2017-06-11T20:58:39Z
ethz.source
ECOL
ethz.source
ECIT
ethz.identifier.importid
imp59366b882c4a964544
ethz.identifier.importid
imp593653ace887f71744
ethz.ecolpid
eth:48671
ethz.ecitpid
pub:167010
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2017-07-18T08:18:07Z
ethz.rosetta.lastUpdated
2025-02-07T00:26:15Z
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true
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Doctoral Thesis [30785]