{"id":125260,"date":"2024-01-23T09:37:45","date_gmt":"2024-01-23T08:37:45","guid":{"rendered":"https:\/\/www.wifo.ac.at\/publication\/125260\/"},"modified":"2025-10-22T22:10:34","modified_gmt":"2025-10-22T20:10:34","slug":"international-passenger-transport-and-climate-change-a-sector-analysis-in-car-demand-and-associated-co2-emissions-from-2000-to-2050","status":"publish","type":"publication","link":"https:\/\/www.wifo.ac.at\/en\/publication\/125260\/","title":{"rendered":"International passenger transport and climate change: A sector analysis in car demand and associated CO2 emissions from 2000 to 2050"},"content":{"rendered":"","protected":false},"featured_media":0,"template":"","class_list":["post-125260","publication","type-publication","status-publish","hentry"],"acf":{"subtitle":"","text":"The paper provides global regionalised projections of passenger car demand, use and associated CO2 emissions from 11 world regions. The study is based on empirical data that have been originally collated from international sources for the purpose of modelling region-specific car stock demand. Derived demands serve as indicator of car related fuel consumption and associated CO2 emissions, which are calculated on the basis of behavioural and technological scenarios. The obtained CO2 emission paths are sectoral baseline scenarios that identify region-specific potentials of growth in car induced CO2 emissions assuming that current trends continue to prevail. The study adopts a multi-model approach to car demand by applying two methods rooted in the economics of consumption: utility maximisation and single equation models. The utility maximisation method for modelling car demand is driven by the preferences of the representative consumers of each world region, subject to exogenous price and income trajectories. The latter is adopted from an optimal growth model. This is a novel approach to projecting global regionalised sectoral car demands. The study is complemented by the application of single equation income-consumption models based on logistical Gompertz functions and non-linear regression techniques to compare model results.","onlinedate":"2007-01-01 01:00:00","lang":"English","publication_series":"","publication_date":"20070101","publication_date_year":"2007","publication_date_full":false,"publication_num_pages":"","keywords":"[\"Passenger car demand; CO2 emissions scenarios; Climate policy\"]","jelcodes":"[]","related_publications":"[]","pdf":null,"zip":null,"link":"https:\/\/www.wifo.ac.at\/wwa\/pubid\/59399","monthly_report":false,"monthly_report_main":false,"monthly_report_volume":"35","monthly_report_pages":"6332-6345","monthly_report_pages_sort":"6332","issue":"12","journal":"Energy Policy","publisher":"","invisible":false,"external":true,"embargo_date":null,"types":[83083],"research_groups":[3655],"collaboration":"","persons":[3711,14093,14095],"persons_data":"[{\"personId\":3711,\"personName\":\"Ina Meyer\",\"organisationNames\":[]},{\"personId\":14093,\"personName\":\"Marian Leimbach\",\"organisationNames\":[]},{\"personId\":14095,\"personName\":\"Carlo C. 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