Project Details
Description
The economic miracles of countries such as China and Brazil have led to explosive growth of private car ownership. The rapid growth in motor vehicle fleets has resulted in serious problems like traffic congestion and air pollution. In response to these problems, the so-called plate-number-based traffic rationing policies, which restrict the usage of cars with certain plate numbers on specific days, have been implemented in Mexico City, Beijing and other cities. The existing literature on car ownership may help answer some of the problems faced by the developing countries. However, the scale of car ownership growth observed in China and other developing countries today and the types of response policies adopted deserve research efforts, which may improve our understanding about car ownership. Equally important, we think that the existing car ownership studies can be extended along a different direction. Existing studies mostly treat car ownership as questions of whether to own or how many to own; to our knowledge, hardly any study considers car ownership as a household expenditure commitment competing with other long term decisions such as employment commitments and housing choices. We believe that car ownership should be studied from the point of view of household time and money allocation.
This research project is proposed to: a). Develop a household time and money allocation-based model to analyze households’ decision on car ownership. The model will incorporate households’ consideration of income earning, spending patterns and the time allocation of individual household members. Variables on government traffic rationing policies will be included in the model; b). Collect data on car ownership, car usage, time use and households’ socioeconomics to calibrate the model and study the features of households’ decision on and determinants of car ownership in urban China; and c). Study the impacts of plate-number-based traffic rationing policies on car ownership and the resulting time and budget allocation. This proposed research will contribute to the literature with a new perspective and a modeling approach that links car ownership decision with other household long run decisions. The study will also enrich the literature on determinants of car ownership with new evidences from China; a country that has recently entered the motorized era. Finally, this study will provide evidences on how the plate number–based traffic rationing policies impact on car ownership. Findings of this research will be of highly relevance for policy making.
This research project is proposed to: a). Develop a household time and money allocation-based model to analyze households’ decision on car ownership. The model will incorporate households’ consideration of income earning, spending patterns and the time allocation of individual household members. Variables on government traffic rationing policies will be included in the model; b). Collect data on car ownership, car usage, time use and households’ socioeconomics to calibrate the model and study the features of households’ decision on and determinants of car ownership in urban China; and c). Study the impacts of plate-number-based traffic rationing policies on car ownership and the resulting time and budget allocation. This proposed research will contribute to the literature with a new perspective and a modeling approach that links car ownership decision with other household long run decisions. The study will also enrich the literature on determinants of car ownership with new evidences from China; a country that has recently entered the motorized era. Finally, this study will provide evidences on how the plate number–based traffic rationing policies impact on car ownership. Findings of this research will be of highly relevance for policy making.
Status | Finished |
---|---|
Effective start/end date | 1/01/14 → 31/12/16 |
Fingerprint
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.