Tobit specification to deal with the zero-expenditure problem, they find that households’ socioeconomic characteristics and geographic region of residence drive their decisions to own or not a vehicle.

Turning now to studies that examine household transport expenditure along with other household expenditures, Sanchez et al. (2006) investigate the choice working households in the United States make between housing and transport expenditures. They use cluster analysis to show that these two types of spending must be analyzed conjointly. In a later study, Ferdous et al. (2010) indicate that households in the United States allocate their transport expenditures according to their socio-demographic characteristics. For instance, urban households spend a higher proportion of their income on housing and public transportation. We complement this first strand of related literature by providing stylized facts on transport expenditures at the household level based on various data sources from a heterogeneous set of countries. Transport-related questions, except for fuel consumption and asset ownership, have been difficult to harmonize across countries (Lebrand and Yin, 2022). We therefore harmonized expenditures from LSMS surveys for as many countries as possible and draw additional insights from larger harmonized survey efforts available at the country level.

Second, this paper is linked to the literature analyzing the relationship between household transport choices, energy demand, and pollution. One important margin to understand the impact of rising incomes on carbon footprint in low- and middle-income countries is the first-time acquisition of carbon-intensive vehicle by households. The growth in energy demand among first-time purchasers is likely to have important implications for macro-level trends in energy use and carbon emissions. Gertler et al. (2016) analyze household decisions to acquire energyusing assets, focusing on the role of rising incomes in the developing world, and show that non-linearities dues to credit constraints will have large impacts on energy use in developing countries. Among these studies, Dai et al. (2012) use household expenditure data in China from 1985 to 2009 to investigate how household consumption expenditure change with rises in income and infer the impacts on carbon emissions. As income rises, the authors find that households spend more on transport and energy-related products, leading to a drastic increase in carbon emissions. To reduce carbon emissions, they suggest a shift of household expenditure from material and transport products to service-oriented goods. In the same vein, Wang et al. (2016) use the social accounting matrix of China to investigate how household expenditure affects carbon emissions through income distribution in rural and urban areas. They find that carbon emissions increase with income levels for urban and rural households. They report that rural households spend a large share of their income on carbon-intensive expenditures like transport. From another perspective, some studies focus on the relationship between vehicle ownership and greenhouse gas emissions. For instance, Vasic and Weilenmann (2006) propose a comparison between the emissions from motorcycles and cars. The authors mention that motorcycles emit less carbon dioxide than cars since they are lighter and less fuel-consuming. We 6