et al., 2008). We complement these papers by providing consistent stylized facts on transport expenditures and its composition across and within countries for most countries in the world.

Second it provides estimates of Engel curves that have been widely used including in the assessment of policies related to taxation, housing, trade, but relatively less for transport. We estimate transport expenditures as a linear-quadratic function of total expenditures and other controls. Vehicle purchase is a main part of household expenditure, for which we also document an S-shaped relationship between income and durable asset ownership. Gertler et al. (2016) have rationalized the non-linearity of asset purchase in developing countries because of the presence of credit constraints. They show, in the context of rural Mexico, above a certain threshold increases in income are much more likely to lead to asset purchases. In terms of identification of the elasticity estimates, there are many unobservables that affect both total expenditures and transport expenditures that might bias the Engel curve estimates. AIDS/QAIDS type of models that overcome this problem cannot be used as price data are not available in standard household surveys. Additional works have focused on non-unitary (bargaining and collective) models to include intra-household consumption patterns and inequality (Chiappori and Meghir, 2015; Dunbar et al., 2013; Chavas et al., 2018) and on the identification of potentially confounding sources of heterogeneity in standard household Engel curve estimations due to intra-household interactions (Vreyer et al., 2020). We use standard household-level crosssectional surveys and therefore cannot identify that effect. However, Vreyer et al. (2020) find that the null hypothesis that the household-level estimation of the Engel curves gives the same parameter estimates as one would obtain by consistent aggregation of the individual-level Engel curves for household members cannot be rejected for transport. This can be explained by the fact that vehicle purchases, a large part of transport expenditures, are common goods for the household.

Among the studies that examine the determinants of transport demand, Gandelman et al. (2019) show that incomes, gender, and age explained the level of household transport expenditures in Latin America and the Caribbean (LAC). The authors use income and expenditure surveys and find that transport expenditures increase with income. In particular, the income elasticity of public transport is lower than one while the income elasticity of private transport is greater than one. We complement this paper by doing a similar exercise for a different set of countries and improve their empirical strategy by using a ZIP regression model which performs better given the large number of zero observations. In the same vein, Graham and Glaister (2002) demonstrate that the demand of owning a car depends strongly on income with an income elasticity for fuel demand that falls in the range of 1.1 to 1.3. In another study, Thakuriah and Liao (2006) use consumer expenditure survey data to examine the relationship between transport expenditures and income in the United States. They found that transport expenditures and income belong to a virtuous circle. Indeed, they argue that increase income implies an increase of transport expenditures and vice-versa. Moreover, Thakuriah and Liao (2005) use consumer expenditure survey data to examine vehicle ownership in the United States. Using a 5