# **1 Introduction**

Economic development is associated with higher transport mobility. Households get richer and transition from walking to using public transport or buying a private vehicle. Consumption habits also change, and cars are increasingly used to drive around in sprawling cities. However, transport currently accounts for a quarter of energy-related carbon emissions and ranks among the fastest growing sources of such emissions (Sims, 2014; IEA, 2012). In addition, carbon emissions are unequally distributed not only between countries but also within countries (Chancel, 2021). This paper first quantifies how transport consumption, and its composition, changes as incomes rise across and within countries. It then simulates changes in carbon footprint and carbon inequalities for 18 low- and middle-income countries as income reach their 2035 levels. Such estimates can be used to assess the future distributional impacts of climate and energy policies.

The literature has shown that household demand for transport varies significantly across income levels. In high-income countries, studies using survey micro-data provide scattered evidence that direct transport-related energy consumption is less than proportional to income (Caron and Fally, 2022). Evidence from low- and middle-income countries is more limited. Studies focusing on the purchase of energy-intensive durable goods however, tend to find clear income effects towards the middle of the income distribution, suggesting significant future increases in energy demand, and carbon emissions, as large populations are just beginning to purchase energy-intensive goods (Gertler et al., 2016).

In this paper, we show how standard household surveys can be used to understand how rising incomes will affect transport consumption and the resulting transport carbon footprints and inequalities. Similar works have mostly relied on cross-country data or focused on one country, often an OECD country. However, carbon emission are expected to grow the most in nonOECD countries, for which consistent cross-country data or transportation household surveys are difficult to find. In addition, recent works have shown the benefits of using household-level data. Gertler et al. (2016) use household surveys to document motivating evidence of a nonlinear relationship between income and both asset ownership and energy use at the individual and municipality levels. Household survey data can also be used to document the distribution of transport expenditure shares within countries, which is key for the political economy of climate policies such as carbon pricing.

We identify several extensive and intensive margins of interest to quantify the impacts of rising incomes on transport consumption that are relevant for low- and middle-income countries. In low-income countries, the share of households not consuming transport goods and services remains high. The lack of access to and affordability of such goods and services limits mobility and access to economic opportunities. As their income increases, households spend more on transport and can then choose between public and/or private transport options. While private transport might be more efficient, it is also more carbon-intensive than public transport. In 2