Assessment of mobility inequalities and income data collection. Methodological issues and a case study (Douala, Cameroon)

• Income data collection impacts the measurement of daily mobility inequalities.
• Simplified income data collection misrepresents the income distribution.
• It leads to an underestimation of mobility inequalities.
• The level of underestimation depends on the mobility indicator.
• Errors are greater in the case of remote areas.

In order to understand the scale and nature of inequalities in intra-urban mobility we need reliable income data, but this is generally difficult to collect in household surveys. The methodological approaches that are employed to overcome difficulties in income data collection may affect the relative position of individuals and households within the income distribution and our estimates of mobility inequalities. In the context of a case study of Douala, this paper evaluates how the way income data is collected affects its accuracy and therefore the measurement of daily mobility inequalities. Simplified data collection tends to minimise the scale of inequalities as it misrepresents the income distribution. The error is greater in remote zones. Shortcomings in the statistical apparatus with regard to income data thus blur our perception of mobility inequalities and impede investigation of the links between daily travel, poverty and social exclusion.