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This paper presents the utilization of mobile phone data for transport models, with spatial modeling of the study region in geographical units that allows the integration of aggregated call detail records (CDR) with demographic data and other sources. The algorithm used for the estimation of the origin–destination matrices obtained a distribution of the number of trips compatible with those of a household survey conducted in 2013. With the use of a one-year dataset, two mobility patterns were identified in Rio de Janeiro: home–work and weekend trips. Changes in mobility patterns because of an important road modification were also detected, demonstrating that the use of CDR for urban planning and monitoring is a robust and low-cost option.

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Most of the transport equity and TRSE studies assume that increasing accessibility levels lead to increased activity participation and, therefore, a reduction in social exclusion. Although this assumption makes sense from a theoretical point of view, this causal relationship has not yet been validated in practice. Previous studies investigating the accessibility-participation relationship were inconclusive, indicating that increasing accessibility has a limited impact on activity participation levels, if any. Moreover, the existing empirical evidence in the literature in the Global South context is scarce, is merely correlational and fails to infer causality between both variables. The contributions of the paper are threefold. First, (a) to provide a conceptual model of the causal relationship between accessibility, activity participation and risk of transport-related social exclusion (TRSE); second, (b) to summarise the available empirical evidence about the accessibility-activity participation relationship through a systematic literature review; and third, (c) to provide evidence of the causal relationship between accessibility and activity participation levels in a Global South context. Three Poisson regression models associated with an instrumental variable identification strategy were used to assess the causal effect between accessibility and participation in total, mandatory and discretionary activities in the city of São Paulo, Brazil. The three models showed a highly significant, strong correlation between an individuals’ accessibility level and their actual participation in total, mandatory and discretionary activities. Based on our results, we argue that low accessibility levels may severely restrict individuals’ life chances and add evidence that accessibility has to be an important instrument to support transport policies' decision-making.