Equity concerns of urban planners and policy-makers cannot be addressed unless disability effects on daily activities are disentangled. The ndings, however, strongly depend on how disability is incorporated into the model. Two Multiple Discrete-Continuous Extreme Value (MDCEV) models for analyzing disability effects on daily Activity type and duration are discussed and compared in this paper. In the \classic" approach, an independent dummy variable is used to distinguish disability. However, in the \separate" approach, the dataset is divided into disabled and non-disabled groups and, then, a separate model is calibrated for the disabled group. The two approaches achieve different coe cients and elasticity values, evidencing that model speci cation matters for policy assessments. Three transferability metrics are adopted to illustrate that the separate approach outperforms the classic approach in explaining travel patterns of persons with disabilities. Finally, three policies that have been practiced across the globe to prevent social exclusion of disabled people are discussed in terms of the effects of model speci cation on the policy assessment outcomes. This assessment offers managerial insights for policymakers to develop appropriate infrastructure and accessibility strategies for disabled people.