How effectively do state governments translate spatial development objectives into policy outcomes, and under what institutional conditions does policy intervention succeed in correcting — rather than reinforcing — existing spatial inequalities? This study addresses these governance questions through a causal evaluation of Uttar Pradesh’s 2018 and 2022 state-level development policies, using subnational visitor flows as a measurable outcome of spatial redistribution. Applying a continuous-treatment difference-in-differences framework — the first to use policy-document-derived treatment intensity — across all 75 districts over 2017–2022, we show that policy attention (measured as district mention frequency in official policy documents) generated no statistically significant average effect on domestic or foreign visitor arrivals. Heterogeneity analysis reveals a significant positive effect on foreign arrivals in medium-growth heritage districts under the 2022 policy, but high-growth religious destinations remain unresponsive, driven by place-specific pull factors that operate beyond the reach of state intervention. These findings support a structural policy reinforcement model: state development policies in spatially heterogeneous developing economies tend to amplify pre-existing destination hierarchies rather than correct them, reflecting a fundamental absorptive capacity constraint on governance effectiveness. The study contributes to public policy implementation theory, spatially differentiated governance, and the comparative political economy of subnational development in Asia.