The Policy Spatial Footprint: Causal Identification of Land Value Capitalization Using Network-Time Exposure

Policies rarely act on simple circles around project sites. We develop a policy-semantics-to-geometry workflow that converts clause-level rules in ordinances into auditable Policy Spatial Footprints (PSFs) with explicit boundaries, timing markers, and intensity tiers, and we measure exposure in network time on road–rail graphs. Using 1.10 million arm’s-length parcel transactions from five Yangtze River Delta cities (2012–2024) and a catalog of 64 policies across regulatory, transport, and industrial/functional families, we estimate dynamic capitalization under staggered roll-outs while separating direct footprint effects from adjacency diffusion. Direct exposures are associated with policy-relevant uplifts that build over several years and then stabilize; spillovers attenuate within a few minutes of network travel time. Effects are systematically larger in thicker markets and where pre-policy regulatory headroom is greater. The PSF framework yields estimator-consistent maps with provenance and uncertainty tiers, providing a transparent basis for land-value-capture scheduling and equity-aware carve-outs.