Between 2000 and 2025, 38 U.S. states adopted tax incentives to attract data center investment. We provide causal evidence that these incentives increased state-level data center construction, with effects concentrated among large-scale facilities for cloud computing and, more recently, large language models. We develop a quantitative model endogenizing development location decisions and state tax incentives. The model implies strong fiscal competition among states: a coordinated repeal of incentives would improve total state-government welfare. It also implies large expected economic gains from data centers. We explore job market spillovers and find null results for data centers’ impact on local tech-related employment.

States and counties are offering large incentives to attract data centers, yet it remains unclear whether host communities benefit from the buildout of AI infrastructure. We find no detectable average effect of data-center load on residential or commercial electricity prices, and no broad gains in local revenue, employment, or IT spending. These results suggest that host communities help finance the buildout of AI infrastructure without receiving broad local gains. We argue that the historical null in electricity prices is consistent with supply-side absorption: during our sample, load growth appears to have landed largely on slack segments of local supply curves. Private procurement and behind-the-meter contracts matter mainly for forward-looking scenarios, not for explaining the historical null.

We build a novel property-level database of U.S. datacenter mortgages, documenting a source of AI-buildout financing that has received little attention. Unlike corporate debt, which is observable through public bond and loan disclosures, property-level mortgage lending is fragmented across property records, local lenders, and non-public loan documents. By linking these mortgages to lender balance sheets, we document a large, recent, and highly concentrated market. The market is dominated by banks with a high propensity to originate loans for distribution rather than retention, that is, originate-to-distribute (OTD) banks, and by Undiversified Datacenter borrowers, firms whose repayment capacity depends on continued AI demand for datacenter capacity rather than diversified revenue. We then ask whether OTD incentives relax lending standards in this market. We find that High-OTD lenders extend substantially higher leverage and finance more Undiversified Datacenter deals. Moreover, the leverage premium itself concentrates among these same borrowers.