The paper
When a data center opens in a U.S. county it brings an unusual bundle: hundreds of millions of dollars of long-lived capital, large electricity and water draws, and a thin permanent payroll. This paper asks what such a facility does to local investment, the tax base, and employment, and whether the public incentives used to attract it justify their cost. The organizing move is to separate two objects that public debate routinely conflates. Ledger A is the investment itself: its capital, output, low-service-burden tax base, modest workforce, and any agglomeration spillovers. Ledger B is the firm-specific subsidy used to attract it. We bring the modern place-based-policy and heterogeneity-robust difference-in-differences toolkit to bear on a county panel of staggered first openings, anchor the employment evidence to Bahar and Wright (2026), and evaluate subsidies through a cost-per-induced-job and marginal-value-of-public-funds accounting that applies the but-for rates of Bartik (2018a). The original county-panel estimates are forthcoming and are flagged as such throughout; the conclusions drawn here rest on the external causal literature. The evidence points in opposite directions on the two ledgers. The investment is plausibly net-positive locally, concentrated in hyperscale clusters; the firm-specific subsidy is usually value-destroying because most of its dollars are inframarginal. The policy that follows is to welcome the plants, tax their capital neutrally, and retire the discretionary abatements.
At a glance
Question
Local investment, tax-base, and employment effects of data centers — and whether the incentives pay off.
Thesis
“Welcome the plants, question the abatements.” Separate the investment from the subsidy.
Method
Staggered DiD (Callaway–Sant'Anna) on a county panel of first openings + an incentive cost-benefit.
Data
56 pro-grade public datasets (8 must-have), merged on county FIPS.
Thesis & angle
Free-market-favorable, but rigorous — the case is stronger for engaging the counterarguments.
The organizing move is to separate two objects public debate routinely conflates. Ledger A is the data-center investment itself — long-lived capital, output, a low-service-burden tax base, a modest permanent workforce, and any agglomeration spillovers — which is plausibly net-positive locally. Ledger B is the firm-specific subsidy used to attract it, which is usually value-destroying because most subsidy dollars are inframarginal: paid for investment that would have arrived anyway. The policy that follows is to welcome the plants, tax their capital neutrally, and retire the discretionary abatements.
Methodology
Three escalating tiers; the headline estimator is heterogeneity-robust.
- Descriptive + case studies. Profile data-center counties (Loudoun, VA via synthetic control) using locations, electricity, employment, and subsidies.
- Difference-in-differences. Primary estimator: Callaway–Sant'Anna group-time ATT with not-yet-treated controls, aggregated to an event study. Robustness: Sun–Abraham, Borusyak–Jaravel–Spiess imputation, de Chaisemartin–D'Haultfœuille, a TWFE benchmark, the Goodman-Bacon decomposition, and Rambachan–Roth honest-DiD sensitivity.
- Incentive cost-benefit. Cost per promised vs. induced job (Bartik but-for rates), an MVPF account, and the break-even but-for rate.
did, fixest::sunab, didimputation, HonestDiD, tidysynth); the headline econometrics also map to Stata (csdid, eventstudyinteract, did_imputation, honestdid) per AIER's toolchain.Evidence base
Adversarially-verified facts anchoring the paper (every claim sourced).
Data pipeline
Raw public data → tidy clean files → county-FIPS panel → estimates. Reproducible end to end.
Datasets
56 tried-and-true datasets professional economists use — 8 must-have. Full log in the repo's data/raw/SOURCES.md.
Paper outline
- 1. Introduction
- 2. Institutional and Industry Background
- 3. Conceptual Framework
- 4. Literature Review
- 5. Data
- 6. Empirical Strategy
- 7. Results: Investment, Tax Base, and Employment
- 8. Case Study: Loudoun County, Virginia
- 9. Incentive Cost-Benefit Analysis
- 10. Counterarguments and Externalities
- 11. Policy Implications
- 12. Conclusion