Causal evidence from an NBER paper finds data center expansion raises local employment, house prices, and power costs, with construction and data-processing jobs both rising.
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A new National Bureau of Economic Research working paper delivers causal estimates of how data center growth reshapes U.S. county economies. The study, by Fernando Alvarez, David Argente, Joyce Chow, and Diana Van Patten, uses instrumental variables to address the endogeneity of facility siting. The IV results show that data center revenue growth raises total employment, data-processing employment, construction employment, the number of business establishments, house prices, and electricity prices. The paper also documents increases in tax returns and adjusted gross income, while annual payroll responds less robustly.
The simple read is that data centers create jobs. The better market read is that the employment effect is not a one-time construction bump. The paper finds persistent gains in data-processing roles, which implies that the operational phase sustains a specialized workforce. For investors tracking construction-exposed names, the construction employment channel provides a measurable demand driver tied to a secular compute buildout rather than a cyclical housing cycle. stock market analysis
The IV estimates point to a positive effect on total employment at the county level. The paper documents a lift in data-processing employment and construction employment when data center revenue scales. The number of business establishments also rises. These results hold across different horizons after data center growth, suggesting that the local labor market absorbs both the direct operational staffing and the indirect construction demand.
The construction employment effect appears at multiple horizons, consistent with phased buildouts and ongoing retrofits. The paper’s use of shift-share instruments makes the employment estimates more credible than simple OLS regressions. The instruments leverage pre-existing proximity to InterTubes long-haul fiber nodes and the 1980 county share of U.S. urban college population as shares, with both Chinese and rest-of-the-world data center revenue growth as shifts. This approach isolates the local impact of data center expansion from other economic trends.
Data center growth pushes up house prices in the surrounding county. The paper also finds that electricity prices increase. The house price effect is consistent with higher local incomes and in-migration of workers. The electricity price effect reflects the large power draw of data centers and the strain on local grid capacity.
Tax return counts and adjusted gross income rise, confirming that the activity translates into higher reported earnings for residents. The income gains show up in IRS data, while annual payroll responds less robustly. The electricity price increase is a cost that local households and businesses bear, creating a policy tradeoff between economic development and energy affordability.
The findings sharpen the investment case for data center real estate investment trusts. Rising house prices and employment in data center counties support property values and rental growth for facilities located in those markets. The paper does not break out commercial real estate prices. The residential price signal suggests that the local economic base strengthens, which can feed into higher demand for industrial and data center space.
For electric utilities, the higher electricity prices indicate that data center load growth is not fully absorbed by existing capacity without price pressure. Utilities with exposure to data center clusters may see revenue uplift from volumetric growth and the ability to pass through higher costs. The paper’s causal framework gives investors a cleaner way to model the local price effects of new hyperscale projects.
Construction and engineering firms also get a demand signal. The construction employment effect is not just a short-term spike; it appears at multiple horizons. The paper’s instrument strategy makes the employment estimates more reliable for forecasting labor demand tied to data center buildouts.
The paper opens the door to further work on environmental costs and the distribution of benefits. Local policymakers will weigh the employment and income gains against higher electricity prices and land-use concerns. For markets, the next catalyst is the pace of AI-driven data center announcements (see NVIDIA profile) and the ability of utilities to finance grid upgrades without regulatory lag. The NBER study provides a baseline for quantifying the local economic footprint, and investors can use it to stress-test assumptions about the spillover effects of the compute buildout.
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