Finance and Economics Discussion Series (FEDS)
December 2025
Estimating Aggregate Data Center Investment with Project-level Data
Eirik Eylands Brandsaas, Daniel Garcia, Robert Kurtzman, Joseph Nichols, and Adelia Zytek
Abstract:
Data center investment in the U.S. has increased rapidly in the post-pandemic era, and plans for future investment have surged further. Forecasting investment at such a turning point is an important but potentially fraught exercise, especially given lags in aggregate data availability. We develop a straightforward method to forecast aggregate investment using project-level microdata and a small number of parameters: specifically, abandonment rates, time from plan-to-start, and time from start-to-completion. As a key validation of our approach, we generate estimates that match the recent history of aggregate data center investment in the NIPAs. We then use our method to generate nowcasts of aggregate data center investment in the short run, with the mean forecast indicating that investment will increase to $370 billion annualized by 2026:Q2. We can extend our methodology further out, but our forecasts then become conditional on the assumed flow of new data center plans. Assuming future plans range from one-fourth to twice the average pace of plans from 2024-2025 implies a range of investment forecasts of $360 billion to $930 billion in 2027, demonstrating the substantial upside and downside risks to future levels of investment.
Keywords: data centers, commercial real estate, forecasting, construction, time-to-plan
DOI: https://doi.org/10.17016/FEDS.2025.109
PDF: Full Paper
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