Edward Conard

Top Ten New York Times Bestselling Author

  • “…a must-read for serious students of economic policy.” - Glenn Hubbard, Dean, Columbia Business School, and former Chairman of the Council of Economic Advisers
  • “…reminds us that inequality sends a signal of what society lacks most, in America’s case, entrepreneurship and risk taking.” - Lawrence Lindsey, CEO, The Lindsey Group, former Director of the National Economic Council
  • “Unintended Consequences provides a provocative interpretation of the causes of the global financial crisis and the policies needed to return to rapid growth. Whether you agree or not, this analysis is well worth reading.” - Nouriel Roubini, New York University; Chairman, Roubini Global Economics
  • “…serious thinking for serious thinkers. …a thought-provoking blueprint for growing middle- and working-class incomes.” - Mitt Romney, former Governor of Massachusetts
  • “Unintended Consequences represents the most cogent and persuasive analysis of the Financial Crisis to date.” - Andrei Shleifer, 1999 John Bates Clark Medal Winner
  • “…a fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
  • “…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
  • “Unintended Consequences is far smarter and more thought-provoking than most economics written for the general public” - Greg Mankiw, Harvard University, Former Chairman of the Council of Economic Advisors
  • “Unintended Consequences is full of substance, it is one of the must-read books of the year, and once I finish it I will be giving it a second read through right away.” - Tyler Cowen, Professor, George Mason University
  • “There are an amazing number of good ideas and interesting points made in Unintended Consequences. The thinking underlying it, and the obvious depth of understanding of the author, are very impressive.” - Steven Levitt, coauthor of Freakonomics; 2004 John Bates Clark Medal
  • “Unintended Consequences offers deep and well-argued analyses on almost every issue.” - The New York Times
  • “…a fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
Upside of Inequality Oxford Unintended Consequences

AI Summary. Capital spending on AI data centers is around 20% of railroads' peak spending as a share of GDP and is rising quickly, having already surpassed the dot-com era peak in telecom investment. Unlike long-lived rail infrastructure, data centers are short-lived assets requiring frequent hardware replacement, and the capital is being reallocated from other sectors.

Paul Kedrosky Applied Complexity
Date Posted:
Is Database:
Database

Kedrosky estimates capex related to the datacenter buildout is ~20% of the railroad buildout in the 1880s and rising, though he cautions AI datacenter depreciation is high: “we aren’t building century-long infrastructure…datacenters are short-lived.”

How does AI data center spending compare with past infrastructure booms?

Core argument: AI data center capital expenditures run at roughly 20% of the peak spending on railroads as a share of GDP and are still rising quickly, having already surpassed the dot-com-era peak in telecom spending.

Capital expenditures on AI data centers is likely around 20% of the peak spending on railroads, as a percentage of GDP, and it is still rising quickly. And we've already passed the decades ago peak in telecom spending during the dot-com bubble. Regardless of what one thinks about the merits of AI or explosive datacenter expansion, the scale and pace of capital deployment into a rapidly depreciating technology is remarkable. These are not railroads—we aren’t building century-long infrastructure. AI datacenters are short-lived, asset-intensive facilities riding declining-cost technology curves, requiring frequent hardware replacement to preserve margins. And this surge has unintended consequences. Private capital expenditures don't, for the most part, come from nowhere. While governments can print money to spend, companies generally can't. Capital is being aggressively reallocated—from venture funding to internal budgets—at the expense of other sectors.

Takeaways by Macro Roundup® AI

  1. AI data center capital expenditures run at roughly 20% of the peak spending on railroads as a share of GDP and are still rising quickly, having already surpassed the dot-com-era peak in telecom spending.
  2. Unlike century-long railroad infrastructure, AI data centers are short-lived, asset-intensive facilities on declining-cost technology curves that require frequent hardware replacement to preserve margins.
  3. Private capital for the AI buildout is being reallocated from venture funding to internal corporate budgets at the expense of other sectors, since companies, unlike governments, cannot print money to spend.

Related Articles:

  • Back to Our Regularly Scheduled Programming — The four largest US hyperscalers spent $440bn on capital expenditure and research in 2024, with $596bn projected for 2025, a 35% increase, leaving large gaps between AI spending and AI revenues. These firms account for more than half of all capital expenditure growth in the US equity market.
  • AI Adoption Is Accelerating In 2025 — Nvidia's data center revenue growth is used as a simple extrapolation to project the broader capital-expenditure impact of AI-specific investment on GDP. The aim is not precision but a timely sense of whether the growth contribution from AI capital spending is accelerating or potentially peaking.
  • SPVs, Credit, and AI Datacenters — Companies funding AI data centers through jointly owned special purpose vehicles keep the borrowing off their own balance sheets while retaining shared control and use of the facilities. AI data center spending already exceeds telecom spending during the dot-com bubble, and weak returns would quickly wipe out the thin equity cushion above the vehicles' debtholders.
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