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
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Solopreneurs, Solow, and the SaaSpocalypse

AI Summary. For three decades after commercial electricity delivery began in 1882, inflation-adjusted output per worker grew just 0.5% annually, accelerating to more than double that pace only after factories were redesigned around electric motors rather than retrofitted from steam. The author argues a near-term absence of productivity acceleration from AI is not evidence none is coming.

Ernie Tedeschi Stripe Economics
Date Posted:
May 20, 2026
Is Database:
Database

Tedeschi points to a split in new US business formation: overall applications are rising, but filings from firms likely to hire employees have stalled. He argues AI may be fueling “solopreneur” activity by making it easier to launch without staff.

Does slow early productivity growth mean a new technology won't deliver?

Core argument: For the three decades after Edison began delivering commercial electricity in New York in 1882, inflation-adjusted output per worker grew just 0.5% annually, a sluggish pace relative to what electricity would eventually enable.

For three decades after Thomas Edison began delivering commercial electricity to New York customers in 1882, inflation-adjusted output per worker grew at just 0.5% annually—a sluggish pace relative to what electricity would eventually enable. The gains became evident only as the economy's capital stock and organizational practices adapted to the new technology: new factories designed around electric motors from the ground up, rather than retrofitted from steam. Some of the impetus for this replatforming came from the weapons production spurred by World War I. In the decade after 1917, productivity growth more than doubled its prior three-decade average. The implication for AI is that a near-term absence of productivity acceleration in the aggregate data should not be read as evidence that no acceleration is coming.

Takeaways by Macro Roundup® AI

  1. For the three decades after Edison began delivering commercial electricity in New York in 1882, inflation-adjusted output per worker grew just 0.5% annually, a sluggish pace relative to what electricity would eventually enable.
  2. Productivity gains from electricity emerged only as the economy's capital stock and organizational practices adapted, with new factories designed around electric motors from the ground up rather than retrofitted from steam.
  3. In the decade after 1917, productivity growth more than doubled its prior three-decade average, with some impetus for that replatforming coming from World War I weapons production.

Related Articles:

  • Sectors Embracing AI Are Seeing a Surge in New Business Formation — Sectors with the highest artificial intelligence adoption rates have also seen the strongest growth in new business applications, which one analysis interprets as evidence that AI is lowering the barriers to starting a company.
  • Attention (And Money) Is All You Need: Why Universities Are Struggling to Keep AI Talent — The annual compensation gap between top industry and academic artificial intelligence researchers widened from roughly $294,000 to $1.5m, coinciding with accelerating academic out-migration toward large incumbent technology firms. Researchers who move to industry cut paper production by about 63% while increasing patent filings nearly sixfold, consistent with a shift from open science toward proprietary innovation.
  • Which Entrepreneurs Boost Productivity? — The authors find that a minority of entrepreneurs are "transformative" — generating disproportionate productivity gains, scoring high on IQ tests, being well-educated, and hiring research and development workers. They argue that economies with more such entrepreneurs and R&D workers sustain higher long-run productivity growth.
  • US Business Dynamism
  • Productivity
    • Innovation/Research
    • Investment
Previous articleMay 20, 2026Bond Market Fright May End Cheap Funds EraAuthers notes that the 30-year Treasury yield just hit a 19-year high, last seen in June 2007. He recalls that a column he co-wrote that month warned cheap money was ending. Weeks later, Bear Stearns’ hedge funds collapsed and the GFC spiral began.Next articleMay 21, 2026The Dangerous Brew That’s Rattling Bond MarketsWith US deficits averaging 6.2% of GDP over 2023–2026 (vs. 4.8% over 2010–2019), political populism hindering fiscal restraint, AI Capex, and persistent inflation, 30-year Treasury yields hit a 19-year high of 5.18% Tuesday.
Showing 1 database article primarily about US Business Dynamism

Continued Rise in Business Formation

AI Summary. The gap between growth-oriented and value-oriented new business applications is widening, a divergence likely driven by a proliferation of startups built around artificial intelligence. Large language models are lowering the barriers to starting a business.

Torsten Sløk Apollo
Date Posted:
April 17, 2026
Is Database:
Database

New business applications are ~ back at their pandemic-era level. Sløk argues the increase is “likely driven by the proliferation of AI-enabled startups, as large language models dramatically lower the barriers to entrepreneurship.”

Are AI tools driving a widening surge in high-growth business formation?

Core argument: U.S. business applications continue to rise, and breaking them into value and growth companies reveals a widening divergence between the two categories.

Breaking down business applications into value and growth companies reveals a widening divergence, likely driven by the proliferation of AI-enabled startups, as large language models dramatically lower the barriers to entrepreneurship.

Takeaways by Macro Roundup® AI

  1. U.S. business applications continue to rise, and breaking them into value and growth companies reveals a widening divergence between the two categories.
  2. The widening divergence in business applications is likely driven by the proliferation of AI-enabled startups.
  3. Large language models dramatically lower the barriers to entrepreneurship.

Related Articles:

  • Attention (And Money) Is All You Need: Why Universities Are Struggling to Keep AI Talent — The annual compensation gap between top industry and academic artificial intelligence researchers widened from roughly $294,000 to $1.5m, coinciding with accelerating academic out-migration toward large incumbent technology firms. Researchers who move to industry cut paper production by about 63% while increasing patent filings nearly sixfold, consistent with a shift from open science toward proprietary innovation.
  • Which Entrepreneurs Boost Productivity? — The authors find that a minority of entrepreneurs are "transformative" — generating disproportionate productivity gains, scoring high on IQ tests, being well-educated, and hiring research and development workers. They argue that economies with more such entrepreneurs and R&D workers sustain higher long-run productivity growth.
  • The Economics of Inequality in High-Wage Economies — Information technology created investment opportunities exceeding the supply of properly trained talent, while trade with low-wage economies, low-skilled immigration, trade deficits, and aging demographics eased constraints on low-skilled labor and risk-averse savings. The author argues this framework, rather than rising cronyism, explains high returns to success, slowing productivity growth, and low interest rates.
  • US Business Dynamism
  • Productivity
    • Innovation/Research
    • Startups
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