Edward Conard

Top Ten New York Times Bestselling Author

  • “…challenges misconceptions that distort our economic debates.” - Arthur Brooks, President of the American Enterprise Institute
  • “…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
  • “…a fresh argument for the productive value of inequality.” - David Autor, Professor of Economics, Massachusetts Institute of Technology
  • “Unintended Consequences should be read by anyone who takes for granted the superiority of progressive taxation and has not thought carefully about the trade-offs involved.” - The New Republic
  • “…a comprehensive explanation of the modern economy.” - Julian Robertson, Founder, Tiger Management
  • “…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
  • “…serious thinking for serious thinkers. …a thought-provoking blueprint for growing middle- and working-class incomes.” - Mitt Romney, former Governor of Massachusetts
  • “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
  • “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
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Superstar Returns

Francisco Amaral Federal Reserve Bank of New York
Date Posted:
January 31, 2022
Is Database:
Database

According to @FederalReserveBank of New York, superstar cities have seen higher housing price appreciation over 150 years, but total returns are lower due to higher rent returns in non-superstar cities.

Over the past 150 years, housing price appreciation in "superstar" cities has been higher, with an average annual difference of up to 60 basis points compared to other regions. However, total returns in non-superstar cities have surpassed those in superstar cities due to significantly higher rent returns, estimated at 160 basis points more per annum. This results in a negative return premium of approximately 100 basis points annually for superstar cities. The higher returns outside superstar cities are seen as compensation for greater risk, as these areas exhibit higher covariance with income growth and lower liquidity. Despite the allure of rapid price appreciation, the long-term total returns in superstar cities are lower, with investments in these areas earning only about half the cumulative return compared to national portfolios over the past 70 years. Rent returns, representing about 67% of total housing returns, have been the main driver of this trend.

FRBNY research suggests "Superstar" real estate is safe, "...We study long-term returns on residential real estate in twenty-seven “superstar” cities in fifteen countries over 150 years. We find that total returns in superstar cities are close to 100 basis points lower per year than in the rest of the country. House prices tend to grow faster in the superstars, but rent returns are substantially greater outside the big agglomerations, resulting in higher long-run total returns.The excess returns outside the superstars can be rationalized as a compensation for risk, especially for higher covariance with income growth and lower liquidity. Superstar real estate is comparatively safe...."

Core finding, ".... Our central finding is that, over the long-run, superstar cities have witnessed lower total returns on residential real estate than other parts of the same country. With 5.75 log points per year, average total returns have been smaller compared to the national average of 6.68 log points. In other words, an investment in superstar cities comes with a negative return premium of approximately 90 basis points annually relative to national returns (including the superstars) and about 100 basis points lower than the rest of the country (excluding the superstars).These return differences are a robust feature of the data across countries and time periods, and statistically highly significant. A negative return premium of around 1 percentage point accumulates to substantial return differences in the long run. For instance, an investment in the superstar portfolio earned only about half the cumulative return than the national portfolio over the past 70 years..... We confirm that house price appreciation tends to be higher in superstar cities than in the rest of the country. Over the long run, we estimate an average annual difference of up to 60 basis points annually between our 27 superstars and other parts of the country (albeit with mixed statistical significance).At the same time, rent returns are considerably higher outside the large cities. Our point estimate puts the mean rent return differential at 160 basis points per annum. The differences in rent-price ratios exceed the differences in capital gains in the long run and lead to lower total housing returns…”

Why would this be the case, "...Why are housing returns persistently lower in large cities when compared to the rest of the economy?Our key finding can be rationalized in a standard asset pricing framework where excess returns are a compensation for risk. Observable long-run return differences between different assets must be attributable to differences in risk, or to violations of standard assumptions (such as persistent behavioral biases in expectations). Suppose that everything that makes a national superstar city - its diversified economy, its large market, its amenities, the international demand - also makes it a safer place as an investment. A consequence would be that the present value of future housing services will be subject to less risk so that buyers are willing to pay a higher price and accept a lower return for housing investments in large agglomerations. In turn, higher returns outside the superstars would be a compensation for higher risk. For remote locations to attract capital, they have to offer higher returns..."
Evidence

"... The left-hand panel of Figure 4 shows average log housing returns for the full time period and the right-hand panel for the period post 1950. City-level total housing returns have been in the four to six log point range per year, with some differences across the cities in our sample. Toronto, Amsterdam, Gothenburg, Tokyo and Sydney are the cities with the highest long-run returns. The panel on the right shows that housing returns have been higher in the post 1950 period and reached about 6 log points...."

Superstar Returns: Extended Excerpt Image 1


"... Figure 5 plots the distribution of annual log real housing returns for the pre- and post-1950 period. While housing returns were on average lower in the pre-1950 period, they also displayed a higher standard deviation than in the post-1950 period, apparent in a thicker left-tail in the pre-1950 period. This does not come as a surprise, considering that this period featured two World Wars, the Great Depression and large variations in housing policies. Post-1950 superstar returns were close to 2 percentage points higher with a lower standard deviation..."

Superstar Returns: Extended Excerpt Image 2


"...Panel (a) of Figure 6 plots 10-year lagged moving averages of log real housing returns averaged over the 27 national superstars over time. Housing returns dropped sharply around the World Wars as house prices dropped. The effect is particularly pronounced after World War I, as many governments introduced rent freezes in high inflation environments as discussed by Pooley (1992) and White, Snowden, and Fishback (2014)...Higher mean annual total returns in the post-1950 period are driven by substantially higher capital gains. While mean annual capital gains were, on average, 2.95 log points higher in the post-1950 period when compared to the pre-1950 period, mean annual rent returns were, on average, 1.22 log points lower. Panel (b) ofFigure 6 shows the difference in means between the post- and pre-1950 period by city.Across the majority of cities in our sample, mean capital gains were substantially higher in the post-1950 period, while mean rent returns were lower. The increase in mean capital gains is mostly driven by the largely negative capital gains during the war periods. Kuvshinov and Zimmermann (2020) discuss that the fall in rent returns mirrors the secular decline in the yield component of stock returns over the same period. Rent returns represent approximately 67% of total housing returns over the last 150 years. Panel (a) of Figure 7 shows that, although the relative share of rent returns has been quite volatile over time, it has remained by and large the main contributor to total housing returns. In fact, for all cities in our sample, with the exception of Milan, rent returns represent more than 50% of total housing returns in the long-run. This result is in line with the findings in Jord`a et al. (2019) and Demers and Eisfeldt (2021)...."

Francisco Amaral, Martin Dohmen, Sebastian Kohl, and Moritz Schularick, "Superstar Returns," Federal Reserve Bank Of New York, December 2021, https://www.newyorkfed.org/research/staff_reports/sr999

Superstar Returns: Extended Excerpt Image 3

Superstar Returns: Extended Excerpt Image 4


"...To guide the reader through the results, we start with an example of an undisputed national superstar city for which we have high quality data: Paris. Our data show that an investor who bought an apartment in Paris in 1950 realized an average yearly capital gain of 4.85 log points over the period until 2018. The annual rent return in Paris was 3.66 log points on average, resulting in a healthy total annual return of 8.33 log points. This means, for instance, that investments in Parisian residential real estate beat investments in the French equity market by a substantial margin, even on an unleveraged basis. How does this investment return compare to the rest of France? According to Jord`a et al. (2019), an investment in the French national housing portfolio over the same 70-year period saw annual capital appreciation of 4.48 log points, somewhat lower than Paris. As Paris is a substantial part of the French national portfolio, the difference must be driven by other regions in France, in which house prices have risen about half a percentage point less per year than in Paris. However, the picture changes when we bring in rent returns, which were substantially higher in the rest of the country (5.06 vs. 3.66) and more than offset Paris’ advantage with respect to capital gains. Total housing returns were 9.15 per annum for the rest of France and thus about 85 basis points per year higher than in Paris. Despite higher capital appreciation, the superstar city Paris underperformed the rest of France with respect to total returns on housing investment...."

Superstar Returns: Extended Excerpt Image 5


"... Figure 9 shows that the city-level portfolio increased much faster in value than the national one, because house prices in the superstar cities appreciated more, namely by a factor of 6.2 compared to 4.7 for the national portfolio.11 Once again, the picture changes when rent returns are added in the right panel of Figure 9. Assuming reinvestment of rent returns, the national portfolio outperforms the city-level portfolio by a large margin. From 1950 to 2018, the cumulative return on a national housing portfolio has been twice as high as the returns in the superstars...."

Superstar Returns: Extended Excerpt Image 6

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Previous articleJanuary 31, 2022Slowing Women's Labor Force Participation: The Role of Income InequalityHigher earnings among married men led to a decline in their spouses’ workforce participation, a trend linked to rising income inequality, according to @StefaniaAlbanesi @nberpubs. @nberpub.Next articleFebruary 2, 2022The Power Law: Venture Capital and the Making of the New FutureVC valuation surge signals market transformation: Early-stage rises 4x ($5m to $20m), late-stage 4x ($50m to $200m) 2004-2020. Trend reflects VC’s expanding role in tech innovation/market leadership.
Showing 218 database articles primarily about Business Cycle

3% vs. 60%

AI Summary. Direct lending represents roughly 3% of total U.S. household and business debt, a fraction of the 60% share mortgages held at the peak of the housing bubble.

Torsten Sløk Apollo
Date Posted:
April 8, 2026
Is Database:
Database

Torsten Sløk notes the direct lending market is ~$2T or 3% of household and non-financial debt outstanding. To provide context, he shows that in 2006, on the eve of the crisis, mortgages accounted for ~60% of such debt.

Core argument: Direct lending represents a small but growing alternative to traditional bank financing for businesses and households.

The direct lending market is roughly $2 trillion, or about 3% of total debt outstanding for US households and businesses. By comparison, mortgages accounted for about 60% of total household and corporate debt at the peak of the housing bubble in 2006.

Takeaways by Macro Roundup® AI

  1. Direct lending represents a small but growing alternative to traditional bank financing for businesses and households.
  2. The mortgage market’s dominance has shifted dramatically since the 2006 housing peak, reducing systemic risk concentration.
  3. Non-bank lenders now capture meaningful market share in credit provision across the economy.

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Top 10% of Earners Drive a Growing Share of US Consumer Spending

Jonnelle Marte Bloomberg
Date Posted:
September 17, 2025
Is Database:
Database

Mark Zandi finds Americans in the top 10% of the income distribution accounted for 49.2% of consumer spending in Q2, the highest level since 1989.

Consumers in the top 10% of the income distribution accounted for 49.2% of total spending in the second quarter, up from 48.5% in the first quarter, reaching the highest level in data going back to 1989, according to an analysis of Federal Reserve data by Mark Zandi, chief economist for Moody’s Analytics. In contrast, the bottom 80% of the income distribution, or consumers making less than roughly $175,000 a year, have seen their spending merely keep pace with inflation since the pandemic.

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  • GDP
  • Workforce
    • Inequality

Litigation Nation, Engineering Empire

Jonathon Sine Cogitations
Date Posted:
September 2, 2025
Is Database:
Database
Is Important:
Important

Jonathon Sine argues China “is moving beyond its breakneck industrial prime, facing similar dilemmas to those America confronted in the 1960s and 70s.” The ratio of science/engineering to humanities undergraduate majors is 2:1 in both the PRC and US.

Dan Wang’s “big idea” [is] “China is an engineering state, building big at breakneck speed, in contrast to the United States’ lawyerly society, blocking everything it can, good and bad.” I re-group US college majors according to Chinese disciplines to allow for rough comparison. Surprisingly, the ratio of science/engineering to humanities/social sciences is 2:1, the same as in China (if one groups management with science/engineering, as I also do for China). As with China today, America’s breakneck building phase was decidedly winding down by the 1960s. Urbanization went from 40% in 1900 to 70% by 1960, and grew much more incrementally over the next 60 years to 85% by 2020. The country simply did not need to continue building dams, expressways, and energy production facilities at breakneck pace. It became much more a matter of maintaining and upgrading (which has not gone well, at least according to the American Society of Civil Engineers’ report card). The American [building/investment slowdown that started after the 1970s] may be more about structural economic shifts than lawyers.

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  • America’s Housing Affordability Crisis and the Decline of Housing Supply — Why are constant-quality house prices 15% above their pre-2007 peak? Ed Glaeser notes that US housing grew just 0.6% annually in the 2010s, down from 4% in the…
  • Business Cycle
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How America’s AI Boom Is Squeezing The Rest Of The Economy

Economist Staff The Economist
Date Posted:
August 19, 2025
Is Database:
Database
Is Important:
Important

As AI-related investment has risen since 2023, residential and nonresidential investment have declined or flatlined. This may suggest that a relatively rate-insensitive AI buildout is crowding out more interest-sensitive forms of investment.

Something like a sixth of the 2% rise in American real GDP over the past year has come from investments in computer and communications equipment, including chips, and data centres. Add in the grid upgrades to power AI models, plus the intellectual-property value of the software itself, and one estimate puts the boom’s contribution to real GDP growth at 40%. The trouble is that the very sector powering so much of America’s economic growth is squeezing the rest of its output. Housebuilders, for instance, cannot afford to be blithe about higher borrowing costs. Data centres have also constrained the rest of the economy by keeping energy prices high. Average American electricity bills have risen by 7% so far in 2025, at least in part due to the extra strain data centres have put on the grid. Real consumption has flatlined since December. Housebuilding has slumped, as has non-AI business investment.

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  • Business Cycle
  • GDP
  • Productivity
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Is it Over?

Joseph Wang Fed Guy Blog
Date Posted:
August 18, 2025
Is Database:
Database

Following tepid reactions to the release of GTP-5, Joe Wang observes, “It is looking more like companies are spending hundreds of billions on rapidly depreciating GPUs that produce a commoditized product that most clients only modestly benefit from.”

GPT-5 users widely expressed disappointment in the capabilities of the new release, which seemed in some ways a step back. This sentiment is reflected in benchmarks that show a modest improvement in capabilities since the significant improvement in version 4 released two years ago. In addition, the benchmarks suggest a broader convergence in the capabilities of AI models. Commentary suggests this could be due to inherent limitations in the LLM technology and exhaustion of new training data. AI is fascinating technology, but it may not justify the enormous sums spent in its pursuit. It is looking more like companies are spending hundreds of billions on rapidly depreciating GPUs that produce a commoditized product that most clients only modestly benefit from. The entire macro landscape would look very different without the support of the AI boom.

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  • AI’s $600B Question — .@DavidCahn6 at @sequoia argues that because of lack of pricing power and rapidly improving chip technologies, multi-$B investments in current-generation GPUs…
  • Business Cycle
  • GDP
    • Financial Markets
  • Productivity
    • Innovation/Research
    • Investment

US Households and Firms Are in Great Shape

Torsten Sløk Apollo
Date Posted:
March 31, 2025
Is Database:
Database

​​Torsten Sløk notes that US household and banking sector debt has fallen to its lowest level in decades as a % of GDP, while corporate leverage has moved sideways. “The bottom line is that the private sector in the US is in incredibly good shape.”

Household sector leverage and banking sector leverage have declined significantly since 2008. Over the same period, federal government leverage has increased significantly, and corporate leverage has moved sideways. The bottom line is that the private sector in the US is in incredibly good shape.

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