The Skyscraper Curse: And How Austrian Economists Predicted Every Major Economic Crisis of the Last Century

The skyscraper, that unique celebration of secular capitalism and its values, challenges us on every level. It offers unique opportunities for insightful analysis in the broadest terms of twentieth-century art, humanity, and history.  — Ada Louisa Huxtable, The Tall Building Artistically Reconsidered

People have been seeking to discover the cause of the business cycle since the dawn of capitalism. For an even longer time people have sought a magic crystal ball that predicts the future. This book provides some insight for both quests.

The skyscraper is the great architectural contribution of modern capitalism, on par with the canals and railroads that transformed the economy of the nineteenth century. However, no one ever thought to connect it with the quintessential feature of modern capitalism — the business cycle. James Grant1 did make a clear connection between real estate and skyscrapers on the one hand and the business cycle on the other in The Trouble with Prosperity, and that book could have been an inspiration to Andrew Lawrence.

In 1999, Lawrence published his Skyscraper Index, which purported to show that the building of the tallest skyscrapers coincides with economic booms. Specifically, he showed that the building of the world’s tallest skyscraper is a good proxy for dating the onset of a major economic crisis — the skyscraper curse. His index does not apply to the irregular ebbs and flows of the economy, only substantial economic crises.

Lawrence is an investment analyst whose Skyscraper Index records the history of the world’s record-breaking skyscrapers and major economic crises. According to his index, when there is a groundbreaking ceremony for a new world-record-height skyscraper the economy is booming, but when the record height is achieved a significant economic crisis soon follows. The “curse” is the economic crisis, which is usually self-evident by the time the opening ceremony occurs. The mystery is, how can record-breaking skyscrapers be connected to economic crises?

Does this represent a cause and effect relationship? Can building a skyscraper cause business cycles? Architectural historian Carol Willis describes a very similar empirical conundrum:

In the overheated speculation of the 1920s, as land prices rose, towers grew steadily taller. Or should the order be: as skyscrapers grew taller, land prices rose? The variables that contributed to real estate cycles were even more complex than this “chicken and egg” conundrum.2

What is the nature of the relationship between skyscraper building and the business cycle? Surely, building the world’s tallest building does not cause economic collapse. Just as clearly, there are well-known economic linkages between construction booms and financial busts. So what theoretical connections can be made between skyscrapers and business cycles?

Lawrence considered overinvestment, monetary expansion, and speculation as possible explanations for the relationship his index revealed, but he did not explore these issues at length or come to a definitive conclusion. Instead he finished with the notion that his Skyscraper Index was an unhealthy hundred-year correlation. Without an established connection or theory for the Skyscraper Index there are strong reasons to doubt its usefulness.

For example, with the destruction of the World Trade Center and the increased threat of terrorism, the Skyscraper Index may have already lost its usefulness for prediction. However, Edward Glaeser and Jesse Shapiro3 did not find a statistically significant link between terrorism and the numbers of skyscrapers built. They also note that because of government interventions — for example, building codes — as well as psychological reasons such as a builder’s desire for personal fame, the number of skyscrapers may not be market determined.

The business press reported on Lawrence’s Skyscraper Index, but without much fanfare. Investors’ Business Daily4 seemed somewhat sympathetic to his “impressive” evidence, but asked: “How could something bad come of building the world’s biggest skyscraper? After all, bigger is better. Having the biggest building on earth can be a source of national pride.”

Also positive was Barron’s, which seemed to agree that it was an “excellent forecasting tool for economic and financial imbalance.”5 Business Week raised the question of how to connect skyscrapers with economic crisis as described by the Skyscraper Index.6 The first and most concerned report came from the Far Eastern Economic Review, which noted that China was planning on breaking the record for the world’s tallest building and was constructing three of the ten tallest buildings on the planet to be completed by 2010.7

The main reason for the muted response to the Skyscraper Index by the business press is that most economic indicators have eventually failed over time. There have been numerous indicators put forth to help us predict the business cycle and stock markets, but they have not passed the test of time. As Goodhart’s law8 states: “Any observed statistical regularity will tend to collapse once pressure is placed upon it for control purposes.” This is also a likely fate of the Skyscraper Index.

For example, the Super Bowl indicator predicts that if the championship team from the National Football Conference (the old NFL) beats the championship team from the American Football Conference (the old AFL) in the Super Bowl game it should be a good year for the stock market and ipso facto a good year for the economy. This is a classic case of a “coincidental indicator.” This type of coincidental indicator (with no causal connections) should be differentiated from the traditional type of coincidental economic indicators that track changes in the business cycle. For example, payroll statistics are clearly linked with economic activity over time. If payrolls increase, then there is more economic activity and GDP. There is a real reason why we expect both statistics to change roughly in unison.

When this Super Bowl connection was first noticed in the 1970s by sports writer Leonard Koppett it was nearly perfect.9 Since then it has lost much of its credibility, with an overall record of about 80 percent but only about 50 percent over the last fifteen years. Therefore, the early success of the Super Bowl indicator manifested just a coincidence and a statistical illusion, as Koppett himself professed.

There are also seasonal indicators like the “January effect,” which claims that if stock markets increase in January, then stock markets will increase that year as well. However, this effect has been given multiple justifications, such as year-end bonuses and tax-avoidance strategies. It is also not clear whether the January effect is based on the performance of the stock market during the first week of January or during the entire month. It is also unclear whether it applies only to small-company stocks or the entire stock market. The January effect also suffers from the fact that once everyone is aware of it, it becomes anticipated and therefore no longer offers reliable investment advice or insight into the economy. As a result, such indicators do not have a reliable record for predicting the stock market or business cycles.

Political indicators of the economy are based on the political business cycle theory. This theory maintains that politicians will use monetary and fiscal policy, along with other policy measures at their disposal, to boost the economy, job growth, and the stock market prior to an election in order to enhance the probability of being reelected. Then after the election they will reverse those policies, creating a recession. Despite its intuitive appeal, the political business cycle theory has found little consistent empirical support. This failure may be the result of the difficulty of knowing what ruling coalition is truly in charge of government or how the different levels of government are interacting over their respective election cycles. These and other problems leave the theory with only a weak link between politics and the economy.

According to Paul Cwik,10 indicators with good causal-economic links to the economy include the inverted yield curve. When short-term interest rates rise above long-term interest rates, the yield curve becomes inverted, and this indicates trouble ahead for the economy. High short-term lending rates may indicate that borrowers are desperate for funds and lenders are reluctant to loan due to the perception of increased risk. The Index of Leading Economic Indicators was once the official crystal ball of the economy. However, in recent years it has had less success predicting changes in the economy. Two other indicators that I use to gauge the global economy are the price of oil and the Baltic Dry Shipping Index, which is a measure of the cost of ocean transportation. When both are high, it is an indication of global economic expansion, a boom, or a bubble. When both are low, it is an indication of economic contraction, a bust, or an economic crisis. However, all of these indicators are error prone and generally only provide a limited advanced notice of cyclical change. Such indicators certainly cannot issue alerts far enough in advance to be helpful for large capital-investment decisions.

Economist Richard Roll explained that economic indicators have only questionable or fleeting value for real-world investing:

I’m not just an academic but also a businessman. … [W]e could sure do a heck of a lot better for our clients in the money management business than we’ve been doing. I have personally tried to invest money, my client’s money and my own, in every single anomaly and predictive device that academics have dreamed up. … I have attempted to exploit the so-called year-end anomalies and a whole variety of strategies supposedly documented by academic research. And I have yet to make a single nickel on any of these supposed market inefficiencies.11

The problems with stock market and economic indicators are many. Some have a poor track record of predictions, while others have a good track record but no economic rationale and thus offer little confidence that they are not just statistical anomalies.

The Skyscraper Index, in contrast, does have a good record in predicting important downturns in the economy. This index is a leading economic indicator. The announcement of building plans — and in particular, groundbreaking ceremonies — typically occurs during economic expansions long before the onset of an economic crisis.

The most important question about the Skyscraper Index is why it has had such a good record of predictive success. Why does it work? What can it tell us about the structure of the economy over the course of a business cycle? Before we answer those questions, let us first examine the history of the index’s success in predicting the curse.

• 1James Grant, The Trouble with Prosperity: The Loss of Fear, the Rise of Speculation, and the Risk to American Savings (New York: Random House, 1996).
• 2Carol Willis, Form Follows Finance: Skyscrapers and Skylines in New York and Chicago (New York: Princeton Architectural Press, 1995), p. 88.
• 3Edward L. Glaeser, and Jesse M. Shapiro, “Cities and Welfare: The Impact of Terrorism on Urban Form,” NBER Working Paper 8696 (Cambridge, MA: National Bureau of Economic Research, 2001), p. 15.
• 4Investors’ Business Daily, “Edifice Complex,” May 6, 1999.
• 5William Pesek, Jr., “Want to Know Where the Next Disaster Will Hit? Look Where the World’s Biggest Skyscraper’s Going Up,” Barron’s, May 17, 1999, MW11.
• 6Gene Koretz, 1999. “Do Towers Rise before a Crash?” Business Week, May 17, 1999, p. 26.
• 7Alkman Granitsas, “The Height of Hubris: Skyscrapers Mark Economic Bust,” Far Eastern Economic Review 162, no. 6 (February 11, 1999): 47.
• 8Charles A.E. Goodhart, “Problems of Monetary Management: The U.K. Experience,” in Charles A.E. Goodhart, “Problems of Monetary Management: The U.K. Experience,” in Inflation, Depression, and Economic Policy in the West, edited by Anthony S. Courakis (Lanham, MD: Rowman & Littlefield, 1981), p. 116.
• 9Jason Zweig, “Super Bowl Indicator: The Secret History,” Wall Street Journal, January 28, 2011.
• 10Paul Cwik, “The Inverted Yield Curve and the Economic Downturn,” New Perspectives on Political Economy: A Bilingual Interdisciplinary Journal 1, no. 1 (2005): 1–35.
• 11Richard Roll, “Volatility in U.S. and Japanese Stock Markets: A Symposium,” Journal of Applied Corporate Finance 5, no. 1 (Spring 1992): 29–30.