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Friday, February 12, 2016

The Skyscraper Economist

The Valley of Depth

The following is an amateurish attempt to summarize Barr, Tassier, & Trendafilov (2011) and Barr's subsequent work on the economics of really tall buildings. 

Dr. Jason Barr, my former professor and thesis adviser as an undergrad, has been studying the economics of skyscrapers for years. When I was a freshman in his intro micro lecture, he inadvertently convinced me to study urban economics and, most significantly, of the amazing versatility of modern economics in its ability to study seemingly every facet of modern life.

What sealed the deal for me was an earlier paper of his (pay-walled, but you can download an earlier version) on what determined the location of Manhattan's first skyscrapers. If you look at Manhattan from afar (pictured above), you'll see tall buildings crowded together in the downtown and midtown, but between them is a valley of much shorter buildings. Some geologists and historians believed that the primary reason for this height valley was the fact that the bedrock below Manhattan also forms a valley between downtown and midtown. Since skyscrapers have to be anchored into the bedrock to avoid sinking, the costs of construction were expected to rise beyond profitable levels in this bedrock valley. Thus, skyscraper builders skipped up to midtown where the bedrock once again rises close to the surface.[1]

Barr and Drs. Troy Tassier and Rossen Trendafilov of Fordham were apparently the first to test this claim empirically. Analyzing data on all buildings 80 meters or taller built between 1890 and 1915 in Manhattan, they found that depth to bedrock had only a small effect on total construction costs.[2] It was actually often cheaper to build a tall building in the bedrock valley, since land prices in the downtown district dwarfed the costs of anchoring. They noted that some of the tallest buildings swarmed City Hall, where the bedrock valley is deepest.

Probit regression then showed that the probability of a skyscraper being built on a given lot was significantly related to transit and park access (positive), distance from the city center of Wall Street and Broadway (negative), land values (negative but possibly endogenous), and demographic factors.[3] [4] Greater depth to bedrock had a negative but statistically insignificant effect.

In fact, when the authors distinguished between bedrock above and below sea level, greater depth to bedrock above sea level actually significantly increased the probability of skyscraper location, since bedrock above sea level is nearer to the surface and may have to be blasted away, but you're less likely to have to splurge on dynamite if the bedrock is just far enough away from the surface. Thus, lots with bedrock above sea level but deep enough to avoid blasting were preferred.

The story this evidence supports is economically intuitive and jives well with historic data. Initially, builders face a tradeoff between the higher costs of acquiring land downtown and the external benefits from locating close to their competitors ("agglomeration economies," or external economies of scale, as they're called). The first skyscrapers will cluster around the city center, but newer builders will have to locate further away until eventually the agglomeration benefits fall off and are dwarfed by the new costs borne from locating in the "rougher" industrial neighborhoods of Five Points and SoHo. With the predominantly white, urban middle class skipping north to modern-day midtown, the later skyscraper builders followed the labor supply.[5]

The paper was picked up in 2012 by the New York Observer and earned a somewhat barbed comment from Paul Goldberger of the New Yorker. Nevertheless, Dr. Barr's media portrayal as the Skyscraper Economist officially began with what he called the Manhattan Bedrock Myth and its subsequent debunking. The NYT covers Barr et. al. (2011) for a general audience.

At first, I was tempted to call Barr's work "myth-busting," applying a variety of cutting edge economic models to various historical contexts in order to empirically test commonly held beliefs (maybe like Freakonomics without the coding errors and climate change tomfoolery). But I prefer the term "myth fact-checking." The goal is to add an extra layer of qualification through a formal analytic framework and empirical scrutiny, to supplement myths--not bust them. Hence how political facts can be judged "True," "Mostly True," Somewhat True," and so on.

This was one of the first real economics papers I ever read, which may be why I dwell so much on it, but Barr has quite a lot of more recent work to check out (including a book dropping in May). I certainly can't do all (or any) of them justice here, so I'll outsource some of that job to major news outlets and other bloggers:
  • The Economist covered Barr, Mizrach, & Mundra (2015) on "The Skyscraper Curse," first posited by Lawrence (1999), which states that the completion of record-setting tall buildings is an indicator of malinvestment and incoming financial crisis and economic decline. More myth fact-checking, and the verdict: Mostly False.[6]
  • Washington Post's WonkBlog most recently covered the Curse paper, with a neat interactive timeline of NYC's skyscrapers from the Council on Tall Buildings and Urban Habitat.
  • Elsewhere in the blogosphere, there's a great post by Socioeconomic Science on the Skyscraper Curse, geared toward a more academic audience.
  • NEP-HIS and Vox cover Barr, Smith, and Kulkarni's (2015) attempt to measure how much Manhattan's land is worth today. You can download the paper directly here.
Other papers which are well worth reading but might not have been picked up by the media include Barr (2010), a fully fleshed-out model of skyscraper height determinants; Barr & Cohen (2014), which presents and analyzes data on floor-area ratios in NYC from 1890-2009; Barr (2013), which studies strategic interaction between skyscraper developers in NYC and Chicago from 1885-2007; and Graham & Barr (2008), which used Granger causality tests on state-level panel data from 2000-2006 to reject the claim that an increase in same-sex couple households caused a decline in married heterosexual households.[7]

Notice throughout all of this work is an eye toward history.



Footnotes:

[1] - Here, skyscrapers are defined as buildings 80 meters or taller in height.

[2] - New York's first zoning ordinances were enacted in 1916. Thus, focusing on this time period probably eliminates such a potentially tricky confounding factor.

[3] - The authors' take on the endogeneity of land values here:
"We have decided to use land values as an independent variable in one of the specifications for the following reason: The emergence of separate business districts began in the second half of the nineteenth century, with the construction of the elevated railroads and the northward movement of the population. As such, the land values in 1909 most likely reflect land value patterns that were in place before the development of skyscrapers. In addition, however, we are less concerned about the estimated coefficient for the land value variable, but rather we are interested in including it as a possible control variable, to see how its inclusion affects the estimate of the depth to bedrock variable. As will be discussed in more detail below, its inclusion provides evidence that, holding land values constant, depth to bedrock did have some influence on the placement of skyscrapers. For example, within lower Manhattan, builders were sensitive to the expense of anchoring the building to the bedrock. However, the effect of bedrock is small when compared to the effects for other variables." (p. 1068)
[4] - That is, density of manufacturing worker residents (negative) and percent white residents (positive). As Barr puts it, “Who’s moving north? It’s the wealthy and the middle class. If you’re an insurance salesman, do you really want to be traipsing through the slums of Five Points or the factories of Soho to get to work? That land was cheap, but the location was worthless.” (The NY Observer, 01/17/12)


[5] - The reason may not seem obvious, but skyscrapers rent office space to companies. If the middle class office workers lived further away from their workplaces, they would have to be paid  more by the companies to cover transportation costs. Thus, companies are less willing and able to pay rent for remote office space, and thus a skyscraper was less profitable in a location far from the middle class.
[6] - This paper was written with Bruce Mizrach (Rutgers) and Kusum Mundra (Rutgers), another former professor of mine who has done awesome work on immigrant homeownership (covered by WaPo) and trade creation.
[7] - John Graham is another former professor of mine who also has a (text)book out that I'm using to torment my own students this semester.

References:
Cohen, Jeffrey P. & Jason Barr. (2014). "The Floor-Area Ratio Gradient: New York City, 1890-2009." Regional Science and Urban Economics 48: 110-119.

Barr, Jason, Bruce Mizrach, & Kusum Mundra. (2015). "Skyscraper Height and the Business Cycle: Separating Myth From Reality." Applied Economics 47(2): 148-160.

Barr, Jason, Fred Smith, & Saylai Kulkarni. (2015). "What's Manhattan Worth? A Land Values Index from 1950 to 2013." Working Papers Rutgers University, Newark 2015-002. Download link.

Barr, Jason. (2013). "Skyscrapers and Skylines: New York and Chicago, 1885-2007." Journal of Regional Science 53(3): 369-391.

Barr, Jason, Troy Tassier, & Rossen Trendafilov. (2011). "Depth to Bedrock and the Formation of the Manhattan Skyline, 1890-1915." The Journal of Economic History 71(4): 1060-1077.

Barr, Jason. (2010). "Skyscraper Height." The Journal of Real Estate Finance and Economics 45(3): 723-753.

Graham, John & Jason Barr. (2008). "Assessing the Geographic Distribution of Same Sex and Opposite Sex Couples Across the Unites States: Implications for Claims of Causality Between Traditional Marriage and Same Sex Unions." Review of Economics of the Household 6(4): 347-367.

Lawrence, Andrew. (1999). “The Skyscraper Index: Faulty Towers.” Dresdner Kleinwort Benson Research. Not available online.