Skyscrapers and Skylines: New York and Chicago, 1885-2007

1. Skyscrapers and Skylines: New York and Chicago, 1885-2007 Jason Barr Rutgers University

2. Zukowsky (1984) “Chicago and New York—these are often thought to be the two great superpowers of American architecture. Architects consider each city to have its own style, its own way of shaping its local environment, its own individualistic contributions to the history of architecture. Yet these contributions were not developed in isolation. Throughout the 19th and 20th centuries there has been, and still is, a considerable amount of competitive interactions between architects, contractors, and developers in both cities.” (emphasis added).

3. Research Questions • Is there evidence for “height competition” across cities? • What are the determinants of the skyline (height and # of skyscrapers)? • Which of the two cities is more “prolific,” controlling for the underlying economic environments and building regulations? • How have height regulations affected the skylines? • Are there different “tastes” for height? • Does the ‘Willis Hypothesis’ on plot sizes hold up?

4. Chicago • Great Fire 1871 destroyed downtown. • Rebuilding with fireproof construction. • Home Insurance Building (1885) – considered world’s first skyscraper (incorporated steel into its frame). • 10 stories. • Demolished in 1931.

5. New York • New York’s first skyscraper, the Tower Building (1888) • First in city to use steel skeleton construction. • Tiny plot encouraged use of steel to increase # of usable floors (due to problem of masonry walls). • Demolished in 1926.

6. Louis Sullivan Schlesinger and Mayer Department Store (1904) Chicago Bayard-Condict Building (1899) New York

7. George Fuller Monadnock Building (1893) Chicago Flatiron (1902) New York

8. Raymond Hood Tribune Tower (1925) Chicago New York Daily News (1929) New York

9. SOM Sears (Willis) Tower (1973) Chicago Lever House (1952) New York

10. Donald Trump Trump International Hotel & Tower (2009) Chicago Trump Tower (1983) New York

11. Time Series, MA(5). Top: # Completions, Bottom: Height of Tallest Building

12. Regional Population (City + Contiguous Counties)

13. Cumulative # of skyscrapers per Million People

14. Height of Tallest Building per Million people, MA(5)

15. Granger Causality • If the two cities are competing, then we would expect to see Granger causality (e.g. lags of height in one city would be used to predict height in the other city). • Look at VAR of # of completions and tallest building completed each year. • VAR(1) “best” order. No unit roots.

16. VAR P

17. GC Results (p-values)

18. Height Regulations

19. Skyline Determinants • Yi,j,t=f(supply, demand, regulations), • i=height, count, j=NYC, Chicago, t=year • National Variables: • Detrended GDP • % F.I.R.E/Emp. • Real Materials Costs • Real Interest Rates • Real Estate Loans • S&P Index • Local Variables: • Metro. Population • Cumulative Completions • Stock Exchange Volume

20. Ln(1+Count): Economic Variables

21. Ln(1+Count): Chicago Height Limits

22. Max Height: (Economic Variables)

23. Max Height: (Height Restrictions)

24. Competitive Interactions

25. GC Tests vs. Regressions

26. Willis (1999) on Lot Size in Chicago • Platted in 1830s, the city was laid out with large, squarish blocks of 360 x 320 and streets 66 or 80 feet wide.” (pps. 49-50). • “Together, municipal regulations and the city’s historic plat of large square blocks generated the Chicago vernacular—a big, boxy building penetrated at the center or rear by a large light court” (p. 65)

27. Histogram of Plot Sizes of Skyscrapers

28. Plot Size Hypothesis

29. Plot Size Hypothesis • Linear regression Number of obs = 1243 • F( 5, 1237) = 39.97 • Prob > F = 0.0000 • R-squared = 0.1518 • Root MSE = .26619 • ------------------------------------------------------------------------------ • | Robust • lnheight | Coef. Std. Err. t P>|t| [95% Conf. Interval] • -------------+---------------------------------------------------------------- • lnplot | .0977717 .0127975 7.64 0.000 .0726645 .1228789 chicago*lnplot | .0081692 .0254287 0.32 0.748 -.0417189 .0580574 • year | .0013687 .0003196 4.28 0.000 .0007417 .0019957 • chicago | -1.972405 1.106864 -1.78 0.075 -4.143942 .1991326 • chicago*year | .0008911 .0005699 1.56 0.118 -.000227 .0020092 • _cons | 1.157989 .6446874 1.80 0.073 -.1068125 2.422791 • ------------------------------------------------------------------------------

30. Conclusions • GC tests & regressions confirm strategic interaction. • Relative to NYC, Chicago’s height restrictions had significant effect on skyline. • NYC is “more responsive” to fundamentals. • Cet. par. “Chicago effect” is positive and significant. • Plot sizes are same for skyscrapers in two cities.