The Dynamics of Subcenter Formation: Midtown Manhattan, 1861-1906

PublicationsUrban Economics
J. Barr, T. Tassier
Journal of Regional Science, 56(5), 754-791
Publication year: 2016

Abstract

Midtown Manhattan is the largest business district in the country. Yet only a few miles to the south is another district centered at Wall Street. This paper aims to understand when and why midtown emerged. We have created a new data set from historical New York City directories that provide the employment location, residence and job for several thousand residents in the late 19th and early 20th centuries. We supplement this with data from historical business directories. The data allow us to describe how, when and why midtown emerged as a center of commerce. We find that midtown arose because of economies of scale related to shopping, rather than congestion in lower Manhattan or wage differentials across the city. Specifically, the evidence suggests that firms moved to midtown to be near retail businesses and other commercial activity in order to be closer to customers, who had been moving north on the island throughout the 19th century. Once several industries moved from lower Manhattan it triggered a spatial equilibrium readjustment in the 1880s, which then promoted the rise of skyscrapers in midtown around the turn of the 20th century, several years before the opening of Grand Central Station in 1913.

Building the Skyline: The Birth and Growth of Manhattan's Skyscrapers

Books
J. Barr
New York: Oxford University Press
Publication year: 2016

The Manhattan skyline is one of the great wonders of the modern world. But how and why did it form? Much has been written about the city’s architecture and its general history, but little work has explored the economic forces that created the skyline. This book chronicles the economic history of the Manhattan skyline! In the process, the book debunks some widely-held misconceptions about the city’s history. You can purchase the book through Amazon or Oxford University Press.

Skyscraper Height and the Business Cycle: Separating Myth from Reality

PublicationsUrban Economics
J. Barr, B. Mizrach, K. Mundra
Applied Economics, 47(2), 148-160
Publication year: 2015

Abstract

This article is the first to rigorously test how skyscraper height and output co-move. Because builders can use their buildings for nonrational or nonpecuniary gains, it is widely believed that height competition occurs near the business cycle peaks. This would suggest that extreme building height is a leading indicator of GDP, since the tallest buildings are likely to be completed at or near the peak of a cycle. To test these claims, first we look at both the announcement and the completion dates for record-breaking buildings and find there is very little correlation with the business cycle. Second, cointegration and Granger causality tests show that while height and output are cointegrated, height does not Granger cause output. These results are robust for the United States, Canada, China and Hong Kong.

What’s Manhattan Worth? A Land Values Index from 1950 to 2014

Urban EconomicsWorking Papers
J. Barr, F. Smith, S. Kulkarni
Publication year: 2014

Abstract

Using vacant land sales, we construct a land values index for Manhattan from 1950 to 2014. We find three major cycles (1950 to 1977, 1977 to 1993, and 1993 to 2009), with land values reaching their nadir in 1977, just after the city’s fiscal crisis. Overall, we find the average annual real growth rate to be 5.5%. Since 1993, land prices have risen quite dramatically, and much faster than population or employment growth, at an average annual rate of 15.8%, suggesting that barriers to entry in real estate development are causing prices to rise faster than other measures of local wellbeing. Further, we estimate the entire amount of developable land on Manhattan in 2014 was worth approximately $1.74 trillion. This would suggest an average annual return of about 6.4% since the island was first inhabited by Dutch settlers in 1626.

The floor area ratio gradient: New York City, 1890–2009

PublicationsUrban Economics
J. Barr, J. Cohen
Regional Science and Urban Economics, 48, 110-119
Publication year: 2014

Abstract

An important measure of the capital–land ratio in urban areas is the Floor Area Ratio (FAR), which gives a building’s total floor area divided by the plot size. Variations in the FAR across cities remain an understudied measure of urban spatial structure. We examine how the FAR varies across the five boroughs of New York City. In particular, we focus on the FAR gradient over the 20th century. First we find that the gradient became steeper in the early part of the 20th century, but then flattened in the 1930s, and has remained relatively constant since the mid-1940s. Next we identify the slope of the gradient across space, using the Empire State Building as our core location. We find significant variation of the slope coefficients, using both ordinary least squares and geographically weighted regressions. We then identify subcenters, and show that while accounting for them can better capture New York’s spatial structure, by and large, the city remains monocentric with respect to its FAR. Lastly, we find a nonlinear relationship between plot sizes and the FAR across the city.

Population Density across the City: The Case of 1900 Manhattan

Urban EconomicsWorking Papers
J. Barr, T. Ort
Publication year: 2014

Abstract

The literature on urban spatial structure tends to focus on the distribution of residents within metropolitan areas. Little work, however, has explored population density patterns within the city. This paper focuses on a particularly important time and place in urban economic history: 1900 Manhattan. We investigate the determinants of residential spatial structure during a period of rapid population growth. We explore the effects of environmental factors (such as historic marshes and elevation), immigration patterns, the location to amenities, and employment centers. While environmental features and amenities were significant, their effects were dominated by the location choices of immigrants. On the supply side, we also explore how the grid plan affected density.

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

PublicationsUrban Economics
J. Barr
Journal of Regional Science, 53(3), 369-391
Publication year: 2013

Abstract

This paper investigates skyscraper competition between New York City and Chicago. The urban economics literature is generally silent on strategic interaction between cities, yet skyscraper rivalry between these cities is a part of U.S. historiography. This paper tests whether there is, in fact, strategic interaction across cities. First, I find that each city has positive reaction functions with respect to the other city, suggesting strategic complementarity. In regard to zoning, I find that height regulations negatively impacted each city, but produced positive responses by the other city, providing evidence for strategic substitutability.

Skyscraper Height

PublicationsUrban Economics
J. Barr
Journal of Real Estate Finance and Economics, 45(3),723-753
Publication year: 2012

Abstract

This paper investigates the determinants of skyscraper height. First a simple model is provided where potential developers desire not only profits but also social status. In equilibrium, height is a function of both the costs and benefits of construction and the heights of surrounding buildings. Using data from New York City, I empirically estimate skyscraper height over the 20th century. Via spatial regressions, I find evidence for height competition, which increases during boom times. In addition, I provide estimates of which buildings are economically “too tall” and by how many floors.

Bedrock Depth and the Formation of the Manhattan Skyline, 1890-1915

PublicationsUrban Economics
J. Barr, T. Tassier, R. Trendafilov
Journal of Economic History, 71(4), 1060-1077
Publication year: 2011

Abstract

Skyscrapers in Manhattan need to be anchored to bedrock to prevent (possibly uneven) settling. This can potentially increase construction costs if the bedrock lies deep below the surface. The conventional wisdom holds that Manhattan developed two business centers—downtown and midtown—because the depth to the bedrock is close to the surface in these locations, with a bedrock “valley” in between. We measure the effects of building costs associated with bedrock depths, relative to other important economic variables in the location of early Manhattan skyscrapers (1890-1915). We find that bedrock depths had very little influence on the skyline; rather its polycentric development was due to residential and manufacturing patterns, and public transportation hubs.

Skyscrapers and the Skyline: Manhattan, 1895–2004

PublicationsUrban Economics
J. Barr
Real Estate Economics, 38(3), 567-597
Publication year: 2010

This article investigates the market for skyscrapers in Manhattan from 1895 to 2004. Clark and Kingston (1930) have argued that extreme height is a result of profit maximization, while Helsley and Strange (2008) posit that skyscraper height can be caused, in part, by strategic interaction among builders. I provide a model for the market for building height and the number of completions, which are functions of the market fundamentals and the desire of builders to stand out in the skyline. I test this model using time series data. I find that skyscraper completions and average heights over the 20th century are consistent with profit maximization; the desire to add extra height to stand out does not appear to be a systematic determinant of building height.

Endogenous Neighborhood Selection and the Attainment of Cooperation in a Spatial Prisoner’s Dilemma Game

PublicationsUrban Economics
J. Barr, T. Tassier
Computational Economics, 35(5) 211-234
Publication year: 2010

Abstract 

There is a large literature in economics and elsewhere on the emergence and evolution of cooperation in the repeated Prisoner’s Dilemma. Recently this literature has expanded to include games in a setting where agents play only with local neighbors in a specified geography. In this paper we explore how the ability of agents to move and choose new locations and new neighbors influences the emergence of cooperation. First, we explore the dynamics of cooperation by investigating agent strategies that yield Markov transition probabilities. We show how different agent strategies yield different Markov chains which generate different asymptotic behaviors in regard to the attainment of cooperation. Second, we investigate how agent movement affects the attainment of cooperation in various networks using agent-based simulations. We show how network structure and density can affect cooperation with and without agent movement.

Who has the power in the EU?

Power in the European UnionPublications
J. Barr, F. Passarelli
Mathematical Social Sciences, 57, 339-366
Publication year: 2009

Abstract

The European countries are in the process of reforming the EU’s institutions. If ratified, the Lisbon Treaty will have strong implications for the balance of power among member states. Building on the work of Shapley [Shapley, L.S., 1977, A Comparison of Power Indices and a Nonsymmetric Generalization. Paper P-5872. The Rand Corporation, Santa Monica] and Owen [Owen, G., 1972, Political games. Naval Research Logistics Quarterly, 18, 345–354], we present a measure of power that is based on players’ preferences and number of votes. We apply this measure to the Council of Ministers to see who wields power now and who is likely to wield power with the future voting scheme. Further, we show how a country’s power can change, based on the preferences of the agenda setter which, in this case, is the European Commission.

Organization, learning and cooperation

Computational Industrial OrganizationPublications
J.Barr, F. Saraceno
Journal of Economic Behavior and Organization,70, 39-53
Publication year: 2009

Abstract

This paper models the organization of the firm as a type of artificial neural network in a duopoly setting. The firm plays a repeated Prisoner’s Dilemma type game, and must also learn to map environmental signals to demand parameters and to its rival’s willingness to cooperate. We study the prospects for cooperation given the need for the firm to learn the environment and its rival’s output. We show how profit and cooperation rates are affected by the sizes of both firms, their willingness to cooperate, and by environmental complexity. In addition, we investigate equilibrium firm size and cooperation rates.

Segregation and Strategic Neighborhood Interaction

PublicationsUrban Economics
J. Barr, T. Tassier
Eastern Economic Journal, 34,(4),480-503
Publication year: 2008

Abstract

We introduce social interactions into the Schelling model of residential choice; these interactions take the form of a Prisoner’s Dilemma game. We first study a Schelling model and a spatial Prisoner’s Dilemma model separately to provide benchmarks for studying a combined model, with preferences over like-typed neighbors and payoffs in the spatial Prisoner’s Dilemma game. We find that the presence of these additional social interactions may increase or decrease segregation compared to the standard Schelling model. If the social interactions result in cooperation then segregation is reduced, otherwise it can be increased.

Organizations undertaking complex projects in uncertain environments

Computational Industrial OrganizationPublications
J. Barr, N. Hanaki
Journal of Economic Interaction and Coordination, 3(2), 119-135
Publication year: 2008

Abstract

Recent evidence suggests that firms’ environments are becoming more complex and uncertain. This paper investigates the relationship between the complexity of a firm’s activities, environmental uncertainty and organizational structure. We assume agents are arranged hierarchically, but decisions can be made at different levels. We model a firm’s activity set as a modified NK landscape. Via simulations, we find that centralized decision making generates a higher payoff in more complex and uncertain environments, and that a flatter structure is better for the organization with centralized decision making, provided the cost of information processing is low enough.

Cournot Competition and Endogenous Firm Size

Computational Industrial OrganizationPublications
J.Barr, F. Saraceno
Journal of Evolutionary Economics, 18(5), 615-538
Publication year: 2008

Abstract

The paper studies the dynamics of firm size in a repeated Cournot game with unknown demand function. We model the firm as a type of artificial neural network. Each period it must learn to map environmental signals to both a demand parameter and its rival’s output choice. However, this learning game is in the background, as we focus on the endogenous adjustment of network size. We investigate the long-run evolution of firm/network size as a function of profits, rival’s size, and the type of adjustment rules used.

Preferences, the Agenda Setter, and the distribution of power in the EU

Power in the European UnionPublications
F. Passarelli, J. Barr
Social Choice and Welfare, 28(1), 41-60
Publication year: 2007

Abstract

In this paper, we present a generalization of power indices which includes the preferences of the voters. Using a Multilinear Extension perspective (Owen in Manage Sci 18:p64–p72, 1972a) we measure the probability of the players’ voting “yes” for a particular political issue. Further, we randomize the issues and show the influence that the Agenda Setter can have on a player’s power. We demonstrate these results using data from the European Union to show how the power distribution may shift after enlargement and under the new Constitutional Treaty.

Charter School Performance in New Jersey

Urban EducationWorking Papers
J. Barr
Publication year: 2007

Abstract

This paper investigates charter school performance in New Jersey from 2000 to 2006. The analysis shows that charter schools have lower performance than public schools in the same districts on fourth grade standardized tests for Language and Math, but performance improves as charter schools gain experience. In addition, I find that the N.J. Dept. of Education is effectively closing low-performing charter schools. Lastly, regression results provide evidence of a competitive effect from charter schools to public schools.

Charter Schools and Urban Education Improvement: A Comparison of Newark’s District and Charter Schools

PublicationsUrban Education
J. Barr, A. Sadovnik, L. Visconti
The Urban Review, 38(4), 291-311
Publication year: 2006

Abstract 

This article compares student achievement of fourth graders in charter schools and district public schools in Newark, New Jersey. We find that Newark and New Jersey’s charter schools mirror the educational inequalities of the state as a whole, as well as its Abbott Districts. The data indicate that charter schools are similar to district urban public schools, with pockets of excellence and mediocrity. We measure school performance based on two criteria: actual test score performance, and the difference between actual and predicted performance. We find that some charter schools are able to achieve performance above predicted, given their school and student characteristics, while other schools do worse than predicted. Thus charter schools are not simply a magic bullet, but rather they warrant further investigation to see which practices work and which don’t, especially in a challenging urban setting such as Newark.

Teacher location choice and the distribution of quality: Evidence from New York city

PublicationsUrban Education
J. Barr
Contemporary Economic Policy, 23(4), 585-600
Publication year: 2005

Abstract

This article studies the distribution of teacher quality measures across the New York City school system. Because teachers are paid along a fixed salary schedule and they have the option to transfer schools, this analysis measures the degree to which environmental factors affect teacher location choice. Both school-based and neighborhood-based effects are measured, and both types are significant. Furthermore, this article finds that the location of the school in relation to the suburban borders is an important determinant of teacher location choice. (JEL I29, J24, J61)

Cournot competition, organization and learning

Computational Industrial OrganizationPublications
J.Barr, F. Saraceno
Journal of Economic Dynamics and Control, 29, 277-295
Publication year: 2005

Abstract

We model +rms’ output decisions in a repeated duopoly framework, focusing on three interrelated issues: (1) the role of learning in the adjustment process toward equilibrium, (2) the role of organizational structure in the +rm’s decision making, and (3) the role of changing environmental conditions on learning and output decisions. We characterize the +rm as a type of arti+cial neural network, which must estimate its optimal output decision based on signals it receives from the economic environment (which in4uences the demand function). Via simulation analysis we show: (1) how organizations learn to estimate the optimal output over time as a function of the environmental dynamics, (2) which networks are optimal for each level of environmental complexity, and (3) the equilibrium industry structure

A Computational Theory of the Firm

Computational Industrial OrganizationPublications
J.Barr, F. Saraceno
Journal of Economic Behavior and Organization, 49, 345-361
Publication year: 2002

Abstract 

This paper proposes using computational learning theory (CLT) as a framework for analyzing the information processing behavior of firms; we argue that firms can be viewed as learning algorithms. The costs and benefits of processing information are linked to the structure of the firm and its relationship with the environment. We model the firm as a type of artificial neural network (ANN). By a simulation experiment, we show which types of networks maximize the net return to computation given different environments.