Abstract:
Since 1978, when China instituted economic reforms, cities throughout the country have embraced skyscraper construction. Despite their importance, little is understood about what has been driving skyscraper heights and frequencies in China. This work explores the degree to which skyscraper construction patterns are the result of economic fundamentals, versus political factors and intercity competition. We find a strong economic rational across China, but we also find evidence of noneconomic factors. We show that incentives for political officials, such as career promotion, are helping to contribute to the growth in China’s skylines. We also find that small cities tend to overbuild skyscrapers. Spatial autoregression results further suggest some intercity competition, especially for those within the same tier.
Abstract:
The impacts of a major hurricane on commercial and residential real estate can be devastating. Recent events in Houston (with Hurricane Harvey), Florida (with Hurricane Irma), and New York City (with Hurricane Sandy) are examples of how flooding damage can unexpectedly extend beyond the FEMA flood zones. Such surprises or shocks can provide property owners—including those that are not flooded—with new information about future flood risks, based on the difference of the property distance from the flood zone and the distance to the actual locations of flooding. We apply a new estimation strategy to quantify the effects of these shocks on property values, using information on repeat property sales to estimate a separate shock effect for each dry property. We demonstrate our approach with an application to non-flooded properties in New York City for Hurricane Sandy. We find that, in general, houses, apartments, and commercial properties show the most price volatility within the older, denser urban core, mostly in those neighborhoods that appear to be gentrifying.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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)
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
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.