THE PENNSYLVANIA STATE UNIVERSITY SCHREYER HONORS COLLEGE

DEPARTMENT OF FINANCE

PSYCHIC VALUE AND URBAN REGENERATION: HOW AND WHY SIGNATURE ARCHITECTURE AFFECTS REGIONAL ECONOMIES

ALEXANDER GROSEK SUMMER 2020

A thesis submitted in partial fulfillment of the requirements for a baccalaureate degree in Finance with honors in Finance

Reviewed and approved* by the following:

Christoph Hinkelmann Clinical Associate Professor of Finance Thesis Supervisor

Brian Davis Clinical Associate Professor of Finance Honors Adviser

* Electronic approvals are on file. i

ABSTRACT

Focusing on buildings designed by winners of the Pritzker Prize for Architecture, I create a sample of 509 buildings-designed-by-signature-architects (BDSA) in the United States. This yields 170 metropolitan statistical areas (MSAs) that contain 509 BDSA. Drawing on U.S.

Census data from 2010 2019, 13 economic data points are collected for each MSA in the sample, yielding 2,210 initial data points. The same 13 data points are collected for each of the 37 states where at least one BDSA currently resides, yielding an additional 481 unique data points

Finally, the same 13 data points are collected for the U.S. economy as a whole. This data is sorted using basic weighted-average calculations to measure the relationship between the number of

BDSA and the regional economic performance of the group of MSAs containing those BDSA, weighted by the number of BDSA in each city. The BDSA-weighted average of these economic statistics is then compared to the state and national averages for the same economic indicators.

The results of this study show that the 170 regions under analysis have BDSA-weighted economic indicators that, when viewed together, demonstrate significantly more robust regional economic environments than the population-weighted average statistics for the 37 state economies in which they reside and the national average for the U.S. The results of this study show that BDSAs overwhelmingly appear in economically vibrant cities that are wealthier, more racially diverse, more educated and more employed than the respective average for the 37 states that contain at least one BDSA, and the United States overall.

ii

Architecture goes past function. It intelligently solves problems it in elicil aked o solve and inspires awe by demonstrating the creative potential of humans.

- Anonymous

Architecture is aesthetically diincie becae i i an a of deign. Achiece individuality comes from the fact that it is a useful art, and that the aesthetics of architecture should be based on recognizing its usefulness.

- Richard Hill, Purpose, Function, Use

A fit object is one the contemplation of which ought to give rise to a state of mind which is good.

- John Maynard Keynes

Figure 1 - Bank in Kingston, PA Designed by Peter Bohlin (AIA Gold 2010) Figure 2 - A Run-Of-The-Mill Bank Branch, Anywhere-Ville, USA

Image Source | Author Image Source | https://tinyurl.com/ycbewt59

Examine the two bank branches above… Is there one that you would prefer to have in your neighborhood?

iii

TABLE OF CONTENTS

LIST OF FIGURES ...... iv

LIST OF TABLES ...... v

ACKNOWLEDGEMENTS ...... vi

PREFACE ...... vii

Chapter 1 Introduction ...... 1

Chapter 2 Literature Review ...... 8

Chapter 3 Methodology ...... 17

Chapter 4 Data ...... 20

Chapter 5 Results ...... 33

Chapter 6 Conclusion ...... 41

Appendix A Cities w/ BDSA By State ...... 45

Appendix B Economic Indicators Used in This Study ...... 64

Appendix C BDSA Dispersal by Zip code ...... 72

BIBLIOGRAPHY ...... 79

iv

LIST OF FIGURES

Figure 1 - Bank in Kingston, PA Designed by Peter Bohlin (AIA Gold 2010) ... ii

Figure 2 - A Run-Of-The-Mill Bank Branch, Anywhere-Ville, USA ...... ii

Figure 3 - Bhimbetka and Daraki-Chattan Cupules (290700,000 BC) ...... 1

Figure 4 - Salvator Mundi by Leonardo da Vinci ...... 4

v

LIST OF TABLES

Table 1 - Pritzker Prize Winners (1979 - 2020) ...... 20

Table 2 - List of Built Works by Pritzker Laureates in the U.S...... 21

Table 3 - U.S. Cities w/ BDSA (Sorted by # BDSA) ...... 33

Table 4 - U.S. States w/ BDSA (Sorted by # BDSA) ...... 38

Table 5 - 170 Cities w/ BDSA v. United States ...... 39

Table 6 - 170 Cities w/ BDSA v. 37 States w/ BDSA ...... 39

Table 7 - 509 BDSA By Building Type ...... 40

Table 8 - 170 Cities by Type (Urban / Rural) ...... 40

vi

ACKNOWLEDGEMENTS

I would like to thank my parents for encouraging me to be curious. Without their commitment to fostering an imaginative spirit at home, I would not look at the world the same way. I would like to thank Dr. Christoph Hinkelmann for exposing me to the world of research.

Without his invisible hand overseeing my thesis, I would have failed to deliver a research project at all. I would like to thank Dr. Randall J. Woolridge for his unwavering support for me throughout college. Dr. Woolridge showed me how to approach work, life and relationships with confidence, humor and respect. I would like to thank Dr. Brian Davis for reinforcing my academic curiosity; for harboring a community of intellectually curious students at Penn State; and for always treating my ideas with dignity and respect. Thank you to my friends, there are many of you, who challenge my point of view and expose me to interesting and wonderful things.

Finally, I would like to thank my sisters. Julia, thank you for showing me how to face the world with compassion. You push me to seek out an understanding of the bigger picture and to never accept other peoples dogma. Katrina, thank you for showing me how to have fun and live for the moment. Because of you both, I wake up every day grateful and happy to be alive.

vii

PREFACE

This paper begins by introducing art as a measurable and economically relevant component of global financial markets. Chapter 2 discusses architecture as a hybrid form of art that serves a clear functional purpose, as well as a secondary purpose as a medium for creative expression, by summarizing a few prominent studies that guide much of the current debate over the economic value of architecture. Chapter 3 describes the methodology for my empirical analysis that addresses two key questions: 1) Where in the United States is signature architecture concentrated? and 2) How do these regional economies stack up against the state and national economies in which they operate? Chapter 4 presents the data gathered for this study without additional commentary. Chapter 5 provides data tables summarizing the key information gleaned from the data in Chapter 4. Chapter 6 discusses the findings and draws conclusions based on the data. In addition, Chapter 6 recommends further research and offers a few concluding thoughts.

The key finding of this paper is that buildings designed by signature architects (BDSA) are concentrated in many of the wealthiest and most-educated cities in the United States, implying that an appreciation for high design ma be a common element of economicall productie societies. Further, the available data strengthens the point made in past studies that the very presence of good architecture helps inspire positive mindsets in people, which can indirectly trickle down into higher achievement and increased local economic productivity.

1

Chapter 1

Introduction

Art has existed in human civilization long before value was a concept entrenched in economic thinking. In fact, the oldest remnants of art, the Bhimbetka and Daraki-Chattan

Cupules, have been dated to around 290 - 700,000 BCE. This period aligns with the earliest fossil evidence of Homo sapiens, which appeared in Africa some 300,000 years ago (Bhimbetka,

2020). These early stone carvings were created and preserved by humans despite their clear lack of functional value. As time progressed, human societies continued to create and preserve art for no reason other than a shared understanding and appreciation for beautiful things. Today, our world is rich in new, contemporary art as well as vast collections of works preserved over the course of human history, dating all the way back to the Daraki-Chattan Cupules so many years ago.

Figure 3 - Bhimbetka and Daraki-Chattan Cupules (290–700,000 BC) 2 However, despite its constant presence in society, contemporary arguments that encourage investment in the arts are resisted by economic thought as well as empirical analysis.

In 2013, for example, research done by analysts at Stanford found that the real annual return of art since 1973 has been 6.5 percent, well below the 10 percent that is often claimed by proponents of the arts as a reliable financial asset (Korteweg et. al, 2013). They found that selection bias, in which the repeat sale of popular pieces is not considered, drove up the historic average annual returns and, when corrected, yielded a real return of 6.5 percent. While this is still an impressive rate of return, well above current interest rates that can be earned on safe assets such as government bonds, it is an aggregate number. This means that, as a whole, art investments may be quite profitable, but one must correctly choose which individual pieces will appreciate, which is no easy feat.

A popular and oft-cited example of this dynamic occurring in the real world is John

Maynard Keynes famous art collection. In 2018, The Wall Street Journal conducted an analysis and found that, in 2018 dollars, J.M. Keynes spent $840,000 to amass an art collection now worth

$99 million, working out to an average annual return of 10.9 percent (Zweig, 2018). However, when they looked beneath the headline numbers, researchers found that only two pieces of art in the 135-piece collection accounted for half of the growth in value of the entire collection. Further, only 10 pieces constituted approximately 91 percent of the collections last measured value.

Keynes and other wealthy art collectors will often note that they do not amass art for purely financial reasons, but rather for a simple, human appreciation for arts incredible beaut. While some investors may get lucky and find that a particular piece of art experiences an enormous rise in value, it is more likely the case that lopsided inconsistent returns, if any at all, will be earned.

While the prices of stocks do not vary significantly based on where they trade, art pieces do not have the same luxury of an active and liquid market hosted on a centralized group of exchanges. In the case of art, the asset markets are highly illiquid, falling to a few one-off 3 auctions for pieces, and investors may be able to buy an asset cheaply, if they are lucky. As a result of this illiquidity, dealers, auction houses and private transactions often prices the same work of art at significantly different prices, depending on the time, buyer, location and number of other factors. Additionally, the process of buying art is expensive, with high commissions and markups paid to the intermediary facilitating the sale of the piece. However, while the prices and return on art as an investment is more often less than desirable, strict financial measures fail to capture the psychic value of living a life surrounded by history and beauty. In much the same way with architecture, stakeholders must acknowledge that, in the end, the psychic value of living in the presence of beautiful architecture is the only return one can consistently count on.

However, as will be argued throughout this paper, I believe the financial community is misrepresenting arts value, specifically architecture, by overemphasizing financial value as the key data point when assessing the value of art and architecture in society. Logical actors call investment in the arts superfluous, implying that there are other more productive fields, such as energy, education, healthcare, infrastructure, or technology, that ought to command investment before the arts. And return on investment in the arts is not much better, as is evidenced above.

The reality, though, is that artistic activity is higher in productive economies and tends to indicate a more progressive and innovative society. In 2007, Florida and Melander studied communities with large bohemian populations, defined as every individual employed in arts, design, entertainment and media occupations. The authors concluded that communities with higher bohemian populations enjoy an aesthetic-amenity premium and an open culture premium due in part to their large artistic communities, which was found to have a substantial direct positive correlation with housing values, as well as with regional income, wages, technology and human capital (Florida, Mellander 2007).

The perceived value of art in the modern world is significant. And while assigning an economic value to art is difficult, there is a shared human understanding of the value of the arts, 4 demonstrated b our societs infatuation ith the creatie pursuits as mediums for entertainment, academic study, and enormous financial investment. To call investment in the arts superfluous, then, is a mistake. The preservation of art throughout human history, as well as modern research demonstrating the vibrant economies associated with artistic cities, makes clear that art has a dynamic effect on its local environment.

The value of art is determined by a combination of often intangible factors. Why did

Salvator Mundi sell for $450 million at Sothebs in 2017 (Blostein, Libetti, & Crow, 2018)?

You can be assured it is not just the oil paints used, or the parchment, or the frame, but rather a combination of attributes including (most notably) the reputation of its creator, Leonardo Da

Vinci, as well as its innovative use of light, shade and shadow to create a figure that seems alive on the canvas. Abiding by the assumption that art will stay relevant long into the future, collectors view art as a passive form of diversification and a reasonable store of value to combat inflation and earn a return over the long term.

Figure 4 - Salvator Mundi by Leonardo da Vinci

5 Hoeer, the argument remains that in the moment, art offers little to societ in terms of real economic value. A painting, sculpture, or beautiful piece of architecture cannot always feed a village and does not translate to predictable rises in income, local GDP growth, or other discernible economic improvement. However, this conclusion ignores an important reality: that the development of the arts has a noticeable connection to the health and wealth of a society. The proliferation of art is often a reflection of the strength and values of a society at a point in time.

Man of histors greatest artists came to prominence in powerful economic systems, where excess capital was available to fund endeavors that sought to achieve something greater than basic human survival. But does this mean great art only appears as a byproduct of economic growth? Not necessarily. The potential for excellence exists in all people. However, the reality is that an economically downtrodden society rarely has the spare resources needed to support the deelopment of the arts. When ones primar focus is here the net meal ill come from, it is difficult to find the time or energy necessary to create.

This helps explain why great renaissance artists were concentrated in a few small cities in

Italy, for example. The inhabitants of fifteenth-century Florence included Brunelleschi, Ghiberti,

Donatello, Masaccio, Filippo Lippi, Fra Angelico, Verrocchio, Botticelli, Leonardo, and

Michelangelo. These ten artists, considered to be among the greatest in human history, all lived and worked in Renaissance Italy, primarily in the city of Florence, during the same general time period. Based on this and other historical and modern examples, it can be argued that good design occurs in chunks of time, guided by geographical proximity. During the fifteenth century, Milan was about as big as Florence. Yet there are few world-renowned Milanese artists from this period.

Florence at this time already had a connected community of incredibly talented individuals working on similar problems, in this case, art, architecture and design. At that time, a promising artist had a significantly greater chance of finding success simply by being born and brought up in 6 Florence instead of Milan, where their skillset could be nurtured by the vibrant artistic community already in place.

These artists found themselves in a vibrant society that aggressively funded their artistic pursuits, benefiting greatly from the social and economic infrastructure laid by the Romans. This environment ensured the artists had the necessary financial support to develop into the masters we no recognie them as. This instance sparks a fundamental question about the arts: is a regions artistic economy a byproduct of a strong economy and thus an indulgent response to innovation and growth achieved within other fields? Or can investment in the arts itself jumpstart an economy and provide the cultural and environmental influences necessary to spur local innovation and economic growth? In other words, was Florence so wealthy, and thus able to fund the arts, thanks to, in part, an innovative and entrepreneurial social mindset that was encouraged by the artistic community? Or was the explosion of the arts only a happy after-effect of an industrious economy? Which came first? The chicken or the egg?

While it is true that mobility today is much higher than fifteenth century Italy, it is still the case that much of the great creative work is being done in a few hotspots around the world, such as Berlin, New York City, Cambridge, London and Silicon Valley. For anyone interested in leading-edge technological development, biomedical research, great writing, or great visual arts, they would find difficulty in perfecting their craft working in isolation, removed from these creative centers. In the same way that these creative communities prosper by grouping talented individuals together in one geographic proximity, they also cement their status as innovative and creatively important societies through the construction of signature architecture. We will find in this study that signature architecture is overwhelmingly concentrated in those U.S. cities which are already known for being the cultural, political and economic centers of the country (Table 3).

This thesis attempts to explore the concept of art, specifically fine architecture, as an agent of economic change. This paper supports arguments that favor investment in the arts by 7 demonstrating, through a study of award-winning architects in the United States, that the presence of signature architecture in a regional economy will often be correlated with above-average economic conditions, specifically measured by a more racially diverse population; a more educated population; higher earning households and individuals; higher percentage of working adults; and higher housing values and gross rents. The goal of this paper is to demonstrate that thoughtful design can spark economic groth b acting as a conduit for knoledge transfer across firms and industries, creating a multiplier effect of sorts (Curried, 2006, 2007) that has a spillover effect, resulting in improving the surrounding economy. My research tests the ability of signature architects to help facilitate urban regeneration through the design and development of flagship buildings. More specifically, I analyze what economic characteristics are associated with regions with high concentrations of buildings-designed-by-signature-architects (BDSA). My hope is to gather data that lends to the argument that the symbolic presence of a signature architects built works can itself indirectly spark urban regeneration and local innovation, which translates into higher wages, education levels, property values and more civilians in the labor force, by attracting and encouraging innovative thinkers to a regional area. This papers overarching goal is to further inform the debate over whether buildings-designed-by-signature-architects (BDSA) should be considered premium assets that are uniquely valuable when compared to the masses of repetitive human structures that dominate much of the built environment in the United States, by looking at how their surrounding economies trend and compare to state and national averages for the U.S.

8 Chapter 2

Literature Review

The following review is focused on authors who study art or architecture in a strictly economic context. I only briefly discuss the gentrification of neighborhoods that is inevitably associated with urban development. Nor do I spend much time discussing the underlying systems that allow architecture to be realized at all, such as institutional coordination, large checkbooks, and an intensely focused group of designers, engineers, investors, inhabitants and owners. The reality is that there a diversity of factors at play in any architectural development scenario, and a variety of stakeholders. To summarize the relevance of architecture to all stakeholders, and to weigh the pros and cons of architectural development at all, is beyond the scope of this paper. My focus, instead, is on assessing the works of architecture we are lucky enough to already have built in the United States, and provide context that helps describe the economic zones in which these buildings reside.

In this section, I will present research that demonstrates that there are positive externalities associated with high-amenity regions, including their role in attracting educated populations which results in higher concentrations of human capital and subsequent economic innovation, and that this cycle drives up local wages, property values, and quality of life in a regional area, resulting in a self-sustaining cycle of growth and innovation. Studies have shown that cities with high-artistic character have more established networks of artistic and creative individuals, who act as conduits for knowledge transfers across firms that result in new ideas, commercial innovation and income growth (Florida, Mellander 2009).

The body of literature analyzing the value of art is significant. There are a variety of ways an author can go about defining art, alue and societ. For the purpose of this study, I have chosen to focus on architecture because buildings have an ingrained functional use which 9 prescribes them a clearer economic context than other visual and creative arts, such as painting, sculpture or multimedia work. I view architecture as a hybrid form of art that serves a clear functional purpose as a built environment, but also a secondary purpose as a medium for creative expression. According to Fuerst, McAllister and Murray, architecture can be said to occupy a middle position between pure use value and pure aesthetic value (Fuerst et al 2011). When acquiring real estate assets designed by signature architects, investors are buying both the rights to future income streams and, what many may perceive to be, a work of art (Fuerst et al 2011).

Defining Design

The first step in discussing how design impacts regional economies is to define design clearly. According to Julier, design is the link between the circuits of production, which includes manufacture, materials, and technologies, as well as marketing, advertising and distribution, with consumption, which includes use, ownership and meaning (Julier 2000). The designer is tasked with taking the tools of production and deploying them in a satisfying way that meets the needs of consumption. Cultural economies describe regions where this interplay between production, consumption and design is recognized and celebrated (McRobbie 1999) and is characterized by locales that are innovative and adaptive. In this study, I hypothesize that cities with high concentrations of BDSA have stronger cultural economies, and should therefore expect to record more economically productive, racially diverse, and employed populations, as well as higher housing values and gross rents, when compared to state and national averages for the U.S.

Local Design Spillover

These cultural economies have been subject to analysis. A number of researchers have demonstrated that bohemian (artistic and gay) populations act as urban pioneers and that their location choices tend to result in positively appreciating housing values (Castells, 1983; Ley 10 1994; Zukin, 1995; Smith, 1996). The basic thinking reasons that locations that attract artistic populations will have amenity, authenticity and aesthetic value and thus will command a premium for their cultural amenities, neighborhood character and aesthetic quality of the housing stock. As artists and bohemians themselves produce amenities, their location will directly reflect higher levels of amenities. Thus, where artists and bohemians live can be expected to have an aesthetic amenity premium which translates into higher housing values, local wages and other positive economic indicators (Florida, Mellander 2009)

Secondly, locations with higher concentrations of artists and bohemians enjoy a tolerance, or open-culture, premium. Local economies receive a number of benefits from open- cultures, including reduced barriers to entry for human capital; increased efficiencies of knowledge spillovers; promotion of self-expression and idea generation; and decreased friction facing the mobilization of resources for entrepreneurs (Florida, Mellander 2009). In this study, I consider the presence of signature architecture to be a comparable metric to the Bohemian-Gay

Index created by Florida and Mellander, and thus a factor that contributes to the amenity and open-culture premium that appears in economically innovative societies, as is measured and described in past studies (Florida, Mellander 2009).

Design Led Urban Regeneration

Flagship buildings are premier real estate assets often located in highly visible city centers meant to visually symbolize urban growth. It is normal practice for private developers, foundations, universities, medical systems, local governments, businesses and other wealthy patrons to commission high-profile architects to design flagship buildings in city centers to spur economic and social regeneration. However, according to Bell and Jayne (2003), exactly how these buildings translate into urban regeneration is a fu concept (Bell et al 2003). According to multiple authors, there is little consensus about what strictly defines design-led urban 11 regeneration, sustainable design policy or design economy, and it is not made clear what factors must be present for successful urban regeneration.

Bilbao Case Study

It is not uncommon for flagship building efforts to turn out to be flops. However, a notable positive outcome which must be mentioned occurred in Bilbao, Spain, where Pritzker

Prize winning architect Frank Gehry designed the Guggenheim museum. The positive results, as evidenced by high metrics for isitors numbers (1 million+ per year) and a resulting economic uplift due to tourism and increased media coverage, was imitated by multiple cities around the globe (Plaza 2006). According to Juan Ignacio Vidarte, the museums director, the flagship building was meant from the beginning to be a transformational project to turn around an industrial city in decline, and it did just that (Plaza 2006). But folloing the buildings unique success, a building boom around Spain was initiated, with multiple cities constructing similar, curvy contemporary buildings, which ultimately failed to spark the same regeneration. What then, was different about Bilbao? And how can its lessons be applied to the broader idea of urban regeneration through flagship architecture?

Beatriz Plaza explores these questions and notes that the case of Bilbao, while successful, should not be uncriticall replicated elsehere (Plaa 2006) due to the high risks inoled in the development project. With Bilbao specifically, much of the success can be attributed to the

Museum Directors effort to offer innoatie actiities to keep the publics interest and maintain an inflow of tourists to the area. Where variations of this factor, as well as other local conditions unrelated to the Guggenheim itself, exist, urban regeneration is more difficult to predict.

However, the author warns that such success stories should not be employed as a whitewashed justification for signature architecture or other extreme investments.

12 Economic / Financial Concepts

According to Fuerst, the equilibrium values for the future income streams of real estate assets are tied to economic fundamentals such as construction costs, demand, and cost of capital.

However, the work of architecture as art does not have the same basis for estimating equilibrium values since it is arguably immersed in a more diverse and complex system of values (Fuerst

2009). Objectively speaking, the building has a number of purely economic attributes, including development costs, construction costs, financing, leasing period, professional design fees, operating costs, utilities, maintenance, repair, occupation operating costs, rental productivity, energy efficiency, holding costs, vacancy periods, management costs, depreciation, and finally financial return associated with the buildings rent or sale alue. Hoeer, the ork of architecture also has a number of intangible attributes which can generate positive externalities.

These include the possibility that neighboring properties can command higher rents and prices due to proximity to signature architecture; a quality of exterior appearance which can generate positive spillover effects in its general vicinity by acting as a premium view for neighboring parties; and finall the pschic alue the building ma produce, hich describes the increased sense of utility from positive perceptions of the building by the local public, which may result in a higher willingness to pay to inhabit or purchase the building by occupants and investors.

Understanding Market Participants

According to Fuerst et all, 2011, there are three main categories of market participants in any architectural development: owners / investors, occupants, and neighbors. The first group is owners and investors. These parties are primarily concerned with investment performance driven by changes in capital and rental values of the developed property. The architect influences a number of factors that are relevant to the owners and investors. First, the architect can affect the development and operating costs of the building by efficiently coordinating construction crews, 13 lighting and structural engineers, electricians, plumbers and other human capital, as well as helping to plan for and navigate local zoning and building code laws. In addition, the architect can help save time and money by ensuring the construction project secures the necessary building permits and other legal clearances required through a unique local knowledge of the law, relationships with municipal agents, and the foresight necessary to design a building in such a way so that it is legal to construct and easy-to-follow the blueprints for the human capital inoled in its construction. The buildings risk premium will be influenced by all the above factors leading up to the unveiling of the building, as well as the quality of the building itself.

For investors, property class is an important consideration because each class, ranging from Class A to Class C, represents different levels of risk and return. Investors use these differences in property class types to consider how any single property fits within their overall strategy of investing, such as return objectives and the amount of risk they are willing to accept in order to achieve the returns they seek. Class A to Class C property classifications reflect different levels of risk and return because the properties are grouped into class buckets according to a combination of both geographical and physical characteristics. The letter grades that are assigned to properties consider a combination of factors, such as age of the property, location of the property, tenant income levels, growth prospects, appreciation, amenities, and rental income.

According to (Fuerst et all, 2011) a capital provider in commercial real estate markets recognizes the higher relative risk-adjusted returns from good design, described above, that would provide an incentive to allocate resources to well-designed buildings. In my own study, I do not consider property class of each building, but the majority of the buildings in my list would be considered

Class A properties (Table 2).

The second ke group of stakeholders are the buildings occupiers. In almost every built setting that is not a private residence, the occupiers of the building are primarily concerned with the relative costs of maintaining residence in the building as well as the performance of their 14 business or service within the building. The architect can create potential benefits for occupants in three primary ways. The first is by reducing the gross costs of occupying a building.

Increasingly architecture is adopting a mindset rooted in sustainable building practices, where elements of design such as energy efficiency, water capture, efficient waste management and carbon neutrality guide the design process. This is a relatively new trend in construction, arising as a response to the precipitous state of the global climate. According to architecture2030.org, a non-profit research agency, buildings generate nearly 40% of global GHG emissions and approximately two thirds of the building area that exists today will still exist in 2050. As such, it is paramount that existing building renovations and new construction are done in a way that is environmentally sustainable. Luckily for building occupiers, environmentally-sustainable buildings tend to be lower cost to maintain, due to their ability to generate electricity, conserve waste, collect and distribute water, and generally operate in a passive way that requires less electricity and general utility spending.

Second, occupiers benefit from well-designed spaces through higher productivity associated with a well-planned building, such as ease of access to the building, available work space, appropriate interior spaces to suit the needs of occupants, and various inspirational common spaces to encourage collaboration and innovation among residents. Third, occupants of these buildings gain image benefits. It is no coincidence that the buildings in this study are overwhelmingly occupied by foundations, corporations, governments and other prominent societal actors. These parties all benefit from being associated ith high-design, hich signals their ability to plan and execute for the future and consider the small details that add up to a quality work of design. By inhabiting beautiful architecture, occupants communicate to the world that they hold themselves to the same standard of work as that which underlies the very building in which they reside. 15 Finally, the third primary group of stakeholders are neighbors. These parties experience positive externalities that are generated by real estate assets designed by signature architects. It is this third group of stakeholders that drive the central research question of this thesis: What do the surrounding economies of buildings-designed-by-signature-architects look like? In one study of the local economic impact of museums in four U.S. neighborhoods, Sheppard finds that properties nearest to the museums in his study increase in value between 20 and 50 percent, with the effect tapering off as the distance from the museum increases (Sheppard, 2013). Sheppard accomplishes this study by creating a hedonic regression model used to study the impact of a number of factors that affect housing prices, such as the price itself, the date of sale, the geographic location, and other structure and lot characteristics.

Various authors, such as Fuerst et al, 2009, 2011 and Vandell, 1989, conducted studies that show clear rental and transaction premiums associated with office buildings designed by signature architects. These authors again choose to focus on building-specific cost data, whereas I ignore this data and focus instead on the regional economic indicators for the cities that contain the buildings themseles. These authors demonstrated that there is a quantifiable marketing

eight that architects build up oer a career of inolement ith certain high profile building projects. In one instance in 1986, world-famous architect Frank Lloyd Wright described his clients as paing additional costs to commission him because he as proiding a record of economic as ell as creatie achieement (Wright, 1986, page 154).

Gentrification vs. Social Good

No discussion of urban regeneration can avoid the topic of gentrification. Gentrification is the process of renovating and improving a house or district so that it conforms to middle class taste. Flagship buildings and urban regeneration efforts often push out low-income residents and can contribute to increases in regional inequality. Pritzker Prize winning architect Jean Nouvel 16 describes on his website the key challenge of receiving a flagship commission. He states, [t]he great temptation is to build a heroic milestone hich makes ou forget the neighboring buildings

eaknesses. But that attitude ould be to use the neighbors eaknesses as an assertion.

(LACMA, 2020). One of the reasons why Tadao Ando, another Pritzker Prize winner, is called a rare architect is his active commitment to social activities that go beyond the framework of architecture. Underling Andos, Nouels and man other Pritker architects dierse actiities is a sensitivity that seeks to involve citizens in the architecture that is created in a city, rather than further the divide between the haves and the have-nots. These architects (Table 1) stand out due to a shared philosophy of not just designing beautiful buildings, but actively working to raise the area in which they build to new heights of cultural involvement, innovation and inclusivity for all regional residents. In summary, we find in the study that the list of 509 buildings under analysis are overwhelmingly public-good buildings, primarily cultural and educational, as well as commercial spaces open to the public, healthcare facilities that serve the public, and open-air facilities that serve to protect and honor the natural identity of a place (Table 7).

17 Chapter 3 Methodology

I start by defining signature architecture as any building in the United States designed by a Pritzker Prize winning architect. While the award was first granted in 1979, the list of buildings goes back to 1942, in respect for the fact that the Pritzker prize is awarded after the architect has already completed a substantial quantity of built work. Due to the collaborative nature of the work that underlies architecture and building construction, it is impossible to assign any building to one single architect. So, while the name of the architect guides the selection of buildings in this dataset, the sample of 509 buildings is made up of (almost) every U.S. building designed by the firms of Pritzker Prize winning architects from 1979 2020 (see Table 1).

In the world of real estate development, the name of a Pritzker Prize laureate adds instant value to a building before it is built, and justifiably so. These buildings become dramatic additions to the citys skyline by setting new standards of recognition for previously overlooked areas and serving as newfound status symbols for occupants, neighbors and building owners.

Inside the Pritzker Prize laureates' designs, one can expect to find high attention to detail, top-of- the-line appliances and finishes, and interior spaces that live up to the reputation of the building and architect. Due to the expected high qualit of Pritker laureates ork, it is safe to assume that the buildings and interiors listed in Table 2 all achieve a relatively equal level of quality design.

I then identify 170 census-designated cities that contain the 509 buildings in Table 2.

These cities are the smallest possible geographic areas that contain BDSA and are classified as census-designated areas. This ensures consistency in the availability of economic data. I then gather 13 data points for each city, as well as for each of the 37 states in which the 170 cities reside, as well as the same 13 data points for the United States overall. A summary of the key economic indicators and their reason for selection can be found immediately below. Included in 18 APPENDIX B are the precise details describing how each data point is calculated by the U.S.

Census, with text descriptions inserted directly from census.gov/quickfacts page. To stay in a reasonably focused scope, I focus this study on buildings in the U.S. market only.

After gathering the list of buildings, I create a table of the 170 cities, ranked from most

BDSA to least BDSA, and then do the same for the 37 states. After assembling the 13 data points per city and per state (not included in this study; for summaries see APPENDIX A), I take an aerage of each economic indicator, eighting each cits contribution to the aerage first b total number of BDSA, and then by population for a sanity check. I then compare these weighted averages to the same indicators for the U.S. economy as a whole (Table 5) and against the 37 states, weighted by population, in which the BDSA reside (Table 6). I also create 37 state-level data tables (APPENDIX A) which compare the BDSA-weighted average of each economic indicator for the city or cities within a given state to the overall state average. This allows me to measure the economic averages of any group of BDSA-designated cities and then compare those averages to the state economy in which the cities with BDSA reside.

I then create a table summarizing the mix of 509 BDSA classified by building type

(Table 7). Finally, I create a table summarizing the mix of 170 BDSA-designated cities by type

(Urban / Rural). I define Urban as a population per square mile greater than or equal to 1000 persons, per U.S. census methodology.

19

KEY ECONOMIC INDICATORS (SEE APPENDIX B FOR MORE DETAIL)

Average Population Used to determine the # of people in each MSA and State Persons under 18 years, percent Used to determine the # of working age persons in each MSA and State Persons 65 years and over, percent Used to determine the # of working age persons in each MSA and State White alone, percent Used to determine the level of racial diversity in each MSA and State Owner-occupied housing unit rate, 2014 – 2018 Used to determine the number of home-owners in each MSA and State Median value of owner-occupied housing units, 2014 – 2018 Used to determine the average property values in each MSA and State Median Gross Rent, 2014 – 2018 Used to determine the average property values in each MSA and State High school graduate or higher, percent of persons age 25+ years, 2014 – 2018 Used to determine the education level of the population in each MSA and State Bachelor's degree or higher, percent of persons age 25+ years, 2014 – 2018 Used to determine the education level of the population in each MSA and State In civilian labor force, total, percent of population age 16+ years, 2014 – 2018 Used to determine the overall employment level of each MSA and State Median household income (in 2018 dollars), 2014 – 2018 Used to determine the average wealth of the population in each MSA and State Per capita income in past 12 months (in 2018 dollars), 2014 – 2018 Used to determine the average wealth of the population in each MSA and State Persons in poverty, percent Used to determine the average wealth of the population in each MSA and State Population per square mile, 2010 Used to determine the population density of each MSA and State

20 Chapter 4

Data

Table 1 - Pritzker Prize Winners (1979 - 2020)

*Indicates multiple award winners in the same year YEAR FIRST LAST BDSA FIRM BIOGRAPHY

2020 Yvonne * Farrell 0 Grafton Architects Biography

2020 Shelley* McNamara 0 Grafton Architects Biography

2019 Arata Isozaki 6 Arata Isozaki & Associates Biography

2018 Balkrishna Doshi 0 Vastushilpa Consultants Biography

2017 Rafael* Aranda 0 RCR Arquitectes Biography

2017 Carme* Pigem 0 RCR Arquitectes Biography

2017 Ramon* Vilalta 0 RCR Arquitectes Biography

2016 Alejandro Aravena 1 Elemental S.A. Biography

2015 Frei Otto 0 Atelier (Frei Otto) Warmbronn Biography

2014 Shigeru Ban 5 Shigeru Ban Architects Biography

2013 Toyo Ito 0 Toyo Ito & Associates Biography

2012 Wang Shu 0 Amateur Architecture Studio Biography

2011 Eduardo Souto 0 Souto Moura Arquitectos Biography

2010 Kazuyo* Sejima 2 SANAA Biography

2010 Ryue* Nishizawa 0 SANAA Biography

2009 Peter Zumthor 1 Peter Zumthor & Partner Biography

2008 Jean Nouvel 5 Ateliers Jean Nouvel Biography

2007 Richard Rogers 3 Rogers Stirk Harbour Biography

2006 Paulo Mendes da Rocha 0 - Biography

2005 Thom Mayne 32 Morphosis Biography

2004 Zaha Hadid 2 Zaha Hadid Architects Biography

2003 Jern Utzon 0 Utzon Associates Architects Biography

2002 Glenn Murcutt 0 OZ.E.TECTURE Biography

2001 Jacques* Herzog 12 Herzog & De Meuron Biography

2001 Pierre* De Meuron 0 Herzog & De Meuron Biography

2000 Rem Koolhaas 9 OMA Biography

1999 Norman Foster 31 Foster + Partners Biography

1998 Renzo Piano 18 Renzo Piano Workshop Biography

1997 Sverre Fehn 0 - Biography

1996 Rafael Moneo 10 Rafael Moneo Arquitecto Biography

1995 Tadao Ando 9 Tadao Andoand Associates Biography

1994 Christian de Portzamparc 3 2Portzamparc Biography

1993 Fumihiko Maki 7 Maki and Associates Biography

1992 Alvaro Siza 0 Alvaro Leite Siza Biography

1991 Robert Venturi 79 VSBA Architects & Planners Biography

1990 Aldo Rossi 4 Fondazione Aldo Rossi Biography

1989 Frank Gehry 47 Gehry Partners, LLP. Biography

1988 Gordon* Bunshaft 19 Skidmore, Owings & Merrill Biography

1988 Oscar* Neimeyer 0 Skidmore, Owings & Merrill Biography

1987 Kenzo Tange 1 Tange Associates Biography

1986 Gottfried Boehm 0 - Biography

1985 Hans Hollein 1 Hans Hollein & Partner Biography

1984 Richard Meier 64 Richard Meier & Partners Biography

1983 I.M. Pei 52 Pei Cobb Freed & Partners Biography

1982 Kevin Roche 51 Roche Dinkeloo Biography

1981 James Stirling 3 Stirling / Wilford Partnership Biography

1980 Luis Barragan 0 - Biography

1979 Philip Johnson 32 PJAR Architects Biography

21

Table 2 - List of Built Works by Pritzker Laureates in the U.S.

CODE YEAR BUILDING TITLE TYPE CITY STA. SKU

2 1986 Museum of Contemporary Art (MOCA) Cultural Los Angeles CA 1

2 1991 Team Disney Building Commercial / Office Orlando FL 2

2 1999 COSI Columbus Cultural Columbus OH 3

2 2009 Collins Park Place Cultural Miami Beach FL 4

2 1986 Bjornson Studio and House Private Residence Los Angeles CA 5

2 1992 Brooklyn Museum Expansion Cultural NYC NY 6

5 2009 Hunt, Le Mans and Johnson Residential Halls Educational Austin TX 7

7 2014 Aspen Art Museum Cultural Aspen CO 8

7 2017 Cast Iron House Private Residence NYC NY 9

7 2006 Sagaponac House Private Residence Suffolk County NY 10 Post-Hurricane Reconstruction Housing (Make It 7 2009 Private Residence New Orleans LA 11

Right)

7 2010 Metal Shutter House Private Residence NYC NY 12

11 2007 New Museum Cultural NYC NY 13

11 2015 Grace Farms Nature Preserve New Canaan CT 14

12 1999 Cloud Rock Wilderness Lodge Nature Preserve Moab UT 15

13 2019 Tour de Verre - 53W53 Residential Tower NYC NY 16

13 2011 Jane's Carousel Cultural NYC NY 17

13 2010 Chelsea 100 11th Avenue Residential Tower NYC NY 18

13 2008 40 Mercer St Residential Tower NYC NY 19

13 2006 Theatre Guthrie Cultural Minneapolis MN 20

14 2019 International Spy Museum Cultural DC DC 21

14 2018 3 World Trade Center Commercial / Office NYC NY 22

14 2009 300 New Jersey Avenue Commercial / Office DC DC 23

16 1981 Sedlack Residence Private Residence Los Angeles CA 24 Commercial /

16 1983 72 Market Street Los Angeles CA 25 Restaurant

16 1984 Lawrence House Private Residence Hermosa Beach CA 26 Commercial /

16 1984 Angeli Restaurant Los Angeles CA 27 Restaurant

16 1986 Leon Max Showroom Commercial / Retail Los Angeles CA 28 Commercial /

16 1986 Kate Mantilini Beverly Hills CA 29 Restaurant

16 1988 Contempo Casuals Retail Store Commercial / Retail Los Angeles CA 30

16 1988 Cedars-Sinai Comprehensive Cancer Center Healthcare Los Angeles CA 31

16 1991 Salick Healthcare Administrative Headquarters Commercial / Office W. Hollywood CA 32

16 1996 FJC Communications Commercial / Office Burbank CA 33

16 1997 Landa Residence Private Residence Man. Beach CA 34

16 1997 Blades Residence Private Residence Santa Barbara CA 35 Commercial /

16 1999 Lutece Las Vegas NV 36 Restaurant

16 1999 SHR Perceptual Management Commercial / Office Scottsdale AZ 37

16 1999 International Elementary School Educational Long Beach CA 38 Commercial /

16 1999 Tsunami Asian Grill & Sushi Las Vegas NV 39 Restaurant 22

16 1999 Diamond Ranch High School Educational Pomona CA 40

16 2004 Dr. Theodore Alexander Science Center School Educational Los Angeles CA 41

16 2005 University of Cincinnati Campus Recreation Center Educational Cincinnati OH 42

16 2005 NOAA Satellite Operation Facility Governmental Suitland MD 43

16 2005 Caltrans District 7 Headquarters Governmental Los Angeles CA 44

16 2006 Wayne Lyman Morse United States Courthouse Governmental Eugene OR 45

16 2007 San Francisco Federal Building Governmental San Francisco CA 46 Cahill Center for Astronomy and Astrophysics at 16 2008 Educational Pasadena CA 47

Caltech

16 2009 41 Cooper Square Educational NYC NY 48

16 2009 FLOAT House Private Residence New Orleans LA 49 Commercial /

16 2012 Clyde Frazier's NYC NY 50 Restaurant

16 2012 Perot Museum of Nature and Science Cultural Dallas TX 51

16 2014 Bill and Melinda Gates Hall Educational Ithaca NY 52

16 2014 Emerson College Los Angeles Center Educational Los Angeles CA 53

16 2016 Taubman Complex at Lawrence Tech Educational Southfield MI 54

16 2017 Bloomberg Center at Cornell Tech Educational NYC NY 55

17 2003 Lois & Richard Rosenthal Center Cultural Cincinnati OH 56

17 2012 Eli & Edythe Broad Art Museum Cultural East Lansing MI 57

20 2018 Leroy Street Residential Tower NYC NY 58

20 2017 215 Chrystie Hotel NYC NY 59

20 2018 Jade Signature Residential Tower Sunny Isles FL 60

20 2012 Parrish Art Museum Cultural Southhampton NY 61

20 2013 Perez Art Museum Miami Cultural Miami FL 62

20 2016 Park Avenue Armory Governmental NYC NY 63

20 2010 1111 Lincoln Road Commercial / Retail Miami Beach FL 64

20 2007 40 Bond Residential Tower NYC NY 65

20 2002 Prada Headquarters Commercial / Office NYC NY 66

20 2005 Walker Art Center, Expansion Cultural Minneapolis MN 67

20 2005 De Young Museum Cultural San Francisco CA 68

20 1998 Dominus Winery Nature Preserve Napa Valley CA 69

21 2009 Dee and Charles Wyly Theater Cultural Dallas TX 70

21 2003 IIT McCormick Tribune Campus Center Educational Chicago IL 71

21 2002 Lehmann Maupin Gallery Cultural NYC NY 72

21 2011 Milstein Hall Cornell University Educational Ithaca NY 73

21 2004 Prada Epicenter Los Angeles Commercial / Retail Los Angeles CA 74

21 2001 Prada Epicenter New York Commercial / Retail NYC NY 75

21 2004 Seattle Central Library Educational Seattle WA 76

21 1999 Second Stage Theatre Cultural NYC NY 77

21 2019 121 East 23rd Street Residential Tower NYC NY 78

22 2018 100 E 53rd St Residential Tower NYC NY 79

22 2018 Apple Park Commercial / Office Cupertino CA 80

22 2019 Sheila and Eric Samson Pavilion Educational Cleveland OH 81

22 2019 Norton Museum of Art Cultural W. Palm Beach FL 82

22 2019 Apple Carnegie Library Commercial / Retail DC DC 83

22 2019 Apple Aventura Commercial / Retail Aventura FL 84

22 2019 Apple Fifth Avenue Commercial / Retail NYC NY 85 23

22 2019 Four Seasons Hotel at Comcast Technology Center Hotel Philadelphia PA 86

22 1994 Addition to Joslyn Art Museum Cultural Omaha NE 87

22 2000 Center for Clinical Science Research Educational Stanford CA 88

22 2003 James H. Clark Center Educational Stanford CA 89

22 2004 Asprey Store Commercial / Retail NYC NY 90

22 2006 Hearst Tower Commercial / Office NYC NY 91

22 2007 Smithsonian Institution Courtyard Governmental DC DC 92

22 2008 John Spoor Broome Library Educational Camarillo CA 93

22 2009 Winspear Opera House Cultural Dallas TX 94

22 2010 Sperone Westwater Cultural NYC NY 95

22 2010 Museum of Fine Arts Cultural Boston MA 96

22 2014 Spaceport America Governmental Truth or Con. NM 97

22 2014 Edward P. Evans Hall Educational New Haven CT 98

22 2014 CityCenterDC Mixed-Use DC DC 99

22 2015 Porcenalosa New York Flagship Store Commercial / Retail NYC NY 100

22 2015 Faena House Residential Tower Miami Beach FL 101

22 2015 United Nations Plaza Residential Tower NYC NY 102

22 2016 University of Iowa Stead Family Children's Hospital Healthcare Iowa City IA 103

22 2016 Apple Union Square Commercial / Retail San Francisco CA 104

22 2017 Steve Jobs Theater Cultural Cupertino CA 105

22 2017 R/GA Commercial / Office NYC NY 106

22 2017 Apple Park Visitor Center Commercial / Office Cupertino CA 107

22 2017 Apple Michigan Avenue Commercial / Retail Chicago IL 108

22 2017 551 W 21st St Residential Tower NYC NY 109

23 1986 The Menil Collection Cultural Houston TX 110

23 1995 Cy Twombly Gallery Cultural Houston TX 111

23 2003 Nasher Sculpture Center Cultural Dallas TX 112

23 2005 High Museum of Art Expansion Cultural Atlanta GA 113

23 2006 The Morgan Library & Museum Expansion Cultural NYC NY 114

23 2007 The New York Times Building Commercial / Office NYC NY 115

23 2008 California Academy of Sciences Rebuilding Cultural San Francisco CA 116

23 2009 Nichols Bridgeway Cultural Chicago IL 117 Modern Wing expansion of the Art Institute of 23 2009 Cultural Chicago IL 118

Chicago

23 2012 Isabella Stewart Gardner Museum Wing Cultural Boston MA 119

23 2013 Kimbell Art Museum Expansion Cultural Fort Worth TX 120

23 2014 Harvard Art Museums Expansion and Renovation Cultural Cambridge MA 121

23 2015 Whitney Museum of American Art Cultural NYC NY 122

23 2010 Private Home in Colorado Private Residence Rockies CO 123

23 2010 The Resnick Pavilion Cultural Los Angeles CA 124

23 2016 Jerome L. Greene Science Center Educational NYC NY 125

23 2017 Lenfest Center for the Arts Educational NYC NY 126

23 2018 The Forum Educational NYC NY 127

25 2014 Princeton Neuroscience Institute Educational Princeton NJ 128

25 2010 Laboratories Building for Columbia University Educational NYC NY 129

25 2008 Laboratory for Integrated Science and Engineering Educational Cambridge MA 130

25 2008 Chase Center Educational Providence RI 131 24

25 2005 Pollallis House Private Residence Belmont MA 132

25 2002 Cathedral of Our Lady of the Angels Cultural Los Angeles CA 133

25 2002 Spanish Ambassador's Residence in Washington Private Residence DC DC 134

25 2000 Audrey Jones Beck Building Cultural Houston TX 135

25 2002 Addition to Cranbrook Academy of Art Museum Educational Bloomfield Hills MI 136

25 1993 Davis Museum Cultural Wellesley MA 137

26 1997 Eychaner/Lee House Private Residence Chicago IL 138

26 2001 Pulitzer Arts Foundation Cultural St. Louis MO 139

26 2002 Modern Art Museum of Fort Worth Cultural Fort Worth TX 140 Commercial /

26 2005 Morimoto NYC NY 141 Restaurant

26 2009 Tom Ford's Cerro Pelon Ranch Private Residence Santa Fe NM 142

26 2014 Clark Art Institute Expansion / Visitor Center Cultural Williamstown MA 143

26 2018 152 Elizabeth Street Condominiums Residential Tower NYC NY 144

26 2018 Wrightwood 659 Cultural Chicago IL 145

26 2012 Malibu House III United States Malibu Private Residence Malibu CA 146

27 2014 One57 New York Residential Tower NYC NY 147

27 2016 Prism Tower Residential Tower NYC NY 148

27 1999 LVMH Tower Commercial / Office NYC NY 149

28 2013 4 World Trade Center Commercial / Office NYC NY 150

28 2013 51 Astor Place Commercial / Office NYC NY 151

28 2009 The MIT Media Lab Complex Educational Cambridge MA 152

28 2009 UPenn Annenberg Public Policy Center Educational Philadelphia PA 153

28 2006 Sam Fox School of Design and Visual Arts Educational St. Louis MO 154

28 1993 Yerba Buena Center for the Arts Cultural San Francisco CA 155

28 1962 Steinburg Hall Educational St. Louis MO 156 Mount Desert

30 1998 Kamp Kippy Educational ME 157 Island

30 1999 Adventure Aquarium Entrance Cultural Camden NJ 158

30 2012 Allentown Art Museum Cultural Allentown PA 159

30 1993 The Charles P. Stevenson, Jr. Library Educational Ann.-on-Hudson NY 160

30 1996 Barnes Foundation Renovation Cultural Merion PA 161

30 2009 Beth Sholom Synagogue, Visitor Center Cultural Elkins Park PA 162

30 2005 Bryn Mawr College, Campus Center Renovation Educational Merion PA 163

30 1992 Children's Museum of Houston Cultural Houston TX 164

30 2008 Congregation Beth El Cultural Sunbury PA 165

30 2011 Curtis Institute of Music, Lenfest Hall Educational Philadelphia PA 166

30 2002 Dartmouth College, Baker/Berry Library Educational Hanover NH 167 Dartmouth College, Rauner Special Collections 30 2000 Educational Hanover NH 168

Library

30 1990 Dartmouth College, Thayer School of Engineering Educational Hanover NH 169

30 1974 Dixwell Fire Station Governmental New Haven CT 170

30 2005 Dumbarton Oaks New Library Building Educational DC DC 171

30 2007 Dumbarton Oaks, Main House Private Residence DC DC 172

30 2008 Episcopal Academy, Chapel Cultural Newton Square PA 173

30 1968 Fire Station No. 4 Governmental Columbus IN 174

30 1976 Franklin Court Cultural Philadelphia PA 175

30 1964 Guild House Residential Tower Philadelphia PA 176 25

30 2008 Harvard University, Divinity School, Rockefeller Hall Educational Cambridge MA 177

30 1996 Harvard University, Memorial Hall & Loker Commons Educational Cambridge MA 178

30 1999 Historical Society of Pennsylvania Cultural Philadelphia PA 179

30 1969 House in Barnegat Light Private Residence Ocean County NJ 180

30 1990 House in East Hampton Private Residence East Hampton NY 181

30 1985 House in Glen Cove Private Residence Glen Cove NY 182

30 1972 House in Greenwich Private Residence Greenwich CT 183

30 1975 House in Katonah Private Residence Westchester NY 184

30 1983 House in New Castle County Private Residence New Castle DE 185

30 1979 House in Pittsburgh Private Residence Pittsburgh PA 186

30 1989 House in Seal Harbor Private Residence Seal Harbor ME 187

30 1984 House in Stony Creek Private Residence Stony Creek CT 188

30 1977 House in Vail Private Residence Vail Village CO 189

30 1982 Donald A. Petrie House Private Residence East Hampton NY 190

30 1981 Houses on Block Island Private Residence Block Island RI 191

30 1971 Trubek-Wislocki House Private Residence Nantucket MA 192

30 1979 Institute for Scientific Information Commercial / Office Philadelphia PA 193

30 2008 Lehigh Valley Hospital - Cedar Crest Healthcare Allentown PA 194

30 2005 Lehigh Valley Hospital - Muhlenberg Healthcare Bethlehem PA 195

30 2008 LVH - Cedar Crest, CAH, Heart Specialists Healthcare Allentown PA 196

30 2008 LVH - Cedar Crest, CAH, Neuroscience Center Healthcare Allentown PA 197

30 1996 Museum of Contemporary Art Cultural San Diego CA 198

30 2009 Museum Place Post Office Governmental Fort Worth TX 199

30 1976 Oberlin College, Allen Memorial Art Museum Educational Oberlin OH 200

30 2006 Ohio State University, Biomedical Research Tower Educational Columbus OH 201

30 2008 Pembroke North Condominiums Residential Tower Wayne PA 202

30 1976 Pennsylvania Academy of the Fine Arts Exhibition Cultural Philadelphia PA 203

30 1997 Philadelphia Museum of Art, West Foyer Cultural Philadelphia PA 204

30 1985 Philadelphia Zoo, Tree House & Children's Zoo Cultural Philadelphia PA 205

30 1990 Princeton Club of New York Cultural NYC NY 206

30 1990 Princeton University, Fisher and Bendheim Halls Educational Princeton NJ 207

30 2000 Princeton University, Frist Campus Center Educational Princeton NJ 208

30 1983 Princeton University, Gordon Wu Hall Educational Princeton NJ 209

30 1986 Princeton University, Lewis Thomas Laboratory Educational Princeton NJ 210

30 1993 Princeton University, Schultz Laboratory Educational Princeton NJ 211

30 2012 Radcliffe Institute, Fay House Educational Cambridge MA 212

30 2004 Radcliffe Institute, Schlesinger Library Educational Cambridge MA 213

30 1991 Seattle Art Museum Cultural Seattle WA 214

30 2005 Stuart Country Day School, Cor Unum Center Cultural Princeton NJ 215

30 1985 Swarthmore College, Tarble Student Center Educational Swarthmore PA 216

30 2009 The Linceowitz House Private Residence Hudson NY 217

30 2002 Trenton Central Fire Headquarters & Museum Governmental Trenton NJ 218

30 1998 UCLA, GondaNeuroscience & Genetics Lab Educational Los Angeles CA 219

30 1991 UCLA, Gordon & Virginia Macdonald Lab Educational Los Angeles CA 220

30 2006 UCSB, California NanoSystems Institute Educational Santa Barbara CA 221

30 1996 Trabant University Center Educational Newark DE 222

30 2005 University of Kentucky, BBSRB Lab Educational Lexington KY 223 26

30 2005 University of Michigan, Palmer Drive Complex Educational Ann Arbor MI 224

30 1998 University of Michigan, Stadium Improvements Educational Ann Arbor MI 225 University of Pennsylvania, Clinical Research 30 1990 Educational Philadelphia PA 226

Building

30 1991 Fisher Fine Arts Library (Furness Building) Educational Philadelphia PA 227

30 2000 University of Pennsylvania, Perelman Quadrangle Educational Philadelphia PA 228

30 2007 University of Pennsylvania, Vagelos Laboratories Educational Philadelphia PA 229

30 1964 Vanna Venturi House Private Residence Philadelphia PA 230

30 1996 Walt Disney, Celebration Bank Commercial / Office Celebration FL 231

30 1998 Walt Disney, Frank G. Wells Building Commercial / Office Burbank CA 232

30 1994 Walt Disney, Reedy Creek Emergency Services HQ Governmental Orange County FL 233

30 2006 Woodmere Art Museum Cultural Philadelphia PA 234

30 2003 Yale University, Anlyan Center Educational New Haven CT 235

31 1991 ABC Riverside Building Commercial / Office Burbank CA 236

31 2001 Scholastic Corporation Headquarters Commercial / Office NYC NY 237

31 2005 360 Newbury Street Residential Tower Boston MA 238

31 1996 Disney Development Company Office Complex Commercial / Office Celebration FL 239

32 1957 David Cabin Private Residence Riverside CA 240

32 1963 Kline Residence Private Residence Los Angeles CA 241

32 1970 Park West Apartments Residential Tower Irvine CA 242

32 1972 Ronald Davis Studio & Residence Private Residence Malibu CA 243

32 1974 Merriweather Post Pavilion Cultural Columbia MD 244

32 1975 Concord Pavilion Cultural Concord CA 245

32 1977 Harper House Residential Tower Baltimore MD 246

32 1978 Gehry Residence Private Residence Santa Monica CA 247

32 2002 Loyola Law School Educational Los Angeles CA 248

32 1980 Spiller House Private Residence Los Angeles CA 249

32 1980 Santa Monica Place Commercial / Retail Santa Monica CA 250

32 1981 Cabrillo Marine Aquarium Cultural Los Angeles CA 251

32 1984 California Aerospace Museum Cultural Sacramento CA 252

32 1984 Edgemar Retail Complex Commercial / Retail Santa Monica CA 253

32 1984 Norton House Private Residence Los Angeles CA 254 Frances Howard Goldwyn Hollywood Regional 32 1985 Educational Los Angeles CA 255

Library

32 1988 Sirmai-Peterson House Private Residence Thousand Oaks CA 256

32 1989 Yale Psychiatric Institute Educational New Haven CT 257

32 1989 Rockwell and Marna Schnabel House Private Residence Los Angeles CA 258 Herman Miller Factory (now William Jessup

32 1989 Educational Rocklin CA 259

University)

32 1990 McDonnell Douglas Engineering Auditorium Educational Irvine CA 260

32 1991 Chiat/Day (Binoculars) Building Commercial / Office Los Angeles CA 261

32 1991 Artists' Studios Residential Tower Santa Monica CA 262

32 1992 Iowa Advanced Technology Laboratories Educational Iowa City IA 263

32 1993 Frederick Weisman Museum of Art Cultural Minneapolis MN 264

32 1993 University of Toledo Center for the Visual Arts Educational Toledo OH 265

32 1995 Anaheim Ice Athletic Anaheim CA 266

32 1999 University of Cincinnati Academic Health Center Educational Cincinnati OH 267

32 2000 Condé Nast Publishing Headquarters Cafeteria Commercial / Office NYC NY 268

32 2000 Museum of Pop Culture Cultural Seattle WA 269 27

32 2001 Issey Miyake Flagship Store Commercial / Retail NYC NY 270

32 2002 Peter B. Lewis Building Educational Cleveland OH 271

32 2003 Richard B. Fisher Center for the Performing Arts Cultural Ann.-on-Hudson NY 272

32 2003 Walt Disney Concert Hall Cultural Los Angeles CA 273

32 2004 Ray and Maria Stata Center Educational Cambridge MA 274

32 2004 Jay Pritzker Pavilion Cultural Chicago IL 275

32 2004 BP Pedestrian Bridge Governmental Chicago IL 276

32 2007 IAC Building Commercial / Office NYC NY 277

32 2008 Peter B. Lewis Library Educational Princeton NJ 278

32 2010 Lou Ruvo Center for Brain Health Healthcare Las Vegas NV 279

32 2010 Ohr-O'Keefe Museum of Art Cultural Biloxi MS 280

32 2011 New World Center Cultural Miami Beach FL 281

32 2011 New York by Gehry (Beekman Tower) Residential Tower NYC NY 282

32 2012 Pershing Square Signature Center Cultural NYC NY 283

32 2012 Duplex Residence Private Residence New Orleans LA 284

32 2015 Facebook West Campus Commercial / Office Menlo Park CA 285

32 1942 Great Lakes Naval Training Center, Hostess House Governmental Great Lakes IL 286

33 1951 Lever House Commercial / Office NYC NY 287

33 1952 Manhattan House Residential Tower NYC NY 288

33 1953 Manufacturers Hanover Trust Company Building Commercial / Retail NYC NY 289

33 1956 Ford World Headquarters Commercial / Office Dearborn MI 290

33 1957 Connecticut General Life Insurance Headquarters Commercial / Office Bloomfield Hills CT 291

33 1958 Reynolds Metals Company Headquarters Commercial / Office Richmond VA 292

33 1961 28 Liberty Street Commercial / Office NYC NY 293

33 1962 Albright-Knox Art Gallery Cultural Buffalo NY 294

33 1963 Beinecke Library Educational New Haven CT 295 American Republic Insurance Company 33 1965 Commercial / Office Des Moines IA 296

Headquarters

33 1965 NY Public Library for the Performing Arts (Interiors) Educational NYC NY 297

33 1967 140 Broadway Commercial / Office NYC NY 298

33 1971 Lyndon Baines Johnson Library and Museum Cultural Austin TX 299

33 1973 Uris Hall, Cornell University Educational Ithaca NY 300

33 1974 Solow Building - 9 West 57th Street Commercial / Office NYC NY 301

33 1974 W. R. Grace Building Commercial / Office NYC NY 302

33 1974 Hirshhorn Museum and Sculpture Garden Cultural DC DC 303

33 1947 Headquarters of the United Nations Governmental NYC NY 304

33 1990 American Medical Association Headquarters Building Commercial / Office Chicago IL 305

34 1974 Minneapolis Art Complex Cultural Minneapolis MN 306

36 1969 Feigen Gallery Cultural NYC NY 307

37 2000 United States Courthouse Governmental Phoenix AZ 308

37 1986 Ackerberg House Private Residence Malibu CA 309 Commercial /

37 2006 CUT and Sidebar Beverly Hills CA 310 Restaurant

37 2014 Edie and Lew Wasserman Building Educational Los Angeles CA 311

37 2000 Friesen House Private Residence Los Angeles CA 312

37 1995 Gagosian Gallery Cultural Beverly Hills CA 313

37 2003 International Center for Possibility Thinking Cultural Garden Grove CA 314

37 2006 Malibu Beach House Private Residence Malibu CA 315 28

37 1996 Museum of Television & Radio Cultural Beverly Hills CA 316

37 2010 New Pacific Realty Headquarters Commercial / Office Beverly Hills CA 317

37 2004 Painted Turtle Camp Educational Los Angeles CA 318

37 2005 San Jose City Hall Governmental San Jose CA 319

37 2003 Santa Ynez House Private Residence Santa Barbara CA 320

37 2001 Southern California Beach House Private Residence Malibu CA 321

37 1997 The Getty Center Cultural Los Angeles CA 322

37 2006 UCLA Eli & Edythe Broad Art Center Cultural Los Angeles CA 323

37 2012 United States Courthouse, San Diego Governmental San Diego CA 324

37 1989 Bridgeport Center Commercial / Office Bridgeport CT 325

37 1981 Hartford Seminary Cultural Hartford CT 326

37 1967 Smith House Private Residence Darien CT 327

37 2004 Yale University History of Art & Arts Library Building Educational New Haven CT 328

37 2011 Beach House Condominium Residential Tower Miami FL 329

37 1979 House in Palm Beach Private Residence Palm Beach FL 330

37 1998 Neugebauer House Private Residence Naples FL 331

37 2018 The Surf Club Residential Tower Surfside FL 332

37 1983 High Museum of Art Cultural Atlanta GA 333

37 1982 Clifty Creek Elementary School Educational Columbus IN 334

37 1979 The Atheneum Private Residence New Harmony IN 335

37 1984 Des Moines Art Center Addition Cultural Des Moines IA 336

37 1973 Douglas House Private Residence Harbor Springs MI 337

37 2003 Viking Research Center Commercial / Office Starkville MS 338

37 1989 Grotta Residence Private Residence Morris County NJ 339

37 1965 Meier House Private Residence Essex Falls NJ 340

37 2017 Teachers Village Mixed-Use Newark NJ 341

37 2019 1 Waterline Square Mixed-Use NYC NY 342

37 2006 165 Charles Street Residential Tower NYC NY 343

37 2002 173-176 Perry Street Condominium Residential Tower NYC NY 344 Commercial /

37 2003 66 Restaurant NYC NY 345 Restaurant

37 2019 685 First Avenue Residential Tower NYC NY 346

37 2001 Bethel Performing Arts Center Cultural NYC NY 347

37 1977 Bronx Development Center Healthcare Bronx NY 348

37 1988 Cornell University, Alumni & Admission Center Educational Ithaca NY 349

37 2008 Cornell University, Weill Hall Educational Ithaca NY 350

37 2008 Fifth Avenue Apartment Private Residence NYC NY 351

37 2013 Fire Island House Private Residence Suffolk County NY 352

37 2016 Flying Point Residence Private Residence Southampton NY 353

37 1967 Hoffman House Private Residence East Hampton NY 354

37 1971 House in Old Westbury Private Residence Nassau County NY 355

37 2008 IMG World Headquarters Commercial / Office NYC NY 356

37 2006 Joy Apartment Private Residence NYC NY 357

37 2003 Kojaian Apartment Residential Tower NYC NY 358

37 1962 Lambert House Private Residence Suffolk County NY 359

37 1976 Maidman House Private Residence Pt. Washington NY 360

37 2009 On Prospect Park Residential Tower NYC NY 361 29

37 1987 Richard Meier & Partners New York Office Private Residence NYC NY 362

37 1969 Saltzman House Private Residence East Hampton NY 363

37 1974 Shamberg House Private Residence Westchester NY 364

37 1995 Swissair North American Headquarters Commercial / Office Melville NY 365

37 1974 Twin Parks Northeast Housing Residential Tower Bronx NY 366

37 2000 United States Courthouse, Islip Governmental Central Islip NY 367

37 1970 Westbeth Artists’ Housing Residential Tower NYC NY 368

37 1986 Westchester House Private Residence North Salem NY 369

37 1983 Giovannitti House Private Residence Pittsburgh PA 370

37 1996 Rachofsky House Private Residence Dallas TX 371

38 1949 131 Ponce de Leon Avenue Mixed-Use Atlanta GA 372

38 1956 Roosevelt Field Mall Commercial / Retail Garden City NY 373

38 1956 Mile High Center & Denver's Courthouse Square Governmental Denver CO 374

38 1960 William L. Slayton House Private Residence DC DC 375

38 1961 University Apartments Residential Tower Chicago IL 376

38 1972 Cathedral Square of Saints Peter and Paul Cultural Providence RI 377

38 1962 John F. Kennedy Theatre Cultural Honolulu HI 378

38 1962 Hale Manoa Dormitory Educational Honolulu HI 379

38 1963 Kips Bay Plaza Residential Tower NYC NY 380

38 1964 Society Hill Towers Residential Tower Philadelphia PA 381

38 1964 MIT Green Building Educational Cambridge MA 382

38 1964 S.I. Newhouse School of Public Communications Educational Syracuse NY 383

38 1964 Washington Plaza Residential Tower Pittsburgh PA 384

38 1965 The Century Towers Residential Tower Los Angeles CA 385

38 1966 University Village Residential Tower NYC NY 386

38 1967 Pei Residence Halls and Student Union Educational Sarasota FL 387

38 1967 Mesa Laboratory Educational Boulder CO 388

38 1968 Sculpture Wing of the Des Moines Art Center Cultural Des Moines IA 389

38 1968 Everson Museum of Art Cultural Syracuse NY 390

38 1969 Cleo Rogers Memorial Library Educational Columbus IN 391

38 1970 Dreyfus Chemistry Building Educational Cambridge MA 392

38 1971 Wilmington Tower (I. M. Pei Building) Commercial / Office Wilmington DE 393

38 1972 Paul Mellon Arts Center at Choate Rosemary Hall Educational Wallingford CT 394

38 1973 Spelman Halls at Princeton University Educational Princeton NJ 395

38 1973 Herbert F. Johnson Museum of Art Cultural Ithaca NY 396

38 1976 Ralph Landau Chemical Engineering Building Educational Cambridge MA 397

38 1976 Wilson Commons, University of Rochester Educational Rochester NY 398

38 1977 Dallas City Hall Governmental Dallas TX 399

38 1978 East Building, National Gallery of Art Cultural DC DC 400

38 1979 John F. Kennedy Library Educational Boston MA 401

38 1979 One Dallas Center Commercial / Office Dallas TX 402

38 1980 Biltmore Company Building Commercial / Office Asheville NC 403

38 1981 West Wing, Museum of Fine Arts Cultural Boston MA 404

38 1982 Indiana University Art Museum Cultural Bloomington IN 405

38 1982 Texas Commerce Tower Commercial / Office Houston TX 406

38 1982 16th Street Mall Commercial / Retail Denver CO 407

38 1983 Energy Plaza Commercial / Office Dallas TX 408 30

38 1984 Wiesner Building for the Arts and Media Technology Educational Cambridge MA 409

38 1984 IBM Corporate Headquarters (now MasterCard HQ) Commercial / Office Harrison Town NY 410

38 1986 Fountain Place Commercial / Office Dallas TX 411

38 1987 Miami Tower Commercial / Office Miami FL 412

38 1989 Morton H. Meyerson Symphony Center Cultural Dallas TX 413

38 1989 Carl C. Icahn Center for Science Educational Wallingford CT 414

38 1989 Creative Artists Agency Headquarters Commercial / Office Beverly Hills CA 415

38 1991 The Towers at Wildwood Plaza Commercial / Office Atlanta GA 416

38 1992 The Kirklin Clinic at Birmingham Health System Healthcare Birmingham AL 417

38 1993 Four Seasons Hotel New York Hotel NYC NY 418

38 1995 Rock and Roll Hall of Fame Cultural Cleveland OH 419

38 1996 Buck Institute for Research on Aging Educational Novato CA 420

38 2000 Republic of Korea Permanent Mission to UN Governmental NYC NY 421

38 2006 Embassy of the People's Republic of China Governmental DC DC 422

38 1967 Metropolitan Museum of Art Cultural NYC NY 423

39 2013 American Museum of Natural History Cultural NYC NY 424

39 1997 Museum of Jewish Heritage Cultural NYC NY 425

39 1968 The Oakland Museum Cultural Oakland, CA CA 426

39 1993 The Jewish Museum Cultural NYC NY 427

39 1992 Abby Aldrich Rockefeller Folk Art Center Cultural Williamsburg VA 428

39 2004 Zesiger Sports and Fitness Center Athletic Cambridge MA 429

39 2009 David S. Ingalls Hockey Rink Renovation Athletic New Haven CT 430

39 2003 Helen and Martin Kimmel Center for University Life Educational NYC NY 431

39 1971 UMich Power Center for Performing Arts Cultural Ann Arbor MI 432

39 2001 NYU Palladium Building Educational NYC NY 433

39 1973 Wesleyan Center for the Arts Cultural Middletown CT 434

39 1974 UMass Fine Arts Center Cultural Amherst MA 435

39 1969 RIT Student Union & Physical Education Buildings Educational Rochester NY 436

39 1982 TCU Moudy Visual Arts & Communication Building Educational Fort Worth TX 437

39 2003 Station Place U.S. SEC Governmental DC DC 438

39 1968 Ford Foundation Headquarters Commercial / Office NYC NY 439

39 1983 General Foods Corporation Headquarters Commercial / Office Rye Brook NY 440 Hanover

39 2002 Agere Systems Expansion Commercial / Office PA 441 Township

39 1993 Borland International Corporate Headquarters Commercial / Office Scotts Valley CA 442

39 1984 Conoco Inc. Petroleum Headquarters Commercial / Office Houston TX 443

39 1989 J.P. Morgan & Company Commercial / Office NYC NY 444

39 1978 Deere & Company Corporate Headquarters Commercial / Office Moline IL 445

39 1985 Cummins Engine Company Corporate Headquarters Commercial / Office Columbus IN 446

39 1993 Corning Inc. Corporate Headquarters Commercial / Office Corning NY 447

39 1972 Irwin Union Bank and Trust Commercial / Office Columbus IN 448

39 1969 Knights of Columbus Headquarters Commercial / Office New Haven CT 449

39 1982 Union Carbide World Corporation Headquarters Commercial / Office Danbury CT 450

39 1989 Leo Burnett Company Headquarters Commercial / Office Chicago IL 451

39 1993 Merck and Company World Headquarters Commercial / Office Whitehouse St. NJ 452

39 1969 Aetna Life and Casualty Computer Headquarters Commercial / Office Hartford CT 453

39 1988 Deutsche Bank AG Headquarters Commercial / Office NYC NY 454 31

39 1973 Kentucky Power Company Headquarters Commercial / Office Ashland KY 455

39 1975 Richardson-Vicks Inc. Headquarters Commercial / Office Wilton CT 456

39 1993 Bank of America Plaza Commercial / Office Atlanta GA 457

39 1992 Ravinia Headquarters Complex Commercial / Office Atlanta GA 458

39 1996 Cummins CEP Expansion Project Commercial / Office Columbus IN 459

39 1980 John Deere Financial Services Headquarters Commercial / Office Moline IL 460

39 1987 U.N.I.C.E.F. Headquarters Commercial / Office NYC NY 461

39 1975 Worcester County National Bank Commercial / Office Worcester MA 462

39 1981 Indiana & Michigan Electric Company Headquarters Commercial / Office Fort Wayne IN 463

39 2009 Lafayette Tower Commercial / Office DC DC 464

39 2007 1101 New York Avenue Commercial / Office DC DC 465

39 2002 20 Westport Road Commercial / Office Wilton CT 466

39 1969 United Nations Plaza | UNICEF Headquarters Commercial / Office NYC NY 467

39 1990 750 Seventh Avenue Commercial / Office NYC NY 468

39 1969 U.S. Post Office Governmental Columbus IN 469

39 1980 Denver Center for Performing Arts Cultural Denver CO 470

39 1988 Central Park Zoo Cultural NYC NY 471

39 2001 Lucent Technologies Research & Development Commercial / Office Lisle IL 472

39 1975 Cummins Engine Company Sub-Assembly Plant Commercial / Office Columbus IN 473

39 1981 Rice University School of Architecture Extension Educational Houston TX 474

40 1984 Arthur M. Sackler Museum Educational Cambridge MA 475

40 1980 Columbia University Chemistry Department Educational NYC NY 476

40 1988 Schwartz Center for the Performing Arts Educational Ithaca NY 477

42 1986 190 South La Salle Street Commercial / Office Chicago IL 478

42 1984 AT&T Tower (renamed Sony Plaza) Commercial / Office NYC NY 479

42 1973 Boston Public Library Extension Cultural Boston MA 480

42 1961 Amon Carter Museum Cultural Fort Worth TX 481

42 1977 Century Center Cultural South Bend IN 482

42 1996 City Hall Governmental Celebration FL 483

42 1983 Cleveland Playhouse Complex Cultural Cleveland OH 484

42 1985 The Crescent Commercial / Office Dallas TX 485

42 1977 General Life Insurance Building Commercial / Office St. Louis MO 486

42 1995 Glass House Complex Private Residence New Canaan CT 487

42 1985 Gerald D. Hines College of Architecture Educational Houston TX 488

42 1970 Kennedy Memorial Cultural Dallas TX 489

42 1965 Kline Biology Tower Educational New Haven CT 490

42 1950 MOMA Guesthouse Private Residence NYC NY 491

42 1992 Mathematics Tower Educational Columbus OH 492

42 1987 Momentum Place (now Bank One) Commercial / Office Dallas TX 493

42 1964 Lincoln Center for the Performing Arts Cultural NYC NY 494

42 1987 One Atlantic Center (IBM Tower) Commercial / Office Atlanta GA 495

42 1990 One-Ninety-One Peachtree Tower Commercial / Office Atlanta GA 496

42 1984 One United Bank Center (now Norwest Tower) Commercial / Office Denver CO 497

42 1984 PPG Place Commercial / Office Pittsburgh PA 498

42 1973 Pennzoil Place Commercial / Office Houston TX 499

42 1984 Republic Bank Center Commercial / Office Houston TX 500

42 1960 Roofless Church Cultural New Harmony IN 501 32

42 1971 Rothko Chapel Cultural Houston TX 502

42 1995 St. Basil's Chapel Cultural Houston TX 503

42 1992 Science and Engineering Library Educational Columbus OH 504

42 1963 Sheldon Memorial Art Gallery Cultural Lincoln NE 505

42 1973 Thanks-Giving Square Cultural Dallas TX 506

42 1996 Turning Point, Case Western Reserve University Educational Cleveland OH 507

42 1958 University of St. Thomas Campus Educational Houston TX 508

42 1974 Water Gardens Cultural Fort Worth TX 509

33

Chapter 5

Results

Table 3 - U.S. Cities w/ BDSA (Sorted by # BDSA)

TYPE CITY STATE BDSA SKU

Urban New York City New York 95 1

Urban Los Angeles California 31 2

Urban Philadelphia Philadelphia 17 3

Urban DC DC 15 4

Urban Dallas Texas 14 5

Urban Cambridge Massachusetts 14 6

Urban Chicago Illinois 12 7

Urban Houston Texas 12 8

Urban New Haven Connecticut 9 9

Urban Princeton New Jersey 9 10

Urban Atlanta Georgia 8 11

Urban Columbus Indiana 8 12

Urban Ithaca New York 7 13

Urban Beverly Hills California 6 14

Urban Boston Massachusetts 6 15

Urban Fort Worth Texas 6 16

Urban San Francisco California 5 17

Urban Cleveland Ohio 5 18

Rural Malibu California 5 19

Urban Miami Beach Florida 4 20

Urban Minneapolis Minnesota 4 21

Urban St. Louis Missouri 4 22

Urban Allentown Pennsylvania 4 23

Rural East Hampton New York 4 24

Urban Pittsburgh Pennsylvania 4 25

Urban Santa Monica California 4 26

Urban Denver Colorado 4 27

Urban Columbus Ohio 3 28 34

Rural Suffolk County New York 3 29

Urban New Orleans Louisiana 3 30

Urban Burbank California 3 31

Urban Santa Barbara California 3 32

Urban Las Vegas Nevada 3 33

Urban Cincinnati Ohio 3 34

Urban Miami Florida 3 35

Urban Cupertino California 3 36 New

Urban Hanover 3 37 Hampshire

Urban Ann Arbor Michigan 3 38

Rural Celebration Florida 3 39

Urban Des Moines Iowa 3 40

Urban Austin Texas 2 41

Rural New Canaan Connecticut 2 42

Rural Southhampton New York 2 43

Urban Seattle Washington 3 44

Urban Stanford California 2 45

Urban Iowa City Iowa 2 46

Urban Providence Rhode Island 2 47

Urban Bloomfield Hills Michigan 2 48 Annandale-on- Rural New York 2 49

Hudson

Urban Merion Pennsylvania 2 50

Urban San Diego California 2 51

Urban Newark New Jersey 2 52

Urban Irvine California 2 53

Urban Hartford Connecticut 2 54

Rural New Harmony Indiana 2 55

Urban Bronx New York 2 56

Urban Honolulu Hawaii 2 57

Urban Syracuse New York 2 58

Urban Wallingford Connecticut 2 59

Urban Rochester New York 2 60

Urban Moline Illinois 2 61

Rural Wilton Connecticut 2 62

Urban Orlando Florida 1 63

Urban Aspen Colorado 1 64

Urban Moab Utah 1 65

Urban Hermosa Beach California 1 66

Urban West Hollywood California 1 67

Urban Manhattan Beach California 1 68

Urban Scottsdale Arizona 1 69

Urban Long Beach California 1 70 35

Urban Pomona California 1 71

Urban Suitland Maryland 1 72

Urban Eugene Oregon 1 73

Urban Pasadena California 1 74

Urban Southfield Michigan 1 75

Urban East Lansing Michigan 1 76

Urban Sunny Isles Beach Florida 1 77

Urban Napa Valley California 1 78

Urban West Palm Beach Florida 1 79

Urban Aventura Florida 1 80

Urban Omaha Nebraska 1 81

Urban Camarillo California 1 82 Truth or Rural New Mexico 1 83

Consequences

Rural Rocky Mountains Colorado 1 84

Urban Belmont Massachusetts 1 85

Urban Houston Texas 1 86

Urban Wellesley Massachusetts 1 87

Rural Santa Fe County New Mexico 1 88

Rural Williamstown Massachusetts 1 89

Rural Mount Desert Island Maine 1 90

Urban Camden New Jersey 1 91

Urban Elkins Park Pennsylvania 1 92

Urban Sunbury Pennsylvania 1 93

Urban Newton Square Pennsylvania 1 94

Rural Ocean County New Jersey 1 95

Urban Glen Cove New York 1 96

Urban Greenwich Connecticut 1 97

Urban New Castle County Delaware 1 98

Rural Seal Harbor Maine 1 99

Urban Stony Creek Connecticut 1 100

Urban Vail Village Colorado 1 101

Rural Block Island Rhode Island 1 102

Urban Nantucket Island Massachusetts 1 103

Urban Bethlehem Pennsylvania 1 104

Urban Oberlin Ohio 1 105

Urban Columbus Ohio 1 106

Rural Wayne Pennsylvania 1 107

Urban Swarthmore Pennsylvania 1 108

Urban Hudson New York 1 109

Urban Trenton New Jersey 1 110

Urban Lexington Kentucky 1 111

Urban Orange County Florida 1 112

Rural Riverside County California 1 113

Urban Columbia Maryland 1 114

Urban Concord California 1 115

Urban Baltimore Maryland 1 116 36

Urban Sacramento California 1 117

Urban Thousand Oaks California 1 118

Urban Rocklin California 1 119

Urban Toledo Ohio 1 120

Urban Anaheim California 1 121

Urban Biloxi Mississippi 1 122

Urban Menlo Park California 1 123

Urban Great Lakes Illinois 1 124

Urban Dearborn Michigan 1 125

Urban Richmond Virginia 1 126

Urban Buffalo New York 1 127

Urban Phoenix Arizona 1 128

Urban Garden Grove California 1 129

Urban San Jose San Jose 1 130

Urban Bridgeport Connecticut 1 131

Urban Darien Connecticut 1 132

Urban Palm Beach Florida 1 133

Urban Naples Florida 1 134

Urban Surfside Florida 1 135

Rural Harbor Springs Michigan 1 136

Rural Starkville Mississippi 1 137

Urban Morris County New Jersey 1 138

Rural Essex Falls New Jersey 1 139

Urban Nassau County New York 1 140

Urban Port Washington New York 1 141

Urban Westchester New York 2 142

Urban Melville New York 1 143

Urban Central Islip New York 1 144

Rural North Salem New York 1 145

Urban Garden City New York 1 146

Urban Sarasota Florida 1 147

Urban Boulder Colorado 1 148

Urban Wilmington Delaware 1 149

Urban Asheville North Carolina 1 150

Urban Bloomington Indiana 1 151

Urban Harrison Town New York 1 152

Urban Birmingham Alabama 1 153

Urban Novato California 1 154

Urban Oakland, CA California 1 155

Urban Williamsburg Virginia 1 156

Urban Middletown Connecticut 1 157

Urban Amherst Massachusetts 1 158

Urban Rye Brook New York 1 159

Rural Hanover Township Pennsylvania 1 160

Urban Scotts Valley California 1 161

Urban Corning New York 1 162

Urban Danbury Connecticut 1 163 37

Rural Whitehouse Station New Jersey 1 164

Urban Ashland Kentucky 1 165

Urban Worcester Indiana 1 166

Urban Fort Wayne Indiana 1 167

Urban Lisle Illinois 1 168

Urban South Bend Indiana 1 169

Urban Lincoln Nebraska 1 170

38

Table 4 - U.S. States w/ BDSA (Sorted by # BDSA) STATE BDSA SKU

New York 133 1

California 86 2

Texas 35 3

Pennsylvania 34 4

Massachusetts 26 5

Connecticut 24 6

Florida 19 7

Illinois 16 8

New Jersey 16 9

District of Columbia 15 10

Ohio 14 11

Indiana 13 12

Colorado 8 13

Georgia 8 14

Michigan 8 15

Iowa 5 16

Minnesota 4 17

Missouri 4 18

Delaware 3 19

Louisiana 3 20

Maryland 3 21

Nevada 3 22

New Hampshire 3 23

Rhode Island 3 24

Washington 3 25

Arizona 2 26

Hawaii 2 27

Kentucky 2 28

Maine 2 29

Mississippi 2 30

Nebraska 2 31

New Mexico 2 32

Virginia 2 33

Alabama 1 34

North Carolina 1 35

Oregon 1 36

Utah 1 37

39

Table 5 - 170 Cities w/ BDSA v. United States

170 CITY-LEVEL DATA vs. UNITED STATES AVERAGE 170 CITIES % DIFF 170 CITIES % DIFF U.S.

SUMMARY STATISTICS | US AVERAGE (BDSA-Wt'd) v. U.S. (POP-Wt'd) v. U.S. (POP-Wt'd) - Average Population 2,205,486.92 -99.33% 2,242,078.48 328,239,523.00 99.32% Persons under 18 years, percent 19.88% -10.87% 21.71% -2.64% 22.30% - Persons 65 years and over, percent 14.22% -13.84% 13.29% 16.50% 19.44% - White alone, percent 56.93% -25.39% 55.16% 76.30% 27.71% - Owner-occupied housing unit rate, 2014 - 2018 46.22% -27.55% 47.66% 63.80% 25.30% Median value of owner-occupied housing units, 2014 - 2018 $485,027.31 136.71% $376,016.14 83.51% $204,900.00

Median Gross Rent, 2014 - 2018 $1,340.14 31.00% $1,245.52 21.75% $1,023.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 86.69% -1.15% 84.56% -3.58% 87.70%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 43.39% 37.76% 36.86% 17.03% 31.50%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 63.10% 0.32% 65.14% 3.56% 62.90%

Median household income (in 2018 dollars), 2014 - 2018 $68,150.62 13.03% $62,047.52 2.91% $60,293.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $41,400.25 26.91% $35,461.86 8.71% $32,621.00

Persons in poverty, percent 16.85% 42.78% 16.88% 43.04% 11.80%

Population per square mile, 2010 9,909.07 112x 8,471.73 96x 87.40

Table 6 - 170 Cities w/ BDSA v. 37 States w/ BDSA

170 CITY-LEVEL DATA vs. AVERAGE OF 37 STATES W/ AT LEAST 1 BDSA 170 CITIES % DIFF 170 CITIES % DIFF 37 STATES

SUMMARY STATISTICS | 37 STATES (BDSA-Wt'd) v. U.S. (POP-Wt'd) v. U.S. (POP-Wt'd)

Average Population 2,205,486.92 -86.20% 2,242,078.48 -85.97% 15,978,765.06

Persons under 18 years, percent 19.88% -10.51% 21.71% -2.24% 22.21%

Persons 65 years and over, percent 14.22% -11.64% 13.29% -17.38% 16.09%

White alone, percent 56.93% -22.82% 55.16% -25.22% 73.76%

Owner-occupied housing unit rate, 2014 - 2018 46.22% -26.86% 47.66% -24.59% 63.20%

Median value of owner-occupied housing units, 2014 - 2018 $485,027.31 95.24% $376,016.14 51.36% $248,423.08

Median Gross Rent, 2014 - 2018 $1,340.14 24.55% $1,245.52 15.75% $1,076.03

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 86.69% -0.88% 84.56% -3.31% 87.46%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 43.39% 35.65% 36.86% 15.24% 31.99%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 63.10% 0.08% 65.14% 3.31% 63.05%

Median household income (in 2018 dollars), 2014 - 2018 $68,150.62 9.37% $62,047.52 -0.42% $62,309.60

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $41,400.25 25.38% $35,461.86 7.40% $33,019.87

Persons in poverty, percent 16.85% 29.70% 16.88% 29.93% 12.99%

Population per square mile, 2010 9,909.07 34x 8,471.73 29x 282.59

40

Table 7 - 509 BDSA By Building Type

BDSA MIX BY BUILDING TYPE Cultural 122

Educational 112

Commercial / Office 93

Private Residence 70

Residential Tower 37

Governmental 26

Commercial / Retail 18

Commercial / Restaurant 9

Healthcare 9

Mixed Use 4

Nature Preserve 3

Hotel 3

Athletic 3

Table 8 - 170 Cities by Type (Urban / Rural)

CITY MIX BY TYPE Urban 145

Rural 25

41

Chapter 6

Conclusion

Summary of Results

Based on the data gathered, I find that cities with BDSA have a working-age population that is 4.71% greater than the U.S. average, and 4.21% greater than the average of the 37 states in which the cities reside. I find that cities with BDSA are 25.39% more racially diverse when compared to the U.S. average and 22.82% more diverse when compared to the average of the 37 states in which the cities reside. I find that cities with BDSA have 27.55% more renters than the national average and 26.86% more renters than the 37 states in which the cities with BDSA reside. This implies that more people in these cities are temporary residents, there primarily to work during their most economically productive years, rather than settling down, buying a home and starting a family. This makes sense, as the majority of BDSA fall within larger, younger and more mobile cities, where the residential status of city-dwellers is constantly in flux. I find that the median value of owner-occupied housing is 136.71% greater than the national average in cities with BDSA, and 95.24% greater when compared to the average of the 37 states in which the BDSA reside. I find that gross rents in cities with BDSA are 31.00% and 24.55% greater than the national average and the average of the 37 states in which the BDSA reside, respectfully.

Surprisingly, I find that cities with BDSA have slightly lower high school graduate populations, with the average for cities with BDSA coming in 1.15% lower than the national average and

0.88% lower than the 37 states in which the BDSA reside. Hoeer, hen looking at Bachelors degree holders, the results realign with my hypothesis that cities with BDSA are more highly- educated. The results sho that cities ith BDSA hae 37.76% more bachelors degree holders as a percentage of the population when compared to the national average, and 35.65% more 42 bachelors degree holders hen compared to the 37 states in hich the BDSA reside. I find that median household incomes in cities with BDSA are 13.03% and 9.37% greater than the national average and the average of the 37 states in which the BDSA reside, respectfully. I find that the average per-capita income in cities with BDSA is 26.91% higher than the national average, and

25.38% higher than the average of the 37 states in which the BDSA reside. Unsurprisingly, I find that the poverty rates for cities with BDSA are higher by 42.78% and 29.70% than the national and 37 state averages. This is primarily due to the fact that BDSA are concentrated in higher- population-density regions of the United States, where there is significantly more wealth than average, but also greater levels of income inequality. Confirming this last point in the data, I find that cities with BDSA are 112 times more densely populated than the national average and 34 times more densely populated than the average of the 37 states in which the BDSA reside.

I also find that the majority of BDSA are cultural institutions, primarily museums, or educational facilities, primarily student dormitories and campus research buildings. This is an encouraging finding because it implies that a large percentage of BDSA in the United States are open and accessible to the public to enjoy and for young people to be exposed to during their high school and undergraduate experience (Table 7). A significant force in shifting peoples behaior towards being more thoughtful and appreciative of design is by repeatedly exposing them to quality design. Thankfully, the majority of buildings in this study are located in urban areas, meaning a large number of people can easily view the exterior (and often interior) of the buildings in this study (Table 8).

Implications

The results of this study imply that cities with higher concentrations of signature architecture tend to be more economically productive, more racially diverse, more employed, higher earning, higher-renting, denser and more unequal than the average for the country and the

37 states in which the cities with BDSA reside. The primary goal of this paper is to describe the 43 average economic environment that surrounds BDSA, and it is now clear that cities with BDSA are generally more economically vibrant zones. This strengthens the argument that the local design spillover effect is real, and that there may be intangible, positive externalities given off by well-designed locales that result in higher levels of economic participation and productivity.

The results of this study suggest that growing cities may find an increasing number of signature buildings appear in lockstep with economic growth, partly funded by the local wealth that is being created, and partly spurring further innovation and collaboration that will lead to more wealth and economic growth down the line. These architectural environments may encourage unconventional creativity and further attract more adventurous, open-minded and educated populations who enjoy the aesthetic and cultural amenity premiums associated with living in a well-designed city. Of course, any one building makes up but a small percentage of the total real estate of any MSA in this study. However, the presence of even one BDSA in an MSA sends an important message about the values and priorities of that city. While a city might currently have only one BDSA, it can be observed that cities such as New York, Los Angeles,

Philadelphia and D.C. have accumulated large numbers of BDSA over time, and continue to experience economically-vibrant local conditions. The buildings highlighted in this study communicate to inhabitants, neighbors and passerbs that ecellence is attainable, and that they can indeed be different. They act as beacons of light in otherwise repetitive built environments, and their natural tendency to stick around and stay occupied acts as a constant positive reminder that stays visible to the city inhabitants. Further, the results of this analysis strengthen the argument that educated people, clustered together, can make an area unbelievably rich and productive, which results in the arrival of world-class architecture to support their needs.

According to (Landry, 1995), a high proportion of regional and local development organizations in the UK stress cultural factors in their locational marketing. For the cities in the list, there is a clear case to be made in marketing the the local architectural environment as an 44 important factor in attracting new residents. For cities without BDSA, the positive results of this study may encourage developers, municipal directors and other involved parties to coordinate signature architecture developments to try and contribute to an urban regeneration effort through the gradual refinement of the locally-built environment.

What past papers demonstrate is that there is a clear economic effect that appears alongside architectural marketing weight. However, by focusing only on house prices, past studies capture more of a look-at-me premium that might falsely inflate local values. What other authors missed is the economic value capture that is reflected in a broader range of indicators that describe the local economy, rather than the building itself. The results of this study suggest that there is an economic case to be made for commissioning a high-profile architect compared to a local architect when developers consider the added value of a more vibrant regional economy.

Further Research

The primary value offered by this paper is the assembly of a large data set of BDSA in the United States. The quantitative summary laid out in this paper is relatively simple, rudimentary at best. My hope is that future researchers will take the large dataset which I have collected for this study and more intelligently and rigorously apply statistical analysis to the data in order to gather more prescient insights. For example, after eliminating outlier cities such as

New York City, Washington D.C., Los Angeles and Chicago from the list, where the difference between BDSA-weighted and population-weighted statistics is 1.50% or greater, a researcher might determine whether the results are robust with respect to outliers. Finally, I have assembled a substantial bibliography of sources related to the topic of this paper, which should hopefully act as a useful jumping off point for another future researcher interested in this or a related topic. 45

Appendix A

Cities w/ BDSA By State

ALABAMA CITIES W/ BDSA vs. ALABAMA STATE OVERALL BDSA CITIES ALABAMA (AL) SUMMARY STATISTICS | ALABAMA (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 209,403.00 -95.73% 4,903,185.00

Persons under 18 years, percent 20.30% -8.56% 22.20%

Persons 65 years and over, percent 14.20% -17.92% 17.30%

White alone, percent 25.30% -63.39% 69.10%

Owner-occupied housing unit rate, 2014 - 2018 45.80% -33.24% 68.60%

Median value of owner-occupied housing units, 2014 - 2018 $89,200.00 -34.99% $137,200.00

Median Gross Rent, 2014 - 2018 $797.00 3.24% $772.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 86.10% 0.35% 85.80%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 26.00% 4.42% 24.90%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 60.00% 5.08% 57.10%

Median household income (in 2018 dollars), 2014 - 2018 $35,346.00 -27.10% $48,486.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $22,993.00 -14.35% $26,846.00

Persons in poverty, percent 27.20% 61.90% 16.80%

Population per square mile, 2010 1,453.00 14x 94.40

ARIZONA CITIES W/ BDSA vs. ARIZONA STATE OVERALL BDSA CITIES ARIZONA (AR) SUMMARY STATISTICS | ARIZONA (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 969,530.50 -86.68% 7,278,717.00

Persons under 18 years, percent 21.25% -5.56% 22.50%

Persons 65 years and over, percent 16.85% -6.39% 18.00%

White alone, percent 80.10% -3.03% 82.60%

Owner-occupied housing unit rate, 2014 - 2018 59.85% -5.90% 63.60%

Median value of owner-occupied housing units, 2014 - 2018 $336,650.00 60.62% $209,600.00

Median Gross Rent, 2014 - 2018 $1,141.50 13.13% $1,009.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 89.00% 2.53% 86.80%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 42.70% 47.75% 28.90%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 64.50% 8.95% 59.20%

Median household income (in 2018 dollars), 2014 - 2018 $69,683.00 23.96% $56,213.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $43,911.50 50.05% $29,265.00

Persons in poverty, percent 13.80% -1.43% 14.00%

Population per square mile, 2010 1,989.90 34x 56.30

46

CALIFORNIA CITIES W/ BDSA vs. CALIFORNIA STATE OVERALL BDSA CITIES CALIFORNIA (CA) SUMMARY STATISTICS | CALIFORNIA (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 1,635,370.85 -95.86% 39,512,223.00

Persons under 18 years, percent 19.57% -13.04% 22.50%

Persons 65 years and over, percent 14.46% -2.31% 14.80%

White alone, percent 43.87% -38.98% 71.90%

Owner-occupied housing unit rate, 2014 - 2018 44.51% -18.47% 54.60%

Median value of owner-occupied housing units, 2014 - 2018 $951,647.06 99.97% $475,900.00

Median Gross Rent, 2014 - 2018 $1,722.26 20.52% $1,429.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 86.27% 4.07% 82.90%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 47.55% 42.80% 33.30%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 65.35% 3.57% 63.10%

Median household income (in 2018 dollars), 2014 - 2018 $84,159.66 18.16% $71,228.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $51,452.14 46.92% $35,021.00

Persons in poverty, percent 13.93% 8.80% 12.80%

Population per square mile, 2010 7,084.20 29x 239.10

COLORADO CITIES W/ BDSA vs. COLORADO STATE OVERALL BDSA CITIES COLORADO (CO) SUMMARY STATISTICS | COLORADO (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 379,222.25 -93.41% 5,758,736.00

Persons under 18 years, percent 16.26% -25.74% 21.90%

Persons 65 years and over, percent 15.86% 8.65% 14.60%

White alone, percent 84.56% -2.69% 86.90%

Owner-occupied housing unit rate, 2014 - 2018 53.43% -17.68% 64.90%

Median value of owner-occupied housing units, 2014 - 2018 $484,037.50 54.35% $313,600.00

Median Gross Rent, 2014 - 2018 $1,265.00 5.77% $1,196.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 92.21% 0.89% 91.40%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 55.26% 37.81% 40.10%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 69.91% 3.42% 67.60%

Median household income (in 2018 dollars), 2014 - 2018 $65,099.75 -5.39% $68,811.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $46,016.88 26.37% $36,415.00

Persons in poverty, percent 13.31% 38.67% 9.60%

Population per square mile, 2010 2,920.80 59x 48.50

47

CONNECTICUT CITIES W/ BDSA vs. CONNECTICUT STATE OVERALL BDSA CITIES CONNECTICUT (CO) SUMMARY STATISTICS | CONNECTICUT (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 80,211.91 -97.75% 3,565,287.00

Persons under 18 years, percent 23.09% 13.19% 20.40%

Persons 65 years and over, percent 13.38% -24.39% 17.70%

White alone, percent 62.59% -21.47% 79.70%

Owner-occupied housing unit rate, 2014 - 2018 46.65% -29.63% 66.30%

Median value of owner-occupied housing units, 2014 - 2018 $454,734.78 67.06% $272,200.00

Median Gross Rent, 2014 - 2018 $1,464.09 26.65% $1,156.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 88.01% -2.75% 90.50%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 42.87% 10.19% 38.90%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 63.74% -3.72% 66.20%

Median household income (in 2018 dollars), 2014 - 2018 $82,117.74 7.90% $76,106.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $47,285.00 9.82% $43,056.00

Persons in poverty, percent 16.51% 58.74% 10.40%

Population per square mile, 2010 4,566.61 5x 738.10

DC CITIES W/ BDSA vs. DC STATE OVERALL BDSA CITIES DC (DC) SUMMARY STATISTICS | DC (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 705,749.00 -27.52% 973,764.00

Persons under 18 years, percent 8.20% -60.77% 20.90%

Persons 65 years and over, percent 12.40% -36.08% 19.40%

White alone, percent 46.00% -33.53% 69.20%

Owner-occupied housing unit rate, 2014 - 2018 41.80% -41.21% 71.10%

Median value of owner-occupied housing units, 2014 - 2018 $568,400.00 132.28% $244,700.00

Median Gross Rent, 2014 - 2018 $1,487.00 33.96% $1,110.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 90.60% 0.89% 89.80%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 57.60% 83.44% 31.40%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 69.50% 11.56% 62.30%

Median household income (in 2018 dollars), 2014 - 2018 $82,604.00 25.87% $65,627.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $53,321.00 56.88% $33,989.00

Persons in poverty, percent 16.20% 29.60% 12.50%

Population per square mile, 2010 9,856.50 20x 460.80

48

DELAWARE CITIES W/ BDSA vs. DELAWARE STATE OVERALL BDSA CITIES DELAWARE (DE) SUMMARY STATISTICS | DELAWARE (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 314,459.50 -55.44% 705,749.00

Persons under 18 years, percent 22.30% 22.53% 18.20%

Persons 65 years and over, percent 14.40% 16.13% 12.40%

White alone, percent 49.85% 8.37% 46.00%

Owner-occupied housing unit rate, 2014 - 2018 56.40% 34.93% 41.80%

Median value of owner-occupied housing units, 2014 - 2018 $211,950.00 -62.71% $568,400.00

Median Gross Rent, 2014 - 2018 $1,057.50 -28.88% $1,487.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 89.20% -1.55% 90.60%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 32.10% -44.27% 57.60%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 63.75% -8.27% 69.50%

Median household income (in 2018 dollars), 2014 - 2018 $56,925.00 -31.09% $82,604.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $32,776.50 -38.53% $53,321.00

Persons in poverty, percent 18.35% 13.27% 16.20%

Population per square mile, 2010 3,880.45 -1x 9,856.50

FLORIDA CITIES W/ BDSA vs. FLORIDA STATE OVERALL BDSA CITIES FLORIDA (FL) SUMMARY STATISTICS | FLORIDA (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 196,220.53 -99.09% 21,477,737.00

Persons under 18 years, percent 16.81% -14.67% 19.70%

Persons 65 years and over, percent 22.47% 7.50% 20.90%

White alone, percent 80.84% 4.58% 77.30%

Owner-occupied housing unit rate, 2014 - 2018 50.12% -22.90% 65.00%

Median value of owner-occupied housing units, 2014 - 2018 $428,442.11 117.70% $196,800.00

Median Gross Rent, 2014 - 2018 $1,429.68 26.75% $1,128.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 90.37% 2.70% 88.00%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 45.56% 56.04% 29.20%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 60.51% 3.79% 58.30%

Median household income (in 2018 dollars), 2014 - 2018 $63,546.63 19.30% $53,267.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $52,049.00 72.36% $30,197.00

Persons in poverty, percent 13.97% 2.75% 13.60%

Population per square mile, 2010 7,271.68 20x 350.60

49

GEORGIA CITIES W/ BDSA vs. GEORGIA STATE OVERALL BDSA CITIES GEORGIA (GE) SUMMARY STATISTICS | GEORGIA (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 506,811.00 -95.23% 10,617,423.00

Persons under 18 years, percent 18.50% -21.61% 23.60%

Persons 65 years and over, percent 11.40% -20.28% 14.30%

White alone, percent 40.30% -33.06% 60.20%

Owner-occupied housing unit rate, 2014 - 2018 43.40% -31.22% 63.10%

Median value of owner-occupied housing units, 2014 - 2018 $261,400.00 56.71% $166,800.00

Median Gross Rent, 2014 - 2018 $1,099.00 13.53% $968.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 90.30% 4.15% 86.70%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 49.90% 62.54% 30.70%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 65.10% 4.33% 62.40%

Median household income (in 2018 dollars), 2014 - 2018 $55,279.00 -0.72% $55,679.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $43,468.00 47.23% $29,523.00

Persons in poverty, percent 21.60% 51.05% 14.30%

Population per square mile, 2010 3,154.30 18x 168.40

HAWAII CITIES W/ BDSA vs. HAWAII STATE OVERALL BDSA CITIES HAWAII (HA) SUMMARY STATISTICS | HAWAII (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 974,563.00 -31.17% 1,415,872.00

Persons under 18 years, percent 21.00% -0.94% 21.20%

Persons 65 years and over, percent 18.20% -4.21% 19.00%

White alone, percent 21.60% -15.29% 25.50%

Owner-occupied housing unit rate, 2014 - 2018 55.80% -4.29% 58.30%

Median value of owner-occupied housing units, 2014 - 2018 $649,800.00 10.57% $587,700.00

Median Gross Rent, 2014 - 2018 $1,703.00 8.75% $1,566.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 91.70% -0.11% 91.80%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 34.30% 5.54% 32.50%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 61.60% -0.32% 61.80%

Median household income (in 2018 dollars), 2014 - 2018 $82,906.00 6.18% $78,084.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $35,202.00 3.43% $34,035.00

Persons in poverty, percent 7.70% -12.50% 8.80%

Population per square mile, 2010 1,586.70 6x 211.80

50

ILLINOIS CITIES W/ BDSA vs. ILLINOIS STATE OVERALL BDSA CITIES ILLINOIS (IL) SUMMARY STATISTICS | ILLINOIS (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 2,070,639.31 -83.66% 12,671,821.00

Persons under 18 years, percent 21.41% -3.55% 22.20%

Persons 65 years and over, percent 13.22% -17.90% 16.10%

White alone, percent 57.44% -25.21% 76.80%

Owner-occupied housing unit rate, 2014 - 2018 50.15% -24.02% 66.00%

Median value of owner-occupied housing units, 2014 - 2018 $237,143.75 26.68% $187,200.00

Median Gross Rent, 2014 - 2018 $1,054.63 7.18% $984.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 86.24% -2.99% 88.90%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 38.62% 13.25% 34.10%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 66.71% 2.48% 65.10%

Median household income (in 2018 dollars), 2014 - 2018 $58,847.00 -7.44% $63,575.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $35,730.06 3.68% $34,463.00

Persons in poverty, percent 17.19% 42.05% 12.10%

Population per square mile, 2010 9,515.91 40x 231.10

INDIANA CITIES W/ BDSA vs. INDIANA STATE OVERALL BDSA CITIES INDIANA (IN) SUMMARY STATISTICS | INDIANA (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 563,063.50 -91.64% 6,732,219.00

Persons under 18 years, percent 22.69% -2.64% 23.30%

Persons 65 years and over, percent 14.97% -7.01% 16.10%

White alone, percent 80.49% -5.08% 84.80%

Owner-occupied housing unit rate, 2014 - 2018 61.24% -11.12% 68.90%

Median value of owner-occupied housing units, 2014 - 2018 $152,078.57 12.32% $135,400.00

Median Gross Rent, 2014 - 2018 $869.50 7.74% $807.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 90.98% 2.68% 88.60%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 36.43% 40.65% 25.90%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 64.28% 0.75% 63.80%

Median household income (in 2018 dollars), 2014 - 2018 $55,299.29 1.79% $54,325.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $30,212.14 6.15% $28,461.00

Persons in poverty, percent 15.63% 19.30% 13.10%

Population per square mile, 2010 1,856.86 9x 181.00

51

IOWA CITIES W/ BDSA vs. IOWA STATE OVERALL BDSA CITIES IOWA (IO) SUMMARY STATISTICS | IOWA (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 158,594.20 -94.97% 3,155,070.00

Persons under 18 years, percent 21.14% -8.09% 23.00%

Persons 65 years and over, percent 10.86% -37.94% 17.50%

White alone, percent 76.64% -15.41% 90.60%

Owner-occupied housing unit rate, 2014 - 2018 55.30% -22.22% 71.10%

Median value of owner-occupied housing units, 2014 - 2018 $157,720.00 10.84% $142,300.00

Median Gross Rent, 2014 - 2018 $874.80 14.20% $766.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 89.90% -2.28% 92.00%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 39.20% 39.01% 28.20%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 69.24% 2.73% 67.40%

Median household income (in 2018 dollars), 2014 - 2018 $50,260.60 -14.20% $58,580.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $28,008.20 -9.90% $31,085.00

Persons in poverty, percent 21.36% 90.71% 11.20%

Population per square mile, 2010 2,594.68 47x 54.50

KENTUCKY CITIES W/ BDSA vs. KENTUCKY STATE OVERALL BDSA CITIES KENTUCKY (KE) SUMMARY STATISTICS | KENTUCKY (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 171,649.00 -96.16% 4,467,673.00

Persons under 18 years, percent 22.10% -1.34% 22.40%

Persons 65 years and over, percent 15.40% -8.33% 16.80%

White alone, percent 84.35% -3.60% 87.50%

Owner-occupied housing unit rate, 2014 - 2018 57.45% -14.25% 67.00%

Median value of owner-occupied housing units, 2014 - 2018 $140,000.00 3.47% $135,300.00

Median Gross Rent, 2014 - 2018 $748.50 1.01% $741.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 90.00% 5.02% 85.70%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 33.20% 40.68% 23.60%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 60.65% 2.97% 58.90%

Median household income (in 2018 dollars), 2014 - 2018 $46,682.00 -3.53% $48,392.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $28,574.50 6.04% $26,948.00

Persons in poverty, percent 21.30% 26.04% 16.90%

Population per square mile, 2010 1,531.00 13x 109.90

52

LOUISIANA CITIES W/ BDSA vs. LOUISIANA STATE OVERALL BDSA CITIES LOUISIANA (LO) SUMMARY STATISTICS | LOUISIANA (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 390,144.00 -91.61% 4,648,794.00

Persons under 18 years, percent 20.20% -13.68% 23.40%

Persons 65 years and over, percent 13.50% -15.09% 15.90%

White alone, percent 34.00% -45.86% 62.80%

Owner-occupied housing unit rate, 2014 - 2018 47.40% -27.41% 65.30%

Median value of owner-occupied housing units, 2014 - 2018 $219,600.00 39.16% $157,800.00

Median Gross Rent, 2014 - 2018 $973.00 14.47% $850.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 86.20% 1.65% 84.80%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 36.80% 55.27% 23.70%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 61.10% 3.04% 59.30%

Median household income (in 2018 dollars), 2014 - 2018 $39,576.00 -17.45% $47,942.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $30,177.00 11.66% $27,027.00

Persons in poverty, percent 24.60% 32.26% 18.60%

Population per square mile, 2010 2,029.40 18x 104.90

MAINE CITIES W/ BDSA vs. MAINE STATE OVERALL BDSA CITIES MAINE (MA) SUMMARY STATISTICS | MAINE (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 54,987.00 -95.91% 1,344,212.00

Persons under 18 years, percent 17.00% -8.11% 18.50%

Persons 65 years and over, percent 25.30% 19.34% 21.20%

White alone, percent 95.80% 1.48% 94.40%

Owner-occupied housing unit rate, 2014 - 2018 75.40% 4.43% 72.20%

Median value of owner-occupied housing units, 2014 - 2018 $211,700.00 14.74% $184,500.00

Median Gross Rent, 2014 - 2018 $810.00 -2.53% $831.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 94.10% 1.95% 92.30%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 32.30% 4.53% 30.90%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 60.90% -3.18% 62.90%

Median household income (in 2018 dollars), 2014 - 2018 $53,068.00 -4.25% $55,425.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $32,491.00 3.96% $31,253.00

Persons in poverty, percent 11.60% 0.00% 11.60%

Population per square mile, 2010 34.30 x 43.10

53

MARYLAND CITIES W/ BDSA vs. MARYLAND STATE OVERALL BDSA CITIES MARYLAND (MA) SUMMARY STATISTICS | MARYLAND (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 239,643.33 -96.04% 6,045,680.00

Persons under 18 years, percent 22.27% 0.75% 22.10%

Persons 65 years and over, percent 12.43% -21.80% 15.90%

White alone, percent 29.60% -49.40% 58.50%

Owner-occupied housing unit rate, 2014 - 2018 49.90% -25.30% 66.80%

Median value of owner-occupied housing units, 2014 - 2018 $248,533.33 -18.65% $305,500.00

Median Gross Rent, 2014 - 2018 $1,362.33 0.39% $1,357.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 89.90% -0.11% 90.00%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 36.37% -8.16% 39.60%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 69.53% 3.47% 67.20%

Median household income (in 2018 dollars), 2014 - 2018 $71,864.33 -12.22% $81,868.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $36,601.00 -9.67% $40,517.00

Persons in poverty, percent 12.43% 38.15% 9.00%

Population per square mile, 2010 5,621.73 8x 594.80

MASSACHUSETTS CITIES W/ BDSA vs. MASSACHUSETTS STATE BDSA CITIES MASSACHUSETTS OVERALL (MA) SUMMARY STATISTICS | MASSACHUSETTS (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 236,289.36 -96.60% 6,949,503.00

Persons under 18 years, percent 14.49% -26.06% 19.60%

Persons 65 years and over, percent 11.78% -30.71% 17.00%

White alone, percent 66.46% -17.54% 80.60%

Owner-occupied housing unit rate, 2014 - 2018 41.50% -33.38% 62.30%

Median value of owner-occupied housing units, 2014 - 2018 $660,468.00 80.06% $366,800.00

Median Gross Rent, 2014 - 2018 $1,838.08 50.05% $1,225.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 93.02% 2.90% 90.40%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 68.32% 59.25% 42.90%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 67.88% 1.17% 67.10%

Median household income (in 2018 dollars), 2014 - 2018 $90,801.28 17.35% $77,378.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $50,425.84 20.65% $41,794.00

Persons in poverty, percent 14.70% 47.04% 10.00%

Population per square mile, 2010 12,830.21 14x 839.40

54

MICHIGAN CITIES W/ BDSA vs. MICHIGAN STATE OVERALL BDSA CITIES MICHIGAN (MI) SUMMARY STATISTICS | MICHIGAN (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 73,883.11 -99.26% 9,986,857.00

Persons under 18 years, percent 17.78% -17.31% 21.50%

Persons 65 years and over, percent 15.64% -11.61% 17.70%

White alone, percent 73.24% -7.52% 79.20%

Owner-occupied housing unit rate, 2014 - 2018 57.94% -18.39% 71.00%

Median value of owner-occupied housing units, 2014 - 2018 $265,511.11 81.61% $146,200.00

Median Gross Rent, 2014 - 2018 $1,123.78 32.21% $850.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 94.43% 4.35% 90.50%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 60.72% 112.32% 28.60%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 60.68% -1.02% 61.30%

Median household income (in 2018 dollars), 2014 - 2018 $71,874.78 30.83% $54,938.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $42,072.78 38.69% $30,336.00

Persons in poverty, percent 18.47% 30.97% 14.10%

Population per square mile, 2010 2,903.26 16x 174.80

MINNESOTA CITIES W/ BDSA vs. MINNESOTA STATE OVERALL BDSA CITIES MINNESOTA (MI) SUMMARY STATISTICS | MINNESOTA (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 429,606.00 -92.38% 5,639,632.00

Persons under 18 years, percent 20.10% -12.99% 23.10%

Persons 65 years and over, percent 9.50% -41.72% 16.30%

White alone, percent 63.80% -23.87% 83.80%

Owner-occupied housing unit rate, 2014 - 2018 47.30% -33.94% 71.60%

Median value of owner-occupied housing units, 2014 - 2018 $235,900.00 11.38% $211,800.00

Median Gross Rent, 2014 - 2018 $985.00 4.34% $944.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 89.70% -3.55% 93.00%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 49.40% 39.55% 35.40%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 74.40% 6.74% 69.70%

Median household income (in 2018 dollars), 2014 - 2018 $58,993.00 -13.77% $68,411.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $37,071.00 2.28% $36,245.00

Persons in poverty, percent 19.90% 107.29% 9.60%

Population per square mile, 2010 7,088.30 105x 66.60

55

MISSISSIPPI CITIES W/ BDSA vs. MISSISSIPPI STATE OVERALL BDSA CITIES MISSISSIPPI (MI) SUMMARY STATISTICS | MISSISSIPPI (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 35,932.50 -98.79% 2,976,149.00

Persons under 18 years, percent 20.95% -10.85% 23.50%

Persons 65 years and over, percent 12.75% -22.26% 16.40%

White alone, percent 62.25% 5.33% 59.10%

Owner-occupied housing unit rate, 2014 - 2018 42.45% -37.76% 68.20%

Median value of owner-occupied housing units, 2014 - 2018 $163,950.00 43.19% $114,500.00

Median Gross Rent, 2014 - 2018 $814.00 6.82% $762.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 89.00% 6.08% 83.90%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 36.50% 67.43% 21.80%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 56.40% -1.05% 57.00%

Median household income (in 2018 dollars), 2014 - 2018 $39,457.00 -9.43% $43,567.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $24,345.00 3.89% $23,434.00

Persons in poverty, percent 26.10% 32.49% 19.70%

Population per square mile, 2010 1,044.55 16x 63.20

MISSOURI CITIES W/ BDSA vs. MISSOURI STATE OVERALL BDSA CITIES MISSOURI (MI) SUMMARY STATISTICS | MISSOURI (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 300,576.00 -95.10% 6,137,428.00

Persons under 18 years, percent 19.70% -11.66% 22.30%

Persons 65 years and over, percent 12.60% -27.17% 17.30%

White alone, percent 46.20% -44.27% 82.90%

Owner-occupied housing unit rate, 2014 - 2018 43.40% -35.03% 66.80%

Median value of owner-occupied housing units, 2014 - 2018 $131,900.00 -12.99% $151,600.00

Median Gross Rent, 2014 - 2018 $810.00 0.12% $809.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 86.90% -3.01% 89.60%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 35.00% 22.38% 28.60%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 65.40% 4.47% 62.60%

Median household income (in 2018 dollars), 2014 - 2018 $41,107.00 -23.25% $53,560.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $28,478.00 -3.59% $29,537.00

Persons in poverty, percent 24.20% 83.33% 13.20%

Population per square mile, 2010 5,157.50 58x 87.10

56

NEBRASKA CITIES W/ BDSA vs. NEBRASKA STATE OVERALL BDSA CITIES NEBRASKA (NE) SUMMARY STATISTICS | NEBRASKA (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 383,647.00 -80.17% 1,934,408.00

Persons under 18 years, percent 23.70% -3.66% 24.60%

Persons 65 years and over, percent 12.70% -21.60% 16.20%

White alone, percent 81.50% -7.49% 88.10%

Owner-occupied housing unit rate, 2014 - 2018 57.65% -12.78% 66.10%

Median value of owner-occupied housing units, 2014 - 2018 $156,150.00 5.65% $147,800.00

Median Gross Rent, 2014 - 2018 $859.00 6.71% $805.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 91.00% -0.11% 91.10%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 37.70% 20.45% 31.30%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 70.60% 1.58% 69.50%

Median household income (in 2018 dollars), 2014 - 2018 $56,002.00 -5.27% $59,116.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $30,905.50 -0.63% $31,101.00

Persons in poverty, percent 14.25% 29.55% 11.00%

Population per square mile, 2010 3,058.65 128x 23.80

NEVADA CITIES W/ BDSA vs. NEVADA STATE OVERALL BDSA CITIES NEVADA (NE) SUMMARY STATISTICS | NEVADA (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 651,319.00 -78.85% 3,080,156.00

Persons under 18 years, percent 24.10% 7.11% 22.50%

Persons 65 years and over, percent 14.50% -9.94% 16.10%

White alone, percent 62.20% -15.83% 73.90%

Owner-occupied housing unit rate, 2014 - 2018 52.50% -5.91% 55.80%

Median value of owner-occupied housing units, 2014 - 2018 $234,700.00 -3.18% $242,400.00

Median Gross Rent, 2014 - 2018 $1,057.00 -0.28% $1,060.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 84.40% -2.20% 86.30%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 23.90% -1.24% 24.20%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 62.60% -1.26% 63.40%

Median household income (in 2018 dollars), 2014 - 2018 $54,694.00 -5.04% $57,598.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $29,304.00 -2.19% $29,961.00

Persons in poverty, percent 15.80% 22.48% 12.90%

Population per square mile, 2010 4,298.20 174x 24.60

57

NEW HAMPSHIRE CITIES W/ BDSA vs. NEW HAMPSHIRE STATE OVERALL BDSA CITIES NEW (NE) HAMPSHIRE SUMMARY STATISTICS | NEW HAMPSHIRE (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 8,636.00 -99.36% 1,359,711.00

Persons under 18 years, percent 10.70% -43.09% 18.80%

Persons 65 years and over, percent 12.30% -34.22% 18.70%

White alone, percent 79.40% -14.72% 93.10%

Owner-occupied housing unit rate, 2014 - 2018 56.10% -20.99% 71.00%

Median value of owner-occupied housing units, 2014 - 2018 $576,700.00 128.13% $252,800.00

Median Gross Rent, 2014 - 2018 $1,436.00 33.33% $1,077.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 95.80% 3.12% 92.90%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 82.70% 126.58% 36.50%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 44.40% -34.42% 67.70%

Median household income (in 2018 dollars), 2014 - 2018 $103,558.00 39.84% $74,057.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $45,383.00 17.73% $38,548.00

Persons in poverty, percent 13.30% 75.00% 7.60%

Population per square mile, 2010 1,911.00 12x 147.00

NEW JERSEY CITIES W/ BDSA vs. NEW JERSEY STATE OVERALL BDSA CITIES NEW JERSEY (NE) SUMMARY STATISTICS | NEW JERSEY (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 133,044.53 -98.50% 8,882,190.00

Persons under 18 years, percent 20.73% -4.91% 21.80%

Persons 65 years and over, percent 15.88% -4.32% 16.60%

White alone, percent 66.73% -7.19% 71.90%

Owner-occupied housing unit rate, 2014 - 2018 56.94% -10.89% 63.90%

Median value of owner-occupied housing units, 2014 - 2018 $553,776.47 68.89% $327,900.00

Median Gross Rent, 2014 - 2018 $1,365.12 5.41% $1,295.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 89.81% 0.35% 89.50%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 55.19% 41.87% 38.90%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 61.48% -6.13% 65.50%

Median household income (in 2018 dollars), 2014 - 2018 $95,566.65 20.42% $79,363.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $55,175.65 34.92% $40,895.00

Persons in poverty, percent 11.99% 26.25% 9.50%

Population per square mile, 2010 6,182.17 4x 1,195.50

58

NEW MEXICO CITIES W/ BDSA vs. NEW MEXICO STATE OVERALL BDSA CITIES NEW MEXICO (NE) SUMMARY STATISTICS | NEW MEXICO (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 78,055.50 -96.28% 2,096,829.00

Persons under 18 years, percent 17.15% -24.45% 22.70%

Persons 65 years and over, percent 27.80% 54.44% 18.00%

White alone, percent 87.90% 7.33% 81.90%

Owner-occupied housing unit rate, 2014 - 2018 68.75% 1.70% 67.60%

Median value of owner-occupied housing units, 2014 - 2018 $181,150.00 8.60% $166,800.00

Median Gross Rent, 2014 - 2018 $753.00 -9.06% $828.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 85.15% -0.18% 85.30%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 29.45% 8.67% 27.10%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 52.60% -8.36% 57.40%

Median household income (in 2018 dollars), 2014 - 2018 $43,351.50 -9.80% $48,059.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $30,264.50 16.14% $26,058.00

Persons in poverty, percent 21.45% 10.00% 19.50%

Population per square mile, 2010 155.20 8x 17.00

NEW YORK CITIES W/ BDSA vs. NEW YORK STATE OVERALL BDSA CITIES NEW YORK (NE) SUMMARY STATISTICS | NEW YORK (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 6,014,095.32 -69.08% 19,453,561.00

Persons under 18 years, percent 20.16% -2.61% 20.70%

Persons 65 years and over, percent 14.65% -13.32% 16.90%

White alone, percent 51.55% -25.93% 69.60%

Owner-occupied housing unit rate, 2014 - 2018 39.58% -26.57% 53.90%

Median value of owner-occupied housing units, 2014 - 2018 $536,604.51 77.57% $302,200.00

Median Gross Rent, 2014 - 2018 $1,414.77 14.09% $1,240.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 83.82% -3.10% 86.50%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 39.85% 10.99% 35.90%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 58.39% -7.32% 63.00%

Median household income (in 2018 dollars), 2014 - 2018 $64,641.35 -1.04% $65,323.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $39,042.20 4.47% $37,370.00

Persons in poverty, percent 18.92% 39.08% 13.60%

Population per square mile, 2010 20,628.16 49x 411.20

59

NORTH CAROLINA CITIES W/ BDSA vs. NORTH CAROLINA STATE BDSA CITIES NORTH OVERALL (NO) CAROLINA SUMMARY STATISTICS | NORTH CAROLINA (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 92,870.00 -99.11% 10,488,084.00

Persons under 18 years, percent 17.40% -20.55% 21.90%

Persons 65 years and over, percent 18.40% 10.18% 16.70%

White alone, percent 83.00% 17.56% 70.60%

Owner-occupied housing unit rate, 2014 - 2018 49.60% -23.69% 65.00%

Median value of owner-occupied housing units, 2014 - 2018 $242,500.00 46.17% $165,900.00

Median Gross Rent, 2014 - 2018 $1,001.00 14.14% $877.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 92.40% 5.72% 87.40%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 47.80% 56.72% 30.50%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 63.90% 4.24% 61.30%

Median household income (in 2018 dollars), 2014 - 2018 $47,803.00 -8.80% $52,413.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $32,459.00 10.19% $29,456.00

Persons in poverty, percent 13.50% -3.57% 14.00%

Population per square mile, 2010 1,855.90 8x 196.10

OHIO CITIES W/ BDSA vs. OHIO STATE OVERALL BDSA CITIES OHIO (OH) SUMMARY STATISTICS | OHIO (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 478,003.93 -95.91% 11,689,100.00

Persons under 18 years, percent 21.90% -0.90% 22.10%

Persons 65 years and over, percent 12.46% -28.78% 17.50%

White alone, percent 51.48% -36.99% 81.70%

Owner-occupied housing unit rate, 2014 - 2018 43.05% -34.77% 66.00%

Median value of owner-occupied housing units, 2014 - 2018 $109,600.00 -21.71% $140,000.00

Median Gross Rent, 2014 - 2018 $774.29 -1.74% $788.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 85.53% -5.07% 90.10%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 28.62% 2.95% 27.80%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 63.39% 0.45% 63.10%

Median household income (in 2018 dollars), 2014 - 2018 $39,701.64 -27.20% $54,533.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $24,550.79 -18.98% $30,304.00

Persons in poverty, percent 27.53% 98.05% 13.90%

Population per square mile, 2010 4,050.40 13x 282.30

60

OREGON CITIES W/ BDSA vs. OREGON STATE OVERALL BDSA CITIES OREGON (OR) SUMMARY STATISTICS | OREGON (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 172,622.00 -95.91% 4,217,737.00

Persons under 18 years, percent 17.70% -13.66% 20.50%

Persons 65 years and over, percent 15.40% -15.38% 18.20%

White alone, percent 83.30% -3.92% 86.70%

Owner-occupied housing unit rate, 2014 - 2018 47.90% -22.62% 61.90%

Median value of owner-occupied housing units, 2014 - 2018 $272,000.00 -5.33% $287,300.00

Median Gross Rent, 2014 - 2018 $988.00 -5.90% $1,050.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 93.10% 2.99% 90.40%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 41.30% 25.53% 32.90%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 61.90% -0.32% 62.10%

Median household income (in 2018 dollars), 2014 - 2018 $49,029.00 -17.45% $59,393.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $29,306.00 -8.55% $32,045.00

Persons in poverty, percent 21.50% 70.63% 12.60%

Population per square mile, 2010 3,572.10 89x 39.90

PENNSYLVANIA CITIES W/ BDSA vs. PENNSYLVANIA STATE OVERALL BDSA CITIES PENNSYLVANIA (PE) SUMMARY STATISTICS | PENNSYLVANIA (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 867,463.94 -93.22% 12,801,989.00

Persons under 18 years, percent 21.39% 3.83% 20.60%

Persons 65 years and over, percent 14.70% -21.39% 18.70%

White alone, percent 56.95% -30.21% 81.60%

Owner-occupied housing unit rate, 2014 - 2018 54.80% -20.58% 69.00%

Median value of owner-occupied housing units, 2014 - 2018 $184,147.06 5.77% $174,100.00

Median Gross Rent, 2014 - 2018 $1,002.38 9.55% $915.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 86.62% -3.97% 90.20%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 32.98% 7.08% 30.80%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 61.41% -1.90% 62.60%

Median household income (in 2018 dollars), 2014 - 2018 $53,059.71 -10.74% $59,445.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $31,277.79 -4.90% $32,889.00

Persons in poverty, percent 21.09% 72.88% 12.20%

Population per square mile, 2010 7,889.79 26x 293.90

61

RHODE ISLAND CITIES W/ BDSA vs. RHODE ISLAND STATE OVERALL BDSA CITIES RHODE ISLAND (RH) SUMMARY STATISTICS | RHODE ISLAND (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 161,781.00 -84.73% 1,059,361.00

Persons under 18 years, percent 20.47% 6.04% 19.30%

Persons 65 years and over, percent 13.97% -21.09% 17.70%

White alone, percent 67.30% -19.50% 83.60%

Owner-occupied housing unit rate, 2014 - 2018 48.23% -20.01% 60.30%

Median value of owner-occupied housing units, 2014 - 2018 $237,500.00 -4.92% $249,800.00

Median Gross Rent, 2014 - 2018 $1,014.67 3.43% $981.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 84.70% -3.75% 88.00%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 35.13% 5.51% 33.30%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 62.60% -2.80% 64.40%

Median household income (in 2018 dollars), 2014 - 2018 $55,205.67 -12.78% $63,296.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $30,623.33 -11.54% $34,619.00

Persons in poverty, percent 20.00% 55.04% 12.90%

Population per square mile, 2010 6,579.37 5x 1,018.10

TEXAS CITIES W/ BDSA vs. TEXAS STATE OVERALL BDSA CITIES TEXAS (TE) SUMMARY STATISTICS | TEXAS (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 1,594,739.64 -94.50% 28,995,881.00

Persons under 18 years, percent 25.36% -0.56% 25.50%

Persons 65 years and over, percent 10.07% -21.94% 12.90%

White alone, percent 60.98% -22.51% 78.70%

Owner-occupied housing unit rate, 2014 - 2018 45.15% -27.06% 61.90%

Median value of owner-occupied housing units, 2014 - 2018 $150,333.33 -7.03% $161,700.00

Median Gross Rent, 2014 - 2018 $1,033.28 3.53% $998.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 78.93% -5.13% 83.20%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 32.91% 12.31% 29.30%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 68.05% 6.00% 64.20%

Median household income (in 2018 dollars), 2014 - 2018 $54,469.67 -8.56% $59,570.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $32,327.33 7.25% $30,143.00

Persons in poverty, percent 11.36% -23.77% 14.90%

Population per square mile, 2010 3,292.17 33x 96.30

62

UTAH CITIES W/ BDSA vs. UTAH STATE OVERALL BDSA CITIES UTAH (UT) SUMMARY STATISTICS | UTAH (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 5,336.00 -99.83% 3,205,958.00

Persons under 18 years, percent 20.30% -30.00% 29.00%

Persons 65 years and over, percent 15.30% 34.21% 11.40%

White alone, percent 90.80% 0.22% 90.60%

Owner-occupied housing unit rate, 2014 - 2018 53.20% -23.89% 69.90%

Median value of owner-occupied housing units, 2014 - 2018 $231,700.00 -9.74% $256,700.00

Median Gross Rent, 2014 - 2018 $824.00 -16.60% $988.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 91.20% -0.87% 92.00%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 28.10% -15.62% 33.30%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 72.00% 6.04% 67.90%

Median household income (in 2018 dollars), 2014 - 2018 $48,879.00 -28.51% $68,374.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $23,219.00 -17.78% $28,239.00

Persons in poverty, percent 10.50% 16.67% 9.00%

Population per square mile, 2010 1,220.90 35x 33.60

VIRGINIA CITIES W/ BDSA vs. VIRGINIA STATE OVERALL BDSA CITIES VIRGINIA (VI) SUMMARY STATISTICS | VIRGINIA (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 122,695.00 -98.56% 8,535,519.00

Persons under 18 years, percent 14.40% -33.94% 21.80%

Persons 65 years and over, percent 13.60% 130.51% 5.90%

White alone, percent 59.95% -13.62% 69.40%

Owner-occupied housing unit rate, 2014 - 2018 45.75% -30.89% 66.20%

Median value of owner-occupied housing units, 2014 - 2018 $260,400.00 -1.70% $264,900.00

Median Gross Rent, 2014 - 2018 $1,064.00 -11.48% $1,202.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 90.30% 1.12% 89.30%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 47.60% 24.61% 38.20%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 56.85% -11.45% 64.20%

Median household income (in 2018 dollars), 2014 - 2018 $50,640.00 -29.24% $71,564.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $30,419.00 -19.45% $37,763.00

Persons in poverty, percent 23.45% 119.16% 10.70%

Population per square mile, 2010 2,487.00 11x 202.60

63

WASHINGTON CITIES W/ BDSA vs. WASHINGTON STATE OVERALL BDSA CITIES WASHINGTON (WA) SUMMARY STATISTICS | WASHINGTON (BDSA-Wt'd) % DIFF (OVERALL)

Average Population 753,675.00 -90.10% 7,614,893.00

Persons under 18 years, percent 15.10% -30.73% 21.80%

Persons 65 years and over, percent 12.30% -22.64% 15.90%

White alone, percent 68.00% -13.38% 78.50%

Owner-occupied housing unit rate, 2014 - 2018 46.10% -26.48% 62.70%

Median value of owner-occupied housing units, 2014 - 2018 $605,200.00 94.16% $311,700.00

Median Gross Rent, 2014 - 2018 $1,496.00 25.29% $1,194.00

High school graduate or higher, percent of persons age 25+ years, 2014 - 2018 94.60% 3.84% 91.10%

Bachelor's degree or higher, percent of persons age 25+ years, 2014 - 2018 62.80% 77.90% 35.30%

In civilian labor force, total, percent of population age 16+ years, 2014 - 2018 72.90% 14.80% 63.50%

Median household income (in 2018 dollars), 2014 - 2018 $85,562.00 22.03% $70,116.00

Per capita income in past 12 months (in 2018 dollars), 2014 - 2018 $55,789.00 51.24% $36,888.00

Persons in poverty, percent 11.80% 14.56% 10.30%

Population per square mile, 2010 7,250.90 71x 101.20

64 Appendix B

Economic Indicators Used in This Study

All Descriptions Pasted directly from (census.gov/quickfacts)

Average Population

All persons who are "usually resident" in a specified geographic area. For the United States, the resident population includes all persons who usually reside in the 50 states and the District of Columbia, but excludes residents of the Commonwealth of Puerto Rico and the Island areas under U.S. sovereignty or jurisdiction (principally American Samoa, Guam, United States Virgin Islands, and the Commonwealth of the Northern Mariana Islands). In addition, the U.S. resident population excludes U.S. Armed Forces overseas and civilian U.S. citizens whose usual place of residence is outside the United States.

Persons under 18 years, percent

Age estimates of the population are produced for places, zona urbanas and comunidades (place- equivalents for Puerto Rico), and minor civil divisions. Data on age are used to determine the applicability of other questions for a particular individual and to classify other characteristics in tabulations. Age data are needed to interpret most social and economic characteristics used to plan and analyze programs and policies.

Persons 65 years and over, percent

Age estimates of the population are produced for places, zona urbanas and comunidades (place- equivalents for Puerto Rico), and minor civil divisions. Data on age are used to determine the applicability of other questions for a particular individual and to classify other characteristics in tabulations. Age data are needed to interpret most social and economic characteristics used to plan and analyze programs and policies. 65

White alone, percent

The U.S. Census Bureau collects race data in accordance with guidelines provided by the U.S. Office of

Management and Budget (OMB), and these data are based on self-identification. The racial categories included in the census questionnaire generally reflect a social definition of race recognized in this country and not an attempt to define race biologically, anthropologically, or genetically. In addition, it is recognized that the categories of the race item include racial and national origin or sociocultural groups.

People may choose to report more than one race to indicate their racial mixture, such as "American

Indian" and "White." People who identify their origin as Hispanic, Latino, or Spanish may be of any race.

White is defined as a person having origins in any of the original peoples of Europe, the Middle East, or

North Africa. It includes people who indicate their race as "White" or report entries such as Irish,

German, Italian, Lebanese, Arab, Moroccan, or Caucasian.

Owner-occupied housing unit rate, 2014 – 2018

A housing unit is owner-occupied if the owner or co-owner lives in the unit, even if it is mortgaged or not fully paid for. The owner or co-owner must live in the unit and usually is Person 1 on the questionnaire.

The unit is "Owned by you or someone in this household with a mortgage or loan" if it is being purchased with a mortgage or some other debt arrangement such as a deed of trust, trust deed, contract to purchase, land contract, or purchase agreement. The unit also is considered owned with a mortgage if it is built on leased land and there is a mortgage on the unit. Mobile homes occupied by owners with installment loan balances also are included in this category. For the complete definition, go to ACS subject definitions "Tenure." The homeownership rate is computed by dividing the number of owner-occupied housing units by the number of occupied housing units or households. This Fact is based on data collected in the American Community Survey (ACS) and the Puerto Rico Community Survey (PRCS) conducted annually by the U.S. Census Bureau. A sample of over 3.5 million housing unit addresses is interviewed 66 each year over a 12-month period. This Fact (estimate) is based on five years of ACS and PRCS sample data and describes the average value of person, household and housing unit characteristics over this period of collection.

Median value of owner-occupied housing units, 2014 – 2018

Value is the respondent's estimate of how much the property (house and lot) would sell for if it were for sale. This tabulation includes only specified owner-occupied housing units--one-family houses on less than 10 acres without a business or medical office on the property. These data exclude mobile homes, houses with a business or medical office, houses on 10 or more acres, and housing units in multi-unit structures. Certain tabulations elsewhere include the value of all owner-occupied housing units and vacant-for-sale housing units. Also available are data on mortgage status and selected monthly owner costs. The median divides the value distribution into two equal parts: one-half of the cases falling below the median value of the property (house and lot) and one-half above the median. Median value calculations are rounded to the nearest hundred dollars. This Fact is based on data collected in the

American Community Survey (ACS) and the Puerto Rico Community Survey (PRCS) conducted annually by the U.S. Census Bureau. A sample of over 3.5 million housing unit addresses is interviewed each year over a 12-month period. This Fact (estimate) is based on five years of ACS and PRCS sample data and describes the average value of person, household and housing unit characteristics over this period of collection.

Median Gross Rent, 2014 – 2018

Gross rent provides information on the monthly housing cost expenses for renters. Gross rent is the contract rent plus the estimated average monthly cost of utilities (electricity, gas, and water and sewer) and fuels (oil, coal, kerosene, wood, etc.) if these are paid by the renter (or paid for the renter by someone else). Gross rent is intended to eliminate differentials that result from varying practices with respect to the 67 inclusion of utilities and fuels as part of the rental payment. The estimated costs of water and sewer, and fuels are reported on a 12-month basis but are converted to monthly figures for the tabulations. Renter units occupied without payment of rent are shown separately as "No rent paid" in the tabulations For the complete definition, go to ACS subject definitions "Gross Rent." This Fact is based on data collected in the American Community Survey (ACS) and the Puerto Rico Community Survey (PRCS) conducted annually by the U.S. Census Bureau. A sample of over 3.5 million housing unit addresses is interviewed each year over a 12-month period. This Fact (estimate) is based on five years of ACS and PRCS sample data and describes the average value of person, household and housing unit characteristics over this period of collection.

High school graduate or higher, percent of persons age 25+ years, 2014 – 2018

High School Graduates include people whose highest degree was a high school diploma or its equivalent, people who attended college but did not receive a degree, and people who received an associate's, bachelor's, master's, or professional or doctorate degree. People who reported completing the 12th grade but not receiving a diploma are not included. These data include only persons 25 years old and over. The percentages are obtained by dividing the counts of graduates by the total number of persons 25 years old and over. This Fact is based on data collected in the American Community Survey (ACS) and the Puerto

Rico Community Survey (PRCS) conducted annually by the U.S. Census Bureau. A sample of over 3.5 million housing unit addresses is interviewed each year over a 12-month period. This Fact (estimate) is based on five years of ACS and PRCS sample data and describes the average value of person, household and housing unit characteristics over this period of collection.

Bachelor's degree or higher, percent of persons age 25+ years, 2014 – 2018

Persons with a Bachelor's Degree or Higher are those who have received a bachelor's degree from a college or university, or a master's, professional, or doctorate degree. For the complete definition, go 68 to ACS subject definitions "Educational Attainment." These data include only persons 25 years old and over. The percentages are obtained by dividing the counts of graduates by the total number of persons 25 years old and over. This Fact is based on data collected in the American Community Survey (ACS) and the Puerto Rico Community Survey (PRCS) conducted annually by the U.S. Census Bureau. A sample of over 3.5 million housing unit addresses is interviewed each year over a 12-month period. This Fact

(estimate) is based on five years of ACS and PRCS sample data and describes the average value of person, household and housing unit characteristics over this period of collection.

In civilian labor force, total, percent of population age 16+ years, 2014 – 2018

Civilian Labor Force consists of people classified as employed or unemployed in accordance with the criteria described below. Employed - This category includes all civilians 16 years old and over who either

(1) were "at work," that is, those who did any work at all during the reference week as paid employees, worked in their own business or profession, worked on their own farm, or worked 15 hours or more as unpaid workers on a family farm or in a family business; or (2) were "with a job but not at work," that is, those who did not work during the reference week but had jobs or businesses from which they were temporarily absent due to illness, bad weather, industrial dispute, vacation, or other personal reasons.

Excluded from the employed are people whose only activity consisted of work around the house or unpaid volunteer work for religious, charitable, and similar organizations; also excluded are all institutionalized people and people on active duty in the United States Armed Forces. For the complete definition, go to ACS subject definitions "Employment Status." This Fact is based on data collected in the

American Community Survey (ACS) and the Puerto Rico Community Survey (PRCS) conducted annually by the U.S. Census Bureau. A sample of over 3.5 million housing unit addresses is interviewed each year over a 12-month period. This Fact (estimate) is based on five years of ACS and PRCS sample data and describes the average value of person, household and housing unit characteristics over this period of collection. 69

Median household income (in 2018 dollars), 2014 – 2018

Income in the Past 12 Months - Income of Households: This includes the income of the householder and all other individuals 15 years old and over in the household, whether they are related to the householder or not. Because many households consist of only one person, average household income is usually less than average family income. Although the household income statistics cover the past 12 months, the characteristics of individuals and the composition of households refer to the time of interview. Thus, the income of the household does not include amounts received by individuals who were members of the household during all or part of the past 12 months if these individuals no longer resided in the household at the time of interview. Similarly, income amounts reported by individuals who did not reside in the household during the past 12 months but who were members of the household at the time of interview are included. However, the composition of most households was the same during the past 12 months as at the time of interview. The median divides the income distribution into two equal parts: one-half of the cases falling below the median income and one-half above the median. For households and families, the median income is based on the distribution of the total number of households and families including those with no income. The median income for individuals is based on individuals 15 years old and over with income.

Median income for households, families, and individuals is computed on the basis of a standard distribution. For the complete definition, go to ACS subject definitions "Income in the Past 12 Months."

This Fact is based on data collected in the American Community Survey (ACS) and the Puerto Rico

Community Survey (PRCS) conducted annually by the U.S. Census Bureau. A sample of over 3.5 million housing unit addresses is interviewed each year over a 12-month period. This Fact (estimate) is based on five years of ACS and PRCS sample data and describes the average value of person, household and housing unit characteristics over this period of collection.

Per capita income in past 12 months (in 2018 dollars), 2014 – 2018 70 Per capita income is the mean income computed for every man, woman, and child in a particular group including those living in group quarters. It is derived by dividing the aggregate income of a particular group by the total population in that group. This measure is rounded to the nearest whole dollar. For the complete definition, go to ACS subject definitions "Income in the Past 12 Months, Per Capita Income."

This Fact is based on data collected in the American Community Survey (ACS) and the Puerto Rico

Community Survey (PRCS) conducted annually by the U.S. Census Bureau. A sample of over 3.5 million housing unit addresses is interviewed each year over a 12-month period. This Fact (estimate) is based on five years of ACS and PRCS sample data and describes the average value of person, household and housing unit characteristics over this period of collection.

Persons in poverty, percent

How the Census Bureau measures poverty: The Census Bureau poverty definition - Following the Office of Management and Budget's (OMB) Statistical Policy Directive 14, the Census Bureau uses a set of money income thresholds that vary by family size and composition to determine who is in poverty. If a family's total income is less than the family's threshold, then that family and every individual in it is considered in poverty. The official poverty thresholds do not vary geographically, but they are updated for inflation using Consumer Price Index (CPI-U). The official poverty definition uses money income before taxes and does not include capital gains or noncash benefits (such as public housing, Medicaid, and food stamps). For more information: How the Census Bureau Measures Poverty Data at a national level -

Current Population Survey Annual Social and Economic Supplement (CPS ASEC); Data at a state level -

American Community Survey (ACS), Puerto Rico Community Survey (PRCS), one-year estimates.

Data at a county level - Small Area Income and Poverty Estimates (SAIPE); Data at a Sub-county level -

American Community Survey (ACS) and Puerto Rico Community Survey (PRCS), five-year estimates.

Population per square mile, 2010 71 Land area - an area measurement providing the size, in square meters, of the land portions of geographic entities for which the Census Bureau tabulates and disseminates data. Area is calculated from the specific boundar recorded for each entit in the Census Bureaus geographic database (see "MAF/TIGER

Database"). The Census Bureau provides area measurement data for both land area and water area. The water area figures include inland, coastal, Great Lakes, and territorial sea water. Inland water consists of an lake, reseroir, pond, or similar bod of ater that is recorded in the Census Bureaus geographic database. It also includes any river, creek, canal, stream, or similar feature that is recorded in that database as a two-dimensional feature (rather than as a single line). The portions of the oceans and related large embaments (such as Chesapeake Bay and Puget Sound), the Gulf of Mexico, and the Caribbean Sea that belong to the United States and its territories are classified as coastal and territorial waters; the Great

Lakes are treated as a separate water entity. Rivers and bays that empty into these bodies of water are treated as inland water from the point beyond which they are narrower than 1 nautical mile across.

Identification of land and inland, coastal, territorial, and Great Lakes waters is for data presentation purposes only and does not necessarily reflect their legal definitions. Land area measurements are originally recorded as whole square meters (to convert square meters to square kilometers, divide by

1,000,000; to convert square kilometers to square miles, divide by 2.58999; to convert square meters to square miles, divide by 2,589,988). Persons per square mile - population and housing unit density are computed by dividing the total population or number of housing units within a geographic entity by the land area of that entity measured in square miles or in square kilometers. Density is expressed as

"population per square mile (kilometer)" or "housing units per square mile (kilometer)." To determine population per square kilometer, multiply the population per square mile by .3861.

72

Appendix C

BDSA Dispersal by Zip code

ZIPCODE BDSA SKU 75201 11 1 10019 7 2 10014 7 3 10022 7 4 02138 7 5 19104 7 6 10011 6 7 10012 6 8 10036 6 9 06511 6 10 10017 6 11 47201 6 12 90291 5 13 14853 5 14 77006 5 15 10016 5 16 10027 5 17 08544 5 18 90265 5 19 90095 5 20 90012 4 21 90048 4 22 02115 4 23 60601 4 24 76107 4 25 08540 4 26 02142 4 27 10013 3 28 70117 3 29 10002 3 30 73 20001 3 31 90212 3 32 10003 3 33 14850 3 34 95014 3 35 44106 3 36 30309 3 37 20007 3 38 02139 3 39 03755 3 40 11937 3 41 18103 3 42 43210 3 43 34747 3 44 90049 3 45 10005 3 46 90210 3 47 77002 3 48 32830 2 49 33140 2 50 06840 2 51 10007 2 52 89109 2 53 94103 2 54 90028 2 55 11976 2 56 10065 2 57 33139 2 58 94118 2 59 10010 2 60 10153 2 61 19103 2 62 94305 2 63 10021 2 64 60611 2 65 60603 2 66 02903 2 67 77005 2 68 60614 2 69 12504 2 70 47203 2 71 19106 2 72 74 15217 2 73 48109 2 74 19118 2 75 06519 2 76 10023 2 77 33154 2 78 47631 2 79 50312 2 80 11706 2 81 30308 2 82 06492 2 83 75202 2 84 06897 2 85 76102 2 86 43215 1 87 78704 1 88 81611 1 89 11963 1 90 84532 1 91 11201 1 92 55415 1 93 20024 1 94 90254 1 95 90046 1 96 90079 1 97 90025 1 98 91505 1 99 90266 1 100 93101 1 101 85254 1 102 90802 1 103 91766 1 104 90007 1 105 45221 1 106 20746 1 107 97401 1 108 91106 1 109 10008 1 110 48075 1 111 10044 1 112 45202 1 113 48824 1 114 33160 1 115 33132 1 116 55403 1 117 94599 1 118 60616 1 119 75 98104 1 120 33401 1 121 33180 1 122 68102 1 123 20002 1 124 93012 1 125 87901 1 126 52242 1 127 94108 1 128 10001 1 129 80517 1 130 90036 1 131 02478 1 132 48304 1 133 02481 1 134 63108 1 135 87540 1 136 01267 1 137 63130 1 138 63112 1 139 04609 1 140 08103 1 141 18101 1 142 19066 1 143 19027 1 144 19010 1 145 77004 1 146 17801 1 147 19073 1 148 19123 1 149 19107 1 150 08008 1 151 11542 1 152 06831 1 153 10536 1 154 19807 1 155 04662 1 156 06405 1 157 81657 1 158 11975 1 159 02807 1 160 02554 1 161 18017 1 162 92037 1 163 44074 1 164 19087 1 165 19102 1 166 76 19130 1 167 98101 1 168 19081 1 169 12534 1 170 08618 1 171 19716 1 172 40536 1 173 48104 1 174 91521 1 175 91506 1 176 92549 1 177 90077 1 178 92612 1 179 21044 1 180 94521 1 181 21210 1 182 90403 1 183 90015 1 184 90401 1 185 90731 1 186 95652 1 187 90405 1 188 91360 1 189 95765 1 190 92617 1 191 90404 1 192 52245 1 193 55455 1 194 43620 1 195 92805 1 196 45229 1 197 98109 1 198 89106 1 199 39530 1 200 10038 1 201 94025 1 202 60088 1 203 48126 1 204 06002 1 205 23230 1 206 14222 1 207 50309 1 208 78705 1 209 10110 1 210 20560 1 211 55404 1 212 10075 1 213 77 85003 1 214 92840 1 215 93532 1 216 95113 1 217 93460 1 218 92101 1 219 06604 1 220 06105 1 221 06820 1 222 33480 1 223 34102 1 224 49740 1 225 39759 1 226 07935 1 227 07021 1 228 07102 1 229 10069 1 230 12720 1 231 10461 1 232 11568 1 233 11050 1 234 11238 1 235 10018 1 236 10549 1 237 11747 1 238 10457 1 239 11722 1 240 10560 1 241 75225 1 242 11530 1 243 80290 1 244 20016 1 245 60605 1 246 96822 1 247 96848 1 248 13210 1 249 15219 1 250 90067 1 251 34243 1 252 80305 1 253 13202 1 254 19801 1 255 14627 1 256 20565 1 257 02125 1 258 28801 1 259 47405 1 260 78 80265 1 261 10577 1 262 33131 1 263 30339 1 264 35233 1 265 44114 1 266 94945 1 267 20008 1 268 10028 1 269 10024 1 270 10280 1 271 94607 1 272 10128 1 273 23185 1 274 06459 1 275 01003 1 276 14623 1 277 76109 1 278 20549 1 279 10573 1 280 18109 1 281 95066 1 282 77079 1 283 61265 1 284 14831 1 285 06510 1 286 06810 1 287 08889 1 288 06156 1 289 41102 1 290 30346 1 291 61625 1 292 01608 1 293 46802 1 294 20006 1 295 20005 1 296 80204 1 297 60563 1 298 02117 1 299 46601 1 300 44115 1 301 63101 1 302 77204 1 303 30303 1 304 80203 1 305 15222 1 306 68508 1 307 79

BIBLIOGRAPHY

Ahlfeldt, G. M. (2013). Urbanity. SERC Discussion Paper 136.

Ahlfeldt, G. M., & Kavetsos, G. (2014). Form or Function? The impact of new sports stadia on property prices in London. Journal of the Royal Statistical Society A, 177(1), 169-190.

Ahlfeldt, G. M., & Kavetsos, G. (2014). Form or Function? The impact of new sports stadia on property prices in London. Journal of the Royal Statistical Society A, 177(1), 169-190.

Ahlfeldt, G. M., & Maennig, W. (2009). Arenas, Arena Architecture and the Impact on Location Desirabilit: The Case of Olmpic Arenas in Berlin-Prenzlauer Berg. Urban Studies, 46(7), 1343-1362.

Ahlfeldt, G. M., & Maennig, W. (2010). Substitutability and Complementarity of Urban Amenities: External Effects of Built Heritage in Berlin. Real Estate Economics, 38(2), 285-323.

Ahlfeldt, G. M., Moeller, K., Waights, S., & Wendland, N. (2014). Game of zones: The political economy of conservation areas. CESifo Working Paper No. 4755.

Ahlfeldt, Gabriel M. and Holman, Nancy, Distinctively Different: A New Approach to Valuing Architectural Amenities (February 27, 2015). CESifo Working Paper Series No. 5221. Available at SSRN: https://ssrn.com/abstract=2576166

Albouy, D. (2009). What are cities worth? Land rents, local productivity, and the capitalization of amenity values. NBER Working Paper 14981.

Albouy, D. (2012). Are Big Cities Bad Places to Live? Estimating Quality of Life across Metropolitan Areas. Working Paper.

BEDNARIK, ROBERT G. THE OLDEST KNOWN ROCK ART IN THE WORLD. Anthropologie (1962-), vol. 39, no. 2/3, 2001, pp. 8998. JSTOR, www.jstor.org/stable/26292558. Accessed 20 May 2020.

Bell, D., & Jane, M. (2003). Design-led Urban Regeneration: A Critical Perspective. Local Economy, 18(2), 121134. https://doi.org/10.1080/0269094032000061396

Bhimbetka Petroglyphs (290,000-700,000 BCE) Cupules at Auditorium Cave & Daraki-Chattan Rock Shelter. (n.d.). Retrieved July 13, 2020, from http://www.visual-arts- cork.com/prehistoric/bhimbetka-petroglyphs.htm

Blomquist, G. C., Berger, M. C., & Hoehn, J. P. (1988). New Estimates of Quality of Life in Urban Areas. The American Economic Review, 78(1), 89-107. doi: 10.2307/1814700

Blostein, D., Libetti, R., & Crow, K. (2018, September 19). How a $450 Million da Vinci Was Lost in America-and Later Found. Retrieved July 13, 2020, from 80 https://www.wsj.com/articles/fresh-details-reveal-how-450-million-da-vinci-was-lost-in- americaand-later-found-1537305592

Brueckner, J. K., Thisse, J.-F., & Zenou, Y. (1999). Why Is Central Paris Rich and Downtown Detroit Poor? An Amenity-Based Theory. European Economic Review, 43(1), 91-107.

Castells, M. (1983) Cultural identity, sexual liberation and urban structure: The gay community in San Francisco. In the City and the Grassroots: A Cross-Cultural Theory of Urban Social Movements, pp. 138 -170. London: Edward Arnold

Cebula, R. J. (2009). The Hedonic Pricing Model Applied to the Housing Market of the City of Savannah and Its Savannah Historic Landmark District. The Review of Regional Studies, 39(1), 9-22.

Cellini, S. R., Ferreira, F., & Rothstein, J. (2010). The value of school facility investments: Evidence from a dynamic regression discontinuity design. The Quarterly Journal of Economics, 125(1), 215-261.

Chambers, David and Dimson, Elroy and Spaenjers, Christophe, Art as an Asset: Evidence from Keynes the Collector (October 5, 2019). Available at SSRN: https://ssrn.com/abstract=2657741 or http://dx.doi.org/10.2139/ssrn.2657741

Cheshire, P. C., & Dericks, G. (2014). 'Iconic Design' as Deadweight Loss: Rent Acquisition by Design in the Constrained London Office Market. SERC discussion paper 154.

Cheshire, P. C., & Sheppard, S. (1995). On the Price of Land and the Value of Amenities. [Article]. Economica, 62(246), 247-267.

Clark, D. E. & Kahn, J. R. (1988), The social benefits of urban cultural amenities., Journal of Regional Science 28 (3), 363 - 377.

English Heritage. (2011). Valuing places a good practice guide. London: English Heritage.

English Heritage. (2012). Understanding place: Conservation Area Designation, Appraisal and Management Revision Note 2012 (2012)

Florida, R. & Mellander, C. (2010), There goes the metro: Ho and h bohemians, artists and gas affect regional housing alues., Journal of Economic Geography 10 (2), 167 188

Fre, B. (1997), Ealuating cultural propert, International Journal of Cultural Property 6, 231 246

From Ando to Zaha: Listings in NYC Buildings Designed by Pritzker Prize-Winning Architects. (n.d.). Retrieved July 13, 2020, from https://www.cityrealty.com/nyc/market- insight/features/future-nyc/from-ando-zaha-listings-nyc-buildings-designed-pritzker-prize- winning-architects/20189

Fuerst, F., McAllister, P., & Murray, C. B. (2011). Designer buildings: estimating the economic value of 'signature' architecture. Environment and Planning A, 43(1), 166-184.

81 Gabriel, S. A., & Rosenthal, S. S. (2004). Quality of the Business Environment Versus Quality of Life: Do Firms and Households Like the Same Cities? The Review of Economics and Statistics, 86(1), 483.

Gibbons, S. (2014). Gone with the Wind: Valuing the Visual Impacts of Wind turbines through House Prices. SERC Discussion Paper 159.

Holman, N., & Ahlfeldt, G. M. (2014). No escape? The coordination problem in heritage preservation. Environment & Planning A, forthcoming.

Jim, C. Y., & Chen, W. Y. (2009). Value of scenic views: Hedonic assessment of private housing in Hong Kong. Landscape and Urban Planning, 91(4), 226-234.

Julier, G. 2000: The culture of design, London: Sage

Korteweg, Arthur G. and Kraeussl, Roman and Verwijmeren, Patrick, Does It Pay to Invest in Art? A Selection-Corrected Returns Perspective (June 25, 2015). Review of Financial Studies, Vol. 29, No. 4, 2016, Available at SSRN: https://ssrn.com/abstract=2280099 or http://dx.doi.org/10.2139/ssrn.2280099

Koster, H. R. A., Van Ommeren, J. N., & Rietveld, P. (2014). Upscale Neighborhoods: Historic Amenities, Income and Spatial Sorting of Households. Journal of Economic Geography, forthcoming.

Koster, H. R. A., Van Ommeren, J. N., & Rietveld, P. (2014). Upscale Neighborhoods: Historic Amenities, Income and Spatial Sorting of Households. Journal of Economic Geography, forthcoming.

Landry, C. 1995: The Creative City, London: Demos

Ley, D. (1994) Gentrification and the politics of the new middle class. Environment and Planning D: Society and Space, 12: 53-74

Listokin, D., Listokin, B., & Lahr, M. (1998). The Contributions of Historic Preservation to Housing and Economic Development. Housing Policy Debate, 9(3), 431-478.

Los Angeles County Museum of Art (LACMA). (n.d.). Retrieved July 13, 2020, from http://www.jeannouvel.com/en/projects/los-angeles-county-museum-of-art-lacma/.

McCarthy, K.F., Ondaatje, E.H., Zakaras, L. & Brooks, A. (2004), Gifts of the Muse - Reframing the Debate About the Benefit of the Arts, Rand Corporation, Santa Monica, CA.

McIntyre, M. H. (2006). A Literature Review of The Social, Economic and Environmental Impact of Architecture and Design (Rep.). Edinburgh: Information and Analytical Services Division, Scottish Executive Education Department.

McRobbie, A. 1999: In the Culture Society: art, fashion and popular music, London: Routledge Plaza B (2006) The return on investment of the Guggenheim Museum Bilbao. Int J Urban Reg Res 30(2):452467. https://doi.org/10.1111/j.1468-2427.2006.00672.x.

82 Rauch, J. E. (1993), Productiit gains from geographic concentration of human capital: Eidence from the cities., Journal of Urban Economics 34 (3), 380 400

Sasaki, M., & Yamamoto, K. (2018). Hedonic Price Function for Residential Area Focusing on the Reasons for Residential Preferences in Japanese Metropolitan Areas. Journal of Risk and Financial Management, 11(3). doi:10.3390/jrfm11030039

Schmidt, L. & Courant, P.N. (2006), Sometimes close is good enough: The value of nearby enironmental amenities. Journal of Regional Science 46 (5), 931 951

Sheppard, S. (2013). Museums in the Neighborhood: The Local Economic Impact of Museums. Handbook of Industry Studies and Economic Geography, elgar original reference, Chapter 8.

Smith, N. (1996) The New Urban Frontier: Gentrification and the Revanchist City. London: Routledge

Vandell, K. D., & Lane, J. S. (1989). The Economics of Architecture and Urban Design: Some Preliminary Findings. Journal of the American Real Estate & Urban Economics Association, 17(2), 235-260.

What is Class A, Class B, or Class C property? (n.d.). Retrieved July 13, 2020, from https://www.realtymogul.com/knowledge-center/article/what-is-class-a-class-b-or-class-c- property

Wright F-L, 1986 Letters to Clients (Architectural Press, London)

Zukin, S. (1995) The Cultures of Cities. Cambridge, MA and Oxford: Blackwell Publishers

Zweig, J. (2018, March 30). What It Takes to Build a $100 Million Art Collection. Retrieved July 13, 2020, from https://blogs.wsj.com/moneybeat/2018/03/30/what-it-takes-to-build-a-100- million-art-collection/

ALEXANDER A. GROSEK

Education

The Pennsylvania State University | Schreyer Honors College University Park, PA

Smeal College of Business | Bachelor of Science in Finance Class of 2020

College of Arts and Architecture | Minor in Architecture Studies

Education Abroad Russia (2018), China (2019)

Studied Russian language, history and gender-related topics during a four-month study abroad program Explored engineering, education and cultural landmarks in China during a 30-day study abroad program

Relevant Experience

Chute Consignment State College, PA

Co-Founder | Head of Store Operations Jan 2020 – Mar 2020 Co-designed, renovated and managed a 90-day pop-up consignment store in State College, PA that generated ~$9.5k in top-line revenues on ~$3.5 k of expenses (primarily rent, renovation and wages for in-store employees) Built an automated Google Sheets database that tracked in-store inventory, recorded sales, managed payments to vendors, and updated a Shopify store, which cross listed every in-store SKU for sale online (shop.fittedlaundry.com)

Bank of America Merrill Lynch New York, NY

Investment Banking Summer Analyst | Consumer & Retail Group (C&R) Jun 2019 – Aug 2019 Staffed on seven corporate finance deals, including a $500 million debt refinancing for The Michaels Companies, a portfolio and credit valuation for JAB Holding Company, and a convertible debt issuance for Restoration Hardware Collaborated with ~100 C&R bankers to advise corporations and their subsidiaries on corporate finance strategy, fair market valuation, acquisition and divestment opportunities, and strategies for entering new markets

Nittany Lion Fund, LLC. University Park, PA

Director of Equity Research Aug 2018 – Dec 2018 Assisted in managing the Nittany Lion Fund (NLF), a SEC-registered hedge fund controlling ~$10 million in invested capital from 78 alumni, attempting to outperform the market through stock selection across the S&P 500 11 sectors

Lead Portfolio Manager | Real Estate Aug 2017 – Dec 2017 Collaborated with one other analyst to manage $173,000 in real estate investment trust (REIT) investments

Summer Lead Portfolio Manager | Healthcare and Real Estate May 2017 – Aug 2017 Collaborated with a team of five analysts to manage $1.17 MM in Healthcare and REIT investments

Nference, Inc. Cambridge, MA

Marketing and Business Development Intern Jun 2018 – Aug 2018 Managed digital marketing channels for the Company, co-designed and distributed a merchandise order for employees, and utilized Google, Twitter and LinkedIn Analytics to improve he Compan SEO Researched the market potential for a business intelligence software product by coordinating conversations with potential data suppliers and conducting basic data analysis using Excel pivot tables

Volunteer Experience

Saint Petersburg State University St. Petersburg, RU

English as a Second Language (ESL) Teacher Feb 2018 – May 2018 Taught weekly English classes to ~25 Russian high school students through a SPBGU university volunteer program

The Pittsburgh Project Pittsburgh, PA

Construction Volunteer Apr 2019 – Apr 2019 Worked with a team of contractors and Penn State students to build an addition o a Pibgh famil home

Interests

Interests: Concerts, Board Games, Snowboarding, Skateboarding, Hiking, Traveling, Architecture, Art, Entrepreneurship