Revitalization, Transformation, and the 'Bilbao Effect'

REVITALIZATION,
TRANSFORMATION, AND THE
‘BILBAO EFFECT’
TESTING THE LOCAL AREA IMPACT OF ICONIC ARCHITECTURAL DEVELOPMENTS IN NORTH AMERICA, 2000 TO 2009.

Matt Patterson
Department of Sociology
University of Calgary

A revised version of this article has been published in European Planning Studies, available here: https://www.tandfonline.com/doi/full/10.1080/09654313.2020.1863341.

ABSTRACT

The term “Bilbao effect” describes the potential of iconic architectural developments (IADs) designed by world famous architects to act as a catalyst for economic revitalization and transformation within neighbourhoods or regions. Despite the ubiquity of this term, its validity is still debated. Furthermore, research on the topic has relied almost exclusively on individual or small-N comparative case studies. This paper builds on this research by testing the Bilbao effect through a quantitative analysis of 142 IADs completed in Canada and the United States between 2000 and 2009. Using “fixed effects” modelling, a method that controls for selection bias, the analysis examines the effect of IADs on a set of outcome variables that measure neighbourhood-level economic and cultural changes between 2000 and 2010: population, rent, the number of local arts establishments, and the number of cultural workers living in the area. The analysis demonstrates that neighbourhoods with IADs generally experienced more economic and cultural growth than non-IAD neighbourhoods during this time period. However, the paper also complicates these findings by examining differences in how this growth manifests itself within emerging versus established neighbourhoods. These differences are illustrated through a comparison of the Dallas Arts District and Lincoln Square, Manhattan.

INTRODUCTION

Iconic architectural developments (IADs), alternatively called “starchitecture” or “star architecture”, are elaborate and attention-grabbing buildings designed by elite global architecture firms. Since the beginning of the 21st-century, these projects have served as the quintessential form of “culture-led urban re-generation” (Miles and Paddison 2005; Evans 2003), a regional

economic strategy that involves the development of cultural amenities for the purpose of attracting investors, tourists, and skilled migrants (Heidenreich and Plaza 2015).

The term “Bilbao effect” has emerged as a shorthand to refer to the promise of IADs in transforming ailing post-industrial cities into global cultural hotspots. Bilbao, Spain is often credited with having made this transition in the late 1990s in part due to the construction of the Museo Guggenheim, designed by Frank Gehry, which opened in 1997 (Stephens 1999; Plaza 2000).

Despite the prominence of the Bilbao effect narrative in contemporary urban studies, relatively little research has attempted to test the effect on a broad scale. For the most part, scholars of IADs have expressed skepticism over generalization and emphasized the diversity of motivations and outcomes of these projects (e.g. Alaily-Mattar et al. 2018; Ponzini and Nastasi 2011). As a result of this skepticism, most research has focused on individual or small-N comparative case studies that usually prioritize qualitative data (Ponzini, Alaily-Mattar, and Thierstein 2020:4).

These small-N studies have been useful in unraveling the complex webs of relationships that bring about IADs in the first place (e.g. Alaily-Mattar et al. 2018; Balke, Reuber, and Wood 2018), and the ways in which communities and audiences respond to IADs (e.g. Lindsay 2018). However, when it comes to testing the Bilbao effect directly, it is difficult for small-N case studies to disentangle the effects of a building from other causal factors (Alaily-Matter et al. 2018).

Addressing this problem, this study adopts a large-N approach, testing the Bilbao effect on neighbourhoods through an analysis of 142 IADs completed within Canada and the United States between 2000 and 2009. The approach can potentially reveal underlying causal relationships that cut across the unique complexities of individual cases.

In evaluating the Bilbao effect, this paper focuses on two specific neighbourhood-level outcomes often attributed to IADs. The first is economic revitalization, operationalized as population growth and increased rent. The second outcome is economic transformation to a culture-based economy, operationalized as an increase in arts establishments and residents who are employed as cultural workers. Testing these outcomes, the paper employs “fixed effects” modelling (Allison 1994), a method designed to evaluate the effects of an event (in this case, an IAD) independent of selection factors. The method is, therefore, ideally suited to examine the effects

of the IAD itself independent of the characteristics of neighbourhoods that are more likely to have IADs in the first place.

The results of this approach provide nuanced but consistent evidence in support of both the revitalization and transformation claims of the Bilbao effect. Economically, IADs tend to be associated either with population growth or rent increases (but not both at the same time). Rents tend to increase more with commercial IADs such as office buildings and condominiums than non-commercial IADs. In terms of culture, all types of IADs are associated with increases in the number of local arts establishments as well as the number of local residents who are employed as cultural workers.

The paper ends with a comparison of two neighbourhoods that saw three IADs each during the 2000s: the Dallas Arts District and Lincoln Square, Manhattan. These neighbourhoods illustrate two distinct manifestations of the Bilbao effect that are evident in the quantitative analysis. The Dallas Arts District fits the more conventional interpretation of Bilbao, where the construction of three new iconic cultural destinations were accompanied by an apartment boom that tripled the local population and where new residents were younger, more diverse, and more likely to be cultural workers. By contrast, Lincoln Square illustrates how IADs built in already elite neighbourhoods contribute to making them even more exclusive and less accessible.

WHAT IS THE “BILBAO EFFECT”?

Bilbao effect narratives are ubiquitous within scholarly and popular publications concerning iconic architecture and have typically focused their attention squarely on the figure of the architect (Ponzini 2000; Lieto 2020:23-24). According to these narratives, the architect’s talent does not rest in solving technical problems for a client through design. Rather, the power of the architect is lies in what Bourdieu (1996) calls the “charismatic ideology of creation”. The Bilbao effect occurs when an architect is able to capture the attention of the world not only through the shocking and unique aesthetics of their buildings, but also the charisma and celebrity of their personality (Stephens 1999; Rybczynski 2002; Jencks 2005). In other words, not an architect, but a “starchitect”.

Architectural critic Charles Jencks summed up this combination of economic value and artistic creativity inherent in the Bilbao effect:

If a city can get the right architect at the right creative moment of his career, and take the economic and cultural risk, it can make double the initial investment in about three years. It can also change the fortunes of a declining industrial region. To put it crudely, the tertiary economy of the culture industry is a way out of Modernist decline. (Jencks 2005:19 quoted in Ponzini 2010:5)

While initial use of the term was celebratory, “Bilbao effect” is now primarily used by critics to denounce the influence of Gehry’s building on architecture and urban design. For example, in a 2002 essay titled “The Bilbao effect,” critic Witold Rybczynski (2002) argued that “the ‘wow factor’ may excite the visitor and the journalist, but it is a shaky foundation on which to build lasting value. Great architecture … should have more to say to us than ‘Look at me’” (n.p.).

Meanwhile, Marxist and other critical scholars have argued that the Bilbao effect represents a commodification of architecture, furthering the interests of a global capitalist class at the expense of local culture and authenticity (e.g. Ho 2006; Kaika and Thielen 2006; Sklair 2017;). IADs and other culture-led development projects have also raised questions over gentrification and whether their benefits are realized only by white, professional-class residents at the expense of racialized and economically marginalized communities (Mathews 2010; Sze 2010).

Whether celebratory or critical, scholars have noted how the Bilbao effect narrative has spread rapidly across the world, being picked up by a diversity of localities and cultural institutions despite facing very different contexts and problems (Gonzolaz 2011; Ponzini and Nastasi 2011). While Bilbao itself is a mid-sized European city, studies have shown how the narrative has emerged in the development of projects in large North American cities such as Toronto (Patterson 2012: 3297) and Chicago (Gilfoyle 2006: 94) that already have strong cultural economies. It seems that the appeal of economic growth and transformation (and the fear of being left behind) are powerful subjective forces, no matter how objectively privileged the city or neighbourhood.

EVALUATING THE “BILBAO EFFECT”

What is notable about the spread of the Bilbao effect narrative is that it has occurred despite a lack of evidence that the effect actually exists on a broad scale (Evans 2005). As mentioned, research that seeks to evaluate the effect has tended to focus on individual case studies. These studies have provided mixed evidence. Central to this literature is the work of Plaza (2000; 2006; 2008) which has revealed a positive effect of the Museo Guggenheim specifically on tourism

within Bilbao. Other examples include a study by Ahlfeldt and Mastro (2012) who found that home prices in the Oak Park neighbourhood of Chicago increased the closer the property was located to one of several Frank Lloyd Wright-designed houses. Meanwhile, Raevskikh (2018) demonstrates that the anticipation of an IAD can drive major socio-economic changes in a neighbourhood even before construction begins, which she observes in the case of the Gehry-designed Luma Foundation Building in Arles, France.

Other studies, however, have shown the failure of IADs to make significant impacts on their surroundings. For example, Grodach’s (2008) study of two art museums in Los Angeles and San Jose reveals how the impact of these projects was undermined by contextual factors such as the existing built environment and competition from other regional consumer designations.

While greatly advancing our understanding of IADs, these studies do not tell us whether the Bilbao effect is typical of IADs in general. Moreover, attempting to test an effect in a single case runs into problems of disentangling causality. As has been argued by Alaily-Mattar et al. (2018), with small-N case study research, “it is problematic to causally dissociate a given aspect of star architecture [from], for example, the physical structure, the function, the institution or the site. They are tightly intertwined with each other in various ways” (pp.3-4) and “are never isolated physical objects” (p.3)1.

In addressing this challenge, large-N approaches have an advantage: they potentially reveal patterned relationships between different elements that cut across the unique complexities of individual cases. One of the only large-N studies of the economic impact of iconic architecture is by Fuerst, McAllister, and Murray (2011). Using a sample of about 17,000 office buildings in the United States, they found that those buildings designed by elite architects extracted 5-7% higher rents and were sold for 17% more than buildings designed by non-elites.

While their work provides additional evidence for an association between elite architects and economic rewards, it also has limitations. In particular, Fuerst et al. (2011) acknowledge that their cross-sectional data limits their ability to establish causal direction (p.180). Do elite

1 See debates between Plaza (1999) and Gómez (1998) and Gómez and González (2001) for evidence of the difficulty of evaluating the Bilbao Effect even in the case of the Museo Guggenheim itself.

architects actually produce higher rents, or do they tend only to be hired for the kinds of projects that would be able to charge higher rents anyway?

A related challenge to studying the Bilbao effect is selection bias. IADs are not randomly assigned to different neighbourhoods. They are far more likely to occur within very specific places: university campuses, post-industrial waterfronts, and the downtown cores of major cities (Jeong and Patterson, forthcoming). It is therefore important to disentangle the impact of the IAD on its surroundings from the effect of the surroundings on attracting IADs in the first place.

Thus, existing research on the Bilbao effect has run into four main problems: generalizability, disentangling casual factors, establishing causal direction, and eliminating selection bias. Outlined in the next section, the methodology adopted in this paper is designed to address all four of these problems.

METHODOLOGY
This paper builds on a framework developed by Thierstein, Alaily-Mattar, and Dreher (2020). They conceptualize IADs as a “process” with four dimensions: (1) “starting conditions” that lead IADs to occur and certain places rather than others, (2) the “actions” involved in the development process, (3) the immediate “outputs” of that process, including the building itself, but also the media coverage, the user experience, etc., and (4) the secondary “effects” of the IAD on its surroundings. Addressing each of these dimensions requires making methodological decisions. Those decisions are detailed in this section and summarized in Figure 1.

FIGURE 1. METHODOLOGICAL FRAMEWORK (BASED ON THIERSTEIN ET AL. 2020).

STARTING CONDITIONS (STUDY POPULATION)
The first dimension, starting conditions, concerns the identification of a study population. As mentioned, while Bilbao is a mid-sized European city, the Bilbao effect narrative itself has spread to many different types of cities and neighbourhoods. It is fair to say that many developers hope that building iconic architecture will produce wide-spread economic benefits, no matter the existing state of their cities and neighbourhoods. For this reason, this study does not impose selection criteria based on starting conditions. It includes all neighbourhoods in Canada and the United States.

Canada and the United States were selected because these two countries maximize the number of cases while minimizing issues of data comparability. Between the two countries there are hundreds of metro areas containing tens of thousands of neighbourhoods which are defined in similar ways by Statistics Canada and the US Census Bureau.

ACTION (OPERATIONALIZING ICONIC ARCHITECTURAL DEVELOPMENTS)
The second and third dimensions, “actions” and “outputs”, raise the issue of how to operationalize and sample IADs: based on the motivations and actions taken by the developer, or based on the finished product? While both dimensions are important, selecting cases based on their output – that is, whether the building is “iconic” – presents a problem. Iconicity is an outcome rather than a cause of development. It fundamentally tied up with an IAD’s secondary effects, since buildings that positively impact their surroundings are more likely to be perceived as iconic (Patterson 2020). In other words, sampling based on achieved iconicity is akin to sampling on the dependent variable, which misses out on projects that were intended to become iconic and failed, and potentially includes projects that became iconic unintentionally such as the “Hollywood” sign in Los Angeles. The Bilbao effect typically refers to buildings that are designed intentionally to become iconic, which is why the second dimension, “action” is a preferable basis for sampling.

For this reason, this paper follows precedents set by Ponzini and Manfredini (2017) and Sklair (2005) in operationalizing IADs not based on the characteristic of the final building, but on the architectural firm that designed it. In other words, “starchitecture” is defined as any structure designed by a “starchitect”. This strategy has the advantage of more clearly indicating the original intention of the developers and the actions they take to create an iconic structure,

whether or not the resulting building actually achieves iconic status. For example, while not every building designed by Zaha Hadid or Rem Koolhaas has become iconic, hiring these world-famous architects is a clear indicator that iconicity is the intension. As Ponzini and Nastasi (2011) argue, “a star architect’s name has been assumed to be a determinant by key actors not only in designing projects for developing and regenerating urban areas, but also in defining a positive and communicative image [for the project]” (p. 8, italics added).

How, then, to define and operationalize the concept of “starchitect”? This paper draws on and slightly modifies a four-dimensional definition developed by Sklar (2017:124), which is outlined in Table 12.

Dimension Conceptual Description Indicators
Consecration The architect has achieved a high level of prestige within the field of architecture, signifying a career oriented primarily toward “cultural capital” as opposed to “economic capital” (Stevens 2002; Bourdieu 1996). Winners of major architectural prizes:

2 Sklar’s (2017) original definition includes “fame”, “brand-stretching”, “recognition”, and “global reach”.

OUTPUT (DATA SELECTION)
The data selection process followed the pioneering work of Ponzini and Manfredini (2017) and Sklair (2005) in first assembling a long list of potential architecture firms. These firms were selected based on major award winners (e.g. Pritzker Prize), a Factiva database search for the term “starchitect” and “starchitecture”, and the author’s own knowledge of the architecture field. Once the list was assembled, each architect or firm was evaluated against the four dimensions and ranked based on how closely they conformed to the descriptions. At the top of the list were figures such as Frank Gehry, Rem Koolhaas, and Zaha Hadid who clearly fit all four dimensions. Further down the list were architects that lack certain dimensions such as Daniel Libeskind (consecration) or Antonine Predock (charisma).

Also taken into consideration was the time period when each architectural firm achieved these characteristics. SANAA, for example, was characterized by an avant-garde aesthetic orientation and a global reach early in the decade, but did not achieve significant consecration until the end of the decade (winning the Pritzker Prize in 2010). As a result, SANAA is ranked lower on the list.

As there is no clear line separating “starchitects” from regular architects, deciding where to cut off the list is somewhat arbitrary. To address this issue and test the robustness of this “starchitect” measure, the analysis was run twice: once with a shorter, more restrictive list of only the top 12 firms, and a second time with a longer, inclusive list expanded to the top 25 firms. Since both lists produced similar results, the analysis in this paper uses the longer, inclusive list. See Table 2 for both lists.

TABLE 2. ARCHITECTS AND FIRMS INCLUDED IN DATASET.

Restrictive List Inclusive List
Architect/Firm Architect/Firm
Projects Projects
Frank Gehry Rafael Vinoly
Thom Mayne Antoine Predock
Norman Foster Richard Meier
Daniel Libeskind Moshe Safdie
Renzo Piano Steven Holl
Santiago Calatrava Tadao Ando
Rem Koolhaas Diller Scofidio + Renfro
Fumihiko Maki Bernard Tschumi
Herzog & de Meuron David Chipperfield
Jean Nouvel Coop Himmelb(l)au
Zaha Hadid SANAA
Richard Rogers David Adjaye
Restricted Total MVRDV

Total projects in dataset (restricted and broader): 142

Further following Ponzini and Manfredini (2017), the final step was to assemble a list of projects, which were taken from the online portfolios listed on the official websites of all 25 firms. Projects were limited to those completed within the timeframe (2000 to 2009) and located within Canada or the United States. The projects were also limited to permanent, large-scale and/or publicly-visible projects such as museums, condominiums, public art, and office buildings, but not private houses, interior design, or installation art. The resulting dataset includes a total of 142 IADs.

Each project was further coded according to its function. Consistent with previous findings (Patterson 2012), the dataset was dominated by public or non-profit projects, such as cultural institutions, universities, and government buildings, over commercial real estate such as condominiums, hotels, or office buildings (see Table 3).

EFFECTS (ESTABLISHING HYPOTHESES AND DEPENDENT VARIABLES)
In Thierstein et al.’s (2020) model, the effects of IADs can be economic, socio-cultural, and/or morphological. This paper adopts a relatively narrow reading of the Bilbao effect by focusing specifically on economics. Heidenreich and Plaza (2015) identify three basic economic outcomes often attributed to IADs. The first is that IADs make neighbourhoods more attractive, which draws in new residents and visitors, raising the economic value of the immediate area. Second, IADs raise the international profile of the neighbourhoods and cities in which they are located. Third, IADs create spillover effects that stimulate growth and innovation within the cultural industries as a whole.

The first two outcomes can be measured through the same neighbourhood-level result: a general increase in the intensity of land use in the areas surrounding the IDAs, thereby raising their economic value (Logan and Molotch 1987). This process can be called economic revitalization and summarized as hypothesis one:

H1. Neighbourhoods in which IADs are built will experience more intensification of land use than those without IADs.

In this paper, intensification of land use is conceptualized as (1) population growth and (2) increasing rents.

Heidenreich and Plaza’s third outcome implies that IADs should lead to growth specifically within local cultural industries. This process can be called economic transformation and summarized as hypothesis two:

H2. Neighbourhoods in which IADs are built will experience more growth in the local cultural economy than those without IADs.

Growth in the cultural economy is measured as (1) the change in arts-related organizations or business establishments within an area, and (2) the change in the number of artists and cultural workers living within the area. Arts establishments refer to the total number of art dealers, arts schools, musical theatre, opera, and dance companies, independent artists, and non-commercial art galleries within each zip/postal code. Culture workers refer to the number of local residents whose reported occupation falls into the category “arts, design, entertainment, sports, and media”.

With the exception of arts establishments, all outcomes variables were calculated using the 2000 US Census and 2001 Canadian census for time-point 1, and the 2008-12 American Community Survey and 2011 Canadian National Household Survey for time-point 2. Rent was set to US dollars in 2010 to adjust for inflation and currency differences. Arts establishments are calculated using data from annual business surveys collected by the US Census Bureau and Statistics Canada. Because these surveys are conducted annually, the change is taken between rolling averages calculated from 1999 to 2002 and 2010 to 2012.

LEVEL OF ANALYSIS
While Thierstein et al. (2020) argue that their model is multi-scalar, this paper focuses primarily on neighbourhoods for methodological and theoretical reasons. Methodologically, it is easier to draw causal inference about a building’s effect on its immediate surroundings than on the city or region in which it is located. Neighbourhoods also provide many more cases to examine. Theoretically, this analysis rests on the assumption that the impacts of IADs will be strongest at the local level and become more diffuse at higher geographic levels. If no neighbourhood-level effect is observable, it is very unlikely that the IADs will be shown to have an impact at the city or regional level either.

Neighbourhoods are operationalized as US zip codes and Canadian forward sortation areas (FSAs) respectively (N=∼32,000). Both zip codes and FSAs have been used previously to represent neighbourhoods because of the stability of their boundaries over time, and because their geographic area tends to best approximate a neighbourhood (Silver and Clark 2016).

FIXED EFFECTS MODELLING

To address the challenges of causality mentioned earlier, this analysis employs “fixed effects” modelling in combination with longitudinal data (Allison 1994). The primary benefit of this approach is that fixed effect models isolate variation at the level of individual cases across time periods, which eliminates selection bias. In this case, the model explains the variation within each neighbourhood between 2000 and 2010, while holding time-invariant differences between neighbourhoods constant (e.g. location in large versus small cities). In other words, neighbourhoods with an IAD in 2010 are evaluated in comparison to how they looked in 2000 before they had an IAD. They are not compared directly to other neighbourhoods without IADs.

Based on these advantages, Allison (1994) argues that fixed effects models are particularly well suited to estimate the effects of events when the events themselves are not randomly distributed across cases. In this paper, the fixed effect model estimates whether economic changes between 2000 and 2010 are significantly different between neighbourhoods that experienced IAD and those that did not experience IAD.

The fixed effect model can be represented in the following equation (based on Allison 1994:180):

Yi2010−Yi2000=(μ2010−μ2000)+δXi+γ(Wi2010−Wi2000)+εi2010−εi2000

In this equation, Xi is a dichotomous variable that represents the existence of an IAD within a given neighbourhood i. Xi=1 for any neighbourhood that experienced at least one IAD between 2000 and 2009, and Xi=0 for all other neighbourhoods. Of the 32,000 neighbourhoods in the dataset, a total of 118 include IADs. The effect of Xi on the outcome variable is represented by the coefficient δ.

Y_{i2010} - Y_{i2000}$$ represents the change between 2000 and 2010 in the four outcome variables: population, rent, arts establishments, and residents who are cultural workers. $W_{i2010} - W_{i2000}$ are time-varying control variables. As mentioned, control variables that do not change over time need not be included in fixed effect models. Inclusion of specific control variables are noted in the findings section. In order to test the robustness of the findings, the models were run multiple times within different subpopulations: (1) all US zip codes, (2) all metro regions with populations greater than 500,000 people, and (3) only in those metro regions that experienced at least one IAD between 2000 and 2010. Given the size and number of IADs located in New York and Los Angeles, the models were also run only for these two cities and excluding these two cities. Except in one case (discussed in the analysis section below) there was no significant differences between subpopulations. FINDINGS WHERE IS STARCHITECTURE BUILT? The 142 projects in the database were distributed across 56 towns and metro areas in the US and 2 cities in Canada. However, the projects were heavily concentrated in a handful of metros, particularly the New York City and Los Angeles areas, which were home to 22 and 11 projects respectively (see Figure 2 and Table 4). TABLE 4. METRO AREAS WITH 5 OR MORE IADS. | Metro Area | # of Projects | | :--- | :--- | | New York City | 22 | | Los Angeles | 12 | | Boston | 7 | | Washington | 7 | | Dallas | 6 | | Chicago | 5 | | San Francisco | 5 | | Toronto | 5 | In total, 118 neighbourhoods had at least one IAD. Among those, five stand out for having three projects each: Lincoln Square in Manhattan (10023), the Dallas Arts District (and its surroundings) (75201), the Civic Center area of Los Angeles (90012), and the University of Toronto campus in downtown Toronto (M5S). Given these findings, it should be noted that many IADs are built in cities and neighbourhoods that are already dominant in the global economy and that have thriving cultural sectors, reflecting an earlier finding by Ponzini and Manfredi (2017) in their global-level analysis (p.103). These findings contrast with the narrative of the Bilbao effect that stresses the role that these buildings play within declining, post-industrial cities. FIGURE 2. IAD LOCATIONS IN NORTH AMERICA. CIRCLE SIZE INDICATES THE NUMBER OF PROJECTS PER METRO AREA. HYPOTHESIS ONE: ECONOMIC REVITALIZATION POPULATION GROWTH Neighbourhoods with IADs grew, on average, by 1,566 people, which is more than double the average population growth of those without (710 people). However, regression analysis (not shown) indicates that much of this difference can be explained by the fact that most IADs are located in large, rapidly growing metro areas. Within large metros, neighbourhoods with IADs grew only marginally more than those without (by about 200 people). Focusing on outlier cases indicates that population growth is greatly determined by the kinds of places in which IADs are built. Among neighbourhoods that built IADs, the most rapid population growth tended to occur within new suburban communities. For example, Ashburn, Virginia (home to the Rafael Vinoly-designed Janelia Farm Research Campus), grew by 24,319 people. Rapid growth was also seen in the downtown cores of large cities. Downtown Cincinnati, for example, where a Zaha Hadid-designed art museum completed was in 2003, grew by 9,400 people even as Cincinnati as a whole shrank by 33,306. By contrast, 27 of the 118 neighbourhoods with IADs saw population decline. Many of these cases were of IADs built on university campuses within older, inner-city neighbourhoods of larger cities, such as the University of Chicago, Case Western Reserve University in Cleveland, Washington University in St. Louis, and the Harlem campus of City College of New York in Manhattan. RENT At the national level, IAD are positively associated with increased rents, even after controlling for changes in population and median household income (see Models A and B in Table 5). These results hold, no matter what subpopulation is examined. TABLE 5. REGRESSION MODELS ON CHANGE IN RENT, 2000 TO 2010. | | Model A | Model B | Model C | Model D | Model E | | :--- | :---: | :---: | :---: | :---: | :---: | | Constant | 73.65*** | 82.48*** | 73.68*** | 82.49*** | 82.44*** | | IAD | 64.62*** | 47.80** | | | 69.69*** | | IAD (commercial) | | | 211.32*** | 183.43*** | | | IAD (non-commercial) | | | 30.80 | 17.90 | | $\Delta$ Population | 0.003*** | | 0.003*** | 0.003*** | | :---: | :---: | :---: | :---: | :---: | :---: | | IAD*$\Delta$ Population | | | | -0.014** | | $\Delta$ Median hh income | 0.005*** | | 0.005*** | -0.005*** | | R-Square | 0.000 | 0.041 | 0.001 | 0.041 | 0.041 | | N | 29,195 | 29,195 | 29,195 | 29,195 | 29,195 | * $p < 0.05$, ** $p < 0.01$, *** $p < 0.001$ As Models C and D in Table 5 illustrate, the positive relationship between IADs and rent is driven primarily by commercial IADs such as condominiums and office buildings as opposed to non-commercial projects such as libraries or art museums. This strong association is likely explained by the fact that commercial developers will typically only hire elite starchitects within the hottest real estate markets such as Manhattan. Indeed, over half the commercial projects in the dataset were located in New York City. Other commercial developments were found in places like Las Vegas, Los Angeles, and Washington, DC. Non-commercial projects, by contrast, are more diffuse throughout the continent and tied less closely to the local real estate market. These projects therefore have more diverse outcomes when it comes to rent. It should noted, however, that the largest rent increases among IAD neighbourhoods occurred next to non-commercial IADs located within the downtown cores of large metro areas: the Chicago Art Institute in Chicago’s central Loop, and the David L. Lawrence Convention Center in downtown Pittsburgh. RENT VERSUS POPULATION GROWTH It is also worth noting that while changes in population and rent are positively correlated at the national level, they are negatively correlated among IAD neighbourhoods (Pearson’s r -0.175). This observation is reinforced by Model E (in Table 5) which tests the interaction of IADs and population growth on rent. The negative effect of the interaction term suggests that IADs tend only to cause rent increases within neighbourhoods that have stable or decreasing populations. The negative relationship points to two manifestations of economic growth, which can be seen in the four neighbourhoods listed in Table 6. On one hand, when IADs are built in established areas where population growth is limited, their economic effect is primarily seen through increased rents. Lincoln Square in Manhattan and the Central Loop in Chicago illustrate this phenomenon. On the other hand, when IADs are built in neighbourhoods that have the potential for extensive upzoning (such as in former industrial lands or in the vast swaths of parking lots in many American central cities), rents remain stable or even decline. This can be seen in the downtown cores of Dallas and Cincinnati, where thousands of new apartment dwellers pay, on average, lower rents than the previously existing households in the area. The contrast between Dallas and Manhattan is examined more closely in the discussion section of this paper. TABLE 6. RENT AND POPULATION CHANGE IN FOUR NEIGHBOURHOODS. | Neighbourhood | Zip code | Projects, Architects, Year of Completion | Δ Rent | Δ Population | | :--- | :--- | :--- | :--- | :--- | | Lincoln Square, Manhattan | 10023 | • Jazz at Lincoln Center (Rafael Vinoly, 2004) | \$356.00 | -1,208 | | | | • Alice Tully Hall (Diller Scofidio + Renfro, 2009) | | | | | | • Lincoln Center Plaza Renovation (Diller Scofidio + Renfro, 2010) | | | Central Loop, Chicago | 60603 | • Chicago Art Institute Expansion (Renzo Piano, 2009) | \$1139.00 | 115 | Dallas Arts District (and surroundings) | 75201 | • Margot and Bill Winspear Opera House (Norman Foster, 2009) | -\$214.00 | 6,061 | | | | • Dee and Charles Wyly Theatre (Rem Koolhaas, 2009) | | | | | | • Nasher Sculpture Center (Renzo Piano, 2003) | | | Downtown Cincinnati | 45202 | • Lois & Richard Rosenthal Center for Contemporary Art (Zaha Hadid, 2003) | -\$92.00 | 9,400 | In sum, the analysis confirms hypothesis #1. IADs are positively associated with intensified land use. However, this intensification manifests itself either as increased rent or increased population, but typically not both at the same time. HYPOTHESIS TWO: ECONOMIC TRANSFORMATION ARTS ESTABLISHMENTS When it comes to evaluating cultural impact, the data show a clear and robust positive relationship between IADs and arts-related establishments. The number of arts establishments increased in IAD neighbourhoods by an average of 4.1, whereas this increase was only 0.4 in neighbourhoods without IADs. In regression analysis, IADs were positively associated with change in arts establishments, even when controlling for change in population and rent (see Models F and G in Table 7). This positive relation held for both cultural IADs and non-cultural IADs alike (Model H). TABLE 7. REGRESSION MODELS ON CHANGE IN THE NUMBER OF ARTS ESTABLISHMENTS, 2000 TO 2010. | | Model F | Model G | Model H | | :--- | :---: | :---: | :---: | | Constant | 0.50*** | 0.40*** | 0.5*** | | IAD | 4.15*** | 4.05*** | *** | | IAD (cultural) | | | 3.48*** | | IAD (non-cultural) | | | 4.57*** | | $\Delta$ Population | | 0.0001*** | 0.0001*** | | $\Delta$ Median rent | | 0.0002* | 0.0002* | | R-Square | 0.005 | 0.019 | 0.02 | | N | 27,656 | 27,656 | 27,656 | * $p < 0.05$, ** $p < 0.01$, *** $p < 0.001$ It is worth noting that this relationship was particularly pronounced in Midtown and Lower Manhattan, which saw hundreds of new arts establishments in addition to the dozens of commercial and non-commercial IADs. However, the relationship also held outside New York City. CULTURAL WORKERS The positive relationship between IADs and culture is more complicated when it comes to the residential patterns of cultural workers. In neighbourhoods with IADs, the number of residents reporting a cultural occupation actually declined by an average of 4 people, whereas it increased by an average of 6 people in neighbourhoods without IADs. This effect was even greater after controlling for increasing populations and rents. This result is reflected in regression Models I and J in Table 8. TABLE 8. REGRESSION MODELS ON CHANGE IN RESIDENTS WHO ARE CULTURAL WORKERS, 2000 TO 2010. | | All Canada and USA | Only NYC | Excluding NYC | | :--- | :---: | :---: | :---: | | | Model I | Model J | Model K | Model L | Model M | Model N | | Constant | 6.89*** | -1.48*** | 33.54** | 6.41 | 6.09*** | -1.60** | | IAD | -10.65 | -18.15* | -288.25*** | -304.81*** | 40.33*** | 32.45*** | | Δ Population | | 0.01*** | | 0.03*** | | 0.01*** | | Δ Median rent | | 0.02*** | | 0.08 | | 0.01*** | | R-Square | 0.000 | 0.124 | 0.016 | 0.138 | 0.001 | 0.166 | | N | 27,681 | 27,681 | 816 | 816 | 26,864 | 26,864 | * p < 0.05, ** p < 0.01, *** p < 0.001 However, upon closer inspection, it appears this relationship is driven primarily by New York City (see Models K and L). IAD neighbourhoods in Manhattan saw among the highest losses of culture workers (in absolute terms and as a proportion of population). However, the opposite relationship is found outside New York City (Modes M and N). Here, IADs are positively associated with culture workers above and beyond the effects of population growth and rent. In fact, excluding New York City, IAD neighbourhoods added an average of 26 cultural workers over the decade (far greater than the 6 added in non-IAD neighbourhoods). Interestingly, some of the IAD neighbourhoods that saw the greatest increase in culture workers were also located in New York City – specifically in Brooklyn (11238) and Harlem (10031). Other IAD neighbourhoods that saw large increases in cultural workers were located in Washington, DC, San Diego, Los Angeles, Dallas, and Philadelphia. Thus, hypothesis two is also supported. IADs are related to cultural sector growth. The major exception to this rule is Lower and Midtown Manhattan, which represents extremes in adding IADs and arts establishments while losing significant numbers of cultural workers (likely to nearby places like Brooklyn and Harlem). DISCUSSION: A TALE OF TWO BILBAO EFFECTS? Overall the findings present strong evidence in support of the Bilbao effect. However, the nuances of these findings point to two distinct scenarios. In the first, IADs act as catalyst for broader neighbourhood revitalization by raising the profile and desirability of vacant or declining areas, leading to the redevelopment of brownfield sites and attracting new residents and firms, particularly within the cultural and creative industries (Heidenreich and Plaza 2015:1444). A new supply of small, more densely concentrated housing units may even reduce rents and make the neighbourhood accessible to people with less economic resources. In the second scenario, already successful neighbourhoods attract or demand high-end commercial real estate developments or major renovations to existing cultural or educational institutions. In these neighbourhoods, the potential for population growth is limited due to lack of available land and/or by powerful community opposition. Instead of new housing, the economic benefits of IADs are channeled into higher rents and property values which may push out cultural workers even as arts establishments thrive by catering to tourists or high-income residents. Zip codes 75201 in Dallas and 10023 in Manhattan, both of which had three IADs in the 2000s, provide examples of these respective scenarios (see Table 6 for the list of projects in each neighbourhood). 75201 is centred on the Dallas Arts District, but also includes parts of Downtown Dallas to the south and a small section of Oak Lawn to the North. The area is typical of many inner-city American neighbourhoods. Originally home to a thriving African American community, it was targeted by slum clearance projects and the construction of two major freeways (Skipper 2015). The result was a desolate stretch of empty lots on the northern border of Downtown Dallas. In the late 1970s, urbanist Kevin Lynch proposed relocating many of Dallas’s major arts institutions into the area in order to create the “Arts District”. The goal was to create a vibrant neighbourhood connecting Downtown Dallas and Oak Lawn. For decades, however, plan was criticized for doing little more than raising the property values of the vacant lots without attracting street life or artistic activity (Dillon 2019 [1985]). The 2000s were a turning point for the area and saw the addition of an opera house, theatre, and sculpture center along the district’s main street, all designed by starchitects (see Table 6). Concurrently, the areas surrounding the Art District were experiencing an apartment and condominium boom that continues to this day. The population of the zip code nearly tripled to 9,409 between 2000 and 2010, with cultural workers making up almost 8% of the new residents. As census data reveals, however, this is not a clear case of gentrification (see Table 9). Over the decade, the average household income and rent decreased, and the population as a whole became younger and more diverse. TABLE 9. DEMOGRAPHIC AND ECONOMIC CHANGES IN THE DALLAS ARTS DISTRICT AND LINCOLN SQUARE, MANHATTAN, 2000-2010. | | Dallas Arts District (75201) | Lincoln Square, Manhattan (10023) | | | :--- | :---: | :---: | :---: | | | 2010 | Change from 2000 | 2010 | Change from 2000 | | Population | 9409 | +6061 | 60,998 | -1208 | | Median Rent | \$1,333 | -\$214 | \$1,902 | +\$356 | | Cultural Workers | 606 | +464 | 3902 | -1052 | | Arts Establishments | 18 | -1 | 171 | +37 | | % Non-White | 32% | +5% | 18% | -0.1% | | % Immigrant | 12% | +6% | 20% | -1% | | % 25 to 35 year olds | 42% | +4% | 19% | -7% | | Median Household Income | \$64,520 | -\$9857 | \$105,311 | +\$3993 | The second scenario can be observed in zip code 10023, corresponding roughly to Lincoln Square, a neighbourhood located in the affluent Upper West Side of Manhattan. Like the Dallas Arts District, Lincoln Square is a product of postwar slum clearance projects that targeted at an existing African American community (San Juan Hill). However, unlike Dallas, where the community was replaced by freeways and empty lots, Lincoln Square was rebuilt immediately under the guidance of Robert Moses with subsidized and market-rate apartment buildings, schools, the Coliseum convention centre, and major institutions such as Fordham University, the Julliard School, and the Lincoln Center for the Performing Arts (Columbia University Graduate School of Architecture 2007). These projects turned the area into a major architectural and cultural destination well before the 2000s. The IADs of the 2000s were not aimed at revitalizing the neighbourhood. Instead they served to renew expand the Lincoln Center. Two of the projects, both by Diller Scofidio + Renfro, renovated Lincoln Centre Plaza and the neighboring Julliard Building. The third project, Jazz at Lincoln Centre by Rafael Vinoly, contributed new performance spaces to a larger project, the Time Warner Centre, designed by SOM. That project was the end result of decades of public struggles over how to replace the long-vacated Coliseum convention center, revealing the power of local residents and the significance of the property, which demanded nothing less than the best architecture for such a prominent location (St. John 2013; Zukin 2005). In the case of Lincoln Square, we can see how IADs can fit into what Lees (2003) calls “super-gentrification”, which she defines as “the transformation of already gentrified, prosperous and solidly upper-middle-class neighbourhoods into much more exclusive and expensive enclaves” (p.2487). Indeed, census data reveals that Lincoln Square did become more exclusive over the decade. Its population shrunk, but also became richer, older, and somewhat less diverse (see Table 9). And while there was a significant increase in arts establishments in the area, the number of cultural workers decreased dramatically. Thus, while Lincoln Square demonstrates a positive relationship between IADs and economic and cultural growth, it does not fit the usual Bilbao effect narrative. Nonetheless, as mentioned earlier, the Bilbao effect narrative is still routinely invoked in cases such as these (Gilfoyle 2006; Patterson 2012). CONCLUSION Urban scholars have long expressed caution over the possibility of recreating the Bilbao effect of Frank Gehry’s Museo Guggenheim (e.g. Evans 2005; Grodach 2008; Ponzini and Nastasi 2011). Indeed, there is even debate over the extent to which the Museo Guggenheim itself has achieved the level of success often attributed to it (Plaza 2001; 2006; Gómez 1998; Gómez and González 2001). With mostly individual and small-N comparative case studies to go on, it has been difficult to resolve these uncertainties. By adopting a large-N approach, longitudinal data, and fixed-effects modeling, this paper has provided strong evidence in support of the Bilbao effect. On the whole, the neighbourhoods in North America that experienced iconic architectural development saw significantly more land use intensification and cultural sector growth than neighbourhoods without iconic architecture. However, the study also adds nuances to the Bilbao effect. Economic revitalization tends to manifest itself either as population growth or increased rent, but not both. Those rent increases are more associated with commercial IADs as opposed to public projects. In terms of culture sector growth, while IADs are generally associated with an increase in both arts establishments and cultural workers, Manhattan provides a striking example of how arts establishments can increase dramatically around IADs while cultural workers themselves are pushed out of the neighbourhood. These nuances were conceptualized through a comparison of the Dallas Arts District and Lincoln Square, Manhattan. In the former case, IADs were associated with a dramatic increase in the local population, which became younger, more diverse, and included more cultural workers. In the latter case, IADs were associated with a process of “super-genrification” (Lees 2003) in which the neighbourhood became more exclusive. Notwithstanding these contributions, the paper has limitations that point to new research directions. While IADs are multi-scalar in nature (Thierstein et al. 2020), this analysis has focused primarily on neighbourhoods. Having shown clear neighbourhood-level effects, future research should expand this analysis to better understand how city- and regional-level characteristics influence local-level dynamics. Indeed, the analysis presented here shows clear evidence that IADs tend to work somewhat differently in a major global city like New York than they do in smaller cities such as Dallas or Cincinnati. Furthermore, while this analysis has focused on Canadian and American neighbourhoods, the Bilbao effect narrative and culture-led urban regeneration emerged initially in Europe. Despite their political and economic similarities, there are significant differences between the two continents when it comes to urban governance and major public works projects (Ponzini et al. 2020:6-8). It remains to be seen whether the findings presented here would hold within the European context. One final limitation of this paper is its relatively narrow focus on two neighbourhood-level economic outcomes. As Thierstein et al. (2020) argue, however, IADs have several potential outcomes that can be economic, socio-cultural, and morphological (p.51). 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