2000 The economic geography of talent

The Economic Geography of Talent September 2000 Richard Florida* Contact Information: H. John Heinz Professor of Regional Economic Development, Heinz School of Public Policy and Management, Carnegie Mellon University, Pittsburgh PA, 15213, e-mail: florida@andrew.cmu.edu Acknowledgements: The research was supported in part by the Alfred P. Sloan Foundation. Richard Kind Mellon Foundation, and the Heinz Endowments. Gary Gates, Sam Youl Lee, Ji Woong Yoon, Derek Davison, and Karin Tuxen provided research assistance. 2 Abstract The paper explores the economic geography of talent. It argues that the distribution of talent – that is high human capital individuals – plays a fundamental role in the distribution of high-tech firms and in regional economic outcomes. To shed light on these issues, this paper summarizes the results of statistical research as well as interview and focus groups. The findings shed light on the geography of talent, the factors that shape that geographic distribution, and the effects of talent and the location of high-technology industry and other regional outcomes. They indicate hat the economic geography is talent is associated with diversity (low entry barriers) and quality of place. Talent in turn attracts high-technology industry. Together, talent and technology based industries generate positive regional economic outcomes in the form of higher per capita incomes. The findings further suggest that the ability to attract talent is a fundamental dimension of city and regional growth. This contrasts with the preoccupation in the extant literature that emphasizes the attraction of firms and the formation of industrial clusters. It is talent that orients the location decisions of firms and which underpins the formation and evolution of industrial clusters. Furthermore, the research suggests that places matter significantly in the economic geography of talent. Places provide the infrastructure required to generate, attract, and retain talent. Place-based advantages stem in turn from two underlying economic factors: low entry barriers to human capital and efficiencies in the delivery of consumer services. Simply put, there is an economic rationale behind what may be perceived as “nice” places to live. 3 Introduction Geographers, economists and other social scientists have long been concerned with the economic geography of firms and industries. Ever since the pioneering work of von Thünen and Marshall, scholars have probed the processes of firm location, the spatial division of labor, and the phenomena of agglomeration, clustering, and industrial complex formation (Piore and Sabel 1984; Henderson 1974; 1988; Porter 2000, Krugman 1991). This important body of work has for the most part focused on the geographic distribution of firms, and the forces that make economic actors concentrate or alternatively disperse their activities over space. Those concerned with economic geography however have paid much less attention to the various economic, social, and geographic forces that act on and shape the spatial distribution of people who establish firms and populate industries. There is a significant literature on human capital, but it has not sufficiently dealt with geographical and regional factors and it has certainly not linked human capital to regional outcomes in ways that control for the independent effects for industry mix or other place-based characteristics. Recent years have seen renewed interest in the role of human capital in economic development. In a seminal paper, Lucas (1988) builds upon Jacob’s basic insights to offer a theory of the role of human capital in cities and economic development. Jacobs (1961, 1969) long ago called attention to the central role played by people in the generation and organization of economic activity in cities. In her view, cities play a crucial role in economic development, through the generation and mobilization of new knowledge. The scale of cities and their diversity of inhabitants create the interactions that generate new ideas. In other words, the diversity of economic actors within cities, and their high level of interaction promote the creation and development of new products and new technology. 4 Building upon this insight, Lucas essentially argues that cities function to collect and organize human capital, giving rise to strong external economies, which he refers to as external human capital, that increase productivity and spur growth. If we postulate the usual list of forces, cities should fly apart. The theory of production contains nothing that holds a city together. A city is simply a collection of factors of production - capital people and land - and land is always far cheaper outside cities than inside. Why don't capital and people move outside combining themselves with cheaper land and thereby increasing profits? Of course people like to live near shopping and shops need to be located near their customers, but circular considerations of this kind explain shopping centers, not cities ...It seems to me that the "force" we need to postulate to account for the central role of cities in economic life is of exactly the same character as external human capital. What can people be paying in Manhattan or downtown Chicago rent FOR, if not to be near other people" (Lucas 1988). Several studies (Eaton and Eckstein 1997; Black and Henderson 1999) have found that workers are more productive when they locate around others with high levels of human capital. Other empirical studies have found that human capital is strongly associated with urban and regional growth. Research by Glaeser, Sheinkman and Sheifer (1995) found a strong relationship between human capital and city growth. In other research, Glaeser (2000) noted that it is the need to access common pools of labor or talent rather than access to suppliers and customers what drives the tendency of firms to cluster together in regional complexes. Simon (1998) found a strong relationship between the average level of human capital and regional employment growth over the period 1940-1986. Glendon (1998) found a strong positive relationship between the level of human capital in a city at the turn of the 20th century and subsequent economic growth. Following Jacobs (1961), Glendon suggested that cities and regions with high levels of human capital were able to more readily incubate new ideas and shift their industrial structures into growing industries (see Mathur 1999 for a review of human capital based theories of economic development). The “new growth theory” associated with Romer (1990) calls attention to the importance of knowledge and human capital in generating economic growth. As he notes: “what is important for growth is integration not into an economy with a large number of 5 people, but rather into one with a large amount of human capital” (Romer 1990). Furthermore, the rise of the so-called knowledge economy has created renewed interest in the role of human capital in economic activity. Firms have recognized that the “new economy” is driven by human capital – a phenomenon that the consulting firm, McKinsey and Company has dubbed the “war for talent.” High human capital individuals are highly mobile. Shortages of talent in key sectors such as software development and information technology have been noted in numerous studies and reports. Cities and regions in the United States and around the world have also become much more concerned with their ability to generate, attract and retain highly educated and highly skilled people upon which knowledge based industries depend. All of this has generated renewed interest in the relationships between knowledge creation, human capital, and economic growth. This paper has a rather basic aim: It hopes to reacquaint those who work in the fields of economic geography and urban and regional economics with the importance of the economic geography of human capital. At one level, this paper is a descriptive exercise. It aims to provide a rich empirical description of the economic geography of talent using a variety of measures. It also tries to systematically sort through and shed light on the factors that shape that observed geographic distribution. And, it examines the effects of the economic geography of talent on regional outcomes such as the location of high-technology industries and regional incomes. At a second level, the paper also aims to develop and test theory regarding the economic geography of talent. Here, it attempts to identify the mechanisms by which talented individuals select locations and sort themselves into places. Following Lucas and Jacobs, the underlying theory is that talented and productive people - that is people with high levels of human capital - tend to co-locate to realize gains in productivity. Put another way, the basic mechanics of city formation, growth and structure turn on the process of productive agents selecting locations that reinforce their productivity. This is very different 6 from the cost-minimization and firm linkage theories of clustering that dominate much of economic geography. Taking this as a point of departure, the theory further argues that the characteristics of places matter significantly in this sorting process. People are attracted to real places. Cities and regions facilitate the co-location of people that results in resource mobilization, new knowledge generation, and new ideas; and reduces the costs associated with generating and transmitting ideas and knowledge. Places thus provide the historically inherited and built up social and economic capabilities that create the capacity to attract human capital. Because knowledge is non-rival and partially excludable, knowledge spillover occurs in places that have qualities that facilitate that spillover. The implication here is that places need to be taken much more seriously into account. Simply put, place contributes to and shapes the geographic sorting of human capital. Places attract talent through two interrelated mechanisms. Glaeser (1999) has called attention to the role of both market and non-market forces in shaping urban and regional processes and outcomes. Both are important to the economic geography of talent. On the one hand, places are home to market based forces, i.e., the industries and firms, which create the demand for talent. On the other hand, they reflect what can be referred to as a set of place-based characteristics – a bundle of amenities, lifestyle options, types of people and the like – that function to attract human capital. Anyone who has taught in a university and made their own location decision or has tried to attract faculty should understand the role of place-based characteristics or quality of place. Talented people do not simply select a place to work based on the highest salary, they are typically concerned with a whole series of place-based characteristics. The theory identifies two types of non-market forces that are associated with place: amenities and diversity. Recent research by Glaeser, Kolko and Saiz (2000) find an association between amenities and city growth. They suggest that high human capital 7 workers not only increase productivity, but that high human capital areas are pleasant places to live in. They conclude that: “If cities are to remain strong, they must attract workers on the basis of quality of life as well as on the basis of higher wages” (Glaeser, Kolko and Saiz 2000: 23). Furthermore, these place based characteristics not only provide for the lifestyles needs of high human capital. They are reflective of a place which efficiently delivers a wide range of services. According to the perspective advanced here, diversity is even more important. In formal terms, high amenity places reflect underlying efficiencies in the delivery and consumer services. The theory suggests that places that attract diverse groups of people (by race, ethnicity, nationality, gender, and sexual orientation) can be said to have a high degree of system openness. Simply put, such places comprise an environment that is easy to plug into. In formal terms, such places can be said to have low entry barriers for talent. In advancing this basic theory, the paper is organized around two more targeted arguments or hypothesis. The first hypothesis concerns the factors that affect the geographic distribution of talent. The ability of cities and regions to attract high human capital individuals is a function of their openness and quality of place as well as the demand that comes from high-technology industries. Here, I argue that the economic geography is jointly shaped by: (1) demand, (2) low entry barriers, i.e. diversity/ openness, and (3) quality of place. The second hypothesis concerns the effect of the economic geography of talent on regional economic outcomes. Previous models have looked at the direct effects of human capital on employment growth and income. This paper adds to this line of research by controlling for the independent effects of industry mix (i.e. high technology industry) and place-based characteristics (i.e. amenities and diversity). Cities and regions with high levels of talent will generate relatively higher levels of both high- technology industry and income. This reflects the fact that the distribution of human capital 8 is highly skewed. Places that attract such talent are able to generate higher levels of firms and economic activity, while those that do not are less likely to do so. To shed light on these issues, this paper summarizes the results of empirical research on the economic geography of talent. Qualitative research consisting of interviews, focus groups and field studies was employed in an exploratory fashion to probe the factors associated with the location decisions of highly talented people. Quantitative research was used in a more confirmatory fashion to provide an empirically based explanation of the factors that shape the economic geography of talent. The paper is organized as follows. The next section outlines the research design and methodology. The paper then turns to findings, starting with an empirical description of the economic geography of talent. It then turns to an analysis of the relative effect of the various factors that effect that observed distribution. This is followed by an analysis of the effect of talent on economic outcomes such as the location of high-technology industries and regional incomes. The final section summarizes the key findings and provides a discussion the implications of the work. Identifying the Economic Geography of Talent: Research Design The paper employs a variety of qualitative and quantitative data to shed light on the economic geography of talent. While the bulk of the research revolved around quantitative statistical analysis, qualitative research was done to help structure and inform the collection and analysis of statistical data. Qualitative Research The quantitative research included interviews, focus groups, and field research in several cities and regions. The qualitative research was exploratory in nature, and designed to inform and structure the quantitative statistical research outlined below 9 Interviews were used to shed light on the factors that motivate the location decisions of people. Unstructured open-ended interview were conducted with more than 100 people who were making or had recently made location decisions. The interviews focused on the various factors involved in these location decisions, including job opportunities, labor markets, amenities, diversity, and cost of living among others. Additional interviews were conducted with human resource executives, CEOs, recruiters, workforce development officials, and economic developers throughout the country. Structured focus groups were conducted with the assistance of a professional focus group organization to further assess the factors involved in personal location decisions. Four focus groups were done. The participants included college seniors in scientific and technical fields, college seniors in management disciplines, graduate students in technical and management disciplines, and young professionals. Advanced college and graduate students were utilized for several reasons. They possess relatively high levels of human capital, are relatively mobile, and are in the process of making location decisions. The focus groups were conducted in Pittsburgh, Pennsylvania in April 1999. Participants originally came from a wide a range of regions throughout the United States and the world and represented a wide range of races, ethnicities and nationalities. The fieldwork involved site visits to and personal interviews with private companies and government agencies in Seattle, Washington and Austin, Texas. These regions were selected because they have generated strong knowledge based industries, have low rates of unemployment, and have developed strategies to attract talent. Austin, for example, is known for its so-called “Wired for Talent” strategy that is designed to attract talent from around the country - a partnership between Hire.com, a leading developer of recruitment software, the Austin-American Statesman, the Mayor’s office, and the Chamber of Commerce. 10 Data, Variables, and Statistical Methods The bulk of the research is based upon an empirical analysis of the economic geography of talent of the factors that affect that distribution, and of its effect on the location of high-technology industries and other economic outcomes. This aspect of the research was confirmatory in nature. The aspect of the research employs several types of variables and measures: (1) human capital or talent measures, (2) quality of place such as amenities, (3) diversity measures, (4) measures of high-technology industry location, and (5) regional income measures. These data are used to generate the descriptive statistics, maps, and trends, and also in the statistical and econometric analyses described below. The analysis is based on the 50 largest metropolitan regions, those with populations of 700,000 and above. For most regions, the metropolitan statistical area or MSA is employed as the unit of analysis. The consolidated metropolitan statistical area or CMSA is used as the unit of analysis for the five largest regions: San Francisco, Los Angeles, Miami-Fort Lauderdale, New York, and Dallas-Fort Worth, to account for broad commuting patterns in these regions. The research employs three measures of talent. The basic talent measure is a measure of highly educated people defined as those with a bachelor’s degree and above. Two additional measures are used to supplement this: professional and technical workers and scientists and engineers. Each of these measures is normalized on a percentage basis or per thousand people and based on the 1990 Decennial Census Public Use Microdata Samples. Table 1 provides descriptive statistics for the various measures used in this research. 11 Table 1: Descriptive Statistics Variable Obs Mean Std.Dev. Min Max Diversity 50 1.32 0.87 0.19 5.39 Hightech 50 1.40 1.88 0.06 8.24 Scientists & Engineers 50 15.77 5.62 6.33 30.93 Professional & Technical 50 286.84 30.27 235.75 356.18 Talent 50 0.24 0.05 0.14 0.42 Coolnes