Abstract
Song and Waters narrate a tale of two cities, namely, Washington metropolitan area and Baltimore metropolitan area; about the rise of one and the fall of the other; about a metro that landed Amazon’s distribution centers and the other, highly coveted the company’s second headquarters (HQ2). In today’s knowledge economy where the most valuable companies are digital platforms, it’s a winner-take-all when it comes to regional economic development. The authors discuss how the paradigm of place-based policies of the industrial age that sought to attract large manufacturers with tax incentives is outdated. There is no better example of this paradigm shift in economic development from cost minimization to value maximization, from emphasis on physical capital to human capital, embodied in the case of Amazon HQ2 race, which ultimately landed in Crystal City, Virginia. Amazon HQ2 race represents a great lesson for what technology businesses value: talent. Virginia demonstrated a good understanding of tech firms’ market needs and its development strategy evidenced the importance of prioritizing the talent pipeline.
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Notes
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We use employment data from the Bureau of Labor Statistics’ Quarterly Census of Employment and Wages. We use 4-digit NAICS codes. NAICS data are used unaltered. While NAICS updates the classifications on occasion, we do not control for changes. We use Metropolitan Statistical Areas as the geography of analysis, with no alterations to control for changes among years. Thus, each year is calculated independently.
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Negative values are dropped as they indicate a repulsion between two industries.
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LVC communities have higher co-occurrence values between industries within the community than with industries outside the community. For the entire period analyzed (1990 to 2020), the same resolution parameter of 0.8 is used to find communities. This parameter was chosen to reveal 2 communities for the entire period.
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Exceptions were the years 1995, 2001, 2004, 2005, and 2018. These years, the community with the highest share of MTT industries was identified as the MTT community.
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In 2020, the larger community, which we refer to as MTT community, had 178 industries. Of the 178 total industries in the MTT community, 111 (62.4%) were accounted for by MTT industries
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In the Service community, only 46 of the 126 industries (36.5%) were MTT. Despite the identification of two communities, community modularity, which ranges from 0 to 1, was just 0.12 in 2020. This indicates that the internal cohesion of the communities is relatively weak.
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While the specialized industries of the two MSAs are located in different portions of the network, given the low modularity, the differing locations are subtle. While the two communities are found in all years, the definitions and xi, j values vary annually. It may be the case that if occupation or skills networks were used, the variation would be smaller, as such communities have been found to be more distinct (Alabdulkareem et al., 2018; Shutters & Waters, 2020).
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This is the combination of all industry specialties.
References
Acs, Z. J., Song, A. K., Szerb, L., Audretsch, D. B., & Komlosi, E. (2021). The evolution of the global digital platform economy: 1971–2021. Small Business Economics, 57(4), 1629–1659.
Alabdulkareem, A., Frank, M. R., Sun, L., AlShebli, B., Hidalgo, C., & Rahwan, I. (2018). Unpacking the polarization of workplace skills. Science advances, 4(7), eaao6030.
Arthur, W. B. (2021). Foundations of complexity economics. Nature Reviews Physics, 3(2), 136–145.
Bartik, T. J. (2019). Making sense of incentives: Taming business incentives to promote prosperity. W.E.
Boschma, R., Balland, P. A., & Kogler, D. F. (2015). Relatedness and technological change in cities: The rise and fall of technological knowledge in US metropolitan areas from 1981 to 2010. Industrial and Corporate Change, 24(1), 223–250.
Cheong, S. H., & Si, Y. W. (2016). Accelerating the Kamada-Kawai algorithm for boundary detection in a mobile ad hoc network. ACM Transactions on Sensor Networks (TOSN), 13(1), 1–29.
De Nooy, W., Mrvar, A., & Batagelj, V. (2018). Exploratory social network analysis with Pajek: Revised and expanded edition for updated software (Vol. 46). Cambridge university press.
Greenstein, S., & Fang, T. P. (2020). Where the cloud rests: The Location Strategies of Data Centers. Harvard Business School Working Paper, No. 21-042, September 2020 (Revised June 2022).
Guevara, M. R., Hartmann, D., Aristarán, M., Mendoza, M., & Hidalgo, C. A. (2016). The research space: Using career paths to predict the evolution of the research output of individuals, institutions, and nations. Scientometrics, 109(3), 1695–1709.
Hidalgo, C. A. (2021). Economic complexity theory and applications. Nature Reviews Physics, 3(2), 92–113.
Kogler, D. F., Rigby, D. L., & Tucker, I. (2013). Mapping knowledge space and technological relatedness in US cities. European Planning Studies, 21(9), 1374–1391.
Li, Y., Kenney, M., Patton, D., & Song, A. (2022). Entrepreneurial ecosystems and industry knowledge: Does the winning region take all? Small Business Economics, in press. https://doi.org/10.1007/s11187-022-00681-y
Liu, A. (2016, November 30). Why economic development matters. Brookings. https://www.brookings.edu/blog/the-avenue/2016/03/07/why-economic-development-matters/
Muneepeerakul, R., Lobo, J., Shutters, S. T., Goméz-Liévano, A., & Qubbaj, M. R. (2013). Urban economies and occupation space: Can they get “there” from “here”? PLOS One, 8(9), e73676.
Shutters, S. T., Muneepeerakul, R., & Lobo, J. (2015). Quantifying urban economic resilience through labour force interdependence. Palgrave Communications, 1(1), 1–7.
Shutters, S. T., Herche, W., & King, E. (2016). Anticipating megacity responses to shocks: Using urban integration and connectedness to assess resilience. Small Wars Journal, 26, 21.
Shutters, S. T., & Waters, K. (2020). Inferring networks of interdependent labor skills to illuminate urban economic structure. Entropy, 22(10), 1078.
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Appendix
Appendix
As an alternate examination of Table 9.4, Table 9.6 shows all pairs of industries that are both specialized in each MSA. For example, in 2020 the DC MSA specialized in NAICS 5413, Architectural, Engineering, and Related Services, (LQ = 1.93) and NAICS 5417, Scientific Research and Development Services, (LQ = 3.77), both industries are in the Service community. DC also specializes in NAICS 3271, Clay Product and Refractory Manufacturing, which is in the MTT community. Thus, there is one link within the Service community and two links between the Service and MTT community for these three NAICS. If one industry is specialized and the other is not, the pair is not included. In 2020, Baltimore and DC had 5151 and 4095 specialty pairs, respectively.Footnote 16
Table 9.6 shows the portion of within and between community pairs. DC increased the share of within Service community pairs from 38% in 1990 to 46% in 2001, before slipping somewhat in 2020. Baltimore also increased the share of within Service community pairs, from 20% in 1990 to 29% in 2020. In 2000, DC had a 21 percentage point advantage over Baltimore. However, DC’s advantage narrowed to 19 percentage points in 2010 and 12 percentage points in 2020.
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Song, A., Waters, K. (2023). A Tale of Two Cities: How Arlington Won and Baltimore Lost in Battle for Amazon’s HQ2. In: Acs, Z.J., Lafuente, E., Szerb, L. (eds) The Entrepreneurial Ecosystem. Palgrave Studies in Entrepreneurship and Society. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-031-25931-9_9
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