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Innovative Start-Ups and the Distribution of Human Capital pp 79–117Cite as

Quality of Life and the Geography of Human Capital

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Part of the book series: Contributions to Economics ((CE))

Abstract

There is a general consensus in the literature, rooted in the relationship between knowledge and economic growth (Nelson and Phelps 1966; Romer 1986, 1990; Lucas 1988; Benhabib and Spiegel 1994, 2005; Glaeser et al. 2004), that human capital, especially in the form of highly educated people, has a positive effect on regional development (Glaeser et al. 1995; Simon 1998; Moretti 2004a). Highly educated people not only have—by definition—more knowledge, but often are also possessed of the ability to absorb additional knowledge and even generate new knowledge (Schultz 1961; Becker 1962, 1964; Mincer 1958, 1974). These people tend to be highly productive and are disproportionately found to be involved in innovation processes. Moreover, they often have a relatively high propensity to set up high-quality new firms (Acs and Armington 2004, 2006; Lee et al. 2004, 2010; Qian and Acs 2011; Qian et al. 2013).

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Notes

  1. 1.

    For more literature, see http://www.uic.edu/orgs/qli/publications/publicationshome.htm

  2. 2.

    For instance, Roback (1982), Blomquist et al. (1988), Gyourko and Tracy (1991), Stover and Leven (1992), and Giannias (1998).

  3. 3.

    For more discussion, see CAE and SVR (2010, pp. 61–66).

  4. 4.

    An example of the first type is the index generated by Buettner and Ebertz (2009) for German regions. An example of the second type is the approach of CAE and SVR (2010).

  5. 5.

    For a survey on the empirical literature on the relationship between health outcomes and weather, see Deschênes (2012).

  6. 6.

    For instance, Weber (1899), Beeson and Eberts (1989), Glaeser and Maré (2001), Moeller and Haas (2003), Yankow (2006), Rosenthal and Strange (2008), Kim et al. (2009), Chung et al. (2009).

  7. 7.

    For an official translation for the German administrative divisions, see EC-DGT (2014).

  8. 8.

    Mulligan and Sala-i-Martin (2000) find that the dispersion of the stock human capital across US increased during the 1980s, while the dispersion of the average years of schooling decreased for the same period.

  9. 9.

    “We hope to minimize concerns about endogeneity by including a large number of important amenities, but the results should still be interpreted with some caution” (Winters 2011c, pp. 451–452).

  10. 10.

    For instance, Marcuse (2003), Sawicki (2003), Glaeser (2005), Montgomery (2005), Peck (2005), Markusen (2006), McGranhan and Woja (2007), and Hoyman and Faricy (2009).

  11. 11.

    See, for instance, Wooldridge (2009, pp. 506–545).

  12. 12.

    These universities are public universities, land-grant universities, and Research I universities. Their location of these types of HEIs is believed not to be influenced by current levels of human capital and to be outside of the control of local population.

  13. 13.

    For more details, see Jöreskog (1973) and Acock (2013).

  14. 14.

    Model I is very complex and so to achieve a clear view of the structure of the relationships among the variables, the covariances are not shown in Fig. 1.1. See Fig. A.3 in the Appendix for an illustration of Model I showing the covariances.

  15. 15.

    Chi2 = 1.75 (p = 0.1864) for universities and political participation; chi2 = 0.79 (0.3734) for universities and political preferences; chi2 = 0.42 (0.5151) for universities and foreigners; chi2 = 1.09 (0.2968) for political participation and political preferences; chi2 = 0.93 (0.3344) for political participation and foreigners; chi2 = 0.29 (0.5889) for political preferences and foreigners.

  16. 16.

    Chi2 = 0.08 (p = 0.7757) for consumer services and recreation; chi2 = 6.12 (0.0134) for consumer services and water areas; chi2 = 25.83 (0.0000) for consumer services and sunshine; chi2 = 1.23 (0.2680) for recreation and water areas; chi2 = 4.42 (0.0354) for recreation and sunshine; chi2 = 3.44 (0.0635) for water areas and sunshine.

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    Ronney Aamoucke

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Aamoucke, R. (2016). Quality of Life and the Geography of Human Capital. In: Innovative Start-Ups and the Distribution of Human Capital. Contributions to Economics. Springer, Cham. https://doi.org/10.1007/978-3-319-44462-8_4

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