by Rizal K.*
In part-1, we have discussed about how the growth theories try to explain the unbalanced outcomes of economic development. In fact, some branches in neoclassical economics put considerable effort to explain the economic performance of spaces, such as Geographical Economics, or for some called it as New Economic Geography (NEG), or later labelled as Spatial Economics, and Urban Economics. This Part-2 briefly discusses the underlying ideas of those theories. Here, the term region is used interchangeably with city or space.
Geographical economics, New Economic Geography (NEG), Urban Economics
Despite its insistence on equilibrium, selected recent work embedding increasing returns in their conceptual apparatus demonstrates that national and regional divergence in GDP per capita and growth rates are possible. Maintaining perfectly rational profit-maximising individuals from the neoclassical conceptual framework, Krugman (1991) developed a formal model based on agglomeration economies, which were introduced a long time ago by Alfred Marshall (2014,1890) and cumulative causation, which first was introduced by Gunnar Myrdal (1957). Related to the concept of agglomeration economies is the concept of increasing returns to scale (Krugman, 1991). In short, by co-locating in the same place, firms can take advantage of a bigger market and gain efficiency by exploiting economies of scale.
In general, the literature distinguishes two forms of agglomeration economies: Localization (Marshall, 2014, 1890) and Urbanization Economies (Jacobs, 1970). Urbanization economies accrue to firms if they locate in large, diverse cities, while localization economies accrue to firms if they locate in cities specialized in the industry in which they are active. Advantages of locating in large cities are the availability of a large, diverse labour pool, a large number of different suppliers and customers and between industry knowledge spillovers (Jacobs, 1970). The advantages for firms to locate in specialized cities are the availability of a large pool of specialized labour and related suppliers and customers that result in more limited knowledge spillovers (Marshall, 2014, 1890). Duranton and Puga (2004) focus on what cities actually do for firms and identify sharing (of specialised input suppliers and skilled labour), matching (of suppliers to customers and workers with jobs) and knowledge spillovers or learning as key tasks accomplished in cities creating static and dynamic forms of externalities.
In terms of its dynamic externalities, Glaeser et al. (1992) distinguish three types of agglomeration, which are Marshall-Arrow-Romer (MAR) externalities, Jacobs’ externalities, and Porter’s externalities. MAR, Jacobs and Porter’s externalities are commonly referred as specialisation, diversity, and competition externalities respectively. The key distinction of those three externalities is laid on the nature of knowledge spillovers within agglomeration. Specialisation concept stresses on intra-industry knowledge spillovers, diversity emphasizes on inter-industry knowledge spillovers, while competition underlines the role of competition in knowledge spillovers. Beaudry and Schiffauerova (2009) summarize the effects of dynamic externalities on knowledge spillovers in Table 1.
Source: Beaudry and Schiffauerova (2009)
While a large number of empirical studies attempted to establish the relative importance of the effects of specialisation and diversity externalities on knowledge spillovers and innovative activities (Capello, 2002; Combes, 2000; Glaeser et al., 1992; Henderson, 2003), the results seem inconclusive (Beaudry and Schiffauerova, 2009; Groot et al., 2009). Various factors are suspected causing the divergent results mainly related to the methodological and measurement issues as well as to the choice of cases and time periods. It is worth to note that most empirical works on agglomeration externalities use some sorts of spatial concentration or polarization measures as approximation of regional specialisation and diversity (see for example Cingano and Schivardi, 2004; Combes, 2000; Dekle, 2002; Henderson, 2003; 2001). The underlying idea of the measure is that the more concentrated an industry within a certain region, the more specialized is the region. Concentration is commonly measured as the shares of employments or outputs of industries in a region relative to its broader (usually national) aggregation. Meanwhile, regional diversity is commonly measured as the inverse of specialisation. For example, Duranton and Puga (2000), Henderson et al. (1995), and Combes (2000) are some who develop diversity measures based on the inverse of Hirschman-Herfindahl index. Although specialisation and diversity are often viewed in the empirical works in opposition to each other, Nakamura and Paul (2009) argue that they are not. Diversity may also consist of complex specialisations (Malizia and Ke, 1993).
Amid inconclusive results whether specialisation or diversity is more important to promote knowledge spillover and innovative activities, Neffke (2009) identifies the roles of technological maturity and relatedness between industries as major omission in the empirical works (for an exception see Duranton and Puga (2001) on nursery cities). Specific to relatedness, the author argues that agglomeration externalities in the form of knowledge spillovers should be viewed within the framework of related specialisation and related diversity instead of pure specialisation and diversity. In other words, pure specialisation and pure diversity do not automatically promote knowledge spillover if the specialisations are not related cognitively (Nooteboom, 2000). Neffke’s findings suggest that maturity and relatedness of industries do have effects on agglomeration externalities.
Furthermore, the actual learning processes leading to technology spillovers and external economies of scale and scope are not developed in detail by NEG. If technology spillover is identified as key factor, then this is a serious omission that needs to be addressed when studying regional growth and development.
In sum, NEG demonstrates the possibilities for divergent outcomes of regional development in the form of agglomerated economies. However, this theoretical framework is not supported by conclusive empirical literature yet, particularly in addressing the relative importance of different agglomeration factors on knowledge spillovers. This may be due to a lack of considerations for differences and similarities (relatedness) between industries.
Beaudry, C., Schiffauerova, A., 2009. Who’s right, Marshall or Jacobs? The localization versus urbanization debate. Res. Policy 38, 318–337.
Capello, R., 2002. Spatial and Sectoral Characteristics of Relational Capital in Innovation Activity. Eur. Plan. Stud. 10, 177–200.
Cingano, F., Schivardi, F., 2004. Identifying the Sources of Local Productivity Growth. J. Eur. Econ. Assoc. 2, 720–742.
Combes, P.-P., 2000. Economic Structure and Local Growth: France, 1984?1993. J. Urban Econ. 47, 329–355.
Dekle, R., 2002. Industrial Concentration and Regional Growth: Evidence from the Prefectures. Rev. Econ. Stat. 84, 310–315.
Duranton, G., Puga, D., 2004. Micro-Foundations of Urban Agglomeration Economies. Handb. Reg. Urban Econ., Cities and Geography 4, 2063–2117.
Duranton, G., Puga, D., 2001. Nursery Cities: Urban Diversity, Process Innovation, and the Life Cycle of Products. Am. Econ. Rev. 91, 1454–1477.
Duranton, G., Puga, D., 2000. Diversity and Specialisation in Cities: Why, Where and When Does it Matter? Urban Stud. 37, 533–555.
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Jacobs, J., 1970. The economy of cities, Vintage books. Vintage Books, New York.
Krugman, P., 1991. Increasing Returns and Economic Geography. J. Polit. Econ. 99, 483–499.
Malizia, E.E., Ke, S., 1993. The Influence of Economic Diversity on Unemployment and Stability. J. Reg. Sci. 33, 221–235.
Marshall, A., 2014. Principles of Economics. Palgrave Macmillan Macmillan [distributor, New York; Gordonsville.
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Nakamura, R., Paul, C.J.M., 2009. Measuring agglomeration, in: Handbook of Regional Growth and Development Theories. Edward Elgar, Cheltenham, UK; Northampton, MA, pp. 305–328.
Neffke, F., 2009. Productive place: the influence of technological change and relatedness on agglomeration externalities (Unpublished thesis). Utrecht.
Nooteboom, B., 2000. Learning and Innovation in Organizations and Economies. Oxford University Press.
 There are some indexes found in the literature to measure regional specialization such as Location Quotient (LQ) and Hirschman-Herfindahl Index (HHI), Gini Index (distribution of industrial composition), Ellison and Glaeser Index, and Krugman Index (Nakamura and Paul, 2009).