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Erschienen in: The Annals of Regional Science 2/2021

02.03.2021 | Original Paper

Location patterns of service activities in large metropolitan areas: the Case of São Paulo

verfasst von: Edilberto Tiago de Almeida, Raul da Mota Silveira Neto, Jaime Macedo de Brito Bastos, Rubens Lopes Pereira da Silva

Erschienen in: The Annals of Regional Science | Ausgabe 2/2021

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Abstract

We present a set of detailed evidence about the location patterns of service activities in the largest and most important Brazilian metropolitan region, the São Paulo Metropolitan Region (SPMR). Different from previous analysis of this big urban agglomeration, our results are obtained using a unique dataset of geocoded firms and a distance-based measure of firms’ location, thus not susceptible to the modifiable areal unit problem (MAUP). We find that around 89% of 3-digit service sectors present significant defined location patterns and, based on maximum distances where significant location patterns are observed, identify spatial location of clusters of some activities. Our results also indicate that firms’ activities of FIRE (finance and real estate), IT-related services, and high human capital-based services present the highest probability of location at shorter distance from each other. The tendency for location at shorter distances between firms engaged in these activities contrasts with the more decentralized patterns observed for firms involved in retail and urban infrastructure services. Additional results indicate that both the location patterns of activities and the degree of proximity or agglomeration of firms are positively associated with human capital, the degree of product differentiation, and the degree of inter-sector dependence between activities.

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Fußnoten
1
The municipality is the local administrative unit in Brazil. It is akin to a county, except with a single mayor and municipal council. Municipalities range from lightly populated rural ones with one or two small towns to heavily populated urban ones that are part of greater metropolitan regions. There are no unincorporated areas in Brazil.
 
2
More details available at: http://​www.​seade.​gov.​br/​.
 
3
 
4
Previous evidence for Brazil shows that the externalities generated by locally diversified and specialized economic environments are important to explain the spatial configuration of productive activity (see Silva (2007); Silva and Silveira Neto (2009); Fochezatto and Valentini (2010); Rocha et al. (2013) and Almeida et al. (2017)).
 
5
We use distance between municipal centroids.
 
6
The formal jobs include formally registered workers, employers, and autonomous workers that contribute to any social security system.
 
7
Although there is a newer version of CNAE released in 2007 (CNAE 2.0), there are no significant differences for the sectors analyzed in this survey. More details on the correspondence between the versions can be found at: https://​concla.​ibge.​gov.​br/​classificacoes/​correspondencias​/​atividades-economicas.​html.
 
8
Following Silverman (2018), the ideal bandwidth for the Gaussian kernel function is \(1.06sn ^{- 0.2}\) where s is the standard deviation of n(n-1) bilateral distances.
 
9
Klier and McMillen (2008), for example, used zip codes with no plants as possible counterfactual of randomly located industries. Note, however, that this kind of alternative does not avoid using, for example, manufacturing locations or residential lots as possible counterfactuals for service establishments.
 
10
Following Duranton and Overman (2005), robustness tests with 2,000 and 10,000 simulations are also performed.
 
11
Unlike Duranton and Overman (2005), Behrens and Bougna (2015) and Aleksandrova et al. (2019) analyzed large countries with large territorial extension, so it is important to define an adequate range. For Canada, Behrens and Bougna (2015) used 800 kilometers and for Russia, Aleksandrova et al. (2019) used 1,000 kilometers. For more details on the computational implementation, see Aleksandrova et al. (2019).
 
12
When a sector shows peaks of concentration, it is possible that other points of the curve will fall below the lower confidence bound as a form of compensation. This happens because the values are normalized to sum to 1; this does not imply dispersion.
 
13
For every meter, we have an estimate; so we work with 52,900 observations of the index for each sector.
 
14
Although some of these activities can be classified as creative sectors (Méndez-Ortega and Arauzo-Carod 2019), they are often based on higher levels of human capital.
 
15
Using the index of Ellison and Glaeser (1997) for the USA, Kolko (2010) found that service sectors are also heavily concentrated.
 
16
As a specific example, consider the case of firms of Non-specialized retailing-CNAE 521 we have discussed above.
 
17
Considering the 5 km column of Table 5, the value of Spearman’s rank correlation coefficient is 0.5173, while Kendall’s rank correlation coefficients have values of 0.3864 and 0.3886 for \(\tau _a\) and \(\tau _b\), respectively.
 
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Metadaten
Titel
Location patterns of service activities in large metropolitan areas: the Case of São Paulo
verfasst von
Edilberto Tiago de Almeida
Raul da Mota Silveira Neto
Jaime Macedo de Brito Bastos
Rubens Lopes Pereira da Silva
Publikationsdatum
02.03.2021
Verlag
Springer Berlin Heidelberg
Erschienen in
The Annals of Regional Science / Ausgabe 2/2021
Print ISSN: 0570-1864
Elektronische ISSN: 1432-0592
DOI
https://doi.org/10.1007/s00168-021-01054-1

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