Dots to boxes: Do the size and shape of spatial units jeopardize economic geography estimations?

Briant, Anthony; Combes, Pierre-Philippe; Lafourcade, Miren

doi:10.1016/j.jue.2009.09.014

Cited by 258 publications

(233 citation statements)

References 21 publications

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“…Smaller areas (e.g. five-digit postal code areas) result in relatively many more areas without logistics employment (76% of all five-digit postal code areas versus 19% of the four-digit postal code), artificially increasing spatial concentration measures such as the locational Gini coefficient (Briant et al, 2010). Larger areas are not an option due to two reasons.…”

Section: Spatial Clusters and Location Dynamics In Logistics In A Dutmentioning

confidence: 99%

“…Bathelt et al, 2004), logistics specific agglomeration economies, like the opportunity to exchange transport capacity, are especially relevant in close proximity. As Dutch postal code areas are defined based on the distribution of the population, this administrative zoning scheme minimizes distortions (Briant et al, 2010). Hence, the analyses will be conducted for four-digit postal code areas.…”

Section: Spatial Clusters and Location Dynamics In Logistics In A Dutmentioning

confidence: 99%

See 1 more Smart Citation

Spatial concentration and location dynamics in logistics: the case of a Dutch province

Heuvel¹,

Langen²,

Donselaar³

et al. 2013

Journal of Transport Geography

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Section: Spatial Clusters and Location Dynamics In Logistics In A Dutmentioning

confidence: 99%

Section: Spatial Clusters and Location Dynamics In Logistics In A Dutmentioning

confidence: 99%

Spatial concentration and location dynamics in logistics: the case of a Dutch province

Heuvel¹,

Langen²,

Donselaar³

et al. 2013

Journal of Transport Geography

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“…2 See Briant, Combes, and Lafourcade (2010) for further discussion about this issue. 3 The preparation of the wage data follows that of these two papers closely but we use a different set of years.…”

Section: Datamentioning

confidence: 99%

Sorting and local wage and skill distributions in France

Combes

Duranton

Gobillon

et al. 2012

Regional Science and Urban Economics

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This paper provides descriptive evidence about the distribution of wages and skills in denser and less dense employment areas in France. We confirm that on average, workers in denser areas are more skilled. There is also strong over-representation of workers with particularly high and low skills in denser areas. These features are consistent with patterns of migration including negative selection of migrants to less dense areas and positive selection towards denser areas. Nonetheless migration, even in the long-run, accounts for little of the skill differences between denser and less dense areas. Finally, we find marked differences across age groups and some suggestions that much of the skill differences across areas can be explained by differences between occupational groups rather than within. The Institute for the Study of Labor (IZA) in Bonn is a local and virtual international research center and a place of communication between science, politics and business. IZA is an independent nonprofit organization supported by Deutsche Post Foundation. The center is associated with the University of Bonn and offers a stimulating research environment through its international network, workshops and conferences, data service, project support, research visits and doctoral program. IZA engages in (i) original and internationally competitive research in all fields of labor economics, (ii) development of policy concepts, and (iii) dissemination of research results and concepts to the interested public.IZA Discussion Papers often represent preliminary work and are circulated to encourage discussion. Citation of such a paper should account for its provisional character. A revised version may be available directly from the author. ABSTRACT Sorting and Local Wage and Skill Distributions in France *This paper provides descriptive evidence about the distribution of wages and skills in denser and less dense employment areas in France. We confirm that on average, workers in denser areas are more skilled. There is also strong over-representation of workers with particularly high and low skills in denser areas. These features are consistent with patterns of migration including negative selection of migrants to less dense areas and positive selection towards denser areas. Nonetheless migration, even in the long run, accounts for little of the skill differences between denser and less dense areas. Finally, we find marked differences across age groups and some suggestions that much of the skill differences across areas can be explained by differences between occupational groups rather than within.JEL Classification: J31, J61, R12, R23

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“…For example, Ellison and Glaeser index (EG index) (1997) is one of the most popular methods which consider space in a discrete manner. This index is believed to measure the extent of industrial agglomeration more accurately than Gini index due to the purge of the plant size effect (Briant et al, 2010;Lin et al, 2011). Many empirical studies have employed EG index to explain the growth (Braunerhjelm and Borgman, 2004) and found out the factors of industrial agglomeration (Henderson, 2003;Ellison et al, 2010;Alfaro and Chen, 2014).…”

Section: Introductionmentioning

confidence: 99%

“…Basically, the observations on different levels probably lead to various spatial patterns. In other words, the results are quite sensitive to the shape, size, and position of the areal units, namely the Modifiable Areal Unit Problem (MAUP) (Morphet, 1997;Briant et al, 2010). Furthermore, those area units, are usually shaped to meet the administrative needs rather than to reflect the economic relations within the units.…”

Section: Introductionmentioning

confidence: 99%

Industrial spatial agglomeration using distance-based approach in Beijing, China

Zhang

et al. 2015

Chin. Geogr. Sci.

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To study the difference of industrial location among different industries, this article is to test the spatial agglomeration across industries and firm sizes at the city level. Our research bases on a unique plant-level data set of Beijing and employs a distance-based approach, which considers space as continuous. Unlike previous studies, we set two sets of references for service and manufacturing industries respectively to adapt to the investigation in the intra-urban area. Comparing among eight types of industries and different firm sizes, we find that: 1) producer service, high-tech industries and labor-intensive manufacturing industries are more likely to cluster, whereas personal service and capital-intensive industries tend to be randomly dispersed in Beijing; 2) the spillover of the co-location of firms is more important to knowledge-intensive industries and has more significant impact on their allocation than business-oriented services in the intra-urban area; 3) the spatial agglomeration of service industries are driven by larger establishments, whereas manufacturing industries are mixed.

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Dots to boxes: Do the size and shape of spatial units jeopardize economic geography estimations?

Cited by 258 publications

References 21 publications

Spatial concentration and location dynamics in logistics: the case of a Dutch province

Spatial concentration and location dynamics in logistics: the case of a Dutch province

Sorting and local wage and skill distributions in France

Industrial spatial agglomeration using distance-based approach in Beijing, China

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