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| Título: | An empirical typology of travel-to-work areas in Argentina based on sectoral profiles of territorial coagglomeration |
| Autor(es): | Niembro, Andrés Alberto Calá, Carla D. Belmartino, Andrea |
| Fecha de publicación: | dic-2019 |
| Es parte de: | Workshop on Economic Complexity and Development: Growth, Structural Change, and Sustainability |
| Resumen: | Spatial location of economic activities is a central aspect for the analysis of a country's productive structure and the design of productive development policies. In developed countries there is a large number of investigations that describe regional specialization profiles within a single country and explain the observed patterns based on different factors, such as the existence of economies of scale, the endowment of natural resources or fiscal incentives. The specialization profile is also typically used as an input to explain the economic performance of the regions in terms of employment growth, productivity or value added (Frenken et al., 2007; Bishop and Gripaios, 2010; van Oort et al., 2015; Cortinovis and van Oort, 2015). Besides, the evolution of regional specialization profiles can be used to illustrate or describe processes of structural change. In Latin America, a set of studies calculate and analyze the type of regional specialization, linking it with the degree of diversification and regional development in Uruguay, Chile, Paraguay and El Salvador (Rodríguez Miranda et al., 2019). In Argentina some contributions quantify and describe the type of productive specialization at the regional level (provinces), either for manufacturing (Jaramillo et al., 2017) or for all sectors (Keogan et al., 2020). Other studies link the type of specialization of Travel-to-Work Areas2 (TWA) with productive diversity (Rotondo et al., forthcoming) or with their ability to recover from crises (Otegui Banno et al., 2019). All these contributions -both for developed and developing countries- use basic specialization measures (relative indices3) that usually have several limitations. On the one hand, calculations with a low level of sectoral disaggregation do not allow distinguishing specializations that may be qualitatively different within the same category, such as regions specialized in "trade and services". On the other hand, if the level of disaggregation is high, a large number of specializations are identified in each region, which difficults a clear exposition of results, and leads to a loss of valuable information when analyzing only the first specialization. In addition, in order to compute these relative indices, each sector is considered separately, without taking 1 We thank the Employment and Business Dynamics Observatory (EBDO/OEDE), under the Ministry of Production and Labor, for facilitating access to the database and for the valuable suggestions to this preliminary version. We are also grateful to Santiago Otegui Banno and Manuela Coppola Goyhenespe for research assistance. 2 A Travel-to-Work Area is a geographical area which is delimited by daily displacements (the so-called pendulum movements) that people make to go to (and back from) their work (Borello, 2002). 3 The relative specialization index measures the proportion of employment or value added in a certain activity in a region over the proportion of employment or value added that the same activity has in the whole country. The region will be specialized in those activities with indexes higher than one. 1 into account the interdependencies between activities. That is, the fact that certain activities are frequently located near (or developed alongside) others, such as the set of "heavy industries" or activities that are part of the same production network or value chain, is ignored. We propose to overcome these limitations by using a combination of multivariate analysis techniques. First, we empirically build a set of sectoral profiles that group economic activities according to their proximity or joint development, without taking into account ad-hoc classifications. Unlike the idea of value chains or production networks, these sectoral co- agglomeration profiles show what kind of activities tend to be developed jointly in a specific territory, and do not necessarily indicate the existence of backward or forward linkages. Secondly, we use these sectoral profiles to classify the main 85 Travel-to-Work Areas (TWA) in Argentina, thus defining an empirical typology based on their patterns of productive specialization. Our results indicate that in some TWA a single set of co-agglomerated sectors stands out, while in others several co-agglomeration profiles coexist. |
| URI: | https://rid.unrn.edu.ar/jspui/handle/20.500.12049/4495 http://nulan.mdp.edu.ar/3296/1/cala-etal-2019.pdf |
| Aparece en las colecciones: | Objetos de conferencia |
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| Archivo | Descripción | Tamaño | Formato | |
|---|---|---|---|---|
| CALA2019-An empirical typology.pdf | 1,1 MB | Adobe PDF | Visualizar/Abrir |
Este documento es resultado del financiamiento otorgado por el Estado Nacional, por lo tanto queda sujeto al cumplimiento de la Ley N° 26.899
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