La evolución espacial de los subcentros de empleo en Ciudad Juárez, Chihuahua (1994-2004)
Un análisis con indicadores de autocorrelación espacial global y local / The Spatial Evolution of Employment Subcenters in Ciudad Juárez, Chihuahua (1994-2004): An Analysis Using Global and Local Spatial Autocorrelation Indicators
Bibliographic Data
| ID | 4959953 |
|---|---|
| Authors | César Mario Fuentes (0000-0002-7224-5723, El Colegio de la Frontera Norte, corresponding author), Vladimir Hernández (0000-0003-0206-9768, Rafael Advanced Defense Systems (Israel)) |
| Year | 2015 |
| Volume | 30 |
| Issue | 2 |
| Pages | 433 |
| Publication date | 2015-05-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Estudios Demográficos y Urbanos (JOURNAL) |
| Journal identifiers | ISSN: 0186-7210 • E-ISSN: 2448-6515 |
| Publisher | El Colegio de Mexico, A.C (PUBLISHER) |
| DOI | 10.24201/edu.v30i2.1480 |
| OpenAlex | W2318020808 |
| Language | ES |
| Citations received | 3 |
| References cited | 21 |
El objetivo del artículo es identificar los subcentros de empleo total mediante el uso de indicadores de autocorrelación espacial global y local en Ciudad Juárez, Chihuahua, en el periodo 1994-2004. Esta metodología usa matrices de pesos espaciales e incorpora la noción de unidades vecinas y no está limitada al criterio de contigüidad del método de doble umbral. La variable usada fue la densidad bruta de empleo total (manufactura, comercio y servicio) en los años 1994 y 2004 a nivel de AGEB, obtenida de los Censos Económicos (INEGI, 1994 y 2004). Mediante el uso de dos indicadores de autocorrelación espacial, en específico el I de Moran y los indicadores locales de asociación espacial (LISA por sus siglas en inglés), fue posible identificar varios centros y subcentros de empleo total. Los resultados muestran la presencia de dependencia y heterogeneidad espacial que se manifiestan en la forma de agrupamientos de alta densidad de empleo (alto-alto) tanto en el distrito central de negocios (DCN) como en el subcentro de empleo mixto localizado en el corredor industrial de la avenida Rafael Pérez Serna. Asimismo, existen varios subcentros de empleo manufacturero aislados de alta densidad (alto-alto) localizados sobre las principales vialidades dirigidas a puertos internacionales. En este contexto, se puede concluir que la distribución del empleo fuera del DCN, producto de economías de aglomeración, implica la presencia de una estructura urbana policéntrica.Abstract:The objective of this article is to identify total employment subcenters through the use of global and local spatial autocorrelation indicators in Ciudad Juárez, Chihuahua, during the period from 1994-2004. This methodology uses spatial weights matrices, includes the notion of neighboring units and is not restricted to the contiguity criterion of the double threshold method. The variable used was the gross density of total employment (manufacturing, trade and service) in 1994 and 2004 at the ageb level, obtained from the Economic Census (INEGI, 1994 and 2004). Two spatial autocorrelation indicators, specifically Moran's I and local indicators of spatial association (LISA) were used to identify several centers and sub-centers of total employment. The results show the presence of dependence and spatial heterogeneity expressed in the form of groups of high density employment (high-high) in both the central business district (CBD) and the mixed employment subcenter located in the industrial corridor of Avenida Rafael Pérez Serna. Likewise, there are several isolated high density manufacturing employment subcenters (high-high) located on the main roads leading to international ports. In this context, one can conclude that employment distribution outside the CBD, resulting from agglomeration economies, implies the presence of a polycentric urban structure
Art · Cartography · Geography · Humanities · Regional Development and Innovation · Regional Economic and Spatial Analysis · Regional Economics and Spatial Analysis
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| Unique citing works | 3 |
|---|---|
| Citations per year | 0,43 |
| Citation span | 2019 - 2023 (5) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 3 |