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Grados de Ruralidad: Una Propuesta de Medición para Argentina

Author

Listed:
  • Ivan Albina

    (CEDLAS-IIE-FCE-UNLP)

  • Leonardo Gasparini

    (CEDLAS-IIE-FCE-UNLP & CONICET)

  • Pablo Gluzmann

    (CEDLAS-IIE-FCE-UNLP & CONICET)

Abstract

Este trabajo contribuye a la medición de “grados de ruralidad†en Argentina. El trabajo propone un índice multidimensional relativo de ruralidad que integra la clasificación tradicional de áreas de INDEC con datos censales y estimaciones de distancias a centros poblados. Como ejercicios de robustez, se comparan los resultados con los obtenidos de luces en la noche e imágenes satelitales. Además de presentar mapas del grado de ruralidad para todo el territorio argentino, el trabajo ofrece una caracterización amplia de la población por categorías de ruralidad para el a˜no 2022 y de los cambios en el período intercensal 2010-2022. Esta caracterización incorpora variables socioeconómicas clave, como ingresos familiares, que trascienden la información disponible en los censos. A través de una medición más granular de la ruralidad, el trabajo contribuye a una mejor caracterización de las necesidades y realidades de las poblaciones que habitan zonas aisladas y de transición.

Suggested Citation

  • Ivan Albina & Leonardo Gasparini & Pablo Gluzmann, 2025. "Grados de Ruralidad: Una Propuesta de Medición para Argentina," CEDLAS, Working Papers 0358, CEDLAS, Universidad Nacional de La Plata.
  • Handle: RePEc:dls:wpaper:0358
    as

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    File URL: http://www.cedlas.econo.unlp.edu.ar/wp/wp-content/uploads/doc_cedlas358.pdf
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    References listed on IDEAS

    as
    1. Chris Elbers & Jean O. Lanjouw & Peter Lanjouw, 2003. "Micro--Level Estimation of Poverty and Inequality," Econometrica, Econometric Society, vol. 71(1), pages 355-364, January.
    2. Waldorf, Brigitte S., 2006. "A Continuous Multi-dimensional Measure of Rurality: Moving Beyond Threshold Measures," 2006 Annual meeting, July 23-26, Long Beach, CA 21383, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    3. Ravallion, Martin & Chen, Shaohua, 2003. "Measuring pro-poor growth," Economics Letters, Elsevier, vol. 78(1), pages 93-99, January.
    4. Abbate Nicolás & Gasparini Leonardo & Gluzmann Pablo Alfredo & Montes Rojas Gabriel & Sznaider Iván & Yatche Tobías, 2023. "Ingreso Estructural Por Área Geográfica: una aplicación para Argentina," Asociación Argentina de Economía Política: Working Papers 4622, Asociación Argentina de Economía Política.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    JEL classification:

    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
    • R23 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Regional Migration; Regional Labor Markets; Population
    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis

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