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An annual estimate of spatially disaggregated populations: Spain, 1900–2011

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  • Rafael González-Val

    (Universidad de Zaragoza
    Universitat de Barcelona)

  • Javier Silvestre

    (Universidad de Zaragoza)

Abstract

Long-term population estimates are usually based on decennial (or roughly decennial), census-type data, especially those that go beyond the aggregate or national level. The lack of annual population datasets, however, restricts the range of analysis and therefore our knowledge of populations’ behaviour over time. This paper contributes to this scant literature by providing two new long-term, annually and spatially disaggregated population estimates for Spain, a key case study. We use a set of official sources and propose a straightforward method to estimate Spanish annual populations at two levels of spatial disaggregation, the provinces (NUTS III) and their capital cities (a selection of LAU II/NUTS V), between 1900 and 2011. For the cities, our estimates account for changes in boundaries. Our proposed method is especially suitable for countries with a lack of long-term, systematic, historical migration statistics, a common issue. To test the robustness of our estimates, some comparisons are made with previous more aggregated-level or decennial census-based estimates, and a preliminary analysis of the evolution of disaggregated Spanish population is presented.

Suggested Citation

  • Rafael González-Val & Javier Silvestre, 2020. "An annual estimate of spatially disaggregated populations: Spain, 1900–2011," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 65(2), pages 491-508, October.
  • Handle: RePEc:spr:anresc:v:65:y:2020:i:2:d:10.1007_s00168-020-00992-6
    DOI: 10.1007/s00168-020-00992-6
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    References listed on IDEAS

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    3. Rafael González-Val & Luis Lanaspa & Fernando Sanz-Gracia, 2014. "New Evidence on Gibrat’s Law for Cities," Urban Studies, Urban Studies Journal Limited, vol. 51(1), pages 93-115, January.
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    More about this item

    JEL classification:

    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts
    • N33 - Economic History - - Labor and Consumers, Demography, Education, Health, Welfare, Income, Wealth, Religion, and Philanthropy - - - Europe: Pre-1913
    • N34 - Economic History - - Labor and Consumers, Demography, Education, Health, Welfare, Income, Wealth, Religion, and Philanthropy - - - Europe: 1913-
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)

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