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Journal of Geographical Systems

, Volume 8, Issue 3, pp 307–316 | Cite as

Estimation of a continuous spatio-temporal population model

  • Javier Alvarez
  • Pascal MossayEmail author
Original paper

Abstract

In this paper we propose a continuous spatio-temporal model that describes population change in a region in terms of population growth, migration drift towards regions with better economic or climate conditions, and population diffusion from more populated to less populated areas. Finite-differences are used to approximate the space and time derivatives. The model is estimated by using population data from the US census corresponding to the period 1790–1910. People tend to migrate from east to west, and to relocate towards regions with lower precipitation levels and more abundant coal and iron resources. Also population growth tends to be larger in zones with higher precipitation levels and higher temperatures.

Keywords

Population dynamics Migration Diffusion Drift Estimation 

JEL classification

R23 C51 

Notes

Acknowledgements

We would like to thank the editor Manfred Fischer as well as three anonymous referees for their valuable comments that have helped to improve the clarity and quality of the paper. Financial support from the Spanish Ministerio de Ciencia y Tecnología, under ERDF project SEJ2004-08011ECON, is acknowledged.

References

  1. Beckmann M, Puu T (1985) Spatial economics: potential, density and flow. North-Holland, AmsterdamGoogle Scholar
  2. Beeson PE, DeJong D, Troesken W (2001) Population growth in U.S. counties 1840–1990. Reg Sci Urban Econ 31(6):669–699CrossRefGoogle Scholar
  3. Donaghy KP (2001) Solution and econometric estimation of spatial dynamic models in continuous space and continuous time. J Geogr Syst 3(3):257–270CrossRefGoogle Scholar
  4. Donaghy KP, Plotnikova M (2004) Econometric estimation of a spatial dynamic model in continuous space and continuous time: an empirical demonstration. In: Getis A, Mur J, Zoller H (eds) Spatial econometrics and spatial statistics. Palgrave Macmillan, London, pp 89–104Google Scholar
  5. Hotelling H (1921) A mathematical theory of migration. MA Thesis reprinted in Environment and Planning A (1978) 10:1223–1239Google Scholar
  6. Isard W, Liossatos P (1979) Spatial dynamics and optimal space-time development. North-Holland, AmsterdamGoogle Scholar
  7. Mossay P (2003) Increasing returns and heterogeneity in a spatial economy. Reg Sci Urban Econ 33(4):419–444CrossRefGoogle Scholar
  8. Murray JD (2004) Mathematical biology. Springer, Berlin Heidelberg New YorkGoogle Scholar
  9. Skellam JG (1951) Random dispersal in theoretical populations. Biometrika 38:196–218PubMedGoogle Scholar
  10. Sonnenschein H (1982) Price dynamics based on the adjustment of firms. Am Econ Rev 72(5):1088–1096Google Scholar
  11. Tobler W (1981) A model of geographic movement. Geogr Anal 13:1–20CrossRefGoogle Scholar
  12. Tobler W (1997) Movement modeling on the sphere. Geogr Environ Model 1:97–103Google Scholar
  13. US Department of Commerce and Labor, Bureau of the Census (1909) A century of population growth. Goverment Printing Office, WashingtonGoogle Scholar
  14. US Department of the Interior, Census Office (1886) Report on the mining industries of the United States. Goverment Printing Office, WashingtonGoogle Scholar

Copyright information

© Springer-Verlag 2005

Authors and Affiliations

  1. 1.Departamento de Fundamentos del Análisis EconómicoUniversidad de AlicanteAlicanteSpain
  2. 2.Banco de EspañaMadridSpain

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