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Modelling Inter-urban Migration in an Open Population Setting: The Case of New Zealand

Chapter
Part of the New Frontiers in Regional Science: Asian Perspectives book series (NFRSASIPER, volume 40)

Abstract

In this chapter, we revisit the modelling of gross inter-urban migration flows in New Zealand. As in previous work, we identify a range of geographic, demographic, economic and climatic characteristics of urban areas, which are statistically significant determinants of migration. However, we argue that in a small but open population such as New Zealand (in which one quarter of the resident population is foreign born and one sixth of the New Zealand-born population lives abroad), inter-urban migration should be modelled jointly with rural-urban and international migration. We proceed to estimate a modified gravity model of migration in which the flow matrix is augmented with rural-urban and international migration. Migration data are obtained from four successive population censuses since 1996. We find notable differences in the impact of migration determinants when comparing urban-urban, urban-rural and urban-world migration flows. The estimation of these models is straightforward and does not require collection of data on rural areas or foreign countries. Hence, the method can be easily applied to other case studies in which international and/or rural-urban migration are important components of population churn.

Keywords

Gravity model Internal migration International migration New Zealand 

Notes

Acknowledgements

Research for this study was originally funded by the 2012–2014 Nga Tangata Oho Mairangi project, Ministry of Business Innovation and Employment grant CONT-29661-HASTR-MAU, and more recently by the 2016–2019 National Science Challenge 11: Building Better Homes, Towns and Cities project. Access to the data used in this study was provided by Statistics New Zealand (SNZ) under conditions designed to give effect to the security and confidentiality provisions of the Statistics Act 1975. All frequency counts using census data were subject to base three rounding in accordance with SNZ’s release policy for census data.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Waikato Management SchoolUniversity of WaikatoHamiltonNew Zealand
  2. 2.Motu Economic and Public Policy ResearchWellingtonNew Zealand
  3. 3.National Institute of Demographic and Economic Analysis (NIDEA)University of WaikatoHamiltonNew Zealand
  4. 4.Department of Spatial EconomicsVrije Universiteit AmsterdamAmsterdamThe Netherlands

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