The estimation and interpretation of coefficients in panel gravity models of migration

Michael P. Cameron, Jacques Poot

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

In this paper, we demonstrate that the conventional ordinary least squares and fixed effects estimators of classical gravity models of migration are biased, and that the interpretation of coefficients in the fixed effects gravity model is typically incorrect. We then present a best linear unbiased (BLU) estimator for gravity models of migration, and illustrate its application with inter-regional data from New Zealand. The results demonstrate that the standard ordinary least squares and fixed effect models lead to biased coefficients on population. Alternative estimates that are BLU are provided for a data generating process with fixed origin and destination effects. The coefficients on population must be interpreted in this model as growth rate effects rather than level effects. Our findings also have significance for other types of spatial interaction modelling.

Original languageEnglish
Pages (from-to)9-15
Number of pages7
JournalLetters in Spatial and Resource Sciences
Volume12
Issue number1
DOIs
Publication statusPublished - 4 Apr 2019

Fingerprint

migration
gravity
interpretation
Coefficients
Gravity model
effect
New Zealand
Estimator
Fixed effects
Ordinary least squares
interaction
modeling
Modeling
Level effect
Destination
Data generating process
Fixed effects model
Spatial interaction

Keywords

  • Fixed effects
  • Gravity model
  • Gross migration flows
  • New Zealand

Cite this

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The estimation and interpretation of coefficients in panel gravity models of migration. / Cameron, Michael P.; Poot, Jacques.

In: Letters in Spatial and Resource Sciences, Vol. 12, No. 1, 04.04.2019, p. 9-15.

Research output: Contribution to JournalArticleAcademicpeer-review

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AB - In this paper, we demonstrate that the conventional ordinary least squares and fixed effects estimators of classical gravity models of migration are biased, and that the interpretation of coefficients in the fixed effects gravity model is typically incorrect. We then present a best linear unbiased (BLU) estimator for gravity models of migration, and illustrate its application with inter-regional data from New Zealand. The results demonstrate that the standard ordinary least squares and fixed effect models lead to biased coefficients on population. Alternative estimates that are BLU are provided for a data generating process with fixed origin and destination effects. The coefficients on population must be interpreted in this model as growth rate effects rather than level effects. Our findings also have significance for other types of spatial interaction modelling.

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