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Erschienen in: Empirical Economics 4/2019

25.06.2018

A spatio-temporal analysis of migration

verfasst von: Alice Milivinti

Erschienen in: Empirical Economics | Ausgabe 4/2019

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Abstract

Migration is a space- and time-dependent phenomenon. Traditional geographical migration models have considered the distance between source and destination countries or have applied suitable normalizations to treat the correlation among migratory flows. To disentangle cross-sectional dependence, spatial correlation is explored in mainly two directions. First, migratory flows from “neighbouring” countries are considered to be directly interconnected. Second, a set for exogenous drivers are allowed to be correlated among the different economic units. Swiss immigration, from 153 source countries from 1981 to 2011, is modelled using a dynamic spatial econometric model able to capture both path-dependency and spatial interactions. An out-of-sample forecasting, performed to assess the model’s accuracy, confirms the crucial role played by the spatial terms over the dynamic ones.

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Fußnoten
1
The author acknowledges this approach has been criticized by Reed (2015).
 
2
The demeaning process subtracts unit i mean value of both the dependent (\(\bar{y}_{i}\)) and independent variables (\(\bar{X_i}\)) from the respective variables.
 
3
Nickell (1981) demonstrates that the bias is of order 1 / T as \(N \rightarrow \infty \).
 
4
Only time-independent matrices are used in the current study to guarantee a reliable degree of exogeneity. In general, spatial models are not well suited to fit time-varying spatial matrices.
 
5
The model is estimated using XSMLE: Stata module for spatial panel data model estimation (Belotti et al. 2017), which uses the Yu et al. (2008) estimator.
 
6
In 2011, there were changes in production methods and the concept for the permanent resident population including persons in the asylum process resident for 12 months or more in Switzerland, which it was not the case before.
 
7
Immigration from Liechtenstein equals 5313 people over 31 years. It may also be noticed that immigration of Swiss and Liechtenstein citizens is minor and nearly constant over time.
 
8
Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg, the Netherlands, Portugal, Spain, Sweden, UK (EU15) and Iceland, Norway, Liechtenstein, Switzerland (EFTA) became part of the agreements in 2002, Cyprus, Malta, Estonia, Latvia, Lithuania, Poland, Czech Republic, Slovakia, Slovenia, Hungary (EU8) in 2006, Bulgaria and Romania in 2009 and Croatia in 2016. However, the efficacy of the agreements was limited through quotas and other controls until 2007 for the EU15, EFTA states, Cyprus and Malta, until 2011 for the EU8 while it is still constrained for Bulgaria, Romania and Croatia. Furthermore, in 2013 limitations were extended to all countries after the results of the popular initiative (in the context of Swiss direct democracy this procedure allows citizens to propose modifications to the Federal Constitution).
 
9
RGDP per capita is used instead of wage as illustrated in the theoretical model (Sect. 2.) due to the lack of available data.
 
10
This choice prevents the inclusion in the model of time-dummies.
 
11
The Population module of FAOSTAT contains time series data on population, including urban, rural, labour force, agricultural and economically active population. The original sources of the series are:
  • World Population Prospects: The 2012 Revision from the UN Population Division.
  • World Urbanization Prospects: The 2011 Revision from the UN Population Division. Long term series estimates and projections from 1961 to 2050.
  • Economically active population from the ILO and the data refers to the 5th edition, revision 2009. Long term series estimates and projections from 1980 to 2020.
 
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Metadaten
Titel
A spatio-temporal analysis of migration
verfasst von
Alice Milivinti
Publikationsdatum
25.06.2018
Verlag
Springer Berlin Heidelberg
Erschienen in
Empirical Economics / Ausgabe 4/2019
Print ISSN: 0377-7332
Elektronische ISSN: 1435-8921
DOI
https://doi.org/10.1007/s00181-018-1514-8

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