Publication: A stochastic approach for quantifying immigrant integration: the Spanish test case
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2014-10-24
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IOP Publishing
Abstract
We apply stochastic process theory to the analysis of immigrant integration.
Using a unique and detailed data set from Spain, we study the relationship
between local immigrant density and two social and two economic immigration
quantifiers for the period 1999–2010. As opposed to the classic time-series
approach, by letting immigrant density play the role of ‘time’ and the quantifier
the role of ‘space,’ it becomes possible to analyse the behavior of the quantifiers
by means of continuous time random walks. Two classes of results are then
obtained. First, we show that social integration quantifiers evolve following
diffusion law, while the evolution of economic quantifiers exhibits ballistic
dynamics. Second, we make predictions of best- and worst-case scenarios taking
into account large local fluctuations. Our stochastic process approach to integration
lends itself to interesting forecasting scenarios which, in the hands of
policy makers, have the potential to improve political responses to integration
problems. For instance, estimating the standard first-passage time and maximum-span walk reveals local differences in integration performance for
different immigration scenarios. Thus, by recognizing the importance of local
fluctuations around national means, this research constitutes an important tool to
assess the impact of immigration phenomena on municipal budgets and to set up
solid multi-ethnic plans at the municipal level as immigration pressures build
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Keywords
Continuous time random walks, Quantitative sociology, Immigration theories, Random-walks
Bibliographic citation
Agliari, E., Barra, A., Contucci, P., Sandell, R., & Vernia, C. (2014). A stochastic approach for quantifying immigrant integration: the Spanish test case. New Journal of Physics,16 (10), p. 103034.