Published February 28, 2022 | Version v3
Dataset Open

Modeling local variations in intermarriage [Data set & Code]

  • 1. Universitat Autònoma de Barcelona
  • 2. Universidad Autónoma de Madrid

Description

Dataset accompanying the publication "Modeling local variations in intermarriage". We utilized all Spanish marriage records available at the municipality level from 2005-2007 to model spatial variations in intermarriage. We constructed a spatial regime zero inflated Poisson model and grouped-data probit model, with spatially lagged regressors, to predict the absolute and relative presence of intermarriage between Spaniards and migrants based on structural characteristics of the local marriage markets and their neighboring areas (i.e., relative group size, homogeneity of national origins, and sex ratio indicators). Our models do not assume collapsibility of the marriage market. Instead, they incorporate the local dimension of the marriage mar-ket and examine the association between intermarriage and structural variables at the spatial lo-cal level. The model also investigates intermarriage variation by size of place. The local characteristics of the marriage markets are robust indicators of both the absolute and relative importance of intermarriage, but their impact varies by size of municipality. The relative size of the migrant community positively impacts intermarriage. The homogeneity of the origins of migrants is negatively related to it. The impact of sex ratios in the migrant and native communities on intermarriage is not uniform across all municipalities and is not always related to more intermarriage.

Methods

Spatial regime Zero Inflated Poisson model and Grouped-data Probit model

Other

How to cite the database (APA style): Esteve A, Chasco C, López-Gay A. (2022) Modeling Local Variations in Intermarriage [Data set & Code]. (doi: https://doi.org/10.23728/b2share.36129082d0884c039a266767dd3675a1) Source: Esteve A, Chasco C, López-Gay A. (2022) Modeling Local Variations in Intermarriage. Mathematics 10(7):1106. https://doi.org/10.3390/math10071106

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Additional details

Identifiers

b2rec
36129082d0884c039a266767dd3675a1

Funding

GLOBFAM project, Ministerio de Ciencia e Innovación de España, grant number RTI2018-096730-B-I00
CERCA Programme, Generalitat de Catalunya
Talent Programme, Universitat Autònoma de Barcelona
es-MyData project, Comunidad de Madrid