Spatial interaction models with individual-level data for explaining labor flows and developing local labor markets

DOI10.1016/j.csda.2012.08.016zbMath1365.62464OpenAlexW2007565311MaRDI QIDQ2361204

Yanyan Li

Publication date: 30 June 2017

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2012.08.016

zbMATH Keywords

Markov chain Monte Carloconditionally autoregressive modelsBayesian hierarchical modelingspatial partitioningapproximate block diagonalizationorigin-destination models

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Inference from spatial processes (62M30) Bayesian inference (62F15) Economic time series analysis (91B84)

Related Items (2)

Local labour markets delineation: an approach based on evolutionary algorithms and classification methods ⋮ Welfare gains of the poor: An endogenous Bayesian approach with spatial random effects

Uses Software

• spBayes
• Algorithm 447

Cites Work

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• Model choice: a minimum posterior predictive loss approach
• Mixed-integer quadratic programming
• Introduction to Stochastic Search and Optimization
• Bayesian Measures of Model Complexity and Fit

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