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Spatial Discrete Choice Models: A Review Focused on Specification, Estimation and Health Economics applications

Author

Listed:
  • Giuseppe Arbia

    () (Catholic University of the Sacred Heart, Rome, Department of Statistical Science)

  • Anna Gloria Billé

    () (Free University of Bozen-Bolzano, Faculty of Economics and Management)

Abstract

Modeling individual choices is one of the main aim in microeconometrics. Discrete choice models have been widely used to describe economic agents' utility functions, and most of them play a paramount role in applied health economics. On the other hand, spatial econometrics collects a series of econometric tools which are particularly useful when we deal with spatially-distributed data sets. It has been demonstrated that accounting for spatial dependence can avoid inconsistency problems of the commonly used estimators. However, the complex structure of spatial dependence in most of the nonlinear models still precludes a large diffusion of these spatial techniques. The purpose of this paper is then twofold. The former is to review the main methodological problems and their different solutions in spatial discrete choice modeling as they have appeared in the econometric literature. The latter is to review their applications to health issues, especially in the last few years, by highlighting at least two main reasons why spatial discrete neighboring effects should be considered and then suggesting possible future lines of the development of this emerging field.

Suggested Citation

  • Giuseppe Arbia & Anna Gloria Billé, 2018. "Spatial Discrete Choice Models: A Review Focused on Specification, Estimation and Health Economics applications," BEMPS - Bozen Economics & Management Paper Series BEMPS54, Faculty of Economics and Management at the Free University of Bozen.
  • Handle: RePEc:bzn:wpaper:bemps54
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    File URL: http://pro1.unibz.it/projects/economics/repec/bemps54.pdf
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    Keywords

    Discrete Choice Modeling; Health Economics; Spatial Econometrics;

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • I10 - Health, Education, and Welfare - - Health - - - General

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