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Spatial structures of health outcomes and health behaviours in Scotland: Evidence from the Scottish Health Survey

Author Info

  • Arnab Bhattacharjee

    (Heriot-Watt University)

  • Taps Maiti

    (Michigan State University)

  • Dennis Petrie

    (University of Melbourne)

Abstract

Socioeconomic characteristics, health behaviours, and the utilisation and quality of healthcare are prime examples of socioeconomic, cultural and demographic phenomena that are inherently spatial in nature. Understanding the spatial structure of these factors is particularly relevant in order to efficiently allocate resources. This paper explores the general equilibrium spatial structure of health outcomes and health behaviours across Scottish health boards using a variant of the spatial Durbin model which allows for an a priori unknown spatial weights matrix. The results suggest that there is substantial spatial dynamics in behaviours across Health Boards and that these spillovers are, as expected, asymmetric. We then demonstrate how the model can be used to estimate the behavioural and health impact of a targeted education policy within each health board taking into account both the direct effect on the particular health board itself and the indirect effect in terms of spillovers. The results illustrate how the dynamic effects play a large role in designing place based policies that maximise the overall effectiveness of health interventions. Taking into account the spatial dynamics allows policy makers to better target resources and interventions on particular clusters where the direct and indirect spillover benefits are likely to be the greatest in terms of improving health.

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Paper provided by Spatial Economics and Econometrics Centre, Heriot Watt University in its series SEEC Discussion Papers with number 1401.

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Date of creation: 2014
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Handle: RePEc:hwe:seecdp:1401
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Keywords: spatial econometrics; spatial weights matrix; spatial Durbin model; health outcomes; health behaviours; health care utilisation;

Find related papers by JEL classification:

  • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
  • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
  • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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Cited by:

  1. Eibich, Peter & Ziebarth, Nicolas R., 2014. "Examining the structure of spatial health effects in Germany using Hierarchical Bayes Models," Regional Science and Urban Economics, Elsevier, vol. 49(C), pages 305-320.
  2. Eibich, Peter & Ziebarth, Nicolas, 2013. "Examining the Structure of Spatial Health Effects using Hierarchical Bayes Models," Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79844, Verein für Socialpolitik / German Economic Association.

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