Income-tested health entitlements: microsimulation modelling using SILC

Callan, T., Colgan, B., Keane, C., Logue, C. and Walsh, J., 2018. Income-tested health entitlements: microsimulation modelling using SILC. Journal of the Statistical and Social Inquiry Society of Ireland, XLVI, pp. 97-109. ISSN 0081-4776

[img]
Preview
Text
1235140_Logue.pdf - Published version

Download (427kB) | Preview

Abstract

The application of microsimulation techniques to tax and welfare policies is well established in many countries, including Ireland. The richness of the data contained in SILC, the CSO’s Survey on Income and Living Conditions, means that similar methods can also be applied to the analysis of policy in some other key areas. Income-tested health entitlements, which include most medical cards and many GP visit cards, are a major feature of the Irish health system. We examine how the income tests for such schemes can be modelled using the detailed income and demographic information in the CSO Survey on Income and Living Conditions. The ESRI’s SWITCH model is extended to apply the rules for income-related cards to each family in this nationally representative sample. A key issue which emerges is the apparently low level of take up among those entitled to GP visit cards. This has implications for the costing of policy changes, such as a shift to Universal Health Insurance (UHI) or widening of the age bands qualifying for non-income tested GP visit cards.

Item Type: Journal article
Publication Title: Journal of the Statistical and Social Inquiry Society of Ireland
Creators: Callan, T., Colgan, B., Keane, C., Logue, C. and Walsh, J.
Publisher: Statistical and Social Inquiry Society of Ireland
Date: 12 January 2018
Volume: XLVI
ISSN: 0081-4776
Identifiers:
NumberType
1235140Other
Divisions: Schools > Nottingham Business School
Depositing User: Jonathan Gallacher
Date Added: 15 Nov 2019 11:01
Last Modified: 15 Nov 2019 11:01
Related URLs:
URI: http://irep.ntu.ac.uk/id/eprint/38309

Actions (login required)

Edit View Edit View

Views

Views per month over past year

Downloads

Downloads per month over past year