Designing a property tax without property values: Analysis in the case of Ireland. ESRI WP352. September 2010

Tol, Richard S.J. and Mayor, Karen and Lyons, Sean (2010) Designing a property tax without property values: Analysis in the case of Ireland. ESRI WP352. September 2010. [Working Paper]

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Abstract

We examine the implications of using hedonic regressions of house values as the basis for property tax assessment in the Republic of Ireland. Ad valorem property taxes are more equitable than flat rate taxes, but their equity benefits can be reduced if the relative values of dwellings are inaccurately assessed. Achieving greater accuracy in assessment tends to increase administrative costs, so policymakers face a trade-off between cost and accuracy. Using the Irish National Survey of Housing Quality of 2002, this study analyses the contribution that information about selected property characteristics can make to determine the relative values of residential properties in Ireland. These characteristics are the location of the dwelling, house size in square meters, the number of rooms and bedrooms in the home, the age of the house and the type of dwelling. The values of residential properties are estimated using these variables in turn and the prediction errors are presented in terms of the absolute value error and the assessment ratio (the estimated value divided by the market value). We find that it is possible to assign approximately 80% of houses nationally within the correct tax valuation band using just one of five house characteristics. Households whose house price is under assessed tend to be those with the greatest means (highly skilled professionals and high income earners), so a tax assessment system based on this type of valuation would tend to make regressive errors (while a property tax itself is regressive too). Consequently, checks would need to be put in place in order to more accurately estimate very highly priced properties as well as introducing exemptions for lower value properties and low income groups. The system could also be used to identify likely misreporting if using a self-assessment system.

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