Improving Land Valuation Models in Sparse Markets: A Comparison of Spatial Interpolation Techniques in Mass Appraisal

Paul Bidanset, Michael McCord, PT Davis, William McCluskey

Research output: Contribution to conferencePaperpeer-review

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The research in this working paper has set up the groundwork for a national AVM of Malawi, Africa, using only secondary data collected by the 2010-2011 Integrated Household Survey. Model variables include physical characteristics of the property, economic variables, as well as location-specific distance and climate variables. This paper additionally helps bridge the current gap in development property tax literature by evaluating response surface analysis (RSA) at a national level, specifically with respect to technical standards of the International Association of Assessing Officers (IAAO). Our initial research shows that variables with positive effects on perception of value include agricultural plot size and estimated annual income (rental) potential. Plots situated further from agrimarkets and auction locations are perceived to be less valuable. Negative effects are associated with sandy soil, higher average annual rainfall, moderate to steep slopes, and plots situated in swamps or marshlands. The ordinary kriging-based predictions, while seemingly less likely to overestimate perceived value, are more regressive. Ordinary kriging achieves superior scores of vertical equity, but inferior scores of uniformity when compared to a current OLS model with location factor adjustment variables derived from RSA
Original languageEnglish
Publication statusPublished (in print/issue) - 20 Mar 2017
EventWorld Bank Land & Poverty Conference: Responsible Land Governance—Towards an Evidence-Based Approach - World Bank HQ, Washington DC, United States
Duration: 20 Mar 201724 Mar 2017


ConferenceWorld Bank Land & Poverty Conference
Country/TerritoryUnited States
CityWashington DC
Internet address


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