Understanding the Impact of the Property Tax Appeal Process on Assessment Uniformity: Procedures, Structures, and Outcomes

Property taxes serve as a vital revenue source for local governments. The revenues derived from the property tax function as the primary funding source for a variety of critical local public service systems. Property tax appeal systems serve as quasi-administrative-judicial mechanisms intended to assure the public that property tax assessments are correct, fair, and equitable. Despite these important functions, there is a paucity of empirical research related to property tax appeal systems. This study contributes to property tax literature by identifying who participates in the property tax appeal process and examining their motivations for participation. In addition, the study sought to determine whether patterns of use and success in appeal systems affected the distribution of the tax burden. Data were collected by means of a survey distributed to single-family property owners from two Florida counties. In addition, state and county documents were analyzed to determine appeal patterns and examine the impact on assessment uniformity, over a three-year period. The survey data provided contextual evidence that single-family property owners are not as troubled by property taxes as they are by the conduct of local government officials. The analyses of the decision to appeal indicated that more expensive properties and properties excluded from initial uniformity analyses were more likely to be appealed, while properties with homestead exemptions were less likely to be appealed. The value change analyses indicated that appeals are clustered in certain geographical areas; however, these areas do not always experience a greater percentage of the value changes. Interestingly, professional representation did not increase the probability of obtaining a reduction in value. Other relationships between the variables were discovered, but often with weak predictive ability. Findings from the assessment uniformity analyses were also interesting. The results indicated that the appeals mechanisms in both counties improved assessment uniformity. On average, appealed properties exhibited greater horizontal and vertical inequities, as compared to non-appealed properties, prior to the appeals process. After, the appeal process was completed; the indicators of horizontal and vertical equity were largely improved. However, there were some indications of regressivity in the final year of the study.

Forecasting enrollment in differential assessment programs using cellular automata

Urban growth models have been used for decades to forecast urban development in metropolitan areas. Since the 1990s cellular automata, with simple computational rules and an explicitly spatial architecture, have been heavily utilized in this endeavor. One such cellular-automata-based model, SLEUTH, has been successfully applied around the world to better understand and forecast not only urban growth but also other forms of land-use and land-cover change, but like other models must be fed important information about which particular lands in the modeled area are available for development. Some of these lands are in categories for the purpose of excluding urban growth that are difficult to quantify since their function is dictated by policy. One such category includes voluntary differential assessment programs, whereby farmers agree not to develop their lands in exchange for significant tax breaks. Since they are voluntary, today’s excluded lands may be available for development at some point in the future. Mapping the shifting mosaic of parcels that are enrolled in such programs allows this information to be used in modeling and forecasting. In this study, we added information about California’s Williamson Act into SLEUTH’s excluded layer for Tulare County. Assumptions about the voluntary differential assessments were used to create a sophisticated excluded layer that was fed into SLEUTH’s urban growth forecasting routine. The results demonstrate not only a successful execution of this method but also yielded high goodness-of-fit metrics for both the calibration of enrollment termination as well as the urban growth modeling itself.