Farms are highly heterogeneous and never identical. No two farms are ever alike in terms of (1) the basic resources, land, labour, or capital that are available, (2) the way these resources or factors of production are combined, or (3) in terms of the amounts of various crops and livestock produced. There are numerous factors that influence the price of a farm and some of these factors are not monetary related. This makes the task of the valuer complex, and it increases the possibility of large differences in the estimated market value determined and the actual selling price.
The development and use of AVM (Automated Valuation Method) models in the valuation of especially residential property, is a worldwide phenomenon. The majority of AVM models use MRA (Multiple Regression Analysis) as a basis. The accuracy of a MRA relies heavily on the quality and accuracy of the data that are used. Thus, the availability of quality and accurate data has a significant impact on the potential accuracy of a MRA.
Accurate MRA valuation estimates will be fair to individual farm owners regarding their municipal tax assessments and it will lead to a wider use of MRAs for the valuation of farms, with the associated benefits of lower valuation costs and speedier valuations, especially by financial institutions.
This study analyses the unique and distinctive attributes of farms, which must be taken into account when a MRA model is developed. By following a stepwise regression approach, a regression model is developed which is fairly accurate, but it does not achieve a high level of accuracy.
Furthermore, the results of the study show that it is difficult to have enough appropriate and accurate data available to develop a regression analysis for agricultural property to satisfy accuracy requirements. Although it is difficult, it is possible to develop MRA models that are fairly accurate. Therefore, if MRA models are currently used for the municipal valuation of farms, which are not fairly accurate, it should be possible to improve the accuracy. However, maximum accuracy cannot be achieved with MRA models. Thus, it cannot replace a valuation done by a skilled and knowledgeable professional valuer, when maximum accuracy is required.