An analysis of the use of mass appraisal methods for agricultural properties - Van der Walt, Kobus; Boshoff, Douw (University of the Free State, 2017)
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 increases the possibility of large differences in the estimated market value determined and the actual selling price. This article reports the results of a study that analysed the unique and distinctive attributes of farms, in order to determine whether it is possible to develop a linear multiple regression model for the valuation of farms (which satisfies accuracy requirements) with reasonably available data. The improvement of accuracy levels of Multiple Regression Analysis (MRA) models as well as the limitations of using these MRA models during farm evaluations was also studied. By following a stepwise regression approach, 60 farms, primarily located in the eco-zone “mixed bushveld” western area of the Limpopo province, were analysed using ten independent variables. Three models have been developed. The results showed that a fairly accurate regression model could be developed. However, a model that achieves a high level of accuracy could not be developed, due to multifaceted reasons, including non-farm factors and the size of the geographical areas. Accurate MRA valuation estimates will be to the advantage of individual farm owners regarding their municipal tax assessments. It will lead to a wider use of MRAs for the valuation of farms, but great circumspect should be taken when using MRA models in farm valuations. This is due to the possibility that the MRA models do not satisfy minimum accuracy requirements. It is difficult, but possible, to develop a fairly accurate MRA model for the valuation of farms. Therefore, if currently used MRA models are not fairly accurate for municipal valuation purposes, it should be possible to improve the accuracy. Further research is recommended in the use of other regression techniques such as non-linear, geographic weighted regression and quantile regression. These other techniques would, however, require a larger data sample, in order to provide meaningful results.

Daar is veelvuldige faktore wat die prys van ’n plaas beïnvloed, wat nie noodwendig suiwer finansieël van aard is nie. Dit maak die taak van die waardeerder moeilik en kompleks, wat weer veroorsaak dat die moontlikheid bestaan dat daar groot verskille tussen die gewaardeerde waardes en die verkooppryse van plase voorkom. Hierdie artikel rapporteer die resultate van ’n studie wat die unieke en onderskeidende eienskappe van plase ontleed ten einde te bepaal of dit moontlik is om ’n liniêre regressie-analiese model te ontwikkel (wat aan minimum akkuraatheidsvlakke voldoen) met redelik beskikbare inligting, vir die waardasie van plase. Die verbetering van die akkuraatheidsvlakke van MRAmodelle sowel as die beperkings van hierdie MRA-modelle, vir gebruik in plaas waardasies, is ook nagevors. Deur middel van ’n stapsgewyse regressie-analiese metode, is 60 plase wat hoofsaaklik in die “gemengde bosveld” ekosone, in die westelike gedeelte van die Limpopo-provinsie geleë is, ontleed deur van 10 onafhanklike veranderlikes gebruik te maak. Drie modelle is ontwikkel. Die resultate het aangetoon dat ’n regressiemodel ontwikkel kan word wat redelik akkuraat is, maar ’n model met ’n hoë mate van akkuraatheid kon nie ontwikkel word nie as gevolg van veelvuldige redes, insluitend redes wat nie direk verwant is aan plaasfaktore nie en die grootte van die geografiese gebiede. Alhoewel akkurate MRA-waardasies tot voordeel sal wees van plaas eienaars vir die bepaling van munisipale belastingwaardes en dit sal lei tot ’n wyer en meer algemene gebruik van MRA’s vir plaaswaardasies, moet groot versigtigheid aan die dag gelê word met die gebruik van MRA-modelle in plaaswaardasies omdat dit waarskynlik is dat die MRA-modelle nie aan minimum akkuraatheidvereistes voldoen nie. Dit is moeilik, tog moontlik, om ’n MRA-model vir plaaswaardasies te ontwikkel wat redelik akkuraat is. Dus, waar MRA-modelle vir munisipale waardasies gebruik word, wat nie redelik akkuraat is nie, behoort die akkuraatheid verhoog te kan word. ’n MRA-modelwaardasie sal egter nooit die waardasie van ’n ervare en kundige professionele waardeerder kan vervang, wanneer ’n maksimale akkurate waardasie benodig word nie.
Keywords: Argitectural property; Automated Valuation Methodology (AVM); Farm valuation; Mass appraisal; Valuation methodology