Determinants of Property Valuation Errors
The literature identifies several determinants of property valuation errors. However, in the main, these can be categorized into errors occasioned by the state of the property market, valuation models and assumptions, quantity and quality of market data, and heuristic behavior of valuers or behavioral factors (Iroham, Ogunba, and Oloyede, 2014). A core issue in property valuation is valuers’ ability to interpret the property market correctly in their quest to assign value (Brown, 1992). Consequently, when there are doubts or uncertainties associated with the property market or misreading of the market by valuers, there is the likelihood that errors will occur (Matysiak and Wang, 1995). In their studies of the correspondence between valuations and subsequent prices in the UK, for example, Matysiak and Wang (1995) came to the conclusion that valuations tend to lag behind market prices during periods of rising markets, while they are usually above market prices in times of falling markets.
As stated previously, valuation is not a precise science. However, they rely on scientific processes and methods and are expected to be carried out in a methodical manner using the appropriate basis, set of assumptions, and methodology (Crosby, Lavers, and Murdoch, 1998).This requires understanding on the part of valuers as to clarity of instruction and purpose of valuation. It also requires valuers to undertake meticulous referencing of the subject matter of valuation—undertaking an inspection of the property to take inventory of its details, including its nature and complexity, checking the root of title and other encumbrances among other things, and employing the right basis of valuation, assumptions, and methodology. Without such a methodical approach, valuations are more likely to be engulfed in errors (Olawore et al., 2011). Indeed, Bretten and Wyatt (2001) in their study in the UK established that valuation models or methodologies have influence on valuation errors, while valuation of complex properties comparatively is more prone to errors.
Closely aligned with the state of the property market is availability of market data, such as evidence of sales and lettings of similar properties. Not only should data be adequate, it also needs to be of good quality (Olawore et ah, 2011). Matysiak and Wang (1995) point out that inadequate market transactions or data are a recipe for property valuation errors. Brown (1992) also opines that valuations are a function of information. The better the information set, the better the valuation. Ratcliff (1968),, cited in Brown (1992, p.200), further states that:
The prediction of value is no different than any other economic forecast. It is a prediction of human behaviour conditioned by a combination of dynamic known and unknown factors. It can never be predicted as a certainty and in some cases, the degree of uncertainty is high. Certainty of prediction is a function of the adequacy of the information on which the prediction is based and the skill and competence of the analyst.
Clearly, adequacy of information is paramount to good valuations and without it, errors are bound to occur. Peto (1997) acknowledges this view and makes the point that availability of market information should be seen from two standpoints: provision of accurate and timely data on transactions; and availability of data series and valuations to allow forecasting and modeling. To this end, several studies such as Peto (1997), Wyatt (1997), and Dunse et al. (1998) have been conducted in the developed world to improve property market data access and management for valuation purposes.
Behavioral factors—heuristic behaviors of valuers, including anchoring—have been identified as one of the causes of property valuation errors. Although research into this genre of causes of property valuation errors is fairly recent, it continues to receive attention and has become one of the topical areas in property research (Bretten and Wyatt, 2001; Iroham, Ogunba, and Oloyede, 2014). These heuristic behaviors encompass the use of simplifying short-cut means or rules of thumb developed over time to make value judgments and client pressures that influence value judgments. Iroham, Ogunba, and Oloyede (2014) identify four main heuristic behaviors. These are availability, representative, anchoring and adjustment, and positive heuristics. The availability heuristics are based on the experience decision-makers—in this instance, valuers—have had in the past with regard to solving the situation or problem at hand. This means that the strategy or solution that worked in the past is bound to be followed. The representative heuristics are more in the category of stereotyping, while anchoring and adjustment heuristics have to do with valuers making a priori judgments as to an estimate of value and then beginning to adjust the value as new information trickles in. The positive heuristics relate to valuers finding sets of data or information or design strategies to support their estimate of values rather than falsifying them.