Current rural valuation practice : a survey of valuers and agribusiness managers on farm management and sustainable rural land use

Over the past 20 years the nature of rural valuation practice has required most rural valuers to undertake studies in both agriculture (farm management) and valuation, especially if carrying out valuation work for financial institutions. The additional farm financial and management information obtained by rural valuers exceeds that level of information required to value commercial, retail and industrial by the capitalisation of net rent/profit valuation method and is very similar to the level of information required for the valuation of commercial and retail property by the Discounted Cash Flow valuation method. On this basis the valuers specialising in rural valuation practice have the necessary skills and information to value rural properties by an income valuation method, which can focus on the long term environmental and economic sustainability of the property being valued. This paper will review the results of an extensive survey carried out by rural property valuers in Australia, in relation to the impact of farm management on rural property values and sustainable rural land use. A particular focus of the research relates to the increased awareness of the problems of rural land degradation in Australia and the subsequent impact such problems have on the productivity of rural land. These problems of sustainable land use have resulted in the need to develop an approach to rural valuation practice that allows the valuer to factor the past management practices on the subject rural property into the actual valuation figure. An analysis of the past farm management and the inclusion of this data into the valuation methodology provides a much more reliable indication of farm sustainable economic value than the existing direct comparison valuation methodology.

Commentary on the article by Swanenburg et al. ‘Validity and reliability of a German version of the Neck Disability Index (NDI-G)’

We commend Swanenburg et al. (2013) on translation, development, and clinimetric analysis of the NDI-G. However, the dual-factor structure with factor analysis and the high level of internal consistency (IC) highlighted in their discussion were not emphasized in the abstract or conclusion. These points may imply some inconsistencies with the final conclusions since determination of stable point estimates with the study's small sample are exceedingly difficult.

An optimal design for screening trials

Yao, Begg, and Livingston (1996, Biometrics 52, 992-1001) considered the optimal group size for testing a series of potentially therapeutic agents to identify a promising one as soon as possible for given error rates. The number of patients to be tested with each agent was fixed as the group size. We consider a sequential design that allows early acceptance and rejection, and we provide an optimal strategy to minimize the sample sizes (patients) required using Markov decision processes. The minimization is under the constraints of the two types (false positive and false negative) of error probabilities, with the Lagrangian multipliers corresponding to the cost parameters for the two types of errors. Numerical studies indicate that there can be a substantial reduction in the number of patients required.