Australian Journal of Agricultural and Resource Economics

We review the basic principles for the evaluation of design efficiency in discrete choice modelling with a focus on efficiency of WTP estimates from the multinomial logit model. The discussion is developed under the realistic assumption that researchers can plausibly define a prior belief on the range of values for the utility coefficients. D‐, A‐, B‐, S‐ and C‐errors are compared as measures of design performance in applied studies and their rationale is discussed. An empirical example based on the generation and comparison of fifteen separate designs from a common set of assumptions illustrates the relevant considerations to the context of non‐market valuation, with particular emphasis placed on C‐efficiency. Conclusions are drawn for the practice of reporting in non‐market valuation and for future work on design research.

Economic development for remote Indigenous communities cannot be understood unless the relative importance of customary activity, potentially enhanced by native title legal rights in resources, is recognised. The present article uses a three‐sector hybrid economy framework, rather than the usual two‐sector private (or market) and public (or state) model to more accurately depict the Indigenous economy. Examples are provided of the actual and potential significance of the customary sector of the hybrid economy. Focusing on the concepts of property and institutions, it is demonstrated that significant local, regional, and national benefits are generated by the Indigenous hybrid economy. A role is foreshadowed for resource economists and the New Institutional Economics in quantifying these benefits, including positive externalities, so that they might be more actively supported by the state.

Although the benefits of organic farming are already well known, the conversion to organic farming does not proceed as the Dutch government expected. In order to investigate the conversion decisions of Dutch arable farms, a discrete stochastic dynamic utility‐efficient programming (DUEP) model is developed with special attention for yield and price risk of conventional, conversion and organic crops. The model maximizes the expected utility of the farmer depending on the farmer’s risk attitude. The DUEP model is an extension of a dynamic linear programming model that maximized the labour income of conversion from conventional to organic farming over a 10 year planning horizon. The DUEP model was used to model a typical farm for the central clay region in the Netherlands. The results show that for a risk‐neutral farmer it is optimal to convert to organic farming. However, for a more risk‐averse farmer it is only optimal to fully convert if policy incentives are applied such as taxes on pesticides or subsidies on conversion, or if the market for the organic products becomes more stable.

In this paper, we generalise the constant market shares (CMS) framework, with particular attention to the underlying theoretical conditions required for diagnostic interpretation. The approach is applied to the analysis of the export performance of the Australian processed food sector in South‐East Asia over the period 1980–2003. We conclude that the usefulness of CMS analysis for evaluating a country's international trade performance depends upon the empirical validity of the aggregation assumptions implicit in the diagnostic interpretation.

We review and implement a reversible jump approach to Bayesian model averaging for the Probit model with uncertain regressors. Two applications are investigated. The first is the adoption of organic systems in UK farming, and the second is the influence of farm and farmer characteristics on the use of a computer on the farm. While there is a correspondence between the conclusions we would obtain with and without model averaging results, we find important differences, particularly in smaller samples. Concerning the adoption of an organic system, we find that attitudes to the sustainability of the current system along with the ability of organic farms alone to satisfy society’s needs for food are influential. Additionally, the source of management information used by the farmer has a significant impact. Regarding the adoption of computers, we confirm the findings of previous work that the level of education affects uptake and that age is a factor determining adoption. We also find that dairy and organic farms are more likely to use a computer. The physical size of the farm is positively associated with the probability of computer use while net farm income has a limited impact.