No abstract

The importance of dealing properly with spatial effects, such as spatial autocorrelation, in cross‐sectional econometric estimation has become more widely recognised in recent years. Spatial autocorrelation is similar in many ways to serial correlation, but while the latter is ordered on a one‐dimensional time axis, the former is ordered in two dimensions. The multi‐directional nature of spatial dependence means that specialised techniques are needed for diagnostic testing and estimation purposes. This paper uses these specialised diagnostics to test for spatial effects within a hedonic pricing study of the agricultural land market. The tests indicate that spatial autocorrelation (in the form of spatial lag dependence) and spatially distinct sub‐markets (or spatial heterogeneity) are present. Ignoring these effects in the estimation process is likely to lead to biased parameter estimates. Consequently, we re‐specify the hedonic model to allow for these spatial effects. The presence of spatial lag dependence suggests that there is circularity of price setting within the agricultural land market. This means that agricultural land prices are not solely determined by the inherent characteristics of the land, but tend to reflect also the average local price per acre.

The chaotic distribution and dispersal of phosphorus (P) used in food systems (defined here as disorderly disruptions to the P cycle) is harming our environment beyond acceptable limits. An analysis of P stores and flows across Europe in 2005 showed that high fertiliser P inputs relative to productive outputs was driving low system P efficiency (38 % overall). Regional P imbalance (P surplus) and system P losses were highly correlated to total system P inputs and animal densities, causing unnecessary P accumulation in soils and rivers. Reducing regional P surpluses to zero increased system P efficiency (? 16 %) and decreased total P losses by 35 %, but required a reduction in system P inputs of ca. 40 %, largely as fertiliser. We discuss transdisciplinary and transformative solutions that tackle the P chaos by collective stakeholder actions across the entire food value chain. Lowering system P demand and better regional governance of P resources appear necessary for more efficient and sustainable food systems.

Negative externalities such as nitrogen (N) surplus that accompany dairy production activities are not usually accounted for in the market place since they are not costed. Using a parametric hyperbolic environmental technology distance function approach, we estimate the environmental efficiency and farm-specific abatement costs (shadow price) of nitrogen surplus in dairy farms on the island of Ireland (Northern Ireland and the Republic of Ireland). The methodology, unlike previous approaches (output/input distance functions), allows for asymmetric treatments of production outputs (desirable and undesirable outputs). We also analyse the farm level nitrogen pollution costs ratio and its determinants. The results of our analyses showed that the average environmental technical efficiency estimates for the Republic of Ireland and Northern Ireland are 0.89 and 0.92 and the mean abatement costs per kg of N surplus is €4.02 and €6.2 respectively. We found a reasonable degree of variation in the spectrum of abatement costs across the dairy farms with a relative increase observed over the years.