Abstracts of communications: Proceedings of the thirty-nineth meeting of the Agricultural Research Modellers' Group

This group, which is concerned with the applications of mathematics to agricultural science, was formed in 1970 and has since met at approximately yearly intervals in London for one-day meetings. The thirty-ninth meeting of the group, chaired by Professor N. Crout of the University of Nottingham, was held in the Kohn Centre at the Royal Society, 6 Carlton House Terrace, London on Friday, 30 March 2007 when the following papers were read.

Curbing agricultural exceptionalism: The EU's response to external challenge

From 1948 to 1994, the agricultural sector was afforded special treatment in the GATT. We analyse the extent to which this agricultural exceptionalism was curbed as a result of the GATT Uruguay Round Agreement on Agriculture, discuss why it was curbed and finally explore the implication of this for EU policy making. We argue that, in particular, two major changes in GATT institutions brought about restrictions on agricultural exceptionalism. First, the Uruguay Round was a 'single undertaking' in which progress on other dossiers was contingent upon an outcome on agriculture. The EU had keenly supported this new decision rule in the GATT. Within the EU this led to the MacSharry reforms of the Common Agricultural Policy (CAP) in 1992, paving the way for a trade agreement on agriculture within the GATT. Second, under the new quasi-judicial dispute settlement procedure, countries are expected to bring their policies into conformity with WTO rules or face retaliatory trade sanctions. This has brought about a greater willingness on the part of the EU to submit its farm policy to WTO disciplines.

Ideational change in the WTO and its impacts on EU agricultural policy institutions and the CAP

This paper argues that the Uruguay Round Agreement on Agriculture (URAA) introduced the market liberal paradigm as the ideational underpinning of the new farm trade regime. Though the immediate consequences in terms of limitations on agricultural support and protection were very modest, the Agreement did impact on the way in which domestic farm policy evolves. It forced EU agricultural policy makers to consider the agricultural negotiations when reforming the Common Agricultural Policy (CAP). The new paradigm in global farm trade resulted in a process of institutional layering in which concerns raised in the World Trade Organization (WTO) were gradually incorporated in EU agricultural institutions. This has resulted in gradual reform of the CAP in which policy instruments have been changed in order to make the CAP more WTO compatible. The underlying paradigm, the state-assisted paradigm, has been sustained though it has been rephrased by introducing the concept of multifunctionality.

The visibility of agricultural subsidies and market illusions in the Common Agricultural Policy: Some evidence from farmers' views in Germany, Portugal and the United Kingdom

This article demonstrates that the design and nature of agricultural support schemes has an influence on farmers' perception of their level of dependence on agricultural support. While direct aid payments inform farmers about the extent to which they are subsidised, indirect support mechanisms veil the level of subsidisation, and therefore they are not fully aware of the extent to which they are supported. To test this hypothesis, we applied data from a survey of 4,500 farmers in three countries: the United Kingdom, Germany and Portugal. It is demonstrated that indirect support, such as that provided through artificially high consumer prices, gives an illusion of free and competitive markets among farmers. This 'visibility' hypothesis is evaluated against an alternative hypothesis that assumes farmers have complete, or at least a fairly comprehensive level of, information on agricultural support schemes. Our findings show that this alternative hypothesis can be ruled out.

Translating climate forecasts into agricultural terms: advances and challenges

Seasonal climate prediction offers the potential to anticipate variations in crop production early enough to adjust critical decisions. Until recently, interest in exploiting seasonal forecasts from dynamic climate models (e.g. general circulation models, GCMs) for applications that involve crop simulation models has been hampered by the difference in spatial and temporal scale of GCMs and crop models, and by the dynamic, nonlinear relationship between meteorological variables and crop response. Although GCMs simulate the atmosphere on a sub-daily time step, their coarse spatial resolution and resulting distortion of day-to-day variability limits the use of their daily output. Crop models have used daily GCM output with some success by either calibrating simulated yields or correcting the daily rainfall output of the GCM to approximate the statistical properties of historic observations. Stochastic weather generators are used to disaggregate seasonal forecasts either by adjusting input parameters in a manner that captures the predictable components of climate, or by constraining synthetic weather sequences to match predicted values. Predicting crop yields, simulated with historic weather data, as a statistical function of seasonal climatic predictors, eliminates the need for daily weather data conditioned on the forecast, but must often address poor statistical properties of the crop-climate relationship. Most of the work on using crop simulation with seasonal climate forecasts has employed historic analogs based on categorical ENSO indices. Other methods based on classification of predictors or weather types can provide daily weather inputs to crop models conditioned on forecasts. Advances in climate-based crop forecasting in the coming decade are likely to include more robust evaluation of the methods reviewed here, dynamically embedding crop models within climate models to account for crop influence on regional climate, enhanced use of remote sensing, and research in the emerging area of 'weather within climate'.

Translating climate forecasts into agricultural terms: advances and challenges

Seasonal climate prediction offers the potential to anticipate variations in crop production early enough to adjust critical decisions. Until recently, interest in exploiting seasonal forecasts from dynamic climate models (e.g. general circulation models, GCMs) for applications that involve crop simulation models has been hampered by the difference in spatial and temporal scale of GCMs and crop models, and by the dynamic, nonlinear relationship between meteorological variables and crop response. Although GCMs simulate the atmosphere on a sub-daily time step, their coarse spatial resolution and resulting distortion of day-to-day variability limits the use of their daily output. Crop models have used daily GCM output with some success by either calibrating simulated yields or correcting the daily rainfall output of the GCM to approximate the statistical properties of historic observations. Stochastic weather generators are used to disaggregate seasonal forecasts either by adjusting input parameters in a manner that captures the predictable components of climate, or by constraining synthetic weather sequences to match predicted values. Predicting crop yields, simulated with historic weather data, as a statistical function of seasonal climatic predictors, eliminates the need for daily weather data conditioned on the forecast, but must often address poor statistical properties of the crop-climate relationship. Most of the work on using crop simulation with seasonal climate forecasts has employed historic analogs based on categorical ENSO indices. Other methods based on classification of predictors or weather types can provide daily weather inputs to crop models conditioned on forecasts. Advances in climate-based crop forecasting in the coming decade are likely to include more robust evaluation of the methods reviewed here, dynamically embedding crop models within climate models to account for crop influence on regional climate, enhanced use of remote sensing, and research in the emerging area of 'weather within climate'.

Assessing the impact of the 'Decoupling' reform of the common agricultural policy on Irish farmers' off-farm labour market participation decisions

This paper assesses the impact of the 'decoupling' reform of the Common Agricultural Policy on the labour allocation decisions of Irish farmers. The agricultural household decision-making model provides the conceptual and theoretical framework to examine the interaction between government subsidies and farmers' time allocation decisions. The relationship postulated is that 'decoupling' of agricultural support from production would probably result in a decline in the return to farm labour but it would also lead to an increase in household wealth. The effect of these factors on how farmers allocate their time is tested empirically using labour participation and labour supply models. The models developed are sufficiently general for application elsewhere. The main findings for the Irish situation are that the decoupling of direct payments is likely to increase the probability of farmers participating in the off-farm employment market and that the amount of time allocated to off-farm work will increase.