Claire Mosnier

On-Farm Weather Risk Management in Suckler Cow Farms: A Recursive Discrete Stochastic Programming Approach

The 4.3 million French suckler cows represent more than one third of all European suckler cows and supply around 60% of the beef production in France. They also participate in rural development, as few economic alternatives to livestock farming exist in these production areas and they help in maintaining large areas under grassland which favors biodiversity and limits pollution and erosion (Le Goffe 2003), even if their complete environmental impact should be taken into account (FAO 2006). However, these farms rely on grassland production which is very sensitive to weather conditions (Gateau et al. 2006). Currently the EU and France are thinking at introducing a risk management framework into their agricultural policy. Since farmers individual risk-management strategies can supplement or replace public compensation policies and private insurance, they have to be well understood. Farm risk management aims at profitably securing and improving farms potential of profit over time. It encompasses two stages. The first one, prior to the realisation of a random event, deals with the mitigation of future risks of loss. The second stage, subsequent to the realisation of this uncertain event, corresponds to decisions adjustments in order to take advantage or to limit damages caused by the random event. These two stages are interlinked since first stage decisions can reduce for instance farm exposure or increase adjustments capacity.

Self-insurance and multi-peril grassland crop insurance: the case of French suckler cow farms

Purpose - – From the perspectives of the probable replacement of the national calamity funds by multi-peril grassland insurance, the purpose of this paper is to estimate demand for grassland production insurance. Design/methodology/approach - – A discrete stochastic programming model with a three-year planning horizon was used to run simulations for farms raising suckler cows primarily with grasslands. In this model, the annual area insured and some production decisions are optimized under grasland yield uncertainty, with possible ex post production-system adjustments. The effects of insurance loading cost (14 levels), insurance coverage level (three levels), risk aversion (two levels) and stock levels (forage and animal stocks vary according to grassland yields and to farm management of the previous years) were analyzed. Findings - – The results show that grassland insurance could be used as a flexible risk management tool, when farm becomes vulnerable to fodder shortfall. According to previous years’ grassland yields and to the subsequent states of hay stock and animal liveweight, the area insured could vary between nearly the none and full. Farmers with low-average stocking rate and important hay storage capacity have less incentive to buy grassland insurance. The author also demonstrates that for a given loading cost, more insurance is purchased at a coverage level of 70 percent of average yield than at higher coverage levels. The cost of self-insurance increases for important and rare losses while multi-peril grassland insurance premium decreases. Higher levels of risk aversion also raise the quantity of insurance subscribed. Eventually, insurance price is a key factor. Almost no insurance is bought for loading costs greater than 1.1 under low-risk aversion and for loading costs greater than 1.3 under moderate risk aversion. Research limitations/implications - – The willingness to pay for insurance could have been overestimated for different reasons. First, basis risks have not been introduced in the simulation framework. Although the Forage Production Index performed quite well, basis risks are high enough to trigger inappropriate indemnifications in some cases. Consequences of these risks should be estimated in further research. Second, other self-insurance options and public emergency measures such as subsidized loan or reduction in social security contributions should also be considered to assess and reduce farmers vulnerability to risks. Practical implications - – The launching of the multi-peril grassland insurance is likely to be successful thanks to the 65 percent of public subsidies on insurance premiuml. However, considering that the loading cost is likely to be high and that demand for grassland production insurance is rather low, multi-peril grassland production insurance may struggle to continue unsubsidized. Originality/value - – This paper provides a framework that enables to estimate demand for grassland production insurance factoring in substitution with self-insurance and taking into account successive risks.

Three decades of productivity change in French beef production: a Färe-Primont index decomposition

The Fare‐Primont index is used to evaluate total factor productivity (TFP) change and its components for a sample of French suckler cow farms in grassland areas in 1985–2014. The results reveal an increase in TFP of 6.6 per cent over the whole observation period, with technological progress being the major source of productivity growth. Meanwhile, efficiency decreased. Farms experienced great technological progress from 1991 to 2000. From a methodological point of view, the comparison with results obtained with Malmquist indexes shows similar trends but different magnitudes, with the Malmquist index overestimating the TFP and technological changes compared to the Fare‐Primont index. In addition, the use of a sequential approach that restricts technological change to being positive or null allows for the precise calculation of technology changes, disregarding the effects of external conditions that are captured in efficiency changes. Finally, the estimation of full dimensional efficient facets (FDEFs) that guarantees the positivity of all shadow prices used to assess the mix efficiency component of TFP change is promising.