AbstractTo meet their climate policy obligations towards the EU, some EU member states will have to adopt strict climate policies towards agriculture. Responding to this need, the Danish parliament recently decided to impose a tax on greenhouse gas (GHG) emissions from the country's livestock production. We develop a simple model of primary agriculture and its interaction with the food industry to illustrate the main economic mechanisms determining the impact of a unilateral tax on GHG emissions from domestic agriculture. To study the allocation effects of the GHG tax on agriculture and the impact on the wider economy over time, we then present a disaggregated dynamic simulation model of Danish agriculture, embedded in a large‐scale computable general equilibrium model. The model predicts that a large share of the cost increase induced by the tax will be shifted forward onto higher input prices in the food industry and ultimately onto consumers via higher food prices, but landowners will also bear a significant part of the burden through a fall in land prices. The GHG tax will induce a reallocation from animal to plant production, which would be even more pronounced in the case of a livestock‐specific tax as currently foreseen, and from conventional to organic farming. This will help to reduce the total emissions from agriculture, but the largest share of the emission cuts will stem from a fall in output, as there are still few low‐cost technical abatement possibilities in agriculture.

AbstractLimiting the impact of climate change on agriculture is a major goal of the European Union. This requires the evaluation of farm‐level adaptation measures, available within the Common Agricultural Policy. We investigate how the adoption of soil conservation measures by farms in Austrian arable regions affects their economic performance. By applying an endogenous switching regression model to panel data, we find that climatic conditions significantly influence the decision on whether to adopt soil conservation measures. The net revenue of adopters is less sensitive to long‐term temperature and precipitation changes than for non‐adopters. The measures are profitable for a majority of farms. However, profitability is linked to baseline climatic conditions, with negative effects in cool, wet regions and significantly greater positive effects in warm, dry regions.

AbstractIn light of the urgent need for farms to mitigate greenhouse gas emissions while maintaining economic viability, this paper analyses technical and environmental inefficiencies and their determinants based on a flexible multi‐equation by‐production stochastic frontier model, which accounts for the stochastic dependence between good and bad outputs via a copula function. An empirical application to Dutch dairy farms illustrates the distortions in the inefficiency scores and in the estimates of their determinants that occur when the dependence between good and bad outputs is ignored. The empirical results indicate a strong positive dependence between the good output (milk) and the bad output (methane emissions), which is particularly pronounced in the upper tail of the distribution. Notably, farms exhibit high efficiency in maximising their good output and minimising their bad output. Subsidies are negatively related to good output inefficiency but positively related to bad output inefficiency, while stock density exhibits a negative association with inefficiencies in both outputs. Disregarding output dependence leads to distortions in inefficiency estimates, particularly affecting the estimates for their determinants.

AbstractRainfall index insurance can enable farm households to manage production risk, but demand in developing countries remains low at market prices, in part because the insurance trigger may not correlate well with individual farm losses. Area‐yield crop insurance, which links payouts to average yield in a geographic zone, attempts to increase demand by more accurately targeting insurance payouts to production shortfalls. However, shifting from an exogenous weather‐based to an endogenous yield‐based index introduces concerns of asymmetric information, which can lead to market failures that constrain supply from providers. These features are inversely related: larger insurance zones inhibit index manipulation, but average yield is less informative about any individual plot. We quantify this tradeoff for maize in Ghana using a spatial yield model calibrated to match observed production. Insurers must demarcate zones of no more than 5000 farmers for area‐yield insurance to outperform weather insurance. The framework presented in this paper allows assessment of the relationship between index performance and asymmetric information in new crop insurance products.

AbstractThis study empirically analyses the effect of agricultural commercialisation on food spending and nutrition outcomes in Bangladesh. We examine whether exposure to exogenous climate shocks moderates these relationships. We construct individual‐level nutrition measures and time‐varying climate extremes using nationally representative panel data. To address endogeneity concerns, we use an instrument variable approach. Results show that commercialisation leads to an improvement in the broad nutritional profile of individuals. However, the commercialisation–nutrition linkage is weaker for households exposed to frequent climate shocks than those in climate‐resilient areas. Importantly, climate shocks dampen the positive nutritional impacts of commercialisation and exacerbate existing inequalities in the nutritional status within the households. Women and girls appear disproportionately vulnerable to the nutrition‐weakening effects of weather stresses in commercialised agricultural households. This highlights twin policy challenges: strengthening smallholders' resilience to escalating climate risks alongside promoting gender‐equitable, nutrition‐sensitive agricultural commercialisation.