Stricter cross-compliance standards in Switzerland: Economic and environmental impacts at farm- and sector-level

A Swiss popular initiative reflecting large public concerns about the negative environmental impacts of agricultural production launched a proposal to rigorously tighten environmental cross-compliance standards. The so-called drinking water initiative (DWI) proposes restricting direct payments to farms that (1) preserve biodiversity, (2) do not use any pesticides, (3) adapt their livestock to their on-farm feed capacity and (4) do not use antibiotics regularly or prophylactically. Based on the recursive-dynamic, agent-based agricultural sector model SWISSland, we assessed, ex-ante, the impacts of the initiative on environmental and economic indicators at the farm- and sector-level. Stakeholders from both groups, supporters and opponents of the initiative, were involved in the assessment. We found that the incorporation of far more stringent environmental standards into the cross-compliance system caused a larger number of farms to opt-out: For 33–63% of the pork and poultry farms and 51–93% of the vegetable/orchards/winery farms, it was more profitable to forego direct payments. However, the majority of the ruminant farms (87%) were expected to comply with the standards. Although the non-complying farm types were associated with the most severe environmental impacts, we found that the initiative nonetheless had positive effects on water quality at the sectoral level in Switzerland: e.g., the share of pesticide-free arable land increased to 70–92%, those of the permanent cropland to 11–52%, and the nitrogen surplus decreased. However, the total agricultural production measured in calories decreased (12–21%), and therefore agricultural imports would increase. If the current direct payment budget goes completely to the complying farms, and if these farms receive a price premium, then we predict an average farm income increase of 2–34% for the complying farms; otherwise, a decrease of 6–22% will be found depending on the scenario. A sensitivity analysis showed that price uncertainties had the highest impact on farm income.