Abstract. We extend Sklyanin's method of separation of variables to quantum integrable models associated to elliptic curves. After reviewing the differential case, the elliptic Gaudin model studied by Enriquez, Feigin and Rubtsov, we consider the difference case and find a class of transfer matrices whose eigenvalue problem can be solved by separation of variables. These transfer matrices are associated to representations of the elliptic quantum group E τ,η (sl 2 ) by difference operators. One model of statistical mechanics to which this method applies is the IRF model with antiperiodic boundary conditions. The eigenvalues of the transfer matrix are given as solutions of a system of quadratic equations in a space of higher order theta functions.

Investing in larger barns and increasing herd size are crucial milestones in dairy production. Based on the Swiss Farm Accountancy Data Network and data on government-supported investments, we investigate the development of two key variables over the first eight years after investment: change in herd size and calculated profit, that is, farm income minus opportunity costs for family labour and capital. We apply a fixed-effects panel regression and test for autocorrelation present in the time series. Compared to the year before the investment, calculated profit decreases in the first three years, while in the remaining years no significant difference compared to the year before investment can be seen. Herd size increases slowly, predominantly in the second and third years after investment, to some extent explaining the less favourable development of profitability in these years. We conclude that investment in a dairy barn does not lead to improved profitability in the short and medium term, pointing to the question of whether this picture changes in the long term.<br />

Purpose The purpose of this paper is to propose a novel way of determining optimal capital structure, applied to sub-groups of Swiss dairy farms from 2003 to 2014. Optimization of capital structure is carried out with respect to two performance indicators from an economic value added perspective. Design/methodology/approach Optimal values of capital structure are obtained based on a minimization of correlation between economic performance indicators and a distance function of the debt-to-asset ratio distribution to its quantiles. The approach differs from existing approaches in relying solely on empirical data and in using fewer external parameters, which are difficult to estimate, such as risk aversion coefficients. An unbalanced panel data set from the Swiss Farm Accounting Network with almost 14,000 dairy farm observations serves as input data to the model. Findings Concise optimal values of capital structure result for regional and temporal sub-groups of Swiss dairy farms. Comparing the evolution of optimal values for these sub-groups with existing models of optimal capital structure, the authors infer that dairy farmers in the mountain region are less risk averse than their counterparts in the valley region and that falling interest rates increase the optimal value of debt-to-asset ratio. Originality/value The straightforward computation of optimal values for capital structure without intermediate parameters is useful and new. In addition, the authors’ model can be used as a tool for comparison and validation of previous models with the same aim, e.g. for comparison of risk aversion coefficients or qualitative behavior of optimal values for capital structure.

This paper analyzes the factors that influence the economic success of Swiss dairy farms, as measured by the annual income per family work unit, using panel data regression techniques. Based on more than 5,400 farm-year observations, the main focus of the analysis concerns the milk yield per cow and year as the key explanatory variable, which can be adjusted by the farm manager in the medium term. We apply both a random effects model and a quantile regression based on deciles, which allows us to study the heterogeneity of the sample in greater detail. Consistent with the current literature, the random effects model shows the positive contribution of the milk yield, namely an additional 1,000 kg/cow results in an increase of CHF 2,660; that is, 6% of the annual income. The quantile regression reveals that the effect of the milk yield differs between deciles, with a high milk yield being most beneficial for the best-performing farms, accounting for up to CHF 7,210 per 1,000 kg (where CHF1 = €0.86 = $1.01). Our analysis further shows the influence of the milk yield on profitability to be highly heterogeneous among Swiss dairy farms, indicating business-specific extension services and not suggesting the requirement for an increased milk yield at each level of economic success.

We analysed the adjustment phase following a dairy shed investment. On the basis of farm observations from both the Swiss Farm Accountancy Data Network (FADN) and a database of government-supported investments from 2003 through 2014, we focused on the imputed profit, the farm income minus opportunity costs for family labour and family capital. After investment, the analysed farms needed three years to return to the same profit level as that before the investment (median value). A Cox proportional-hazards model (survival analysis) showed that the probability of reattaining the imputed profit increased with equity capital. A reduction of the probability was related to a high imputed profit, a high off-farm income, high expenses for purchased animals and, in particular, a greater use of family labour before the investment. We conclude that the use of family labour after investment should be addressed more thoroughly during the planning process prior to an investment.