Insights into land size and productivity in Ethiopia: What do data and heterogenous analysis reveal?

This study investigates whether the historical inverse relationship (IR) between land (farm and plot) size and productivity holds for Ethiopia farms. The study uses plot-level and household-level data from the three waves of the Ethiopia Socioeconomic Survey. The main finding, which confirms previous studies, is that the plot-size IR holds when productivity measurement is based on self-reported yields. However, the effects were reversed when we used crop-cut yields. Including labor inputs significantly reduces the magnitude of the coefficients on land size but not the sign. Finally, the quantile regression reveals interesting findings. These are: (1) a strong positive effect of farm (and plot) size on productivity; (2) the magnitude of the effect decreases monotonically with quantile; (3) farm size displays a robust negative impact on gross revenue and the magnitude of the effect increases (in absolute terms) monotonically with quantiles; (4) the effect of farm (and plot) size on productivity decreases in magnitude when we control for labor input; (5) the IR between farm (and plot) size and total and family labor was negative and significant and the effect increases (in absolute terms) monotonically with quantiles.

A generic bio-economic farm model for environmental and economic assessment of agricultural systems

Bio-economic farm models are tools to evaluate ex-post or to assess ex-ante the impact of policy and technology change on agriculture, economics and environment. Recently, various BEFMs have been developed, often for one purpose or location, but hardly any of these models are re-used later for other purposes or locations. The Farm System Simulator (FSSIM) provides a generic framework enabling the application of BEFMs under various situations and for different purposes (generating supply response functions and detailed regional or farm type assessments). FSSIM is set up as a component-based framework with components representing farmer objectives, risk, calibration, policies, current activities, alternative activities and different types of activities (e.g., annual and perennial cropping and livestock). The generic nature of FSSIM is evaluated using five criteria by examining its applications. FSSIM has been applied for different climate zones and soil types (criterion 1) and to a range of different farm types (criterion 2) with different specializations, intensities and sizes. In most applications FSSIM has been used to assess the effects of policy changes and in two applications to assess the impact of technological innovations (criterion 3). In the various applications, different data sources, level of detail (e.g., criterion 4) and model configurations have been used. FSSIM has been linked to an economic and several biophysical models (criterion 5). The model is available for applications to other conditions and research issues, and it is open to be further tested and to be extended with new components, indicators or linkages to other models.

Modelling Common Agricultural Policy-Water Framework Directive interactions and cost-effectiveness of measures to reduce nitrogen pollution

Selecting cost-effective measures to regulate agricultural water pollution to conform to the Water Framework Directive presents multiple challenges. A bio-economic modelling approach is presented that has been used to explore the water quality and economic effects of the 2003 Common Agricultural Policy Reform and to assess the cost-effectiveness of input quotas and emission standards against nitrate leaching, in a representative case study catchment in Scotland. The approach combines a biophysical model (NDICEA) with a mathematical programming model (FSSIM-MP). The results indicate only small changes due to the Reform, with the main changes in farmers' decision making and the associated economic and water quality indicators depending on crop price changes, and suggest the use of target fertilisation in relation to crop and soil requirements, as opposed to measures targeting farm total or average nitrogen use.