Urban Influence on Costs of Production in the Corn Belt

This article determines the relative technical efficiency of rural- and urban-influenced crop/livestock enterprises in the Corn Belt. Farmers in urban-influenced locations are less technically efficient than farmers in rural locations. During 1998–2000, stochastic production frontier procedures indicate that a 10% increase in urban influence leads to a close to 4% decrease in technical efficiency. The most successful urban-influenced farms have controlled costs as effectively as rural farms. They have tended to de-emphasize that nondairy livestock activities—particularly beef and hogs—do not rely extensively on off-farm income, and have relatively large, less residential/lifestyle operations compared to less successful urban-influenced farmers. However, our statistical analysis clearly bears out the refrain in popular literature that urban proximity raises the cost for, and decreases the viability of, traditional farms.     

Sources of productivity growth on Finnish dairy farms—application of an input distance function

The objective is to examine sources of productivity change on Finnish dairy farms in the 1990s. The decomposition of productivity change into technical and technical efficiency change is widely recognized but it neglects the scale effect. Generalized decompositions incorporating all three components are calculated for a sample of Finnish dairy farms from 1989-2000. This period is of interest because of the drastic change in agricultural policy when Finland joined the European Union (EU) in 1995. The results indicate that productivity growth was on average low, approximately 0.15% per year. Neutral technical change was identified as the most important source of productivity growth (1.1%). Technical efficiency decreased by almost 0.5% annually. The contribution of the scale effect in productivity change increased towards the end of study period.     

Do family farms really converge to a uniform size? The role of unobserved farm efficiency*

We analyse the growth of family farms in Israeli cooperative villages during a period of economic turmoil. We use instrumental variables to account for the endogeneity of initial farm size, and correct for selectivity as a result of farm survival. We also include a technical efficiency index, derived from the estimation of a stochastic frontier production model, as an explanatory variable. Our aim is to check whether ignoring efficiency could have been the reason for convergence results obtained elsewhere in the literature. We found that technical efficiency is an important determinant of farm growth, and that not controlling for technical efficiency could seriously bias the results. In particular, larger farms are found to grow faster over time, while without controlling for technical efficiency the farm growth process seemed to be independent of initial farm size. The increasing polarisation of farm sizes in Israel has ramifications for the inefficiencies induced by the historical quota system, for the political power of the farm sector and for the social stability of farm communities.     

How limiting is finance for Dutch dairy farms? A dynamic profit analysis

Accessibility to financial resources is considered a prevalent problem in the agricultural sector. We develop an approach to quantify the long-term opportunity costs of financial constraints in relation to peers who do not face any financial constraints. Using data on past financial performance, we assess creditworthiness and the size of an additional accessible bank loan to farmers. Combining this with data on reported expenditure, we determine the accessible finance. We quantify the opportunity cost as the forgone dynamic profit (intertemporal profit in current-value terms) from financial constraints. Using data envelopment analysis, we apply our approach to 264 specialised Dutch dairy farms for the years 2006–2017 and explore the potential impact of changes in finance provision for several scenarios. Our results show an increasing gap between frontrunners and other farmers, as the latter generate progressively less dynamic profit in comparison to their best peers. The gap between the dynamic profit of the average farm and that of its best peers from their production and investment decisions made over the span of 1 year grew from €40,040 in 2009 to €114,548 in 2017. However, the growth is not driven by insufficient access to finance. Financial constraints can only explain 6% of the forgone dynamic profit in 2009 and as little as 1% for 2017. The number of farms classified as financially constrained in comparison to their peers decreases in our sample from 44% in 2009 to 8% in 2017. This suggests that non-financial factors are driving the growing gap.     

发达地区不同规模家庭农场粮食生产技术效率的实证研究基于上海松江家庭农场的调查

目的 松江在发展家庭农场方面的探索和实践,被认为是可以在我国经济较发达地区推广和复制的“松江模式”。通过对该地区家庭农场粮食生产的技术效率进行实证研究,可以为发达地区家庭农场推进适度规模经营、优化资源配置提供理论依据和政策支持。方法 基于2017年上海市松江区943个家庭农场的问卷调查数据,文章运用随机前沿生产函数模型测算了不同经营规模家庭农场粮食生产的技术效率,并在此基础上运用Tobit模型进一步探究了其影响因素。结果 上海市松江区家庭农场粮食生产的技术效率水平较高,达到0.922 6,且适度中规模家庭农场粮食生产的技术效率最高,家庭农场主的性别、受教育程度、务农年限和经营家庭农场的年限以及家庭农场主的父辈是否经营家庭农场、家庭农场种植制度的选择等对家庭农场粮食生产的技术效率具有显著性影响。结论 对于经济发展水平较高的地区而言,必须坚持以农户家庭经营作为农业生产的基本单位,因地制宜推进家庭农场的适度规模经营,同时,大力发展农机社会化服务,鼓励家庭农场主对稻田进行3年1次轮茬,在改良后的土地上种植二麦。     

Estimation of Profit Functions When Profit is Not Maximum

This paper deals with derivation and implications of profit functions when profit is not maximum due to the presence of either technical inefficiency or allocative inefficiency, or both. We show that input demand and output supply, elasticities, and returns to scale are, in general, affected by these inefficiencies. We also show that the overall profit efficiency is not necessarily the product of technical and allocative efficiencies, meaning that technical and allocative inefficiencies are not necessarily independent. Estimation techniques are developed for both cross-sectional and panel data models. Working of the model is illustrated using a panel of 60 salmon farms.