Gains and structural effects of exploiting scale-economies in Norwegian dairy production

In this paper, we present calculations of the economic gains in terms of reduced costs by exploiting scale‐economies in dairy production in Norway, and the effect this would have had on the number of farms. We also explore whether or not optimal scale and unexploited scale‐economies change over time due to scale‐augmenting technical change. The analysis is based on homothetic cost functions estimated by means of data for individual dairy farms for the period 1972–1996. For 1972, we find that, by full exploitation of scale‐economies, the costs could have been reduced by almost 40%, while the number of farms would have been reduced by more than 85%. The number of small farms has been substantially reduced in the period considered. This fact, combined with small scale‐augmenting technical change, implies that the gains and structural effects of exploiting scale‐economies have decreased over time. In 1996, costs could have been reduced by close to 30% by full exploitation of scale‐economies, while the number of farms would have been reduced by slightly more than 70%. Thus, both gains and structural effects are substantially less than in 1972. Nevertheless, the calculated gains for 1996 make almost 5 billion NOK. This corresponds almost exactly to the total public support to the dairy farms in 1996. The unexploited scale‐economies are largely due to the agricultural policy. Thus, a substantial share of the same can be considered as part of the‘price’ the Norwegian society has to pay for this policy. In addition, there are likely to be large hidden costs of this policy due in particular to the quota system and other direct production regulations. They imply that technical innovations and other efficiency‐improving investments requiring increased production to be profitable are not carried out. This is the more likely explanation for the extremely poor efficiency development in Norwegian dairy production in the period studied.     

Enhancing productivity on suburban dairy farms in China

Dairy farms in China's suburban areas have been playing an important role in providing urban markets with fresh milk. With the rising demand for fluid milk and dairy products in the cities, there is a perception that small and scattered dairy farms in China's provinces are gradually disappearing and more concentrated dairy cattle farming is being formed near suburban areas. This article uses farm‐level survey data and stochastic input distance functions to make estimates of total factor productivity (TFP) on suburban dairy farms, as well as for the entire dairy sector. The results show that over the past decade TFP growth has been positive on suburban dairy farms, and this rise in productivity has been driven mostly by technological change. However, at the same time we find that, on average, the same farms have been falling behind the advancing technical frontier. We also find one of the drivers of the suburban dairy sector is the relatively robust rate of technological change of these farms, which has been more rapid than on farms in the dairy sector as a whole. The results suggest that efforts to achieve greater adoption of new technologies and better advice on how to use the technologies and manage production and marketing within the suburban dairy sector will further advance productivity growth in the sector.     

Small U.S. dairy farms: can they compete?

The U.S. dairy industry is undergoing rapid structural change, evolving from a structure including many small farmers in the Upper Midwest and Northeast to one that includes very large farms in new production regions. Small farms are struggling to retain competitiveness via improved management and low‐input systems. Using data from USDA's Agricultural Resource Management Survey, we determine the extent of U.S. conventional and pasture‐based milk production during 2003–2007, and estimate net returns, scale efficiency, and technical efficiency associated with the systems across different operation sizes. We compare the financial performance of small conventional and pasture‐based producers with one another and with large‐scale producers. A stochastic production frontier is used to analyze performance over the period for conventional and pasture technologies identified using a binomial logit model. Large conventional farms generally outperformed smaller farms using most economic measures—technical efficiency, various profitability measures, and returns to scale.     

水产养殖业新型农业经营主体全要素生产率研究——基于微观主体面板数据和SFA法

目的 新型农业经营主体是推动农业现代化发展的重要力量,研究其生产效率及变化趋势、分析比较不同类型新型农业经营主体的效率对于推进农业高质量发展、促进乡村振兴具有重要意义。方法 文章聚焦水产养殖领域,基于2018—2021年全国429个养殖生产新型农业经营主体样本面板数据,采用随机前沿生产函数分析了全要素生产率（TFP）,并分解其驱动因素。采用共同随机前沿模型比较分析了龙头企业、农民专业合作社和家庭农场3类新型农业经营主体模式的生产技术效率。结果 （1）增加物质资料、劳动力、固定资产等方面的投入对产出增长有显著促进作用,但增加服务投入并未显著促进产出。（2）TFP增长的动力来源是技术进步,规模报酬率的贡献不大,而技术效率和配置效率的下降对TFP增长起到阻碍作用。（3）龙头企业、合作社、家庭农场3类新型农业经营主体的技术效率各有特点,以群组前沿面为基准时家庭农场的技术效率最高,以共同前沿面为基准时合作社的技术效率最高,以技术差距比表征的技术水平衡量,则龙头企业技术水平最高。结论 建议加强科技投入,提升技术效率,优化成本投入结构,加强各类新型农业经营主体的联合与合作。     

Specialization,diversification, and productivity: a panel data analysis of rice farms in Korea

This article examines the microeconomics of productivity associated with specialization/diversification in production activities, with an application to Korean rice farms. Korean rice farms tend to be very small and highly specialized. Our analysis examines the productivity effects associated with both farm size and farm specialization/diversification in Korean agriculture. Relying on farm‐level panel data, the analysis studies farm productivity in a multi‐input multi‐output context, accounting not only for changes in inputs and technical change in rice production, but also for the role of diversification in the production of other crops in current and previous periods. We find positive but small productivity gains from farm diversification. These gains come mostly from complementarity effects across farm outputs, with minimal effect of scale economies. The positive complementarity effects work against nonconvexity effects, which provide strong productivity incentives for rice farms to specialize.     

Decomposition of output growth in the Tunisian olive-growing sector: A frontier production function approach

The aim of this paper is to investigate the relative contribution of technical efficiency, technological change, and increased input use to the output growth of the Tunisian olive oil growing farms, using a stochastic frontier production function approach applied to panel data for the period 1995-1997. The proposed methodology is based on the use of a flexible translog functional form. Results indicate that technical efficiency of production in the sample of olive producing farms investigated ranges from a minimum of 24.8% to a maximum of 84.6% with an average technical efficiency estimate of 48.5%. This suggests that olive producers may increase their production by as much as 51.5% through more efficient use of production inputs. Further, the production is characterized by decreasing returns to scale, which on average was 0.8. Finally, investigation of the sources of production growth reveals that the contribution of conventional inputs (labor, in particular) and technical change are found to be the main source of that growth, since total factor productivity increased during the study period, but at a slowing rate.     

Estimating Farm Productivity Differentials using Panel Data: The Hausman‐Taylor Approach

This paper investigates the relation between unobserved farm productivity and other production factors in a system of netput equations for specialised pig breeding farms in the Netherlands. In order to estimate the system, a Hausman‐Taylor panel data estimator is developed for a system of equations with unbalanced panel data. Tests on the correlation between model variables and farm‐effects are performed, yielding an insight into the sources of differences in total factor productivity and its components (e.g. managerial ability and scale economies). Results indicate that specialised pig breeding farms that are characterised by high total factor productivity have more buildings and machinery than farms with low total factor productivity.     

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.     

Productivity Growth in German Dairy Farming using a Flexible Modelling Approach

A random‐coefficients specification of an output distance function is used to measure and decompose productivity growth in German dairy farming. This specification can accommodate heterogeneity with respect to the technology employed by dairy farms, allowing for specialised and non‐specialised farms to be included in the analysis. The proposed modelling approach is favoured by the data when compared with the conventional translog specification of distance functions. The average total factor productivity growth rate for German dairy farms is estimated at 1.1%, with the technical progress component contributing most of this growth.     

Total factor productivity change in hog production and Quebec's revenue insurance program

Quebec's hog industry is supported by a revenue insurance program that guarantees a minimum price, but it also faces strict environmental constraints. Under price volatility, risk-averse farms may contract their output enough to produce under increasing returns. We show that the subsidy and downside risk reduction effects of the revenue insurance program tend to stimulate output and increase the likelihood of production under increasing returns. Environmental constraints that raise the cost of manure management and limit areas under cultivation also increase the likelihood of decreasing returns. Scale efficiency and technical efficiency measures are obtained through a parametric decomposition of total factor productivity (TFP) obtained from the estimation of an output distance function. As in hog studies pertaining to other countries, we found a TFP average annual growth of 5.2% between 2004 and 2012. Scale efficiency is much lower than in other countries, as per our prior about the program's distortions and environmental constraints. Integrating annual TFP gains into the setting of the minimum guaranteed price could reduce program costs by $12 million per year. About $70–80 million per year could be saved by investing in extension activities that would bring increase the level of technical efficiency of inefficient farms to the provincial average. A metatechnology frontier approach allowing for an endogenous input was also implemented to assess the robustness of the scale efficiency results.     

On the nature and magnitude of cost economies in hog production

In this article, we assess the impact of farm size on production cost and evaluate the marginal costs and margins by considering that input prices may change with the scale of production. By using French hog farm data, we estimate a system of equations including a feed price function, input demand functions, and an output supply function based on a technology approximated by a combined generalized Leontief‐Quadratic form. Our results suggest that the marginal costs are over‐estimated when the adjustment of the feed unit prices to a change in farm size is not controlled for. More specifically, the cost economies for large farms (enjoying the highest profits) arise primarily from lower feed prices, with technological scale economies having little impact. In contrast, farms with no hired labor exhibit technological scale economies and reach higher price‐cost margins compared to larger farms.     

Input Substitution,Productivity Performance and Farm Size

This paper develops a theoretical model to examine the relationship between the input elasticity of (technical) substitution and both farm total factor productivity and size. In the presence of ongoing technical change and its factor bias, the ‘income effect’ arising from farms' cost minimising behaviour enables them to increase productivity by saving inputs or, through the dual equivalent, enlarging farm size. As such, farms with higher elasticities of substitution tend to grow larger and become more productive, which provides a new mechanism through which farm heterogeneity in productivity growth can be examined. Empirical evidence from Australian broadacre agriculture supports this theory and points to important policy implications.     

Feed use intensification and technical efficiency of dairy farms in New Zealand

In recent years, the traditionally pasture‐based dairy farms in New Zealand have become more intensive by using higher proportions of supplementary feed. This trend has been attributed to a range of factors, such as productivity enhancement, overcoming pasture deficits and the improvement of body condition scores. However, there is a lack of knowledge as to how feed use intensification affects the technical efficiency of dairy farms in New Zealand. This paper addresses the research gap by estimating the impact of feed use intensification on the technical efficiency of New Zealand dairy farms, using a fixed effects stochastic production frontier model and a balanced panel of 257 farms from 2010 to 2013. The empirical results show that technical efficiency on New Zealand dairy farms is positively and significantly influenced by feed use intensification, herd size and milking frequency.     

Technology and efficiency in a panel of Italian dairy farms: an SGM restricted cost function approach

This article employs a short‐term specification of the symmetric generalised McFadden (SGM) cost function capable of accommodating quasi‐fixed factors and variable returns. Temporary equilibrium and scale economies are investigated while maintaining the consistency of the estimated model with microeconomic theory and approximation properties. It also makes use of a two‐step procedure to estimate first the technology parameters and then time‐varying efficiency at farm level. No distributional assumptions are required on efficiency as we consider a fixed effect model. A balanced panel of Italian dairy farms during the years from 1980 to 1992 serves as the case study. The results suggest a rigid productive structure during the pre‐ and post‐quota period. Moreover, Italian milk producers are found to exhibit considerable excess capacity and rather low input technical efficiency.     

Technology choice and efficiency on Australian dairy farms*

Deregulation of the Australian dairy industry, specifically the removal of price subsidies to ‘market milk’, as well as ongoing drought in many dairy regions, has placed considerable pressure on farm cash income and a search for ways in which dairy farms can be made to operate more efficiently. Using traditional farm survey data and a unique biannual data set on farm technology use, this paper estimates a stochastic production frontier and technical efficiency model for dairy farms in New South Wales and Victoria, determining the relative importance of each input in dairy production, the effects of key technology variables on farm efficiency, and overall farm profiles based on the efficiency rankings of dairy producers. Results show that production exhibits constant returns to scale and although feed concentration and the number of cows milked at peak season matter, the key determinants of differences in dairy farm efficiency are the type of dairy shed used and the proportion of irrigated farm area. Overall farm profiles indicate that those in the ‘high efficiency group’ largely employ either rotary or swing‐over dairy shed technology and have almost three times the proportional amount of land under irrigation.     

典型家庭农场组织化程度对生产效率的影响分析

现阶段中国农业生产仍属于高投入、低效率的粗放模式,粮食安全缺乏可持续性。研究不同规模下不同组织形式的家庭农场生产效率,有助于揭示在中国农业高质量发展阶段中通过转变农业经营组织形式提高粮食生产效率,保障国家粮食安全的新路径。本文利用湖北武汉、安徽郎溪等地家庭农场的问卷调查数据,采用三阶段DEA方法比较纯种植与种养结合两类典型家庭农场的全要素生产率和水稻生产效率差异,并探讨农业生产效率的影响因素和水稻的适度经营规模。结果显示,家庭农场的全要素生产率和水稻生产效率都有较大的提升空间。不论是全要素生产率、水稻生产效率还是要素投入效率,种养结合农场总体高于纯种植农场。随着经营规模的扩大,种养结合农场中合理组织化对水稻生产效率的提升作用超过了纯种植农场中的专业化作用,其具有高单产、少物耗、轻污染、低成本、抗风险等优点,充分符合国家的"藏粮于技"战略,应受到积极鼓励和广泛推广。经营规模扩张对家庭农场生产效率的影响作用较为复杂,并不完全是线性的,应基于家庭和生产实际,合理确定家庭农场经营规模,走适度规模经营之路。     

Evaluating research and education performance in Indian agricultural development

India's agricultural research spending has long been regionally uneven. Regional research intensity ratios, which account for size differences, indicate research spending has consistently favored southern and western states over northern, central, and eastern ones. Farm production patterns have, however, changed in recent years and regional output growth is being driven by new commodity mixes. In this article, we ask which region had the highest factor productivity growth and rate of return to investments in public agricultural research and higher education. Our analysis relies on a 1980–2008 Indian agricultural production and policy data set together with a dual heteroscedastic production frontier to decompose total factor productivity (TFP) growth into formal technical progress and efficiency elements. The model's regional flexibility affords region‐to‐region comparison of multiple research return rates, TFP growth, and the elements influencing them. Regardless of return‐rate measure or allocation scenario evaluated, the North has enjoyed the highest return to research spending, and the Central and East the lowest. Factor productivity growth has however been strongest in the South, primarily on account of efficiency gains. Overall, though, the technical progress and productivity growth easily attributable to government‐supported research has accounted for about one‐quarter of the sector's TFP growth.     

Broadacre farm productivity and profitability in south‐western Australia

This paper examines broadacre farm performance in south‐western Australia. This region has experienced pronounced climate variability and volatile commodity prices since the late 1990s. Relationships between productivity and profitability are explored using panel data from 47 farms in the study region. The data are analysed using nonparametric methods. By applying the Fare‐Primont index method, components of farm productivity and profitability are measured over the period 1998–2008. Growth in productivity is found to be the main contributor of profitability. Gains in efficiency and technical change are identified as jointly and similarly important in their contribution to total factor productivity for the farm sample in the region from 1998 to 2008. However, across environments, efficiency gains play an increasingly important role in influencing productivity as growing season rainfall increases. We conclude that R,D&E that delivers further improvement in technical efficiency and technical change is needed to support the profitability of farms across the study region.     

Decomposition of Productivity Growth Using Distance Functions: The Case of Dairy Farms in Three European Countries

Within an output distance function framework, the Total Factor Productivity growth index is decomposed into four components (technical change, technical and allocative efficiency, and scale component). We estimate stochastic translog output distance functions using panel data from dairy farms over the period 1991–94 for three European countries (Germany, the Netherlands, and Poland). Results indicate that the change in the productivity growth index in Germany (+6%) and Poland (−5%) are mainly dictated by the technical change component. In contrast, the productivity growth index in the Netherlands (+3%) is influenced by allocative efficiency components.