基于第二次全国R&D资源清查的农业科技资源配置效率分析

[目的]农业科技资源配置效率的高低在一定程度上决定着农业科技系统的运行效率,而农业科技系统的运行效率状况对提高农业科技资源的高效利用、增强农业科技创新能力、加快促进农业现代化进程有着重要的影响。文章基于2009年第二次全国RD资源清查数据,对政府部门属农业科研机构的配置效率进行测算,并分析其规模报酬以便为相关决策部门提供参考。[方法]通过构建农业科技资源配置效率评价的投入产出指标体系,选取包含科技人员、科技经费及科技成果在内的6个投入产出指标,运用数据包络分析方法 (DEA)中的超效率模型测算全国32个省份政府部门属自然科学和技术领域研究机构(含直辖市)的综合效率、纯技术效率、规模效率。[结果]全国农业科研机构科技资源技术效率平均值为0.581,科技运行效率还有较大的提升空间。按机构学科领域分,水产学学科的效率值最高(TE Score=2.867 9);按机构服务的国民经济行业分,渔业的效率值最高(TE Score=1.901 1)。各省(市、区)农、林、牧、渔业农业科研机构的综合运行效率值大于1的有天津、吉林、贵州、宁夏、北京、辽宁。规模效率的平均值是0.686,规模收益递减的省(市、区)占87%。[结论]DEA非效率地区所占比例较大,技术效率低于全国平均值的地区占56%,地区规模效率的提升可以依靠加大科研投入来实现。农业科技资源配置的结构需要进行调整,在合理调控种植业科研机构的发展规模的同时优化其科技人员结构。通过开展农业科技计划绩效评价、组建农业科技创新联盟来促进农业科技协同创新。同时应根据农业科研机构的不同类型提出相应的管理措施,以便实现分类指导和科学管理。     

Modernization of a peasant crop in Colombia: evidence and implications

The survival of the small-farm sector in the process of agricultural modernization in Latin America has been a concern for many authors and institutions. It is generally believed that the small-farm sector is bypassed in the process of agricultural development. The authors analyze modernization of bean/maize cropping systems in Southern Colombia. Prices, production practices and profitability are compared for 1975 and 1989. By means of a production function, the effects of allocative efficiency, technical efficiency and technical change on productivity and profitability are analyzed. The observed changes reflect very well the price trends over the period. Between 1975 and 1989, total factor productivity increased by 50%. Bean/maize producers almost doubled returns to land and labor. Increased technical efficiency had most effect on profitability, followed by technical change. Allocative efficiency had more impact on yields than on profitability because it was associated with high input costs. Considerable opportunities for further productivity increases were identified. Conclusions on the nature of the modernization process are drawn. Implications for agricultural policy, research and the role of the small farm in agricultural development are derived.     

Efficiency estimation in a profit maximising model using flexible production function

This paper uses a flexible (translog) production function to estimate efficiency of 227 farms from West Bengal, India. We consider estimation of technical and allocative inefficiencies using a profit maximising framework which accommodates both endogenous and exogenous inputs. The maximum likelihood method of estimation developed in this paper is based on the production function and the first-order conditions of profit maximisation. Farm-specific technical and allocative inefficiencies are also estimated. Empirical results show that the mean level of technical efficiency is 75.46% while the best farm is 85.87% efficient (technically). So far as allocative efficiency is concerned the majority of the farms are found to be under-users of the endogenous inputs, viz., fertiliser, manure, human and bullock labour.     

RECENT DEVELOPMENTS IN FRONTIER MODELLING AND EFFICIENCY MEASUREMENT

In this paper recent developments in the estimation of frontier functions and the measurement of efficiency are surveyed, and the potential applicability of these methods in agricultural economics is discussed. Frontier production, cost and profit functions are discussed, along with the construction of technical, allocative, scale and overall efficiency measures relative to these estimated frontiers. The two primary methods of frontier estimation, econometric and linear programming, are compared. A survey of recent applications of frontier methods in agriculture is also provided.     

Is Input Mix Inefficiency Neglected in Agriculture? A Case Study of Pig‐based Farming Systems in England and Wales

The principal concern of this article is the relative importance of input mix as a source of inefficiency. Emphasis in efficiency analysis studies in agricultural production has historically focused on technical inefficiency as a single concept until methodological advances enabled it to be decomposed into pure technical inefficiency and scale inefficiency. But, this advance was insufficient to identify what we consider to be the major source of inefficiency in agricultural production, namely mix inefficiency. We consider that farm enterprises may be particularly susceptible to input mix inefficiency because of restrictions on movement around the frontier isoquant; delays in the adoption of improved technologies embodied in new vintages of production processes; risk as a source of friction in input allocation decisions; and the potential for inconsistency in simultaneously attempting to reach points of allocative efficiency and mix efficiency in input use. We use non‐parametric methods to calculate a Hicks–Moorsteen productivity index using panel data for a sample of specialised pig producers in England and Wales. This index is then decomposed into measures of technology, technical efficiency, scale efficiency and mix efficiency for an input orientation. Results of the analysis show that the estimated mean mix inefficiency (0.736) was substantially larger than mean technical inefficiency (0.975) and mean scale inefficiency (0.957) over the study period.     

Technical,allocative and economic efficiencies in swine production in Hawaii: a comparison of parametric and nonparametric approaches

Technical, allocative and economic efficiency measures arc derived for a sample of swine producers in Hawaii using the parametric stochastic efficiency decomposition technique and nonparametric data envelopment analysis (DEA). Efficiency measures obtained from the two frontiei approaches are compared. Firm-specific factors affecting productive efficiencies are also analyzed. Finally, swine producers, potential for reducing cost through improved efficiency is also examined. Under the specification of variable returns to scale (VRS), the mean technical, allocative and economic efficiency indices are 75.9%, 75.8% and 57.1%, respectively, for the parametric approach and 75.9%, 80.3% and 60.3% for DEA; while for the constant returns to scale (CRS) they are 74.5%, 73.9% and 54.7%, respectively, for the parametric approach and 64.3%, 71.4% and 45.7% for DEA. Thus the results from both approaches reveal considerable inefficiencies in swine production in Hawaii. The removal of potential outliers increases the technical efficiencies in the parametric approach anil allocative efficiencies in DEA, but, overall, contrary to popular belief, the results obtained from DEA are found to be more robust than those from the parametric approach. The estimated mean technical and economic efficiencies obtained from the parametric technique are higher than those from DEA for CRS models but quite similar for VRS models, while allocative efficiencies are generally higher in DEA. However, the efficiency rankings of the sample producers based on the two approaches are highly correlated, with the highest correlation being achieved for the technical efficiency rankings under CRS. Based on mean comparison and rank correlation analyses, the return to scale assumption is found to be crucial in assessing the similarities or differences in efficiency measures obtained from the two approaches. Analysis of the role of various firm-specific factors on productive efficiency shows that farm size has strong positive effects on efficiency levels. Similarly, farms producing market hogs arc-more efficient than those producing feeder pigs. Based on these results, by operating at the efficient frontier the sample swine producers would be able to reduce their production costs by 38-46% depending upon the method and returns to scale considered.     

Publicly-funded UK agricultural R&D and 'social' total factor productivity

Most studies concerned with measuring the rate of return to publicly‐funded agricultural R&D investment have found high returns, suggesting under‐investment, and calls for increased expenditure have been common. However, the evaluation of returns tends to measure the effect of research expenditure against growth in total factor productivity (TFP), based on market inputs and outputs. When compared against growing public unease over the environmental effects of pursuing agricultural productivity growth, TFP indices become a misleading measure of growth. This paper integrates some non‐market components into the TFP index. The costs of two specific externalities of agricultural production, namely fertiliser and pesticide pollution, are integrated in a TFP index constructed for the period 1948–1995. This adjusted, or ‘social’, TFP index is measured against UK public R&D expenditures. The rates of return to agricultural R&D are reduced by using the ‘social’ as opposed to the traditional TFP index. Whilst both remain at justifiable levels, previous studies appear to have over‐estimated the effect of agricultural R&D expenditures. Furthermore, with changes in policy towards more socially acceptable but non‐productivity enhancing outcomes, such as animal welfare, rural diversification and organic farming, the future framework for analysing returns to agricultural R&D should not be so dependent on productivity growth as an indicator of research effectiveness.     

Relative efficiency of women as farm managers: Profit function analysis in Côte d'Ivoire

The efficiency of women farmers in the agricultural sector of developing countries is passionately debated. Very few studies have examined this issue in African agriculture. All previous studies were based on production functions, but have been criticised as suffering from simultaneous equation bias because the input levels are endogenous. The profit function method avoids these problems. No previous study has used the profit function method to lest for technical, allocative and economic efficiency differences between women and men farmers. The objective of this paper was to determine whether women rice farmers are less efficient than men rice farmers in Côte d'Ivoire using the restricted normalised profit function method. Our results show that the relative degree of efficiency of women is similar to that of men. The paper provides empirical support for efforts to eliminate bias against women farmers in African agriculture.     

Profit Based Efficiency Measures,with an Application to Rice Production in Southern India

Using non‐parametric methods, we estimate the foregone rents due to credit, allocative, and technical inefficiencies of subsistence farmers in Southern India. The lost rents are estimated directly from the Nerlovian efficiency index, and the results suggest the largest foregone rents derive from allocative inefficiencies and then credit inefficiencies. Also, results suggest that farms without well access experience larger losses than those with well access. Econometric results suggest education, the presence of tank water management efforts, and well access influence the level of foregone rent due to allocative and Nerlovian inefficiencies. Educational activities and policies to encourage better management of tanks are considered important for lowering the foregone losses.     

Economic efficiency in farm households: trends, explanatory factors, and estimation methods

Factors explaining differences in economic efficiency between farms are of major interest to owners, managers, and other stakeholders as they strive to improve earnings and improve the chances of firm survival. This study is undertaken to improve our understanding of interfarm differences in, and opportunities to improve, farm household efficiency in utilizing their land, labor, and capital resources to achieve household objectives. The technical, allocative, and scale efficiencies of farm households are estimated using a nonparametric, output-based data envelopment analysis (DEA) of a panel data set from 1993 to 2006. Single and double bootstrapping procedures are used to estimate technical efficiency. Initial technical efficiency assuming variable returns to scale (TEV) is estimated to be 0.83. Using single bootstrapping, the average bias-corrected TEV estimate is 0.70; using double bootstrapping, the TEV estimate is 0.72. Allocative efficiency is estimated to be 0.81. Scale efficiency is estimated to be 0.93. The only factor that is consistently associated with higher technical efficiency across analysis methods and years is larger farm size (as measured by the log of farm income). The significance of other factors changes with analysis methods.     

Efficiency and technical progress in traditional and modern agriculture: evidence from rice production in China

Productive efficiency for Chinese hybrid and conventional rice production is estimated using a dual stochastic frontier efficiency decomposition model. Results reveal significant differences in technical and allocative efficiency between conventional and hybrid rice production, and indicate significant regional efficiency differences in hybrid rice production, but not in conventional rice production.     

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.     

Linear Input Aggregation Bias in Nonparametric Technical Efficiency Measurement

An attraction of the nonparametric approach to measuring technical efficiency is that no a priori structure is placed on the production process of the firm. However, inputs are typically linearly aggregated, either explicitly or implicitly. It is shown that this introduces bias in the technical efficiency measurement. The computed technical efficiency measure becomes an economic efficiency measure comprised of both technical and allocative efficiency. An empirical application demonstrates the bias.     

基于超效率DEA模型的中国农业科技资源配置效率动态演化研究

[目的]通过测算中国农业科技资源配置效率,分析存在的差异性,为配置效率的提升寻求有效措施。[方法]运用超效率DEA,对2001~2014年间中国31个区域的面板数据进行农业科技资源配置效率的全面评估,从中探究区域农业科技资源配置效率的变动趋势和时空特征,构建Malmquist指数以从技术进步水平和技术效率水平考察影响区域农业科技资源配置效率变动的因素。[结果]中国各地区整体的配置效率呈现上升趋势,超效率平均值从2001年的0.520上升到2014年的0.764;农业全要素生产率平均增长1.3%,其中综合技术效率指数年均增长4.2%、技术进步变化指数年均下降2.8%;从影响农业科技资源配置效率的技术进步和技术效率来看,技术效率已成为主要因素。从细分的6个区域来看,华东地区全要素生产率平均值最高,西北地区最低。从具体省份情况来看,有17个省(市、区)的全要素生产率指数大于1,其中天津、上海、广东、海南全要素生产率增长较快,年均增长率达到10%以上。[结论]提高中国农业科技资源配置效率,可采取优化农业科技资源配置结构,各地根据农业科技资源实际扬长避短、合作共赢,实施农业科技"走出去"战略等措施。     

The extent of resource use inefficiencies in cotton production in Pakistan's Punjab: an application of Data Envelopment Analysis

This paper attempts to identify sources of resource use inefficiency for cotton production in Pakistan's Punjab. The use of a non‐parametric method, Data Envelopment Analysis (DEA), is developed to study the relative technical and allocative efficiencies of individual farms which use similar inputs, produce the same product and operate under comparable circumstances. In the ‘cotton‐wheat’ system of Pakistan, there are a considerable number of farms that are both technically and allocatively inefficient. The use of DEA shows that the technique provides a clear identification of both the extent and the sources of technical and allocative inefficiencies in cotton production. However, both the interpretation of the farm level results generated and the projection of these results to a higher level require care, given the technical nature of the agricultural production processes.     

农地富集区农地经营效率差异及影响因素 ——建档立卡农户与非建档立卡农户比较

研究目的：基于生计资本差异分析东北农地富集区建档立卡农户与非建档立卡农户农地经营效率差异及其影响因素,为巩固脱贫攻坚成果并向乡村振兴有效过渡提供参考。研究方法：DEA模型与Tobit模型。研究结果：（1）研究区农户农地经营效率偏低,建档立卡农户的综合技术效率与纯技术效率均显著低于非建档立卡农户,而农地经营效率差异主要是由二者的纯技术效率差异引起的;（2）建档立卡农户与非建档立卡农户均存在土地与资金投入冗余;（3）在生计资本差异下,样本农户总体、建档立卡农户、非建档立卡农户的农地经营效率主要受人力资本、自然资本、金融资本的影响。研究结论：应注重从农业技术应用、农业生产金融体系建立、新型农业经营主体培育等多方面着手提高农户农地经营效率。     

认定等级差异视角下休闲农业经营主体效率分析——以南京市休闲农业经营主体为例

[目的]在政府大力推进休闲农业发展的背景下,合理测算不同认定等级休闲农业经营主体效率,分析当前认定等级对休闲农业经营主体效率的影响,对于完善现有认定体系、引导休闲农业经营主体效率提升以及促进休闲农业健康可持续发展具有重要作用和意义。[方法]基于2019年南京市72家规模以上休闲农业经营主体调查数据,文章采用数据包络分析法(DEA)方法,兼顾休闲农业经营主体经济效益和社会效益的多重发展目标,更合理、准确地对休闲农业经营主体效率进行测算,分析不同认定等级休闲农业经营主体的效率差异及其成因。[结果]随着休闲农业经营主体认定等级的提高,其综合技术效率、规模效率以及纯技术效率等指标并未同步提高;休闲农业经营主体土地与劳动力投入随着认定等级提高,存在不同程度冗余现象。[结论]建议进一步完善各级各类休闲农业经营主体认定指标体系、政策支持体系与认定类型,同时加强认定观念引导与宣传,通过加强政策引导与资源支持,推进休闲农业主体和休闲农业的健康可持续发展。     

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.     

农业科技园区规划关键技术方法与实证经验

［目的］农业科技园区建设符合乡村振兴战略的发展需求。农业科技园区规划采用的关键技术方法是否规范化对新时期园区规划的前瞻性和科学性具有重要作用。从城乡规划学、地理信息科学、农业科技、环境科学、大数据等多学科交叉角度围绕农业科技园区的规划流程、编制内容、技术方法等过程开展关键技术与方法优化研究,为新时期农业科技园区规划提供新思路和标准范式。［方法］基于农业科技园区相关国家政策和学术文献的梳理和研究,结合农业科技园区规划实践经验,集成应用城乡规划、农业大数据分析、可视化等技术,优化园区规划方法。［结果］将规划编制分为前期准备阶段、规划编制阶段、规划评估阶段,从规划过程、规划编制内容体系、技术方法等多维度提出了农业科技园区规划编制方法,建立了农业科技园区规划编制技术方法体系。［结论］提升了规划编制的科学性和可操作性,阐明了规划编制技术方法体系的实证经验,强化了规划科学基础并提升了规划技术水平。     

我国农业科技创新效率的区域差异及其影响因素研究

[目的]分析我国区域农业科技创新效率差异,为提高农业科技创新效率整体水平和推进农业现代化提供参考依据。[方法]运用超效率DEA模型,对2007—2016年全国29个区域的农业科技创新效率进行测算和评价,并将所有区域划分为4个效率梯队。构建Malmquist指数,全面分析各梯队农业科技创新效率变动的影响因素。[结果]我国农业科技创新效率水平整体较低,但处于缓慢增长的阶段;不同梯队的效率差异较大,但受技术效率的影响差距正在不断缩减;由于农业科技创新资源配置不均,导致东部地区与中西部地区农业科技创新效率差异突显;第二梯队中多数地区缺乏合理的评估机制,农业科技创新成果转化率低。[结论]提高中西部地区的农业科技创新资源配置比例,发挥高效率地区的中心辐射作用;要突出市场在农业科技创新体系中的重要地位;采取差异化战略,实现资源最大化利用和最大化的产出。