供给侧结构改革背景下的西南地区农业全要素生产率分析

［目的］探究在制度改革背景下的农业生产力发展水平和地区差异,有利于全面了解农业发展状况,为后期农业政策的制定、调整以及农业发展提供理论基础。［方法］文章利用DEA-Malmquist指数法对我国西南地区5个省（市）农业全要素生产率（TFP）水平变化发展趋势进行分析,并在此基础上对不同地区农业TFP差异变化和发展趋势进行预测。［结果］（1）Malmquist指数分析结果表明,我国西南地区农业TFP呈缓慢增长的趋势。通过对不同地区农业TFP结果进行比较,四川省农业TFP有先逐渐上升后下降的趋势,而技术进步是影响四川省农业TFP增长的原因;（2）重庆市农业TFP也是呈现波动式缓慢增加的趋势,年平均增长率为354%; 贵州省农业TFP近20年来增长速度最快,主要影响因素为技术进步; 云南和广西农业TFP也均呈缓慢增长的趋势,技术效率和技术进步在不同时期对农业TFP的影响有所差异。（3）收敛性分析结果表明,我国西南地区农业TFP差异有减小的趋势,并且不同地区农业TFP水平具有向各自稳定状态发展的可能性。［结论］我国西南地区农业TFP增长与技术进步具有较高的同步性,因此,制约我国西南地区农业全要素生产率增长的关键因素是农业科技进步。在供给侧结构性改革背景下,必须以市场需求为科研导向,加大科技创新投入力度,促进我国西南地区农业的可持续发展。     

Six Decades of Total Factor Productivity Change and Sources of Growth in Bangladesh Agriculture (1948–2008)

This study applies the Färe–Primont index to calculate total factor productivity (TFP) indices for agriculture in 17 regions of Bangladesh covering a 61‐year period (1948–2008). It decomposes the TFP index into six finer components (technical change, technical‐, scale‐ and mix‐efficiency changes, residual scale‐ and residual mix‐efficiency changes). Results reveal that TFP grew at an average rate of 0.57% p.a. led by the Chittagong, Rajshahi, Rangpur, Dinajpur and Noakhali regions. TFP growth is largely powered by technological progress estimated at 0.74% p.a. Technical efficiency improvement is negligible (0.01% p.a.) due to stagnant efficiency in most of the regions. Decline in scale efficiency is also negligible (0.01% p.a.), but the decline in mix efficiency is high at 0.19% p.a. Decomposition of the components of TFP changes into finer measures of efficiency corrects the existing literature’s blame of a decline in technical efficiency as the main cause of poor TFP growth in Bangladesh. Among the sources, farm size, R&D investment, extension expenditure and crop specialisation positively influenced TFP growth, whereas the literacy rate had a negative influence on growth. Policy implications include encouraging investment in R&D and extension, land reform measures to increase average farm size, promotion of Green Revolution technology and crop diversification.     

Three decades of productivity change in French beef production: a Färe‐Primont index decomposition

The Färe‐Primont index is used to evaluate total factor productivity (TFP) change and its components for a sample of French suckler cow farms in grassland areas in 1985–2014. The results reveal an increase in TFP of 6.6 per cent over the whole observation period, with technological progress being the major source of productivity growth. Meanwhile, efficiency decreased. Farms experienced great technological progress from 1991 to 2000. From a methodological point of view, the comparison with results obtained with Malmquist indexes shows similar trends but different magnitudes, with the Malmquist index overestimating the TFP and technological changes compared to the Färe‐Primont index. In addition, the use of a sequential approach that restricts technological change to being positive or null allows for the precise calculation of technology changes, disregarding the effects of external conditions that are captured in efficiency changes. Finally, the estimation of full dimensional efficient facets (FDEFs) that guarantees the positivity of all shadow prices used to assess the mix efficiency component of TFP change is promising.     

基于碳排放的河南省粮食绿色全要素生产率分析及对策建议

［目的］为探索粮食绿色增产模式，推进农业供给侧结构性改革和绿色可持续发展。［方法］分别运用SBM-ML指数模型与DEA Malmquist指数模型对2004—2016年河南省粮食绿色全要素生产率和传统全要素生产率进行测算和对比分析，并采用ESDA法探讨了粮食绿色全要素生产率与粮食产出的空间关联性。［结果］河南省粮食绿色全要素生产率明显低于传统全要素生产率； 2004—2016年河南省粮食绿色全要素生产率的驱动因素经历了由技术进步驱动转变为技术效率驱动再转变为技术进步和技术效率共同驱动的过程，但技术进步的贡献率明显高于技术效率； 河南省粮食绿色全要素生产率与粮食产出的二元全局空间自相关大体呈“N”型变化，粮食绿色全要素生产率和粮食产出由不平衡发展逐渐趋向平衡发展。［结论］忽视碳排放的传统粮食全要素生产率测算与实际有较大偏差。建议通过转变发展模式，探索粮食绿色增产道路； 因地制宜，有效利用技术进步和技术效率双轮驱动； 不断推进河南省粮食绿色全要素生产率与粮食产出的平衡发展3项措施来实现粮食生产的综合提升。     

Asian Agricultural Productivity and Convergence

This paper measures agricultural total factor productivity (TFP), for eighteen Asian countries, from 1965 to 1996. TFP is measured by calculating the Malmquist index with respect to the sequential frontier, which is appropriate when the cross section is relatively small. The results show that half the countries have experienced negative productivity growth, due to losses in technical efficiency combined with stagnation in technological progress. Both cross‐section and time series tests show that there is no evidence of convergence in agricultural productivity for these countries. The less productive countries are falling further behind, rather than catching up. Finally, comparisons with Africa show that although Asia has had faster TFP growth than Africa, three of the five African regions (East, Central and Southern) have grown faster than any of the Asian regions.     

中国农业全要素生产率的动态演进及其影响因素分析

[目的]通过测算中国农业全要素生产率,揭示其动态演进趋势及影响因素,从而为推动我国农业供给侧结构性改革,实现农业现代化提供科学的决策依据。[方法]文章使用SBM-Global Malmqusit生产率指数法测算了中国农业全要素生产率,在此基础上利用Kernel核密度估计方法刻画了中国农业TFP增长的动态演进,并通过建立面板数据模型对影响中国农业TFP增长的诸多因素进行了分析。[结果]中国农业全要素生产率增长的主要源泉是技术进步,而技术效率的下降是阻碍其增长的主要原因;核密度估计表明各省份之间的农业相对全要素生产率水平差距不断扩大,技术效率普遍恶化,而技术进步增长速度显著;农业金融发展水平、工业化水平、农业科技水平对中国农业TFP都产生了显著的促进作用,而农业产业结构调整、对外开放水平对中国农业TFP则产生了阻碍作用,农村人力资本则对农业TFP产生的正效应不显著。[结论]提高农业全要素生产率,实现农业现代化.各省份应加强农业科技创新,深化农业科技体制改革,完善农村金融服务体系,推动工业化和农业现代化深度融合,培育新型职业农民等措施。     

Nonparametric estimates of productivity and efficiency change in Australian Broadacre Agriculture

This paper computes and decomposes Färe‐Primont indexes of total factor productivity of Australian broadacre agriculture by estimating distance functions. Using state‐level data from 1990 to 2011, the empirical results show that TFP grew at an average rate of 1.36 per cent per annum in the broadacre agriculture over the period 1990–2011. There are variations of total factor productivity (TFP) growth across states and fluctuations over time within each state and territory. However, overall, there is a clear movement towards slower TFP growth across the sample period. Further decomposition of TFP growth shows that it is declining growth in technical possibilities (technological progress) that is the main driver of the declining trend in productivity growth in broadacre agriculture in Australia.     

The challenge of building an effective innovation system for catch-up

To date, the concept, measurement and interpretation of total factor productivity (TFP) growth remains highly discussed but poorly understood. This paper attempts to provide a review of these issues. First, the definition of TFP growth and the related concepts of embodied and disembodied technical change are discussed. Second, a brief overview and critique of TFP growth measuring techniques is provided. Third, the debate surrounding the accounting identity underlying the estimation of a production function for TFP growth is highlighted. Fourth, the usefulness of TFP growth is evaluated (and maintained) in the light of the criticisms hurled at this measure. Finally, some direction for future work on TFP growth is suggested.     

Dual Technological Development in Botswana Agriculture: A Stochastic Input Distance Function Approach

To improve the welfare of the rural poor and keep them in the countryside, the government of Botswana has been spending 40% of the value of agricultural GDP on agricultural support services. But can investment make smallholder agriculture prosperous in such adverse conditions? This paper derives an answer by applying a two‐output six‐input stochastic translog distance function, with inefficiency effects and biased technical change to panel data for the 18 districts and the commercial agricultural sector, from 1979 to 1996. This model demonstrates that herds are the most important input, followed by draft power, land and seeds. Multilateral indices for technical change, technical efficiency and total factor productivity (TFP) show that the technology level of the commercial agricultural sector is more than six times that of traditional agriculture and that the gap has been increasing, due to technological regression in traditional agriculture and modest progress in commercial agriculture. Since the levels of efficiency are similar, the same pattern is repeated by the TFP indices. This result highlights the policy dilemma of the trade‐off between efficiency and equity objectives.     

我国水禽全要素生产率增长和贡献及区域差异分析

[目的]通过测算水禽全要素生产率（TFP）来评估水禽的投入产出效率,同时分别对比各养殖区域之间TFP的增长率及贡献的差异。[方法]文章依托全国22个省、（市、自治区）水禽投入产出数据,基于索洛残差法和DEA-Malmquist指数法分别从水禽TFP指数、TFP增长率和TFP贡献率3个角度展开分析。[结果]（1）全国水禽TFP均值为1.352,大多数地区的水禽TFP指数均大于1,山东省的技术效率、纯技术效率、规模效率均为全国第一;（2）全国水禽TFP增长率平均值为0.19,水禽TFP贡献率平均值为120%,TFP贡献率和增长率较上一年都有所提升;（3）区域差异比较后发现,西南地区的水禽TFP指数、TFP增长率和水禽TFP贡献率的均值最大,而华中地区的3个指标均值均为全国最小,水禽的TFP区域特征呈现出“北向南移”趋势。[结论]技术进步对水禽产业发展作出了很大的贡献,说明水禽产业需要进一步加强新技术投入;突发事件一定程度上刺激了水禽产量的增长,说明不仅要预防突发事件,而且要不断挖掘突发事件后的边际效应;水禽TFP区域差异显著,要求结合区域特征分析后因地制宜施策,最终提升水禽生产要素投入效率...     

Measuring and decomposing agricultural productivity and profitability change*

Profitability change can be decomposed into the product of a total factor productivity (TFP) index and an index measuring changes in relative prices. Many TFP indexes can be further decomposed into measures of technical change, technical efficiency change, scale efficiency change and mix efficiency change. The class of indexes that can be decomposed in this way includes the Fisher, Törnqvist and Hicks–Moorsteen TFP indexes but not the Malmquist TFP index of Caves, Christensen and Diewert (1982). This paper develops data envelopment analysis methodology for computing and decomposing the Hicks–Moorsteen index. The empirical feasibility of the methodology is demonstrated using country‐level agricultural data covering the period 1970–2001. The paper explains why relatively small countries tend to be the most productive, and why favourable movements in relative prices tend to simultaneously increase net returns and decrease productivity. Australia appears to have experienced this relative price effect since at least 1970. Thus, if Australia is a price‐taker in output and input markets, Australian agricultural policy‐makers should not be overly concerned about the estimated 15 per cent decline in agricultural productivity that has taken place over the last three decades.     

中国林业投入资金利用效率研究——基于Dea-Malmquist指数

以1998～2010年我国30个省面板数据为基础,对我国林业系统资金利用效率定量测算和分解。结果表明,全要素生产率(TFP)对我国林业系统产业总产值、在岗职工年均工资、造林面积等产出指标贡献度为负值,说明我国资金投入没有达到有效推进林业发展的目标。TFP分解后,技术进步落后是资金利用效率较低的重要诱因。就四大经济区而言,TFP指数与各区域技术进步水平一致,林业投入资金效率高低依次为东部地区、东北地区、西部地区、中部地区。     

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.     

Sources and Measurement of Agricultural Productivity and Efficiency in Canadian Provinces: Crops and Livestock

This paper measures and assesses the variation in total factor productivity (TFP) growth among Canadian provinces in crops and livestock production over the period 1940–2009. It also determines if agricultural productivity growth in Canada has recently slowed down as indicated by earlier studies. The paper uses the stochastic frontier approach that incorporates inefficiency to decompose TFP growth into technical change (TC), scale effect (SE), and technical efficiency change. The results indicate that productivity changes were mainly driven by TCs for crops, while the productivity changes in livestock was mainly driven by SEs and technical progress. Though change in technical efficiency is mainly positive (except for New Brunswick and Nova Scotia), its contribution to productivity growth was very little for the provinces. We also found that over the entire period, the productivity growth rates for the crop subsector are on average higher for the Prairie provinces than for the Eastern and Atlantic provinces. On the other hand, the productivity growth rates in the livestock subsector are on average higher in the Eastern and Atlantic provinces than in the Prairie region with the exception of Manitoba. Finally, we found that though there is some evidence of a recent decline in productivity growth for the crops subsector, there is no such evidence in the livestock subsector.     

TOTAL FACTOR PRODUCTIVITY IN UK AGRICULTURE, 1967-90

Indices of total factor productivity (TFP) measure aggregate output per unit of aggregate input, providing a guide to the efficiency of agricultural production. This paper outlines the relationship between production functions and TFP indices. An index for the period 1967-90, constructed from the UK aggregate agricultural accounts, shows that TFP grew at an average rate of 1.9% per annum and that TFP growth has increased since the UK joined the European Community. At the aggregate level, this change seems to be explained by increased aggregate output and decreased aggregate input, in about equal proportions. Disaggregation shows the intensification effect of the CAP price regime. There has been rapid growth in the output of farm crops, relative to other enterprises, and in the use of agricultural chemicals.     

Labor productivity measurement in Japanese agriculture, 1956–90

This paper investigates the factors responsible for a drastic decline in the growth rate of labor productivity of the agricultural sector for the 1956–90 period. This investigation is carried out by a newly devised procedure which decomposes the growth rate of labor productivity into (1) the total substitution effect which consists of the effects due to factor price changes and biased technological change, and (2) the TFP effect composed of the effects due to scale economies and technological progress. Based on empirical estimation of the translog cost function, it was found that the total substitution effect contributed to the growth of labor productivity much more than the TFP effect did for the period under question.     

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。     

The Effect of Investment,LFA and Agri-environmental Subsidies on the Components of Total Factor Productivity: The Case of Slovenian Farms

The effect of subsidies on the performance of farms has received a great deal of attention in the literature, although results are inconclusive. Furthermore, much of the related literature examines the effect of subsidies only on technical efficiency (TE). We examine the effect of different types of subsidies on the different components of total factor productivity (TFP) in Slovenian agriculture over the period 2006–2013. We first estimate a Random Parameter Stochastic production frontier model. Then, based on the estimates of this model, we calculate and decompose the TFP index into TE, scale efficiency and technological change. Third, we apply combined difference-in-difference and a matching estimator to examine the effect of investment, less favoured area (LFA) and agri-environmental (AE) subsidies on the different components of TFP. In our case, these subsidies are found to have no significant effect on either TFP or on its components.     

中国大宗淡水鱼养殖户技术效率、TFP增长及分解——基于25个省份微观调查数据

本文基于2011—2017年养殖户的微观调查数据,利用超越对数的随机前沿生产函数实证分析了大宗淡水鱼养殖户的技术效率、TFP增长及其分解。研究发现,(1)大宗淡水鱼养殖户的技术效率为0.827,表明养殖户的技术利用水平还存在较大的改进空间;(2)不同养殖规模对养殖户技术效率影响不显著,但专业化养殖对技术效率具有显著的正向影响;(3)养殖户TFP年均增长率为3.29%,且呈持续增长趋势;(4)养殖户TFP增长主要来源于技术进步,但技术效率的下降阻碍了TFP的增长;(5)技术效率和TFP增长都具有明显的区域性特征,总体表现为从西部到东部递减的趋势。     

Livestock in China: Commodity-Specific Total Factor Productivity Decomposition Using New Panel Data

Studies of total factor productivity (TFP) in livestock production are rare, but when available provide useful information especially in the context of developing countries such as China where livestock is becoming more important in the domestic agricultural economy. We estimate TFP for four major livestock products in China employing the stochastic frontier approach, and decompose productivity growth into its technical efficiency (TE) and technical progress components. Efforts are made to adjust and augment the available livestock statistics. The results show that growth in TFP and its components varied between the 1980s and the 1990s as well as over production structures. While there is evidence of considerable technical innovation in China's livestock sector, TE improvement has been relatively slow.