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.     

Evaluating Agricultural Productivity and Policy in Russia

Russia's transition to a market economy in the early 1990s shocked its agricultural sector, creating the potential for profit and gains from specialisation and productivity improvements. However, subsequent regional agricultural development has been highly uneven, and the sources of the sector's productivity improvement remain unclear. Drawing on a newly-assembled Russian regional farm production and policy dataset, we evaluate agricultural total factor productivity growth from 1994 to 2013, decomposing that growth into technical progress and efficiency gains, for the nation as a whole and for the major agricultural districts of the South and Central. We then test how investments in road and rail infrastructure and human capital have influenced those gains. The South substantially outperformed the Central district and the nation at large with respect to all three performance indicators. However, contrary to the literature, we find that these particular state policies provided no substantial growth advantages, there or elsewhere. Rather, the dominant force behind Russia's agricultural growth has been informal technical change.     

The effect of agriculture on repayment efficiency: a look at MFI borrowing groups

There is a widely held industry assumption from microfinance institutions that agricultural loans have poorer repayment rates, which has resulted in many loans being provided for small businesses as opposed to agricultural purposes. Using data from a sample of 100 borrowing groups from a south Indian Microfinance Institutions (MFI), this study challenges this belief by analyzing the repayment efficiency of borrowing groups and reflects on the implications for agricultural microfinance loans. The analysis is run using Bayesian stochastic frontier estimation with an exponential hierarchical prior on the efficiency term. Our results indicate that the average efficiency of the borrowing groups analyzed was approximately 75% and that having a higher percentage of agricultural loans increased borrowing group efficiency while gains in efficiency also rose as the size of the borrowing group increases.     

Accounting for the Gender Technology Gap Amongst Smallholder Rice Farmers in Northern Ghana

Narrowing the gender technology gap in agricultural production has become a critical policy issue in sub‐Saharan Africa. A better understanding of the gender technology gap is essential for policy formulation and programme planning to ensure equity in resource allocation, and household‐level food security in low and middle income countries, such as Ghana. We employ a metafrontier approach to analyse the differences in the efficiency of male and female farmers, recognising the endogeneity of some of the variables in the inefficiency effects model, in particular the credit constraints of the rice farmers under study. Our findings show that while the rice farms themselves are very similar, average yields for male managed farms tend to be significantly higher than female managed farms reflecting higher seeding and fertiliser application rates on male managed farms. However, there is no significant difference between the genders in either land used for rice or total output per farm household. We find some evidence that relative to the metafrontier, male managed farms are less efficient than female managed farms. The results further show gender technology gap amongst the smallholder rice farmers with females’ technology gap ratio being significantly greater than that of males, with females operating on a production frontier closer to the metafrontier. Policies that provide females more access to productive resources and other agricultural services could assist in the generation of relatively higher output.     

The Technical Efficiency Impact of Farm Credit Programmes: A Case Study of Northern Germany

We analyse the technical efficiency of dairy farms in Schleswig‐Holstein that took part in the European Farm Credit Programme over the period 1987 to 1994. One goal of this programme is to increase the productivity of farms. We test whether participants show higher technical efficiency. We utilise a stochastic frontier model that allows for heteroscedasticity and estimation of determinants of technical inefficiency. Statistical tests indicate dominance of this model over alternative specifications. On average, we observe a high level of technical efficiency between 1987–94, but participation in the programme has rather led to a slight decrease. Thus, the programme seems to have failed to increase the competitiveness of farms.     

农业技术进步、空间效应与城乡收入差距基于省级面板数据的分析

目的 通过构建空间计量模型，实证检验2007—2018年我国农业技术进步对城乡收入差距的直接影响和空间溢出效应。方法 文章基于我国31个省（区、市，不含港澳台）的面板数据，利用空间杜宾模型，并设置邻接矩阵、地理距离矩阵和经济距离矩阵，分析农业技术进步对城乡收入差距的影响，并进一步将农业技术进步分解为农业前沿技术进步和农业技术效率。结果 （1）中国省域城乡收入差距具有显著的空间集聚特征，呈现出“高—高”和“低—低”的空间分布特征。（2）农业技术进步不仅有利于缩小当地城乡收入差距，还可以通过空间溢出效应促进邻近地区城乡收入差距的缩小。（3）农业前沿技术进步对当地城乡收入差距的缩小具有显著的促进作用，但对邻近地区的溢出效应不明显；农业技术效率则具有明显的空间溢出效应。结论 农业技术进步有助于缩小城乡收入差距。要继续加大农业科技投入，进行农业科技创新，提升农业技术效率，同时加强省际间的交流与合作，促使区域间农业技术的创新、转化与扩散。     

Explaining agricultural productivity growth: an international perspective

This article presents multi-output, multi-input total factor productivity (TFP) growth rates in agriculture for 88 countries over the 1970–2001 period, estimated with both stochastic frontier analysis (SFA) and the more commonly employed data envelopment analysis (DEA). We find results with SFA to be more plausible than with DEA, and use them to analyze trends across countries and the determinants of TFP growth in developing countries. The central finding is that policy and institutional variables, including public agricultural expenditure and proagricultural price policy reforms, are significant correlates of TFP growth. The most significant geographic correlate of TFP growth is distance to the nearest OECD country.     

The Current State of the Russian Agricultural Sector

Russia's agriculture produces around 3.7 per cent of the country's GDP, employs 9.2 per cent of the national workforce and contributes around 6 per cent of the country's exports. The sector has shown remarkable resilience in the face of wider economic turbulence. Self‐sufficiency rates for the main agricultural commodities are relatively high. Agricultural exports have grown very significantly since 2000 especially for wheat and meslin (wheat and rye mixture). Meat production has been growing steadily, particularly in the poultry and pork sectors. Whilst the agri‐food sector has great potential to play an even more prominent role in Russia's economy, it suffers from relatively low productivity and an outdated technological base. The main drive for efficiency has come mainly from the relatively large‐scale agricultural firms, who generated more than half of the total value of agricultural output in 2016. Foreign policy instability, including economic sanctions, the devaluation of the national currency and declining economic growth have weakened the sector and caused an increase in the prices of imported goods and equipment. At the same time Russian products have replaced high value‐added imports and Russia's agricultural producers are expanding into new markets.     

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。     

基于三阶段SBM模型的中国农业生态效率研究

[目的]剔除外生环境影响和随机干扰对农业生态效率的影响,更精准测度中国各地农业生态效率,为中国绿色农业发展提供有效建议。[方法]文章基于考虑非期望产出的SBM模型结合三阶段DEA建模法构建考虑非期望产出的三阶段SBM模型,利用2008—2017年中国31省(市、自治区)面板数据,在剔除外生环境影响和随机干扰的基础上对中国各地农业生态效率进行了测度。[结果]外生环境影响和随机干扰对农业生态效率测度有着明显影响,在外生环境影响和随机干扰下2008—2017年中国31省市农业生态效率均值皆有明显下降,因此使用三阶段SBM模型是必要的;宏观经济环境改善会增加农业生态效率冗余,政策支持力度的加大和科技发展能减少农业生态效率冗余;整体来看,中国农业生态效率不断改善,第三阶段中国31省市农业生态效率均值从2008年的0.37增长到2017年的0.59,但未达到效率前沿,仍具有改进空间,其中,农业生态效率领先省(市、自治区)与落后省(市、自治区)之间差距较大,第三阶段农业生态效率均值最高的广东省比最低的西藏自治区高出0.85。[结论]为了提高农业生态效率促进绿色农业发展一方面需要营造良好外部环境,重视科技创新作用;另一方面要多角度推动农业环境改善,促进地区交流合作。     

Sustainable agricultural intensification in forest frontier areas

The Lore Lindu region in Indonesia—as in many forest frontier areas in Southeast Asia—has experienced rapid deforestation due to agricultural expansion in the uplands, at the forest margins. This has resulted in aggravated problems of erosion and water availability, threatening agricultural productivity growth. At the same time, technical progress is promoting agricultural intensification in the lowlands. In this article, we examine how improved technologies for paddy rice cultivation in the lowlands have affected agricultural expansion and deforestation in the uplands. The question of a “forest‐saving” or “forest‐clearing” effect related to technical innovation is important from a sustainable development perspective and remains a controversial issue in the literature. We address this question for the Lore Lindu region with an empirical model in which expansion in the lowlands and the uplands is estimated simultaneously. We use data from an extensive village survey conducted in the region, combined with GIS data. To guide the empirical analysis, we develop a theoretical framework based on a Chayanov‐type agricultural household model. The model analyzes farmers' land allocation decisions, taking into account the lowland–upland dichotomy in the agricultural sector. The empirical findings, corroborated by the analytically derived results, show how technical progress for lowland production affects land use at the forest margins and how these effects depend on the factor‐intensity of the technology. The findings imply specific rural development policies for sustainable agricultural intensification in forest frontier areas.     

Subsidies and agricultural productivity in the EU

This paper investigates the relationship between EU agricultural subsidies and agricultural labor productivity growth by estimating a conditional convergence growth model. We use more representative subsidy indicators and a wider coverage (panel data from 213 EU regions over the period 2004–2014) than have been used before. We find that, on average, EU's Common Agricultural Policy (CAP) subsidies increase agricultural labor productivity growth, but this aggregate effect hides important heterogeneity of effects of different types of subsidies. The positive effect on productivity comes from decoupled subsidies, that is, Pillar I decoupled payments and some Pillar II payments. Coupled Pillar I subsidies have the opposite effect: they slow down productivity growth.     

Trade policy, biotechnology and grain self-sufficiency in China

Over the past 20 years the growth of China's agricultural economy has been extraordinary. However, it seems unlikely that China will maintain self‐sufficiency in grains by 2005 without substantial intervention. We develop a CGE model to assess the options available to Chinese policy makers. We compare the welfare effects of import tariffs and domestic support, and explore the potential of biotechnology as a means to achieve self‐sufficiency through improvements in agricultural productivity. Our results indicate that the price interventions that would be required to maintain China's desired self‐sufficiency ratios are considerable, and are unlikely to be compatible with WTO accession. The productivity improvements required are also significant, and likely beyond the current potential of biotechnology.     

Scale Economies,Technical Efficiency,and the Sources of Total Factor Productivity Growth of Quebec Dairy Farms

Canada's average cost for milk production is among the highest in the world. This paper focuses on specific potential causes by estimating economies of scale and technical efficiency for a panel of Quebec dairy farms that spans the 2001–10 period. Additionally, this paper investigates the sources of total factor productivity growth. The stochastic frontier analysis, based on an input‐distance function, is used to estimate returns to scale relationships across dairy farms. The results show that there is significant economies scale to be exploited and that cost of production could also be reduced by improving technical efficiency. Accordingly, the paper indicates that input‐mix effect is the main source of total factor productivity growth. The results have important implications for Canada's supply management policy, and more specifically for the trading of production quota between dairy farmers, as well as for the delivery of targeted extension services.     

Is a slowdown in agricultural productivity growth contributing to the rise in commodity prices?

A slowdown in the rate of agricultural productivity growth is thought by many observers to be contributing to the recent rise in agricultural prices. In this article I decompose sources of output growth in global agriculture into aggregate input and total factor productivity (TFP) components and examine whether productivity growth slowed substantially in the years leading up to the recent rise in commodity prices. Contrary to widely held perceptions, I find no evidence of a general slowdown in sector‐wide agricultural TFP, at least through 2006. If anything, the growth rate in agricultural TFP accelerated in recent decades. However, the results do show a slowdown in the growth of agricultural investment. Accelerating TFP growth largely offset decelerating input growth to keep the real output of global agriculture growing at about 2% per year since the 1960s. Regionally, however, agricultural productivity performance has been uneven. These findings have important implications for the appropriate supply‐side policy response to the current agricultural price crisis.     

FRONTIER PRODUCTION FUNCTIONS AND THE MEASUREMENT OF TECHNICAL EFFICIENCY

A measure of relative producer performance is often useful for policy purposes and the concept of economic efficiency provides a theoretical basis for such a measure. Yet several authors argue that the concept of efficiency and conventional efficiency measures are meaningless for the evaluation of real-world performance. This paper examines some of the issues and argues that producers' performance may be measured using the concept of technical efficiency. Alternative technical efficiency measures are examined including those of Timmer (1971) and Kopp (1981). A frontier production function is estimated for a cross-section of North West farms and these two measures are computed under various assumptions on the fixity of agricultural inputs.     

Spillovers

Interstate and international spillovers from public agricultural research and development (R&D) investments account for a significant share of agricultural productivity growth. Hence, spillovers of agricultural R&D results across geopolitical boundaries have implications for measures of research impacts on productivity, and the implied rates of return to research, as well as for state, national and international agricultural research policy. In studies of aggregate state or national agricultural productivity, interstate or international R&D spillovers might account for half or more of the total measured productivity growth. Similarly, results from studies of particular crop technologies indicate that international technology spillovers, and multinational impacts of technologies from international centres, were important elements in the total picture of agricultural development in the 20th Century. Within countries, funding institutions have been developed to address spatial spillovers of agricultural technologies. The fact that corresponding institutions have not been developed for international spillovers has contributed to a global underinvestment in certain types of agricultural research.     

基于双前沿面SBM-DEA模型的农业用水效率评价

基于有效效率前沿(乐观)和无效效率前沿(悲观)面SBM-DEA模型,对中国31个省(市、自治区)2003—2017年的农业用水效率进行评价,并运用Tobit模型对农业用水效率影响因素进行分析。研究发现:中国农业用水综合效率较低,其中,乐观效率呈现小幅度上升趋势,悲观效率呈现下降-上升-下降-上升趋势。不同农业用水区之间用水效率差异较小,高农业用水区农业用水效率最高,中农业用水区次之,低农业用水区最低。第一产业增加值所占地区生产总值比重、节水灌溉技术、水库总库容量与农业用水效率显著正相关,水资源禀赋、地区教育水平与农业用水效率显著负相关。     

Productivity growth and the returns from public investment in R&D in Australian broadacre agriculture

Investment in R&D has long been regarded as an important source of productivity growth in Australian agriculture. Perhaps because research lags are long, current investment in R&D is monitored closely. Investment in R&D has been flat while productivity growth has remained strong, relative both to other sectors of the Australian economy and to the agricultural sectors of other countries. Such productivity growth, at a time when the decline in terms of trade facing Australian farmers has slowed, may have enhanced the competitiveness of Australian agriculture. The econometric results presented here suggest no evidence of a decline in the returns from research from the 15 to 40 per cent per annum range estimated by Mullen and Cox. In fact the marginal impact of research increases with research over the range of investment levels experienced from 1953 to 2000, a finding which lends support to the view that there is underinvestment in agricultural research. These results were obtained from econometric models which maintain strong assumptions about how investments in research and extension translate into changes in TFP. Hence some caution in interpreting the results is warranted.     

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.