Short and long‐run returns to agricultural R&D in South Africa,or will the real rate of return please stand up?

This paper briefly presents the results of a total factor productivity (TFP) study of South African commercial agriculture, for 1947‐1997, and illustrates some potential pitfalls in rate of return to research (ROR) calculations. The lag between R&D and TFP is analyzed and found to be only 9 years, with a pronounced negative skew, reflecting the adaptive focus of the South African system. The two‐stage approach gives a massive ROR of 170%. The predetermined lag parameters are then used in modeling the knowledge stock, to refine the estimates of the ROR from short‐ and long‐run dual profit functions. In the short run, with the capital inputs treated as fixed, the ROR is a more reasonable 44%. In the long run, with adjustment of the capital stocks, it rises to 113%, which would reflect the fact that new technology is embodied in the capital items. However, the long‐run model raises a new problem since capital stock adjustment takes 11 years, 2 years longer than the lag between R&D and TFP. If this is assumed to be the correct lag, the ROR falls to 58%, a best estimate. The paper draws attention to the possible sensitivity of rate of return calculations to assumed lag structure, particularly when the lag between changes in R&D and TFP is skewed.     

Productivity and the Returns to Levy-Funded R&D for Sugar Production in the Eastern Counties of England

Estimates of the rate of return (ROR) to publicly funded-agricultural research are getting lower as private expenditures and spill-overs are more adequately handled. For UK sugar beet there is a pool of technology available and the spill-ins are not measurable. An alternative approach is to assume that the difference between productivity growth in sugar and the rest of UK agriculture is attributable to the Sugar Beet Research and Education Committee's R&D and extension expenditures, funded by the only long-standing producer levy in the UK. These expenditures are used to explain the difference between total factor productivity (TFP) growth in sugar (3.5 per cent per annum) and the rest of UK agriculture (2.0 per cent per annum). The producer's ROR calculated using this approach is 11 per cent and the lower bound on the total return, to producers and consumers is 21 per cent, whereas the conventional methodology gives returns of 87 per cent. Thus, the upward bias in ROR calculations may be removed by changing the approach to the problem.     

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.     

Structural and productivity change in US agriculture, 1950–1982

This paper tests whether structural change in US agriculture is an important channel to TFP growth and evaluates the relative impact of (i) public research and education policies, (ii) private R&D and market forces, and (iii) government farm programs on structural change. We specify a structural econometric model, fit it to US state aggregate data, 1953–1982, and use the associated reduced‐form model to perform counter‐factual policy simulations. The findings include: structural change is a channel to TFP growth in both crop and livestock subsector, i.e. specialization, size, and part‐time farming do impact TFP, holding other variables constant. Public R&D and education have been at least as important as private R&D and market forces for changing livestock specialization, farm size, and farmers’ off‐farm work participation over the study period, but private R&D and market forces have been relatively more important for crop specialization. Changes in farm commodity programs had little impact on farm structure over these study period. Overall, we conclude that if public R&D and education policies had been unchanged at their 1950 values over 1950–1982, major structural changes in US agriculture would have occurred anyway. The forces of private R&D and market forces were at work, including a decline in the price of machinery services and agricultural chemicals, relative to the farm wage.     

Explaining the Decline in UK Agricultural Productivity Growth

This paper reports the results of a study of total factor productivity (TFP) growth in UK agriculture, from 1953‐2000. It shows that prior to 1984 TFP grew at 1.68% per annum and after that date at only 0.26%. International comparisons show that the UK has fallen far behind the leading EU countries. Yield growth declined even more and only labour productivity continues to grow rapidly. In part, the result is due to better data that incorporates more quality adjustment, but the real decline can be explained mainly by cuts in R&D, less patents, less growth in farm size and the demise of public extension. There are other negative factors, which have not been quantified, including asset fixity, convergence and ozone pollution, and a background argument that recent growth rates cannot be sustained.     

COINTEGRATION,AND CAUSALITY: EXPLORING THE RELATIONSHIP BETWEEN AGRICULTURAL AND PRODUCTIVITY

This study investigates the causal relationships between total factor productivity (TFP) and explanatory variables, such as public sector agricultural extension, farmer education, private sector patents and the weather. Cointegration and Granger causality tests are applied to the UK data which were used by Hallam (1990). Unlike Hallam, we find that there is a relationship between research spending and productivity. The same methodology is applied to new data for ten EC countries and the USA. In all cases there is evidence of a long run relationship between TFP and. Pooling the data for the ten EC countries and the USA, and then testing for causality shows that expenditures are Granger prior to TFP and that TFP is also Granger prior to expenditures. This result agrees with Pardey and Craig's (1989) US study.     

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.     

Technology catch-up in agriculture among advanced economies

We examine whether countries with low initial levels of agricultural total factor productivity (TFP) tend to ‘catch up’ with the technology leaders. We first compare relative levels of agricultural TFP, capital services and labour input levels in agriculture for 17 OECD countries between 1973 and 2011. Then we apply (conditional) convergence analysis to the panel data to examine the speed of convergence and test whether the convergence is transitory or permanent by analysing TFP changes over the business cycle. Capital intensities, quality improvement of capital, factors such as human capital spillovers, and certain agricultural policies are conditioning variables. We examine how differences in relative capital intensities affect agricultural productivity convergence over the business cycle. We find evidence that the speed of convergence increases during periods of contraction in economic activity.     

The public R&D and productivity growth in Australia's broadacre agriculture: is there a link?

This paper investigates the dynamic relationships between research and development (R&D) expenditure and productivity growth in Australian broadacre agriculture using aggregate time series data for the period 1953 to 2009. The results show a cointegrating relationship between R&D and productivity growth and a unidirectional causality from R&D to TFP (total factor productivity) growth in Australian broadacre agriculture. Using the dynamic properties of the model, data from beyond the sample period are analysed by employing the variance decomposition and the impulse response function. The findings reveal that R&D can be readily linked to the variation in productivity growth beyond the sample period. Furthermore, the forecasting results indicate that a significant out‐of‐sample relationship exists between public R&D and productivity in broadacre agriculture.     

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。     

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.     

Measuring productivity growth when technological change is biased–a new index and an application to UK agriculture

Productivity growth is conventionally measured by indices representing discreet approximations of the Divisia TEP index under the assumption that technological change is Hicks-neutral. When this assumption is violated, these indices are no longer meaningful because they conflate the effects of factor accumulation and technological change. We propose a way of adjusting the conventional TFP index that solves this problem. The method adopts a latent variable approach to the measurement of technical change biases that provides a simple means of correcting product and factor shares in the standard Tornqvist-Theil TFP index. An application to UK agriculture over the period 1953–2000 demonstrates that technical progress is strongly biased. The implications of that bias for productivity measurement are shown to be very large, with the conventional TFP index severely underestimating productivity growth. The result is explained primarily by the fact that technological change has favoured the rapidly accumulating factors against labour, the factor leaving the sector.     

Convergence and divergence in regional agricultural productivity growth: evidence from Italian regions, 1951–2002

This article analyzes long‐term agricultural Total Factor Productivity (TFP) growth at regional level by testing its time‐series properties and identifying factors associated with divergence as opposed to convergence. The empirical application concerns Italian regions over the 1951–2002 time period. TFP growth decomposition ultimately attributes the observed productivity growth performance to these contrasting (convergence vs. divergence) forces. We find that technological spillovers are the key convergence force regardless of how the spillover effects are computed. At the same time, forces favoring convergence are almost offset by divergence forces (mainly scale or learning effects). This decomposition may explain the persistence of TFP growth rate differences in Italian agriculture, and could be applicable elsewhere.     

Productivity and Producer Welfare in the Presence of Production Risk

Production risk is an inherent characteristic of agriculture and changes in production risk will affect the welfare of risk‐averse producers. Using standard concepts from the literature on uncertainty, we introduce a welfare measure which comprises total factor productivity (TFP), production risk and farmer risk preferences, and which reflects the impact on producer welfare of changes in production technology. An empirical application is carried out using data from a sample of Spanish dairy farms which shows how the positive impact of increases in TFP on welfare can be offset by increases in the risk premium (‘cost of risk’) to the point where welfare may decrease.     

Productivity and Convergence in European Agriculture

We investigate relative productivity levels and decompose productivity change for European agriculture between 2004 and 2013. Specifically (i) we contribute to the debate on whether agricultural Total Factor Productivity (TFP) has declined or not in the European Union (EU); (ii) we compare the relative TFP level across EU Member States and investigate the difference between ‘old’ Member States (OMS, i.e. the EU‐15) and ‘new’ Member States (NMS); and (iii) we test whether TFP is converging or not among Member States. The empirical analysis applies an aggregate quantity framework to country‐level panel data from the Economic Accounts for Agriculture for 23 EU Member States. The results imply that TFP has slightly decreased in the EU over the analysed period; however there are significant differences between the OMS and NMS and across Member States. Finally, our estimates suggest that productivity is generally converging over this period, albeit slowly.     

Public infrastructure and productivity growth in Greek agriculture

Recent research has focused on the effect of public infrastructure on economic performance. In this paper, a model of Greek agriculture's technology and behaviour is constructed based on the dual cost function framework. The model provides a decomposition of productivity growth into the components technical change, returns to scale, and public infrastructure. The empirical estimates indicate that public infrastructure investment provides a significant return to agriculture and augments productivity growth. Over the period 1960–1995, the impact of public infrastructure on productivity growth in livestock and crop production is found to be positive, although it has been declining since the late 1970s. These results strongly suggest that a decline in public infrastructure investment can partly explain the observed decline in the productivity growth of Greek agriculture in the 1980s.     

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.     

Total factor productivity change in China's grain production sector: 1980–2018

This study analyses changes in total factor productivity (TFP) of grains as an aggregate commodity and major grain crops including rice, wheat, and corn, using pooled provincial and time-series data from 1980 to 2018 for China. Results show that the growth of TFP in the grain sector was driven by technical improvements. Moreover, the grain output and wheat production benefited more from TFP growth, whereas the growth in the usage of inputs drove the growth in rice and corn production. Findings also indicate that the laissez-faire market-oriented policy led to a dramatic fall in output while the intervention-led policy resulted in a substantial rise in output, but neither of them fostered the growth of productivity. Conversely, the incentive-led policy in a market-oriented environment that raised the comparative profitability in grain production promoted the growth in both output and productivity in the grain sector. As the comparative advantage shifts away from agriculture in China, an appropriate support is thus necessary to stimulate farmers' incentive in growing grain crops.     

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。     

Research and productivity in Thai agriculture

This paper examines the impact that publicly funded agricultural research has on productivity in crop production within Thailand. It tests empirically the two hypotheses that, first, publicly funded research and development (R&D) in crop production is a significant determinant of total factor productivity (TFP) in the crop sector and, second, that its social rate of return is high. The statistical analysis applies error correction methods to national level time series data for Thailand, covering the period 1970–2006. Emphasis is given to public research in crop production, where most publicly funded agricultural R&D has occurred. The role of international research spillovers and other possible determinants of TFP are also taken into account. The results demonstrate that public investment in research has a positive and significant impact on TFP. International research spillovers have also contributed to TFP. The results support the finding of earlier studies that returns on public research investment have been high. This result holds even after controlling for possible sources of upward biases present in most such studies, due to the omission of alternative determinants of measured TFP. The findings raise a concern over declining public expenditure on crop research, in Thailand and many other developing countries.