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.     

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.     

Measuring agricultural total factor productivity in China: pattern and drivers over the period of 1978‐2016

The Chinese agricultural sector has experienced a substantial increase in total output since dramatic reforms were introduced in 1978. This paper uses the index method to measure agricultural total factor productivity (TFP) for China’s crop and livestock industries, based on the gross output model from 1978 to 2016. We construct production accounts for the industries using input‐output relationships for the 26 main agricultural commodities and commodity groups, which account for over 90 per cent of the total agricultural inputs and outputs. The results show that China’s agricultural TFP grew at a rate of approximately 2.4 per cent a year before 2009, which is comparable to the main OECD countries and is double the world average. TFP growth accounts for approximately 40 per cent of output growth, suggesting that input growth was the main driver of output growth in the past. However, average productivity growth slowed down after 2009 though it has gradually recovered since 2012. The slowdown reflects the emerging challenges to existing farm production practices in Chinese agriculture, suggesting the need for further institutional reform.     

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。     

The benefits from public agricultural research in Uruguay

We use newly constructed data to model and measure agricultural productivity growth and the returns to public agricultural research conducted in Uruguay over the period 1961–2010. We pay attention specifically to the role of levy‐based funding under INIA, which was established in 1990. Our results indicate that the creation of INIA was associated with a revitalization of funding for agricultural R&D in Uruguay, which spurred sustained growth in agricultural productivity during the past two decades when productivity growth was stagnating in many other countries. The econometric results were somewhat sensitive to specification choices. The preferred model includes two other variables with common trends, a time‐trend variable and a proxy for private research impacts, as well as a variable representing the stock of public agricultural knowledge that entailed a lag distribution with a peak impact at year 24 of the 25‐year lag. It implies a marginal benefit‐cost ratio of 48.2, using a real discount rate of 5 per cent per annum and a modified internal rate of return of 24 per cent per annum. The benefit‐cost ratio varied significantly across models with different lag structures or that omitted the trend or the private research variable, but across the same models, the modified internal rate of return was very stable, ranging from 23 per cent per annum to 27 per cent per annum. These results suggest that the revitalized investment in research spending under INIA has been very profitable for Uruguay and that a greater rate of investment would have been justified.     

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.     

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.     

Encountering Order and Disjuncture: Contemporary Anthropological Perspectives on the Organization of Development

This paper presents new estimates of total factor productivity (TFP) growth in Chinese industry over the past half century that seek to improve on earlier estimates in several respects: better data series are developed for capital and labour; the production function is estimated with fewer restrictive assumptions and corrected for serial correlation; and the TFP estimates are adjusted for cyclical fluctuations. The paper also offers a broader than usual interpretation of TFP growth. Its main findings are: (i) that over the whole period 1952–2005 the main source of industrial output growth was capital accumulation; (ii) that during the period since 1980 TFP growth also contributed significantly to industrial output growth; and (iii) that TFP growth in Chinese industry accelerated from the late 1980s, probably as a result of changes in the pattern of ownership and increased integration into the world economy.     

Multifactor productivity growth and the Australian mining sector

A commonly used, but unadjusted, measure of Australian mining multifactor productivity (MFP) fell by about one‐third over the first decade of the mining boom, coinciding with very large increases in resource prices. Using growth accounting methods and our own adjustments, based on energy use and capital‐output lags to account for depletion effects we find (i) the Australian annual average MFP growth in mining was 2.5 per cent a year between 1985–1986 and 2009–2010 compared to ?0.65 per cent for the unadjusted measure and (ii) productivity growth was positive in the 2000s, albeit at a lower rate than in the 1990s. Our adjusted MFP growth measures at a state level and subsector level are greater than unadjusted productivity measures. In a complementary study using an econometric decomposition of mining MFP at a state level, we find no statistically significant effect of technological change on MFP growth in the sector, but positive and statistically significant effects of technical efficiency and scale over the period 1990–1991 to 2009–2010. Our results do not support specific policy interventions to increase productivity growth in the mining sector beyond appropriate incentives for resource exploration including the provision of precompetitive resource data.     

Is there a slowdown in agricultural productivity growth in South America?

This article estimates agricultural productivity growth in 10 South American countries in 1969–2009 with the objective of investigating if the slowdown being measured in other countries is present in the region. Results show that productivity growth accounts for half of the three‐fold increase in agricultural output during this period and that performance is sensitive to R&D investments in the sector. The slowdown found for the 1990s to 2000s in the U.S. and some European economies does not seem to be present yet in South America. The region's total factor productivity (TFP) growth rate increased steadily from 1.07% during the 1970s to 2.29% during the 2000s. Given lags in adoption and the adaptive nature of innovations in these economies, we have yet to see the potential effects in South American agriculture of decreases in R&D in advanced economies.     

Catching Up or Falling Behind in European Agriculture: The Case of Milk Production

The paper explores and analyses the catching up and falling behind processes in the European dairy sector over the period 2004–2011, using a stochastic metafrontier multiple output distance function for 24 EU Member States. The metafrontier estimates reveal considerable productivity differences in milk production across the EU at the regional (NUTS‐2) level. Milk yield per cow is the highest in the old Member States, especially in those regions located in the northwest of the EU, while the lowest productivity is observed in Eastern Europe. The same structure was found for both the TFP (Total Factor Productivity) levels and TFP growth. Moreover, the results for technical change suggest that farm sizes are not optimal in many regions in Central and Eastern Europe from a dynamic perspective. The comparative analysis suggests that in the new compared to the old Member States, fewer farms could benefit from the movement of the frontier. Moreover, there are no signs that poorly performing farms are catching up with the best performing farms in the EU regions/countries.     

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.     

Exploring the impact of R&D and climate change on agricultural productivity growth: the case of Western Australia*

This article empirically examines the impact of R&D and climate change on the Western Australian Agricultural sector using standard time series econometrics. Based on historical data for the period of 1977–2005, the empirical results show that both R&D and climate change matter for long‐run productivity growth. The long‐run elasticity of total factor productivity (TFP) with respect to R&D expenditure is 0.497, while that of climate change is 0.506. There is a unidirectional causality running from R&D expenditure to TFP growth in both the short run and long run. Further, the variance decomposition and impulse response function confirm that a significant portion of output and productivity growth beyond the sample period is explained by R&D expenditure. These results justify the increase in R&D investment in the deteriorating climatic condition in the agricultural sector to improve the long‐run prospects of productivity growth.     

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。     

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.     

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.     

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.     

Productivity growth in pre‐ 1990 Mongolian agriculture: spiralling disaster or emerging success?

The reasons for the spectacular collapse of so many centrally-planned economies are a source of ongoing debate. In this paper, we use detailed farm-level data to measure total factor productivity (TFP) changes in Mongolian grain and potato farming during the 14-year period immediately preceding the 1990 economic reforms. We measure TFP growth using stochastic frontier analysis (SFA) and data envelopment analysis (DEA) methods. Our results indicate quite poor overall performance, with an average annual TFP change of – 1.7% in grain and 0.8% in potatoes, over the 14-year period. However, the pattern of TFP growth changed substantially during this period, with TFP growth exceeding 7% per year in the latter half of this period. This suggests that the new policies of improved education, greater management autonomy, and improved incentives, which were introduced in final two planning periods in the 1980s, were beginning to have a significant influence upon the performance of Mongolian crop farming.     

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.     

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.