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.     

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。     

Agricultural productivity in developing countries

This paper examines changes in agricultural productivity in 18 developing countries over the period 1961–1985. We use a nonparametric, output-based Malmquist index and a parametric variable coefficients Cobb-Douglas production function to examine, whether our estimates confirm results from, other studies that have indicated declining agricultural productivity in LDCs. The results confirm previous findings, indicating that at least half of these countries have experienced productivity declines in agriculture.     

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 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.     

Assessing Total Factor Productivity Growth in Sub‐Saharan African Agriculture

The importance of the agricultural sector in the economic development process is well known. Improvements in agricultural productivity are often found to spill into other areas of a developing economy, potentially improving the standards of living of urban and rural workers alike. Given the importance of this sector, accurate measures of total factor productivity (TFP) across countries can be helpful in identifying conditions, institutions or policies that promote agricultural development. In this article, we estimate TFP growth in agriculture for a panel of 39 sub‐Saharan African countries from 1961 to 2007. We also develop a set of development outcome measures theoretically consistent with strong agricultural performance to serve as external validation of our results. We find that three estimation methods (stochastic frontier, generalised maximum entropy, and Bayesian efficiency) generate relative rankings that are consistent with the development outcome measures, providing external validation of the methods. However, the data envelopment analysis approach performs poorly in this regard.     

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.     

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.     

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。     

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。     

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.     

Productivity growth in Indian agriculture: is there evidence of convergence across states?

This paper explores the question of convergence in total factor productivity (TFP) in agriculture across fourteen major agricultural states of India. Using a Törnqvist–Theil index for TFP growth for the period 1973–1993, we find no evidence to support convergence to a single TFP level (σ‐convergence). After grouping the various states on the basis of their productivity performance, we find that the high‐performing states show a gradual movement towards the trend, whereas the low‐performing states generally show more volatility. Testing for long‐run convergence in levels of agricultural productivity, we find evidence of conditional beta‐convergence after controlling for state‐specific factors and idiosyncratic year‐specific volatility. The results are robust to alternative specifications of tests of unit root in panel data developed recently.     

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.     

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.     

China's regional agricultural productivity growth in 1985–2007: A multilateral comparison1

In this study, we estimate total factor productivity (TFP) growth as well as multilateral TFP index for 25 contiguous China provinces over the 1985–2007 period. Agricultural output growth for each province was decomposed into TFP growth and input growth, where input growth was further disaggregated into contributions from growth of labor, capital, land, and intermediate goods. Over the study period, TFP growth contributed 2.7 percentage points to output growth annually, which was slightly higher than the input growth contribution of 2.4 percentage points per annum. On average, the annual rate of productivity growth peaked during 1996–2000, at 5.1%. It slowed in 2000–2005 to a rate of 3.2% per annum and declined in the most recent years (2005–2007) to ?3.7%. Differences in productivity among regions persisted over the entire period. The tendency toward faster TFP growth in relatively well‐off coastal regions may imply a widening of regional inequality.     

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.     

Use of the single factoral terms of trade to analyse agricultural production*

The aim in this note is to reintroduce the single factoral terms of trade into the policy arena. This economic concept has scarcely been used by analysts or policy makers over the past three decades. It is defined and compared favourably with other terms of trade concepts in terms of their usefulness to agricultural policy makers in Australia. A distinction is made between the single factoral terms of trade from the viewpoint of the farm business and from the viewpoint of the farm household, but only slightly different indices are specified in each case because of the very high positive correlation between farm prices paid and consumer prices. Developing industry‐level indices appears to be a more attractive way to proceed given the substantially different rates of growth in total factor productivity (TFP) between agricultural industries. Despite its usefulness, challenges lie ahead in accurately estimating each of the two components of the single factoral terms of trade, the net barter terms of trade and TFP, and the relations between these two components.     

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.     

Regional productivity convergence: An analysis of the pulp and paper industries in U.S., Canada,Finland, and Sweden

In this paper we investigate the presence of productivity convergence in eight regional pulp and paper industries of U.S. and Canada over the period of 1971–2005. Expectation of productivity convergence in the pulp and paper industries of Canadian provinces and of the states of its southern neighbour is high since they are trading partners with fairly high level of exchanges in both pulp and paper products. Moreover, they share a common production technology that changed very little over the last century. We supplement the North-American regional data with national data for two Nordic countries, Finland and Sweden, which provides a scope to compare the productivity performances of four leading players in global pulp and paper industry. We find evidence in favour of the catch-up hypothesis among the regional pulp and paper industries of U.S. and Canada in our sample. The growth performance is at the advantage of Canadian provinces relative to their U.S. counterparts. The two Nordic countries, that had the lowest productivity levels in 1971, erased most of the gap and in some cases moved ahead of their North-American counterparts.     

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.