Productivity,efficiency and technical change: measuring the performance of China’s transforming agriculture

As China enters the twenty-first century the health of the agricultural economy will increasingly rely, not on the growth of inputs, but on the growth of total factor productivity (TFP). However, the tremendous changes in the sector—sometimes back and sometimes forwards—as well as evolving institutions make it difficult to gauge from casual observation if the sector is healthy or not. Research spending has waxed and waned. Policies to encourage the import of foreign technologies have been applied unevenly. Structural adjustment policies also triggered wrenching changes in the sector. Horticulture and livestock production has boomed; while the output of other crops, such as rice, wheat and soybeans, has stagnated or fallen. At a time when China’s millions of producers are faced with complex decisions, the extension system is crumbling and farmer professional associations remain in their infancy. In short, there are just as many reasons to be optimistic about the productivity trends in agriculture as to be pessimistic. In this paper, we pursue one overall goal: to better understand the productivity trends in China’s agricultural sector during the reform era—with an emphasis on the 1990–2004 period. To do so, we pursue three specific objectives. First, relying on the National Cost of Production Data Set—China’s most complete set of farm input and output data—we chart the input and output trends for 23 of China’s main farm commodities. Second, using a stochastic production frontier function approach we estimate the rate of change in TFP for each commodity. Finally, we decompose the changes in TFP into two components: changes in efficiency and changes in technical change. Our findings—especially after the early 1990s are remarkably consistent. China’s agricultural TFP has grown at a healthy rate for all 23 commodities. TFP growth for the staple commodities generally rose around 2% annually; TFP growth for most horticulture and livestock commodities was even higher (between 3 and 5%). Equally consistent, we find that most of the change is accounted for by technical change. The analysis is consistent with the conclusion that new technologies have pushed out the production functions, since technical change accounts for most of the rise in TFP. In the case of many of the commodities, however, the efficiency of producers—that is, the average distance of producers from the production frontier—has fallen. In other words, China’s TFP growth would have been even higher had the efficiency of production not eroded the gains of technical change. Although we do not pinpoint the source of rising inefficiency, the results are consistent with a story that there is considerable disequilibrium in the farm economy during this period of rapid structural change and farmers are getting little help in making these adjustments from the extension system.     

Sources of growth in Indonesian agriculture

Indonesia sustained an average increase in agricultural output of 3.6% per year between 1961 and 2006, resulting in a more than fivefold increase in real output. This paper constructs Tornqvist-Thiel indices of agricultural outputs, inputs and total factor productivity (TFP) to examine the sources of growth in Indonesian agriculture over this period. The paper extends previous work on measuring productivity change in Indonesian agriculture by assembling more complete data on cropland and expanding the commodity coverage to include cultured fisheries in addition to crops and livestock. It also accounts for the contribution of the spread of rural education and literacy to agricultural growth. Results show that Indonesia pursued both agricultural intensification to raise yield, especially for food crops, and extensification to expand crop area and absorb more labor. Productivity growth accelerated in the 1970s and 1980s but stagnated in the 1990s once “Green Revolution” food crop varieties had become widely adopted. TFP growth resumed in the early 2000s led by diversification into non-staple commodities such as tropical perennials, horticulture, livestock and aquaculture. Agricultural extensification continued to be an important source of growth in many of parts of the archipelago where previously forested areas were converted to cropland. Human capital deepening, in the form of the spread of literacy and education in the farm labor force, made a modest but sustained contribution to agricultural productivity growth.     

中国农业生产率的变动与分解分析:1978～2004年--基于非参数的HMB生产率指数的实证研究

本文使用非参数的HMB生产率指数方法，考察了中国农村改革以来农业全要素生产率（TFP）的变动趋势，并把TFP的增长构成分解为技术进步、技术效率变化、规模效应和投入产出混合效应四个部分。结果表明，改革开放以来我国农业TFP的增长主要是由技术进步推动的，技术效率的下降对TFP的增长造成了不利影响，而规模效应和混合效应影响较弱。文章还指出中国农业的育种能力和生物技术的发展是农业技术进步的决定力量。     

Productivity accounting for separable technologies

This paper develops a method for decomposing total factor productivity growth in separable production technologies and uses it to examine the role of pest-damage prevention on agricultural productivity. The rate of technical change is decomposed into output-enhancing and damage-preventing components. Growth accounting cannot provide separate estimates of these two components of technical change, and instead a parametric model is developed based on the dual cost function. The proposed model captures both components of technical change, properly accounts for environmental effects, and also accommodates the presence of capacity utilization and scale biases. The empirical application of the model is to a sample of Cretan olive-oil producers, and the results show that output-enhancing technical change is more important than damage-preventing technical change in explaining observed total factor productivity (TFP) changes. The second largest source of TFP growth is due to the scale effect.     

Reallocation and productivity growth in Japan: revisiting the lost decade of the 1990s

Hayashi and Prescott (Rev Econ Dyn 5(1):206–235, 2002) argue that the ‘lost decade’ of the 1990s in Japan is explained by the slowdown in exogenous TFP growth rates. At the same time, other research suggests that Japanese banks’ support for inefficient firms prolonged recessions by reducing productivity through misallocation of resources. Using the data on large manufacturing firms between 1969 and 1996, the paper attempts to disentangle the factors behind the slowdown in productivity growth during the 1990s. The main results show that there was a significant drop in within-firm productivity, the component that is not affected by reallocation of input and output shares across firms over time, during the 1990s. Although we find that misallocation among large continuing firms represents a substantial drag to overall TFP growth for these firms throughout the sample period, the negative impact of misallocation was least visible during the 1990s. The significant reduction in within-firm productivity growth suggests that, as the Japanese economy has matured, a policy which fosters technological innovations via greater competition, R&D, and fast technological adoption may have become increasingly important in promoting economic growth.

技术进步的就业效应与技术进步路线的选择——基于1990～2005年中国省际面板数据的分析

本文结合1990~2005年中国省际面板数据,运用DEA方法测算了各省历年的全要素生产率变化,用以度量广义技术进步,并对技术进步的就业效应以及不同技术进步路线与就业增长的关系进行实证分析。研究表明虽然技术进步有助于三次产业间就业结构的调整与优化,但实证结果显示现阶段技术进步对中国就业增长产生了不利影响;虽然这并不意味着政府促进技术进步的举措就不利于实现就业的增长,但通过促进教育和培训事业的发展、鼓励科技创新等手段,政府促进技术进步的政策取向可以在不同程度上促进就业的增长,可以抑制技术进步对就业增长的挤出作用。     

A Decomposition of Total Factor Productivity Growth in Korean Manufacturing Industries: A Stochastic Frontier Approach

This paper applies a stochastic frontier production model to Korean manufacturing industries, to decompose the sources of total factor productivity (TFP) growth into technical progress, changes in technical efficiency, changes in allocative efficiency, and scale effects. Empirical results based on data from 1980–1994 show that productivity growth was driven mainly by technical progress, that changes in technical efficiency had a significant positive effect, and that allocative efficiency had a negative effect. This study suggests that specific guidelines are required to promote productivity in each industry, and provides additional insight into understanding the recent debate on TFP growth in Korean manufacturing.     

Trade and product innovations as sources for productivity increases: an empirical analysis

Increases in total factor productivity (TFP) are commonly associated with technological innovations measured by the stock of R&D. Empirical evidence seems to corroborate this relationship. However, in trading countries like The Netherlands, productivity increases, even in industry, can also be the result of innovations in the way transactions are managed. These innovations reduce transaction costs and exploit the welfare gains from (further) international division of labour. Such innovations are only partly included in R&D data. Consequently there is not much attention for these ‘trade innovations’—as we label them—in policy. In an empirical analysis this paper compares the influence of trade innovations with the influence of the stock of R&D on TFP in The Netherlands. The regression results show that in this country trade innovations are as important for TFP as technological innovations which directly affect the efficiency of production, which we label ‘product innovations’.      

Technical progress and induced innovation in China: a variable profit function approach

Journal of Productivity Analysis - We propose a new methodology to estimate empirically the input price-induced technical change and total factor productivity (TFP) growth in China. Our primary...     

Technology capital: the price of admission to the growth club

We assess long-run patterns of global agricultural productivity growth between 1970 and 2005 and examine the relationship between investments in technology capital and productivity. To measure agricultural total factor productivity (TFP) we employ a Solow-type growth accounting method to decompose output growth into input and TFP growth. For technology capital we construct two indexes reflecting national capacities in agricultural research and education-extension for 87 developing countries. We then correlate technology capital levels with long-term growth rates in agricultural TFP. Our findings show that global agricultural TFP growth as a whole accelerated since 1980, although performance was very uneven across developing countries. TFP growth rates were significantly influenced by technology capital. Marginal improvements to research capacity, given a minimal level of extension and schooling existed, were associated with faster TFP growth. However, marginal increases in extension-schooling without commensurate improvements in research capacity did not improve productivity performance.     

改革开放以来中国经济增长动力转换的时空特征

基于中国1978~2012年的省级面板数据,采用检验后的超越对数生产函数的随机前沿模型,利用两套资本存量核算方法,对中国经济增长动力的来源及其时空特征进行分析,并对2008年金融危机的4万亿元投资政策进行了效率评价。研究结果表明,中国属于典型的投资主导型经济,资本投入是中国经济增长持续稳定的最主要来源,TFP贡献率呈现逐年下降的趋势;中国经济增长动力由改革开放初期的资本、劳动力和TFP三驾马车平衡拉动,形成了现阶段的资本投入与TFP反向角力态势;区域经济差距主要源于资本投入与TFP双重差异,但TFP差异是最重要因素;4万亿元经济刺激政策下中国经济复苏属于典型的“投资主导型复苏”,是以牺牲中国生产率为代价的,TFP在2008年后呈现断崖式下降,平均拉低中国TFP达0.23~0.32个百分点。     

Structural change accounting with labor market distortions

This paper quantifies the relative importance of sectoral productivity and labor market distortions for structural change in the U.S., India, Mexico and Brazil between 1960 and 2005. I use census data to compute human capital by sector and infer labor market distortions as sectoral gaps in wage per unit of human capital. I incorporate these distortions into a model of structural change, and calibrate the model to reproduce the time paths of sectoral shares of labor and value added for each country. Counterfactuals reveal that (1) TFP growth in agriculture drives most of the decline in its share of labor; (2) the role of labor market distortions is limited.     

我国技术效率、技术进步与生产率区域差异的实证研究

本文用非参数Malmquist指数方法研究了我国全要素生产率的增长状况及其区域差异,并将其分解为技术进步和技术效率,同时采用增长回归法对我国地区之间TFP、技术效率、科技进步的差异进行了检验。研究表明:1994-2007年间我国全要素生产率年均增长率达到1%,主要得益于技术进步水平的提高,技术效率总体上呈现下滑趋势;我国各省市区的科技进步、技术效率、TFP变化呈现出较为明显的差异,其中TFP和科技进步变化差异最为明显,而技术效率变化差异不大。     

Has agricultural labor restructuring improved agricultural labor productivity in China? A decomposition approach

This paper presents a framework for analyzing the changes in agricultural labor productivity with regards to the structural, land intensity, and land productivity effects. This approach allows for the residual-free decomposition of data from different levels of aggregation. The logarithmic mean Divisia index was applied for the analysis and a data envelopment analysis model was constructed to identify potential gains in agricultural labor productivity due to the optimization of input use and output production. The proposed approach was applied to the case of China over the period of 1997–2017. Province-level data were used to identify the major driving factors behind agricultural labor productivity change. Land productivity change appeared to be the major source of agricultural labor productivity gains in China. The structural change was rather negligible, suggesting that the reallocation of the agricultural labor force did not add to the agricultural labor productivity growth in China. A frontier analysis indicated that agricultural labor productivity could increase by some 45% on average in case full technical efficiency is achieved.     

The Solow residual,Domar aggregation,and inefficiency: a synthesis of TFP measures

We consolidate and interrelate the four main approaches to the measurement and decomposition of total factor productivity growth, namely Solow’s residual analysis, the index number approach, Data Envelopment Analysis, and Domar aggregation. Two new results link the general technology TFP growth measure to the industry Solow residuals and inefficiency.     

Productivity,Technology and Economic Growth: What is the Relationship?

The relationship between productivity, technology and economic growth has been debated extensively in the endogenous growth, growth accounting, New Economy and policy literature. This paper briefly surveys the literature on total factor productivity (TFP) calculations – the various techniques and problems associated with it. We argue that TFP is not a measure of technological change and only under ideal conditions does it measure the supernormal profits associated with technological change. The critical driving force of economic growth is not the super normal profits that technological change generates but rather the continuous creation of opportunities for further technological development. Six illustrations of when TFP fails to correctly measure these super normal profits are provided. A version Carlaw and Lipsey's (2003b) model of endogenous general purpose technology‐ driven growth is then utilized to make some progress toward answering Prescott's (1998) call for a theory of TFP. The model is used to simulate artificial data and connect theoretical assumptions of returns to scale and resource costs to the conditions under which TFP miss‐measures the actual growth of technological knowledge.     

技术效率、技术进步、要素积累与中国农业经济增长——基于SFA的经验分析

本文运用随机前沿方法,将1988～2009年中国省份的农业劳动生产率变化分解为农业技术效率变化、技术进步、物质性要素投入变化和人力资本积累四个来源,分析了它们对中国农业经济增长的影响。结果表明,自1988年以来,技术进步、物质性要素投入变化和人力资本积累在总体上都促进了中国省份农业劳动生产率的增长,而技术效率变化却阻碍了大部分省份的增长,但总的来说,技术进步和技术效率变化的共同作用对增长的贡献还是最大的。     

Exact decomposition of the Fisher ideal total factor productivity index

Decompositions of total factor productivity (TFP) shed light on the driving factors behind productivity change. We develop the first exact decomposition of the Fisher ideal TFP index which contains no debatable mixed-period components or residuals. We systematically isolate five effects of (1) technical change, (2) technical efficiency, (3) scale efficiency, (4) allocative efficiency, and (5) price effect. The three efficiency components (2–4) represent the efficiency of achieving a given target point. Components (1) and (5) capture the changes of the target point. While the technical change component is well-established, changes in the relative input–output prices can have real effects on the scale and scope of the target. Such changes are captured by the new price effect component (5). The new decomposition is compared with existing decompositions both in theory and by means of an empirical application to a panel data of 459 Finnish farms in years 1992–2000.

Financial crisis and relative productivity dynamics in Korea: evidence from firm-level data (1992–2003)

We have estimated the relative TFP growth at firm level and analyzed the firm dynamics in view of entry and exit of firms in Korea during 1992–2003, which includes the turbulent financial crisis of 1997–1998. Following Pyo and Ha, Hitotsubashi J Econ 48(1): 67–81, (2007), we have adopted a gross output model rather than a value added model of relative TFP analysis. We have found that the cyclical variation of productivity growth plays a dominant role in the decomposition effects before and after the 1997 financial crisis in Korea. Productivity growth is modest before the crisis and strong after the crisis owing to the recovering market efficiency. There is the likelihood that the productivity growth of stayers during the post-crisis period was significantly higher than new entrants. The net entry effect is found to be more sensitive in small business and export-based firms than in large business and domestic market-based firms. Our findings suggest that Korean firms have recovered a modest level of technical change after its severe financial crisis owing to the improvement of management transparency and the build-up of market efficiency during the IMF-mandated restructuring process. But since the entry effect is estimated to be still negative in Manufacturing and the exit effect is negative in Service sector after the crisis, the Korean economy has not fully recovered its metabolism in the post-crisis period and still lacks a creative destructive process to resume another round of sustainable growth path.     

General Equilibrium Analysis of International TFP Growth Rates

The paper presents a study of the total factor productivity (TFP) performance among developed countries between 1985 and 1990. The analysis includes the three large economies: the US, Japan and Europe. A general equilibrium model of these economies is used to estimate TFP growth at the sectoral and at the aggregate levels. The model is based on the fundamentals of the economies and employs only data on input-output flows, factor inputs across sectors, consumption and trade patterns and endowments. Prices are endogenous in the model. They are obtained as shadow prices from the model's linear program and then used to measure TFP growth and decompose it in a technical change effect, a demand effect and a terms-of-trade effect. The technical change effect is highly correlated with the conventional Solow residual measure. This result lends support to the standard measure of technological change.