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.     

Environmental regulation,total factor productivity,and enterprise duration: Evidence from China

Environmental regulation has been confirmed to have an important impact on enterprise productivity, which is regarded as a crucial factor of enterprise duration. However, existing studies have paid little attention to how environmental regulation affects enterprise duration. Using firm‐level data from the Chinese Industrial Enterprises Database (2003–2007) and the stochastic frontier analysis method, we estimate enterprise total factor productivity (TFP) and its four decomposed components (scale efficiency change, technological change, factor allocation efficiency change, and technical efficiency change). Meanwhile, we adopt a comprehensive index to measure the environmental regulation intensity. Furthermore, we use the linear probability model and the proportional hazards model to investigate the effect of environmental regulation on enterprise duration through the mediating role of enterprise TFP. The results show that although environmental regulation per se negatively impacts on enterprise duration, environmental regulation can present a synthetic positive effect on enterprise duration due to its positive effect on enterprise TFP. Specifically, environmental regulation significantly mitigates the scale efficiency and technical efficiency of regulated enterprises. It also stimulates regulated enterprises' technological innovation and improves their factor allocation efficiency. In addition, state‐owned and large‐scale enterprises are more malleable when facing environmental regulations. We propose that the government should encourage enterprises to innovate and improve the allocation efficiency of production factors, so as to achieve the purpose of controlling environmental pollution in stages while extending enterprise duration.     

Productivity and efficiency dynamics in Indian banking: An input distance function approach incorporating quality of inputs and outputs

Banking technology is typically characterized by multiple inputs and multiple outputs that are associated with various attributes, such as different types of deposits, loans, number of accounts, classes of employees and location of branches. These quality differentials in inputs and outputs are mostly ignored in empirical studies. These omissions make the practical value of productivity studies in organizations like banks questionable because quality is a key component of performance. This paper proposes using hedonic aggregator functions (as a tool of aggregating inputs and outputs with quality attributes) within an input distance function framework and analyzes the impact of banking deregulation on efficiency and total factor productivity (TFP) change in the Indian banking industry using panel data for the period 1996–2005. Empirical results indicate that banks have improved their efficiency (from 61% in 1996 to 72% in 2005) during the post‐deregulation period, and the gain in efficiency of state‐owned banks has surpassed that of private banks. Improvement in capital base, as indicated by increased capital adequacy ratio, played an important role in ushering efficiency gain. The return to scale estimate suggests that state‐owned banks are operating far above their efficient scale and cost savings can be obtained by reducing their size of operations. Overall, TFP growth was above 3.5% annually. Both technical progress and technical efficiency change consistently played an important role in shaping TFP growth. Copyright © 2010 John Wiley & Sons, Ltd.     

Econometric estimation of distance functions and associated measures of productivity and efficiency change

Multi-input multi-output production technologies can be represented using distance functions. Econometric estimation of these functions typically involves factoring out one of the outputs or inputs and estimating the resulting equation using maximum likelihood methods. A problem with this approach is that the outputs or inputs that are not factored out may be correlated with the composite error term. Fernandez et al. (J Econ 98:47–79, 2000) show how to solve this so-called ‘endogeneity problem’ using Bayesian methods. In this paper I use the approach to estimate an output distance function and an associated index of total factor productivity (TFP) change. The TFP index is a new index that satisfies most, if not all, economically-relevant axioms from index number theory. It can also be exhaustively decomposed into a measure of technical change and various measures of efficiency change. I illustrate the methodology using state-level data on U.S. agricultural input and output quantities (no prices are needed). Results are summarized in terms of the characteristics (e.g., means) of estimated probability density functions for measures of TFP change, technical change and efficiency change.     

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。     

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.     

Analyzing China's productivity growth: Evidence from manufacturing industries

This article examines the growth attributes of manufacturing industries in China for the sample period of 1999–2007. The output growth of manufacturing industries classified under four groups and four regions is decomposed into four components of input growth, scale effect, technical progress, and technical efficiency change. A stochastic frontier model is applied to the translog production function to estimate technical efficiency. Despite the conventional argument that input growth and technical progress are important factors to output growth, the empirical findings show a significant scale effect but a weak technical efficiency change. The contribution to growth from labor has been replaced by human and physical capitals. Structural transformation in the industrial sector is evident, so as regional imbalances.     

Parametric decomposition of the input-oriented Malmquist productivity index: with an application to Greek aquaculture

Using a stochastic frontier approach and a translog input distance function, this paper implements the input-oriented Malmquist productivity index to a sample of Greek aquaculture farms. It is decomposed into the effects of technical efficiency change, scale efficiency change, input-mix and, technical change, which is further attributed to neutral, output- and input-induced shifts of the frontier. Implementable expressions for the aforementioned components are obtained using a discrete changes-approach that is consistent with the usual discrete-form data. Empirical findings indicate that the productivity of the farms in the sample increased during the period 1995–1999 and it was shaped up primarily by the input mix-effect and technical change.     

An aggregate quantity framework for measuring and decomposing productivity change

Total factor productivity (TFP) can be defined as the ratio of an aggregate output to an aggregate input. This definition naturally leads to TFP indexes that can be expressed as the ratio of an output quantity index to an input quantity index. If the aggregator functions satisfy certain regularity properties then these TFP indexes are said to be multiplicatively complete. This paper formally defines what is meant by completeness and reveals that (1) the class of multiplicatively complete TFP indexes includes Laspeyres, Paasche, Fisher, T?rnqvist and Hicks-Moorsteen indexes, (2) the popular Malmquist TFP index of Caves et al. (Econometrica 50(6):1393?C1414, 1982a) is incomplete, implying it cannot always be interpreted as a measure of productivity change, (3) all multiplicatively complete TFP indexes can be exhaustively decomposed into measures of technical change and efficiency change, and (4) the efficiency change component can be further decomposed into measures of technical, mix and scale efficiency change. Artificial data are used to illustrate the decomposition of Hicks-Moorsteen and Fisher TFP indexes.     

Debreu’s coefficient of resource utilization, the Solow residual, and TFP: the connection by Leontief preferences

Debreu’s coefficient of resource utilization is freed from individual data requirements. The procedure is shown to be equivalent to the imposition of Leontief preferences. The rate of growth of the modified Debreu coefficient and the Solow residual are shown to add up to TFP growth. This decomposition is the neoclassical counterpart to the frontier analytic decomposition of productivity growth into technical change and efficiency change. The terms can now be broken down by sector as well as by factor input.

Technical efficiency,specialization and ownership form: evidences from a pooling of Italian hospitals

We evaluate how the productive structure and level of specialization of a hospital affect technical efficiency by analyzing a six-year panel database (2000/2005) drawn from hospital discharge records and Ministry of Health data. We adopt a distance function approach, while measuring the technical efficiency level with stochastic frontier techniques. After controlling for environmental variables and hospital case-mix, inefficiency is negatively associated with specialization and positively associated with capitalization. Capitalization is typical of private structures which, on average, use resources less efficiently with respect to public and not-for-profit hospitals. Finally, by looking at scale elasticities, we find some evidence of unexploited economies of scale, leaving room for centralization.     

Determinants of total factor productivity in former Soviet Union economies: A stochastic frontier approach

This paper investigates the process of GDP generation in former Soviet Union (FSU) economies to provide an understanding of the impact of technology channels on countries’ efficiency. We apply a stochastic frontier approach to 15 FSU economies over the period 1995–2008 and find that FDI and human capital improve countries’ technical efficiency. Furthermore, we show that these factors also have a positive impact on total factor productivity (TFP), which, in turn, improves real GDP growth. Hence, our results suggest that FSU countries should promote public policies that provide incentives to attract foreign investment and enhance domestic education in order to improve their economic growth. Additionally, our empirical evidence argues against the resource curse hypothesis. We also show, by computing efficiency change and technological change indices at the country level, that FSU economies benefit more from exploiting technological progress than from catching up to the best practice frontier.     

Determining the contribution of technical change, efficiency change and scale change to productivity growth in the privatized English and Welsh water and sewerage industry: 1985–2000

The water and sewerage industry of England and Wales was privatized in 1989 and subjected to a new regime of environmental, water quality and RPI+K price cap regulation. This paper estimates a quality-adjusted input distance function, with stochastic frontier techniques in order to estimate productivity growth rates for the period 1985–2000. Productivity is decomposed so as to account for the impact of technical change, efficiency change, and scale change. Compared with earlier studies by Saal and Parker [(2000) Managerial Decision Econ 21(6):253–268, (2001) J Regul Econ 20(1): 61–90], these estimates allow a more careful consideration of how and whether privatization and the new regulatory regime affected productivity growth in the industry. Strikingly, they suggest that while technical change improved after privatization, productivity growth did not improve, and this was attributable to efficiency losses as firms appear to have struggled to keep up with technical advances after privatization. Moreover, the results also suggest that the excessive scale of the WaSCs contributed negatively to productivity growth.     

How to optimize the allocation of research resources? An empirical study based on output and substitution elasticities of universities in Chinese provincial level

Although significant progress has been made in China's basic research in recent years, there remains a wide gap between research in China and that from developed countries. How to optimize the allocative efficiency of research resources is of great importance for increasing research output. In this paper, using the fixed effect stochastic frontier model based on the translog production function, we estimate output and substitution elasticities of research and development (R&D) inputs at universities in China's provincial level during 2009–2016. We find that the R&D technical efficiency of China's universities, after a rapid growth, has tended to become relatively stable. Improvements of internationalization degree and exogenous R&D capabilities are conducive to promoting R&D technical efficiency, whereas expenditures from government grants inhibit the promotion of R&D technical efficiency; the effects of R&D capital deepening and internet penetration are not evident. The output elasticity of R&D capital is much higher than that of R&D personnel, suggesting that R&D capital is the main driving force of research output. The substitution elasticity between R&D capital and personnel has experienced a change from substitution to complementary since 2014. To realize sustained growth of research output, we should increase R&D input with positive output elasticity or reduce R&D input with negative output elasticity, making the necessary trade-offs according to the substitution relationship between the two R&D inputs.     

Specification of Distance Functions Using Semi- and Nonparametric Methods with an Application to the Dynamic Performance of Eastern and Western European Air Carriers

In this paper we examine the productive performance of a group of three East European carriers and compare it to thirteen of their West European competitors during the period 1977–1990. We first model the multiple output/multiple input technology with a stochastic distance frontier using recently developed semiparametric efficient methods. The endogeneity of multiple outputs is addressed in part by introducing multivariate kernel estimators for the joint distribution of the multiple outputs and potentially correlated firm random effects. We augment estimates from our semiparametric stochastic distance function with nonparametric distance function methods, using linear programming techniques, as well as with extended decomposition methods, based on the Malmquist index number. Both semi- and nonparametric methods indicate significant slack in resource utilization in the East European carriers relative to their Western counterparts, and limited convergence in efficiency or technical change between them. The implications are rather stark for the long run viability of the East European carriers in our sample.     

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。     

Relative Performance of U.S. and Japanese Electricity Distribution: An Application of Stochastic Frontier Analysis

This paper estimates and compares the technical efficiency of the U.S. and Japanese electric utilities during the period 1982–1997 using a stochastic frontier analysis. Our focus is on electricity distribution services of major investor-owned utilities. We employ translog input distance functions to represent the technology of electricity distribution. Empirical results show that after controlling for environmental variables, on average, the Japanese electric utilities are more efficient. It is shown, however, that some U.S. utilities are as efficient as the most efficient Japanese utilities, indicating that the estimated frontier is not necessarily dominated by Japanese utilities.An erratum to this article can be found at     

The dynamics of efficiency and productivity growth in U.S. electric utilities

This study recognizes explicitly the efficiency gain or loss as a source in explaining the growth. A theoretically consistent method to estimate the decomposition of dynamic total factor productivity growth (TFP) in the presence of inefficiency is developed which is constructed from an extension of the dynamic TFP growth, adjusted for deviations from the long-run equilibrium within an adjustment-cost framework. The empirical case study is to U.S. electric utilities, which provides a measure to evaluate how different electric utilities participate in the deregulation of electricity generation. TFP grew by 2.26% per annum with growth attributed to the combined scale effects of 0.34%, the combined efficiency effects of 0.69%, and the technical change effect of 1.22%. The dynamic TFP grew by 1.66% per annum for electric utilities located within states with the deregulation plan and 3.30% per annum for those located outside. Electric utilities located within states with the deregulation plan increased the outputs by improving technical and input allocative efficiencies more than those located outside of states with deregulation plans.

Decentralized environmental regulations and plant‐level productivity

Using the framework provided by the Porter hypothesis, we study the impact of environmental regulations and enforcement policies on plant‐level green total factor productivity (TFP) growth and its components related to efficiency change and technical change. The detailed microdata we use are from Sweden and for the pulp and paper industry. This industry is the source of significant amounts of water and air pollution and is one of the most heavily environmentally regulated manufacturing industries. Sweden has a unique decentralized regulatory structure where the manufacturing plants have to comply with plant‐specific regulatory standards stipulated at the national level, as well as decentralized local supervision and enforcement. Our empirical results point to beneficial impacts of the environmental policies on plants' green TFP growth and sustainable production practices. We also find that political economy considerations are important, as the presence of the Green Party and aspects like plant size (with corresponding local and regional economic effects) matter in enforcement of the standards.     

The productivity of private and social farms: Multilateral Malmquist indices for Slovene dairying enterprises

Applying programming techniques to farm-level panel data for four cooperative and 12 private dairy farms in the Yugoslav Republic of Slovenia gives estimates of technical efficiency, scale efficiency, and technical progress. These are used to construct multilateral Malmquist indices of total factor productivity (TFP). For the cooperatives, TFP growth has been slow and is attributable to technical progress. For the private farms, technical progress was also slow, but TFP growth was faster due to improved efficiency. Scale inefficiency explains the poorer absolute performance of the private farms, indicating the need for land reform as well as technological change.