Measuring sectoral productivity across time and across countries

This paper examines the problem of measuring the evolution of productivity changes over time and across the 14 countries included in the OECD's International Sectoral Data Base of two sectors considered essential to the economic growth of any nation, namely manufacturing and services. The basic units of analysis are generalized Malmquist productivity indices. These in turn can be decomposed into several components, associated to the various sources of productivity change. Included here are productivity fluctuations due to economies of scale, being constant or variable, to technical change and technical efficiency change. The computational procedure is based upon the concept of distance function, computed through the use of variations of data envelopment analysis.     

环境约束下中国地区物流业全要素生产率重估及收敛性研究

利用基于方向距离函数的Malmquist-Luenberger(ML)生产率指数方法对环境约束下中国1997-2009年30个省级地区物流业全要素生产率增长及其成分进行了重新估算,并通过技术创新者研究,分析了推动生产可能性边界外移的地区.研究发现:忽视非期望产出的传统Malmquist指数方法会低估物流业技术效率水平、高估物流业技术进步指数和全要素生产率指数.环境约束下我国物流业ML生产率指数年均增长率呈现下降趋势,下降的原因一方面是由于技术效率偏低阻碍了生产率的增长,另一方面是我国物流业技术进步的动力不足所致,物流环境技术创新主要集中于东部和西部地区个别省份,中部地区技术创新水平较低.收敛性检验表明,研究样本期内,全国以及三大地区物流业全要素生产率均存在显著的收敛趋势.     

A generalized Malmquist productivity index

In 1953 Sten Malmquist, a Swedish economist and statistician, published inTrabajos de Estadística the foundations of a productivity index which now bears his name. In this paper we generalize the Malmquist productivity index. We show that (i) the generalized Malmquist productivity index can be expressed as the product of a Malmquist productivity index and a Malmquist scale index; (ii) the generalized Malmquist productivity index can also be expressed as the ratio of a Malmquist output quantity index to a Malmquist input quantity index; (iii) the geometric mean of a pair of Malmquist scale indexes is equal to the reciprocal of the Törnqvist scale index, which implies that (iv) the geometric mean of a pair of generalized Malmquist productivity indexes is equal to a Törnqvist productivity index.     

Bank productivity and performance groups: A decomposition approach based upon the Luenberger productivity indicator

The purpose of this paper is twofold. First, in the framework of the strategic groups’ literature, it analyZes changes in productivity and efficiency of Spanish private and savings banks over an eight-year period (1998-2006). Second, by adapting the decomposition of the Malmquist productivity indices suggested by Färe et al. (1994), it proposes similar components decomposing the Luenberger productivity indicator. Initially, productivity is decomposed into technological and efficiency changes. Thereafter, this efficiency change is decomposed into pure efficiency, scale and congestion changes. Empirical results demonstrate that productivity improvements are partially due to technological innovation. Furthermore, it is shown how the competition between private and savings banks develops in terms of the analyzed productivity and efficiency components. While private banks enjoy better efficiency change, savings banks contribute more to technological progress. Consequently, the Luenberger components are used as cluster analysis inputs. Thus, economic interpretations of the resulting performance groups are made via key differences in productivity components. Finally, following the strategic groups’ literature, supplementary insights are gained by linking these performance groups with banking ratios.     

Nonparametric estimation of education productivity incorporating nondiscretionary inputs with an application to Dutch schools

In this paper we develop a Malmquist productivity index for public sector production characterized by the influence of environmental variables. We extend Johnson and Ruggiero (2011) to the more general case of variable returns to scale to further decompose the Malmquist productivity index into technical, efficiency, scale and environmental change. We apply our model to analyze productivity of Dutch schools using 2002–2007 data. The results indicate that the environment influences the productivity index as well as the technical, efficiency, scale and environmental change components. We see that schools with a moderate classification of environment have the highest productivity numbers. In line with expectations, schools with the worst environment also perform worse and would perform better with an improved environment.     

A global cost Malmquist productivity index using data envelopment analysis

This paper proposes a global cost Malmquist productivity index, new cost Malmquist productivity index, that is circular and that gives a single measure of productivity change. The index is inspired by the global Malmquist productivity index as extended to productivity measurement. Decomposition of the proposed cost Malmquist productivity index is presented. Numerical results are presented for an example taken from the literature to illustrate the proposed algorithm.     

Technical change and the von Neumann coefficient of uniform expansion

We study technical change for multi-product technologies to examine its effect on economic growth for 27 OECD (Organization for Economic Cooperation and Development) countries during 1951–2014. We review the Malmquist index and reexamine von Neumann’s model of an expanding economy. We estimate the coefficient of uniform expansion via DEA (Data Envelopment Analysis) and use it to measure technical change via a Solow residual and an alternative von Neumann technical change index which equals the difference between the growth rates of the slowest growing output and the fastest growing input. We also exploit a property of constant returns to scale in order to examine technical change of the average technology. During 2005–2014 the Solow residual shows relatively fast technical change. In contrast, the Malmquist, average technology and alternative von Neumann technical change indexes show negative or stagnant technical change.     

Efficiency and total quality management in health care organizations: A dynamic frontier approach

This paper analyses hospital performance using Data Envelopment Analysis (DEA) and the Malmquist productivity index. We follow two approaches to quantify movements in productivity: (1) the traditional approach that only considers output and input variables; and (2) a more comprehensive approach that incorporates movements in quality and restricts some achievements, if quality is reduced. On the premise that the indicator for quality (nosocomial infections) is equivalent to a bad output, we explore the characteristics of, and compare the results of, the different technological ways to incorporate quality (good or bad attributes, strong or weak disposability technological assumptions). After discussing the virtues and limitations of the existing possibilities, the paper presents a better formulation that allows the preservation of TQM postulates. The decomposition in the Malmquist productivity index shows an improvement in productivity and a positive technical change, especially when quality is introduced. This paper forms part of a more extensive research work, financed by the Spanish Science and Technology Ministry (ref. SEC2003-047707).     

Aggregation of Malmquist productivity indexes allowing for reallocation of resources

In this paper we consider aggregate Malmquist productivity index measures which allow inputs to be reallocated within the group (when in output orientation). This merges the single period aggregation results allowing input reallocation of Nesterenko and Zelenyuk (2007) with the aggregate Malmquist productivity index results of Zelenyuk (2006) to determine aggregate Malmquist productivity indexes that are justified by economic theory, consistent with previous aggregation results, and which maintain analogous decompositions to the original measures. Such measures are of direct relevance to firms or countries who have merged (making input reallocation possible), allowing them to measure potential productivity gains and how these have been realised (or not) over time.     

Productivity change in the water industry in England and Wales: application of the meta-Malmquist index

This paper uses a meta-Malmquist index for measuring productivity change of the water industry in England and Wales and compares this to the traditional Malmquist index. The meta-Malmquist index computes productivity change with reference to a meta-frontier, it is computationally simpler and it is circular. The analysis covers all 22 UK water companies in existence in 2007, using data over the period 1993–2007. We focus on operating expenditure in line with assessments in this field, which treat operating and capital expenditure as lacking substitutability. We find important improvements in productivity between 1993 and 2005, most of which were due to frontier shifts rather than catch up to the frontier by companies. After 2005, the productivity shows a declining trend. We further use the meta-Malmquist index to compare the productivities of companies at the same and at different points in time. This shows some interesting results relating to the productivity of each company relative to that of other companies over time, and also how the performance of each company relative to itself over 1993–2007 has evolved. The paper is grounded in the broad theory of methods for measuring productivity change, and more specifically on the use of circular Malmquist indices for that purpose. In this context, the contribution of the paper is methodological and applied. From the methodology perspective, the paper demonstrates the use of circular meta-Malmquist indices in a comparative context not only across companies but also within company across time. This type of within-company assessment using Malmquist indices has not been applied extensively and to the authors’ knowledge not to the UK water industry. From the application perspective, the paper throws light on the performance of UK water companies and assesses the potential impact of regulation on their performance. In this context, it updates the relevant literature using more recent data.     

Technological progress and productivity growth in the U.S. mobile telecommunications industry

The fast growing U.S. mobile wireless industry has been experiencing dramatic technological change and substantial competition. As a result of these catalysts, we argue that wireless firms have experienced significant productivity improvement and provide new evidence that technological progress almost exclusively contributed to productivity improvements in the wireless industry by significantly expanding the production possibilities set. We employ nonparametric estimation procedures based on Data Envelopment Analysis (DEA) that utilize input-output data from a representative sample of 16 firms in the mobile wireless industry to estimate productivity change, technological change, and relative efficiency change for the period spanning the years from 2000 to 2002. Our findings show that the industry experienced a significant growth of 13% in productivity, which was primarily due to an average technological progress of 9.9% in the industry. Additionally, we find that national wireless operators experienced significantly higher productivity growth and contributed more to technological progress than regional providers. Firms that were industry pioneers as evidenced by high market share at the beginning of our sample period experienced higher productivity growth and greater technological progress compared to firms with lower initial market share. Moreover, the industry experienced significantly higher productivity growth and technical progress in the later sample period between 2001 and 2002 than in the early period between 2000 and 2001.     

Comparing Malmquist and Hicks–Moorsteen productivity indices: Exploring the impact of unbalanced vs. balanced panel data

We explore the effect of balancing unbalanced panel data when estimating primal productivity indices using non-parametric frontier estimators. First, we list a series of pseudo-solutions aimed at making an unbalanced panel balanced. Then, we discuss some intermediate solutions (e.g., balancing 2-years by 2 years). Furthermore, we link this problem with a variety of literatures on infeasibilities, statistical inference of non-parametric frontier estimators, and the index theory literature focusing on the dynamics of entry and exit in industries. We then empirically illustrate these issues comparing both Malmquist and Hicks–Moorsteen productivity indices on two data sets. In particular, we test for the differences in distribution when comparing balanced and unbalanced results for a given index and when comparing Malmquist and Hicks–Moorsteen productivity indices for a given type of data set. The latter tests are crucial in answering the question to which extent the Malmquist index can approximate the Hicks–Moorsteen index that has a Total Factor Productivity (TFP) interpretation. Finally, we draw up a list of remaining issues that could benefit from further exploration.     

Productivity development of Norwegian institutions of higher education 2004–2013

Productivity growth of institutions of higher education is of interest for two main reasons: education is an important factor for productivity growth of the economy, and in countries where higher education is funded by the public sector, accountability of resource use is of key interest. Educational services consist of teaching, research and the “third mission” of dissemination of knowledge to the society at large. A bootstrapped Malmquist productivity change index is used to calculate productivity development for Norwegian institutions of higher education over the 10-year period 2004–2013. The confidence intervals from bootstrapping allow part of the uncertainty of point estimates stemming from sample variation to be revealed. The main result is that the majority of institutions have had a positive productivity growth over the total period. However, when comparing with growth in labour input, the impact on productivity varies a lot.     

A circular global profit Malmquist productivity index in data envelopment analysis

To remove the difficulty caused by different profit frontiers in different periods of time for calculating profit efficiency changes and its components, this paper proposes a circular global profit Malmquist productivity index. This index is applicable when the input costs and output prices are known and when producers seek to maximize the total profit of their decision making units (DMUs). To this end, first, two methods are introduced to obtain the common costs and prices with or without the decision maker’s preferences, and then, a common profit efficient frontier is obtained. The proposed index can be decomposed into several circular components, viz., profit efficiency change, profit technical change, technical efficiency change, allocative efficiency change, technical change, and cost/price change. The proposed index is then generalised to compare the productivity of two different units at two different points in time. The global profit Malmquist productivity index developed here is unique and is computed using nonparametric linear programming model known as data envelopment analysis (DEA), and there is no need to resort to the geometric mean in the calculation. To illustrate the proposed index and its components, numerical examples at three successive periods of time are given.     

劳动生产率增长源泉与收敛研究

在异质性人力资本的条件下,把劳动生产率增长分解为效率的改变、技术改变、人力资本及物质资本.用核密度函数及回归方法分别对劳动生产率增长及收敛性进行了研究.结果表明:(1)劳动生产率分布由单峰变为多峰,其在初级与高级人力资本下的原因分别为技术改变、物质资本与人力资本;(2)全国的劳动生产率是β收敛的,而西部并不存在β收敛;(3)效率改变及技术改变促进了劳动生产率的发散,而人力资本积累及物质资本积累上促进了劳动生产率的收敛.     

Chinese regional energy efficiency change and its determinants analysis: Malmquist index and Tobit model

China becomes the largest energy consumer in 2010 but its energy productivity is well below the world average. To meet China’s fast growing energy using, energy efficiency should be especially emphasized under China’s energy policy. This paper focuses on the regional level of energy efficiency change in China. And we analyze total factor energy efficiency for 30 Chinese provinces over the period 1998–2009 using Malmquist index method and Tobit analysis. The Malmquist estimation results suggest there is a dropping change trend of energy productivity growth. Chinese energy efficiency still faces with huge regional disparity, but the energy technical efficiency reflects convergence in the nationwide and west region. As a result of Tobit regression, we find that industrial structure, energy consumption structure and institutional factor have different influences on energy efficiency.     

Costs and efficiency of higher education institutions in England: a DEA analysis

As student numbers in higher education in the UK have expanded during recent years, it has become increasingly important to understand its cost structure. This study applies Data Envelopment Analysis (DEA) to higher education institutions in England to assess their cost structure, efficiency and productivity. The paper complements an earlier study that used parametric methods to analyse the same panel data. Interestingly, DEA provides estimates of subject-specific unit costs that are in the same ballpark as those provided by the parametric methods. The paper then extends the previous analysis and finds that further student number increases of the order of 20–27% are feasible through exploiting operating and scale efficiency gains and also adjusting student mix. Finally the paper uses a Malmquist index approach to assess productivity change in the UK higher education. The results reveal that for a majority of institutions productivity has actually decreased during the study period.     

基于灰色Malmquist-DEA的中国粮食生产效率分析

选取全国各省粮食生产指标面板数据,对数据进行灰色拟合处理,采用数据包络分析(DEA)法,测算各区域的粮食生产效率,得到投入产出体系的要素冗余值;同时测算了各区域的全要素生产率,并对Malmquist指数进行分解,分析各区域的效率变化和技术变化趋势.结果显示:东、西部地区粮食生产投入要素大量冗余,要素配置效率不高,中部地区要素利用率较高,要素配置趋于合理;效率变化对全要素生产率的作用不明显,而技术进步是全要素生产率增长的关键驱动因素.     

中国制造业企业绩效分化的关键影响因素识别及传导网络图解——基于机器学习组合算法的研究

大数据相关研究和机器学习方法为寻找中国制造业绩效分化的关键因素,以及探索关键因素对绩效分化的传导路径提供了新途径。本文基于岭回归和套索算法(LASSO)筛选出中国制造业绩效分化的重要影响因素,构建了贝叶斯网络确定制造业绩效分化对关键因素的依赖程度,结果显示:中国制造业企业绩效分化的最重要影响因素为资本生产率,制造业遵循“资本效率驱动型”而非“资本数量驱动型”的绩效增长模式。原材料工业企业绩效分化影响因素中杠杆率的重要度相对较低,装备制造业资本密集型的特点决定了企业绩效分化中资金成本和资产流动性的主要作用,消费品工业企业能否实现规模经济也是影响其绩效水平高低的重要因素。     

Network economics and optimal replacement of age-structured IT capital

The constructed hierarchical optimization model of vintage capital replacement takes into account network effects and the age-dependent technological structure of capital equipment. It involves the control of a network coalition choice, endogenous investments, capital structure, and capital lifetime. The qualitative analysis of the model shows how the lifetime and financial structure of the IT capital depends on technological change. These results are relevant for strategic management on a firm level. Provided numeric examples simulate the optimal lifetime of personal computers. This research is partially supported by the NATO grant CLG 982209.