Malmquist Index Research Articles

Work Force Efficiency in the Safety Match Clusters

India, one of the largest manufacturers of matchboxes, produces about 4 crore boxes per day. There is a need to study the technical efficiency of the workforce of the Safety Match Clusters (SMC) in Tamil Nadu. The objective is to study the physical and financial performance, and technical efficiency of four SMCs in Tamil Nadu. The methodology consists of collection of primary data for various periods from 2016-17 to 2020-21 and secondary data from SMC officials. The input variables are Units, Employment and Investment, whereas the output variables are Production and Turnover. Data was analysed for ascertaining the technical efficiency of 4 SMCs before and after the implementation of the Cluster Development Approach (CDA), using the output-oriented Banker, Charnes, and Cooper (BCC) model of DEA, output-orientated Malmquist DEA, and stochastic frontier analysis. The study concluded that three clusters are highly efficient, but one needs improvement in workforce and investment to increase turnover. The Malmquist Index Summary of Firm Means indicates an efficiency change of 22% and pure efficiency change of 26%. As per the stochastic frontier equation To=-10.51-0.90En+4.34 In, with a unit increase in employment, the turnover decreases by 0.9 units which is insignificant, and for every unit increase in investment on machinery, the turnover increases by 4.4 units which is significant. The workforce needs further improvement for one firm, whereas the other three are highly efficient.

Measuring farm productivity under production uncertainty

AbstractThis research introduces a novel empirical application to the assessment of farm productivity growth. While the existing research on productivity change has primarily focussed on ex post output observations, it has been shown that ignoring production uncertainty can lead to unreliable results. Using a state‐contingent framework to represent the stochastic production environment, we extend the recent line of research that merged the state‐contingent approach and efficiency measurement to productivity change using the Malmquist and Luenberger productivity indices. Using a balanced panel of 117 arable crop farms surveyed in 2011 and 2015, we show through the study results that productivity decreased, with technological regress being the major source of productivity change. Differences in productivity change between nonstochastic and stochastic modelling show the relevance to consider the state‐contingent framework when assessing farms' productivity.

Spatial-temporal evolution of water resources utilization efficiency in Jiangsu Province

Abstract Improving water resource utilization efficiency is essential in alleviating the crisis of water resource shortage and promoting the sustainable development of the social economy. Based on the data envelopment analysis (DEA) and Malmquist index, the agricultural, industrial, and domestic water resource utilization efficiency of Jiangsu Province from 2011 to 2020 are evaluated, respectively. The results show that the DEA efficiency of agriculture and industrial water use is greater than that of domestic while the improvement of agricultural and domestic water efficiency is larger than that of industrial. Temporally, the water use efficiency was on an increasing trend from 2011 to 2020, and technological progress is the main factor in improving the water resource utilization efficiency. Spatially, the water use efficiency of southern cities in Jiangsu Province is higher than that of northern and central cities, but the difference between cities is gradually narrowing. To improve the efficiency of water resource efficiency, the government should formulate water resource management policies according to local conditions.

Analysis of regional differences in green energy efficiency in countries along “the Belt and Road” Initiative zone—Based on super efficiency DEA model and Malmquist index method

This study uses the super-efficiency DEA model and Malmquist index analysis to evaluate the green energy efficiency of 58 countries along “the Belt and Road” Initiative zone from 2012 to 2021 and uses Tobit regression to analyze the external environmental influences on their green energy efficiency. The results of the study show that in the static analysis, The overall green energy efficiency of 58 countries along the “the Belt and Road” initiative area is low, and there are obvious regional differences; In terms of dynamic analysis, the Malmquist Index shows a slight fluctuation trend from 2012 to 2021. Tobit regression models show that external factors such as economic strength, energy consumption structure, industrial structure, and R&D expenditure are significantly and positively related to green energy efficiency. Based on this, this study proposed that countries should make good use of their resource advantages to improve the overall green energy efficiency of “the Belt and Road” Initiative zone according to local characteristics; strengthen inter-regional cooperation and exchange among countries, and implement outbound strategies to create a favorable development environment for green energy efficiency in “the Belt and Road” Initiative zone. Create a favorable development environment for green energy efficiency in “the Belt and Road” Initiative region.

A study on the measurement of operational efficiency of commercial banks--Analysis based on super-efficient DEA model and Malmquist index

The banking sector has a risk-intensive character and early warning of the risk of commercial bank failures is particularly important. In order to measure the efficiency of commercial banks in Poland and provide a cut-off line for bank failure efficiency, this paper firstly adopts the dichotomous method to pre-process the existing data, then selects three representative input indicators and two output indicators to construct an evaluation index system for bank efficiency, and uses the super-efficiency DEA model to measure the efficiency of banks, and concludes that comprehensive technical efficiency inhibits the rise of bank efficiency, and the efficiency of banks in 2017 -2021 banks' efficiency showed a zigzag fluctuation trend; secondly, based on the static analysis of super-efficient DEA, the dynamic efficiency of banks was estimated and decomposed based on the Malmquist index method; finally, the failure cut-off was determined by testing whether there was a significant difference in the mean values.

Measuring Changes in Chinese Banking Productivity and Profitability

Abstract This paper adopts the Hicks-Moorstein (HM) TFP index and Data Envelopment Analysis (DEA) to explore efficiency and its relation to changes in profitability and productivity in Chinese commercial banks (CBs). We decompose the HM TFP index into changes in technology, pure technical efficiency, scale efficiency, and output mix and then test for distribution differences when comparing the Malmquist and Hicks-Moorstein productivity indices for a given type of data. The study results reveal that the CBs experience primarily an increment of mix-efficiency rather than an improvement in pure technical efficiency (improvement in management practices) and that Chinese CBs pursue technological progress to meet the requirements for financial innovation and internet banking. This paper highlights the importance of analyzing performance from multiple perspectives and provides alternative explanations of improving productivity and profitability based on technical efficiency in general. Our results indicate that including non-performing loans as the input increases the efficiency score, but off-balance sheet items do not have a significant impact. JEL classification numbers: D24, E58, G24. Keywords: Trading Conditions, Hicks-Moorsteen(HM) TFP index, Data Envelopment Analysis (DEA), Productivity, Profitability.

Do Financial Investment, Disciplinary Differences, and Level of Development Impact on the Efficiency of Resource Allocation in Higher Education: Evidence from China

Optimizing the allocation of university resources to improve the efficiency of inputs and outputs is an important issue for the high-quality development of universities. In recent years, China has become an important growth pole for the development of global higher education. In particular, Chinese agricultural universities, with their distinctive disciplinary characteristics and outstanding professional advantages, have made important contributions to the sustainable development of agricultural education around the world. In contrast, academic research on the efficiency of resource allocation in Chinese agricultural universities is very limited. To fill this gap, this study was guided by econometrics and took high-level agricultural universities in China as the research object to measure the effects of financial investment, disciplinary differences, and development level on the level of resource allocation efficiency of universities. With the help of a data envelopment model (DEA) and a Malmquist index decomposition model, we found that the overall level of resource allocation efficiency in the sample universities was high, but there were great disparities in resource input–output effectiveness between universities. In many universities, marginal inputs exceeded marginal outputs, resulting in input redundancy and resource wastage. In addition, this study shows that for high-level agricultural universities, the regression of capital input technology is preventing a sustained increase in productivity, which places the total factor productivity of resource allocation in a diminishing state.

Operational Performance Analysis of the Public Transport System over Time

The public transport system is responsible for the displacement of a large part of the population, particularly in developing countries. This fact makes it relevant to evaluate the performance of public transport to provide an efficient and effective service. The purpose of this study is to conduct a performance evaluation of the public transport operation in the Metropolitan Region of Fortaleza (MRF), in the State of Ceará, Brazil. The analysis is based on DEA and the Malmquist index, based on three inputs (total operating time, fleet age, and the mileage traveled) and two outputs (fare revenue and number of passengers). Data were obtained through automated fare collection systems (AFCs) that were implemented in the MRF. Although there were no major fluctuations in performance during the analyzed period, the results indicate that the system’s performance declined in certain years. In addition, the analysis enables a better understanding of route performance, considering the operating company or the area of operation, which helps to diagnose and comprehend the operation more effectively. By analyzing the operational performance over time, the proposed approach provides an additional contribution by offering a comprehensive overview to the involved stakeholders, fostering decision-making processes based on evidence.

Efficiency Evaluation and the Impact Factors of Sustainable Forestry Development in China: Adoption of Super-Efficiency Data Envelopment Analysis and Malmquist Index Methods

Forestry is the underpinning of economic and environmental civilization for sustainable economic development. Forestry benefits ecosystems and local dwellings; thus, transforming and advancing forest products in a civilized society is critical to building a progressive community. This research aims to analyze the merits of forest products based on static, dynamic, and scale efficiency. It employed the super-efficient data envelopment analysis—Charnes, Cooper and Rhodes, and Malmquist index methods with an enhanced robustness check by applying the Stochastic Frontier Analysis. The results show that, first, from the perspective of static efficiency, the forestry industry’s operating performance is maintained at a relatively high level, with a minimal fluctuation range; however, the scale efficiency is observed at a deficient level. Limited by the scale efficiency results, the aggregate comprehensive technical efficiency was at a low standard. The average total factor productivity of dynamic efficiency for each company reached 1.029, indicating that the resource allocation of listed companies is relatively reasonable, operating efficiency is on the rise, and technical level changes are a substantial source of total factor productivity growth. Furthermore, the super efficiency DEA findings indicated that 11 of the most high-performance companies attained an efficiency value above criterion value one after re-ranking. The comprehensive efficiency value of Sun Paper reached 1.438 in 2019, Sophia 1.393, Hexing Packaging 1.383, Fujian Jinsen 1.326, Bunny 1.271, Meike Home Furnishing 1.235, Jingxing Paper 1.222, Zhongshun Jiezou 1.116, Meiying Sen 1.099, Chenming Paper 1.064, Da Ya Dekor 1.015. Second, the comprehensive efficiency value of Fujian Jinsen’s company has a more significant impact on the overall average efficiency of the forestry listed companies. After excluding Fujian Jinsen, the average comprehensive efficiency of 2018–2019 indicated an upward trend for the listed companies. This study suggests that policymakers should strengthen the forestry industry development plan and policy implementation regulations to focus on the forward-looking and guiding principles of industrial and technological innovation policies.

Assessing the impact of COVID-19 on the performance of organ transplant services using data envelopment analysis

Organ transplant is one of the best options for many medical conditions, and in many cases, it may be the only treatment option. Recent evidence suggests, however, that the COVID-19 pandemic might have detrimentally affected the provision of this type of healthcare services. The main purpose of this article is to use Data Envelopment Analysis and the Malmquist Index to assess the impact that the pandemic caused by the novel coronavirus SARS-CoV-2 had on the provision of solid organ transplant services. To this purpose, we use three complementary models, each focusing on specific aspects of the organ donation and transplantation process, and data from Brazil, which has one of the most extensive public organ transplant programs in the world. Using data from 17 States plus the Federal District, the results of our analysis show a significant drop in the performance of the services in terms of the organ donation and transplantation process from 2018 to 2020, but the results also indicate that not all aspects of the process and States were equally affected. Furthermore, by using different models, this research also allows us to gain a more comprehensive and informative assessment of the performance of the States in delivering this type of service and identify opportunities for reciprocal learning, expanding our knowledge on this important issue and offering opportunities for further research.

Combining common-weights DEA window with the Malmquist index: A case of China’s iron and steel industry

In the conventional data envelopment analysis (DEA) window analysis, a decision-making unit (DMU) in each window is treated as different units in each period so that the evaluation for one unit is performed on different scales over time. This paper proposes a novel window analysis based on common weight across time (CWAT), which evaluates each unit in each window by its common scale independent of time. The model for obtaining common weights is described as linear programming. And the paper suggests the Malmquist productivity index (MPI) on CWAT, CWAT MPI, to analyze productivity change by inheriting the result of window analysis. The numerical experiments are illustrated to examine the validity of CWAT and MPI, and the result shows that the proposed method provides a new evaluation scale compared to previous studies. The proposed model is applied to evaluate the performance of China 45 iron and steel enterprises during 2009–2017. The energy and environmental efficiency are calculated using CWAT, and CWAT MPI analyzes the productivity change.

A comparative study of green growth efficiency in Yangtze River Economic Belt and Yellow River Basin between 2010 and 2020

The Yangtze River Economic Belt and the Yellow River Basin are important economic regions and ecological barriers in China. Promoting the development of the Yangtze River Economic Belt and promoting ecological protection and high-quality development in the Yellow River Basin are major regional strategies implemented by the Chinese government, and the green growth of the two regions is important for the high-quality sustainable development of the whole China. To investigate the regional differences in green growth efficiency of the same type of geographical units, this paper measures the green growth efficiency and decomposition indicators of the Yangtze River Economic Belt and the Yellow River Basin from 2010 to 2020 using a three-stage DEA model and the Malmquist index method and establishes a panel Tobit model to identify the influencing factors of green growth efficiency. The results show that: ①After using the three-stage DEA model to remove the influence of external environment and stochastic factors, the mean values of green growth efficiency of Yangtze River Economic Zone and Yellow River Basin from 2010 to 2020 are 0.996 and 1.089, respectively. The change of green growth efficiency of Yangtze River Economic Zone is slightly higher than that of Yellow River Basin. ②The Malmquist indexes of the Yangtze River Economic Belt and the Yellow River Basin have generally increased, with the Technological Progress Index, which characterizes technological innovation, being the main endogenous driver of green growth efficiency in the Yellow River Basin, while the technical efficiency index, which characterizes factor mix and management level, is more significant in the Yangtze River Economic Belt. ③The Tobit model regression results show that the factors influencing green growth efficiency are also different in the two regions. Among them, the urbanization rate has a significantly positive effect on the two regions, while the effects of environmental regulation and research intensity are not significant. External openness has a suppressive effect on green growth efficiency in the Yangtze River Economic Belt, while the level of financial development and human capital negatively affect green growth efficiency in the Yellow River Basin. Therefore, green development in the new era should pay attention to the differences between different regions, and make appropriate development policies according to the local conditions of the development status of different regions.

Total Factor Productivity and Sources of Long-Term Growth in the Bhutanese Rice Production

Sustainable growth in domestic food production cannot just depend on mobilizing its factor resources but will also require higher productivity growth. This paper aims to study the total factor productivity (TFP) of rice in Bhutan for the period 2009-2010 to 2016-2017. The study employs non-parametric Malmquist index approach to measure TFP growth and decompose into efficiency and technical change. In addition, panel data model is applied to determine the factors influencing changes in TFP growth. The results show that average annual Malmquist productivity growth was only slightly positive, mainly propelled by technological change. The analysis of the factors determining TFP changes suggested that irrigation and population are the key to sustaining long-term rice TFP growth.

Carbon Emission Efficiency, Technological Progress, and Fishery Scale Expansion: Evidence from Marine Fishery in China

China’s technical progress on emissions and vast ocean area make the study for CO2 emission reduction suitable in a marine fishery. This study uses the slack variables of SBM and the Malmquist index to analyze the CO2 emission efficiency of Trawler, Seine net, Drift net, Fixed net, and Angling, along with their efficiency values, distinguishing the impact of technological progress, scale expansion, and technological efficiency. Results show that the CO2 emission efficiency of the Angling and Seine industry is high with the development potential of the low-carbon fishery. Moreover, China’s technological progress is increasing, but the technical efficiency of CO2 emission reduction is declining. Lack of pure technical efficiency is the primary constraint of low-carbon capture fishery, making changes in efficiency show a downward trend. These results expand the research depth of the efficiency impact of technological progress and reveal that technological progress keeps increasing, but the CO2 emission reduction efficiency is decreasing. This indicates that emission reduction requires both technological growth and the technology’s capacity to reduce CO2 emissions efficiently.

Based on financing efficiency evaluation and influencing factors of new energy enterprises based on DEA-Malmquist-Tobit model

Based on panel data of 120 new energy enterprises from 2016 to 2021, this paper studies the current situation of financing efficiency of new energy enterprises. DEA-BCC model, Malmquist index and Tobit model are used to measure the financing efficiency of additional energy enterprises and analyze its influencing factors. The results show that the proportion of new energy enterprises with effective financing does not exceed 20 %, but the proportion shows a fluctuating upward trend ; the financing efficiency of new energy enterprises decreased by 2.6 %, which was more obviously restricted by the technological progress index. The level of economic development, the quality of workers and the level of technology have a promoting effect on the financing efficiency of different energy enterprises, while the asset-liability ratio, ownership concentration and operating cost ratio have an inhibitory effect.

Performance assessment of primary health care services using data envelopment analysis and the quality-adjusted malmquist index

Primary Health Care (PHC) is intended to provide a comprehensive response to the patients’ health needs. Considering the increasing demand to optimise the use of the available resources while keeping a high-quality standard, it is essential to investigate the health services’ performance. We propose a methodology based on the Data Envelopment Analysis (DEA) technique, examining the volume of activities performed and considering the impact of these activities by using a quality indicator directly related to care outcomes. To perform a longitudinal analysis and observe the changes in quality separately, a Quality-Adjusted Malmquist Productivity Index is implemented. The methodology is illustrated by analysing the performance and the evolution in productivity and quality of the primary care services delivered by the municipalities of the Brazilian state of Santa Catarina from 2008 to 2014. Our findings reinforce the view that adequate planning and structuring of PHC services must consider not only the volume of activity but also the impact of the services delivered.

Efficiency of scientific and technological resource allocation in Chengdu–Chongqing–Mianyang Urban agglomeration: based on DEA–Malmquist index model

Efficiency of scientific and technological resource allocation in Chengdu–Chongqing–Mianyang Urban agglomeration: based on DEA–Malmquist index model

Will Online MOOCs Improve the Efficiency of Chinese Higher Education Institutions? An Empirical Study Based on DEA

In recent years, the increasingly fierce competition among higher education institutions (HEIs), the finite resources, and the enormous influence of the COVID-19 epidemic on higher education have made it especially important to evaluate the performance of Chinese higher education institutions. This paper utilizes the DEA-BCC and Malmquist index to analyze the efficiency and productivity of 34 Chinese “985 Project” universities in the period 2017–2021. The indicator system includes three inputs and five outputs, contained in Model 1 and Model 2 for comparative analysis. The results demonstrate that the COVID-19 epidemic has had a considerable negative impact on Chinese higher education, and has induced the reduction of technical efficiency and productivity. Setting up online MOOCs is conducive to enhancing the efficiency and productivity of HEIs; in addition, the efficiency mentioned varies noticeably among different university levels, and there is no significant difference in different university types and geographical locations.

Evaluation of the allocation efficiency of medical and health resources in China's rural three-tier healthcare system

ObjectivesEvaluating the efficiency of health resource allocations is critical to improving China's rural three-level health service network. Study designThis was a prospective panel data study. MethodsBased on panel data of the medical and health resources of 31 provinces within rural China, collected from 2003 to 2020, this study uses a three-stage Data Envelopment Analysis–Malmquist index to analyze the evolution of efficiency and productivity. ResultsThe efficiency and productivity of county and county-level medical and health institutions rank highest, followed by township hospitals, whereas village clinics are shown to be in great need of improvement. A decline in technical advancement appears as a crucial factor exacerbating loss of factor productivity. ConclusionsPolicy makers should further optimize the efficiency of medical resource allocation and promote the coordinated development of rural health in China.

Measuring Comprehensive Production Efficiency of the Chinese Construction Industry: A Bootstrap-DEA-Malmquist Approach

Production efficiency is a critical research topic in the field of construction economics and management. It reflects the developmental potential and competitiveness of the economy or an economic system. An objective and reasonable assessment framework of the production efficiency in the construction industry is essential to promote the industry’s high-quality development. This study aims to propose a scientific and holistic framework to examine the production efficiency in the construction industry and to investigate evolution patterns from a macroeconomic perspective. Input and output indicators were identified through the value-added and the fuzzy Delphi methods. In addition, the production efficiency in the construction industry was examined via the bootstrap-DEA and Malmquist exponential decomposition models. A case study in China was conducted at the end of this research. The panel data of 31 provinces from 2010 to 2020 were applied in the case study. The results reveal the following: (1) The bootstrap-DEA model results show that the trends of production efficiency before and after rectification are similar, but the difference is largest at the peak. Moreover, the production efficiency value after correction is evidently lower than that which is obtained by the traditional DEA model. (2) The Malmquist index decomposition results show that the change trend of technical efficiency in the construction industry is contrary to that of the scale efficiency. In addition, the improvement of scale efficiency cannot bring a melioration of management efficiency or the accumulation of production experience. (3) There is no direct correlation between production efficiency and economic development. High-value areas and median areas are contiguous, and they are mainly distributed in the central and eastern provinces. The findings accurately reflect construction industry productivity, providing practical data for developing policy recommendations for bridging regional construction development gaps.