Malmquist Productivity Index Research Articles

An Efficiency Analysis of Sugarcane Farming in India: An Interstate Comparison of Performance with Data Envelopment Analysis and Malmquist Index

Background: This paper aims to evaluate the agricultural production of sugarcane in major sugarcane-producing states of India. Even though agriculture’s share of India’s GDP is decreasing, it still plays a significant role in the labor force by accounting for a sizable number of jobs. Recognizing the importance of sugarcane farming and the variations in resource availability among the states is crucial. The study highlights the importance of enhancing production management and resource allocation to increase sugarcane production and optimize inputs. Methods: The present research employs sophisticated statistical techniques, including Data Envelopment Analysis (DEA) and the Malmquist Productivity Index (MPI), to investigate the influence of variables such as land area and labor utilization on the efficacy of sugarcane cultivation at the state level spanning from 2017 to 2022. It uses DEA to analyze the connection between various agricultural inputs and the efficiency of food grain production and provides recommendations for improved resource allocation among Indian states. Result: The results of the investigation indicate that the mean efficiency of sugarcane cultivation across India is approximately 84.2%. Notably, states such as Uttar Pradesh, Tamil Nadu and Karnataka have demonstrated the highest levels of efficiency in terms of input utilization in sugarcane farming. Conversely, Bihar and Uttarakhand have emerged as the least efficient states in this regard. Furthermore, an analysis using the Malmquist productivity index indicates that Uttar Pradesh has exhibited the most significant average productivity growth, with Maharashtra and Gujarat following closely behind. Conversely, states such as Andhra Pradesh, Punjab, Haryana and Tamil Nadu have demonstrated only marginal enhancements in productivity. The study’s insights on sustainable sugarcane production and enhanced farmer-level regulatory frameworks have the potential to greatly benefit sugarcane-producing states. By implementing these ideas, we can work towards boosting revenue and reducing poverty in rural areas.

The impact of health policy and organisational models on Italian hospital productivity growth

AbstractThe rapid increase in healthcare costs has drawn the attention of managers and policymakers towards regulating health expenditures: many countries have implemented deep reforms to improve efficiency and productivity in the provision of health services. In Italy, the central government has introduced austerity measures, called recovery plans, to force the administrative regions to reduce healthcare deficits. In this study, we first evaluate the impact of these recovery plans on hospitals’ productivity by calculating the Malmquist productivity index using data envelopment analysis. Next, we regress the obtained productivity index and its components on a set of explanatory variables to capture the impact of the austerity measures, the moderating role of the regional organisational models, the variation in hospitals’ size and management autonomy and the capital intensity. The data used to estimate productivity were for an extensive period – from 2006 to 2018. The results could contribute to assessing the increase in the productivity of hospitals and the influence of government policies on the same.

Unveiling Productivity Dynamics Among Regional Rural Banks in India

This study employs the non-parametric Malmquist productivity index to evaluate the total factor productivity (TFP) change among the regional rural banks (RRBs) in India from 2016 to 2023. The analysis of productivity change among the RRBs holds intrinsic significance due to its potential impact on overall performance and to the delivery of quality services among the rural population. To evaluate the productivity change under varying combinations of input and output selections, two distinct approaches were used: the intermediation approach and the production approach. The empirical results reveal substantial variation in average TEP estimates across the RRBs under consideration throughout the sample period. Furthermore, the observed productivity changes predominantly emanated from technological change (TC) rather than efficiency improvements. Additionally, we found that the smaller RRBs were performing better than their larger counterparts. These empirical findings bear noteworthy policy implications, offering valuable insights for policymakers and regulators to formulate effective strategies to ensure the competitiveness and sustainability of RRBs in India.

Evaluating the research and development (R&D) efficiency of the Chinese construction industry

PurposeThe construction industry has been investigating “where Henry Ford is in the industry system.” Given that listed construction enterprises are the backbone of the promotion of the high-quality development of the industry, their research and innovation are of considerable importance. This study aims to comprehensively assess the research and development (R&D) status quo and trends within various types of construction enterprises in order to identify effective strategies to enhance R&D efficiency in the construction industry.Design/methodology/approachBased on the data won from annual reports and the CSMAR database for the period 2016–2020, this study examines 104 listed construction enterprises in China. By applying both the data envelopment analysis (DEA) method and the Malmquist productivity index, this research compares and analyzes the static and dynamic differences in R&D efficiency across different types of construction enterprises.FindingsResults suggest that the magnitude of change in the Malmquist decomposition index of 104 listed construction enterprises gradually narrowed, but the comprehensive technological level remained relatively low. Although state-owned enterprises had an advantage in scale efficiency, meaning they could maximize output with given inputs, their technological progress efficiency, also known as the degree of technological innovation, was significantly lower than that of private enterprises. As one finding, state-owned enterprises in comparison with private enterprises experience significant R&D inefficiency. It represents the main cause of their low degree of technological innovation and efficiency.Originality/valueThis study assesses the R&D efficiency of listed construction enterprises in China from the perspective of different market segments, state-owned and private enterprises and suggests approaches to improve strategies for various corporate types. Thus, the study’s new findings contribute to addressing the challenge of low R&D levels in the construction industry in the fields of engineering, construction and architectural management.

Analisis Efisiensi dan Produktivitas Bank Pembiayaan Rakyat Syariah di Jabodetabek Periode 2019-2023

This research aims to analyze the efficiency and productivity of BPRS in Jabodetabek, totaling 17 BPRS during the 2019-2023 observation period. This research uses the BCC or VRS model as a basic model in analyzing bank efficiency and productivity using Data Envelopment Analysis and the Malmquist Productivity Index. This research uses input variables, namely third party funds and operational expenses, as well as output variables, namely operational income and financing. The results obtained from efficiency analysis using DEA show that there are still many BPRS in Jabodetabek that have not achieved maximum efficiency. The average Jabodetabek BPRS efficiency score fluctuates from year to year during the period 2019 to 2023, with an overall average efficiency of 0.716648. Meanwhile, the average productivity of BPRS in Jabodetabek is 1,102. In 2020 there was a decline in the efficiency and productivity of BPRS due to the Covid-19 pandemic. But Back shows recovery in 2021 to 2023.

Monitoring sustainable waste management in OECD countries: A Malmquist productivity approach

Sustainable waste management (SWM) practices are crucial for tackling environmental concerns under a circular economy (CE) scope. Thirty-one OECD countries have been evaluated on their national SWM performance via Malmquist data envelopment analysis (DEA) methodology from 2000 to 2021. The Malmquist (MPI) and Malmquist-Luenberger (MLPI) productivity indices are compared based on their total factor productivity (TFP) and its elements (i.e., efficiency and technological changes). Both models have the gross domestic product (GDP) as a desirable output, but MLPI also incorporates municipal solid waste (MSW) generation and greenhouse gases (GHGs, i.e. CO2 and CH4) as undesirable outputs. MLPI has a lower average performance (1.74%) than MPI (4.42%), meaning that the incorporation of waste and GHGs has diminished an OECD country’s SWM performance by 2.5 times on average. In essence, it is innovation that drives TFP in the selected countries. Overall, the synergistic implementation of SWM practices, Malmquist DEA-based methodology, and CE principles is crucial for advancing sustainable development and achieving a circular and resilient future. The manuscript also offers policy implications regarding the need of financial incentives, vocational training, and fostering stakeholder encouragement in the waste sectors to implement CE solutions.

A Metafrontier and Malmquist Productivity Index Approach for Analyzing Biased Technological and Efficiency Change in Taiwanese Traditional Chinese Medicine

This study assesses changes in resource productivity in traditional Chinese medicine (TCM) system across Taiwanese counties and cities from 2016 to 2019, stratifying the analysis by population densities. Employing a data envelopment analysis (DEA) metafrontier Malmquist productivity index model, this research relaxes Hicks’ neutrality assumption of technical change, allowing for the measurement of biased technological change and technical gap ratio changes. The empirical findings reveal a decline in TCM system productivity, primarily attributed to reduced technological advancements. Notably, higher productivity changes were observed in counties and cities with lower population densities, contrasting with those having higher population densities, where productivity changes were limited. The results suggest that areas with lower population densities hold significant potential for technological enhancement, as evidenced by intergroup technology updates and technological leadership indices. Furthermore, the estimates of productivity change and technological bias underscore the inadequacy of assuming Hicks’ neutral technological change for analyzing TCM system productivity in Taiwan. These findings highlight the need for improved TCM system technology and innovation within the healthcare system to address the urban-rural gap effectively.

Revisiting the Productivity Paradox: What is Next for the BRICS and European Banking Systems?

Information technology is a critical driver of productivity growth in modern economies. However, there has been no convincing explanation for the observed discrepancy in the literature, increasing suspicion on whether IT can improve institutional performance in contemporary banking markets. The fallacy of productivity adds credence to Robert Solow’s dictum, “You can see the computer age everywhere except in productivity statistics”. We employ two extensive bank-level datasets of 5,794 institutions across 37 nations to estimate the total factor productivity (TFP) payoffs from IT in BRICS and European markets. A DEA-based, Malmquist productivity index quantifies TFP change and its respective components. Findings provide evidence against the paradox as both regions experience IT-fueled productivity growth. Nevertheless, such associations vary across banking sector development, rationalizing how IT spending can explain productivity differences across nations. For BRICS banks, a significant proportion of TFP growth originates from frontier expansion instead of frontier progression, signaling a widening of technology gap. Contrastingly, IT has diminished the technology gap between European banks. Intra-country comparisons suggest that if IT-driven productivity growth is regarded as a nation’s long-term goal, industry characteristics should govern the distribution of knowledge capital.

Balancing economic and environmental strategies in regional hinterland transport: a dynamic network cross efficiency analysis

Regional seaport hinterland transport network development strategies aim to maximize economic benefits while simultaneously mitigating environmental impacts. Tracking hinterland transport’s environmental efficiency is crucial for monitoring and improving sustainable transport policies in regional seaports. Previous research mainly employs static self-assessment models under a single objective, overlooking multi-modal hinterland transport routes. This study introduces network cross-efficiency data envelopment analysis models to assess the efficiency of regional seaport hinterland transport, balancing economic and environmental strategies. We further employ the cross-efficiency global Malmquist productivity index to examine dynamic changes and emission reduction potential. We find that hub seaports advance faster than smaller seaports. Road-rail transport constantly showcases high efficiency. Hinterland transport’s efficiencies under environment priority strategy show a weak positive correlation with balanced strategy, and a moderate negative correlation with economy priority strategy. Efficiency improvements in road and road-rail transport can be achieved through enhanced management, while technological innovation is key for road-inland waterway transport. The models and outcomes provide valuable insights for developing sustainable inland transport policies balancing economic growth and emission reduction in regional seaports.

Bank Productivity: A Meta-Regression Analysis

Purpose: This study aims at examining studies employing the Malmquist Productivity Index (MPI) in calculating banks’ productivity. It also seeks to determine the factors affecting the total factor productivity change of banks through meta-regression analysis. Methodology: On December, 2023, relevant works were systematically reviewed using Web of Science (WoS), Scopus, and Google Scholar. The literature review employed a comprehensive search involving all files with the keywords such as ‘‘productivity” and “bank’’. The research process adhered to the PRISMA guidelines. Findings: Key features of the 35 studies incorporated in the analysis are presented. The samples of 65.71% of the studies are Asian countries. The bank productivity of 45.71% was calculated through the DEA-MPI method. The studies under consideration were sourced from diverse populations. These studies share key similarities in terms of subject and methodology. Random Effects Model was used to test heterogeneity across studies. The common effect size is 19.361 (z= 4.23, 95% CI: [10.384, 28.338]). Inter-study heterogeneity was determined through Cochran Q test and I^2 index (I^2= % 100, df=32.000, Q=141163533.762, p

Statistical inference for Hicks–Moorsteen productivity indices

AbstractThe statistical framework for the Malmquist productivity index (MPI) is now well-developed and emphasizes the importance of developing such a framework for its alternatives. In this paper, we try to fill this gap in the literature for another popular measure, known as the Hicks–Moorsteen productivity index (HMPI). Unlike MPI, the HMPI has a total factor productivity interpretation in the sense of measuring productivity as the ratio of aggregated outputs to aggregated inputs and has other useful advantages over MPI. In this work, we develop a novel framework for statistical inference for HMPI in various contexts: when its components are known or when they are replaced with non-parametric envelopment estimators. This will be done for a particular firm’s HMPI as well as for the simple mean (unweighted) HMPI and the aggregate (weighted) HMPI. Our results further enrich the recent theoretical developments of nonparametric envelopment estimators for the various efficiency and productivity measures. We also examine the performance of these theoretical results for both the unweighted and weighted mean of HMPI for a finite sample, using Monte-Carlo simulations and also provide an empirical illustration along with the computation code.

Productivity in the Insurance Company: A Meta-Regression Analysis

Purpose –This study attempts to examine the studies using Malmquist Productivity Index (MPI) in calculating the productivity of insurance sector and to identify the factors influencing their total factor productivity change through meta-regression analysis. Design/Methodology/Approach –This study employed 29 empirical articles which were published between 1977-2023 and which met the inclusion criteria. Findings –The results on the meta-regression analysis revealed that the publication year of the studies and the income groups of the countries did not have an impact on the total factor productivity. The number of observations, number of variables, and branch of theinsurance company were statistically significant on the estimation of total factor productivity change.Discussion –In this study, a meta-regression analysis systematically highlights the effects of methodological assumptions on the productivity of insurance companies and synthesize empirical findings. The study serves to make the literature more accessible to researchers who will use the MPI method for measuring the productivity of insurance companies. This study is expected to guide managers in enhancing the productivity of insurance companies, considering national requirements, making and implementing legal regulations, and identifying policies

DEA-Based Malmquist Productivity Approach for Assessing Total Factor Productivity Change in Malaysian Public Universities

This study uses the non-parametric frontier method to examine the productivity growth of Malaysian public universities from 2017 to 2021. It examines changes in productivity at university groups and individual institutions, using three inputs (academic staff, undergraduate student enrolment, and postgraduate student enrolment) and three outputs (undergraduate and postgraduate qualifications awarded and publications). This study analyses productivity changes and breaks them down into technical efficiency and technological change using the Data Envelopment Analysis (DEA)-based Malmquist productivity index (MPI). The analysis reveals that public universities in Malaysia have seen an average annual increase in MPI of 0.5% over the period of the study. However, when the components of this productivity change are examined, it becomes evident that Malaysian public universities have had an annual average 1.3% increase in technology along with a 0.8% decline in technical efficiency. Further evaluation of the indexes reveals disparities between Malaysian university groups. Technical, comprehensive, and research universities make up the group that performs the best to the worst. Although Malaysian public universities’ productivity is increasing, it is mostly due to technology, which comes at the expense of decreased technical efficiency.

The impact of big fund on the operational efficiency of semiconductor companies: Corporate social responsibility as a non-economic output

This study contributes to research on the total factor operational efficiency of the semiconductor company considering corporate social responsibility (CSR) by proposing a novel integer-valued nonparametric frontier method. This method adopts an endogenous directional distance function, which first selects the benchmark and then endogenously determines the directional vector. Avoiding the issue of non-integer slack adjustment increases the convenience of formulating incentive plans and calculating efficiency. We apply this method to the input–output data of 185 listed Chinese semiconductor companies from 2010 to 2022, considering integer-valued CSR as non-economic output. Global Malmquist productivity index analysis shows that the average total factor operational efficiency of companies that received investment from the National Integrated Circuit Industry Investment Fund (Big Fund) increased by 6.9%. Using the econometric technique, we verify that the total factor operational efficiency of semiconductor companies receiving Big Fund investment increased by 0.084 compared to those without Big Fund investment. Heterogeneity analysis showed that the effect of Big Fund was more significant in improving the total factor operational efficiency of state-owned, new, and non-integrated circuit semiconductor companies, implying the necessity of purposeful investment policies for the Big Fund.

Study of Impact of COVID-19 Pandemic on Urban Railway Productivity: Focusing on Seoul Urban Railway with Malmquist Productivity Index

Study of Impact of COVID-19 Pandemic on Urban Railway Productivity: Focusing on Seoul Urban Railway with Malmquist Productivity Index

A data envelopment analysis model for optimizing transfer time of ischemic stroke patients under endovascular thrombectomy

This study applies Data Envelopment Analysis (DEA) to optimize transfer times and futile transfers of eligible ischemic stroke patients receiving Endovascular Thrombosis (EVT) in Primary Stroke Centers (PSC) in Nova Scotia. The study aims to assess healthcare delivery in Nova Scotia over two periods. It seeks to improve stroke care for rural populations by examining nine inputs, including age and distance between PSCs and the Comprehensive Stroke Centre (CSC) that provided EVT treatment, concerning a single output variable: whether EVT is performed or not. In the first phase, 115 patients were treated as Decision-Making Units (DMUs) for ten PSCs by applying an input-oriented Variable Returns to Scale (VRS) assisted by super-efficiency analysis using the Python-based PyDEA tool. This tool is known for its unrestricted capacity to handle DMUs, inputs, and outputs. In the second phase, eight PSCs with low patient numbers were merged into four DMUs, each consisting of two PSCs. These two merged PSCs have limited patients, and the selected PSCs are also geographically close. Two PSCs have been kept separate because they had sufficient patient volume. In the first phase, VRS generated more reasonable efficiency scores for evaluation, while in the second phase, Constant Returns to Scale (CRS) outperformed VRS, yielding better results. In the initial stage of the second phase, ten PSCs were considered as six DMUs using the input-oriented CRS and VRS for 115 patients. Super-efficiency measures were applied in this stage to improve the evaluation process further. In the second part of the second phase, a comparison between the first period (2018–2019) and the second period (2020–2021) was conducted using the Malmquist Productivity Index (MPI), considering CRS and VRS to evaluate the relative efficiency and productivity change of six DMUs over time.

Unveiling the impact of remittances on productive efficiencies: investigating productivity growth of prominent remittance-receiving developing nations

PurposeThe present study reviews the theoretical and empirical literature about the significance of international migrants' remittance to empirically analyse the effect of remittance on the productivity growth of developing countries using a panel dataset from 1991 to 2021.Design/methodology/approachThe study utilised the data envelopment analysis (DEA)-based Malmquist Productivity Index (MPI) to measure nationwide production efficiencies. It first performed a unit root test, cointegration test and pool mean group autoregressive distributed lag (PMG-ARDL) technique. To assess the robustness of the findings, the study also uses dynamic ordinary least squares (DOLS) and fully modified OLS (FMOLS) estimators.FindingsThe results demonstrated that remittances are a significant source of funding that promotes innovation [i.e. technological progress (TEC)] and hastens the country's total factor productivity (TFP) growth. However, the study needed to have established the effect of inward remittances on the nation's technical efficiency (EFF).Research limitations/implicationsAs remittances encourage innovation and TFP growth (TFPG), the concerned governments must create favourable and enabling economic environments to increase remittance inflows, which will have far-reaching growth repercussions.Originality/valueThe present study emphasises the connection between remittances and productivity growth, the disintegration of TFP, advanced econometric techniques and contribution to research policy. Despite prior literature exploring the effect of remittances on economic growth, a dearth of literature exists on how remittances affect a country's productivity. The output-based MPI methodology used in this study offered a nuanced understanding of how remittances affect many facets of productivity growth in developing nations.

Decreasing Productivity in the Primary Healthcare: A Study of the Brazilian Case

ABSTRACT: In 2015, the United Nations (UN) proposed the 2030 Agenda, a resolution that outlines the global goals for sustainable development. This report focuses on promoting health and well-being, emphasizing the importance of primary healthcare (PHC). However, Brazil faces challenges in managing its healthcare system, exacerbated by fiscal policy changes that have reduced public sector expenditures after 2015. This study was motivated by these recent changes in Brazil’s fiscal policy. We evaluated potential fluctuations in total factor productivity (TFP) in 5,524 Brazilian municipalities’ primary healthcare from 2015 to 2019. TFP, a measure of efficiency and production technology in PHC, was computed using the bootstrapping Malmquist productivity index (MPI) derived from the Data Envelopment Analysis (DEA) algorithm. This study focused on the economic recession and austerity measures initiated in 2015. Moreover, it’s essential to highlight that the SARS-CoV-2 pandemic in Brazil in 2020 brought significant changes to the country’s economic, social, and health dynamics. Therefore, this research intentionally concentrated on the pre-pandemic period. Our results revealed that TFP in the PHC sector in Brazil decreased between 2015 and 2019. It was possible to note that three out of every four Brazilian municipalities experienced either stagnation or a decline in the TFP of primary healthcare, with more pronounced challenges in the Midwest and Northeast regions. Looking at the TFP elements, we could see a continuous drop in technical efficiency everywhere in the country, markedly in the Midwest and Northeast. Conversely, there was a considerable uptick in Brazil’s technological component. These results implied that there might have been advancements in PHC’s technological infrastructure, preventing even less favorable outcomes in the TFP indicator. We concluded that the productivity of primary healthcare in Brazil declined when the 2015 fiscal ceiling was implemented. This decrease in performance was evident in the sluggish growth rate of primary healthcare inputs, a diminution in vaccination coverage indicators, and an increase in hospitalizations for preventable causes. Given that health is a crucial component of social well-being, it is vital to highlight the need for comprehensive efforts to guarantee the effective operation and advancement of primary healthcare services, even during economic downturns.

Equity and efficiency of health resource allocation in the Chengdu-Chongqing Economic Circle of China.

This study aimed to evaluate the fairness and efficiency of health resource allocation (HRAE) in Chengdu-Chongqing Economic Circle after the new healthcare reform. This study also aimed to identify existing problems, providing empirical evidence for the government to formulate regional health plans scientifically and reasonably. The fairness of health resource allocation was analyzed using the Gini coefficient, Theil index, and agglomeration degree from population and geographical area perspectives. The three-stage data envelopment analysis and the Malmquist productivity index were used to analyze HRAE from static and dynamic perspectives. The Gini coefficient for population allocation in Chengdu-Chongqing Economic Circle was 0.066-0.283, and the Gini coefficient for geographical area allocation was 0.297-0.469. The contribution rate within a region was greater than that between regions, and health resources were mainly concentrated in economically developed core areas. The overall fairness of Chengdu Economic Circle was relatively better than that of Chongqing Economic Circle. Moreover, the adjusted mean technical efficiency was 0.806, indicating room for HRAE improvement in Chengdu-Chongqing Economic Circle. Stochastic Frontier Analysis found that different environmental variables have varying degrees of impact on HRAE. The adjusted mean total factor productivity change (Tfpch) was 1.027, indicating an overall upward trend in HRAE since the new healthcare reform. However, scale efficiency change (Sech) (0.997) limited the improvement of Tfpch. The fairness of health resources allocated by population was better than that allocated by geographical area. The unfairness of health resources mainly stemmed from intra-regional differences, with considerable health resources concentrated in core areas. Over the past 13 years, HRAE has improved but exhibited spatial heterogeneity and Sech-hindered productivity improvement. The study recommends strengthening regional cooperation and sharing to promote the integrated and high-quality development of the health and well-being in Chengdu-Chongqing Economic Circle.

Efficiency evaluation, regional technological heterogeneity and determinant of total factor productivity change in China’s healthcare system

Enhancing efficiency and productivity in countries’ healthcare systems is a global challenge. The Chinese government invested huge resources to improve the efficiency and productivity of the healthcare system across the country. To assess the success of the mission above, this research utilized DEA-SBM Meta frontier analysis alongside the Malmquist Productivity Index. These methodologies were employed to gauge Efficiency, production technology heterogeneity, and productivity of healthcare systems change across 31 mainland Chinese provinces and four distinct geographical regions throughout the study period spanning from 1997 to 2022. Results revealed that the mean efficiency score of China’s healthcare system is 0.7672. It indicates a growth potential of 23.28 percent in the operational efficiency of healthcare systems. The eastern region’s efficiency level (0.86917) is higher among all four regions. Zhejiang, Shandong, and Guangdong are the top three healthcare-efficiency performers. The technology gap ratio indicates that eastern regions witnessed a high TGR (0.9909), showing the country’s attainment of superior healthcare technologies. Beijing, Guangdong, Shanghai, Tianjin, and Zhejiang witnessed higher TGR values among all 31 mainland Chinese provinces. The total factor productivity index of the healthcare system witnessed a slight growth of 0.33%, with an average MI score of 1.0033. Efficiency change (EC) was found to be the main determinant of TFPC as technology change TC is less than EC. Moreover, the MI score of the Western region (1.033) is higher than the corresponding Eastern, northeastern, and central regions. Guizhou, Anhui, and Yunnan were found to be the top three performers in TFPC growth. Finally, the Kruskal–Wallis test confirmed the statistically significant difference among 4 Chinese regions for the healthcare system’s efficiency, TFPC, and TGR.