Malmquist Productivity Index Research Articles

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.

Analyzing changes in EU social inclusion using the global Malmquist productivity index

AbstractIn this paper, we use the global and the biennial Malmquist productivity indices for the Inverted Benefit‐of‐the‐Doubt model to analyze changes in EU social inclusion using data for the period 2011–2020. Our empirical results indicate that relatively more progress took place in EU social inclusion during the period 2015–2020, compared to the period 2011–2015. In addition, in the period 2011–2015, these improvements were possible mainly through the effect of efficiency change, while in the period 2015–2020, the main source of progress was the effect of the best‐practice change. In addition, we found that the “older” Member States achieved slightly faster progress rates, compared to the “new” Member States in the period 2011–2015, while the opposite was true for the period 2015–2020.

G20 countries’ progress on the 7th SDG under circular economy DEA model

The purpose of this paper was to analyze the performance of the G20 nations in terms of efficiency and productivity concerning achieving the seventh Sustainable Development Goal (SDG 7) of providing affordable and clean energy between 2010 and 2019 under a circular economy framework. The diagnostic tools to measure included the output-oriented Data Envelopment Analysis (DEA, SBM) to determine efficiency and the Malmquist Productivity Index (MPI) to measure productivity. In the DEA model, renewable energy is the primary energy source as inputs and outputs as total Greenhouse Gases (GHG) emissions, electricity consumption, and renewable energy consumption. The results indicated that the efficiency and productivity of developed and emerging countries towards the 7th SDG targets were heterogeneous throughout the analysis. The results showed that among the G20 countries that ranked as efficient were emerging countries (South Africa, Brazil, India, and China). Developed countries have more to gain in efficiency by designing strategies with sustainable development and environmental policies consistent with CE actions than emerging countries. In addition, since productivity gains increased more due to efficiency changes than technology gains, as indicated by the MPI analysis, it seems reasonable to infer that strengthening research and development of resource-efficient technologies could help to reach the 7th SDG faster by increasing productivity through adopting new technologies. In the short run, all countries could benefit from a multilateral effort to reduce climate change and GHG emissions if developed countries provided technological support to emerging countries and the latter offered carbon credits to the former in exchange for measures to mitigate the emissions resulting from their rapid economic growth driven by capital investment.

Impact of Islamicity on the productivity of conventional and Islamic banks in selected southeast Asian countries

This study provides a new understanding of how bank-specific characteristics, the macroeconomic environment, and Islamicity affect the productivity of conventional banks (CBs) and Islamic banks (IBs) in selected Southeast Asian countries. The data of 153 banks, collected between 2015 and 2020, were used, and the influence of the selected factors was investigated by using panel data approaches, as well as the data envelopment analysis-based Malmquist productivity index (DEA-MPI). In the first-stage analysis, bank productivity was measured by using total factor productivity changes (TFPC), and in the second-stage analysis, panel regression analysis was performed, specifically, multiple panel regression analysis, which employed pooled ordinary least squares, a fixed-effects model, and a random-effects model. Parametric and nonparametric (Mann–Whitney and Kruskall–Wallis) tests found that the IBs were more progressive than the CBs. The findings indicated that unlike the IBs, change in the productivity of the CBs was adversely affected by economic Islamicity, as well as legal and governance Islamicity, which indicated that macroeconomic and legal structures that leaned toward Islamic values adversely affected the CBs. Meanwhile, the IBs were likely to be structured in line with such values and thus can mitigate the adverse impact of various factors. Both groups were negatively affected by human and political rights Islamicity, which indicated the use of a setup that could not benefit from Islamic values. This finding lends credence to the arguments in the literature that IBs mirror CBs in practice to remain competitive in their pricing based on market principles. The IBs were found to benefit from international relations Islamicity, which bodes well for the competitiveness of new players against the ancient setup of CBs in the globalized world.

Productivity in the Bank: 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

City-level green growth accounting: Evidence from China's thirteen urban agglomerations

Cities play a pivotal role in achieving 'Carbon Peak' and 'Carbon Neutrality' objectives through the implementation of strategies aimed at mitigating environmental risks. While the environmental impacts of industrial production activities have been widely examined, the nuances of their internal structures remain obscure. This study delves into the industrial sector across the 'thirteen urban agglomerations (TUAs)' in mainland China, covering the years 2006–2016, by developing a comprehensive (source-specific and variable-specific) decomposition framework for Malmquist productivity index. The framework is utilized to discern whether efficiency changes or technological advancements drive productivity growth, considering input/output variables such as capital and labor. Findings show that the average annual environmental productivity gain during the examined period was 2.6 %, suggesting a general enhancement in productivity within TUAs' industrial sectors. A detailed breakdown of productivity changes indicates that a combined contribution of 1.8 % to environmental productivity growth stemmed from energy use and pollutant variables, with emissions of industrial sulfur dioxide being the most significant at 0.9 %. Conversely, the 'catch-up effect,' or environmental efficiency change, was negative (−0.2 %), indicating the TUAs' inability to emulate the productivity levels of more advanced areas. Industrial energy use and capital inputs were the primary contributors to this negative trend, each accounting for a −0.2 % impact. The results underscore the importance of facilitating technology transfers from more developed to less advanced regions, especially regarding renewable energy and capital investment, to bolster environmental performance and productivity in the TUAs' industrial sectors.

Measuring dynamic supply chain risks for the offshoring decision in the post‐COVID‐19 era: A longitudinal study

AbstractIn times of prolonged economic doldrums across the globe, multinational firms (MNFs) offshoring blunders can undermine their competitiveness in the marketplace. To help the MNF formulate a more resilient offshoring strategy and identify the most desirable offshoring destination, this article aims to identify dynamic risk factors that significantly hinder the efficiency of offshoring and then measure specific offshoring risks over time using two different versions of data envelopment analysis (DEA) models and Malmquist productivity index (MPI). After assessing the degree of risk resiliency of the offshoring host countries over extended periods and then conducting Tobit regression analysis to identify key factors that significantly influence offshoring risks, we found that the host country's logistics efficiency (i.e., logistics performance index [LPI]) and domestic market size were critical indicators of offshoring success in that country. Since low‐cost sourcing countries (LCCs) tend to have relatively low LPIs and smaller domestic market sizes, they are not attractive offshoring destinations. This finding defies conventional wisdom. This article is one of the first longitudinal studies to assess the comprehensive risk resilience of 87 different offshoring destinations (countries) during multiple periods (6‐year span).

Empirical evidence of the relationship between regulatory efficiency, market openness, and bank productivity in economies at different income levels: Evidence from selected Asian and MENA countries

Research background: Economic freedom plays a pivotal role in ensuring the progressive productivity of banks. It fosters a favorable economic climate and acts as a catalyst for the generation of innovative ideas. In addition, economic freedom allows new domestic and foreign entrants in the banking sector which leads to increased competition as well as wider range of product offerings and thus potentially affect bank efficiency. Purpose of the article: This study aims to identify the effects of regulatory efficiency and market openness in terms of economic freedom on the bank’s productivity at three income levels: lower-middle, upper-middle, and high-income economies. Methods: A sample of 15 countries are included in the study from differing income levels. The study uses the data envelopment analysis (DEA) based Malmquist productivity index (MPI) approach to measure banks’ productivity. This non-parametric approach measures the relative efficiency of banks by considering the production change while taking into account technical efficiency change and technological change in order to capture a comprehensive view over time. Then, regression analysis was performed utilizing the ordinary least squares (OLS) approach, fixed effect (FE), and random effect (RE) panel multiple regression estimation methods are utilized to measure economic freedoms and other determinants’ effect on banks’ productivity change over time. Findings & value added: The results show that banks in high-income economies are more productive and have higher growth rates than those in upper- and lower-income economies. Furthermore, starting, obtaining permits, and closing businesses under business freedom have a detrimental effect on banks’ output, whereas the effects of labor freedom on employing, managing, and supervising staff members have a substantial favorable impact on banks’ productivity. Moreover, financial freedom and investment freedom under the market openness dimension negatively influence banks’ productivity. Government intervention is required to introduce regulations that allow foreign countries to provide labor at lower wages, introduce tax allowances, and control inflation rates. Thus, the empirical results of this study will benefit regulators and policymakers in developing a system and plan to increase banks’ productivity based on indicators of business, labor, financial, and investment freedom.

The performance of Croatian hotel companies – DEA window and Malmquist productivity index approach

The hospitality industry operates in a dynamic and competitive environment whereefficiency and productivity are crucial for sustainable success. The main goal ofthis paper is to assess the dynamic changes in the efficiency and productivity oflarge and very large Croatian hotel companies and to investigate whether theirlocation influences these factors. It also aims to determine how resilient thecompanies are to macroeconomic shocks and to identify the causes of inefficiencyand productivity changes separately for each location. The analysis is conductedfor 70 large and very large hotel companies in total and separately for those incoastal and the continental Croatia from 2017 to 2022 using the Window DataEnvelopment Analysis and the Malmquist Productivity Index. The results show aslight decrease in relative efficiency in 2020 due to the impact of the COVID-19pandemic. The main cause of inefficiency for coastal hotel companies throughoutthe period is management performance and other exogenous factors. Conversely,the main cause of inefficiency for continental hotel companies shifted from non-optimal production size to management and other exogenous factors after 2020.Productivity declined between 2019 and 2020 due to the decline in technologicalchange for companies in both locations. Prior to 2020, coastal and continentalhotel companies followed a similar trend. While coastal hotels recovered faster in2021, continental hotels recovered more steadily and achieved higher productivityin 2022. This research provides valuable insights for hotel managers andacademics seeking to navigate the ever-changing field of hotel management.

A DEA Approach to Efficiency Analysis of Major Indian Airports

Airports’ technical effectiveness contributes to the expansion of the aviation industry. Airports offer enormous potential for any economy. There is a recent initiative by the government to privatize airport operations in India. Private airports need to be technically and operationally efficient in order to be profitable. Data Envelopment Analysis (DEA) is a frontier technique used to assess the technical efficiency of airports. This study uses DEA to evaluate the technical efficiency of 20 major airports in India. It considers the average spending of the airport, the size, the number of parking bays and the runways as the input variables, and average passenger, average revenue, average aircraft movements and freight as output variables. The result observed reflects an increasing return to scale in 10 airports, a decreasing return in 2 airports and a constant return to scale in 8 airports. Malmquist Productivity Index (MPI) applied to measure the productivity index of airports. This index is further broken down into three components: Technical change, efficiency effects and scale effects. DEA implies the highest operational efficiency for Bangalore, Chennai, Cochin, Delhi and Mumbai airports with greater than unity value. By benchmarking airports for target setting and operation mechanisms, this study will support airport management with better decision-making tools.

Can performance-based financing improve efficiency of health centers in Ethiopia? A Malmquist Productivity Index analysis

IntroductionThe Ethiopian government has introduced several healthcare financing reforms intending to improve efficiency. Piloting implementation of performance-based financing is one of these actions. The purpose of this research is to assess the efficiency of healthcare facilities that have implemented performance-based financing compared to those that have not.MethodsEfficiency was measured using a nonparametric data envelopment analysis and the Malmquist Productivity Index technique. Total factor productivity change, technical change, and technological change are compared across eight sampled healthcare facilities that are implementing performance-based financing and eight that are not in Ethiopia.ResultsHealth facilities implementing performance-based financing have a mean technical efficiency score of 64%, allowing for a potential 36% reduction in inputs without affecting outputs. Their scale efficiency is 88%, indicating a potential 12% increase in total outputs without expanding facilities. In contrast, facilities not implementing performance-based financing have a mean technical efficiency score of 62%, with a potential for 38% input reduction without affecting outputs. Their scale efficiency is 87%, suggesting a potential 13% increase in total outputs without scaling up facilities. Among the 16 healthcare facilities observed, seven experienced a decline in the mean total productivity, while one remained stagnant. The remaining eight facilities witnessed an increase in productivity. The healthcare facilities implementing performance-based financing showed a 1.3% decrease in mean total productivity during the observed period. Among them, five showed an increase and three showed a decrease in the total factor of productivity. The mean total factor of productivity of all healthcare facilities not implementing performance-based financing remained stagnant over the three-year period (2019–2021), with four showing an increase and four showing a decrease in total productivity.ConclusionsThe study concludes that implementing performance-based financing did not improve productivity levels among healthcare facilities over three years. In fact, productivity decreased among the facilities implementing performance-based financing, while those not implementing it remained stagnant. This shows health facilities that implement performance-based financing tend to utilize more resources for similar outputs, contradicting the anticipated efficiency improvement.