Inefficient Countries Research Articles

Unlocking Global Innovation

In the dynamic landscape of global innovation, researchers increasingly adopt an integrated approach using nonparametric and regression techniques. This study highlights the significance of this method in enabling countries to understand external factors shaping innovation outcomes. Data Envelopment Analysis (DEA) serves as a robust framework for evaluating innovation efficiency, helping countries optimize their innovation processes by scrutinizing resource utilization and identifying areas for improvement. Complementing DEA, Tobit regression analysis offers insights into the nuanced influence of external drivers on innovation. The findings reveal a mixed landscape: while high-income countries dominate innovation efficiency, some lower-middle and low-income countries show notable proficiency. China, classified as an upper-middle-income country, emerges as the most referenced benchmark. Based on benchmarking, inefficient countries can enhance their innovation policies and strategies, helping to bridge the global innovation gap. Despite all input capabilities showing a negative correlation with innovation efficiency, all output variables exhibit a positive correlation. Notably, there was no association between R&D and innovation efficiency in 2020, highlighting the need for judicious use of innovation inputs to avoid wastage. Additionally, the Tobit regression model exhibits a remarkable R-squared value of 0.8523, indicating that the 16 independent factors account for 85.23% of the variation in the innovation efficiency. Amidst technology-driven transformations, leveraging nonparametric analysis methodologies is essential for organizations aiming to thrive in the global innovation arena. This study highlights the crucial role of DEA in assessing innovation efficiency and emphasizes the importance of incorporating nonparametric analysis and regression techniques into strategic decision-making processes to formulate effective innovation policies.

Application of DEA Models to Develop Strategies for Improving the Energy Efficiency of National Economies: Focusing on SDGs and Best Practices in European Countries

Objective: This study aims to develop a strategy for improving the energy efficiency of national economies through the application of DEA (Data Envelopment Analysis) models. The research focuses on adopting the best practices from European countries in the context of SDGs. Theoretical Framework: The research is grounded in the framework of sustainable development and energy efficiency, focusing on the UN Sustainable Development Goals (SDG 12). DEA models are utilized to assess energy efficiency across various European economies, considering economic, environmental, and energy-related factors. Method: DEA models were applied to assess energy efficiency by analyzing input variables such as energy intensity, CO₂ emissions, and energy consumption. The model used a comparative analysis of 38 European countries, with special attention to the weights (λ) in the VRS model, allowing for variable returns to scale. The data were sourced from Eurostat and the World Bank. Results and Discussion: The results indicated that countries like Ireland and Albania serve as key reference units for Ukraine, highlighting the effectiveness of transitioning to renewable energy sources and reducing dependence on fossil fuels. The analysis demonstrated that inefficient countries could improve their performance by following the strategies of their reference units, specifically in reducing energy consumption and emissions. Research Implications: The study provides practical insights into how less efficient countries, like Ukraine, can enhance their energy policies by adopting successful practices from European nations, ultimately contributing to global sustainability goals. Originality/Value: This research contributes to the literature by offering a structured methodology for enhancing energy efficiency in national economies through DEA modeling. It emphasizes the significance of renewable energy in sustainable development and presents a comparative framework applicable to a broad range of countries.

USING DATA ENVELOPMENT ANALYSIS TO EVALUATE THE EFFICIENCY OF EUROPEAN UNION COUNTRIES IN INFORMATION TECHNOLOGIES

In an environment where international competitive conditions are becoming increasingly difficult in parallel with the changes in science and technology, the importance of developments in information technologies is increasing day by day. This study aims to specify the relative efficiency of European Union countries in the field of information technologies using Data Envelopment Analysis. In this direction, four inputs and four outputs are determined. According to both the CCR and BCC models, Austria, Croatia, Czechia, France, Germany, Lithuania, Poland, Slovakia, Slovenia, and Spain are the countries that cannot show 100% performance in obtaining information technology outputs with the information technology inputs determined in the study. While Belgium and Poland are effective in the BCC analysis, they are not effective in the CCR analysis. In this case, Belgium and Poland are technically effective in BCC analysis, but can not achieve scale efficiency. Input and output rates of inefficient countries are interpreted by comparing them with best practice benchmarks.

Green efficiency strategy considering cyclical relationships among CO2 emissions, green patents, and green bonds

Globally increasing concerns on climate change have garnered considerable attention toward green investments. Although the effects of green investments have been investigated, their productivity remains largely unexplored. This study proposes an initial discussion of green efficiency based on the cyclical relationship among green investments, technology, and national-level performance. This study applies a three-stage data envelopment analysis to compare green efficiency of 19 countries based on carbon dioxide emissions, green patents, and green-bond issuance data of 12 years starting from 2010 when national green-bond issuance was initiated. We use a logistic regression to derive policy implications by analyzing major factors affecting green efficiency. The results reveal that no country is efficient across all stages. Overall, the finding reveals which stage each country should focus on to improve green efficiency; suggests benchmarks and green efficiency strategies for inefficient countries; and highlights the appropriate level of research and development (R&D) expenditure and adoption support for solar/wind energy as part of the technology support policy. As the national green efficiency level is derived in stages, our approach contributes to forming green efficiency strategies at the national level in three stages. Moreover, this study presents the policy implications related to R&D expenditures and technology support to address the limited understanding of green efficiency management.

Assessing the vulnerability of oil-dependent countries in Europe

In this article, we attempt to assess the vulnerability of European oil-dependent countries, using the Weighted Russell Directional Distance Model, which provides a composite index and allows for the analysis of adjustments in different proportions for the evaluation factors to reduce oil vulnerability. Our empirical findings show heterogeneous degrees of vulnerability to oil across countries due to country-specific characteristics. More precisely, Slovakia, the Czech Republic, Sweden, France, the Netherlands, and Spain emerged as the least oil-vulnerable countries. Conversely, Hungary, Poland, and Portugal performed poorly regarding oil supply security. Our productivity analysis indicates that inefficient countries that experienced productivity gains primarily achieved them through technological progress, with the Shannon-Wiener index playing a crucial role. These findings align with the EU's strategy of diversifying supply sources.

Assessing sustainable economic development efficiency: A DEA approach

Background: Widely used in efficiency analysis, data envelopment analysis (DEA) found its use in country efficiency measurement concerning the achievement of desired values of macroeconomic indicators, most often the goals from the category of economic growth. Purpose: The objective of the paper is to examine the possibility of DEA application in sustainable development research. Methodology: The analysis was conducted using a non-oriented DEA model with variable return-to-scale in a group of 26 EU countries and Serbia, as a membership candidate. Four variables were used as input variables: inflation rate, unemployment rate, poverty rate and ecological footprint per capita. Three variables were used on the outputs side: inequality-adjusted human development index, GDP per capita and ecological deficit or reserve per capita. The annual data was collected for the time period of eight years, form 2010 until 2017. Findings: Results show that Finland is the only country efficient throughout the entire period. Average efficiency close to maximum was achieved by the Netherlands. Significant efficiency was achieved by Luxembourg, Germany and Sweden among countries that were EU members before 1995. Among other EU countries, Slovenia and Hungary achieved efficiency on a nearly maximum level. Also, efficient in more than half of the observed years were Cyprus and Romania. The most inefficient countries were the three Baltic countries: Lithuania, Latvia, and Estonia. Among the EU member countries before 1995, Italy and Portugal were the most inefficient. Concerning EU candidate Serbia, the efficiency achieved was generally close to average. Limitations: The performed analysis can answer the question of which country is the most efficient on the way to sustainability. However, the DEA method cannot show whether a country is developing absolutely sustainably or unsustainably, because DEA is a relative method and can only measure efficiency compared to the other units.

Determining Efficiency of 15 OECD Countries Coping with Covid-19 using Data Envelopment Analysis after 2 Years of Pandemic

Covid-19, emerged in Wuhan, a city of China, at the date of December 2019, it spread to the entire world soon and then by the World Health Organization (WHO) accepted as a pandemic. Today, still the coping with Covid-19 is the one of the significant topics of countries. In this study, the relative efficiencies of 15 OECD countries for coping with the pandemic is analyzed with Data Envelopment Analysis (DEA). Current health expenditure (% of GDP), Nurses and midwives (per 1 thousand people), Hospital beds (per 1 thousand people), Physicians (per 1 thousand people) variables used as inputs; Number of Total Cases (per 1 million people), Number of Deaths (per 1 million people) and Number of Tests (per 1 million people) variables used as outputs. Output oriented Charnes, Cooper and Rhodes (CCR) and Banker, Charnes and Cooper (BCC) DEA models are used, scale efficiency values are determined and potential improvement suggestions are given for inefficient countries. Austria, Mexico, South Korea, Spain and Türkiye are found to be both relative technical, total and scale efficient. It is also concluded that inefficient countries must use their input variables efficiently and number of Covid-19 tests is important for a country’s efficiency against Covid-19.

Determinants of the Efficiency of Electricity Generation in Latin America and Caribbean Countries Using a Cragg’s Regression Model

Measuring and understanding the evolution of the electricity generation efficiency sector is a relevant task for policymakers. This study focuses on assessing the determinants of electricity generation efficiency across 24 countries in Latin America and the Caribbean between 2000 and 2020. A hurdle model was employed to account for the censored nature of the dependent variable. The findings show a positive impact of opening up the electricity sector in fully efficient countries. Market liberalization and the involvement of privately owned power plants contribute to efficiency gains in inefficient countries. Additionally, the tariff protectionism level exhibits positive effects for completely efficient and inefficient countries. These results provide valuable insights, as less-efficient countries can glean strategies from their more efficient counterparts to enhance their electricity generation efficiency.

Efficiency Analysis of Middle-Income Countries in Terms of Health Indicators for the Covid Process

Systems transform their current inputs into outputs to achieve their goals and objectives. Efficiency analysis is used to describe the degree to which a system achieves its goals using its resources. Pandemics similar to the Covid process may recur, and countries must use their existing resources more effectively in these struggles. The scope of this study was to evaluate the struggle of middle-income countries with Covid-19 within the scope of certain health indicators according to the World Bank's income classification by using the DEA, one of the methods used to measure the effectiveness of health systems. The ratio of GDP devoted to health services, the number of patient beds, the number of doctors per thousand population, the number of nurses and midwives per thousand population, and finally, the amount of health expenditure per capita were selected as the input variables in the study. The number of people recovering from Covid-19 disease per 100,000 people, total cases per 1 million people, total deaths per 1 million people, and total number of tests per million people were selected as the output variables in the study. The VZA input-oriented CCR model was used in the study. The reasons for the inefficiency of inefficient countries have been identified. In order for these countries to be located on the effective border, the targeted values have been revealed. Based on the efficient countries, potential improvements are made in the input values of the inefficient countries and the input values that can increase their efficiency are calculated. As a result of the study, 18 countries out of 47 countries were located in the effective border. Finally, the reasons for the inefficiency of the countries below the efficient frontier were calculated using the multiple linear regression analysis method, and the suggestions for necessary corrections were presented.
 The VZA input-oriented CCR model was used in the study. The reasons for the inefficiency of inefficient countries have been identified. In order for these countries to be located on the effective border, the targeted values have been revealed. Based on the efficient countries, potential improvements are made in the input values of the inefficient countries and the input values that can increase their efficiency are calculated. As a result of the study, 18 countries out of 47 countries were located in the effective border. Finally, the reasons for the inefficiency of the countries below the efficient frontier were calculated using the multiple linear regression analysis method, and the suggestions for necessary corrections were presented.

Achieving Net Zero—An Illustration of Carbon Emissions Reduction with A New Meta-Inverse DEA Approach

To achieve the goal of limiting global warming to 1.5 °C above preindustrial levels, net-zero emissions targets were proposed to assist countries in planning their long-term reduction. Inverse Data Envelopment Analysis (DEA) can be used to determine optimal input and output levels without sacrificing the set environmental efficiency target. However, treating countries as having the same capability to mitigate carbon emissions without considering their different developmental stages is not only unrealistic but also inappropriate. Therefore, this study incorporates a meta-concept into inverse DEA. This study adopts a three-stage approach. In the first stage, a meta-frontier DEA method is adopted to assess and compare the eco-efficiency of developed and developing countries. In the second stage, the specific super-efficiency method is adopted to rank the efficient countries specifically focused on carbon performance. In the third stage, carbon dioxide emissions reduction targets are proposed for the developed and developing countries separately. Then, a new meta-inverse DEA method is used to allocate the emissions reduction target to the inefficient countries in each of the specific groups. In this way, we can find the optimal CO2 reduction amount for the inefficient countries with unchanged eco-efficiency levels. The implications of the new meta-inverse DEA method proposed in this study are twofold. The method can identify how a DMU can reduce undesirable outputs without sacrificing the set eco-efficiency target, which is especially useful in achieving net-zero emissions since this method provides a roadmap for decision-makers to understand how to allocate the emissions reduction targets to different units. In addition, this method can be applied to heterogeneous groups where they are assigned to different emissions reduction targets.

Efficiency Evaluation of European Countries Based on Case Fatality Rate of COVID-19 Using Data Envelopment Analysis

The COVID-19 pandemic appeared in China on 31 December 2019, and it spread fast in every part of the world, especially, in European countries like Italy and France, consequently, the search for a resolution to this pandemic in all these countries should also be taken into account. The current study aimed to evaluate the efficiency of European Countries based on the case fatality rate of COVID-19, The sample spans 30 countries, the analysis made recourse to Data Envelopment Analysis, the study used population density and total cases as input indicators and case fatality rate (CFR) as output indicator. The results demonstrate that of 30 countries analyzed, only 6 proved efficient. The average efficiency of inefficient countries is 0.372. Greece achieved the least efficiency rate compared to other European countries. The highest case fatality rate has been registered in Belgium, the lowest case fatality rate has been registered in Monaco. We engaged in a year-long battle with a virus that has destroyed this world, that has caused pain, loss, and frustration and that has cost so many lives.

How Latin American multinational companies’ institutional capabilities influence ownership in cross-border acquisitions

Objective: Multinational Companies (MNCs) can learn from their experience in host countries and develop an ability to deal with specific institutional inefficiencies. We advance that MNCs’ institutional capabilities, or the capabilities to deal with institutionally underdeveloped milieus, will likely lower the ownership requirements in subsequent deals. Method: Using regressions with a secondary dataset of 1,686 cross-border acquisitions (CBA) made by Latin American firms worldwide, we investigate how the MNCs’ priorly-acquired capabilities of operating in countries with underdeveloped regulatory quality, less effective rule of law, and lower corruption control lower the ownership acquired in subsequent acquisition deals. Main Results: We show that MNCs with experiences with CBA in countries with poor institutional contexts learn how to work in those contexts. Hence, these MNCs build capabilities that make them more likely to take a lower ownership stake in future CBAs. Relevance/ Originality: There is still much to be understood regarding the extent to which the knowledge developed in one country could be extrapolated and used in another country with similar problems. We delve into this matter with an institution-based view. Theoretical/ Methodological Contributions: This study thus contributes to a better understanding of the effect of MNCs’ institutional capabilities for operating in institutionally inefficient countries on the ownership stakes required.

Analytics Framework for Comparing National Performance Achievements in International Mathematical Olympiads

This study measures and analyzes the performances of the participating nations at the International Mathematical Olympiad (IMO). A country’s success at the IMO is evaluated by the number of gold, silver, and bronze medals won. To measure and compare the performances of the countries, the data envelopment analysis approach is employed and all countries that have won at least one medal have been included in our dataset. As measures for the inputs, two macro-level determinants that can support the effort made by a country are considered: population size and gross domestic product (GDP) per capita. Our findings indicate a mean level of technical efficiency for the nations analyzed. The results suggest that, on average, the inefficient countries in the sample could achieve improved results by increasing the number of outputs produced while maintaining the same level of effort spent.

The Efficiency of Educational and Healthcare public expenditures in Kosovo: A Data Envelopment Analysis Technique

This paper evaluates the performance and efficiency of the government public expenditure in the education and health sectors in the emerging economies context, specifically comparing Kosovo with the Western Balkan countries. The indicators of education and health sectors were used to assess a Public Sector Performance Index (PSP) and the Public Sector Efficiency Index (PSE). Also, this study uses the nonparametric method DEA (Data Envelopment Analysis) to evaluate the input-output oriented efficiency. This study finds that education score of performance ranges from 0.43 which is the minimum to 1.48 which is the maximum. And in the health sector, the PSP score ranges from 0.81 which is the minimum to 1.09 which is the maximum. Kosovo ranks 41st out of 42 countries in this sample, in terms of the education sector, with a performance index of 0.67, which is 37% below the average of 1.00, whilst in terms of the health sector it ranks 39th out of 42 countries in the sample.In the analysis of the input output efficiency model in the education sector, the results show that the countries included in the study achieve an efficiency of 76.69 and it means that countries can reduce relevant public expenditure by 23.3% and maintain the same level of PSP in the education sector. Kosovo is assessed in this analysis as an inefficient country. The value of the input-oriented index is 40.24, which means that Kosovo can achieve the same level of performance in the education sector by using 60% less relative public expenditure, whilst, on the other hand, the input-output efficiency results for the health sector show that the efficiency score for countries is 47.64, and denotes that the countries in the sample could reduce 53% in health expenditure to achieve the same performance in the health sector. Thus, Kosovo compared to other countries in the sample is within the limits of production opportunities and uses public expenditure on health and education inefficiently.

Is the Cohesion Policy Efficient in Supporting the Transition to a Low-Carbon Economy? Some Insights with Value-Based Data Envelopment Analysis

We evaluated the implementation of European Regional Development Funds (ERDF) devoted to Thematic Objective (TO) 4 in 23 beneficiary European Union (EU) Member States (MS). The assessment of each country was made through the value-based data envelopment analysis (VBDEA) approach in three phases. In the first phase, it was possible to conclude that 43% of the MS were efficient in the implementation of the ERDF devoted to a low-carbon economy (LCE), and the reasons for their efficiency were mainly explained by their execution rate. After running the second phase for the inefficient countries, it was possible to obtain the improvements that must be made for these countries to “emulate” their peers at the efficient frontier. Finally, in the third stage, we incorporated political concerns in the evaluation of the implementation of the ERDF by including constraints on the ranking order of the weights. A robustness analysis was also carried out, according to which it was found that only 22% of the MS under evaluation remained surely efficient for tolerances of δ = 5% and δ = 10%, with Spain being the most robust country. Other countries such as Romania (surely inefficient for δ = 5%), Hungary, and the Czech Republic (the most inefficient) did not manage to implement these funds efficiently. Considering these findings, the EU needs to further promote policies that ensure economic benefits from investing in an LCE, specifically for countries with fewer resources, while also providing them with better financial conditions and know-how.

Environmental efficiency, irreversibility and the shadow price of emissions

Assessing the production of goods and services while minimizing the damage to the environment is a key component to advance sustainable development at national and global levels. The nonparametric estimation of lower and upper bounds on shadow prices of pollutants is undertaken to support the design of policies promoting environmental efficiency in the presence of asymmetry in adjusting productive and abatement capital capacity. This framework is applied to the pulp and paper sector of 39 countries for 1996-2009, and finds that the USA, China and Ireland are the most environmentally inefficient countries in the pulp and paper sector. The adjustment costs associated with net investment and disinvestment are found to be asymmetric. For those nations where the shadow price of CO2 is lower than the carbon tax, there is still an opportunity to abate emissions further. Results on complementarity or substitutability between pollutants are in general inconclusive.

A Two-pronged Evaluation of Green Efficiency of the BRICS Economies

This study combines two-pronged approaches of Data Envelope Analysis, (DEA) Super radial CCR-1 and the Principal Component Analysis(PCA) from 2010 to 2019 to perform a critical evaluation of the efficiency of the BRICS of the economies to provide a scientific basis for ensuring efficient development of the BRICS. The findings reveal the Republic of South Africa is the most efficient economy, scoring 52.3% placing first, followed by Russia, which scored 38.5% placing second. Brazil is ranked third with 22.6%. India scores 3.7 percent placing fourth, and ultimately China is the most inefficient country among the BRICS Economies with a score of 1.71 %. The results of the super radial projection show that access to clean cooking, Brazil derives the percentages of 157.4%, China 67.3%, India 199.5%, Russia 251.1%, RSA 199.9%. This connotes the pattern of sustainable consumption or otherwise pathways of these countries. On the other hand, the PCA analysis proved similar results in the components loadings, where renewable energy consumption loaded as an outlier, implying increased renewable consumption among the BRICS nations. Renewable capacity is equally loaded with higher scores plus investment in energy by the private sector. South Africa loaded as an outlier from the score plots, signifying South Africa as the most efficient country among the BRICS nations. China and India are loaded as inefficient countries. The varimax rotation had two significant variables in PCA3: investment in Energy by the private sector and fossil fuels consumption. This means green public financial management and sustainable finance are important to ensuring efficiency among the BRICS nations. This study sought to present empirical findings and advance public knowledge of the concerns about climate change and efficiency consumption and contributes to an informed policy implementation regarding sustainable development. Keywords: DEA, PCA, BRICS, Efficiency, Sustainable Consumption. Investment. JEL Classification: Q4, Q47, Q56, Q58

Global innovation efficiency assessment of EU member and candidate countries via DEA-EATWIOS multi-criteria methodology

Globalization and changing levels of competition highlight the importance of innovation and innovation management, as well as their efficiency, as a critical economic factor for countries. In fact, the perspectives on innovation effectiveness are seen as essential success factors in achieving economic prosperity and competing in the markets. Global innovation efficiency, which is vital for both the European Union member and candidate countries and one of the determinants of the competitive process throughout the world, helps the economies catch up with the developing and changing technology while revealing the innovation perspectives of the countries. The aim of this study is to examine and compare the global innovation efficiency that can be considered as crucial economic factor for European Union member and candidate countries by using the Global Innovation Index (GII), published jointly by Cornell University and WIPO in 2020 in terms of innovation inputs and outputs. Data Envelopment Analysis (DEA) and Efficiency Analysis Technique with Input and Output Satisficing (EATWIOS) methods are applied for comparison. According to the study's findings, the Netherlands, Germany, and Sweden are obtained as the most important countries in terms of global innovation efficiency. Nevertheless, Lithuania, Greece, and North Macedonia have been ranked as the last three inefficient countries. Further, some suggestions are made to eliminate the deficiencies of non-innovative countries.

The Robust Efficiency Estimation in Lower Secondary Education: Cross-Country Evidence

In this study, we assessed the efficiency of compulsory lower secondary education. We selected three variables that may significantly affect students’ performance in a particular country. First, we assumed that student scores achieved in PISA testing determine the number of monetary funds spent on these three variables, specifically student–teacher ratio, class size, and the annual number of hours spent in school. Second, we evaluated the efficiency of education in a sample of 24 different OECD countries, comparing the students’ performance in PISA 2018. Third, we used the two-stage data envelopment analysis with a bootstrapping procedure for estimating technical efficiency scores. Finally, we applied OLS and quantile regression, where our regression estimates in both models showed a positive effect of GDP per capita on students’ achievement across countries. The positive impact of GDP per capita was significant only for the least efficient countries. Conversely, the level of impact of parental education was much stronger and more positive for the inefficient countries and proved to be negative for more efficient countries.

A slack-based DEA analysis for the world cup teams

PurposeThis paper aims to assess the efficiency levels of World Cup teams via the slack-based data envelopment analysis (DEA) approach, which contributes to filling an important gap for performance measurement in football.Design/methodology/approachThis study focuses on a comparative analysis of the past two World Cups. The authors initially estimate the efficiency of the World Cup teams via the slack-based DEA approach, which is a novel approach for sports performance measurement. The authors also present the conventional DEA results to compare results. The authors also include improvement ratios, which provide significant details for inefficient countries to enhance their efficiency. Besides, the authors include effectiveness ratings to present a complete performance overview of the World Cup teams.FindingsAccording to the analysis results of the slack-based DEA approach, titleholder Germany and France are found as efficient teams in the 2014 and 2018 World Cup, respectively. Besides, Belgium and Russia recorded the highest efficiency improvement in the 2018 World Cup. The novel approach for sports performance measurement, the slack-based DEA approach, significantly overlaps with the actual performance of teams.Originality/valueThis study presents novelty in football performance by adopting the slack-based DEA with an undesirable output model for the performance measurement of the World Cup teams. This empirical analysis would be a pioneer study measuring the performance of football teams via the slack-based DEA approach.