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Quantitative Analysis and DEA Modeling in Applied Economics
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Quantitative Analysis and DEA Modeling in Applied Economics

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Financial Mathematics".

Deadline for manuscript submissions: closed (31 August 2022) | Viewed by 62351

Special Issue Editors

Prof. Dr. Anna Firsova

E-Mail Website
Guest Editor
Faculty of Economics, Saratov State University, 410012 Saratov, Russia
Interests: data envelopment analysis; quantitative analysis; innovations; R&D, regional development; finance
Special Issues, Collections and Topics in MDPI journals
Dr. Galina Chernyshova

E-Mail Website
Guest Editor
Faculty of Computer Science and Information Technologies, Saratov State University, 410012 Saratov, Russia
Interests: mathematical modeling in economy; data mining; data envelopment analysis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Quantitative Analysis is an important tool for assessing the efficiency of economic processes. Mathematical modeling based on Data Envelopment Analysis provides the measurement of the relative efficiency of decision making units. These approaches allow to increase the objectivity and the scientific validity of decision making in applied economics.

This Special Issue aims to contribute the theory, methodology, analysis, applications, and strategies of the modern evaluation approaches that may bring novel insight into the quantitative analysis methods in the economy.

Original theoretical and empirical articles containing analysis and interpretation of quantitative techniques for a wide range of problems in applied economics are accepted. Topics of interest include but are not limited to mathematical models using in business, finance, agriculture, education, energy industry, transport, culture, healthcare, regional and spatial development, public administration, and others.

Prof. Dr. Anna Firsova 
Dr. Galina Chernyshova
Guest Editors

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Keywords

  • Quantitative analysis
  • Decision making methods
  • Data analysis
  • Data Envelopment Analysis
  • Optimization models
  • Statistical analysis
  • Econometrics modelling
  • Data Mining
  • Performance measurement
  • Making predictions

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Published Papers (16 papers)

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22 pages, 4611 KiB  
Article
Modelling the Impact of World Oil Prices and the Mining and Quarrying Sector on the United Arab Emirates’ GDP
by Ahmad Al Humssi, Maria Petrovskaya and Milana Abueva
Mathematics 2023, 11(1), 94; https://doi.org/10.3390/math11010094 - 26 Dec 2022
Cited by 2 | Viewed by 5955
Abstract
In this research, we aimed to model the impact of world oil prices on the gross domestic product of the United Arab Emirates (UAE). The objective of the study was to determine the transmission mechanism of the influence of the changing oil price [...] Read more.
In this research, we aimed to model the impact of world oil prices on the gross domestic product of the United Arab Emirates (UAE). The objective of the study was to determine the transmission mechanism of the influence of the changing oil price within the macroeconomic indicators of the UAE. In this study, we analysed the impact of world oil prices and the crude oil sector on economic growth in the UAE for the period of 2001–2020 by applying ADF, OLS, ARDL, and Granger causality techniques. The results also showed the direct impact of the changes in oil prices on the GDP of the UAE in the short and long terms; in other words, a decline in oil prices could pose a threat to the economic security of the UAE in the long term if appropriate corrective measures are not taken. In order to avoid these negative consequences of the oil price crisis, in this study, we emphasize that the only alternative to exporting oil is to diversify economic sources for long-term development and increase the efficiency of non-oil sectors. Full article
(This article belongs to the Special Issue Quantitative Analysis and DEA Modeling in Applied Economics)
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19 pages, 969 KiB  
Article
Personal Traits and Digital Entrepreneurship: A Mediation Model Using SmartPLS Data Analysis
by Abu Elnasr E. Sobaih and Ibrahim A. Elshaer
Mathematics 2022, 10(21), 3926; https://doi.org/10.3390/math10213926 - 23 Oct 2022
Cited by 39 | Viewed by 7399
Abstract
Technological advancements have created a plethora of opportunities for entrepreneurs to develop and extend their business operations. Hence, internet has promoted to the emergence of digital entrepreneurship as a growing form of entrepreneurship among many entrepreneurs, especially digital natives. This research examines to [...] Read more.
Technological advancements have created a plethora of opportunities for entrepreneurs to develop and extend their business operations. Hence, internet has promoted to the emergence of digital entrepreneurship as a growing form of entrepreneurship among many entrepreneurs, especially digital natives. This research examines to what extent personal traits of digital natives’ impact on their digital entrepreneurship intention. The research examined the direct impact of the big five personal traits, i.e., openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism, on digital entrepreneurship intention and the indirect impact through personal attitude. For this purpose, a pre-examined questionnaire was directed to senior students in computer sciences and information technology colleges at public universities in Kingdom of Saudi Arabia (KSA). The results of structural equation modeling using SmartPLS (version 4) confirmed a direct positive and significant impact of the big five personal traits on personal attitude. However, the results revealed that the impact of the big five personal traits (except agreeableness) on digital entrepreneurship intention were positive but insignificant. Additionally, a mediating effect was confirmed for personal attitude in the link between personal traits and digital entrepreneurship intention among senior students in KSA higher education. The results contributed to the research gap in relation to personal traits and its impact on personal attitude and ultimatly on digital entrepreneurship intention, especially among digital natives. Several impactions were merged and discussed for scholars, policy makers and educators in higher education institutions. Full article
(This article belongs to the Special Issue Quantitative Analysis and DEA Modeling in Applied Economics)
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23 pages, 2271 KiB  
Article
Structural Equation Modeling-Based Multi-Group Analysis: Examining the Role of Gender in the Link between Entrepreneurship Orientation and Entrepreneurial Intention
by Abu Elnasr E. Sobaih and Ibrahim A. Elshaer
Mathematics 2022, 10(20), 3719; https://doi.org/10.3390/math10203719 - 11 Oct 2022
Cited by 7 | Viewed by 3275
Abstract
This research examines the role of gender in the link between entrepreneurship orientation and entrepreneurial intention. More exactly, the research examines the differences between male and female senior students in relation to the effect of risk-taking, innovativeness, and pro-activeness on their entrepreneurial intention. [...] Read more.
This research examines the role of gender in the link between entrepreneurship orientation and entrepreneurial intention. More exactly, the research examines the differences between male and female senior students in relation to the effect of risk-taking, innovativeness, and pro-activeness on their entrepreneurial intention. For this purpose, a quantitative research method was conducted through a self-administered questionnaire to a sample of students at King Faisal University, Kingdom of Saudi Arabia. The results of structural equation modeling (SEM) by AMOS software showed a significant positive direct impact of risk-taking on entrepreneurial intention and a significant positive indirect impact through innovativeness and pro-activeness for the structural model of male and female. In the comparison between the two groups using multi-group analysis, the results showed that impacts of risk-taking and innovativeness on entrepreneurial intention were found to be positive and significant in the two groups and the differences in p-value were significant. This means that there are significant differences between males and females in relation to the impact of risk-taking and innovativeness on entrepreneurial intention. These differences were because males were found to be more risk-taking than females whereas females were found to be more innovative than males. On the other side, the results confirmed no significant differences between the two groups in relation to the effect of pro-activeness on entrepreneurial intention. The findings of the study have noble implications for scholars and policymakers, which we have discussed and elaborated on. Full article
(This article belongs to the Special Issue Quantitative Analysis and DEA Modeling in Applied Economics)
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23 pages, 1324 KiB  
Article
The Efficiency of National Innovation Systems in Post-Soviet Countries: DEA-Based Approach
by Svetlana V. Ratner, Svetlana A. Balashova and Andrey V. Lychev
Mathematics 2022, 10(19), 3615; https://doi.org/10.3390/math10193615 - 2 Oct 2022
Cited by 7 | Viewed by 2625
Abstract
The efficiency of the national innovation system (NIS) is widely considered to be the most important factor of innovation-based economic growth. Using the wide spectrum of different metrics for measuring the efficiency of NIS, modern studies focus mainly on high-income or upper-middle-income countries, [...] Read more.
The efficiency of the national innovation system (NIS) is widely considered to be the most important factor of innovation-based economic growth. Using the wide spectrum of different metrics for measuring the efficiency of NIS, modern studies focus mainly on high-income or upper-middle-income countries, while the effectiveness of the NIS in post-Soviet countries has not been studied enough. The post-socialist transformation has led to different models of economic development in these countries, which can be divided into three groups: a group with developed European institutions, a group with a focus on the European path of development, and, finally, a group of countries with an economic model of “state capitalism”. These models formed the trajectory of innovative development. The main purpose of this study is to compare the performance of NIS in post-Soviet countries and to find out whether differences between development institutions can help explain differences in the performance of NIS. The study applies the DEA methodology and considers NISs as homogeneous economic agents, which transform the same types of inputs (knowledge gained using human and financial resources) into the same types of positive outcomes (innovative products and services). The results of a study conducted on data for the period 2011–2018 show that there is no evidence to support the hypothesis that EU institutions or the type of economic model of the country directly relate to the effectiveness of the NIS. The example of Kazakhstan shows that NIS can be effective, even with strong state intervention in the economy. Taken together, the results of the paper suggest that the structure of R&D expenditures by sources of funding and types of research plays an important role in the formation of effective NIS. Full article
(This article belongs to the Special Issue Quantitative Analysis and DEA Modeling in Applied Economics)
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19 pages, 1227 KiB  
Article
The Mediating Effects of Green Innovation and Corporate Social Responsibility on the Link between Transformational Leadership and Performance: An Examination Using SEM Analysis
by Abu Elnasr E. Sobaih, Hassane Gharbi, Ahmed M. Hasanein and Ahmed E. Abu Elnasr
Mathematics 2022, 10(15), 2685; https://doi.org/10.3390/math10152685 - 29 Jul 2022
Cited by 19 | Viewed by 3691
Abstract
Since the inauguration of the United Nations Sustainable Development Goals (UNSDGs), environmental performance and sustainability have become more important to decision makers, scientists and leaders of organizations than before. In response to this, leaders of different organizations spend all endeavors conserving resources and [...] Read more.
Since the inauguration of the United Nations Sustainable Development Goals (UNSDGs), environmental performance and sustainability have become more important to decision makers, scientists and leaders of organizations than before. In response to this, leaders of different organizations spend all endeavors conserving resources and ensuring environmental sustainability. In this context, transformational leaders have the capacity to ensure the green performance of their organization. The purpose of this study is to test the link between green transformational leadership (GTL), green innovation (GI), corporate social responsibility (CSR) and green performance (GP) in the hotel industry in the Kingdom of Saudi Arabia (KSA). The study empirically tests the mediating effect of GI and CSR on the link between GTL and GP. The study used a quantitative research method via a pre-test instrument, self-distributed and collected from employees in large hotels at different regions of the KSA. The findings from 732 valid responses, analyzed with structural equation modeling (SEM) showed that GTL had a significant effect on GI (β = +0.72, t-value = 14.603, p < 0.001), CSR (β = +0.58, t-value = 8.511, p < 0.001) and GP (β = +0.17, t-value = 2.585, p < 0.001). Moreover, GI and CSR had a direct positive effect on GP (β = +0.10, t-value = 2.866, p < 0.01 and β = +0.61, t-value = 4.358, p < 0.001, respectively). GI had a partial mediation effect (p = 0.048 < 0.05) on the link between GTL and GP. On the other hand, CSR had a perfect mediation effect (p = 0.077 > 0.05) on the link between GTL and GP. This reflects the vital part that CSR plays in this relationship, which can be changed based on the status of CSR. In addition, this reflects the value of CSR in achieving GP, which contributes to the achievement of environmental sustainability at a national level (i.e., the Green Saudi Initiative) at a regional level (i.e., the Green Middle East Initiative) and at an international level (i.e., UNSDGs). Full article
(This article belongs to the Special Issue Quantitative Analysis and DEA Modeling in Applied Economics)
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23 pages, 2919 KiB  
Article
DEA and Machine Learning for Performance Prediction
by Zhishuo Zhang, Yao Xiao and Huayong Niu
Mathematics 2022, 10(10), 1776; https://doi.org/10.3390/math10101776 - 23 May 2022
Cited by 14 | Viewed by 4665
Abstract
Data envelopment analysis (DEA) has been widely applied to evaluate the performance of banks, enterprises, governments, research institutions, hospitals, and other fields as a non-parametric estimation method for evaluating the relative effectiveness of research objects. However, the composition of its effective frontier surface [...] Read more.
Data envelopment analysis (DEA) has been widely applied to evaluate the performance of banks, enterprises, governments, research institutions, hospitals, and other fields as a non-parametric estimation method for evaluating the relative effectiveness of research objects. However, the composition of its effective frontier surface is based on the input-output data of existing decision units, which makes it challenging to apply the method to predict the future performance level of other decision units. In this paper, the Slack Based Measure (SBM) model in DEA method is used to measure the relative efficiency values of decision units, and then, eleven machine learning models are used to train the absolute efficient frontier to be applied to the performance prediction of new decisions units. To further improve the prediction effect of the models, this paper proposes a training set under the DEA classification method, starting from the training-set sample selection and input feature indicators. In this paper, regression prediction of test set performance based on the training set under different classification combinations is performed, and the prediction effects of proportional relative indicators and absolute number indicators as machine-learning input features are explored. The robustness of the effective frontier surface under the integrated model is verified. An integrated models of DEA and machine learning with better prediction effects is proposed, taking China’s regional carbon-dioxide emission (carbon emission) performance prediction as an example. The novelty of this work is mainly as follows: firstly, the integrated model can achieve performance prediction by constructing an effective frontier surface, and the empirical results show that this is a feasible methodological technique. Secondly, two schemes to improve the prediction effectiveness of integrated models are discussed in terms of training set partitioning and feature selection, and the effectiveness of the schemes is demonstrated by using carbon-emission performance prediction as an example. This study has some application value and is a complement to the existing literature. Full article
(This article belongs to the Special Issue Quantitative Analysis and DEA Modeling in Applied Economics)
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16 pages, 472 KiB  
Article
Material Sourcing Characteristics and Firm Performance: An Empirical Study in Vietnam
by Phi-Hung Nguyen, Lin Hsu-Hao, Hong-Anh Pham, Huong Le Thi, Quynh Mai Do, Dieu Huong Nguyen and Thu-Ha Nguyen
Mathematics 2022, 10(10), 1691; https://doi.org/10.3390/math10101691 - 15 May 2022
Cited by 4 | Viewed by 4011
Abstract
With the evolution of today’s economy, supply chain management for raw materials is a complex task, but it can be simplified with the appropriate strategies. Thus, relationships between firms and suppliers have become critical for enterprise success and country development. This study investigates [...] Read more.
With the evolution of today’s economy, supply chain management for raw materials is a complex task, but it can be simplified with the appropriate strategies. Thus, relationships between firms and suppliers have become critical for enterprise success and country development. This study investigates the effects of raw materials sources, including domestic and international ones, on small and medium enterprises (SMEs) performance. Supporting this research, all the regression models are conducted on Stata version 16.0 software with the dataset of 3485 manufacturing SMEs, utilizing longitudinal data derived from bi-annually repeated surveys of randomly selected SMEs in ten provinces in Vietnam over the period of 2011–2015. Additionally, the results of this study indicate the significant positive effects of domestic raw materials on firm performance. Meanwhile, international raw material sources present SMEs with several disadvantages in maintaining the effectiveness of SMEs’ operations. In addition, the results also highlight that the overflow of raw materials from non-state enterprises has negative effects on firm performance. Alternatively, this study aims to fill the literature gap on supply chain management to suggest to SMEs some justifiable strategies to fortify sustainable growth and the rational flow of raw materials. Full article
(This article belongs to the Special Issue Quantitative Analysis and DEA Modeling in Applied Economics)
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21 pages, 2575 KiB  
Article
A Two-Stage DEA Approach to Measure Operational Efficiency in Vietnam’s Port Industry
by Chia-Nan Wang, Phi-Hung Nguyen, Thi-Ly Nguyen, Thi-Giang Nguyen, Duc-Thinh Nguyen, Thi-Hoai Tran, Hong-Cham Le and Huong-Thuy Phung
Mathematics 2022, 10(9), 1385; https://doi.org/10.3390/math10091385 - 20 Apr 2022
Cited by 16 | Viewed by 4242
Abstract
Logistics services aid import and export businesses located near ports in terms of ease and efficiency in the globalization era. Furthermore, economic growth and global import–export volumes immediately impact the port industry. This research aims to develop a two-stage Data Envelopment Analysis (DEA) [...] Read more.
Logistics services aid import and export businesses located near ports in terms of ease and efficiency in the globalization era. Furthermore, economic growth and global import–export volumes immediately impact the port industry. This research aims to develop a two-stage Data Envelopment Analysis (DEA) model for measuring the performance efficiency of Vietnam’s top 18 seaports. The DEA resampling technique is used to forecast future performance, and the DEA Malmquist model analyzes efficiency improvement. First, the forecast data for the next three years, from 2021 to 2023, were obtained by resampling Lucas weight prediction with the highest accuracy. The results indicate that 12 out of all ports achieved an average progressive production efficiency over the entire study period of 2018–2023. Further, most ports have advanced slightly in technological efficiency, indicating that the determinants of increased productivity are the technical efficiency change indexes. This work contributes to the body of knowledge by being the first to apply the resampling technique in conjunction with the Malmquist model to forecast performance efficiency in the domain of the seaport sector. Furthermore, the managerial implications serve as a beneficial reference for operation managers, policymakers, and researchers when comparing the operational efficacy of seaports to diverse logistical scenarios. Full article
(This article belongs to the Special Issue Quantitative Analysis and DEA Modeling in Applied Economics)
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23 pages, 3968 KiB  
Article
Output Targeting and Runway Utilization of Major International Airports: A Comparative Analysis Using DEA
by Chia-Nan Wang, Kristofer Neal Castro Imperial, Ching-Chien Huang and Thanh-Tuan Dang
Mathematics 2022, 10(4), 551; https://doi.org/10.3390/math10040551 - 10 Feb 2022
Cited by 5 | Viewed by 2976
Abstract
The aviation industry is a prominent contributor to economic development. The existence of an airport hub that provides a worldwide transportation network generates economic growth, creates jobs, and facilitates international trade and tourism. This industry also helps in connecting different continents, countries, and [...] Read more.
The aviation industry is a prominent contributor to economic development. The existence of an airport hub that provides a worldwide transportation network generates economic growth, creates jobs, and facilitates international trade and tourism. This industry also helps in connecting different continents, countries, and cultures. This study utilizes the Data Envelopment Analysis models Charnes, Cooper, and Rhodes (CCR), Banker, Charnes, and Cooper (BCC), Slacks-Based Measure (SBM), and Epsilon Based Measure (EBM) in analyzing and evaluating the operational performance of the 21 major airports runway design during the years of 2016–2019 using the data of the International Civil Aviation Organization (ICAO) air transport statistics. The objective of this paper is to assess the efficiency of various airport runway configurations based on input factors such as number of runways, dimension of runways, airport area, and output factors such as annual number of flights and annual number of passengers. In the four applied models, the results indicated London Heathrow Airport (LHR) and Munich International Airport (MUC) are efficient in utilizing the runway during the considered periods. Surprisingly, airports in the Asian continent with a parallel runway design are more efficient than in North America and Europe. This study can be a valuable reference for operation managers in evaluating and benchmarking the performance of an airport with different types of runway configurations. Moreover, it can be used by decision-makers, investors, stakeholders, policymakers, private companies, and government agencies as a guideline suitable for an airport. Full article
(This article belongs to the Special Issue Quantitative Analysis and DEA Modeling in Applied Economics)
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16 pages, 1261 KiB  
Article
Financial Stability Control for Business Sustainability: A Case Study from Food Production
by Tomas Macak
Mathematics 2022, 10(3), 292; https://doi.org/10.3390/math10030292 - 18 Jan 2022
Viewed by 2396
Abstract
Conventional financial management methods, based on extrapolation approaches to financial analysis, often reach their limits due to violations of stationary controlled financial variables, for example, interventions in the economy and social life necessary to manage the COVID-19 pandemic. Therefore, we have created a [...] Read more.
Conventional financial management methods, based on extrapolation approaches to financial analysis, often reach their limits due to violations of stationary controlled financial variables, for example, interventions in the economy and social life necessary to manage the COVID-19 pandemic. Therefore, we have created a procedure for controlling financial quantities, which respects the non-stationarity of the controlled quantity using the maximum control deviation covering the confidence interval of a random variable or random vector. For this interval, we then determined the algebraic criteria of the transfer functions using the Laplace transform. For the Laplace transform, we determined the theorem on the values of the stable roots of the characteristic equation, including the deductive proof. This theorem is directly usable for determining the stability of the management for selected financial variables. For the practical application, we used the consistency of the stable roots of the characteristic equation with the Stodola and Hurwitz stability conditions. We demonstrated the procedure for selected quantities of financial management in food production. In conclusion, we proposed a control mechanism for the convergence of regulatory deviation using a combination of proportional and integration schemes. We also determined the diversification of action interventions (into development, production, and marketing) using a factorial design. Full article
(This article belongs to the Special Issue Quantitative Analysis and DEA Modeling in Applied Economics)
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22 pages, 2027 KiB  
Article
Approaches to Efficiency Assessing of Regional Knowledge-Intensive Services Sector Development Using Data Envelopment Analysis
by Anna Firsova, Galina Chernyshova and Ryasimya Tugusheva
Mathematics 2022, 10(2), 173; https://doi.org/10.3390/math10020173 - 6 Jan 2022
Cited by 4 | Viewed by 1896
Abstract
The sector of knowledge-intensive services is one of the fastest-growing sectors in the present-day economy of knowledge, which explains the scientific interest in developing methods of its quantitative assessment. The object of the research is the development of new approaches to the mathematical [...] Read more.
The sector of knowledge-intensive services is one of the fastest-growing sectors in the present-day economy of knowledge, which explains the scientific interest in developing methods of its quantitative assessment. The object of the research is the development of new approaches to the mathematical modeling of the efficiency of the regional knowledge-intensive services sector, based on a distance function approach to assess productivity changes. An approach was proposed to analyze the efficiency of this sector using data envelopment analysis and Malmquist productivity index and its components. The article presents the results of the assessment of indicators characterizing the development of knowledge-intensive services in education, innovation, and ICT obtained from 80 Russian regions for the period 2010–2020. To perform the analysis, the following input variables were used: volume of investments in fixed assets in ICT; share of personnel employed in the ICT; share of internal expenditures on R&D in GRP; the number of personnel engaged in R&D; share of innovative-active organizations and registered patents; funding for higher education institutions; and the number of higher education institutions graduated. Output variables were number of used advanced production technologies in the region; share of innovative goods, works, and services in GRP, and use of the intellectual property. As a result of applying the data envelopment analysis, Malmquist productivity index and its components, data were obtained on the positive dynamics of the development of the knowledge-intensive services sector in Russian regions and conclusions were drawn about the sector’s growth sources due to economies of scale. Full article
(This article belongs to the Special Issue Quantitative Analysis and DEA Modeling in Applied Economics)
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13 pages, 312 KiB  
Article
The Problem of Determining Discount Rate for Integrated Investment Projects in the Oil and Gas Industry
by Alexey Komzolov, Tatiana Kirichenko, Olga Kirichenko, Yulia Nazarova and Natalya Shcherbakova
Mathematics 2021, 9(24), 3327; https://doi.org/10.3390/math9243327 - 20 Dec 2021
Cited by 5 | Viewed by 4263
Abstract
The main aim of this paper was to examine specific approaches to determining the discount rate for comprehensive computation of investment projects efficiency in the oil and gas industry. The objective of the study was to develop a scientific approach for determining the [...] Read more.
The main aim of this paper was to examine specific approaches to determining the discount rate for comprehensive computation of investment projects efficiency in the oil and gas industry. The objective of the study was to develop a scientific approach for determining the discount rate for integrated oil and gas projects. The authors analyze dynamic methods for determining the efficiency of investment projects in the oil and gas industry and conclude that they are advisable for oil and gas projects due to the high capital intensity of the projects and their long payback period. Regarding the need to implement dynamic indicators of efficiency, the authors set the task of deter-mining the proper discount rate as a factor having a significant impact on effectiveness evaluation. The discount rate is proposed to be evaluated by solving the equation and finding the break-even point where the NPV (net present value) of the integrated project will be equal to 0 (taking into account the revenue of the subprojects included in the complex). The practical implementation of methodological approaches to assessing the discount rate for integrated projects is relevant due to the execution of large, systemically important and integrated projects. As a result of the study, the authors put forward a methodological algorithm for determining the discount rate of an integrated project which assumes an assessment of cash flows for the subprojects included in the complex; determination of the target rate of return for subprojects; and calculation of prices for products at which a complex project become break-even. The practical implementation of methodological approaches to assessing the discount rate for integrated projects is relevant due to the execution of large systemically important integrated projects. Full article
(This article belongs to the Special Issue Quantitative Analysis and DEA Modeling in Applied Economics)
18 pages, 1838 KiB  
Article
Evaluation of Bank Innovation Efficiency with Data Envelopment Analysis: From the Perspective of Uncovering the Black Box between Input and Output
by Kaiyang Zhong, Chenglin Li and Qing Wang
Mathematics 2021, 9(24), 3318; https://doi.org/10.3390/math9243318 - 20 Dec 2021
Cited by 21 | Viewed by 3754
Abstract
The evaluation of corporation operation efficiency (especially innovation efficiency) has been always a hot topic. The currently popular evaluation methods are data envelopment analysis (DEA) and its improved methods. However, these methods have the following problems: the production process is regarded as a [...] Read more.
The evaluation of corporation operation efficiency (especially innovation efficiency) has been always a hot topic. The currently popular evaluation methods are data envelopment analysis (DEA) and its improved methods. However, these methods have the following problems: the production process is regarded as a black box, and the actual production relationship between input and output is not analyzed. To solve these problems: (1) the black box theory and production function theory are introduced to uncover the black box of input and output; (2) regression models are used to alleviate the multicollinearity problem of inputs, and the most appropriate model of production relationship is selected; and (3) the results of the production function are compared with the results of the efficiency evaluation from multiple perspectives. Taking rural commercial banks in China as examples to evaluate their innovation efficiency, this article shows the following: (1) with the black box theory and production function theory, the staff, equipment, and intermediate business cost are suitable as innovation input variables, and intermediate business income is suitable as an innovation output variable; (2) the main challenges faced by rural commercial banks are reducing the reliance on human capital investment, strengthening technological innovation, and improving the efficiency of intermediate business cost management, which is hard to reveal with traditional DEA. The method proposed in this article provides an applicable reference for improving DEA method analysis. Full article
(This article belongs to the Special Issue Quantitative Analysis and DEA Modeling in Applied Economics)
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15 pages, 1186 KiB  
Article
The Robust Efficiency Estimation in Lower Secondary Education: Cross-Country Evidence
by Darya Dancaková, Jozef Glova and Alena Andrejovská
Mathematics 2021, 9(24), 3249; https://doi.org/10.3390/math9243249 - 15 Dec 2021
Cited by 1 | Viewed by 2138
Abstract
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Quantitative Analysis and DEA Modeling in Applied Economics)
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31 pages, 6689 KiB  
Article
Conditional Time-Varying General Dynamic Factor Models and Its Application to the Measurement of Volatility Spillovers across Russian Assets
by Vladimir Balash, Alexey Faizliev, Sergei Sidorov and Elena Chistopolskaya
Mathematics 2021, 9(19), 2484; https://doi.org/10.3390/math9192484 - 4 Oct 2021
Cited by 4 | Viewed by 2277
Abstract
This study analyzes the spillover effects of volatility in the Russian stock market. The paper applies the Diebold–Yilmaz connectedness methodology to characterize volatility spillovers between Russian assets. The spectral representation of the forecast variance decomposition proposed by Baruník and Křehlik is used to [...] Read more.
This study analyzes the spillover effects of volatility in the Russian stock market. The paper applies the Diebold–Yilmaz connectedness methodology to characterize volatility spillovers between Russian assets. The spectral representation of the forecast variance decomposition proposed by Baruník and Křehlik is used to describe the connectivity in short-term (up to 5 days), medium-term (6–20 days) and long-term (more than 20 days) time frequencies. Additionally, two new augmented models are developed and applied to evaluate conditional spillover effects in different sectors of the Russian economy for the period from January 2012 to June 2021. It is shown that spillover effects increase significantly during political and economic crises and decrease during periods of relative stability. The rising of the overall level of spillovers in the Russian stock market coincides in time with the political crisis of 2014, the intensification of anti-Russian sanctions in 2018 and the fall in oil prices and the start of the pandemic in 2020. With the consideration of the augmented models it can be argued that a significant part of the long-term spillover effects on the Russian stock market may be caused by the influence of external economic and political factors. However, volatility spillovers generated by internal Russian idiosyncratic shocks are short-term. Thus, the proposed approach provides new information on the impact of external factors on volatility spillovers in the Russian stock market. Full article
(This article belongs to the Special Issue Quantitative Analysis and DEA Modeling in Applied Economics)
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21 pages, 899 KiB  
Article
Efficiency Evaluation of Regional Environmental Management Systems in Russia Using Data Envelopment Analysis
by Svetlana Ratner, Andrey Lychev, Aleksei Rozhnov and Igor Lobanov
Mathematics 2021, 9(18), 2210; https://doi.org/10.3390/math9182210 - 9 Sep 2021
Cited by 17 | Viewed by 3643
Abstract
The concept of eco-efficiency has recently become an issue of great importance due to the growing trend of environmental degradation, and many approaches based on Data Envelopment Analysis (DEA) are used in the literature to evaluate the environmental performance of economic systems. However, [...] Read more.
The concept of eco-efficiency has recently become an issue of great importance due to the growing trend of environmental degradation, and many approaches based on Data Envelopment Analysis (DEA) are used in the literature to evaluate the environmental performance of economic systems. However, research to date has paid little attention to the possibility of extending the DEA approach to the problem of measuring the economic feasibility of eco-efficiency improvement. The main aim of this study is to evaluate the efficiency of investments focused on improving the eco-efficiency of the regional economy in Russia using the DEA approach. The various types of costs for environmental protection measures are considered as inputs and the annual decrease in specific environmental impacts of the regional economy are considered as outputs of DEA models. This is different from previous research, which generally focused on environmental efficiency only, omitting the integration of economic aspects in eco-efficiency measures. This study compares three different modifications of basic DEA models in the context of technical complexity and practical feasibility. The results show that the efficiency of regional environmental management in many Russian regions has a great potential for improvement. From a practical point of view, the Slack-Based Measure (SBM) model provides the most accurate results for policy applications. Unlike other ratings, the DEA-SBM model may stimulate an optimization of environmental protection spending and the introduction of technological and organizational eco-innovations. Full article
(This article belongs to the Special Issue Quantitative Analysis and DEA Modeling in Applied Economics)
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