Advanced Mathematical Methods for Economic Efficiency Analysis

Economic efficiency analysis has received considerable worldwide attention in the last few decades, with Stochastic Frontier Analysis (SFA) and Data Envelopment Analysis (DEA) establishing themselves as the two dominant approaches in the literature. This book, by combining cutting-edge theoretical research on DEA and SFA with attractive real-world applications, offers a valuable asset for professors, students, researchers, and professionals working in all branches of economic efficiency analysis, as well as those concerned with the corresponding economic policies.

The book is divided into three parts, the first of which is devoted to basic concepts, making the content self-contained. The second is devoted to DEA, and the third to SFA. The topics covered in Part 2 range from stochastic DEA to multidirectional dynamic inefficiency analysis, including directional distance functions, the elimination and choice translating algorithm, benefit-of-the-doubt composite indicators,and internal benchmarking for efficiency evaluations. Part 3 also includes exciting and cutting-edge theoretical research on e.g. robustness, nonparametric stochastic frontier models, hierarchical panel data models, and estimation methods like corrected ordinary least squares and maximum entropy.

Presents the latest research on economic efficiency analysis Demonstrates cutting-edge theoretical research using both stochastic frontier analysis and data envelopment analysis Offers attractive real-world applications in areas such as energy, environment, health, agriculture, and sustainability

Autorentext

Pedro Macedo is an assistant professor in the Department of Mathematics at University of Aveiro (DMat-UA, Portugal) and a member of the Center for Research & Development in Mathematics and Applications (CIDMA, Portugal). He holds a PhD in Mathematics (Probability and Statistics), a MSc in Economics, and a licentiate degree in Applied Mathematics. His research interests lie in info-metrics, large-scale data, maximum entropy, productivity and efficiency analysis, and shrinkage estimation. Victor Manuel Ferreira Moutinho has a PhD in Energy Systems and Climate Change. He published several articles in the following journals: Energy Policy, Utilities Policy, Empirical Economics, Renewable and Sustainable Energy Reviews, Journal of Cleaner Production, Environmental Science and Pollution Research, Environment Development and Sustainability, Energy-International Journal, Agricultural Economics, Energy Sources, Part B: Economics, Planning and Policy, Energy Procedia, International Journal of Energy Economics and Policy, International Journal of Energy Technology and Policy. Currently, he is Director of the master in economics at University of Beira Interior (UBI). He is Coordinator of Economics and Finance and Full Researcher at NECE - Research Center in Business Sciences at the UBI, Associate Editor at Environmental Development and Sustainability (Springer), Academic Editor at Energies - MPDI and Academic Editor at The PLOS ONE.

Mara Madaleno is an assistant professor in the Department of Economics, Management, Industrial Engineering and Tourism at the University of Aveiro (DEGEIT-UA, Portugal) and a member of the Research Unit on Governance, Competitiveness and Public Policies (GOVCOPP, Portugal). Currently, she is the Director of the Master in Economics, Vice-director of the Master in Data Science for Social Sciences, and Vice-coordinator of the GOVCOPP research group Systems for Decision Support (SDS). She holds a PhD in Economics (Financial Economics), and a licentiate degree in Economics. Her research interests lie in financial economics, financial markets, energy and environmental financial markets, and financial markets/assets efficiency.

Inhalt
Chapter 1. Introduction.- Part I.- Chapter 2. Production Economics and Economic Efficiency (Mónica Meireles).- Chapter 3. Data Envelopment Analysis: A Review and Synthesis (Ana S. Camanho).- Chapter 4. Stochastic Frontier Analysis: A Review and Synthesis (Mara Madaleno).- Part II.- Chapter 5. Combining Directional Distances and ELECTRE Multicriteria Decision Analysis for Preferable Assessments of Efficiency (Thyago Nepomuceno).- Chapter 6. Benefit-of-the-Doubt Composite Indicators and use of Weight Restrictions (Ana S. Camanho).- Chapter 7. Multidirectional Dynamic Inefficiency Analysis: An Extension to Include Corporate Social Responsibility (Magdalena Kapelko).- Chapter 8. Stochastic DEA (Samah Jradi).- Chapter 9. Internal Benchmarking for Efficiency Evaluations using Data Envelopment Analysis: A Review of Applications and Directions for Future Research (Fabio Sartori Piran).- Part III.- Chapter 10. Recent Advances in the Construction of Nonparametric Stochastic Frontier Models (Christopher F. Parmeter).- Chapter 11. A Hierarchical Panel Data Model for the Estimation of Stochastic Metafrontiers: Computational Issues and an Empirical Application (Christine Amsler).- Chapter 12. Robustness in Stochastic Frontier Analysis (Alexander D. Stead).- Chapter 13. Is it MOLS or COLS? (Christopher F. Parmeter).- Chapter 14. Stochastic Frontier Analysis with Maximum Entropy Estimation (Pedro Macedo).