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Efficiency and Productivity Analysis
A guide to modelling productivity and efficiency using modern statistical tools. Fundamentals of stochastic frontier analysis are introduced and the latest concepts and methods related to the use of copulas in SFA are examined.
Efficiency and Productivity Analysis
This book is an easy-to-understand guide to modeling productivity and efficiency using modern statistical tools. It introduces readers to the fundamentals of stochastic frontier analysis (SFA) and gradually takes them to the forefront of academic research in this area, examining the latest concepts and methods related to the use of copulas in SFA. Following a comprehensive review of classic methodology, Professor Artem Prokhorov covers topics in panel data modeling, in endogeneity in SFA, in joint modeling of technical and allocative inefficiency, and in optimal and robust prediction of inefficiency scores. This is done using copulas to capture various kinds of statistical dependence that ha...
Applied Demography in the 21st Century
The topic of Applied Demography is clearly evolving as its practitioners become involved in the emerging trends of the Twenty-First Century. This book derived from the first post-2000 national conference on Applied Demography, held in San Antonio, Texas, January 7-9, 2007, at The University of Texas. The conference presented a unique opportunity and this resulting work provides a cross-sectional view of Applied Demography and an evaluation of its likely future.
Heavy-Tailed Distributions and Robustness in Economics and Finance
This book focuses on general frameworks for modeling heavy-tailed distributions in economics, finance, econometrics, statistics, risk management and insurance. A central theme is that of (non-)robustness, i.e., the fact that the presence of heavy tails can either reinforce or reverse the implications of a number of models in these fields, depending on the degree of heavy-tailed ness. These results motivate the development and applications of robust inference approaches under heavy tails, heterogeneity and dependence in observations. Several recently developed robust inference approaches are discussed and illustrated, together with applications.
Festschrift in Honor of Peter Schmidt
From the Introduction: This volume is dedicated to the remarkable career of Professor Peter Schmidt and the role he has played in mentoring us, his PhD students. Peter’s accomplishments are legendary among his students and the profession. Each of the papers in this Festschrift is a research work executed by a former PhD student of Peter’s, from his days at the University of North Carolina at Chapel Hill to his time at Michigan State University. Most of the papers were presented at The Conference in Honor of Peter Schmidt, June 30 - July 2, 2011. The conference was largely attended by his former students and one current student, who traveled from as far as Europe and Asia to honor Peter. ...
Asymmetric Dependence in Finance
Avoid downturn vulnerability by managing correlation dependency Asymmetric Dependence in Finance examines the risks and benefits of asset correlation, and provides effective strategies for more profitable portfolio management. Beginning with a thorough explanation of the extent and nature of asymmetric dependence in the financial markets, this book delves into the practical measures fund managers and investors can implement to boost fund performance. From managing asymmetric dependence using Copulas, to mitigating asymmetric dependence risk in real estate, credit and CTA markets, the discussion presents a coherent survey of the state-of-the-art tools available for measuring and managing this...
Computational Data and Social Networks
This book constitutes the refereed proceedings of the 10th International Conference on Computational Data and Social Networks, CSoNet 2021, which was held online during November 15-17, 2021. The conference was initially planned to take place in Montreal, Quebec, Canada, but changed to an online event due to the COVID-19 pandemic. The 24 full and 8 short papers included in this book were carefully reviewed and selected from 57 submissions. They were organized in topical sections as follows: Combinatorial optimization and learning; deep learning and applications to complex and social systems; measurements of insight from data; complex networks analytics; special track on fact-checking, fake news and malware detection in online social networks; and special track on information spread in social and data networks.
Essays in Honor of Subal Kumbhakar
It is the editor’s distinct privilege to gather this collection of papers that honors Subhal Kumbhakar’s many accomplishments, drawing further attention to the various areas of scholarship that he has touched.
