Corruption in Transition Economies: Cause or Effect?

This paper investigates the empirical relationship between corruption, economic growth, and government spending in fourteen transitioning economies from 1995-2013. We find strong evidence of bilateral Granger causation between economic growth and corruption for the full sample but weaker evidence of such a relationship for four former Yugoslav republics. We also find bilateral Granger causality between government spending and corruption but a weaker unidirectional Granger causality from government spending to corruption in four former Yugoslav republics. Our results recommend caution when assuming that corruption is purely exogenous in empirical models

Advanced technologies, systems, and applications

This volume spans a wide range of technical disciplines and technologies, including complex systems, biomedical engineering, electrical engineering, energy, telecommunications, mechanical engineering, civil engineering, and computer science. The papers included in this volume were presented at the International Symposium on Innovative and Interdisciplinary Applications of Advanced Technologies (IAT), held in Neum, Bosnia and Herzegovina on June 26 and 27, 2016. This highly interdisciplinary volume is devoted to various aspects and types of systems. Systems thinking is crucial for successfully building and understanding man-made, natural, and social systems.

Complex Adaptive Systems: Views From the Physical, Natural, and Social Sciences

This book emerged out of international conferences organized as part of the AAAI Fall Symposia series, and the Swarmfest 2017 conference. It brings together researchers from diverse fields studying these complex systems using CAS and agent-based modeling tools and techniques. In the past, the knowledge gained in each domain has largely remained exclusive to that domain. By bringing together scholars who study these phenomena, the book takes knowledge from one domain to provide insight into others. [From the publisher] Complex adaptive systems (CAS) have proven to be a powerful tool for exploring these and other related phenomena. The authors characterize a general CAS model as having a large number of self-similar agents that: 1) utilize one or more levels of feedback; 2) exhibit emergent properties and self-organization; and 3) produce non-linear dynamic behavior. Advances in modeling and computing technology have led not only to a deeper understanding of complex systems in many areas, but they have also raised the possibility that similar fundamental principles may be at work across these systems, even though the underlying principles may manifest themselves differently.https://digitalcommons.odu.edu/emse_books/1009/thumbnail.jp