This interdisciplinary book argues that the economy has an underlying non-linear structure and that business cycles are endogenous, which allows a greater explanatory power with respect to the traditional assumption that dynamics are stochastic and shocks are exogenous.

The first part of this work is formal-methodological and provides the mathematical background needed for the remainder, while the second part presents the view that signal processing involves construction and deconstruction of information and that the efficacy of this process can be measured. The third part focuses on economics and provides the related background and literature on economic dynamics and the fourth part is devoted to new perspectives in understanding nonlinearities in economic dynamics: growth and cycles.

By pursuing this approach, the book seeks to (1) determine whether, and if so where, common features exist, (2) discover some hidden features of economic dynamics, and (3)highlight specific indicators of structural changes in time series. Accordingly, it is a must read for everyone interested in a better understanding of economic dynamics, business cycles, econometrics and complex systems, as well as non-linear dynamics and chaos theory. " This highly-valuable book is a great entry-point for understanding the economy as a self-organizing non-linear dynamical system. This book not only introduces the reader to advanced techniques but also applies them to modern economic growth and business cycle models."Markus Brunnermeier, Edwards S. Sanford Professor of Economics, Director of the Bendheim Center for Finance, Princeton University, USA

Autorentext
Giuseppe Orlando is a Professor at the Department of Economics and Finance, University of Bari (Italy). With a focus on economics, finance and econometrics, his current projects involve business cycle modelling, banking clearing problems and interest rate forecasting.
Alexander N. Pisarchik is a Distinguished Researcher at the Center for Biomedical Technology, Technical University of Madrid (Spain). In 2013 he was appointed the Isaac-Peral Chair of Computational Systems Biology at the Center for Biomedical Technology, Technical University of Madrid in the framework of the BBVA-UPM BioTech Program. His scientific interests include nonlinear dynamics, chaos, synchronization, multistability, intermittency, and stochastic dynamics with applications to lasers, electronics, the brain, neurons and cryptography.
Ruedi Stoop is a Professor at the Institute for Neuroinformatics, University of Zurich (UZH); Swiss Federal Institute of Technology (ETH) in Zurich; the University of Bern and the Technical University Nordwestschweiz (Switzerland). A mathematician and theoretical physicist, his research focuses on biological computing, statistical physics and cochlear modelling.

Inhalt
FM.- Introduction.- Part I: Mathematical background.- Dynamical systems.- An example of nonlinear dynamical system: The Logistic Map.- Bifurcations.- From local bifurcations to global dynamics: Hopf systems from the applied perspective.- Chaos.- Embedding and mutual information.- Part II: Signal analysis and modelling tools for economic systems.- Signal Processing.- Applied spectral analysis.- Recurrence quanti cation analysis: theory and applications.- Part III: Emergence of cycles and growth in economics.- On business cycles and growth.- Trade-cycle oscillations: The Kaldor model and the Keynesian Hansen-Samuelson principle of acceleration and multiplier.- The Harrod model.- Growth and cycles as a struggle: Lotka-Volterra, Goodwin and Phillips.- Stable periodic economic cycles from controlling.- Part IV: New horizons for understanding economics.- Kaldor-Kalecki new model on business cycles.- Recurrence Quanti cation Analysis of Business Cycles.- An empirical test on Harrod's model.- Testing a Goodwin's model with capacity utilization to the US Economy.- Financial Stress, Regime Switching and Macrodynamics.- BM.