Bøger i Dynamic Modeling and Econometrics in Economics and Finance serien

The book presents new developments in the dynamic modeling and optimization methods in environmental economics and provides a huge range of applications dealing with the economics of natural resources, the impacts of climate change and of environmental pollution, and respective policy measures.

In recent years nonlinearities have gained increasing importance in economic and econometric research, particularly after the financial crisis and the economic downturn after 2007. This book contains theoretical, computational and empirical papers that incorporate nonlinearities in econometric models and apply them to real economic problems.

The major goal of the book is to create an environment for matching different d- ciplinary approaches to studying economic growth.

The book examines problems associated with green growth and sustainable development on the basis of recent contributions in economics, natural sciences and applied mathematics, especially optimal control theory.

The uneven geographical distribution of economic activities is a huge challenge worldwide and also for the European Union. In Krugman's New Economic Geography economic systems have a simple spatial structure. At the highest level, economic geography models give a bird eye's view of spatial dynamics.

The field of econometrics has gone through remarkable changes during the last thirty-five years. This development becomes apparent when looking at the biography of an econometrician whose illustrious research and teaching career started about thirty-five years ago and who will retire very soon after his 65th birthday.

Nonlinear Time Series Analysis of Economic and Financial Data provides an examination of the flourishing interest that has developed in this area over the past decade.

Stochastic Volatility in Financial Markets presents advanced topics in financial econometrics and theoretical finance, and is divided into three main parts.

This volume is centered around the issue of market design and resulting market dynamics. Computational methods are used to replicate and understand market dynamics emerging from interaction of heterogeneous agents, and to develop models that have predictive power for complex market dynamics.

The field of econometrics has gone through remarkable changes during the last thirty-five years. This development becomes apparent when looking at the biography of an econometrician whose illustrious research and teaching career started about thirty-five years ago and who will retire very soon after his 65th birthday.

This volume is centered around the issue of market design and resulting market dynamics. Computational methods are used to replicate and understand market dynamics emerging from interaction of heterogeneous agents, and to develop models that have predictive power for complex market dynamics.

The major goal of the book is to create an environment for matching different d- ciplinary approaches to studying economic growth.

Stochastic Volatility in Financial Markets presents advanced topics in financial econometrics and theoretical finance, and is divided into three main parts.

Provides the reader with both the statistical background and the software tools for detecting nonlinear behavior in time series data. This book describes various detection techniques including Engle's LaGrange Multiplier test for conditional hetero-skedasticity and tests based on the correlation dimension and on the estimated bispectrum.

Nonlinear Time Series Analysis of Economic and Financial Data provides an examination of the flourishing interest that has developed in this area over the past decade.