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Nonlinear modelling has become increasingly important and widely
used in economics. This valuable book brings together recent
advances in the area including contributions covering
cross-sectional studies of income distribution and discrete choice
models, time series models of exchange rate dynamics and jump
processes, and artificial neural network and genetic algorithm
models of financial markets. Attention is given to the development
of theoretical models as well as estimation and testing methods
with a wide range of applications in micro and macroeconomics,
labour and finance. The book provides valuable introductory
material that is accessible to students and scholars interested in
this exciting research area, as well as presenting the results of
new and original research. Nonlinear Economic Models provides a
sequel to Chaos and Nonlinear Models in Economics by the same
editors.
Financial crises often transmit across geographical borders and
different asset classes. Modeling these interactions is empirically
challenging, and many of the proposed methods give different
results when applied to the same data sets. In this book the
authors set out their work on a general framework for modeling the
transmission of financial crises using latent factor models. They
show how their framework encompasses a number of other empirical
contagion models and why the results between the models differ. The
book builds a framework which begins from considering contagion in
the bond markets during 1997-1998 across a number of countries, and
culminates in a model which encompasses multiple assets across
multiple countries through over a decade of crisis events from East
Asia in 1997-1998 to the sub prime crisis during 2008. Program code
to support implementation of similar models is available.
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R398
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