Dynamic Disequilibrium Modeling Theory And Applications

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Dynamic Disequilibrium Modeling: Theory and Applications

Author: William A. Barnett
language: en
Publisher: Cambridge University Press
Release Date: 1996-06-13
. The organizers of the ninth symposium, which produced the current proceedings volume, were Claude Hillinger at the University of Munich, Giancarlo Gandolfo at the University of Rome "La Sapienza," A. R. Bergstrom at the University of Essex, and P. C. B. Phillips at Yale University.
Dynamic General Equilibrium Modeling

Author: Burkhard Heer
language: en
Publisher: Springer Science & Business Media
Release Date: 2009-08-12
Modern business cycle theory and growth theory uses stochastic dynamic general equilibrium models. In order to solve these models, economists need to use many mathematical tools. This book presents various methods in order to compute the dynamics of general equilibrium models. In part I, the representative-agent stochastic growth model is solved with the help of value function iteration, linear and linear quadratic approximation methods, parameterised expectations and projection methods. In order to apply these methods, fundamentals from numerical analysis are reviewed in detail. In particular, the book discusses issues that are often neglected in existing work on computational methods, e.g. how to find a good initial value. In part II, the authors discuss methods in order to solve heterogeneous-agent economies. In such economies, the distribution of the individual state variables is endogenous. This part of the book also serves as an introduction to the modern theory of distribution economics. Applications include the dynamics of the income distribution over the business cycle or the overlapping-generations model. In an accompanying home page to this book, computer codes to all applications can be downloaded.
Nonlinear Econometric Modeling in Time Series

Author: William A. Barnett
language: en
Publisher: Cambridge University Press
Release Date: 2000-05-22
Nonlinear Econometric Modeling in Time Series presents the more recent literature on nonlinear time series. Specific topics covered with respect to nonlinearity include cointegration tests, risk-related asymmetries, structural breaks and outliers, Bayesian analysis with a threshold, consistency and asymptotic normality, asymptotic inference and error-correction models. With a world-class panel of contributors, this volume addresses topics with major applications for fields such as foreign-exchange markets and interest rate analysis. Eleventh in this series of international symposia, this volume is also part of the European Conference Series in Quantitative Economics and Econometrics (EC)2.