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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.

Ebook for Dynamic General Equilibrium Modeling is an amazing research study overview that exceeds and past what is frequently expected. The thorough building and construction of this source, which integrates intellectual insights with sensible strategies to exam prep work, makes it an exceptionally beneficial tool for pupils. This manual, which was created by $_authors$, that are well-regarded academics in their corresponding areas, and released by $_publisher$ on $_publish_date$, is an crucial resource for anybody who is pursuing attaining achievement in Test bank, Solution manual.

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 gener

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