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Titlebook: Dynamic General Equilibrium Modeling; Computational Method Burkhard Heer,Alfred Mau?ner Textbook 2024Latest edition The Editor(s) (if appli

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發(fā)表于 2025-3-23 12:46:18 | 只看該作者
OLG Models with Uncertaintyf these models are already familiar from previous chapters on the (stochastic) neoclassical growth model and only need to be modified to allow for the more complex age structure of OLG models. Heer and Mau?ner first introduce individual stochastic productivity into the standard OLG model and apply t
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發(fā)表于 2025-3-23 17:43:21 | 只看該作者
Function Approximationed in Chaps. .–., the discrete state space methods of Chap. ., and the weighted residuals methods of Chap. .. This chapter gathers the most useful tools for this purpose. First, we clarify the notion of function approximation in the next section. We distinguish between local and global methods.
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發(fā)表于 2025-3-23 18:20:21 | 只看該作者
Differentiation and Integrationthe standard methods used to numerically approximate first-order and second-order partial derivatives from finite differences. The second part covers numerical integration, with a special emphasis on the approximation of expectations.
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發(fā)表于 2025-3-24 00:01:11 | 只看該作者
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發(fā)表于 2025-3-24 02:51:41 | 只看該作者
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Textbook 2024Latest edition techniques, including higher-order perturbation, weighted residual methods, and solutions to high-dimensional nonlinear problems. In addition, the authors present further insights from macroeconomic theory, complemented by practical applications like the Smolyak algorithm, Gorman aggregation, rare
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發(fā)表于 2025-3-24 15:49:37 | 只看該作者
Motive und Wirkungen im viralen Marketing subsequent chapters. The solution is characterized along two lines: 1) The Euler equations provide a set of nonlinear difference equations that determine the optimal time path of consumption. 2) Dynamic programming seeks a policy function that relates the agent’s choice of current consumption to hi
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發(fā)表于 2025-3-24 19:57:11 | 只看該作者
Strategien von Communities im Web 2.0are easy to apply. Toolkit programmers can keep all the algorithm details hidden away from users. Due to their widespread use, Heer and Mau?ner examine perturbation methods in detail, over three chapters. The present chapter introduces readers to the perturbation approach and related issues, develop
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發(fā)表于 2025-3-24 23:47:28 | 只看該作者
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