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Author:
Publisher:
ISBN: 9788793195905
Category :
Languages : en
Pages :
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Book Description
Author:
Publisher:
ISBN: 9788793195905
Category :
Languages : en
Pages :
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Book Description
Author: Mads Dang
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Edward P. Herbst
Publisher: Princeton University Press
ISBN: 0691161089
Category : Business & Economics
Languages : en
Pages : 295
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Book Description
Dynamic stochastic general equilibrium (DSGE) models have become one of the workhorses of modern macroeconomics and are extensively used for academic research as well as forecasting and policy analysis at central banks. This book introduces readers to state-of-the-art computational techniques used in the Bayesian analysis of DSGE models. The book covers Markov chain Monte Carlo techniques for linearized DSGE models, novel sequential Monte Carlo methods that can be used for parameter inference, and the estimation of nonlinear DSGE models based on particle filter approximations of the likelihood function. The theoretical foundations of the algorithms are discussed in depth, and detailed empirical applications and numerical illustrations are provided. The book also gives invaluable advice on how to tailor these algorithms to specific applications and assess the accuracy and reliability of the computations. Bayesian Estimation of DSGE Models is essential reading for graduate students, academic researchers, and practitioners at policy institutions.
Author: Burkhard Heer
Publisher: Springer Nature
ISBN: 3031516818
Category : Economic development
Languages : en
Pages : 943
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Book Description
Contemporary macroeconomics is built upon microeconomic principles, with its most recent advance featuring dynamic stochastic general equilibrium models. The textbook by Heer and Maußner acquaints readers with the essential computational techniques required to tackle these models and employ them for quantitative analysis. This third edition maintains the structure of the second, dividing the content into three separate parts dedicated to representative agent models, heterogeneous agent models, and numerical methods. At the same time, every chapter has been revised and two entirely new chapters have been added. The updated content reflects the latest advances in both numerical methods and their applications in macroeconomics, spanning areas like business-cycle analysis, economic growth theory, distributional economics, monetary and fiscal policy. The two new chapters delve into advanced 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 disaster models and dynamic Laffer curves. Lastly, the new edition places special emphasis on practical implementation across various programming languages; accordingly, its accompanying web page offers examples of computer code for languages such as MATLAB®, GAUSS, Fortran, Julia and Python. "This book does not only an excellent job in explaining the existing tools, but it also teaches the reader on how to write his/her own programs and it provides the reader with the tools to help advance the state of the art of dynamic macroeconomics." Wouter J. Den Haan, London School of Economics ”... provides the reader with exactly the necessary computational tools to solve the dynamic general equilibrium models macroeconomists care about. It is therefore the perfect complement to Stokey, Lucas and Prescott's and Sargent and Ljungqvist's theoretical treatment of modern macroeconomics." Dirk Krueger, University of Pennsylvania.
Author: Stephen David Morris
Publisher:
ISBN: 9781321005226
Category : Bayesian statistical decision theory
Languages : en
Pages : 140
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Book Description
The dissertation "Identification of Dynamic Stochastic General Equilibrium Models" by Stephen David Morris is divided into three chapters. The first chapter considers the statistical implications of common identifying restrictions for DSGE models. The second chapter considers the implications of identification failure for Bayesian estimators. The third chapter considers how identification of nonlinear solutions compares with that of linear solutions.
Author: Hamilton Galindo Gil
Publisher: Springer Nature
ISBN: 3031581059
Category :
Languages : en
Pages : 473
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Book Description
Author: David Colander
Publisher: Cambridge University Press
ISBN: 1139459058
Category : Business & Economics
Languages : en
Pages : 33
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Book Description
Macroeconomics is evolving in an almost dialectic fashion. The latest evolution is the development of a new synthesis that combines insights of new classical, new Keynesian and real business cycle traditions into a dynamic, stochastic general equilibrium (DSGE) model that serves as a foundation for thinking about macro policy. That new synthesis has opened up the door to a new antithesis, which is being driven by advances in computing power and analytic techniques. This new synthesis is coalescing around developments in complexity theory, automated general to specific econometric modeling, agent-based models, and non-linear and statistical dynamical models. This book thus provides the reader with an introduction to what might be called a Post Walrasian research program that is developing as the antithesis of the Walrasian DSGE synthesis.
Author: Naijing Huang
Publisher:
ISBN:
Category :
Languages : en
Pages : 62
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Book Description
This paper studies proper inference and asymptotically accurate structural break tests for parameters in Dynamic Stochastic General Equilibrium (DSGE) models in a maximum likelihood framework. Two empirically relevant issues may invalidate the conventional inference procedures and structural break tests for parameters in DSGE models: (i) weak identification and (ii) moderate parameter instability. DSGE literatures focus on dealing with weak identification issue, but ignore the impact of moderate parameter instability. This paper contributes to the literature via considering the joint impact of two issues in DSGE framework. The main results are: in a weakly identified DSGE model, (i) moderate instability from weakly identified parameters would not affect the validity of standard inference procedures or structural break tests; (ii) however, if strongly identified parameters are featured with moderate time-variation, the asymptotic distributions of test statistics would deviate from standard ones and would no longer be nuisance parameter free, which renders standard inference procedures and structural break tests invalid and provides practitioners misleading inference results; (iii) as long as I concentrate out strongly identified parameters, the instability impact of them would disappear as the sample size goes to infinity, which recovers the power of conventional inference procedure and structural break tests for weakly identified parameters. To illustrate my results, I simulate and estimate a modified version of the Hansen (1985) Real Business Cycle model and find that my theoretical results provide reasonable guidance for finite sample inference of the parameters in the model. I show that confidence intervals that incorporate weak identification and moderate parameter instability reduce the biases of confidence intervals that ignore those effects. While I focus on DSGE models in this paper, all of my theoretical results could be applied to any linear dynamic models or nonlinear GMM models.
Author: Harald Uhlig
Publisher:
ISBN:
Category : Discrete-time systems
Languages : en
Pages : 50
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Book Description
Author: Burkhard Heer
Publisher: Springer Science & Business Media
ISBN: 364203148X
Category : Business & Economics
Languages : en
Pages : 720
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Book Description
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.
