Theoretical Foundations of Central Banking: From Monetarism to Dynamic Stochastic General Equilibrium (DSGE) Models

Computational Techniques ◽

Dsge Models ◽

Monte Carlo Techniques ◽

Dynamic Stochastic ◽

Theoretical Foundations

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. The book is essential reading for graduate students, academic researchers, and practitioners at policy institutions.

On DSGE Models

The Journal of Economic Perspectives ◽

10.1257/jep.32.3.113 ◽

2018 ◽

Vol 32 (3) ◽

pp. 113-140 ◽

Cited By ~ 37

Author(s):

Lawrence J. Christiano ◽

Martin S. Eichenbaum ◽

Mathias Trabandt

Keyword(s):

Financial Crisis ◽

General Equilibrium ◽

Policy Change ◽

Great Recession ◽

Relative Strength ◽

Dsge Models ◽

The Great Recession ◽

Dynamic Stochastic ◽

Different Parts

The outcome of any important macroeconomic policy change is the net effect of forces operating on different parts of the economy. A central challenge facing policymakers is how to assess the relative strength of those forces. Economists have a range of tools that can be used to make such assessments. Dynamic stochastic general equilibrium (DSGE) models are the leading tool for making such assessments in an open and transparent manner. We review the state of mainstream DSGE models before the financial crisis and the Great Recession. We then describe how DSGE models are estimated and evaluated. We address the question of why DSGE modelers—like most other economists and policymakers—failed to predict the financial crisis and the Great Recession, and how DSGE modelers responded to the financial crisis and its aftermath. We discuss how current DSGE models are actually used by policymakers. We then provide a brief response to some criticisms of DSGE models, with special emphasis on criticism by Joseph Stiglitz, and offer some concluding remarks.

The scientific foundation of dynamic stochastic general equilibrium (DSGE) models

Public Choice ◽

10.1007/s11127-010-9674-x ◽

2010 ◽

Vol 144 (3-4) ◽

pp. 413-443 ◽

Cited By ~ 55

Author(s):

Paul De Grauwe

Keyword(s):

General Equilibrium ◽

Dsge Models ◽

Scientific Foundation ◽

A NOTE ON AN EXTENSION OF A CLASS OF SOLUTIONS TO DYNAMIC PROGRAMMING PROBLEMS ARISING IN ECONOMIC GROWTH

Macroeconomic Dynamics ◽

10.1017/s136510051000057x ◽

2011 ◽

Vol 16 (3) ◽

pp. 472-476 ◽

Cited By ~ 1

Author(s):

Jürgen Antony ◽

Alfred Maußner

Keyword(s):

Economic Growth ◽

Dynamic Programming ◽

General Equilibrium ◽

Dsge Models ◽

Dsge Model ◽

Savings Rate ◽

Dynamics And Control ◽

Dynamic Stochastic ◽

And Control

This note extends the findings of Benhabib and Rusticchini [Journal of Economic Dynamics and Control 18, 807–813 (1994)], who provide a class of dynamic stochastic general equilibrium (DSGE) models whose solution is characterized by a constant savings rate. We show that this class of models may be interpreted as a standard–representative agent DSGE model with costly adjustment of capital.

On non-computability of dynamic stochastic general equilibrium

10.31219/osf.io/23ep9 ◽

2020 ◽

Author(s):

William Glaciel

Keyword(s):

General Equilibrium ◽

Heterogeneous Agents ◽

Dsge Models ◽

As can be seen in Richter and Wong (1999), non-computability of general equilibrium has been recognized in economics. However, despite general non-computability, equilibrium can indeed be computed in specific cases. In this paper, further restriction on computability of equilibrium is provided in contexts of dynamic stochastic general equilibrium (DSGE) models with heterogeneous agents, demonstrating that non-computability concerns apply more generally than often understood.

Application of dynamic stochastic general equilibrium models to the case of the Serbian economy

Economic Annals ◽

10.2298/eka1401035u ◽

2014 ◽

Vol 59 (201) ◽

pp. 35-68

Author(s):

Branko Urosevic ◽

Nikola Grga

Keyword(s):

General Equilibrium ◽

Banking System ◽

Dsge Models ◽

Impulse Response Functions ◽

Response Functions ◽

Financial Friction ◽

Matlab Program ◽

Dynamic Stochastic ◽

Financial Dollarization

This paper proposes a dynamic stochastic general equilibrium (DSGE) model for the Serbian economy. It is a modification of the existing models of Goodhart, Osorio and Tsomocos (2009) and Martinez and Tsomocos (2012). The model introduces important features of the Serbian economy, financial dollarization and foreign ownership of the banking system, while retaining the most important element of the reference models, financial friction. To solve the model we use Dynare, a specialized Matlab program for solving DSGE models. The model is subject to three different shocks: monetary, productivity, and regulatory, and the results are presented in the form of impulse response functions. It is concluded that the proposed platform has good characteristics, but its complete application to the case of the Serbian economy requires further research.

World Scientific Studies in International Economics - Exchange Rates and Global Financial Policies ◽

The Scientific Foundation of Dynamic Stochastic General Equilibrium (DSGE) Models

10.1142/9789814513197_0017 ◽

2014 ◽

pp. 427-472

Author(s):

Paul De Grauwe

Keyword(s):

General Equilibrium ◽

Dsge Models ◽

Scientific Foundation ◽

Dynamic Stochastic General Equilibrium Models

10.1093/oxfordhb/9780199844371.013.4 ◽

2018 ◽

Author(s):

Michel Juillard

Keyword(s):

General Equilibrium ◽

Prior Information ◽

Local Approximation ◽

Perturbation Approach ◽

Dsge Models ◽

Deterministic Models ◽

New Information ◽

Solution Methods ◽

Dynamic Stochastic General Equilibrium (DSGE) models have become popular in macroeconomics, but the combination of nonlinear microeconomic behavior of the agents and model-consistent expectations raise intricate computational issues; this chapter reviews solution methods and estimation of DSGE models. Perfect foresight deterministic models can easily be solved with a great degree of accuracy. In practice, medium-sized stochastic models can only be solved by local approximation or the perturbation approach. The Bayesian approach to estimation is privileged. It provides a convenient way to communicate both the prior information available to the econo-metrician and new information revealed by the data. This chapter focuses on methods frequently used in applied work rather than aiming at being exhaustive.