scholarly journals Online estimation of DSGE models

2020 ◽  
Author(s):  
Michael Cai ◽  
Marco Del Negro ◽  
Edward Herbst ◽  
Ethan Matlin ◽  
Reca Sarfati ◽  
...  
Keyword(s):  
Sequential Monte Carlo ◽  
Forecast Accuracy ◽  
Predictive Performance ◽  
Dsge Models ◽  
Dsge Model ◽  
Online Estimation ◽  
Prior Variance ◽  
Out Of Sample ◽  
Dynamic Stochastic ◽  
Density Forecasts

Summary This paper illustrates the usefulness of sequential Monte Carlo (SMC) methods in approximating dynamic stochastic general equilibrium (DSGE) model posterior distributions. We show how the tempering schedule can be chosen adaptively, document the accuracy and runtime benefits of generalized data tempering for ‘online’ estimation (that is, re-estimating a model as new data become available), and provide examples of multimodal posteriors that are well captured by SMC methods. We then use the online estimation of the DSGE model to compute pseudo-out-of-sample density forecasts and study the sensitivity of the predictive performance to changes in the prior distribution. We find that making priors less informative (compared with the benchmark priors used in the literature) by increasing the prior variance does not lead to a deterioration of forecast accuracy.

scholarly journals Estimating point and density forecasts for the US economy with a factor-augmented vector autoregressive DSGE model

2015 ◽  
Vol 19 (2) ◽  
Author(s):  
Stelios Bekiros ◽  
Alessia Paccagnini
Keyword(s):  
Dynamic Stochastic General Equilibrium ◽  
Dsge Models ◽  
Dsge Model ◽  
Time Data ◽  
Vector Autoregressive ◽  
Us Economy ◽  
The Us ◽  
Dynamic Stochastic ◽  
Statistical Identification ◽  
Density Forecasts

AbstractAlthough policymakers and practitioners are particularly interested in dynamic stochastic general equilibrium (DSGE) models, these are typically too stylized to be applied directly to the data and often yield weak prediction results. Very recently, hybrid DSGE models have become popular for dealing with some of the model misspecifications. Major advances in estimation methodology could allow these models to outperform well-known time series models and effectively deal with more complex real-world problems as richer sources of data become available. In this study we introduce a Bayesian approach to estimate a novel factor augmented DSGE model that extends the model of Consolo et al. [Consolo, A., Favero, C.A., and Paccagnini, A., 2009. On the Statistical Identification of DSGE Models. Journal of Econometrics, 150, 99–115]. We perform a comparative predictive evaluation of point and density forecasts for many different specifications of estimated DSGE models and various classes of VAR models, using datasets from the US economy including real-time data. Simple and hybrid DSGE models are implemented, such as DSGE-VAR and tested against standard, Bayesian and factor augmented VARs. The results can be useful for macro-forecasting and monetary policy analysis.

Bayesian Estimation of DSGE Models

2015 ◽  
Author(s):  
Edward P. Herbst ◽  
Frank Schorfheide
Keyword(s):  
Monte Carlo ◽  
Sequential Monte Carlo ◽  
Likelihood Function ◽  
Academic Research ◽  
Dynamic Stochastic General Equilibrium ◽  
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.

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

2011 ◽  
Vol 16 (3) ◽  
pp. 472-476 ◽  
Author(s):  
Jürgen Antony ◽  
Alfred Maußner
Keyword(s):  
Economic Growth ◽  
Dynamic Programming ◽  
General Equilibrium ◽  
Dynamic Stochastic 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.

scholarly journals Monetary Policy Analysis with Potentially Misspecified Models

2009 ◽  
Vol 99 (4) ◽  
pp. 1415-1450 ◽  
Author(s):  
Marco Del Negro ◽  
Frank Schorfheide
Keyword(s):  
Policy Analysis ◽  
Recent Literature ◽  
Model Misspecification ◽  
Dynamic Stochastic General Equilibrium ◽  
Dsge Models ◽  
Estimation Of Parameters ◽  
Dsge Model ◽  
Misspecified Models ◽  
Trade Offs ◽  
Dynamic Stochastic

Policy analysis with potentially misspecified dynamic stochastic general equilibrium (DSGE) models faces two challenges: estimation of parameters that are relevant for policy trade-offs, and treatment of the deviations from the cross-equation restrictions. Using post-1982 US data, we study the robustness of the policy prescriptions from a state-of-the-art DSGE model with respect to two approaches to model misspecification pursued in the recent literature: (i) adding shocks to the DSGE model and/or generalizing the processes followed by these shocks; and (ii) explicit modeling of deviations from cross-equation restrictions (DSGE-VAR). (JEL C51, E13, E43, E52, E58)

How do the financial and oil sanctions affect the Iran's economy: a DSGE framework

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Seyyed Reza Nakhli ◽  
Monireh Rafat ◽  
Rasul Bakhshi Dastjerdi ◽  
Meysam Rafei
Keyword(s):  
Open Economy ◽  
Economic Effect ◽  
Current Paper ◽  
Dsge Models ◽  
Dsge Model ◽  
Content Type ◽  
Macroeconomic Variables ◽  
The World ◽  
Dynamic Stochastic ◽  
The Government

PurposeThe purpose of the current paper is to analyze the simultaneous effects of oil sanctions and financial sanctions on Iran's macroeconomic variables in a small open economy in the dynamic stochastic general equilibrium (DSGE) framework.Design/methodology/approachA DSGE model with the new Keynesian approach has been designed for the above mentioned purpose giving consideration to households, production, trade, oil, government and central bank sectors. All of the parameters were calibrated by using geometric means of macroeconomic variables in 2004–2017 as the steady-state values of the variables in the static model.FindingsAmplifying the intensity of the oil sanctions reduces oil production due to decreasing investment, technology and export of oil and reduces the central bank's foreign reserves ratio to the money base that leads to an increasing exchange rate. Furthermore, oil sanctions decrease the government revenues due to a decrease in oil export and by the government imposing an expansionary fiscal policy in the form of increasing current expenditure and preserving construction expenditure to prevent deepening the recession, which causes budget deficit and then the issue of more bonds with a higher nominal interest rate. On the other hand, financial sanctions raise transaction costs and marginal costs in the trade sectors that lead to inflation and a decrease in nonoil export and various kinds of imports. Due to inflation and uncertainty, consumption of a household increases and investment expenditure of a household decreases.Originality/valueTo the best of the author's knowledge, few studies in the world have analyzed the economic effect of the sanctions in the framework of DSGE models. There is no study in Iran to date which investigates the effects of the sanctions in the form of a DSGE model. So, this paper is the first study in Iran and one of the few studies in the world using a DSGE model for analyzing the effects of sanctions. Imposing three kinds of oil sanctions in addition to a financial sanction is another innovation of the current paper.

scholarly journals Forecasting using a Nonlinear DSGE Model

2018 ◽  
Vol 7 (2) ◽  
pp. 73-98
Author(s):  
Sergey Ivashchenko ◽  
Rangan Gupta
Keyword(s):  
Measurement Errors ◽  
Dynamic Stochastic General Equilibrium ◽  
Mean Square ◽  
State Variables ◽  
Dsge Model ◽  
Market Returns ◽  
Stock Market Returns ◽  
Out Of Sample ◽  
Dynamic Stochastic

Abstract A medium-scale nonlinear dynamic stochastic general equilibrium (DSGE) model was estimated (54 variables, 29 state variables, 7 observed variables). The model includes an observed variable for stock market returns. The root-mean square error (RMSE) of the in-sample and out-of-sample forecasts was calculated. The nonlinear DSGE model with measurement errors outperforms AR (1), VAR (1) and the linearised DSGE in terms of the quality of the out-of-sample forecasts. The nonlinear DSGE model without measurement errors is of a quality equal to that of the linearised DSGE model.

Unconventional Monetary Policy in Japan: Empirical Evidence from Estimated Shadow Rate DSGE Model

2019 ◽  
Vol 10 (02) ◽  
pp. 1950007
Author(s):  
Rui Wang
Keyword(s):  
Monetary Policy ◽  
Central Banks ◽  
Economic Research ◽  
Dsge Models ◽  
Unconventional Monetary Policy ◽  
Dsge Model ◽  
Linear Solution ◽  
Medium Scale ◽  
Dynamic Stochastic ◽  
Counterfactual Simulation

The Zero Lower Bound (ZLB) on short nominal interest rates has imposed serious constraint on stimulating and stabilizing economy of major central banks. Analysis of monetary policy by Dynamic Stochastic General Equilibrium (DSGE) models under the existence of ZLB has also been an important issue from both practical and academic views for central banks and macroeconomists. However, the nonlinearity of ZLB constraint makes linear solution and estimation techniques of DSGE models unreliable and impractical. In many recent empirical works, it has been proved that the shadow rate can be used as an accurate proxy to represent the stance of unconventional monetary policy in the ZLB environment. We use shadow rate to estimate a medium-scale DSGE model based on the theoretical foundation proposed by Wu and Zhang (2016). A shadow rate New Keynesian model (No. w22856). National Bureau of Economic Research, and conduct counterfactual simulation exercises to quantify the macroeconomic effects of unconventional monetary policy implemented by Bank of Japan (BoJ). Compared with the estimation results of pre-ZLB sub-sample (1980Q1–1998Q4), the structural parameters estimated from full-sample (1980Q1–2016Q3) with the shadow rate still have very reasonable values that are consistent with most related medium-scale DSGE literature. The statistical properties of model dynamics implied by two groups of estimation are also very close. Counterfactual simulation shows that without the unconventional monetary policy, macroeconomic variables would have worse performance than their actual realizations.

scholarly journals Optimal Environmental Tax Rate in an Open Economy with Labor Migration—An E-DSGE Model Approach

2019 ◽  
Vol 11 (19) ◽  
pp. 5147 ◽  
Author(s):  
Ying Tung Chan
Keyword(s):  
Open Economy ◽  
Labor Migration ◽  
Social Planner ◽  
Dsge Models ◽  
Environmental Tax ◽  
Closed Economy ◽  
Dsge Model ◽  
Tax Rate ◽  
Dynamic Stochastic ◽  
Optimal Environmental Tax

Recent research has started to apply environmental dynamic stochastic general equilibrium (E-DSGE) models for climate policy analysis. However, all of the studies assume a closed economy setting, where there is no interaction of the economy with an outside economy; this paper fills the gap by constructing a two-city E-DSGE model that features labor migration. With the model, we solve for the optimal environmental tax rate determined by a Ramsey social planner, who maximizes household utility and takes into account the policy’s impact on labor migration. We find the following. (i) The optimal environmental tax rate should be more volatile and procyclical than the rates predicted in the aforementioned literature. (ii) In the closed economy setting, a higher environmental tax rate would always dampen production, while in our setting, it could stimulate output through deterring labor outflow and attracting labor inflow. (iii) We complement the existing literature by emphasizing that the optimal environmental tax rate in a city should respond not only to the shocks that occur internally, but also to those that occur in the opponent city. In particular, we find that it is optimal to reduce the environmental tax rate if a positive total factor productivity (TFP) shock occurs in the neighbor city.

scholarly journals Three essays on bayesian analysis of nonlinear DSGE models

2019 ◽  
Author(s):  
◽  
Sanha Noh
Keyword(s):  
Decision Making ◽  
Linear Model ◽  
Open Economy ◽  
Financial Frictions ◽  
Small Open Economy ◽  
Dsge Models ◽  
Dsge Model ◽  
Productivity Shock ◽  
Dynamic Stochastic ◽  
The Impact

The 2008 financial crisis has highlighted the importance of nonlinear features of our economy including risks, uncertainty shocks, rare disasters, structural changes, zero-lower bound, and occasionally binding constraints. Macroeconomists have tried to build nonlinear models to analyze these interesting features and take the models to the data. Dynamic Stochastic General Equilibrium (DSGE) model that essentially takes into account dynamic optimal decision making of households, firms, and government is one of the useful tools to deal with these issues. In the model, there are various random shocks causing the macroeconomic variables such as GDP, consumption, and investment to fluctuate over time. Above all things, the nonlinear approximation of the model allows us to capture the impact of risk on decision making. The focus of this dissertation is to provide a novel Bayesian estimation procedure for the estimation of nonlinear DSGE model and apply the proposed methodologies to analyze some nonlinear issues related to DSGE models. ... In the third chapter, I investigate a real business cycle (RBC) model for a small open economy by estimating the model solved up to second order. The higher order approximation more closely approximates the original model than the linear approximation. In this study, I evaluate the likelihood of the nonlinear model using the Gaussian mixture a lter (GMF) and employ the GMF within the MCMC algorithm. From the estimation results of the quadratic approximation, I obtain the following implications for a small open economy: First, the quadratic RBC model with financial frictions does a good job at identifying the parameters of the nonstationary productivity shock process. Second, the observed data favor the quadratic benchmark RBC and financial-friction models over the linear models. Third, the quadratic RBC model with financial frictions does a better job at capturing serial correlations of the observed data than the linear model with financial frictions. Fourth, contrary to the linear model with financial frictions, a nonstationary productivity shock in the quadratic model plays an important role in explaining Argentine economic fluctuations.

scholarly journals Constructing a Small-Region DSGE Model

2013 ◽  
Vol 2013 ◽  
pp. 1-9
Author(s):  
Kenichi Tamegawa
Keyword(s):  
General Equilibrium ◽  
Interest Rates ◽  
Numerical Simulations ◽  
National Economy ◽  
Regional Economy ◽  
Small Region ◽  
Dynamic Stochastic General Equilibrium ◽  
Dsge Models ◽  
Dsge Model ◽  
Dynamic Stochastic

This paper constructs a tractable dynamic stochastic general equilibrium (DSGE) model of a regional economy that is considered small because it does not affect its national economy. To examine properties of our small-region DSGE model, we conduct several numerical simulations. Notably, fiscal expansion in our model is larger than that in standard DSGE models. This is because the increase in regional output does not raise interest rates, and this leads to the crowding-in effects of investment.

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