Estimation of DSGE models when the data are persistent PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Estimation of DSGE models when the data are persistent PDF full book. Access full book title Estimation of DSGE models when the data are persistent by Yuriy Gorodnichenko. Download full books in PDF and EPUB format.
Author: Yuriy Gorodnichenko
Publisher:
ISBN:
Category : Equilibrium (Economics)
Languages : en
Pages : 34
Get Book Here
Book Description
Dynamic Stochastic General Equilibrium (DSGE) models are often solved and estimated under specific assumptions as to whether the exogenous variables are difference or trend stationary. However, even mild departures of the data generating process from these assumptions can severely bias the estimates of the model parameters. This paper proposes new estimators that do not require researchers to take a stand on whether shocks have permanent or transitory effects. These procedures have two key features. First, the same filter is applied to both the data and the model variables. Second, the filtered variables are stationary when evaluated at the true parameter vector. The estimators are approximately normally distributed not only when the shocks are mildly persistent, but also when they have near or exact unit roots. Simulations show that these robust estimators perform well especially when the shocks are highly persistent yet stationary. In such cases, linear detrending and first differencing are shown to yield biased or imprecise estimates.
Author: Yuriy Gorodnichenko
Publisher:
ISBN:
Category : Equilibrium (Economics)
Languages : en
Pages : 34
Get Book Here
Book Description
Dynamic Stochastic General Equilibrium (DSGE) models are often solved and estimated under specific assumptions as to whether the exogenous variables are difference or trend stationary. However, even mild departures of the data generating process from these assumptions can severely bias the estimates of the model parameters. This paper proposes new estimators that do not require researchers to take a stand on whether shocks have permanent or transitory effects. These procedures have two key features. First, the same filter is applied to both the data and the model variables. Second, the filtered variables are stationary when evaluated at the true parameter vector. The estimators are approximately normally distributed not only when the shocks are mildly persistent, but also when they have near or exact unit roots. Simulations show that these robust estimators perform well especially when the shocks are highly persistent yet stationary. In such cases, linear detrending and first differencing are shown to yield biased or imprecise estimates.
Author: Nathan Balke
Publisher: Emerald Group Publishing
ISBN: 1781903069
Category : Business & Economics
Languages : en
Pages : 480
Get Book Here
Book Description
This volume of Advances in Econometrics contains articles that examine key topics in the modeling and estimation of dynamic stochastic general equilibrium (DSGE) models. Because DSGE models combine micro- and macroeconomic theory with formal econometric modeling and inference, over the past decade they have become an established framework for analy
Author: Gianluca Moretti
Publisher:
ISBN:
Category :
Languages : en
Pages : 39
Get Book Here
Book Description
Author: Gianluca Moretti
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Get Book Here
Book Description
Recent literature claims that key variables such as aggregate productivity and inflation display long memory dynamics. We study the implications of this high degree of persistence on the estimation of Dynamic Stochastic General Equilibrium (DSGE) models. We show that long memory data produce substantial bias in the deep parameter estimates when a standard Kalman Filter-MLE procedure is used. We propose a modification of the Kalman Filter to effectively deal with this problem. The augmented Kalman Filter can consistently estimate the model parameters as well as produce more accurate out-of-sample forecasts compared to the standard Kalman filter.
Author: Michael D. Cai
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Get Book Here
Book Description
This paper illustrates the usefulness of sequential Monte Carlo (SMC) methods in approximating 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 to the benchmark priors used in the literature) by increasing the prior variance does not lead to a deterioration of forecast accuracy.
Author: Markku Lanne
Publisher:
ISBN:
Category :
Languages : en
Pages :
Get Book Here
Book Description
Author: Ana Beatriz Galvão
Publisher:
ISBN:
Category :
Languages : en
Pages : 58
Get Book Here
Book Description
The typical estimation of DSGE models requires data on a set of macroeconomic aggregates, such as output, consumption and investment, which are subject to data revisions. The conventional approach employs the time series that is currently available for these aggregates for estimation, implying that the last observations are still subject to many rounds of revisions. This paper proposes a release-based approach that uses revised data of all observations to estimate DSGE models, but the model is still helpful for real-time forecasting. This new approach accounts for data uncertainty when predicting future values of macroeconomic variables subject to revisions, thus providing policy-makers and professional forecasters with both backcasts and forecasts. Application of this new approach to a medium-sized DSGE model improves the accuracy of density forecasts, particularly the coverage of predictive intervals, of US real macro variables. The application also shows that the estimated relative importance of business cycle sources varies with data maturity.
Author: Pablo Guerrón-Quintana
Publisher:
ISBN:
Category :
Languages : en
Pages : 46
Get Book Here
Book Description
This paper explores the effects of using alternative data sets for the estimation of DSGE models. I find that the estimated structural parameters and the model's outcomes are sensitive to the variables used for estimation. Depending on the set of variables the point estimate for habit formation ranges from 0.70 to 0.97. Similarly, the interest-smoothing coefficient in the Taylor rule fluctuates between 0.06 and 0.76. In terms of the model's predictions, if interest rates are excluded during estimation, the estimated structural coefficients are such that the model forecasts a strong deflation following an expansionary monetary expansion. Three ways to assess different observable sets are proposed. Based on these measures, I find that that including the price of investment in the data set delivers the best results.
Author: Mr.Maxym Kryshko
Publisher: International Monetary Fund
ISBN: 1463904215
Category : Business & Economics
Languages : en
Pages : 62
Get Book Here
Book Description
When estimating DSGE models, the number of observable economic variables is usually kept small, and it is conveniently assumed that DSGE model variables are perfectly measured by a single data series. Building upon Boivin and Giannoni (2006), we relax these two assumptions and estimate a fairly simple monetary DSGE model on a richer data set. Using post-1983 U.S.data on real output, inflation, nominal interest rates, measures of inverse money velocity, and a large panel of informational series, we compare the data-rich DSGE model with the regular - few observables, perfect measurement - DSGE model in terms of deep parameter estimates, propagation of monetary policy and technology shocks and sources of business cycle fluctuations. We document that the data-rich DSGE model generates a higher implied duration of Calvo price contracts and a lower slope of the New Keynesian Phillips curve. To reduce the computational costs of the likelihood-based estimation, we employed a novel speedup as in Jungbacker and Koopman (2008) and achieved the time savings of 60 percent.
Author: John B. Taylor
Publisher: North Holland
ISBN:
Category : Business & Economics
Languages : en
Pages : 596
Get Book Here
Book Description
This text aims to provide a survey of the state of knowledge in the broad area that includes the theories and facts of economic growth and economic fluctuations, as well as the consequences of monetary and fiscal policies for general economic conditions.
