Bayesian Mixed Frequency Estimation of DSGE models
نویسنده
چکیده
In this paper, we present an alternative strategy for estimation of DSGE models when data is available at di¤erent time intervals. Our method is based on a data augmentation technique within Bayesian estimation of structural models and allows us to jointly use data at di¤erent frequencies. The bene ts achieved via this methodology will be twofold, resolution of time aggregation bias and identi cation advantage. This paper works with a simple Real Business Cycle model and estimate structural parameters such total factor productivity, discount factor, depreciation rate of capital and capital share in production technology. When we follow the standard practice of estimation, i.e. Quarterly estimation, total factor productivity persistent parameter was downward biased and its standard deviation was upward biased relative to our benchmark estimation. Also our benchmark estimation shows an identi ction advantage over Coarse estimation. Keywords : Bayesian Estimation, Mixed Frequency Estimation, Time Aggregation Bias JEL Classi cation : C13, C53, C82
منابع مشابه
Does the DSGE Model Fit the Chinese Economy? A Bayesian and Indirect Inference Approach by
This thesis makes three main contributions to the literature on Dynamic Stochastic General Equilibrium (DSGE) models in Macroeconomics. As no previous studies have studied the Chinese economy from the perspective of DSGE, the first contribution of this thesis is estimating a DSGE model for China through a Bayesian approach using the Chinese quarterly post-economic reform data representing the m...
متن کاملBayesian Inference for Spatial Beta Generalized Linear Mixed Models
In some applications, the response variable assumes values in the unit interval. The standard linear regression model is not appropriate for modelling this type of data because the normality assumption is not met. Alternatively, the beta regression model has been introduced to analyze such observations. A beta distribution represents a flexible density family on (0, 1) interval that covers symm...
متن کاملSequential Monte Carlo samplers for Bayesian DSGE models
Bayesian estimation of DSGE models typically uses Markov chain Monte Carlo as importance sampling (IS) algorithms have a difficult time in high-dimensional spaces. I develop improved IS algorithms for DSGE models using recent advances in Monte Carlo methods known as sequential Monte Carlo samplers. Sequential Monte Carlo samplers are a generalization of particle filtering designed for full simu...
متن کاملBayesian forecasting with small and medium scale factor-augmented vector autoregressive DSGE models
Advanced Bayesian methods are employed in estimating dynamic stochastic general equilibrium (DSGE) models. Although policymakers and practitioners are particularly interested in DSGE models, these are typically too stylized to be taken directly to the data and often yield weak prediction results. Hybrid models can deal with some of the DSGE model misspeci cations. Major advances in Bayesian est...
متن کاملThe Anatomy of DSGE Models with Banking Industry for Iran's Economy
The recent financial crisis has raised several questions with respect to the financial institutions and banking industry. Hence, over the last decade the Iranian banking industry has undergone many substantial changes, such as liberalization, government regulation and technological advances. What impacts do these changes have on the policy instruments? We have answered this question in this stu...
متن کامل