European Parliament Library

Bayesian Dynamic Factor Analysis of a Simple Monetary DSGE Model, Maxym Kryshko

Abstract
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
Table Of Contents
Cover Page; Title Page; Copyright Page; Contents; List of Figures; List of Tables; I. INTRODUCTION; II. DATA-RICH DSGE MODEL; REGULAR VS. DATA-RICH DSGE MODELS; B. ENVIRONMENT; Households; Final Good Firms; Intermediate Goods Firms; Monetary and Fiscal Policy; Aggregation; III. ECONOMETRIC METHODOLOGY; A. ESTIMATION OF THE DATA-RICH DSGE MODEL; B. SPEED-UP: JUNGBACKER AND KOOPMAN 2008; IV. DATA AND TRANSFORMATIONS; V. EMPIRICAL RESULTS; A. PRIORS; B. POSTERIORS: REGULAR VS. DATA-RICH DSGE MODEL; C. ESTIMATED STATES: REGULAR VS. DATA-RICH DSGE MODEL; D. SOURCES OF BUSINESS CYCLE FLUCTUATIONS
Language
eng
Literary Form
non fiction
Note
Description based upon print version of record
Physical Description
1 online resource (92 p.)
Specific Material Designation
remote
Form Of Item
online
Isbn
9781283567183

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