nep-ets New Economics Papers
on Econometric Time Series
Issue of 2013‒10‒02
two papers chosen by
Yong Yin
SUNY at Buffalo

  1. Exact Solutions for the Transient Densities of Continuous-Time Markov Switching Models - With an Application to the Poisson Multifractal Model By Thomas Lux
  2. Evaluating point and density forecasts of DSGE models By Wolters, Maik H.

  1. By: Thomas Lux
    Abstract: This paper shows how exact solutions for the transient density of a large class of continuous-time Markov switching models can be obtained. We illustrate the pertinent approach for both simple diffusion models with a small number of regimes as well as for the more complicated so-called Poisson multifractal model introduced by Calvet and Fisher (2001) with an arbitrarily large number of regimes. Our results can be immediately applied as well to various popular Markov switching models in financial economics. Closed-form solutions provide for the possibility of exact maximum likelihood estimation for discretely sampled Markov-switching diffusions and also facilitate the use of such models in applied tasks such as option pricing and portfolio management
    Keywords: regime switching, continuous-time models, multifractal models
    JEL: C13 C58 G12
    Date: 2013–09
  2. By: Wolters, Maik H.
    Abstract: This paper investigates the accuracy of forecasts from four DSGE models for inflation, output growth and the federal funds rate using a real-time dataset synchronized with the Fed's Greenbook projections. Conditioning the model forecasts on the Greenbook nowcasts leads to forecasts that are as accurate as the Greenbook projections for output growth and the federal funds rate. Only for inflation the model forecasts are dominated by the Greenbook projections. A comparison with forecasts from Bayesian VARs shows that the economic structure of the DSGE models which is useful for the interpretation of forecasts does not lower the accuracy of forecasts. Combining forecasts of several DSGE models increases precision in comparison to individual model forecasts. Comparing density forecasts with the actual distribution of observations shows that DSGE models overestimate uncertainty around point forecasts. --
    Keywords: DSGE models,Bayesian VAR,forecasting,model uncertainty,forecast combination,density forecasts,real-time data,Greenbook
    JEL: C53 E31 E32 E37
    Date: 2013

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