widely used two-step approach for SVARs: beginning with estimation of a reduced form and then choosing among observationally … form is a tractable known model for which I provide the first algorithm for Bayesian estimation of all free parameters. I …

Several lessons learned from a Bayesian analysis of basic economic time series models by means of the Gibbs sampling …

observations. A key feature of our approach is the use of the highly efficient difference estimator from the survey sampling …

We consider an adaptive importance sampling approach to estimating the marginal likelihood, a quantity that is … importance sampling approach is that random samples can be obtained from some convenient density with little additional costs. As …

inference that feature varying level of trade-off between estimation precision and computational speed. Using monthly data for …

the fast-time-time scale sampling frequency is held fixed. The realized kernel density estimation enriches the literature … estimation method is applied to DAX intraday prices, which balances between the bias and the variance of the realized moments … with respect to the bandwidth selection as well as the sampling frequency selection. The main finding is that the kernel …