In this paper we adopt the Hamiltonian Monte Carlo (HMC) estimator for DSGE models by implementing it into a state-of-the-art, freely available high-performance software package. We estimate a small scale textbook New-Keynesian model and the Smets-Wouters model on US data. Our results and...

In this chapter, both Maximum likelihood estimation (MLE) and Bayesian MCMC estimation methods are used to test their parameters estimation power while estimating a Markov-Switching generalized autoregressive conditional heteroscedasticity (MS-GARCH) model. The monthly exchange rates of BRICS...

This note provides the details of the estimation procedure in Br¨unner (2019). In Section 2 we derive the posterior distribution. Section 3 describes the MCMC algorithm used to obtain draws from the posterior distribution and in Section 4 we present the method for our model check. We conclude...

Based on a record sample from the Rayleigh model, we consider the problem of estimating the scale and location parameters of the model and predicting the future unobserved record data. Maximum likelihood and Bayesian approaches under different loss functions are used to estimate the model's...