This paper proposes an approach to explore the strength of the financial system of Turkey against the possibility of financial disturbances appearing based on the construction of the Index of Financial Safety (IFS) of a country. For this purpose the macro-prudential approach, system analyses,...

This paper addresses two important questions that have, so far, been studied separately in the literature. First, the paper aims at explaining the high volatility of long-term interest rates observed in the data, which is hard to replicate using standard macro models. Building a small-scale...

We propose a method to incorporate information from Dynamic Stochastic General Equilibrium (DSGE) models into Dynamic Factor Analysis. The method combines a procedure previously applied for Bayesian Vector Autoregressions and a Gibbs Sampling approach for Dynamic Factor Models. The factors in...

This paper proposes a framework for modelling financial contagion that is based on SIR (Susceptible-Infected-Recovered) transmission models from epidemic theory. This class of models addresses two important features of contagion modelling, which are a common shortcoming of most existing...

Recent advances in empirical finance has shown that the adoption of network theory is critical to understand contagion and systemic vulnerabilities. While interdependencies among financial markets have been widely examined, only few studies review networks, however, they do not focus on the...

This paper considers a sparsity approach for inference in large vector autoregressive (VAR) models. The approach is based on a Bayesian procedure and a graphical representation of VAR models. We discuss a Markov chain Monte Carlo algorithm for sparse graph selection, parameter estimation, and...

This paper presents the R-package MitISEM (mixture of t by importance sampling weighted expectation maximization) which provides an automatic and flexible two-stage method to approximate a non-elliptical target density kernel -- typically a posterior density kernel -- using an adaptive mixture...

In this article the theoretical analysis and practical application of Bayesian approach for vector autoregressive model parameters estimation with different priors have been peformed. The time series was from 2001Q1 to 2010Q4 and included the following variables: GDP, CPI, exchange rate,...

Several lessons learned from a Bayesian analysis of basic economic time series models by means of the Gibbs sampling algorithm are presented. Models include the Cochrane-Orcutt model for serial correlation, the Koyck distributed lag model, the Unit Root model, the Instrumental Variables model...

Several lessons learned from a Bayesian analysis of basic economic time series models by means of the Gibbs sampling algorithm are presented. Models include the Cochrane-Orcutt model for serial correlation, the Koyck distributed lag model, the Unit Root model, the Instrumental Variables model...