A standard approach in measuring the effect of monetary policy on output and prices is to estimate a VAR model, characterise somehow the monetary policy shock and then plot impulse responses. In this paper I attempt to do this exercise with Hungarian data. I compare two identification...

This paper empirically tests whether monetary policy can have a perverse effect on aggregate demand in emerging economies, because of short-term speculative inflows. For this purpose, a bayesian VAR is estimated on a panel of six major emerging countries. Monetary and risk shocks are identified...

Using Hungarian macroeconomic and financial data, we estimate a Bayesian structural VAR model suitable for macroprudential simulations. We identify standard macroeconomic and credit supply shocks by sign and zero restrictions. In contrast to the previous literature, different types of credit...

In this paper we introduce two general non-parametric first-order stationary time-series models for which marginal (invariant) and transition distributions are expressed as infinite-dimensional mixtures. That feature makes them the first Bayesian stationary fully non-parametric models developed...

We are interested in forecasting bankruptcies in a probabilistic way. Specifically, we compare the classification performance of several statistical and machine-learning techniques, namely discriminant analysis (Altman's Z-score), logistic regression, least-squares support vector machines and...

This Paper describes a procedure for constructing theory restricted prior distributions for BVAR models. The Bayes Factor, which is obtained without any additional computational e?ort, can be used to assess the plausibility of the restrictions imposed on the VAR parameter vector by competing...

We propose a Bayesian approach to dynamic panel estimation in the presence of cross-sectional dependence and dynamic heterogeneity which is suitable for inference in short panels, unlike alternative estimators. Monte Carlo simulations indicate that our estimator produces less bias, and a lower...

In this paper, I discuss the difference between accommodated evidence (i.e. when evidence is known first and a hypothesis is the proposed to explain and fit the observations) and predicted evidence (i.e., when evidence verifies the prediction of a hypothesis formulated before observing the...

Maniadis et al. (2013) present a theoretical framework that aims at providing insights into the mechanics of proper inference. They suggest that a decision about whether to call an experimental finding noteworthy, or deserving of great attention, should be based on the calculated post-study...

This paper presents a novel Bayesian method for estimating dynamic stochastic general equilibrium (DSGE) models subject to a constrained posterior distribution of the implied Sharpe ratio. We apply our methodology to a DSGE model with habit formation in consumption and leisure, using an estimate...