Central European Journal of Economic Modelling and Econometrics

We introduce consumption habits into a real-business-cycle setup augmented with a detailed government sector. We calibrate the model to Bulgarian data for the period following the introduction of the currency board arrangement (1999-2018). We investigate the quantitative importance of the presence of internal consumption habits motive for the propagation cyclical fluctuations in Bulgaria. Allowing for internal habits in household’s consumption improves the model performance against data, and in addition this extended setup dominates the standard RBC model framework without habits. Therefore, the computational experiments performed in this paper suggest that habits are a quantitatively important model ingredient, which should be taken into consideration when analysing the effects of different policies in Bulgaria. This result can be viewed as an empirical validation of the habit model, and a rejection of the model without habits in the case of Bulgaria. In addition, we also demonstrate that internal habits are quantitatively more important than external habits for the Bulgarian business cycle.

The goal of the paper is to verify the direction of sovereign risk transmission between sovereign CDS and sovereign bond markets in the Central European economies: the Czech Republic, Hungary and Poland. We focus on the hectic crisis period of 2008-2013. On the one hand, the sCDS market is said to react faster to the news than the sovereign bonds market. On the other hand, the bond market is related more closely to the internal situation of the country than the sCDS one and thus can price the sovereign risk more accurate. Moreover, the relationships between the markets can change during crisis time. We find that in the case of most risky and most indebted economy in Hungary there was a feedback between sCDS and sovereign bonds risk. In the case of Poland sCDS market risk Granger caused the risk of sovereign bonds – if we exclude instantaneous causality from the analysis; when it is included, feedback occurred. Eventually, in the case of the Czech Republic the risk of sCDS market Granger caused risk of the bonds market.

Hybrid MSV-MGARCH models, in particular the MSF-SBEKK specification, proved useful in multivariate modelling of returns on financial and commodity markets. The initial MSF-MGARCH structure, called LN-MSF-MGARCH here, is obtained by multiplying the MGARCH conditional covariance matrix H_t by a scalar random variable g_t such that{ln g_t, t ∈ Z} is a Gaussian AR(1) latent process with auto-regression parameter φ. Here we alsoconsider an IG-MSF-MGARCH specification, which is a hybrid generalisation of conditionally Student t MGARCH models, since the latent process {g_t} is no longer marginally log-normal (LN), but for φ = 0 it leads to an inverted gamma (IG) distribution for g_t and to the t-MGARCH case. If φ =/ 0, the latent variables g_t are dependent, so (in comparison to the t-MGARCH specification) we get an additional source of dependence and one more parameter. Due to the existence of latent processes, the Bayesian approach, equipped with MCMC simulation techniques, is a natural and feasible statistical tool to deal with MSF-MGARCH models. In this paper we show how the distributional assumptions for the latent process together with the specification of the prior density for its parameters affect posterior results, in particular the ones related to adequacy of thet-MGARCH model. Our empirical findings demonstrate sensitivity of inference on the latent process and its parameters, but, fortunately, neither on volatility of the returns nor on their conditional correlation. The new IG-MSF-MGARCH specification is based on a more volatile latent process than the older LN-MSF-MGARCH structure, so the new one may lead to lower values of φ – even so low that they can justify the popular t-MGARCH model.