We investigate the evolution of the monetary policy transmission mechanism in the Czech Republic over the 1996-2010 period by employing a time-varying parameters Bayesian vector autoregression model with stochastic volatility. We evaluate whether the response of GDP and the price level to...

This paper shows how fan charts generated from Bayesian vector autoregression (BVAR) models can be useful for assessing 1) the forecasting accuracy of central banks’ prediction models and 2) the credibility of stress tests carried out to evaluate financial stability. Using unique data...

This paper examines the effect of non-linearities on density forecasting. It focuses on the relationship between credit markets and the rest of the economy. The possible non-linearity of this relationship is captured by a threshold vector autoregressive model estimated on the US data using...

The fiscal position of many countries is worrying - and getting worse. Should formally independent central bankers be concerned about observed fiscal excesses spilling over to monetary policy and jeopardizing price stability? To provide some insights, this paper tracks the interactions between...

The paper analyzes the macroeconomic effects of fiscal policy shocks in the Czech Republic. The low number of observations available for fiscal variables significantly affects the setup of the analysis. Firstly, a small-scale VAR is considered. Secondly, the model is estimated using Bayesian...

The paper focuses on the dynamics of unemployment in the Czech Republic over the period 1992-–2007. Unemployment dynamics are elaborated in terms of unemployment inflows and unemployment duration. The paper contributes to the literature dealing with discrete time models of aggregate...

Is inflation persistence in the new EU Member States (NMS) comparable to that in the euro area countries? We argue that persistence may not be as different between the two country groups as one might expect. We confirm that one should work carefully with the usual estimation methods when...

In this paper we use a battery of various mixed-frequency data models to forecast Czech GDP. The models employed are mixed-frequency vector autoregressions, mixed-data sampling models, and the dynamic factor model. Using a dataset of historical vintages of unrevised macroeconomic and financial...