This study examines the use of the exchange rate by the Czech National Bank as a monetary policy instrument at the zero lower bound on interest rates. It provides a review of the economic literature on unconventional monetary policy instruments and particularly on the possibility of using the...

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...

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...

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...

This paper concentrates on describing the available empirical findings on monetary policy transmission in the Czech Republic. Besides the overall impact of monetary policy on inflation and output, it is useful to study its individual channels, in particular the interest rate channel, the...

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...