E17 - General Aggregative Models: Forecasting and Simulation: Models and ApplicationsReturn

The paper deals with a comparison of alternative monetary policy rules also known as Taylor rules. First, a New Keynesian DSGE model is specified. Results of this model are used as a benchmark. These results are obtained using Bayesian techniques. Bayesian techniques are used for both the estimation and the subsequent model comparison. The main experiment introduces three modifications to monetary policy rules. One specifies simple, Svensson and forward-looking monetary policy rules. The estimation is performed on Czech data and the period is from 2000Q1 to 2012Q3. Each specification of the New Keynesian model contains the same observed variables, GDP growth and inflation. The estimation of the benchmark model contains an interesting output as a shock decomposition of both the observed variables. The main finding of this paper is that the parameter estimates of all the modifications of monetary policy rules are almost the same and the log data density looks very similar for all the specified models. On the other hand, a completely opposite conclusion may be derived from the results of the Bayesian comparison of the DSGE models. The key output is that a forward-looking monetary policy rule significantly improves the ability of the New Keynesian DSGE model to fit the observed data.

Enormous development of firm valuation from many aspects can be seen in the recent period. One of the main fields is scoring, which provides a probability verdict about the future development of a firm: its probability of default. This article focuses on introducing macroeconomic modelling using VEC models to predict the future level of default in the Czech economy. Our results have proven a general connection between corporate defaults and the macroeconomic condition of the economy, which is going through a convergence process. The specific findings are new and have not been observed yet. A connection between the GDP and defaults revealed a positive relationship, which is probably a consequence of the convergence process, a development of the economy in many new fields. We have also found a long-term equilibrium among unemployment, loans, price of oil and defaults. We have revealed a higher level of defaults can be expected in 2013, which is connected with the economic contraction in the prediction period.

The paper deals with the estimation of the New Keynesian Phillips curve (NKPC). First, the history of the Phillips curve and the NKPC is outlined. Next, similar research and papers regarding the NKPC are mentioned. The main goal of the paper is to estimate the parameters of the NKPC using the Bayesian techniques. These techniques are widely used for the DSGE model estimation and this paper contains links to the source foreign literature. The NKPC is estimated as part of a fully calibrated Small Open Economy (SOE) DSGE model. The SOE DSGE model consists of households, firms, the government and the central bank. The estimation is performed on the Czech data and the period is from 2001Q1 to 2012Q2. The first output of the paper is the parameter estimates of the NKPC. The main finding is that the future expected inflation plays a crucial role in setting the level of inflation. Moreover, a shock decomposition of domestic and imported inflation is performed and the main output is that the domestic monetary policy shock causes crucial changes in the level of both domestic and imported inflation.

In this paper, I propose the use of fast Fourier transform (FFT) as a convenient tool for combining forecast densities of vector autoregressive models in a hybrid Bayesian manner. While a vast amount of papers comprises combinations based on normal approximations, Monte Carlo methods were fully utilized here, which made the analysis computationally demanding. For the sake of minimization of computational time, the FFT algorithm was used to combine the densities of poorly simulated partial models. As a result, a minor loss of quality in the final combined model was allowed, in contrast with the reduction in the necessary simulation time. However, it turns out in the end that the FFT-based approach exceeds 'brute-force' simulation in all aspects. The suggested method is demonstrated on an ex ante prediction of the Czech GDP and on a pair of artificial examples.