Osvald Vašíček

Financial Frictions Relevance during the Crisis: Czech Case

In this paper, we estimate a small open economy dynamic stochastic general equilibrium model with financial accelerator. Our aim is to find a satellite model with financial block for imposing judgments on comprehensive models which lack direct financial variables. We choose the model originally developed by Mohamad Hasni Shaari [5] as our starting point. After the basic introduction to the model, we show results for a Bayesian estimation and a recursive Bayesian estimation on Czech data. Finally, we carry out an experiment which shows us that the reducing interest rates would probably be faster, bigger and longer lasting with a model, which in itself contains financial frictions. On the other hand, the risk of such a decision stems from the instability of estimated parameters.

Structural changes in the Czech, Slovak and euro area economies during the Great Recession

Abstract The goal of this paper is to identify and compare the most important changes in the structure of the Czech economy, as a small open economy with independent monetary policy, the Slovak economy, as a small open economy that entered monetary union, and the economy of the euro area, which has a common monetary policy, during the turbulent period of the Great Recession, the subsequent anaemic recovery and recent disinflationary period. Structural changes are identified with the help of nonlinear dynamic stochastic models of general equilibrium with time-varying parameters. The model parameters are estimated using Bayesian methods and a nonlinear particle filter. The results confirm the similarity of the Czech and Slovak economies and show that in certain respects the structure of the Czech economy might be closer to that of the euro area than that of Slovakia. The time-varying estimates reveal many similarities between the parameter changes in the Czech economy and those in the euro area. In Slovakia, the situation during the Great Recession was dominated by the country’s adoption of the euro, which caused large deviations in its Calvo parameters.

Habit Formation, Price Indexation and Wage Indexation in the DSGE Model: Specification, Estimation and Model Fit

Habit Formation, Price Indexation and Wage Indexation in the DSGE Model: Specification, Estimation and Model Fit In order to determine which specification provides better fit of the data, this paper presents several specifications of a closed economy DSGE model with nominal rigidities. The goal of this paper is to find out whether some characteristics widely used in New Keynesian DSGE models, such as habit formation in consumption, price indexation and wage indexation, provide better fit of the macroeconomic data. Model specifications are estimated on the data of the US economy and Euro Area 12 economy, using Bayesian techniques, particularly the Metropolis-Hastings algorithm (using Dynare toolbox for Matlab). The data fit measure is a Bayes factor calculated from marginal likelihoods, acquired from Bayesian estimation. Results suggest that including habit formation in consumption significantly improves the empirical data fit of the model, whereas including partial price indexation and partial wage indexation does not improve the empirical data fit of the model. Variants with full price indexation and full wage indexation were the worst ones concerning their data fit.

A Macroeconomic Model and Stability Analysis by Parameters

This article focuses on the New Keynesian multiple-equations small-open-economy macroeconomic model to illustrate deeper relations among model parameters. These relations are more important than the basic values of the parameters because it shows how the system behaves when some changes in the economy occur. The first stage of the analysis introduces a theoretical model. The second stage of the analysis estimates the states and parameters of the model on the quarterly data of the Czech economy. The third stage of the analysis focuses on the transfer function of this model and makes a deeper behavior analysis. In the final stage, the article demonstrates the stability of the model, shown through the impulse functions of the model. This shows response of the macroeconomic model to unanticipated shocks.

Chapter 18 – Identification and Analysis of the Naip Model within a State-Space Framework

Publisher Summary This chapter presents identification and analysis of the non-accelerating inflation product (NAIP) model within a state-space framework. The iterated extended Kalman filter is employed to identify the unobserved states and time-varying parameters. As an approximation of the potential product, the NAIP model is used. The term NAIP is introduced to distinguish among different structural models. The potential product in this concept is modeled as a real product level at which inflation is stable and does not accelerate or decelerate. The model has been estimated in its state-space representation using 30 iterations of EKFS. With this number of iterations, the values of parameters converged and their trajectories are smooth enough to consider the parameters as time invariant. The results are presented for both the time-varying parameters and time-invariant parameters. It can be seen that both cases produce similar responses that only confirm the original statement. It is found that the model implies correct economic relations between model variables.

Chapter 23 – Alternative Models of Adaptive and Near-Rational Expectations — Classification by Bootstrap Filter

Publisher Summary This chapter examines the alternative models of adaptive and near-rational expectations-classification by Bootstrap filter. The problem of deciding between alternative hypotheses is common. There may be two or more theories on a model background or parameter values and the data should determine which alternative is the most plausible. In case one of these models is nonlinear, the Monte Carlo approach should be used instead of linear methods. Such an approach is employed for classifying expectation formation within augmented Phillips curve. It is found that before the prediction phase the importance resampling is performed. It makes it no longer necessary to calculate with sample weights, because they are all equal. The other advantage is that there are no samples with small weights. Some samples with greater weight are selected two or more times while some samples are not selected at all. The prediction step is realized according to the state space model of the system. The probability of each model is computed based on the data. Such an approach is used for the classification of alternative economic models of expectation formation.

Alternative Models of Adaptive and Near-Rational Expectations — Classification by Bootstrap Filter

Abstract The problem of deciding between alternative hypotheses is common. There may exist two or more theories on a model background or parameter values and the data should determine which alternative is the most plausible. In case one of these models is nonlinear, the Monte Carlo approach should be used instead of linear methods. Such an approach is employed for classifying expectation formation within augmented Phillips curve.

Identification and Analysis of the Naip Model Within a State-Space Framework

Abstract In this paper we try to measure the production gap and consequently the Non-Accelerating Inflation Product as a kind of the potential output. The iterated extended Kalman filter is employed to identify unobserved states and time-varying parameters. The analysis is performed on the data of the Czech economy.

Parameter Estimation of US Macroeconomic Alternative Models

Abstract Simple model of US macroeconomy is considered in this paper. Extended Kalman filter is used for state and parameter estimation of this simple macroeconomic model. Smoothing procedure is also used to obtain estimates conditioned by whole set of data. Alternative models of parameter development are used and their probability is evaluated based on the given data. Some interesting results are obtained.