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Macroeconomic Effects of Fiscal Policy in the Czech Republic: Evidence Based on Various Identification Approaches in a VAR Framework
Franta, Michal
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 techniques. Finally, all identification approaches that are currently employed by the literature and that are applicable to the Czech Republic are used. The estimation results suggest that the fiscal policy transmission mechanism in the Czech Republic exhibits some standard features (e.g., a rise in GDP and inflation after unexpected government spending, and an increase in government spending after a positive shock to government revenues). However, the uncertainty associated with the results is substantial. Furthermore, it is discussed how the identification strategy itself may represent an additional source of uncertainty of the results. JEL
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Issues in adopting DSGE models for use in the policy process
Fukač, Martin ; Pagan, Adrian
This discussion is structured by three concerns – model design, matching the data and operational requirements. The paper begins with a general discussion of the structure of dynamic stochastic general equilibrium (DSGE) models where writers investigate issues like (i) the type of restrictions being imposed by DSGE models upon system dynamics, (ii) the implication these models would have for "location parameters", viz. growth rates, and (iii) whether these models can track the long-run movements in variables as well as matching dynamic adjustment.
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Statistical inference for categorical data analysis
Kocáb, Jan ; Pecáková, Iva (advisor) ; Coufalová, Petra (referee)
This thesis introduces statistical methods for categorical data. These methods are especially used in social sciences such as sociology, psychology and political science, but their importance has increased also in medical and technical sciences. In the first part there is mentioned statistical inference for a proportion. Here is written about classical, exact and Bayesian methods for estimating and hypothesis testing. If we have a large sample then we can approximate exact distribution by normal distribution but if we have a small sample cannot use this approximation and it is necessary to use discrete distribution which makes inference more complicated. The second part deals with two categorical variables analysis in contingency tables. Here are explained measures of association for 2 x 2 contingency tables such as difference of proportion and odds ratio and also presented how we can test independence in the case of large sample and small one. If we have small sample we are not allowed to use classical chi-squared tests and it is necessary to use alternative methods. This part contains variety of exact tests of independence and Bayesian approach for the 2 x 2 table too. In the end of this part there is written about a table for two dependent samples and we are interested whether two variables give identical results which occurs when marginal proportions are equal. In the last part there are methods used on data and discussed results.
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