
Three Essays on Empirical Analysis of Economic Policy
Baxa, Jaromír ; Vošvrda, Miloslav (advisor) ; Vašíček, Osvald (referee) ; Hančlová, Jana (referee) ; Slačálek, Jiří (referee)
This dissertation thesis is focused on the empirical analysis of monetary and fiscal policy using nonlinear models. In the first part, I examine the evolution of monetary policy rules in a group of inflation targeting countries. I apply a momentbased estimator in a timevarying parameter model with endogenous regressors. The main findings are twofold. First, with adoption of inflation targeting, coefficients in the monetary policy rules changed rather gradually. Second, the response of interest rates to inflation is particularly strong during periods when central bankers want to break a record of high inflation. Contrary to common view, the response of interest rates to inflation becomes less aggressive after the adoption of inflation targeting, suggesting a positive anchoring effect of this regime on inflation expectations. The second part discusses whether and how the selected central banks responded to episodes of financial stress over the last three decades. The timevarying monetary policy rule is extended for an indicator of financial stress, in order to show the departures of policy rules under financial instability. The findings suggest that central banks often decrease policy rates in the face of high financial stress. However, the size of the policy response varies substantially over time as well...


Predikce měnových kurzů
Dror, Marika ; Pánková, Václava (advisor) ; Arltová, Markéta (referee) ; Hančlová, Jana (referee)
The thesis investigates different exchange rate models and their forecasting performance. The work takes previous literature overview and summarize their findings. Despite the significant amount of papers which were done on the topic of exchange rate forecast, basically none of them cannot find an appropriate model which would outperform a forecast of a simple random walk in every horizon or for any currency pair. However, there are some positive findings in specific cases (e.g. for specific pair or for specific time horizon). The study provides uptodate analysis of four exchange rates (USD/CZK, USD/ILS, USD/GBP and USD/EUR) for the period of time from January 2000 to August 2013 and analyse forecasting performance of seven exchange rate models (uncovered interest rate parity model, purchasing power parity model, monetary model, monetary model with error correction, Taylor rule model, hidden Markov model and ESTAR model). Although, the results are in advantage of Taylor rule model, especially for the exchange rate of USD/CZK, I cannot prove that the forecasting performance is significantly better than the random walk model. Except of the overall analysis, the work suppose instabilities in the time. Stock and Watson (2003) found that the forecast predictability is not stable over time. As a consequence, the econometric model can give us better forecast than random walk process at some period of time, however at other period, the forecasting ability can be worse than random walk. Based on Fluctuation test of Giacomini and Rossi (2010a) every model is analysed how the outofsample forecast ability changes over time.


Aplikace optimalizačních metod na problémy výroby elektřiny
Šumbera, Jiří ; Dlouhý, Martin (advisor) ; Pelikán, Jan (referee) ; Hančlová, Jana (referee)
This thesis deals with application of optimisation methods based on linear and mixedinteger linear programming to various problems in the power sector related to electricity production. The thesis goal is to test the applicability of such methods to formulating and solving various instances from the class of realworld electricity production problems, and to find the advantages and disadvantages associated with using these methods. Introductory chapters describe the main characteristics of power markets, including the historical and regulatory context. Fundamental properties of power markets on both demand and supply side are also described, both from a realworld and a modelling point of view. Benefits of optimisation and modelling are discussed, in particular the solution feasibility and optimality as well as insights gained from sensitivity analysis which is often difficult to replicate with the original system. In the core of the thesis, optimisation techniques are applied to three case studies, each of which deals with a specific problem arising during electricity production. In the first problem, the profit of gasfired power plant in Slovakia from selling power on the dayahead market is maximised. The model is set up using both technical and commercial constraints. The second problem deals with the problem of representing a twodimensional production function which primarily arises for a hydro generator with large variations in the level of its reservoir. Several representations of the original function using piecewise linear subsets are presented, compared, and characterised by their computational intensity both theoretically and practically. In the third problem, the prices on the German dayahead market in 2011 are modelled. Contrary to the previous two models, the model does not capture an optimisation problem faced by a single producer, but incorporates a large subset of the whole market instead. Consequently the model is formed out of generic constraints relevant to all power plants whose parameters are estimated. By combining information about the aggregate availability of power plants with the estimated efficiencies a full supply curve for each day is created. Different scenarios are analysed to test the impact of uncertain inputs such as unknown or estimated constraints. The choice of the investigated problems stems from the attempt to cover electricity production problems from the point of view of multiple criteria. The three investigated electricity production problems span a broad range from the decisions of a single power plant to the modelling a power market as a whole. Formulations of the production function with different level of detail are presented ranging from a simple linear relationship to several bivariate function formulations. While each problem answers a specific question, they all illustrate the ease with which various electricity production problems can solved using optimisation methods based on linear and mixedinteger linear programming. This is mainly due to the ability of these methods to approximate even nonlinear functions and constraints over nonconvex domains and find global solutions in reasonable time. Moreover, models formulated with these methods allow sensitivity and scenario analyses to be carried out easily as is illustrated in each of the case studies.
