C61 - Optimization Techniques; Programming Models; Dynamic AnalysisReturn

Dynamic Model of Common-pool Emission Permit Market as a Method for Solving the Persistent Pollutant Problem In the paper, we develop a common-pool permit market formulated as a dynamic gross pool for trading emission discharge permits (EDPs) for persistent pollutants. We discuss individual agents' demand decisions concerning EDPs and develop a common-pool market dynamic gross pool formulation, including a general set of marginal-cost pricing rules used in this type of permit trading market. Numerical simulations are used to illustrate the usefulness of this type of permit market design for addressing environmental problems.

This paper provides the first academic economic simulation analysis of the impact of increase in predominantly German wind and solar energy production on the Czech electricity transmission network. To assess the exact impact on the transmission grid, updated state-of-the-art techno-economic model ELMOD is employed. Two scenarios for the year 2025 are evaluated on the basis of two representative weeks. The first scenario is considered as baseline and models currently used production mix. The second scenario focuses on the effect of German Energiewende policy on the transmission networks as expected in 2025. The results confirm that in the context of Central Europe, higher feed-in of solar and wind power increases the total transport of electricity between the transmission system operator areas as well as the average load of lines and volatility of flows. Also, an increase in number of critical high-load hours is observable. Taking into account only the Czech transmission system, considerable rise both in transported volume and volatility are observed only on border transmission lines, not inside the country. Moreover, our qualitative analysis shows that all these mentioned effects are strengthened by the presence of German- -Austrian bidding zone.

The models from the GARCH family are often estimated by maximum likelihood method, either parametrically or non-parametrically. Since the parametric estimation procedure is based on an a priori distribution, its misspecification can lead to the inconsistency of the estimators. Therefore non-parametric approach, in which both model's parameters and the distribution of error terms are estimated from the data, seems to be a better alternative. In our work, we propose a non-parametric technique with the use of a heuristic called differential evolution to estimate the parameters of a GARCH-M model. This technique can more likely reach to a global solution of maximum likelihood estimation (MLE) task. Further, it can also more effectively control the required properties of the estimates. The suitability of our approach is verified on modeling the CZK/USD and CZK/EURO forward exchange rate premium of period from 2007 to 2012 by a GARCH-M model.

The paper analyzes 10-year government bond and stock index of the Czech Republic and the United States in period from January 2002 to February 2012. Main purpose of the paper is to show connection between bond and stock market and verify whether bonds can be taken as stock indicators. A detailed study of fi nancial time series of both countries is performed. Different stages of each financial time series which is called bear, normal and bull state are presented. The conclusion is that all three stages have different means return and they are in accordance with financial theory. For the division of time series into each state Markov-Switching model is used.

The paper analyses impacts of environmental regulation on Czech power system. We employ MESSAGE modelling platform to construct a dynamic linear optimisation energy model of the Czech power system. We analyse regulation impacts on fuel use and CO2 emission, fuel-mix and technology-mix, induced investment and fuel and other O&M costs to generate electricity over the period 2006-2030. Negative external costs attributable to endogenously determined new level of air quality pollutants are quantified to make our cost-benefit analysis more complex. Overall, effects of four policy scenarios are assessed, including subsidies for renewable energy, increase in air quality charge rates and an introduction of the EU ETS in the Czech power system. Based on our simulation, we find that prospected 10-fold increase in charging of air quality pollutant would not have any significant effect on emission and would not bring any stimuli for change in technology and fuel mixes. Subsidy to renewable energy would result in their development; however, larger effect would appear in far future and only if new nuclear power units are not allowed to build. Auctioned EUA, especially above €15 per tonne of CO2, would be the only effective instrument with significant effects on power sector. Key factor on CO2 emission is whether scenario consists of new nuclear power units or these units are banned. Our simulation results hold even if we allow the key model assumption to vary, except, the discount rate that would have effect on whether more-investment intensive technologies are used to generate electricity.

Currently a considerable attention to the subject of network industries is being paid in discussions on various levels. It is understandable as network industries in fact ensure the production and distribution of energy sources which play a key role in developed economies. The discussions are usually focused on the question of reasonable profit of network industries subjects and on the other hand the question of generally acceptable costs. Equilibrium on the network industries market, as well as on any market, is being created based on the level of demand and supply on relevant market. In this article we will discuss the analysis of optimization models of consumers and producers behavior on the network industries market as well as the question of effectiveness of this specific market. We will point out certain features of network industries market where the consumer usually is not able to substitute a product of network industry with other product of appropriate characteristics in a short time period, thus considering the product being exclusive. This exclusivity can be formally represented in the utility function and other related analytical tasks. In paper we study the properties of a network industry optimization problem and economically interpretable implications of Kuhn-Tucker optimality conditions of this model.

Knowledgeability about interest rates set by a central bank is very important for all participants in an economy. In this paper we have used publicly available data to model how Czech National Bank manipulates its 2W repo rate when conducts its monetary policy. For this purpose, eight indicators are chosen. They are the Consumer Price Index (CPI), GDP growth rate (HDP), the monthly exchange rate EURCZK (KURZ), the monthly growth rate of monetary aggregate M2 (M2), the monthly unemployment rate (NEZAM), the monetary policy interest rate of the European Central Bank (EBC), the two-week Prague Interbank Interest rate PRIBOR14 and Economic Sentiment Indicator (IES). First, they are used as explanatory variables and then as the input signals to two different artificial neural network types with different architecture: the multilayer perceptron (MLP) and radial basis function (RBF) nets with different number of hidden neurons to model 2W repo rate of CNB. As a result, we fi nd that while the RBF network fails to provide stable results superior to the one of the linear model, the MLP network always can deliver better results than the one of the linear model. The best results are achieved with a network with only two hidden neurons. Further, these results are relatively stable with minimum time needed to complete the calculation. The MLP network therefore seems to be a promising tool for modeling the 2W repo rate of CNB.

This paper presents results of repeated economic lab experiments. They were designed to test a model of combinatorial auctions on the case of providing financial support (capital investment subsidies) to polluters. Combinatorial auctions are those auctions in which bidders can place bids on combinations of items. The advantage of combinatorial auctions is that the bidder can more fully express his preferences. This is particular important when items are complements. In the experiment presented in the paper, the polluters have two options: (i) to invest individually or (ii) create coalitions, i.e. to prepare and realize common capital investment projects. The common model of combinatorial auctions is described first in the paper. The design of the laboratory experiment is presented in the next section and the results are shown in the last section.

Our study contains application of Latent Semantic Indexing on financial crises prediction. Hypothesis to test was that equity markets are able to predict even sharp changes in monetary policy during a quarter ahead of such a change (which was searched during two quarters that followed). This hypothesis, tested on sample of 36 countries between years 1985 and 2007, has been confirmed according to interest rate and foreign exchange expert interpretation. The studied application of LSI even though it timed several crises on their exact start day is not suitable for financial crises prediction but can be recommended for specification and analysis of fragile countries which are or could be prone to a crisis.

The impact of different financing alternatives on two simple models of the university system is analysed in this paper. Both models are agent - based, the reason is that we analyse a system of heterogeneous universities instead of a representative university. Models differ in the rules for the decision-making of universities. In the first - optimising model - each university in each period maximalizes the probability of survival, control variables are the income of universities and the salary of teachers. In the second model we implicitly assume constrained rationality or shortage of relevant information and each university in each period reacts according to simple rules on the difference between the number of applicants and its capacity. Basic result is that the behaviour of models in different situations differs with the financing alternatives and it would be an oversimplification to generalize that some of the financing alternative is always the best.

The paper deals with yield curve construction methods using coupon bonds in Czech bond market. Generally, there are more possibilities how to approach this problem: bootstraping, splines, parametric functions. Due to the lack of tradable public bonds and due to the fact that existing bonds do not pay coupons at the same date of the year, traditional bootstraping method could not be applied under Czech market conditions. It seemed appropriate to use parametrical solutions to the yield curve issue and minimise the sum of squares of differences between market and theoretical prices. There were presented three function types which arrived to similar results in the paper. The authors also used Svensson parametric function to demonstrate the possible use of parametric yield curve construction. It was shown that, after duration adjustment, it can indicate shift in market expectations regarding future short term interest rate moves, and thus regarding future monetary policy, pretty well.

The paper presents the optimal control theory and the maximum principle technique that is suitable for solving dynamic optimalization problems in continuous time. Modern mainstream macroeconomics stresses microeconomics principles of solved problems. However, the application of the standard microeconomic approach - the static optimalization - needs to be replaced in macroeconomics by more sophisticated methods. The maximum principle is one of the possible tools. This text briefly introduces the basics of this method to Czech readers. More detailed treatment can be found in the original literature. The maximum principle method can be applied not only in solving macroeconomic problems, but also in many different areas that deal with the optimalization in continuous time, e.g. finance or engineering.