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Bayesian Selective Transfer Learning for Patient-Specific Inference in Thyroid Radiotherapy
Murray, Sean Ernest ; Quinn, Anthony
This research report outlines a selective transfer approach for Bayesian estimation of patient-specific levels of radioiodine activity in the thyroid during the treatment of differentiated thyroid carcinoma. The work seeks to address some limitations of previous approaches [4] which involve generic, non-selective transfer of archival data. It is proposed that improvements in patient-specific inferences may be achieved via transferring external population knowledge selectively. This involves matching the patient to a similar sub-population based on available metadata, generating a Gaussian Mixture Model within the partitioned data, and optimally transferring a data predictive distribution from the sub-population to the specific patient. Additionally, a performance evaluation method is proposed and early-stage results presented.
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Mixing of Predictors in Parameter Estimation
Podlesna, Yana ; Kárný, Miroslav
This bachelor thesis deals with the design of the method for solving the curse of dimensionality arising in the quantitative modeling of complex interconnected systems. The employed predictive models are based on a discrete Markov process. Prediction is based on estimating model parameters using Bayesian statistics. This work contains method for reducing the amount of data needed for prediction in systems with a large number of occurring states and actions. Instead of estimating a predictor dependent on all parameters, the method assumes the use of several predictors, which arise from estimating parametric models based on dependences on different regressors. The behavioral properties of the proposed method are illustrated by simulation experiments.
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DSGE modeling of business cycle properties of Czech labor market
Sentivany, Daniel ; Maršál, Aleš (advisor) ; Rečka, Lukáš (referee)
The goal of this thesis is to develop a DSGE model that accounts for the key business cycle properties of the Czech labor market. We used standard New Keynesian framework for monetary policy analysis and incorporated an elaborated labor market setup with equi- librium wage derived via an alternating offer bargaining protocol originally proposed by Rubinstein (1982) and follow the work of Christiano, Eichenbaum and Trabandt (2013) in the following steps. Firstly, we calibrated the closed economy model according to values suited for the Czech economy and found that the model can not only account for higher volatility of the real wage and unemployment, but can also explain the contemporaneous rise of both wages and employment after an expansionary shock in the economy, so called Shimer puzzle (Shimer, 2005a). Secondly, we demonstrated that the alternating offer bar- gaining sharing rule outperforms the Nash sharing rule under assumption of using the hiring costs in our framework (more so while using search costs) and therefore is better suited for use in larger scale models. Thirdly, we concluded that after estimating the labor market parameters using the Czech data, our model disproved the relatively low values linked to the probabilities of unsuccessful bargaining and job destruction. JEL...
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Recursive estimation of models relating discrete-valued variables to continuous-valued ones applied to trading with futures
Svoboda, Miroslav ; Kárný, Miroslav (advisor) ; Hurt, Jan (referee)
This bachelor thesis deals with recursive estimation of a dependence of the models with discrete variables on variables that are either discretely or continuously distributed. To this purpose Bayes formula, described in the first chapter, is used, to which an additional assumption of conditional independence is added so that it can be used dynamically. The second chapter describes an approximation algorithm, which is used for recursive approximation of the density of random variable that has been estimated by the Bayesian equation. The third chapter deals with the application of the whole model on a special form of logistic regression. Results are shown on the examples using simulated data. At last, the model along with approximation algorithm is applied on a trading with futures. Powered by TCPDF (www.tcpdf.org)
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Monetary Policy and Macroprudential Policy: Rivals or Teammates?
Malovaná, Simona ; Frait, Jan
This paper sheds some light on situations in which monetary and macroprudential policies may interact (and potentially get into conflict) and contributes to the discussion about the coordination of those policies. Using data for the Czech Republic and five euro area countries we show that monetary tightening has a negative impact on the credit-to-GDP ratio and the non-risk-weighted bank capital ratio (i.e. a positive impact on bank leverage), while these effects have strengthened considerably since mid-2011. This supports the view that accommodative monetary policy contributes to a build-up of financial vulnerabilities, i.e. it boosts the credit cycle. On the other hand, the effect of the higher bank capital ratio is associated with some degree of uncertainty. For these and other reasons, coordination of the two policies is necessary to avoid an undesirable policy mix preventing effective achievement of the main objectives in the two policy areas.
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Iterated Multi-Step Forecasting with Model Coefficients Changing Across Iterations
Franta, Michal
Iterated multi-step forecasts are usually constructed assuming the same model in each forecasting iteration. In this paper, the model coefficients are allowed to change across forecasting iterations according to the in-sample prediction performance at a particular forecasting horizon. The technique can thus be viewed as a combination of iterated and direct forecasting. The superior point and density forecasting performance of this approach is demonstrated on a standard medium-scale vector autoregression employing variables used in the Smets and Wouters (2007) model of the US economy. The estimation of the model and forecasting are carried out in a Bayesian way on data covering the period 1959Q1–2016Q1.
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Bayesovský odhad DSGE modelů
Bouda, Milan ; Pánková, Václava (advisor) ; Kodera, Jan (referee) ; Lukáš, Ladislav (referee)
Thesis is dedicated to Bayesian Estimation of DSGE Models. Firstly, the history of DSGE modeling is outlined as well as development of this macroeconometric field in the Czech Republic and in the rest of the world. Secondly, the comprehensive DSGE framework is described in detail. It means that everyone is able to specify or estimate arbitrary DSGE model according to this framework. Thesis contains two empirical studies. The first study describes derivation of the New Keynesian DSGE Model and its estimation using Bayesian techniques. This model is estimated with three different Taylor rules and the best performing Taylor rule is identified using the technique called Bayesian comparison. The second study deals with development of the Small Open Economy Model with housing sector. This model is based on previous study which specifies this model as a closed economy model. I extended this model by open economy features and government sector. Czech Republic is generally considered as a small open economy and these extensions make this model more applicable to this economy. Model contains two types of households. The first type of consumers is able to access the capital markets and they can smooth consumption across time by buying or selling financial assets. These households follow the permanent income hypothesis (PIH). The other type of household uses rule of thumb (ROT) consumption, spending all their income to consumption. Other agents in this economy are specified in standard way. Outcomes of this study are mainly focused on behavior of house prices. More precisely, it means that all main outputs as Bayesian impulse response functions, Bayesian prediction and shock decomposition are focused mainly on this variable. At the end of this study one macro-prudential experiment is performed. This experiment comes up with answer on the following question: is the higher/lower Loan to Value (LTV) ratio better for the Czech Republic? This experiment is very conclusive and shows that level of LTV does not affect GDP. On the other hand, house prices are very sensitive to this LTV ratio. The recommendation for the Czech National Bank could be summarized as follows. In order to keep house prices less volatile implement rather lower LTV ratio than higher.
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Assessing the Impact of Fiscal Measures on the Czech Economy
Ambriško, Róbert ; Babecký, Jan ; Ryšánek, Jakub ; Valenta, Vilém
We build a satellite DSGE model to investigate the transmission of fiscal policy to the real economy in the Czech Republic. Our model shares features of the Czech National Bank’s current g3 forecasting model (Andrle, Hl´edik, Kamen´ık, and Vlˇcek, 2009), but contains a more comprehensive fiscal sector. Crucial fiscal parameters, related mainly to the specified fiscal rule, are estimated using Bayesian techniques. We calculate a set of fiscal multipliers for individual revenue and expenditure items of the government budget. We find that the largest real GDP fiscal multipliers in the first year are associated with government investment (0.4) and social security contributions paid by employers (0.3), followed by government consumption (0.2).
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The Macroeconomic Analysis with DSGE Models
Průchová, Anna ; Zouhar, Jan (advisor) ; Formánek, Tomáš (referee)
Dynamic stochastic general equilibrium models are derived from microeconomic principles and they retain the hypothesis of rational expectations under policy changes. Thus they are resistant to the Lucas critique. The DSGE model has become associated with new Keynesian thinking. The basic New Keynesian model is studied in this thesis. The three equations of this model are dynamic IS curve, Phillips-curve and monetary policy rule. Blanchard and Kahn's approach is introduced as the solution strategy for linearized model. Two methods for evaluating DSGE models are presented -- calibration and Bayesian estimation. Calibrated parametres are used to fit the model to Czech economy. The results of numeric experiments are compared with empricial data from Czech republic. DSGE model's suitability for monetary policy analysis is evaluated.
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