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Dynamics of consumption and dividends over the business cycle
Pidkuyko, Myroslav
We examine a trivariate time series model that is subject to a regime switch, where the shifts are governed by an unobserved, two-state variable that follows a Markov process. The analysis is performed in a Bayesian framework developed by Albert and Chib (1993), where the unobserved states are treated as missing data and then analyzed via Gibbs sampling. This approach generates the posterior conditional distribution of all the parameters given the hidden states, and the posterior conditional distribution of the states given the parameters. This allows us to obtain the estimated values of all the parameters of interest.
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Issues in adopting DSGE models for use in the policy process
Fukač, Martin ; Pagan, Adrian
Práce se zabývá třemi oblastmi - návrh modelu, sladění údajů a operační požadavky. Práce začíná obecnou diskuzí o struktuře dynamických stochastických modelů všeobecné rovnováhy (DSGE), kde autoři zkoumají problémy, jako např. (i) typy restrikcí, které DSGE modely představují pro systémovou dynamiku, (ii) implikace, kterou by tyto modely měly pro "lokační parametry", konkrétně tempo růstu, a (iii) zda tyto modely mohou sledovat dlouhodobý pohyb veličin a odpovídající dynamické přizpůsobování.
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Sand in the wheels: a dynamic global-game approach
Mathevet, L. ; Steiner, Jakub
We study the impact of frictions on the prevalence of systemic crises. Agents privately learn about a fixed payoff parameter, and repeatedly adjust their investments while facing transaction costs in a dynamic global game. The model has a rich structure of externalities: payoffs may depend on the volume of aggregate investment, on the concentration of investment, or on its volatility. We examine how small frictions, including those similar to the Tobin tax, affect the equilibrium. We identify conditions under which frictions discourage harmful behavior without compromising investment volume. The analysis is driven by a robust invariance result: the volume of aggregate investment (measured in a pivotal contingency) is invariant to a large family of frictions.
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Separable Utility Functions in Dynamic Economic Models
Sladký, Karel
In this note we study properties of utility functions suitable for performance evaluation of dynamic economic models under uncertainty. At first, we summarize basic properties of utility functions, at second we show how exponential utility functions can be employed in dynamic models where not only expectation but also the risk are considered. Special attention is focused on properties of the expected utility and the corresponding certainty equivalents if the stream of obtained rewards is governed by Markov dependence and evaluated by exponential utility functions.
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Characterization of fluctuating discharge
Chumak, Oleksiy ; Hrabovský, Milan
A digital camera coupled with computer has a great potential in an analysis of discharges structures. This work analyzes an approach to visualization of dynamic radiant object. Mapping of brightness uncertainty values is used to show regions of different fluctuation intensity of radiation. The entropy as described by information theory was used as a relevant parameter for an uncertainty value. By a mathematical procedure a relative parameter based on the entropy was evaluated. As result an effects of optics sensitivity or of imperfections of experimental set-up were significantly suppressed.
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Approximate Dynamic Programming based on High Dimensional Model Representation
Pištěk, Miroslav
In this article, an efficient algorithm for an optimal decision strategy approximation is introduced. The proposed approximation of the Bellman equation is based on HDMR technique. This non-parametric function approximation is used not only to reduce memory demands necessary to store Bellman function, but also to allow its fast approximate minimization. On that account, a clear connection between HDMR minimization and discrete optimization is newly established. In each time step of the backward evaluation of the Bellman function, we relax the parameterized discrete minimization subproblem to obtain parameterized trust region problem. We observe that the involved matrix is the same for all parameters owning to the structure of HDMR approximation. We find eigenvalue decomposition of this matrix to solve all trust region problems effectively.
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