Literatura académica sobre el tema "DGE Model"

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.

In this thesis, different topics for models that consist of both differential and algebraic equations are studied. The interest in such models, denoted DAE models, have increased substantially during the last years. One of the major reasons is that several modern object-oriented modeling tools used to model large physical systems yield models in this form. The DAE models will, at least locally, be assumed to be described by a decoupled set of ordinary differential equations and purely algebraic equations. In theory, this assumption is not very restrictive because index reduction techniques can be used to rewrite rather general DAE models to satisfy this assumption. One of the topics considered in this thesis is optimal feedback control. For state-space models, it is well-known that the Hamilton-Jacobi-Bellman equation (HJB) can be used to calculate the optimal solution. For DAE models, a similar result exists where a Hamilton-Jacobi-Bellman-like equation is solved. This equation has an extra term in order to incorporate the algebraic equations, and it is investigated how the extra term must be chosen in order to obtain the same solution from the different equations. A problem when using the HJB to find the optimal feedback law is that it involves solving a nonlinear partial differential equation. Often, this equation cannot be solved explicitly. An easier problem is to compute a locally optimal feedback law. For analytic nonlinear time-invariant state-space models, this problem was solved in the 1960's, and in the 1970's the time-varying case was solved as well. In both cases, the optimal solution is described by convergent power series. In this thesis, both of these results are extended to analytic DAE models. Usually, the power series solution of the optimal feedback control problem consists of an infinite number of terms. In practice, an approximation with a finite number of terms is used. A problem is that for certain problems, the region in which the approximate solution is accurate may be small. Therefore, another parametrization of the optimal solution, namely rational functions, is studied. It is shown that for some problems, this parametrization gives a substantially better result than the power series approximation in terms of approximating the optimal cost over a larger region. A problem with the power series method is that the computational complexity grows rapidly both in the number of states and in the order of approximation. However, for DAE models where the underlying state-space model is control-affine, the computations can be simplified. Therefore, conditions under which this property holds are derived. Another major topic considered is how to include stochastic processes in nonlinear DAE models. Stochastic processes are used to model uncertainties and noise in physical processes, and are often an important part in for example state estimation. Therefore, conditions are presented under which noise can be introduced in a DAE model such that it becomes well-posed. For well-posed models, it is then discussed how particle filters can be implemented for estimating the time-varying variables in the model. The final topic in the thesis is model reduction of nonlinear DAE models. The objective with model reduction is to reduce the number of states, while not affecting the input-output behavior too much. Three different approaches are studied, namely balanced truncation, balanced truncation using minimization of the co-observability function and balanced residualization. To compute the reduced model for the different approaches, a method originally derived for nonlinear state-space models is extended to DAE models.

The purpose of this thesis is to discuss the introduction and the implementation of the idea of model validation, especially in the use of Dynamic Stochastic General Equilibrium (DSGE) models. In this discussion, the mixture models are presented as the recent econometrics tool used in model validation. Two examples of DSGE models are illustrated in order to introduce two problems: omitted variables within the statistical identification problem and the finite-order representation by a Vector Autoregressive (VAR) of a DSGE model. The paper concludes the review considering some pointers for the future research and for the further developments of the use of mixture models for model validation.

Thesis advisor: Zhijie Xiao<br>This dissertation contains three chapters in theoretical Macroeconometrics and applied Macroeconometrics. This first chapter addresses the issues related to the estimation, testing and computation of ordered structural breaks in multivariate linear regressions. Unlike common breaks, ordered structural breaks are those breaks that are related across equations but not necessarily occurring at the same dates. A likelihood ratio test assuming normal errors is proposed in this chapter in order to detect the ordered structural breaks in multivariate linear regressions. The estimation of ordered structural breaks uses quasi-maximum likelihood and adopts the efficient algorithm of Bai and Perron (2003). I also provide results about the consistency and rate of convergence when searching for ordered structural breaks. Finally, these methods are applied to one empirical example: the mean growth rate of output in three European countries and United States. This second chapter focuses on the parameter stability of dynamic stochastic general equilibrium (DSGE) models. To this end, I solve and estimate a representative New Keynesian model using both linear and nonlinear methods. I first examine how nonlinearities affect the parameter stability of the New Keynesian model. The results show that parameter instabilities still exist even using nonlinear solutions, and also highlight differences between two nonlinear solution methods: perturbation method and projection method. In addition, I propose a sequential procedure for searching for multiple structural breaks in nonlinear models, and apply it to the New Keynesian model. Two common structural breaks among these estimated parameters are identified for all the five solutions considered in this chapter. One structural break is in the early 1970s, while another one locates around the middle 1990s. In the third chapter, we investigate changes in long run productivity growth in the United States. In particular, we approach productivity growth from a sectoral perspective, and decompose the whole economy into two broad sectors: investment goods-producing sector and consumption goods-producing sector. Although the evidence of changes in the aggregate productivity growth is far from obvious at conventional test size, we find evidence of structural breaks in the sectoral productivity growth using both growth accounting and DSGE model based measures. There are two structural breaks in investment goods-producing sector using growth accounting measures, which indicates that the era of investment and productivity boom in the middle 1990s may have ended before the Great Recession. In addition, our results show there is one structural break in consumption goods-producing sector around the 1970s and attribute the aggregate productivity slowdown at that time to consumption goods-producing sector. These results are broadly consistent with Ireland and Schuh (2008). Our results offer up with a modestly pessimistic outlook on future productivity growth and, therefore, potential output<br>Thesis (PhD) — Boston College, 2013<br>Submitted to: Boston College. Graduate School of Arts and Sciences<br>Discipline: Economics

O objetivo deste trabalho é estudar a interação entre as autoridades fiscal e monetária no Brasil, de forma a mensurar o nível de dominância fiscal existente na economia brasileira. Para alcançar este objetivo, utiliza-se um modelo de equilíbrio geral dinâmico e estocástico desenvolvido para uma economia com rigidez de preços e com tendência inflacionária, cujos parâmetros de interesses são estimados por inferência bayesiana. Conclui-se que o nível de dominância fiscal na economia brasileira é baixa, em patamar comparado ao da economia norte-americana e canadense. Este resultado tem impacto direto na condução de políticas que visam a redução da inflação, sugerindo que esta atividade deva passar pelo encolhimento das metas inflacionárias, que impactaria diretamente na expectativa dos agentes sobre a inflação futura.<br>The purpose of this dissertartion is to analyse the interaction between fiscal and monetary authorities in Brazil, in a way that we can be able to measure the level of fiscal dominance occurring in brazilian economy. To attain this purpose, we make use of a dynamic stochastic general equilibrium model with sticky prices and non-zero trend inflation, whose parameters are estimated by bayesian inference. We conclude that the level of the fiscal dominance in Brazil is low, in scale compared to american e canadian economies. This result has consequence in policy conduction that aims to decrease inflation, suggesting that may be necessary straiten the inflation target to reduce the inflation and affect the agent’s expectation about the future inflation.

Donat que el volum de dades generat per les aplicacions científiques creix i la pressió sobre el sistema d’E/S dels sistemes HPC també augmenta, es proposa un model de comportament d’E/S per les aplicacions cientifiques paral.leles de pas de missatges MPI (Message Passing Interface) amb l’objectiu d’analitzar l’impacte de les aplicacions en el sistema d’E/S. Analitzar les aplicacions les aplicacions paral.leles MPI a nivell POSIX-IO permet observar com es tracten les dades de l’aplicació en aquest nivell. En aquest treball de recerca es presenta: la definició del model PIOM-PX. la metodologia aplicada per extraure el model i l’eina PIOM-PX-Trace-Tool. Donat que PIOM-PX està basat en el concepte de E/S, es poden identificar les fases més significatives. Fases que tenen més influència que altres en el sistema d’E/S, provocant un coll d’ampolla o un rendiment pobre. L’anàlisis en base a les fases d’E/S permeten identificar, acotar i intentar reduir l’impacte d’aquestes fases sobre el sistema d’E/S. PIOM-PX forma part del model proposat PIOM que integra el model de comportament d’E/S a nivell de POSIX-IO (PIOM-PX) i el model de comportament d’E/S a nivell de MPI-IO (PIOM-MP, antic PAS2P-IO). El model proporciona la informació necessaria, per a que utilitzant programes sintètics programables es pugui replicar el comportament de l’aplicació en diferents sistemes. PIOM-PX-Trace-Tool permet interceptar instruccions de POSIX-IO utilitzades durant l’execució de l’aplicació. Els experiments realitzats s’han executat en varis sistemes HPC estandard i en la plataforma Cloud, on s’ha pogut comprovar la utilitat del model proposat, PIOM.<br>Dado que el volumen de datos generado por las aplicaciones científicas crece y la presión sobre el sistema de E/S de los sistemas HPC también aumenta, se propone un modelo de comportamiento de E/S para las aplicaciones científicas paralelas de paso de mensajes (MPI -Message Passing Interface-) con el objetivo de analizar el impacto de las aplicaciones en el sistema de E/S. Analizar las aplicaciones paralelas MPI a nivel POSIX-IO permite observar cómo se tratan los datos de la aplicación a ese nivel. En este trabajo de investigación se presenta: la definición del modelo PIOM-PX, la metodología aplicada para extraer dicho modelo y la herramienta PIOM-PX-Trace-Tool. Dado que PIOM-PX está basado en el concepto de fase de E/S, se pueden identificar las fases más significativas. Fases que tienen más influencia que otras en el sistema de E/S, que podrían provocar un cuello de botella o un rendimiento pobre. El análisis en base a las fases de E/S permite identificar, acotar e intentar reducir el impacto de esas fases sobre el sistema de E/S. PIOM-PX forma parte del modelo propuesto PIOM que integra el modelo de comportamiento de E/S a nivel de POSIX-IO (PIOM-PX) y el modelo de comportamiento de E/S a nivel de MPI-IO (PIOM-MP, antiguo PAS2P-IO). El modelo proporciona la información necesaria, para que utilizando programas sintéticos programables se pueda replicar el comportamiento de la aplicación en diferentes sistemas. PIOM-PX-Trace-Tool permite interceptar instrucciones de POSIX-IO utilizadas durante la ejecución de la aplicación. Los experimentos realizados se han ejecutado en varios sistemas HPC estándar y en la plataforma Cloud, donde se ha podido comprobar la utilidad del modelo propuesto, PIOM.<br>The volume of data generated by scientific applications grows and the pressure on the I/O system of HPC systems also increases. For this reason, an I/O behavior model is proposed for scientific MPI (Message Passing Interface) parallel applications. The goal is to analyze the applications’ impact on the I/O system. Analyzing the MPI parallel applications at POSIX-IO level allows observing how the application’s data are treated at that level. In this research work, the following is presented: the I/O behavior model definition at POSIX-IO level (PIOM-PX model definition), the methodology applied to extract this model and the PIOM-PX-Trace-Tool. As PIOM-PX is based on the I/O phase concept, it can identify the more significant phases. Phases that have more influence than others in the I/O system and they could provoke a bottleneck or a poor performance. Analysis based on I/O phases allows identifying, delimiting, and trying to reduce each phase’s impact on the I/O system. PIOM-PX is part of proposed model PIOM. PIOM integrates the I/O behavior model at POSIX-IO level (PIOMPX) and the I/O behavior model at MPI-IO level (PIOM-MP, formerly known as PAS2P-IO). The model provides the information necessary to replicate an application’s behavior in different systems using synthetic programmables programs. PIOM-PX-Trace-Tool allows interception of POSIX-IO instructions used during the application execution. The experiments carried out are executed in several standar HPC systems and the Cloud platform, where it is able to test the utility of the proposed model PIOM.

Submitted by Marilia Taveira (marilia.taveira@gmail.com) on 2012-11-06T15:02:22Z No. of bitstreams: 1 Dissertação_Marilia_Final_PosDefesa.pdf: 823265 bytes, checksum: 5a33364964aaba850db6b89019c42d01 (MD5)<br>Approved for entry into archive by Vitor Souza (vitor.souza@fgv.br) on 2012-11-06T15:06:12Z (GMT) No. of bitstreams: 1 Dissertação_Marilia_Final_PosDefesa.pdf: 823265 bytes, checksum: 5a33364964aaba850db6b89019c42d01 (MD5)<br>Made available in DSpace on 2013-02-04T13:08:59Z (GMT). No. of bitstreams: 1 Dissertação_Marilia_Final_PosDefesa.pdf: 823265 bytes, checksum: 5a33364964aaba850db6b89019c42d01 (MD5) Previous issue date: 2012-05-31<br>Este estudo tem dois objetivos principais. O primeiro, discutir o propósito da popularização das políticas macroprudenciais no pós-crise – que surgiram como uma das soluções para a complexa relação entre estabilidade de preços e estabilidade financeira – suas vantagens em relação à abordagem anteriormente predominante – as políticas microprudenciais – e formas de interação com a tradicional política monetária. O segundo grande objetivo reproduzir um modelo da geração novo-keynesiana que contempla um sistema bancário e características que permitem replicar a condução de uma política macroprudencial (colaterais, depósitos compulsórios, requerimentos mínimos de capital) a fim de analisar a resposta de variáveis macroeconômicas a mudanças nestes parâmetros.<br>This study has two main goals. The first one is to discuss the popularization of macroprudential policies in the after crisis, as a solution for the complex linkage between financial stability and price stability, its benefits compared to the previous approach – the microprudential regulation – and the interaction between macroprudential and conventional monetary policies. The second main goal is to simulate a DSGE model with a banking system and subject to reserve requirements and collateral requirements that allow one to assess the effects of macroprudential tools utilization over macroeconomic variables.

Thesis focus on derivation of macro-finance model for analysis of yield curve and its dynamics using macroeconomic factors. Underlying model is based on basic Dynamic Stochastic General Equilibrium DSGE approach that stems from Real Business Cycle theory and New Keynesian Macroeconomics. The model includes four main building blocks: households, firms, government and central bank. Log-linearized solution of the model serves as an input for derivation of yield curve and its main determinants -- pricing kernel, price of risk and affine term structure of interest rates -- based on no-arbitrage assumption. The Thesis shows a possible way of consistent derivation of structural macro-finance model, with reasonable computational burden that allows for time varying term premia. A simple VAR model, widely used in macro-finance literature, serves as a benchmark. The paper also presents a brief comparison and shows an ability of both models to fit an average yield curve observed from the data. Lastly, the importance of term structure analysis is demonstrated using case of Central Bank deciding about policy rate and Government conducting debt management.