Submitted by Jordano Vieira Rocha (jordanorocha@hotmail.com) on 2015-04-30T08:48:24Z No. of bitstreams: 1 Dissertação - Jordano Vieira Rocha.pdf: 1057882 bytes, checksum: 1ba84113f5ec0c31d9c99f3bebe4714d (MD5) / Approved for entry into archive by Suzinei Teles Garcia Garcia (suzinei.garcia@fgv.br) on 2015-04-30T13:02:56Z (GMT) No. of bitstreams: 1 Dissertação - Jordano Vieira Rocha.pdf: 1057882 bytes, checksum: 1ba84113f5ec0c31d9c99f3bebe4714d (MD5) / Made available in DSpace on 2015-04-30T17:23:54Z (GMT). No. of bitstreams: 1 Dissertação - Jordano Vieira Rocha.pdf: 1057882 bytes, checksum: 1ba84113f5ec0c31d9c99f3bebe4714d (MD5) Previous issue date: 2015-04-07 / This work assesses the forecasts of three nonlinear methods — Markov Switching Autoregressive Model, Logistic Smooth Transition Autoregressive Model, and Autometrics with Dummy Saturation — for the Brazilian monthly industrial production and tests if they are more accurate than those of naive predictors such as the autoregressive model of order p and the double differencing device. The results show that the step dummy saturation and the logistic smooth transition autoregressive can be superior to the double differencing device, but the linear autoregressive model is more accurate than all the other methods analyzed. / Este trabalho avalia as previsões de três métodos não lineares — Markov Switching Autoregressive Model, Logistic Smooth Transition Autoregressive Model e Autometrics com Dummy Saturation — para a produção industrial mensal brasileira e testa se elas são mais precisas que aquelas de preditores naive, como o modelo autorregressivo de ordem p e o mecanismo de double differencing. Os resultados mostram que a saturação com dummies de degrau e o Logistic Smooth Transition Autoregressive Model podem ser superiores ao mecanismo de double differencing, mas o modelo linear autoregressivo é mais preciso que todos os outros métodos analisados.

A literatura é extensa no que se refere a estimações de modelos de oferta e demanda para exportações, mas poucos consideram que a resposta em exportações a variações na taxa de câmbio possa ser lenta e assimétrica. Dixit (1989) afirma que a firma que deseja passar a atuar no mercado externo ou deixar tal mercado deve incorrer em custos irrecuperáveis. Além disso, políticas de wait and see fazem com que estas não mudem seu estado (atuantes ou não) imediatamente quando variações significativas na taxa de câmbio acontecem. Tais fatores criam o fenômeno da hysteresis econômica, caracterizado pela forte não-linearidade de uma variável, gerando assimetria dependendo do estado e da magnitude do choque em tal. Assim, propõe-se neste trabalho uma forma alternativa de se captar tal efeito, via modelo de cointegração com transição suavizada, desenvolvido em Saikkonen e Choi (2004). Os resultados encontrados apontam para a evidência do efeito histerético, apresentando tal modelagem não-linear para quatro dos dezesseis setores industriais estudados do Brasil. / The literature is large on what refers to estimation of export supply and demand models, but just a few consider that the response on exports to variations on the exchange rate can be slow and asymmetric. Dixit (1989) says that the firm who wishes to operate on the foreign market or leave it must incur on sunk costs. Besides, wait-and-see policies makes the firm to remain it state unaltered (operating or not) immediately when significant variations on the exchange rate happens. This factor creates the phenomena called economic hysteresis, representing a strong non-linearity of a variable, generating asymmetries depending on the state and magnitude of the shock on the variable. Thus, its proposed on this work an alternative form to capture this effect, by smooth transition cointegration model, developed on Saikkonen and Choi (2004). The results indicate to the evidence of the hysteretic effect, presenting non-linear modeling for four of sixteen industrial sectors studied of Brazil.

Gegenstand dieser Dissertation ist die Rolle fiskalischen Stresses auf die Größe des Staatsausgabenmultiplikators. Hierbei werden zuerst die Folgen von empirisch identifizierten Staatsausgabenschocks in Italien untersucht. Dies geschieht sowohl in einem Zustand mit hohen Risikospreads auf Staatsanleihen, als auch in einem Zustand mit niedrigen Risikospreads. Das Resultat ist, dass kumulative Multiplikatoren kleiner sind, wenn das Ausfallrisiko von Staatsanleihen hoch ist. Zweitens erklärt die Dissertation dieses empirische Resultat im Rahmen eines DSGE Models. Im Model verdrängt ein Anstieg der Staatsausgaben private Investitionen. Der Verdrängungseffekt wird durch fragile Banken und die Rolle aggregierten Risikos ausreichend verstärkt, so dass fiskalischer Stress zu sehr kleinen oder sogar negativen Multiplikatoren führen kann. Zuletzt untersuche ich die Rolle fiskalischen Stresses auf den Staatsausgabenmultiplikator unter der Nebenbedingung, dass die nominale Zinsuntergrenze bei null bindet. In diesem Szenario kann sich der Effekt fiskalischen Stresses ins Gegenteil verkehren und der Staatsausgabenmultiplikator groß werden. / This thesis examines the role of fiscal stress on the size of the government spending multiplier. First, it explores the dynamic consequences of empirically identified government spending shocks in Italy in a regime with high sovereign bond yield spreads and a regime with low spreads. It finds that cumulative multipliers are lower when sovereign risk spreads are high. Secondly, the thesis explains the empirical result of small government spending multipliers in times of high levels of fiscal stress in the context of a DSGE Model. In this model, an increase in government spending crowds out private investment. A fragile banking sector and aggregate risk amplify the crowding out of investment sufficiently to imply small multipliers in the presence of fiscal stress. Finally, I analyze the role of fiscal stress on the multiplier, when the economy is at the zero lower bound for nominal interest rates and find that in this scenario, the effect of fiscal stress is reversed and the government spending multiplier is large.

In an effort to assess the predictive ability of exchange rate models when data on African countries is sampled, this paper studies nonlinear modelling and prediction of the nominal exchange rate series of the United States dollar to currencies of thirty-eight African states using the smooth transition autoregressive (STAR) model. A three step analysis is undertaken. One, it investigates nonlinearity in all nominal exchange rate series examined using a chain of credible statistical in-sample tests. Significantly, evidence of nonlinear exponential STAR (ESTAR) dynamics is detected across all series. Two, linear models are provided another chance to make it right by shuffling to data on African countries to investigate their predictive power against the tough random walk without drift model. Linear models again failed significantly. Lastly, the predictive ability of nonlinear models against both the random walk without drift and the corresponding linear models is investigated. Nonlinear models display useful forecasting gains over all contending models.

Diss. Stockholm : Handelshögsk.

Among the parametric nonlinear time series model families, the smooth transition regression (STR) model has recently received attention in the literature. The considerations in this dissertation focus on the univariate special case of this model, the smooth transition autoregression (STAR) model, although large parts of the discussion can be easily generalised to the more general STR case. Many nonlinear univariate time series models can be described as consisting of a number of regimes, each one corresponding to a linear autoregressive parametrisation, between which the process switches. In the STAR models, as opposed to certain other popular models involving multiple regimes, the transition between the extreme regimes is smooth and assumed to be characterised by a bounded continuous function of a transition variable. The transition variable, in turn, may be a lagged value of the variable in the model, or another stochastic or deterministic observable variable. A number of other commonly discussed nonlinear autoregressive models can be viewed as special or limiting cases of the STAR model. The applications presented in the first two chapters of this dissertation, Chapter I: Another look at Swedish Business Cycles, 1861-1988 Chapter II: Modelling asymmetries and moving equilibria in unemployment rates, make use of STAR models. In these two studies, STAR models are used to provide insight into dynamic properties of the time series which cannot be be properly characterised by linear time series models, and which thereby may be obscured by estimating only a linear model in cases where linearity would be rejected if tested. The applications being of interest in their own right, an important common objective of these two chapters is also to develop, suggest, and give examples of various methods that may be of use in discussing the dynamic properties of estimated STAR models in general.Chapter III, Testing linearity against smooth transition autoregression using a parametric bootstrap, reports the result of a small simulation study considering a new test of linearity against STAR based on bootstrap methodology. / <p>Diss. Stockholm : Handelshögskolan, 1999</p>

The main purpose of this thesis is to assess the potential of emerging stock markets and commodity markets in attracting the attention of international investors who utilize various portfolio diversification strategies to reduce the cumulative risk of their portfolio. A successful portfolio diversification strategy requires low correlation among financial markets. However, it is now well documented that the correlations among financial markets in developed countries are very high and hence the benefits of international portfolio diversification among these markets have been very limited. This fact suggests that investors should look for alternative markets whose correlations with developed markets are low (or even negative if possible) and which have high growth potentials. In this thesis, two emerging countries&#039 / stock markets and two commodity markets are considered as alternative markets. Among emerging countries, Turkey and China are chosen due to their promising growth performance since the mid-2000s. As commodity markets, agricultural commodity and precious metal markets are selected because of the outstanding performance of the former and the &quot / safe harbor&quot / property of the latter. The structures and properties of dependence between these markets and stock markets in developed countries are examined by modeling the conditional correlation in the dynamic conditional correlation framework. The results reveal that upward trend hypothesis is valid for almost all correlations among market pairs and market volatility plays significant role in time varying structures of correlations.

The recent empirical literature has shown that the dynamic generating mechanism of macroeconomic variables can be asymmetric. Inspiring from these empirical results, this thesis uses a class of nonlinear models called smooth transition autoregressive models to investigate possible asymmetric dynamics in inflation and nominal exchange rate series of Turkey. Estimation results imply that variables under consideration contain strong nonlinearities and these can be modeled by STAR models.

<p>The main contributions of this thesis include two points: firstly, we originally establish Complex STM to semi-analytically calculate the mode profiles of multi-layer planar waveguide terminated with both PML and PRB ; secondly, although CMMM has been generally applied to the simulation of waveguide facets, Bragg gratings, etc[52-53], we for the first time demonstrate that CMMM can also be utilized for the modeling of couplings of radiation field outgoing perpendicularly to the waveguide axis with an incident wave launched in the examples of high-index-contrast waveguide crossings and corners. CMMM is proved to be able to estimate the field profiles and power flows accurately through the validation with FDTD.</p> / <p>Optical waveguides are basic building blocks of high-density photonic integrated circuits and play crucial roles in optical access networks, biomedical system, sensors and so on. Various kinds of dielectric waveguides apply the total internal reflection condition to transmit optical field [9] and even more complicated structures based on waveguide interconnects, Bragg grating, photonic crystals are actively developed by corporations and academic institutes. Especially, the fast developing pace of Metal-Organic Chemical Vapor Deposition (MOCVD), Molecular Beam Epitaxy (MBE) and other fabrication techniques has predicted the increasing complication and thus more advanced function of modern optics integrated circuits. Under such circumstances, convenient and accurate modeling and simulation schemes are necessary for the exploration, designing and optimization of photonic devices, systems and networks before the time-consuming and expensive fabrication process.</p> <p>The thesis summarizes several frequency-domain modeling schemes for the calculation of mode profile or beam propagation in 2D dielectric waveguide. The thesis mainly covers conventional Smooth Transition Method (STM), High Order Finite Difference (HOFD) scheme, Complex STM, and Complex Mode Matching Method (CMMM) based on the 2D waveguide model terminated with Perfect Matching Layer (PML) and Perfect Reflection Boundary (PRB). The mode spectrums and modal patterns obtained from Complex STM are compared with those of HOFD, and the simulation of waveguide crossings and corners with CMMM is validated with Finite-Difference-Time-Domain (FDTD) Method.</p> <p><strong> </strong></p> / Master of Applied Science (MASc)

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