Tesis sobre el tema "Generalized Impulse Response Functions"

This final thesis deals with the approximation of time delay in time invariant systems. First, the generalized Laguerre functions and their characteristics are presented. After this, the approximation of the Dirac delta function with the help of these functions is shown. Also, the choice of the free parameters is discussed and the results are evaluated with the help of energy. In the final part of the thesis, the approximations of systems with generalized and simple Laguerre functions are compared.

University of Central Florida College of Engineering Thesis
Window functions have been extensively used for the design of SAW filters. The classical truncated cosine series functions, such as the Hamming and Blackmann functions, are only a few of an infinite set of such functions. The derivation of this set of functions from orthonormal basis sets and the criteria for obtaining the constant coefficients of the functions are presented. These functions are very useful because of the closed-form expressions and their easily recognizable Fourier transform. Another approach to the design of Gaussian shaped filters having a desired sidelobe level using a 40 term cosine series will be presented as well. This approach is again non-iterative and a near equi-ripple sidelobe level filter could be achieved. A deconvolution technique will also be presented. this has the advantage of being non-iterative, simple and fast. This design method produces results comparable to the Dolph-Chebyshev technique.
Ph.D.
Doctorate
Electrical Engineering and Communication
Engineering
Electrical Engineering
41 p.
vii, 41 leaves, bound : ill. ; 28 cm.

Thesis (M.S. in Applied Science (Signal Processing))--Naval Postgraduate School, June 2004.
Thesis advisor(s): Lawrence J. Ziomek. Includes bibliographical references (p. 47). Also available online.

Ultra Wideband (UWB) communication has recently drawn considerable attention from academia and industry. This is mainly owing to the ultra high speeds and cognitive features it could offer. The employability of UWB in numerous areas including but not limited to Wireless Personal Area Networks, WPAN's, Body Area Networks, BAN's, radar and medical imaging etc. has opened several avenues of research and development. However, still there is a disagreement on the standardization of UWB. Two contesting radios for UWB are Multiband Orthogonal Frequency Division Multiplexing (MB-OFDM) and DS-UWB (Direct Sequence Ultra Wideband). As nearly all of the reported research on UWB hasbeen about a very narrow/specific area of the communication system, this thesis looks at the end-to-end performance of an MB-OFDM approach. The overall aim of this project has been to first focus on three different aspects i.e. interference, antenna and propagation aspects of an MB-OFDM system individually and then present a holistic or an end-to-end system analysis finally. In the first phase of the project the author investigated the performance of MB-OFDM system under the effect of his proposed generic or technology non-specific interference. Avoiding the conventional Gaussian approximation, the author has employed an advanced stochastic method. A total of two approaches have been presented in this phase of the project. The first approach is an indirect one which involves the Moment Generating Functions (MGF's) of the Signal-to-Interference-plus-Noise-Ratio (SINR) and the Probability Density Function (pdf) of the SINR to calculate the Average Probabilities of Error of an MB-OFDM system under the influence of proposed generic interference. This approach assumed a specific two-dimensional Poisson spatial/geometric placement of interferers around the victim MB-OFDM receiver. The second approach is a direct approach and extends the first approach by employing a wider class of generic interference. In the second phase of the work the author designed, simulated, prototyped and tested novel compact monopole planar antennas for UWB application. In this phase of the research, compact antennas for the UWB application are presented. These designs employ low-loss Rogers duroid substrates and are fed by Copla-nar Waveguides. The antennas have a proposed feed-line to the main radiating element transition region. This transition region is formed by a special step-generating function-set called the "Inverse Parabolic Step Sequence" or IPSS. These IPSS-based antennas are simulated, prototyped and then tested in the ane-choic chamber. An empirical approach, aimed to further miniaturize IPSS-based antennas, was also derived in this phase of the project. The empirical approach has been applied to derive the design of a further miniaturized antenna. More-over, an electrical miniaturization limit has been concluded for the IPSS-based antennas. The third phase of the project has investigated the effect of the indoor furnishing on the distribution of the elevation Angle-of-Arrival (AOA) of the rays at the receiver. Previously, constant distributions for the AOA of the rays in the elevation direction had been reported. This phase of the research has proposed that the AOA distribution is not fixed. It is established by the author that the indoor elevation AOA distributions depend on the discrete levels of furnishing. A joint time-angle-furnishing channel model is presented in this research phase. In addition, this phase of the thesis proposes two vectorial or any direction AOA distributions for the UWB indoor environments. Finally, the last phase of this thesis is presented. As stated earlier, the overall aim of the project has been to look at three individual aspects of an MB-OFDM system, initially, and then look at the holistic system, finally. Therefore, this final phase of the research presents an end-to-end MB-OFDM system analysis. The interference analysis of the first phase of the project is revisited to re-calculate the probability of bit error with realistic/measured path loss exponents which have been reported in the existing literature. In this method, Gaussian Quadrature Rule based approximations are computed for the average probability of bit error. Last but not the least, an end-to-end or comprehensive system equation/impulse response is presented. The proposed system equation covers more aspects of an indoor UWB system than reported in the existing literature.

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In this thesis, the ocean was modeled as a waveguide with an ideal pressure - release surface, and an ideal rigid bottom. The ocean waveguide was then treated as a linear, time - invariant, space - variant (TISV) filter or communication channel. The filter is time - invariant because no motion was modeled and because the properties of the ocean were assumed to be constant. The filter is space - variant because of the presence of the two boundaries, that is, the ocean surface and ocean bottom. This thesis investigates the ocean as a linear TISV filter by evaluating 1) the complex frequency response, 2) the impulse response, and 3) the transfer function of the ocean with respect to depth. It is shown that the TISV impulse response of the ocean contains information that can be used to help localize a target in range and whether the target is above or below the receiver. Computer simulation results were obtained by evaluating the three filter functions for several different test cases.
Ensign, United States Navy

Vector autoregression (VAR) models are widely used in an attempt to identify and measure the effect of monetary policy shocks on an economy and to forecast economic times series. However, the sparse information sets used in the VAR approach have been subject to criticism and in recent decades, the use of factor models as a means of dimension reduction has been a subject of greater focus. The method of summarizing information contained in a large set of macroeconomic time series by principal components, and use these as regressors in VAR models, has been pointed out as a potential solution to the problems of limited information and estimation of too many parameters. This paper combines the standard VAR methodology with dynamic factor analysis on Swedish data for two purposes, to assess the effects of monetary policy shocks and to examine the forecasting properties. Latent factors estimated by the principal components method are in this study found to contribute to a more coherent picture in line with economic theory, when examining monetary policy shocks to the Swedish economy. The factor-augmented models can on the other hand not be shown to increase the forecasting accuracy to a great extent compared to standard models.

The thesis presents algorithms based on a linear algebraic solution for the identification of the parameters of the FIR system using only higher order statistics when only the output of the system corrupted by additive Gaussian noise is observed. All the traditional parametric methods of estimating the parameters of the system have been based on the 2nd order statistics of the output of the system. These methods suffer from the deficiency that they do not preserve the phase response of the system and hence cannot identify non-minimum phase systems. To circumvent this problem, higher order statistics which preserve the phase characteristics of a process and hence are able to identify a non-minimum phase system and also are insensitive to additive Gaussian noise have been used in recent years. Existing algorithms for the identification of the FIR parameters based on the higher order cumulants use the autocorrelation sequence as well and give erroneous results in the presence of additive colored Gaussian noise. This problem can be overcome by obtaining algorithms which do not utilize the 2nd order statistics. An existing relationship between the 2nd order and any Ith order cumulants is generalized to a relationship between any two arbitrary k, Ith order cumulants. This new relationship is used to obtain new algorithms for FIR system identification which use only cumulants of order > 2 and with no other restriction than the Gaussian nature of the additive noise sequence. Simulation studies are presented to demonstrate the failure of the existing algorithms when the imposed constraints on the 2nd order statistics of the additive noise are violated while the proposed algorithms perform very well and give consistent results. Recently, a new algebraic approach for parameter estimation method denoted the Linear Combination of Slices (LCS) method was proposed and was based on expressing the FIR parameters as a linear combination of the cumulant slices. The rank deficient cumulant matrix S formed in the LCS method can be expressed as a product of matrices which have a certain structure. The orthogonality property of the subspace orthogonal to S and the range space of S has been exploited to obtain a new class of algorithms for the estimation of the parameters of a FIR system. Numerical simulation studies have been carried out to demonstrate the good behaviour of the proposed algorithms. Analytical expressions for the covariance of the estimates of the FIR parameters of the different algorithms presented in the thesis have been obtained and numerical comparison has been done for specific cases. Numerical examples to demonstrate the application of the proposed algorithms for channel equalization in data communication and as an initial solution to the cumulant matching nonlinear optimization methods have been presented.

It is now well established in the literature that oil consumption, oil price shocks, and oil price volatility may impact the economic activities negatively. Studies identifying the relationship between energy and/or oil consumption and output primarily take two different approaches. One approach includes energy or oil consumption in addition to output, labour, and capital. The other approach takes energy and/or oil, output and prices. Based on these two models most of the previous studies suggest energy conservation policies for different economies. However, none of the previous studies considered both of these models jointly to make policy implications and there are not many studies investigating oil consumption-output relationship in a multivariate model in the context of developing economies. Furthermore, one of the important variables in making any conservation policies, carbon emission, is omitted from the models.Similarly, there has been a large body of literature investigating the impact of oil price shocks in different economies. Nevertheless, studies analysing the impact of oil price volatility on economic activities are very limited. More importantly, studies analysing the impact of oil price volatility in developing economies are almost non-existent. In the light of increasing demand for oil from the developing nations, comprehensive studies on identifying the impact of oil consumption, oil prices, and oil price volatility on developing economies is warranted.Hence, in this thesis, the contribution of oil in economic development is investigated with the help of two different models. The first model, termed as supply-side approach, analyses the contribution of oil consumption in economic activities within the traditional production function framework. The second model, termed as demand-side approach, analyses the contribution of energy consumption in economic activities in two stages. In the first stage, oil consumption demand is analysed by a tri-variate model having oil prices as the third variable in addition to oil consumption and GDP. In the second stage, carbon emission output is determined in a tri-variate model with carbon emission as the third variable along with oil consumption and output. This thesis also performs a unique task of analysing the impact of volatility on world crude oil prices on the economic activities of six Asian developing economies.With respect to the oil consumption-output relationship, despite dissimilarities in results for causality relationships between oil consumption and output in three different models for different countries, one common result emerges. Except for the Philippines, all other countries are found to be oil dependent either from supply-side or from demand-side or from both of the sides. This implies that for all the considered developing economies, except for the Philippines, oil conservation policies seem to be harder to implement as that may retard their economic growth. In addition to that, one very important findings of the empirical analysis based on the equation regarding pollutant emission output is that for all the countries, except for Malaysia, output Granger causes pollutant emission (CO2) both in the short run and long run.With respect to the impact of oil price volatility on economies, this study finds that oil price volatility seems to impact all the economies in the short run. According to the results, oil price volatility affects GDP growth in China and Malaysia, GDP growth and inflation in India and Indonesia, while in the Philippines volatility in oil prices impacts inflation. However, in Thailand the impact channels are different for pre- and post-Asian financial crisis period. For Thailand, it can be inferred that oil price volatility impacts output growth for the whole period; however, after the Asian financial crisis the impact seems to disappear.Based on the comprehensive study within three different theoretical frameworks the policy implications regarding oil consumption-output relationship can be summarised as follows. For the Philippines, where uni-directional causality from income to oil consumption is found, she may contribute to the fight against global warming directly implementing energy conservation measures. The direction of causality indicates that the oil conservation policies can be initiated with little or no effect on economic growth. For rest of the oil dependent countries where either bidirectional causality or uni-directional causality from oil consumption to output is found in any of the models, since oil is a critical determinant of economic growth in these countries, limiting its use may retard economic growth. Nevertheless, all of these countries may initiate environmental policies aimed at decreasing energy intensity, increasing energy efficiency, and developing a market for emission trading. These countries can invest in research and development to innovate technology that makes alternative energy sources more feasible, thus mitigating pressure on the environment.According to the impact analysis of oil price volatility on economic activities, the policy implications are as follows. In Thailand, the results after the financial crisis show that adverse effect of oil price volatility has been mitigated to some extent. It seems that oil subsidization of the Thai government by introduction of the oil fund and the flexible exchange rate regime plays a significant role in improving economic performance by lessening the adverse effect of oil price volatility on macroeconomic indicators. For all other countries, the impact of oil price volatility is also of short term. Hence, the short-term impact of oil price volatility on the concerned economies may be exerted though the uncertainty born by the fluctuations in the crude oil price in the world market. As far as the impact on GDP growth is concerned, the short-run impact may also be transmitted through the investment uncertainties resulting from increased volatility in oil prices. However, from the Thai experience it can be inferred that flexible exchange rate regime insulate the economy in the short run from any adverse impact from oil price volatility on growth. Hence, it can be suggested that good subsidization policy with considerable knowledge on international currency market, both spot and future, may shield the economies from adverse consequences due to the fluctuation in oil prices in the short run. Nevertheless, this may affect other sectors of the economy like, inflation, interest rate, government budget deficit, etc.

System identification finds nowadays application in various areas of biological research as a tool of empiric mathematical modeling and model individualization. A fundamental challenge of system identification in biology awaits in the form of response variability. Furthermore, biological systems tend to exhibit high degree of nonlinearity as well as significant time delays. This thesis covers system identification approaches developed for the applications within two particular biomedical fields: neuroscience and endocrinology. The first topic of the thesis is parameter estimation of the classical Elementary Motion Detector (EMD) model in insect vision. There are two important aspects to be taken care of in the identification approach, namely the nonlinear dynamics of the individual EMD and the spatially distributed structure of multiple detectors producing a measurable neural response. Hence, the suggested identification method is comprised of two consecutive stages addressing each of the above aspects. Furthermore, visual stimulus design for high spatial excitation order has been investigated. The second topic is parameter estimation of mathematical model for testosterone regulation in the human male. The main challenges of this application are in the unavailability of input signal measurements and the presence of an unknown pulsatile feedback in the system resulting in a highly nonlinear closed-loop dynamics. Semi-blind identification method has been developed based on a recently proposed pulse-modulated model of pulsatile endocrine regulation. The two system identification problems treated in the thesis bear some resemblance in the sense that both involve measured signals that can be seen as square-integrable functions of time. This property is handled by transforming the signals into the Laguerre domain, i.e. by equivalently representing the functions with their infinite Laguerre series.

Rod and cone photoreceptors in the human eye operate simultaneously under dim (mesopic) illuminations, however, it's not clear how their signals interact to regulate our visual experience. These photoreceptor interactions were investigated using a new methodology designed to isolate rod-mediated vision by separating it from the effects of cone photoreceptor-specific noise. The outcomes revealed a mechanism requiring cone-directed transmission of rod signals through the primary visual pathways that optimizes human vision under twilight illumination.

The transition from communism to capitalism at the end of the last century was one of the most significant events in the world economy since industrialization. During the latter part of the 1980s, people the Central and Eastern European countries and former Soviet Republics opted for a change from highly distorted command economic system to a market driven economic system. Privatization and liberalization policies led to major changes in the commodity mix and volume of agricultural production, consumption and trade. However, the changes and the impacts varied among countries as they followed different transition strategies. This study investigated the impact of market liberalization on the agricultural sector, as well as how the inter-sectoral linkages among the agricultural, industrial and service sectors responded in Poland, Romania, Bulgaria and Hungary using time-series analysis. The study estimated an econometric model that incorporates the linkages among the sectors using a Vector Error Correction Model. The procedure identified long-run and short-run relationships for each country. The results showed that a sector can have a negative linkage to other sectors in the short-run; however, that does not mean that the linkage will be negative in the long-run. Impulse response functions were constructed to determine how a system reacts to a shock in one of the endogenous variable in a model. The study explored how a shock in the agricultural sector was absorbed by the other sectors in the economy, and how a shock in the other sectors was absorbed by the agricultural sector, in all four countries. The responses reflected how the variables are interrelated within a country, and how the shocks are transferred through different linkages over a long period of time. Such dynamic analysis was used to identify the total impacts of different policy alternatives.

RESUMO No início de 1995 foi adotado no Brasil o Plano Real, tendo como um dos seus tripés de sustentação a busca pelo combate ao processo inflacionário crônico brasileiro que já se estendia por um longo período. Assim, a política monetária passou a ter um papel importante na determinação das variáveis macroeconômicas. Este trabalho busca analisar uma regra de política monetária que capte as variações ocorridas em todo o período do Plano Real, se estendendo até meados de 2005, bem como se deram as relações entre as variáveis econômicas neste período. A especificação proposta consiste na estimação de modelos não-lineares distintos dependendo do estado da economia (em crise ou fora de crise). Utilizamos um modelo com chaveamento Markoviano para a dinâmica da taxa de juros nominal onde a determinação de períodos de crise é feita por uma variável nãoobservada. Além disso, procuramos adotar dois algoritmos distintos de estimação, Expectation-Maximization (EM) e Monte Carlo Markov Chain (MCMC), concluindo que a análise para ambos é bastante próxima, sendo identificados os mesmos períodos entre regimes. Finalmente, motivamos a estimação através de modelos econômicos teóricos cujas dinâmicas são compatíveis com uma regra de fixação de juros não-linear, avaliando os padrões de resposta a impulso condicionados ao estado da economia (regimes de estabilidade e crise econômica).
ABSTRACT In the beginning of 1995, continuing the process of inflation combat, the monetary policy should have been an important role in the determinacy of macroeconomics variables. This work has a target analyzing a monetary rule that reflects the occurred variations in every Real Plan?s period. The specification proposed by the authors consists in an estimation of two independent nonlinear models for different states of the nature (crises or not crises). Here we estimate a model where the dynamic of the nominal interest rate follows a Markov Switching process and the regimes are unobservable variables. In addition, we try adopting two different algorithms to estimation; Expectation-Maximization (EM) and Monte Carlo Markov Chain (MCMC), concluded that the results are very similar. Finally, we motivate the estimations analyzing models where the theoretical dynamics of the economy are compatible with a nonlinear interest rate rule, analyzing the impulse response conditioned to state of economy (regimes of crises or not crises).

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
Esta tese apresenta uma parametrização no espaço de estados para a transformada wavelet rápida. Esta parametrização é baseada em funções de base ortonormal e filtros de resposta finita ao impulso simultaneamente, uma vez que, a transformada rápida wavelet é um algoritmo que consiste em decompor sinais no domínio do tempo em sequências de coeficientes baseados numa base ortogonal de funções wavelet. Deste modo, vantagens apresentadas por ambas as propostas são incorporadas. Modelos de resposta finita ao impulso têm propriedades atrativas como vantagens computacionais e analíticas, garantia de estabilidade BIBO e robustez para a mudança de alguns parâmetros, dentre outras. Por outro lado, séries de funções de base ortonormal têm características que as fazem atrativas para a modelagem de sistemas dinâmicos, como ausência de recursão da saída, a não necessidade de se conhecer previamente a estrutura exata do vetor de regressão, possibilidade de aumentar a capacidade de representação do modelo aumentando-se o número de funções ortonormais utilizadas, desacoplamento natural das saídas em modelos multivariáveis; tolerância a dinâmicas não modeladas. Além disso, a realização no espaço de estados é mínima. A contribuição deste trabalho consiste no desenvolvimento de uma realização no espaço de estados para bancos de filtros wavelet, em que há a presença explícita de parâmetros que podem ser livremente ajustados mantendo as propriedades de reconstrução perfeita e ortonormalidade. Para ilustrar o funcionamento e as vantagens da técnica proposta, alguns exemplos de decomposição de sinais no contexto de processamento de sinais mostrando que ela proporciona os mesmos coeficientes wavelet que a transformada wavelet rápida, e uma aplicação em controle através de realimentação dinâmica de estados também são apresentados nesta tese.
This thesis presents a state-space parameterization for the fast wavelet transform. This parameterization is based on orthonormal basis functions and finite impulse response filters at the same time, since the fast wavelet transform is an algorithm, which converts a signal in the time domain into a sequence of coefficients based on an orthogonal basis of small finite wavelet functions. Advantages presented by both proposals are incorporated. Finite impulse response systems have attractive properties, for instance, computational and analytical advantages, BIBO stability and robustness guarantee to some parameter changes, and others. On the other hand, orthonormal basis functions have some characteristics that make them attractive for dynamic systems modeling, examples are, output recursion absence, not requiring prior regression vector exact structure knowledge; possibility of increasing the model representation capacity by increasing the number of orthonormal functions employed; natural outputs uncoupling in multivariable models; tolerance to unmodeled dynamics, and others. Furthermore, the state-space realization is minimal. The contribution of this work consists in the development of a state-space realization for a wavelet filter bank, with the explicit presence of the parameters that can be freely adjusted, keeping perfect-reconstruction and orthonormality guarantees. In order to illustrate advantages and how the proposed technique works, some decomposition examples in signal processing context are presented showing that it provides the same wavelet coefficients as the fast wavelet transform, and an application on dynamic state feedback control is also presented in this thesis.
CNPq: 160545/2013-7

Orientador: Francisco Villarreal Alvarado
Resumo: Esta tese apresenta uma parametrização no espaço de estados para a transformada wavelet rápida. Esta parametrização é baseada em funções de base ortonormal e filtros de resposta finita ao impulso simultaneamente, uma vez que, a transformada rápida wavelet é um algoritmo que consiste em decompor sinais no domínio do tempo em sequências de coeficientes baseados numa base ortogonal de funções wavelet. Deste modo, vantagens apresentadas por ambas as propostas são incorporadas. Modelos de resposta finita ao impulso têm propriedades atrativas como vantagens computacionais e analíticas, garantia de estabilidade BIBO e robustez para a mudança de alguns parâmetros, dentre outras. Por outro lado, séries de funções de base ortonormal têm características que as fazem atrativas para a modelagem de sistemas dinâmicos, como ausência de recursão da saída, a não necessidade de se conhecer previamente a estrutura exata do vetor de regressão, possibilidade de aumentar a capacidade de representação do modelo aumentando-se o número de funções ortonormais utilizadas, desacoplamento natural das saídas em modelos multivariáveis; tolerância a dinâmicas não modeladas. Além disso, a realização no espaço de estados é mínima. A contribuição deste trabalho consiste no desenvolvimento de uma realização no espaço de estados para bancos de filtros wavelet, em que há a presença explícita de parâmetros que podem ser livremente ajustados mantendo as propriedades de reconstrução perfeita e ortonormalidade. ... (Resumo completo, clicar acesso eletrônico abaixo)
Doutor

The aim of this paper is to analyse and compare inflation and its dynamics between two countries -- the Czech Republic and Germany -- applying a special kind of econometric models. The first part of this paper is dedicated to economic theory of inflation -- fundamental terms, measuring methods and its targeting. The monetary policy in the Czech Republic and Germany is also shortly introduced. Next chapter tries to describe the econometric concept which is used in this paper -- vector autoregression model (VAR model). In connection with the VAR models, Granger causality, impulse response function, cointegration and error correction model are mentioned as well. The empirical part includes application of selected models on real time series of macroeconomic indicators. Next to the interpretation of results, the forecasts are also implemented.

This paper focuses on analysing and modelling inflation and its dynamics in Czech Republic applying a special kind of econometric models. Firstly economic theory of inflation is mentioned - fundamental terms, measuring methods of inflation, the way Czech national bank is monitoring the inflation and obviously a short summary of historical evolution of inflation in Czech economy. In the second part of this paper two econometric concepts of modelling time series are introduced - vector autoregression models (VAR models) and volatility models, concretely ARCH and GARCH models. In connection with the VAR models, Granger causality, impulse response functions, cointegration and error correction models are described. The empirical part includes application of selected models on real time series of chosen macroeconomic indicators. The estimation outputs are interpreted and forecasts are implemented. The quality of chosen econometric models for modelling inflation in Czech Republic is discussed.

This article investigates the interrelations between the initial members of the Euro area and five important Central and Eastern European economies. We set up a theoretical open economy model to derive the Purchasing Power Parity, the Interest Rate Parity, the Fisher Inflation Parity, and an output gap relation. After taking convergence into account, they are used as restrictions on the cointegration space of a structural vector error correction model. We then employ generalized impulse response analysis to assess the dynamic effects of shocks in output and interest rates on the respective other area as well as the implications of shocks in the exchange rate and in relative prices on both areas. The results show a high degree of interconnectedness between the two economies. There are strong positive spillovers in output to the respective other region with the magnitude of the impact being similarly strong in both areas. Furthermore, we find a multiplier effect being present in Eastern Europe and some evidence for the European Central Banks' desire towards price stability. (author's abstract)
Series: Department of Economics Working Paper Series

The paper develops empirical measures to estimate the strength and dymanic of fiscal spillover effects in the Euro Area. It moves for estimating a Bayesian VAR model of real and financial variables in order to examine in depth economic policy coordination and policy making, with a strong attention on the current financial crisis. Spillovers are estimated recursively with weakly-exogenous common factors. The aim of the project accounts for interdependencies across countries within the Euro Area and derives impulse response functions and conditional forecasts with the output of a Monte Carlo Marco Chain routine. However, the paper attempts to estimate the systemic contribution and cross-country transmission of unexpected shocks on the productivity in the Eurozone between June 1995 and March 2014. Overall, the positive impact on outputs in the financial dimension indicates the importance of coordinated fiscal actions among euro area members. Shocks overflow in a heterogeneous way across countries. Moreover, financial variables show higher amplification of spillover effects which can be seen as a result of increased interdependence between variables. Finally, the analysis is consistent and robust with the more recent literature on business cycles, which recognizes the importance of both group-specific and global factors in evaluating cross-country spillovers and responses to an unexpected shocks.

The aim of this diploma thesis is to empirically investigate the explanatory power of Austrian business cycle theory. My dataset consists of US quarterly time series within the period between 1971 and 2009. As regards the NBER classification, this dataset covers six complete business cycles, including the recent global financial crisis. Following Wainhouse (1984), Keeler (2001) and Bjerkenes et al. (2010) I use Granger causality as one of the primary tools of the analysis. Moreover I also add Impulse response functions to discover the direction of observed relationships. As regards my primary group of hypotheses I found significant empirical evidence for the connection between changes in interest rate and structure of production. The secondary group of hypotheses is less successful; however I found the very first empirical illustration of Garrison's version of ABCT.

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Impulse Response Functions (IRFs) are important in many engineering applications, mainly in structural dynamics and modal analysis involving experimental modal tests. These IRFs can be identified through several methods. Among these, the classical covariance method is one of the most used and it is based on the sum of convolution from the correlation functions between input and output signals known. However, this method is limited because it employs a large number of samples and has drawbacks related to over parametrization. In this sense, this work presentes and review the covariance method expanded in the ortonormal basis Kautz functions, because this alternative way allows to avoid these drawbacks. In order to ilustrate the procedure an algorithm with multiple objective functions to obtain the optimal poles of the Kautz filter is shown. The results are provided through three degree-of-freedom mechanical system simulated and experimental data in a beam to show the advantages, drawbacks, simplicity and efficiency of the proposed approach.
As funções de resposta ao impulso (IRFs) exercem papel de destaque na identificação de sistemas reais quando têm-se o conhecimento dos dados de entrada/saída do sistema. Essas IRFs são relevantes em muitas aplicações de Engenharia, especialmente em análise modal experimental de estruturas. Dentre os métodos para obtenção dessas IRFs, destaca-se o clássico método das covariâncias baseado na soma de convolução das funções de correlação entre os sinais de entrada e saída conhecidos. No entanto, esse método é limitado quando são coletadas muitas amostras e possui algumas desvantagens como efeitos de sobreparametrização. Neste sentido, este trabalho apresenta e revisa o método das covariâncias expandido na base ortonormal de Kautz para aplicações em identificação de sistemas mecânicos, pois essa forma alternativa permite evitar esses efeitos de sobreparametrização. Para obter os pólos ótimos dos filtros de Kautz, emprega-se um algoritmo multi-objetivo. Os resultados são verificados através de um sistema mecânico com três graus de liberdade e em dados experimentais a partir de uma viga na condição livre-livre no qual verificam-se as vantagens, desvantagens, simplicidade e eficiência do método proposto.

Valutamarknaden är världens största marknad och en nödvändig del av dagens globala samhälle, som gör det möjligt för företag att göra affärer i olika valutor och mellan olika gränser. Marknaden utgör en stor handelsplattform för både små och stora aktörer, för vilka det är viktigt att prognostisera valutakurser med gott resultat. Att modellera finansiella instrument i form av tidsserier är en av de vanligaste investeringsstrategierna och dess användningsområde sträcker sig från valutamarknaden till bland annat aktiemarknaden och råvarumarknaden. I denna uppsats undersöks fyra olika statistiska metoder för att modellera valutakursen Euro-US Dollar givet historisk data, och prognoser görs med de framtagna modellerna. Dessa metoder är slumpvandring, ARIMA, ARIMA-GARCH och VAR. Vidare undersöks för den dynamiska VAR-modellen hur valutamarkanden påverkar, och blir påverkad av, långa och korta räntan. Resultaten visar att ARIMA(3,1,2) förklarar valutakursen bäst medan VAR(2) med valutakursen och skillnaden mellan långa räntor som ingående variabler ger de bästa prediktionerna.
The foreign exchange market is the world’s largest market and is an essential part of the global society of today. The FX market enables companies to trade with different currencies across country borders. It is also a large trade-platform for both big and small financial actors, who greatly benefit from the advantages of good predictions. Modeling of financial instruments is one of the most commonly used investment strategies and its area of application ranges from the FX market to markets suchas the stock market and the commodity market. In this paper, four different statistical models are used to model the currency pair Euro-US Dollar. These methods are random walk, ARIMA, ARIMA-GARCH and VAR. Besides investigating which method that gives the best forecasts, the method that best describes the training datais also found. Furthermore, for the dynamic VAR model, it is explored how the FX market affects, and is affected by, the long term and short term interest. The results show that ARIMA(3,1,2) is the best at describing the exchange rate while VAR(2) with the exchange rate and the difference between long term interests as variables gives the best predictions.

Mestrado em Economia Monetária e Financeira
Tendo em conta o enquadramento da Terceira Fase da UEM, este trabalho aborda a questão da transmissão da política monetária à economia real. São estimados modelos VAR que pretendem identificar os efeitos de choques de taxa de juro sobre o produto e preços de duas economias da UEM, Portugal e Alemanha, em dois contextos distintos, políticas monetárias independentes e política monetária única. Paralelamente, estuda-se a importância relativa dos vários canais de transmissão monetária para o efeito total registado (canais de taxa de juro, taxa de câmbio e crédito). Os resultados confirmaram, como seria esperado, a reacção negativa do produto e preços dos dois países a aumentos de taxa de juro. Na transmissão monetária do período pré-UEM foram encontradas diferenças entre os dois países, a nível da magnitude e do timingdos efeitos. Considerando os resultados no contexto de política monetária única, concluiu-se que parte dessas diferenças estaria associada às diferentes funções de reacção e não a diferenças nos mecanismos de transmissão. Adicionalmente, encontraram-se indícios de que o mecanismo de transmissão destes países não se tenha alterado, de forma significativa, a partir de 1999. Ainda no contexto da UEM, concluiu-se que Portugal ocupa uma posição vulnerável, como país pequeno e como detentor de um mecanismo de transmissão forte. Relativamente aos vários canais de transmissão, os resultados comprovaram a relevância do canal de taxa de câmbio para Portugal no período pré-UEM. O canal do crédito e o de taxa de juro foram considerados relevantes para este país em ambos os regimes de política monetária. Na Alemanha, a taxa de juro terá sido o principal canal de transmissão em funcionamento, tendo repartido parte do seu papel com o canal do crédito no contexto da UEM e, eventualmente, com o canal de taxa de câmbio no período pré-UEM.
This thesis examines the issue of monetary policy transmission against the background of Stage Three of EMU. The intention is to identify, through the estimation of VAR models, the effects of an interest rate shock on the output and prices of two EMU economies, Portugal and Germany. This is done from two different perspectives, monetary policy independence and common monetary policy. Concurrently it is studied the relative strength of different channels of monetary transmission (interest rate, exchange rate and credit). The results confirmed, as expected, that in both countries, an interest rate shock leads to a decrease in both output and prices. In the pre-EMU period, it was found some heterogeneity in monetary policy transmission of the two countries as regards the strength and timing of the effects. However, considering the outcome from the EMU perspective, it was concluded that part of this heterogeneity might be due to the different monetary policy reaction functions rather than different transmission mechanisms. Some results were also found that seem to point to the maintenance of transmission mechanisms, in these countries, after 1999. Under EMU, Portugal was seen as being in a vulnerable position, being a small country with a strong monetary transmission mechanism. As for the monetary transmission channels, the results confirmed the significance for Portugal of the exchange rate channel in the pre-EMU period. Credit and interest rate channels were found to be of relevance, for this country, in both monetary policy regimes. In Germany, the interest rate channel was the dominant factor in monetary policy transmission. However, part of it was shared with the credit channel within the EMU perspective and, possibly, with the exchange rate channel when considering the pre-EMU period.

Das moderne Finanzsystem ist komplex, dynamisch, hochdimensional und oftmals nicht stationär. All diese Faktoren stellen große Herausforderungen beim Messen des zugrundeliegenden Finanzrisikos dar, das speziell für Marktteilnehmer von oberster Priorität ist. Hochdimensionalität, die aus der ansteigenden Vielfalt an Finanzprodukten entsteht, ist ein wichtiges Thema für Ökonometriker. Ein Standardansatz, um mit hoher Dimensionalität umzugehen, ist es, Schlüsselvariablen auszuwählen und kleine Koeffizientenen auf null zu setzen, wie etwa Lasso. In der Finanzmarktanalyse kann eine solche geringe Annahme helfen, die führenden Risikofaktoren aus dem extrem großen Portfolio, das letztendlich das robuste Maß für finanzielles Risiko darstellt, hervorzuheben. In dieser Arbeit nutzen wir penalisierte Verfahren, um die ökonometrischen Maße für das finanzielle Risiko in hoher Dimension zu schätzen, sowohl mit nieder-, als auch hochfrequenten Daten. Mit Fokus auf dem Finanzmarkt, können wir das Risikonetzwerk des ganzen Systems konstruieren, das die Identifizierung individualspezifischen Risikos erlaubt.
Modern financial system is complex, dynamic, high-dimensional and often possibly non-stationary. All these factors pose great challenges in measuring the underlying financial risk, which is of top priority especially for market participants. High-dimensionality, which arises from the increasing variety of the financial products, is an important issue among econometricians. A standard approach dealing with high dimensionality is to select key variables and set small coefficient to zero, such as lasso. In financial market analysis, such sparsity assumption can help highlight the leading risk factors from the extremely large portfolio, which constitutes the robust measure for financial risk in the end. In this paper we use penalized techniques to estimate the econometric measures of financial risk in high dimensional, with both low-frequency and high-frequency data. With focus on financial market, we could construct the risk network of the whole system which allows for identification of individual-specific risk.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Globalization provoked in financial markets by means stock exchanges an interchange among the markets over the world. The aim of this study was to examine the relationship of the ten major main economic index of the world represented in New York (DJIA, S&P500 e Nasdaq), Tokyo (NIKKEI 225), London (FSTE 100), São Paulo (IBOV), Shanghai (SSE180), Paris (CAC-40), Frankfurt (DAX-30) and Buenos Aires (Merval) and looking for its co-integration, to demonstrate the behavior of these indexes and the long run equilibrium, from January of 2010 to March of 2011. To investigate the equilibrium and the long rum behavior the error correction model was used jointly with co-integration test and impulse response based on Cholesky decomposition. The results of this study show that the index of stock markets has long term equilibrium, and American markets, Argentina and English showed a strong influence over other markets. With this research we can infer that a relationship exists between the stock markets under study, confirming that the economy in a country can influence the others. In this sense, the contribution of this study, given this range of discussions involving the interconnection of economies with respect to trades made on the stock exchanges, was to show the relationships and influences in the world.
A internacionalização somada à abertura dos mercados financeiros transformou as economias antes fechadas em economias abertas, provocou um intercâmbio entre as economias mundiais por meio das bolsas de valores. O objetivo deste estudo é examinar a relação entre os dez principais índices econômicos do mundo, sendo eles: Nova York (DJIA, S&P500 e Nasdaq), Tóquio (Nikkei 225), Londres (FSTE 100), São Paulo (IBOV), Shangai (SSE180), Paris (CAC), Frankfurt (DAX-30) e Bueno Aires (Merval), por meio da análise de co-integrações para demonstrar o comportamento desses índices e seus equilíbrios no período de janeiro de 2010 a março de 2011. Para investigar e verificar o comportamento em longo prazo, foi utilizado o modelo de correção de erros e teste de impulso-resposta baseado na decomposição de Cholesky. Os resultados deste estudo mostram que existe equilíbrio em longo prazo entre os índices do mercado de ações. Os mercados americano, argentino e inglês mostraram forte influência sobre os demais mercados. Com esta pesquisa, verifica-se que existe uma relação entre os mercados de ações estudados, confirmando que a economia de um país influencia as demais. A contribuição deste estudo é verificar a assertiva das discussões atuais sobre a dependência das economias mundiais com as negociações por meio da bolsa de valores.

Mestrado em Economia Monetária e Financeira
A questão dos efeitos macroeconómicos da política orçamental tem gerado uma controvérsia sem fim entre as escolas de pensamento económico. Se por um lado, os keynesianos defendem a ocorrência de efeitos positivos e persistentes resultantes de políticas de carácter mais expansionista, os defensores da chamada «perspectiva alemã» advogam precisamente o contrário. De acordo com a visão não-keynesiana, uma política de consolidação gera efeitos expansionistas, assim como uma política dita expansionista provoca, em geral, contracções no PIB e na despesa privada. Este trabalho surge assim no contexto deste intenso debate de ópticas opostas. E elaborado um estudo empírico para a economia portuguesa a partir do qual se pretendem apurar os efeitos de uma variação do consumo público. A partir da estimação de um modelo VAR se mi-estrutural com cinco variáveis endógenas (nas quais se incluem o consumo público real e o PIB real) para um conjunto de observações trimestrais entre 1982 e 2000, é identificado um vector de choques estruturais sobre o consumo público real e simulados os seus efeitos dinâmicos sobre as restantes variáveis do modelo, em particular o PIB real, impondo a restrição de que o consumo público não é contemporaneamente afectado por choques nas restantes variáveis. No final, comparam-se as conclusões com os resultados obtidos nos principais trabalhos de investigação sobre esta matéria.
The discussion about the macroeconomic effects of fiscal policy has been generating a never-ending controversy among the schools of economic thought If on the one hand, Keynesians stand up for the occurrence of posilive and permanent effects arising from policies with a more expansionary nature, on the other hand, defenders of the so-called "German view» defend precisely the opposite. According to the non-keynesian point of view, consolidation produces expansionary effects, whereas an expansionary policy gives rise, in general, to GDP and private expenditure contractions. This work then arises in the context of this deep debate of opposite points of view. We develop an empirical study of the Portuguese economy from which we attempt to investigate the effects of a one-time shock on total public consumption. From the estimation of a semi-structural VAR model with five endogenous variables (including real public consumption and real GDP) to a set of quarterly data from 1982 to 2000, we identify a vector of structural shocks on real public consumption and simulate their dynamic effects on the remaining variables of the model, particularly real GDP, imposing the restriction that the public consumption is not contemporaneously affected by changes in the remaining variables. At the end. we compare our conclusions with the results obtained in related papers.

E’ stato estesamente appurato che i mercati dell'elettricità mostrano mean-reversion e elevata volatilità dei prezzi. Questo lavoro utilizza un modello VAR-MGARCH al fine di cogliere queste caratteristiche presenti sul mercato dell'energia elettrica italiana (IPEX) e analizzare le interrelazioni esistenti tra le diverse regioni in cui il mercato è suddiviso. L’analisi è condotta sui prezzi giornalieri dal 1 ° gennaio 2006 al 31 dicembre 2008. I coefficienti stimati dalle equazioni condizionali indicano che i mercati regionali sono abbastanza integrati e i prezzi regionali dell'energia elettrica possono essere adeguatamente previsti impiegando i prezzi passati di ciascun mercato zonale. La volatilità e la cross-volatility sono significative per tutti i mercati, indicando la presenza di forti componenti ARCH e GARCH e la sostanziale inefficienza dei mercati. E’ inoltre evidente un’elevata persistenza della volatilità e della cross-volatility in tutti i mercati. I risultati indicano inoltre che gli shock rilevati, sia nella volatilità, sia nei vari mercati, persistono nel tempo e che in ogni mercato la persistenza è più marcata quando è causata da innovazioni stimate sulle stesso mercato rispetto a shock stimati su altre aree. Questa persistenza descrive la tendenza delle variazioni dei prezzi a raggrupparsi nel tempo.
It is commonly known that spot electricity markets show mean-reversion and high price volatility. This work employs a VAR-MGARCH model to capture these features in the Italian electricity market (IPEX) and analyze the interrelation existing among the different regions in which the market is divided. Daily spot prices from 1 January 2006 to 31 December 2008 are employed. The estimated coefficients from the conditional mean equations indicate that the regional markets are quite integrated and regional electricity prices could be usefully forecasted using lagged prices from either the same market or from the other areal markets. Volatility and cross-volatility spill-overs are significant for all markets, indicating the presence of strong ARCH and GARCH effects and market inefficiency. Strong persistence of volatility and cross-volatility are also evident in all local markets. The results also indicate that volatility innovations or shocks in all markets persist over time and that in every market this persistence is more marked for own-innovations or shocks than cross-innovations or shocks. This persistence captures the propensity of price changes of similar magnitude to cluster in time.

E’ stato estesamente appurato che i mercati dell'elettricità mostrano mean-reversion e elevata volatilità dei prezzi. Questo lavoro utilizza un modello VAR-MGARCH al fine di cogliere queste caratteristiche presenti sul mercato dell'energia elettrica italiana (IPEX) e analizzare le interrelazioni esistenti tra le diverse regioni in cui il mercato è suddiviso. L’analisi è condotta sui prezzi giornalieri dal 1 ° gennaio 2006 al 31 dicembre 2008. I coefficienti stimati dalle equazioni condizionali indicano che i mercati regionali sono abbastanza integrati e i prezzi regionali dell'energia elettrica possono essere adeguatamente previsti impiegando i prezzi passati di ciascun mercato zonale. La volatilità e la cross-volatility sono significative per tutti i mercati, indicando la presenza di forti componenti ARCH e GARCH e la sostanziale inefficienza dei mercati. E’ inoltre evidente un’elevata persistenza della volatilità e della cross-volatility in tutti i mercati. I risultati indicano inoltre che gli shock rilevati, sia nella volatilità, sia nei vari mercati, persistono nel tempo e che in ogni mercato la persistenza è più marcata quando è causata da innovazioni stimate sulle stesso mercato rispetto a shock stimati su altre aree. Questa persistenza descrive la tendenza delle variazioni dei prezzi a raggrupparsi nel tempo.
It is commonly known that spot electricity markets show mean-reversion and high price volatility. This work employs a VAR-MGARCH model to capture these features in the Italian electricity market (IPEX) and analyze the interrelation existing among the different regions in which the market is divided. Daily spot prices from 1 January 2006 to 31 December 2008 are employed. The estimated coefficients from the conditional mean equations indicate that the regional markets are quite integrated and regional electricity prices could be usefully forecasted using lagged prices from either the same market or from the other areal markets. Volatility and cross-volatility spill-overs are significant for all markets, indicating the presence of strong ARCH and GARCH effects and market inefficiency. Strong persistence of volatility and cross-volatility are also evident in all local markets. The results also indicate that volatility innovations or shocks in all markets persist over time and that in every market this persistence is more marked for own-innovations or shocks than cross-innovations or shocks. This persistence captures the propensity of price changes of similar magnitude to cluster in time.

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.

This paper concentrates on the description of fractional order LTI SISO systems using generalized Laguerre functions. There are properties of generalized Laguerre functions described in the paper, and an orthogonal base of these functions is shown. Next the concept of fractional derivatives is explained. The last part of this paper deals with the representation of fractional order LTI SISO systems using generalized Laguerre functions. Several examples were solved to demonstrate the benefits of using these functions for the representation of LTI SISO systems.

Abstract of thesis submitted in partial fulfilment of the requirements for the Degree of Master of Commerce and Management Dynamics of macroeconomic variables in Fiji : a cointegrated VAR analysis By Shiu Raj Singh The objective of this study is to examine how macroeconomic variables of Fiji inter-relate with aggregate demand and co-determine one another using a vector autoregression (VAR) approach. This study did not use a prior theoretical framework but instead used economic justification for selection of variables. It was found that fiscal policy, which is generally used as a stabilisation tool, did not have a positive effect on real Gross Domestic Product (GDP) growth in the short term. Effects on GDP growth were positive over the long term but not statistically significant. Furthermore, expansionary fiscal policy caused inflationary pressures. Fiji has a fixed exchange rate regime, therefore, it was expected that the focus of monetary policy would be the maintenance of foreign reserves. It was, however, found that monetary expansion in the short term resulted in positive effects on real GDP growth and resulted in inflation. The long term effects of monetary policy on real GDP growth were negative, which are explained by the fixed exchange rate regime, endogenous determination of money supply by the central bank, an unsophisticated financial market and, perhaps, an incomplete transmission of the policy. Both merchandise trade and visitor arrivals growth were found to positively contribute to short term and long term economic growth. Political instability was found not to have significant direct effects on real GDP growth but caused a significant decline in visitor arrivals which then negatively affected economic growth in the short term.

The "global" financial crisis (GFC) emerged during 2008 and it was mainly triggered by the sub-prime mortgage crisis (SMC) in the United States of America. The main aims of this thesis is to conduct an econometric analysis of the financial crisis and household savings in South Africa and also to provide a rationale that will facilitate a policy attention on Domestic Resource Mobilisation (DRM) through household savings. The study uses quarterly time series data for the period 199401 to 201102 obtained on-line from the South African Reserve Bank (SARB). The research is based on the Keynesian saving function, which is a complement of the consumption function. The model will be estimated by using a cointegrating vector autoregressive (CVAR) framework, which allows for endogeneity of the regressors. To check robustness on the cointegration results, the study employs the second empirical technique based on Generalized Impulse Response Function (GIRF) analysis and Variance Decomposition. The regression equation of household savings is expressed as a function of household disposable income, household debt to disposable income, real GOP, interest rate, inflation rate and foreign savings. The variables are tested for the presence of a unit root by the application of the Augmented Dickey-Fuller (AOF), Phillips-Perron (PP) Kwiatkowski, Phillips, Schmidt and Shin (KPSS) tests. The findings of the study are that all variables have unit roots. The cointegration model emphasises the presence of a long run equilibrium relationship between dependent and independent variables. The CVAR reveals the short run of the dynamic household savings model. Taking this into consideration, the study concludes that household debt has a huge influence on the level of household savings. The econometric analysis also revealed that household savings in South Africa actually improved during the period associated with the GFC. It could be postulated that South African households responded to their deteriorating financial situations by reducing their average spending and increasing their savings. Variance decomposition analysis revealed that 'own shocks' constitute the predominant source of variations in household saving therefore household savings can be explained by the disturbances in macroeconomic variables in the study. The study recommends the promotion of household savings and economic growth in order to reduce the dependence of South Africa on foreign savings. DRM is therefore enhanced by a higher level of household savings, which can facilitate higher levels of investment and economic growth.
Thesis (PhD (Economics) North-West University, Mafikeng Campus, 2012

The 2007-2008 US subprime mortgage crisis evolved into a financial crisis that negatively affected many economies in the world and therefore it was widely referred to as the global financial crisis. Since the beginning of this financial crisis of 2008-2009, South Africa experienced a significant increase in its household debt to income ratio. In the main, the aim of this dissertation is to investigate the prominent factors contributing to the rise in the level of household debt in South Africa. Also, we study the response of household debt to various shocks originating from the aforementioned crisis. Additionally, in the context of our timeline (1985 Q1-2012 Q1) we will extrapolate possible graphical trends in the rise and fall of household indebtedness in South Africa associated with various crises. Working from past research papers and a theoretical framework developed by Franco Modigliani and Milton Friedman, seven macroeconomic variables will be considered to examine the rise of household borrowing to income namely; the real house price index, consumer price index. real income, real prime rate, real household consumption expenditure, real gross domestic product and real household savings. Both a long-run cointegration analysis and a short-run error correction model will be used to evaluate the relationship between household debt and the chosen variables by estimating a Vector Error Correction Model. Furthermore, the Variance Decomposition and the Generalized Impulse Response Function will be utilized to assess the impact of household debt to various shocks emanating from the 2008-2009 financial crisis. The different models and tests conducted in this research will be executed using the statistical software package EVIEWS 7. Based on the results, household debt was seen to have been fairly affected by the 2008-2009 financial crisis. The cointegration analysis maintains that in the long run, household borrowing is positively and significantly determined by consumer price index and real household consumption. In addition, it confirms that household borrowing is negatively affected by real household income and real GOP. The rest of the variables were found insignificant. Nevertheless, the short run error correction model reveals that about 3.6% of the disequilibrium will be corrected each quarter for the equilibrium state to be restored. Also, the Variance Decomposition results confirmed that the South African household debt is mostly affected by shocks from real house price index, real household income, real household consumption and real household savings, respectively. Furthermore, the Generalized Impulse Response Function results established the significant positive response of household debt to a shock from real house price index and real household consumption. The response of debt to shocks from consumer price index, real household savings and real income is negative and this outcome is confirmed by the theory. However, the response of debt shows fluctuating behaviours to shocks from LRIN, LRPR and LRGDP over the estimated period. In conclusion, our econometric investigation highlighted the main causes of the high levels of household debt in South Africa both in the short and long run. The Generalized Impulse Response Functions confirm that shocks like the occurrence of the 2007-2008 financial crisis will have a significant impact on real house price index, consumer price index, real household consumption and real household savings. The Engle granger results show that there exist no significant relationship between household debt and unemployment in South Africa over the period 1980 to 2010. However, we propose that this result may have been significant if quarterly unemployment data was available and included in the main data set. Finally, based on the stability, validity and reliability of our model, we recommend its use to facilitate policy analysis and decision making regarding household debt levels in South Africa.
Thesis (M.Com.( Economics) North-West University, Mafikeng Campus, 2012

Questa tesi esamina le interazioni tra l'incertezza e la politica monetaria mediante l'utilizzo di metodi econometrici non lineari. Si compone di tre capitoli distinti. Il primo capitolo si occupa degli effetti degli stimoli inattesi (shock da ora in avanti) di politica monetaria condizionali a diversi livelli di incertezza. Sulla base della letteratura teorica, diverse spiegazioni si pensa siano in grado di ridurre l'efficacia della politica monetaria in tempi incerti (ad esempio, l'esistenza di opzioni reali, un differente comportamento price-maker delle imprese e un maggiore risparmio precauzionale). Al fine di valutare empiricamente le supposizioni teoriche si stima un modello Interacted-VAR non lineare dove, in maniera innovativa rispetto alla letteratura, si modella la variabile condizionante - un indicatore di incertezza nel mio caso - endogenamente nel VAR. Questo implica la necessità di adottare le funzioni di risposta generalizzate (GIRFs, dall'inglese Generalized Impulse Response Functions) à la Koop et al. (1996). I risultati suggeriscono che gli shock di politica monetaria sono significativamente meno efficaci in tempi incerti, con le reazioni di picco di diverse variabili reali circa due terzi più lievi di quelle durante i periodi tranquilli. Trovo anche che l'incertezza diminuisce dopo uno shock di politica monetaria espansiva. Inoltre, mostro che, coerentemente con i risultati teorici di Vavra (2014), la reazione dei prezzi risulta più grande durante i periodi di maggiore incertezza a livello di impresa. Il secondo capitolo (lavoro congiunto con G. Caggiano e E. Castelnuovo) si interessa dell'impatto di aumenti inattesi (shock) di incertezza in presenza di un tasso di interesse a breve periodo pari a zero (in breve ZLB, dall'inglese zero lower bound), una situazione in essere negli Stati Uniti a partire dal dicembre 2008. Diversi recenti studi teorici suggeriscono che, in questa evenienza, gli shock di incertezza dovrebbero generare un calo molto più grande e persistente dell'attività reale (si veda Fernandez-Villaverde et al. (2015), Johannsen (2013), Nakata (2013), and Basu and Bundick (2014, 2015)). Tuttavia, sul lato empirico, non è stata ancora proposta alcuna analisi che modelli esplicitamente la non linearità degli effetti reali degli shock di incertezza dovuta allo ZLB. A questo scopo, ci si avvale di un parsimonioso modello Interacted-VAR non lineare allo scopo di valutare empiricamente le predizioni teoriche. I risultati mostrano che gli effetti recessivi degli shock di incertezza sono statisticamente maggiori in presenza dello ZLB, con differenze che sono economicamente importanti. Si mostra che tali differenze non sono dovute al verificarsi contemporaneo della Great Recession. Il terzo capitolo ritorna sull'argomento del capitolo 1, con l'obiettivo di indagare sulle ragioni strutturali alla base della minore efficacia degli shock di politica monetaria durante i tempi incerti. A questo scopo si adotta un affermato modello DSGE (dall'inglese Dynamic Stochastic General Equilibrium) Neo-Keynesiano. In particolare, si propone una semplice strategia econometrica per stimare con metodo Minimum Distance il modello DSGE condizionalmente a due regimi identificati sulla base dei dati per mezzo di modello Threshold VAR. Questa strategia poi si applica al modello di Altig, Christiano, Eichenbaum e Lindé (ACEL, 2011). Si trova che il modello di ACEL risulta essere notevolmente in grado di eguagliare le risposte del VAR, soprattutto in tempi tranquilli. Questa performance è guidata da dei valori stimati per alcuni parametri strutturali del tutto differenti tra i due regimi. In particolare, una maggiore pendenza della curva di Phillips Neo-Keynesiana, un maggior costo per variare il tasso di utilizzo del capitale, e un minore grado di abitudini nel consumo sono i principali driver della capacità del modello di predire inferiori effetti reali degli shock di politica monetaria in periodi di elevata incertezza.
This thesis assesses the interactions between uncertainty and monetary policy by means of nonlinear econometric methods. It consists of three separate chapters. The first chapter is concerned with the effects of monetary policy shocks conditional on different levels of uncertainty. On the basis of the theoretical literature, several explanations are thought to be able to reduce the effectiveness of monetary policy during uncertain times (e.g., real option effects, …firm-price setting behavior and precautionary savings). In order to empirically assess theoretical predictions I estimate a nonlinear Interacted VAR model, where, in a novel way with respect to the literature, I model the conditioning indicator - uncertainty, in my case, which discriminate "high" from "low" uncertainty states - endogenously in the VAR. This implies the necessity to adopt the Generalized Impulse Response Functions à la Koop, Pesaran and Potter (1996). This strategy enables me to consider both the possible endogenous reaction of uncertainty to the policy shock and its feedbacks on the dynamics of the system. My findings suggest that monetary policy shocks are significantly less effective during uncertain times, with the peak reactions of a battery of real variables being about two-thirds milder than those during tranquil times. I also find that uncertainty decreases after an expansionary monetary policy shock. Further, I show that, consistently with Vavra's (2014) predictions, the reaction of prices appears greater during firm-level uncertain times. The second chapter (coauthored with G. Caggiano and E. Castelnuovo) is concerned with the impact of uncertainty shocks at the zero lower bound (ZLB), which has been hit since December 2008 in the U.S. On the theoretical side, several recent studies suggest that when monetary policy is constrained by the ZLB, uncertainty shocks should generate a much larger and persistent drop in real activity (see Fernandez-Villaverde, Guerron-Quintana, Kuester, and Rubio-Ramirez (2015), Johannsen (2013), Nakata (2013), and Basu and Bundick (2014, 2015)). However, on the empirical side, no analysis explicitly modeling the nonlinearity of the real effects of uncertainty shocks due to the ZLB has been proposed so far. To this aim we employ a parsimonious nonlinear Interacted-VAR model to examine whether the real effects of uncertainty shocks are greater when the economy is at the ZLB. Our results show that the contractionary effects of uncertainty shocks are statistically larger when the ZLB is binding, with differences that are economically important. Such differences are shown not to be driven by the contemporaneous occurrence of the Great Recession. The third chapter returns on the argument of Chapter 1 with the aim of enquiring on the structural reasons behind the lower effectiveness of monetary policy shocks during uncertain times. To do so I adopt the lens of the workhorse New Keynesian model. In particular, I propose a simple state-conditional Minimum Distance estimation strategy of a DSGE model, which I apply to the Altig, Christiano, Eichenbaum and Lindè's (ACEL, 2011) model. The estimator matches as closely as possible the regime-dependent responses coming from an unrestricted Threshold VAR model with the corresponding model-based responses. This approach may capture possibly unmodelled mechanisms through regime-specific estimates of structural parameters. I find the ACEL model to be remarkably able to match the VAR impulse responses, particularly in tranquil times. This performance is driven by very different estimated values for some key-structural parameters in the two states. A higher slope of the new-Keynesian Phillips curve, a higher cost of the variation in capital utilization, and a lower degree of habit formation in consumption are shown to be behind the model ability to predict the lower real effects of monetary policy shocks in periods of high uncertainty.

Tese de mestrado integrado em Engenharia Biomédica e Biofísica (Sinais e Imagens Médicas), Universidade de Lisboa, Faculdade de Ciências, 2021
O processo de desenvolvimento do cérebro humano tem sido objeto de estudo desde há vários anos, levando a avanços significativos no que diz respeito à compreensão das suas diferentes fases e mecanismos. Visto que este desenvolvimento resulta de uma série de complexos processos dinâmicos e adaptativos, existe uma busca contínua de informação sobre a sua organização estrutural e funcional, bem como o seu processo de maturação. A ressonância magnética de difusão (dMRI) é uma técnica bastante completa no que diz respeito à análise do cérebro in vivo. Esta técnica é utilizada para realizar um mapeamento quantitativo, através da aplicação de modelos como o modelo de difusão tensorial (DTI). Estes modelos fornecem medidas que caracterizam o cérebro, tais como a anisotropia fraccional (FA) e difusividade média (MD), permitindo assim a quantificação de microestruturas e consequentemente a reconstrução de feixes de substância branca (WM) que ligam diferentes regiões cerebrais. Dadas as suas propriedades de difusão anisotrópica e a sua constituição fibrosa, as fibras de WM têm sido amplamente estudadas através da dMRI. Além disso, a tractografia tornou-se a abordagem padrão no que diz respeito à avaliação da conectividade cerebral usando dados de dMRI. Os métodos de desconvolução esférica (SD) estão entre os mais utilizados para quantificar a distribuição da orientação das fibras (FOD) a partir de dados dMRI do cérebro, sendo que a forma mais comum de o fazer é com desconvolução esférica limitada (CSD). A ideia original da CSD baseia-se no facto de podermos escolher uma função de resposta (RF) representativa de um determinado tecido presente no cérebro e aplicar a SD para resolver o problema de cruzamento de fibras que o modelo de DTI não consegue resolver. Uma vez que o cérebro possui uma complexa organização de tecidos, múltiplos tecidos devem ser considerados. Não é apropriado usar uma RF de WM em todo o cérebro, pois isso pode levar a reconstruções imprecisas da orientação das fibras e a um mau desempenho durante o processo de tractografia. Ao ter em conta múltiplos tecidos, as propriedades da substância cinzenta (GM) e do líquido céfalo-raquidiano (CSF) podem ser quantificadas, e os efeitos de volume parcial (PVE) podem ser reduzidos. Nos últimos anos, tem sido possível adquirir dados “multi-camada” mais complexos e de elevada resolução, mesmo em recém-nascidos, o que permitiu melhorar a técnica de CSD. Consequentemente, esta aquisição também vai melhorar a reconstrução da FOD no cérebro adulto, pois considera os PVE entre diferentes tipos de tecidos. No cérebro neonatal existem algumas diferenças, pois este é constituído por WM em diferentes fases de maturação, e a GM possui características diferentes em comparação com um cérebro adulto. A possibilidade de distinguir diferentes tipos de fibras apenas com base nas suas características microestruturais deve-se às diferenças presentes no cérebro enquanto este se encontra numa fase de desenvolvimento. Em cérebros adultos, é menos provável conseguir observar tais diferenças. Uma das melhores formas de compreender e estudar estes processos de desenvolvimento cerebral é através do estudo do cérebro de neonatais. Como seria de esperar, o cérebro de um recém-nascido não se encontra completamente maturado, sofrendo por isso diversas alterações até estar totalmente desenvolvido. Estas mudanças vão desde o aumento do tamanho do cérebro a alterações ao nível vascular, levando consequentemente a uma alteração dos processos de cognitivos. Em última análise, a aplicação de CSD a dados de “multi-camada” leva a uma extração mais precisa da FOD que por sua vez irá melhorar o processo de tractografia e levará, consequentemente, a uma melhor compreensão do cérebro humano e do seu desenvolvimento, particularmente se aplicada em recém-nascidos e comparada com adultos. O método Generalized Richardson-Lucy (GRL) pode superar os problemas encontrados pela CSD através da realização de SD robusta, suprimindo picos imprecisos na FOD em dados “multi-camada” de dMRI. Este método pode definir múltiplos tecidos que irão aumentar a precisão da estimativa da FOD. No entanto, no método GRL, as três classes de tecidos representadas (WM, GM e CSF) são pré-definidas com valores FA e MD retirados da literatura. Este estudo consistiu em desenvolver um método que determina automaticamente o número de classes (tecidos) necessárias para aplicar corretamente GRL no cérebro com dados “multi-camada”, utilizando para isso os seus valores de FA e MD. O objetivo é aplicar corretamente o método de GRL no cérebro com as classes obtidas, de forma avaliar se existe uma melhoria no processo de estimação das FOD e por sua vez no processo de tractografia. Os dados utilizados neste trabalho consistem em dados de dMRI de dez neonatais e dez adultos, fornecidos pelo Developing Human Connectome Project (dHCP) e pelo Human Connectome Project (HCP), respetivamente. Estes dados já se encontravam num formato pré-processado, pelo que não foi necessário realizar qualquer etapa adicional neste sentido. A primeira parte do estudo consistiu no desenvolvimento do método de deteção automática do número de tipos de tecidos no cérebro. Para isso, todos os dados foram processados no ExploreDTI, um programa de interface gráfica para dados de dMRI e que permite, por exemplo, a realização de tractografia. Este programa foi também usado para extrair os valores de FA e MD dos dados de dMRI dos cérebros dos neonatais e dos adultos, de modo a analisar a sua distribuição de valores por todo o cérebro através de histogramas. De seguida foi aplicado um gaussian mixture model (GMM) aos histogramas de FA e MD, utilizando o MATLAB R2018a, de forma a decompor os dados em classes. Depois de aplicar o GMM aos dados, foi determinado o número ideal de Gaussianas para os mapas de FA e MD. Para isso foi calculado o Bayesian information criterion (BIC) de cada modelo, em que cada um destes se caracteriza por um certo número de Gaussianas. De seguida, foi calculada a probabilidade do valor de cada voxel pertencer a uma das classes escolhidas de FA e MD, atribuiu-se assim uma classe a cada voxel. Posteriormente selecionaram-se as três melhores combinações de FA e MD de cada classe com base na frequência de ocorrência de cada combinação, sendo que cada classe foi definida pela média e desvio padrão das respetivas Gaussianas. Por fim, foram criados mapas espaciais do cérebro com as classes finais, utilizando o MATLAB R2018a. Na segunda parte do estudo aplicou-se o método GRL aos dados, de forma a estimar a RF de cada um dos tecidos que foram selecionados na primeira parte. Estas duas partes do trabalho integram a nossa abordagem, sendo esta designada por "GRL-auto". No método GRL, a RF da GM e do CSF é baseada em valores de FA e MD retirados da literatura, enquanto que o método GRL-auto desenvolvido neste estudo estima esses valores através da seleção automática dos valores de FA e MD que são característicos de cada um destes tecidos. Obtiveram-se os mapas das frações de sinal da WM, GM, e CSF e foram feitas comparações entre o método GRL e GRL-auto. As FOD da WM obtidas com ambos os métodos foram comparadas entre si em regiões de cruzamento de fibras, tanto para neonatais como para os adultos. Por fim, para ambos os métodos, procedeu-se à tractografia em neonatais. Os resultados indicam que, tanto para recém-nascidos como para adultos, existe consistência em relação aos valores de FA e MD e ao seu respetivo número de classes selecionadas. Além disso, conseguem ser observadas diferentes fases de maturação de WM nos neonatais, mas também algumas imperfeições à volta dos ventrículos e regiões onde ocorre cruzamento de fibras. Todos os mapas espaciais de FA e MD fizeram sentido anatomicamente, sendo consistentes quer nos neonatais quer nos adultos, demonstrando assim a eficácia deste método. Os mapas de sinal das frações de WM, GM, e CSF apresentaram valores plausíveis e concordância com a anatomia esperada, para além de consistência tanto nos recém-nascidos como nos adultos. Os mapas de frações de sinal dos adultos praticamente não apresentaram diferenças entre os dois métodos. No entanto, os neonatais mostraram algumas diferenças notáveis, particularmente nos mapas de GM e CSF. Os resultados relativos às FODs não mostraram diferenças significativas no que diz respeito aos adultos. No entanto, para os neonatais, o método GRL-auto estimou FODs de elevada qualidade na WM, em comparação com o método GRL. Além disso, o método GRL-auto detetou mais picos plausíveis em regiões de cruzamento de fibras par além de uma diferença angular maior entre os principais picos das FOD, em comparação com o método GRL. Por fim, este método demonstrou uma melhoria no processo de tractografia, o que por sua vez levará a uma melhor compreensão do cérebro humano e do seu desenvolvimento. Conclui-se assim que o método desenvolvido neste estudo é eficiente e mostra consistência no que diz respeito ao processo de seleção automática do número de tecidos necessários para efetuar CSD no cérebro. Observou-se uma melhoria na tractografia das fibras, o que permitirá uma melhor compreensão da maturação do cérebro bem como das conexões entre as diversas regiões, tendo-se, assim, cumprido o objetivo principal deste trabalho.
To understand the development of the human brain, more detailed information is required regarding the structural and functional cerebral organization and maturation. This development is the product of a complex series of dynamic and adaptive processes, and one of the best ways to understand it is through the study of the neonatal brain. The neonatal brain is not fully developed as it would be expected, so it goes through many changes regarding brain size, vasculature, and cognition. Constrained spherical deconvolution (CSD) is a widely used approach to quantify the fiber orientation distribution (FOD) from diffusion magnetic resonance imaging (dMRI) data of the brain, which allows the reconstruction of more complex white matter (WM) bundles in vivo, including in neonates. However, this method estimates the response function (RF) based on the model of a single fiber population and uses it to try to reconstruct the local WM orientations. Since the brain has a complex tissue organization, multiple tissues must be considered. It is not appropriate to use a WM RF throughout the whole brain because this can lead to spurious fiber orientation reconstructions and bad performance during fiber tractography. By accounting for multiple tissues, properties of grey matter (GM) and cerebrospinal fluid (CSF) can be captured, and partial volume effects (PVE) reduced. The acquisition of more comprehensive high-resolution multi-shell dMRI data offers opportunities to take into account multiple tissue types. Ultimately, these improve fiber tractography and consequently lead to a better understanding of the human brain and its development. The generalized Richardson-Lucy (GRL) method can overcome these challenges by performing robust spherical deconvolution (SD) and suppress spurious FOD peaks on multi-shell dMRI data due to PVE. However, in the GRL method, three tissue classes are typically pre-defined to represent WM, GM, and CSF, using fractional anisotropy (FA) and mean diffusivity (MD) values taken from literature. These two metrics are derived from the diffusion tensor model (DTI), with FA measuring how anisotropic is the tensor in each voxel and MD measuring the average of the diffusion rate at each voxel. This study aims to develop a method that automatically determines the number of tissue types (classes) that are needed to properly perform GRL in each analyzed brain dataset. The dataset used in this work consists of ten neonates and ten adults from the Developing Human Connectome Project (dHCP) and the Human Connectome Project (HCP), respectively. The first part of this study consisted of developing a method for the automatic detection of the number of tissue types in the brain, by applying a gaussian mixture model (GMM) and the Bayesian information criterion (BIC) to automatically extract the number of tissue classes from the histogram of dMRI properties. In the second part, the GRL method was applied to the data to estimate the RF of each tissue that was automatically chosen in the first part, and therefore calculate the FOD and perform fiber tractography. This approach was designated by “GRL-auto”. Lastly, a comparison between the basic GRL formulation and GRL-auto was done. Since GRL uses predefined values calibrated on HCP data, it becomes clear that small differences were expected on such dataset, whereas on dHCP larger differences were expected. Our analysis showed that our method automatically identified three classes in the FA histogram and two classes in the MD histogram when using HCP and dHCP data. Therefore, these results demonstrated consistency regarding the FA and MD values and their respective number of selected classes, for both datasets. Furthermore, different stages of WM maturation were detected in the dHCP data, but also some imperfections around the ventricles and crossing fibers areas. All FA and MD spatial maps were in line with anatomical correspondence and were consistent across all neonatal and adult subjects, demonstrating the efficiency of this method. The values of the WM, GM, and CSF fraction maps were plausible, in line with the expected anatomy, and looked consistent on both HCP and dHCP datasets. The signal fraction maps determined with the HCP data showed almost no difference between GRL and GRL-auto. However, in the dHCP data, we observed notable differences, particularly in the GM and CSF maps. Regarding the FOD estimation, our results showed no difference in the HCP data. Nevertheless, for the dHCP data, GRL-auto estimated high-quality FODs in WM, and detected more peaks in crossing fiber regions and a bigger angular difference between the main FOD peaks, as compared to GRL. Lastly, we showed that GRL-auto led to improvements in fiber tractography, which will likely support gaining a better understanding of the human brain and its development. Therefore, we can conclude that the method developed in this study is efficient and consistent in the automatic selection of the number of tissues needed to properly perform GRL in a brain, given multi-shell data, which was the main goal.

Rapid increases in consumer food price beginning in 2007 generated interest in identifying the main factors influencing these increases. In subsequent years, food prices have fluctuated, but generally have continued their ascent. The effects of crude oil, gasoline, corn, and ethanol prices, as well as, the relative foreign exchange rate of the U.S. dollar and producer price indexes for food manufacturing and fuel products on domestic food prices are examined. Because the data series are non-stationary and cointegrated, a vector error correction model is estimated. Weak exogeneity and exclusion tests in the cointegration space are performed. Directed acyclical graphs are used to specify contemporaneous causal relationships. Dynamic interactions among the series are given by impulse response functions and forecast error variance decompositions. Weak exogeneity tests indicate all eight series work to bring the system back into equilibrium following a shock to the system. Further, exclusion tests suggest crude oil, gasoline, food CPI, ethanol, and food PPI variables are not in the long-run relationships. Dynamic analyses suggest the following relationships. Ethanol price is not a major factor in domestic food prices, suggesting that food prices are largely unaffected by the recent increased use of corn-based ethanol for fuel. Crude oil prices, corn prices, and the relative foreign exchange rate of the U.S. dollar, however, do influence domestic food prices with corn price contributing the most to food price variability. Innovation accounting inferences are robust to potential different contemporaneous causal specifications.

NO
The relationship between exports and economic growth has been analysed by a number of recent empirical studies. This paper re-examines the sources of growth for the period 1971-2001 for India. It builds upon Feder's (1983) model to investigate empirically the relationship between export growth and GDP growth (the export led growth hypothesis), using recent data from the Reserve Bank of India, and by focusing on GDP growth and GDP growth net of exports. We investigate the following hypotheses: (i) whether exports, imports and GDP are cointegrated using the Johansen approach and Breitung's nonparametric cointegration test; (ii) whether export growth Granger causes GDP growth; (iii) and whether export growth Granger causes investment. Finally, a VAR is constructed and impulse response functions (IRFs) are employed to investigate the effects of macroeconomic shocks.

In this work project we evaluate the impact of the main unconventional monetary policy tool adopted by the ECB in September 2014, namely the negative interest rates policy (NIRP). What is the impact on the economy of Eurozone countries and is this policy the best and efficient? We first explain the reasons behind the use of these measures and then examine the effectiveness of the monetary policy conducted by the ECB. We also assess whether, due to the introduction of negative interest rates, the effects of monetary policy on the real economy are characterized by a structural break. The main conclusion of the analysis is that the introduction of NIRP seems to have been ineffective.

This thesis explores the price determinants of Bitcoin using a macroeconomic model based on the economic equation of exchange presented by Joseph Wang (2014). The thesis provides a concise and structured introduction to Bitcoin and a comprehensive literature review on Bitcoin. The analysis begins with the application of the functions of money to Bitcoin, arguing that while Bitcoin does fulfill the three classical functions of money to a certain extent, its use remains mainly as a speculative instrument. Wang's model is criticized and amended to reflect the realities of empirically analyzing the Bitcoin market. Using the daily number of transactions and Bitcoin days destroyed as proxies for economic activity and inactivity - to measure Bitcoin's velocity on the block chain - vector autoregression modelling is used to determine if there is Granger causality between the price of bitcoin and the two proxies. The results demonstrate that there is a bidirectional Granger-causal relationship between Bitcoin days destroyed and the price of bitcoin and that there is none between the daily number of transactions and the price of bitcoin; proving Wang's two main assumptions. Impulse- response functions are provided to illustrate and discuss this bidirectional relationship. The results are in line with the...

This study aims to analyse the impact of monetary shocks, both on the aggregate euro area as a whole and also at the country level. We estimate a dynamic factor model that summarises the information in a large data set with few estimated factors, subsequently incorporated in a recursive VAR. We find that (i) when compared with the VAR model, the FAVAR better identified the shock, mainly after the 2008 crises; (ii) the monetary policy seems to have lost impact over the economy in recent years; (iii) across countries, the results reveal mixed reactions, being the larger economies the ones that predominantly benefited from the monetary policy.

In speech communication systems such as voice-controlled systems, hands-free mobile telephones and hearing aids, the received signals are degraded by room reverberation and background noise. This degradation can reduce the perceived quality and intelligibility of the speech, and decrease the performance of speech enhancement and source localization. These problems are difficult to solve due to the colored and nonstationary nature of the speech signals, and features of the Room Impulse Response (RIR) such as its long duration and non-minimum phase. In this dissertation, we focus on two topics of speech enhancement and speaker localization in noisy reverberant environments. A two-stage speech enhancement method is presented to suppress both early and late reverberation in noisy speech using only one microphone. It is shown that this method works well even in highly reverberant rooms. Experiments under different acoustic conditions confirm that the proposed blind method is superior in terms of reducing early and late reverberation effects and noise compared to other well known single-microphone techniques in the literature. Time Difference Of Arrival (TDOA)-based methods usually provide the most accurate source localization in adverse conditions. The key issue for these methods is to accurately estimate the TDOA using the smallest number of microphones. Two robust Time Delay Estimation (TDE) methods are proposed which use the information from only two microphones. One method is based on adaptive inverse filtering which provides superior performance even in highly reverberant and moderately noisy conditions. It also has negligible failure estimation which makes it a reliable method in realistic environments. This method has high computational complexity due to the estimation in the first stage for the first microphone. As a result, it can not be applied in time-varying environments and real-time applications. Our second method improves this problem by introducing two effective preprocessing stages for the conventional Cross Correlation (CC)-based methods. The results obtained in different noisy reverberant conditions including a real and time-varying environment demonstrate that the proposed methods are superior compared to the conventional TDE methods.
Graduate
2015-04-23
0544
0984
saeed.mosayyebpour@gmail.com

JEL Classification: E32, E37
This dissertation aims to analyze the dynamics of business cycles across European countries between 1960Q1 and 2016Q1. For such purpose we identify country-groups of national deviation cycles through Hierarchical Agglomerative Clustering with the Ward’s method. The clustering technique suggests the existence of three country-groups, which include, aside from other countries, France and Spain in Cluster 1, United Kingdom and Denmark in Cluster 2 and Germany and Italy in Cluster 3. We execute an extensive analysis on business cycle stylized facts, synchronization and turning points detection over the clusters’ deviation cycles. Further on, we analyze the propagation of economic shocks through a VAR model, over which we study Granger-causalities, Impulse Response Functions and Forecast Error Variance Decomposition. Our results show that both Cluster 1 and Cluster 2 share similar cyclical characteristics when compared to Cluster 3. Nevertheless, Cluster 1 and Cluster 3 appear to be the most synchronous pair, and simultaneously verify the largest proportion of time spent in the same cyclical phase. We show that there has been an increasing business cycle synchronization in Europe since the beginning of the 90’s. The structural analysis shows that Cluster 1 and Cluster 2 have the strongest permanent cumulative shocks, whereas Cluster 3 induces not only the weakest impulses but also explains the smallest fraction of the counterparts’ forecast error variance decomposition. These conclusions question the "German Dominance" hypothesis and allow the identification of alternative major economic propellers in Europe.
A presente tese pretende analisar as dinâmicas dos ciclos económicos na Europa no período compreendido entre 1960Q1 e 2016Q1. Como tal, procedemos à identificação de grupos de ciclos económicos nacionais através de Clusterização Hierárquica Aglomerativa com o método de Ward. A Clusterização sugere a existência de três grupos que incluem, além de outros países, França e Espanha no Cluster 1, Reino Unido e Dinamarca no Cluster 2, e Alemanha e Itália no Cluster 3. Analisamos as principais características, sincronização e cronologia de pontos de inflexão dos ciclos económicos dos clusters. Estudamos ainda a propagação de choques económicos com um modelo VAR, sobre o qual concluímos sobre causalidade à Granger, funções de impulso-resposta e decomposição de variância. Os resultados mostram que o Cluster 1 e Cluster 2 apresentam maiores semelhanças nas características dos seus ciclos quando comparados ao Cluster 3. Simultaneamente, o Cluster 1 e Cluster 3 apresentam quer o maior nível de sincronização quer a maior fração de tempo partilhada na mesma fase cíclica. Concluímos também que o nível de sincronização dos ciclos económicos na Europa apresenta uma tendência crescente, especialmente após os anos 90. A análise estrutural conclui que o Cluster 1 e Cluster 2 produzem os choques permanentes mais fortes, enquanto que o Cluster 3 induz os impulsos mais fracos, além de explicar a menor parte da decomposição de variância do erro de previsão dos restantes. As presentes conclusões questionam a hipótese de "Domínio Alemão" e permitem a identificação de outros propulsores económicos na Europa.

Classificação: C32; C51; E23
No presente estudo é feito o exame da relação existente entre os indicadores de confiança dos Consumidores e dos Empresários com a realidade Económica e Financeira observada em Portugal entre Janeiro de 1999 e Dezembro de 2009. Para representar a realidade económica foi utilizado o Produto Interno Bruto a Preços Constantes e, por sua vez, o índice PSI-20 foi utilizado como indicador representativo da realidade Financeira. Para proceder a esta averiguação foi utilizada uma metodologia de vectores auto regressivos (VAR). De entre as várias conclusões retiradas, é necessário realçar que a variação dos indicadores de confiança é bastante relevante para explicar a evolução económica e financeira de Portugal. Destaque especial para o Indicador de confiança dos consumidores em termos de ajuda na explicação da variação do PIB e na previsão do mesmo. Por sua vez a variação do PSI-20 ajuda a prever a variação da Confiança dos Empresários.Já esta última consegue explicar mais de 17% da variabilidade do principal Índice Bolsista Português. O que é importante reter, neste estudo, é que sendo os indicadores de confiança apresentados com uma maior antecedência em relação à maioria dos indicadores de conjuntura económica e financeira e com uma periodicidade mensal, é necessário que estes sejam alvo frequente de atenção por parte dos vários governos e instituições com responsabilidade económica e financeira (por exemplo a União Europeia o BCE e o FMI) para análise das várias políticas e estratégias de crescimento económico implementadas.
The present study was done by examining the relationship between Consumer and Business confidence indicators and the Economic and Financial reality observed in Portugal between January 1999 and December 2009. To represent the economic reality, we used Gross Domestic Product at Constant Prices, and in turn the PSI-20 was used as a proxy indicator of financial reality. To carry out this investigation we used vector auto regressive methodology (VAR). Among the many conclusions drawn, it must be stressed that the range of confidence indicators is very important to explain the economic and financial developments in Portugal. Of particular note is the indicator of consumer confidence as a help in explaining the variation and also the anticipation of GDP. The variation of the PSI-20 helps predict the variation of the Business Confidence, since it can explain more than 17% of the variability of the main Portuguese stock index. Based on this study, we can point out that the confidence indicators being presented, with a major advance in relation to most indicators of economic and financial environment and on a monthly basis, should be a frequent target of attention from various governments and institutions with responsibility for economy and finances (e.g. the European Union, the ECB and the IMF) for the analysis of various policies and implemented strategies for economic growth.

Mestrado em Economia Monetária e Financeira
Following the tenth anniversary of Stage III of the European Monetary Union, this study assesses the effects of monetary policy shocks in the euro area in I hc period during which there is a commnon monetary policy in Europe. l n order to overcome the omitted information problem of small-scale vector autoregression (VAR) models, we combine the VAR methodology with dynamic factor analysis, a recent time-series technique for the analysis of large data sets. Using the factor-augmented vector autoregressive (FAVAR) approach of Bernanke et al. (2005), we summarise the in­formation contaiined in a large set of macroeconomic time series with a small number of estimated factors and use them as regressors in recursive VARs to evaluate the impact of thc non-systematic component of the ECB's actions. 0verall, our results suggest that the inclusion of factors in the VAR allows us to obtain a more coherent picture of the effects of monctary policy innovations, both by achieving responscs easier to understand from the theoretical point of view and by inc-reasing the preci­sion of such responses. Moreover, to the extent that, we i nclude in the econometric model a very wide set of variables, w hich we believe the ECB effectively monitors, the likelihood of obtaining a contaminated measurement of policy shocks decreases. ln addition, this framework allows us to compute impulse-response functions for all the variables included in the panel, thereby providing a more complete and accurate depiction of the effects of policy disturbances. However, the extra information ge­nerated by the FAVAR also delivers some puzzling responses, in particular those relating to the components of inflation.
Após o décimo aniversário da Fase III da União Monetária Europeia, este estudo avalia os efeitos dos choques de política monetária na área do euro no período em que existe uma politica monetária comum na Europa. Com vista a superar o problema de informação omitida dos modelos vectoriais autoregressivos (VAR), este estudo combina a metodologia VAR com a análise factorial dinâmica, uma técnica recente para análise de amostras amplas. Com base na abordagem VAR aumentada de factores (FAVAR), introduzida por Bernanke et al. (2005), a informação contida num conjunto vasto de séries temporais macroeconómicas é resumida num número reduzido de' factores estimados. que são depois usados como regressores em VARs recursivos, para avaliar os efeitos da componente não sistemática das acções do BCE. Em termos gerais, os resultados do estudo sugerem que a inclusão de factores nos VAR permite obter uma visão rnais coerente dos efeitos dns inovações de política monetária, quer quer pela obtenção de respostas mais facilmente interpretáveis do ponto de vista teórico quer pelo aumento da precisão dessas rcspostas. Adicionalmente, na medida em que é incluído no modelo econométrico um conjunto muito amplo de variáveis, que o BCE à partida acompanha, a probabilidade de obter uma medida enviesada dos choques de política monetária diminui. Esta metodologia permite, também, calcular funções de resposta a impulso para todas as variáveis incluídas na amostra, fornecendo, deste modo, uma visão mais completa e precisa dos efeitos dos choques de política monetária. Contudo, a informação adicional gerada pelos FAVAR também revela algumas respostas inquietantes, em particular as das diferentes componentes da inflação.
N/A

Following the United Kingdom’s vote to leave the European Union, the outlook for growth in the short to medium term weakened markedly, leading the Bank of England’s MPC to introduce a package of measures, such as a cut of the Bank Rate, the expansion of APF, a CBPS and a new TFS, designed to provide additional support to growth and to achieve a sustainable return of inflation to the target of 2%. This Dissertation assesses the macroeconomic effects of some of the unconventional monetary policy measures employed by the MPC on output, inflation, long-term yields and equity prices, as well as on the transmissions channels activated. Therefore, we observe the results from the impulse response functions with an identification scheme, under a VAR model, which relies on monthly data, between August 2016 and January 2019. The results suggest the actual QE asset purchase programme led to a significant initial increase of long-term yields, depreciation of the exchange rate and a reduction of measures of financial market uncertainty. For the remaining variables, there is no evidence of significance response to QE. The estimates are, in general, similar to studies which employ the same identification scheme. However, their magnitude appears to be smaller when compared with impacts from early QE programmes in the UK, supporting the hypothesis that the impacts from asset purchases on the economy are getting smaller with the expansion of QE programmes.
No seguimento da votação do Reino Unido de sair da União Europeia, as perspetivas de crescimento de curto e médio prazo diminuíram significativamente, levando o MPC do Banco de Inglaterra a introduzir um pacote de medidas, incluindo a descida na taxa de juro, a expansão do APF, um CBPS e um novo TFS, destinadas a dar apoio adicional ao crescimento e conseguir um retorno da inflação à meta de 2%. Esta Dissertação avalia os efeitos macroeconómicos de algumas das medidas de política não convencionais implementadas pelo MPC sobre o produto, inflação, yields de longo prazo e nos preços das ações, assim como nos canais de transmissão ativados. Para tal, observamos os resultados das funções de resposta ao impulso utilizando um esquema de identificação através de um modelo VAR, com dados mensais, entre agosto de 2016 e janeiro de 2019. Os resultados sugerem que o programa de QE originou um aumento significativo inicial das yields de longo prazo, uma depreciação da taxa de câmbio, e uma redução das medidas de incerteza do mercado financeiro. Para as restantes variáveis, não há evidência de respostas significativas ao QE. As estimativas são, em geral, semelhantes a estudos que utilizam o mesmo esquema de identificação. Contudo, as magnitudes dos resultados aparentam ser menores quando comparadas com os impactos dos primeiros programas de QE no Reino Unido, validando a hipótese de que os impactos das compras de ativos na economia estão a ficar mais reduzidos à medida que os programas de QE se vão expandindo.

The contribution of this thesis is to build a small macro-econometric model of the Namibian economy, which demonstrates that there is significant statistical support for the hypothesis that there is a contemporaneous relationship between real wage, productivity, unemployment and interest rates in Namibia. This phenomenon has not yet been exploited using macro-econometric modelling, and thus, represents a significant contribution to modelling literature in Namibia. The determination of the sources of unemployment also receives special attention given that high unemployment is a chronic problem in Namibia. All models specified and estimated in the study use the SVAR methodology for the period 1980 to 2013. The study develops a small macro-econometric model using three modular experiments, which include, a basic model, models that separately append demand and exchange rate channels variables to the basic model, and the specification of a small macro-econometric model. The ultimate aim is to find out if monetary policy plays a role in influencing labour market and nominal variables. The hypothesis that the basic real wage, productivity, unemployment rate and interest rate system can be estimated simultaneously is validated. Further, demand and exchange rate channels variables are found to have important additional information, which explains the monetary transmission process, and that shocks to labour market variables affect monetary policy in Namibia. The results also show that the demand channel (import prices and bank credit to the private sector) and the exchange rate channel (nominal exchange rate) variables have important additional information, which affects monetary transmission process in Namibia, which justifies their inclusion in the small macro-econometric model. In addition, shocks to the import price and exchange rate in the macro-econometric model significantly affect labour market variables. However, shocks to bank credit only partially perform as expected, implying that its results need to be considered cautiously. The study further finds that tight monetary policy shocks significantly affect real and nominal variables in Namibia. The results also show that shocks to all variables in the unemployment model significantly affect unemployment, suggesting that the hysteresis assumption is corroborated. This implies that long run aggregate demand is non-neutral in Namibia.
Economics
D. Litt. et Phil. (Economics)

O objecto de estudo desta dissertação consiste na investigação dos impactos do Investimento Público e no sector da Construção na actividade económica. Nesta investigação tem-se como ponto de partida a análise dos planos estatais de estímulo à actividade económica lançados no âmbito da actual crise económica e financeira, maioritariamente compostos por Investimento em activos do sector da Construção, nomeadamente infra-estruturas. Para melhor compreender o contributo do Investimento Público e em Construção procedeu-se à análise da sua importância para uma progressão nos níveis de prosperidade económica e social, que estabeleceu uma visão ampla do seu papel nas economias desenvolvidas e em desenvolvimento. Uma vez que não são visíveis consensos entre os autores de referência em torno desta discussão, foi aplicada a metodologia de Vectores Auto-Regressivos (VAR), onde se decompõem e quantificam, com o recurso a uma base de dados com um horizonte temporal de 1960-2009, para Portugal e para uma amostra internacional de 12 países, as respostas do PIB e Investimento Privado a choques no Investimento Público e em Construção. Através destas torna-se possível a computação das elasticidades do PIB e Investimento Privado relativamente ao Investimento Público e em Construção, dos efeitos de crowding in ou crowding out e respectiva comparação com as conclusões dos demais autores. Assim, obtém-se que os Investimentos Público e em Construção produzem elasticidades positivas no PIB e Investimento Privado, predominando efeitos de crowding in. De forma complementar, foi realizada uma análise previsional do nível das séries para 2010, cujos resultados foram comparados com as estimativas da base de dados AMECO.
The subject of this dissertation is the research of impacts produced by Public Investment and Construction industry Investment in economic activity. In this investigation the starting point is an analysis of the public stimulus plans to economic activity, launched in concern of the current economic and financial crisis, mainly composed by investment in Construction industry assets, as infrastructures. To better understanding such Public and Construction industry Investment contributes, it was developed an analysis of its importance for progression in present economic and social prosperity levels, which established a broad vision of its role in developed and developing economies. Since there is no evident harmony between the main author´s involved this discussion, it was used the Vector Autoregression (VAR) method, where, using a database with a time horizon of 1960-2009 for Portugal and an international sample of 12 countries, the GDP and Private Investment responses to shocks in Public Investment and Construction Investment are decomposed and quantified. With these responses it is possible to compute the elasticities of GDP and Private Investment in relation to Public and Construction Investment, its crowding in or out effects and its comparison with the conclusions obtained by other authors. Therefore, it is concluded that the Public and Construction industry investment produces positive elasticities in GDP and Private Investment, prevailing crowding in effects. In a complementary point of view, it was made a series level forecast analysis for the year of 2010, whose results were compared with the AMECO database estimations.

A realização desta dissertação pretende adicionar um maior contributo ao estudo da política monetária estabelecida em Portugal pelo Banco Central Europeu (BCE). Este estuda um horizonte temporal do qual não se encontraram referências deste tipo, ou seja, de 1996 até 2014. O interesse deste projeto é especialmente relevante no que respeita à aplicação ao caso português, sobre o qual existem ainda poucas referências. A investigação encontra-se estruturada essencialmente em dois capítulos. O primeiro capítulo consiste numa abordagem teórica relativa à Teoria das Zonas Monetárias Ótimas e seguidamente à política monetária do BCE, elaborando um resumo sobre a sua estrutura, objetivos e funcionamento. Posteriormente apresenta-se o modelo econométrico dos vetores auto regressivos (VAR) para cada uma das economias, a de Portugal e a da Zona Euro, onde se pretende identificar se existe ou não correlação dos choques de oferta e procura, entre as mesmas. Assim, este exercício econométrico irá fornecer, desenvolvimentos simulados para as seguintes variáveis – o produto, a taxa de inflação e a taxa de juro Segundo os resultados obtidos nesta dissertação, pode-se apurar conclusões quanto às correlações das variáveis macroeconómicas, bem como para os impactos causados pelos choques nestas. Assim, é possível aferir que ambas as economias sofreram um aumento de correlação no Produto Interno Bruto (PIB) e na Inflação. Tal aumento foi demonstrado mais significativamente no último período analisado da amostra temporal (2006 – 2014), onde se verifica o coeficiente de correlação de 0.518 para o PIB e de 0.483 para a Inflação. No que reporta ao impacto dos choques, destacam-se os choques de procura onde o PIB e a inflação de Portugal e da Europa respondem de maneira semelhante. As diferenças foram apontadas relativamente ao impacto da taxa de juro e dos choques de oferta. O impacto da taxa de juro no PIB foi mais forte em Portugal. Relativamente à inflação, foi negativo na Europa e significativo e para Portugal foi positivo mas não significativo. Por fim, o impacto dos choques de oferta, no que se refere ao PIB, pode-se dizer que ambas as economias sofrem impactos diferentes mas ambos não significativos. Quanto à inflação, o impacto sofrido é positivo e significativo para os dois países, embora na Europa este seja bastante mais forte. Em especial, esta investigação demonstrou que, tendo em conta que Portugal sofreu diversas mutações na sua economia ao longo do tempo, nomeadamente a adesão ao euro, estas manifestaram-se numa maior integração da economia na zona euro e aumento da correlação dos choques de procura e oferta analisados para ambas as economias. Assim, a política monetária do BCE tem-se tornado mais adequada a Portugal.
The proposal of this dissertation is to give a contribute to the study of monetary politics implemented in Portugal by ECB. This dissertation analyses a temporal horizon that you can’t find references of this type, meaning, the 1996Q2 up to 2014Q4. This project interest is particularly relevant with regards to the Portuguese case, which still has little references. The investigation is structured mainly in two chapters. The first chapter consists in a theoretical approach to the Optimal Monetary Zones Theory and to the ECB monetary politic, through a summary of its structure, objectives and operating methods. After the summary it is presented the VAR econometric model for every economy, the Portuguese and the Euro Zone, in order to identify if there is a correlation between the supply and demand chocks. Therefore, this econometric exercise is going to supply, simulated developments for the following variables – the output, the inflation rate and the interest rate. This way, it is possible to verify that both economies suffered both a Gross Domestic Product (GDP) and Inflation correlation increase. Such increase was demonstrated with an higher significance in the last analysed period from the temporal sample (2006-2014), where is stated a correlation coefficient of 0.518 for the GDP and 0.483 for Inflation. Concerning the chock impact, the demand chock stands out, the Portuguese and European GDP and Inflation react in a similar way. The differences identified concern the interest rate impact and supply chock. The interest rate impact in the GDP was stronger in Portugal. Regarding the inflation it was negative and significant in Europe and positive but not significant in Portugal. Lastly, the supply chock impact regarding the GDP, shows that the economies suffer different impacts but both not significant. Concerning the inflation, the suffered impact is positive and significant for both economies, although in Europe it is much stronger. In particular, this investigation demonstrated that taking in to account that Portugal suffered several mutations in its economy during time, especially with joining euro, which resulted in a bigger integration of the economy in the euro zone and increase of the demand and supply chock correlation analysed for both economies. Therefore, the ECB monetary politics has become more suitable to Portugal.