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The primate hand, a biomechanical structure with over twenty kinematic degrees of freedom, has an elaborate anatomical architecture. Although the hand requires complex, coordinated neural control, it endows its owner with an astonishing range of dexterous finger movements. Despite a century of research, however, the neural mechanisms that enable finger and grasping movements in primates are largely unknown. In this thesis, we investigate statistical models of finger movement that can provide insights into the mechanics of the hand, and that can have applications in neural-motor prostheses, enabling people with limb loss to regain natural function of the hands. There are many challenges associated with (1) the understanding and modeling of the kinematics of fingers, and (2) the mapping of intracortical neural recordings into motor commands that can be used to control a Brain-Machine Interface. These challenges include: potential nonlinearities; confounded sources of variation in experimental datasets; and dealing with high degrees of kinematic freedom. In this work we analyze kinematic and neural datasets from repeated-trial experiments of hand motion, with the following contributions: We identified static, nonlinear, low-dimensional representations of grasping finger motion, with accompanying evidence that these nonlinear representations are better than linear representations at predicting the type of object being grasped over the course of a reach-to-grasp movement. In addition, we show evidence of better encoding of these nonlinear (versus linear) representations in the firing of some neurons collected from the primary motor cortex of rhesus monkeys. A functional alignment of grasping trajectories, based on total kinetic energy, as a strategy to account for temporal variation and to exploit a repeated-trial experiment structure. An interpretable model for extracting dynamic synergies of finger motion, based on Gaussian Processes, that decomposes and reduces the dimensionality of variance in the dataset. We derive efficient algorithms for parameter estimation, show accurate reconstruction of grasping trajectories, and illustrate the interpretation of the model parameters. Sound evidence of single-neuron decoding of interpretable grasping events, plus insights about the amount of grasping information extractable from just a single neuron. The Laplace Gaussian Filter (LGF), a deterministic approximation to the posterior mean that is more accurate than Monte Carlo approximations for the same computational cost, and that in an off-line decoding task is more accurate than the standard Population Vector Algorithm.

This paper examines return co-movements and volatility spillovers between major exchange rates before and after the introduction of euro. Dynamic correlations and VAR-based spillover index results suggest significant return co-movements and volatility spillovers, however, their extend is, on average, lower in the post-euro period. Co-movements and spillovers are positively associated with extreme episodes and US dollar appreciations. The euro (Deutsche mark) is the dominant net transmitter of volatility, while the British pound the dominant net receiver of volatility in both periods. Nevertheless, cross-market volatility spillovers are bidirectional, and the highest spillovers occur between European markets. (author's abstract)

Essa pesquisa busca investigar a influência de diferentes níveis de fatores na variância da maturidade do endividamento corporativo na América Latina. Ao todo, foram levantados cinco diferentes grupos (divididos em três níveis de influência) de variáveis que potencialmente determinam a maturidade do endividamento das empresas dos países estudados ao longo do período de 1996 a 2009. Foi utilizado o modelo linear hierárquico, que possibilita o aninhamento de variáveis em diferentes níveis – em que os níveis superiores influenciam os níveis inferiores. Ao longo do estudo, procedeu-se à análise fatorial com o objetivo de extrair fatores representativos do nível de desenvolvimento financeiro e da qualidade das instituições de Argentina, Brasil, Chile, Colômbia, México, Peru, Venezuela e Estados Unidos (países componentes da amostra). Os resultados sugerem que as variações ao longo do tempo e as variações entre as empresas são as maiores fontes de modificações na maturidade do endividamento. Além disso, o tamanho, a liquidez, a taxa real de juros e o nível de desenvolvimento financeiro do país se sobressaem como fatores que impactam de forma significativa a maturidade do endividamento corporativo. Finalmente, os fatores extraídos e a taxa real de juros impactaram indiretamente na maturidade do endividamento através de outras variáveis, a saber: oportunidades de crescimento, tamanho e liquidez. / This research investigates the influence of distinct factor´s levels in corporate debt maturity in Latin America. Five different variables groups (divided into three influence levels) that potentially determine the corporate debt maturity in the countries studied were collected over the period 1996 to 2009. We used Hierarchical Linear Modeling, which allows nesting of variables at different levels – in which the higher levels may influence the lower levels. Throughout the study, we proceeded to factor analysis in order to extract financial development and institutional quality factors in Argentina, Brazil, Chile, Colombia, Mexico, Peru, Venezuela and the United States (countries belonging to the sample). The results suggest that variations over time and variations between firms are the major sources of changes in corporate debt maturity. Moreover, size, liquidity, the real interest rate and the financial development stand out as factors that impact significantly the corporate debt maturity. Finally, the extracted factors and the real interest rate indirectly impacted the corporate debt maturity by others variables, namely: growth opportunities, size and liquidity.

Essa pesquisa busca investigar a influência de diferentes níveis de fatores na variância da maturidade do endividamento corporativo na América Latina. Ao todo, foram levantados cinco diferentes grupos (divididos em três níveis de influência) de variáveis que potencialmente determinam a maturidade do endividamento das empresas dos países estudados ao longo do período de 1996 a 2009. Foi utilizado o modelo linear hierárquico, que possibilita o aninhamento de variáveis em diferentes níveis – em que os níveis superiores influenciam os níveis inferiores. Ao longo do estudo, procedeu-se à análise fatorial com o objetivo de extrair fatores representativos do nível de desenvolvimento financeiro e da qualidade das instituições de Argentina, Brasil, Chile, Colômbia, México, Peru, Venezuela e Estados Unidos (países componentes da amostra). Os resultados sugerem que as variações ao longo do tempo e as variações entre as empresas são as maiores fontes de modificações na maturidade do endividamento. Além disso, o tamanho, a liquidez, a taxa real de juros e o nível de desenvolvimento financeiro do país se sobressaem como fatores que impactam de forma significativa a maturidade do endividamento corporativo. Finalmente, os fatores extraídos e a taxa real de juros impactaram indiretamente na maturidade do endividamento através de outras variáveis, a saber: oportunidades de crescimento, tamanho e liquidez. / This research investigates the influence of distinct factor´s levels in corporate debt maturity in Latin America. Five different variables groups (divided into three influence levels) that potentially determine the corporate debt maturity in the countries studied were collected over the period 1996 to 2009. We used Hierarchical Linear Modeling, which allows nesting of variables at different levels – in which the higher levels may influence the lower levels. Throughout the study, we proceeded to factor analysis in order to extract financial development and institutional quality factors in Argentina, Brazil, Chile, Colombia, Mexico, Peru, Venezuela and the United States (countries belonging to the sample). The results suggest that variations over time and variations between firms are the major sources of changes in corporate debt maturity. Moreover, size, liquidity, the real interest rate and the financial development stand out as factors that impact significantly the corporate debt maturity. Finally, the extracted factors and the real interest rate indirectly impacted the corporate debt maturity by others variables, namely: growth opportunities, size and liquidity.

Submitted by Haroudo Xavier Filho (haroudo.xavierfo@ufpe.br) on 2016-07-01T12:40:07Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Tese_RonyMelo_Versao_BC_2.pdf: 1810035 bytes, checksum: 3c75da73e467a1195a630f09d398de6a (MD5) / Made available in DSpace on 2016-07-01T12:40:07Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Tese_RonyMelo_Versao_BC_2.pdf: 1810035 bytes, checksum: 3c75da73e467a1195a630f09d398de6a (MD5) Previous issue date: 2015-09-18 / Anp/prh-28 / O aprimoramento de tecnologias que possam tornar o processo produtivo mais amigável a sociedade e ao meio ambiente é uma busca constante das grandes indústrias, seja por questões mercadológicas, seja por obrigações legais. A indústria do refino de petróleo, pela própria natureza composicional de sua matéria prima principal, produz efluentes com os mais diferentes riscos, os quais necessitam ser eliminados ou reduzidos a níveis aceitáveis. Inserido dentro deste contexto surge à unidade de abatimentos de emissões atmosféricas SNOX®, cujos objetivos visam o tratamento de efluentes e produção de H2SO4 agregando assim valor comercial ao processo, contudo esses mesmos efluentes conferem a possibilidade de sofrer diversos processos corrosivos e que pode acarretar vazamentos de seus gases, os quais são, em sua maioria, nocivos. O presente trabalho teve como objetivos a elaboração de uma simulação em modo estacionário, do processo SNOX® utilizando o software Hysys® a fim de calcular as concentrações dos diversos gases circulantes, e avaliar, de forma probabilística, a dispersão atmosférica (através do modelo SLAB) desses gases devido à presença de incertezas em diversas variáveis. Para a avaliação probabilística foi utilizada técnicas de Quasi-Monte Carlo (Latin Hypercube) para: definição das incertezas relevantes e hierarquização destas através de análise de sensibilidade por decomposição de variâncias; cálculo do tamanho ideal das amostras que representarão as incertezas, considerando um intervalo de confiança de 90%; e exibição dos resultados na forma de famílias de curvas de distribuição de probabilidade para obtenção probabilidades de certos efeitos adversos referentes aos gases presentes no processo SNOX®. Os resultados mostraram que, considerando as condições operacionais da unidade e o tipo de consequência abordado (intoxicação por gases): coeficiente de descarga, vazão de descarga, velocidade (intensidade) dos ventos e diâmetro do orifício são as variáveis que possuem relevância e as incertezas associadas a esses resultados se propagam até as concentrações finais obtidas pelo modelo SLAB, fazendo com que sua melhor representação seja na forma de curvas de distribuição de probabilidades cumulativas. / The improvement of technologies which can implement greater eco-socialfriendly production processes are a goal for the major industries, either by marketing issues or legal restrictions. The oil industry, by its compositional nature of its feedstock, produces effluents with several hazards which must be eliminated or reduced to acceptable levels. In this context, the SNOX® unit rises as answer to the reduction of the atmospheric emissions, aiming the effluent treatment and H2SO4 production, which increases the commercial value to the process, notwithstanding the fact of these emissions enable corrosive process that may lead to leakage of gases, which are usually harmful. The current work has as main objectives the development of a simulation at stationary-state of the SNOX® process by using the HYSYS® software in order calculate the concentration of released gases and probabilistically evaluate the atmospheric dispersion of these gases employing SLAB method. The Quasi-Monte Carlo (Latin Hypercube) was used for probabilistic estimation for: defining the relevant uncertainties as well its hierarchization through sensibility analysis by variance decomposition; calculation of the ideal size for the samples which will represent the uncertainty with a reliability of 90%; and finally for displaying the results as groups of probability distribution curves to obtain the probability of some adverse effects associated with the gases at the process. The results evidenced that considering the operational conditions and the studied kind of consequences (gas intoxication): discharge coefficient, discharge flow rate, wind velocity (intensity of the wind) and the diameter of the orifice were the variables of relevance and the associated uncertainties of the results propagate to the final concentrations obtained by the SLAB model. Hence the results must be suitably represented by cumulative probability distribution curves.

We develop a new autoregressive conditional process to capture both the changes and the persistency of the intraday seasonal (U-shape) pattern of volatility in essay 1. Unlike other procedures, this approach allows for the intraday volatility pattern to change over time without the filtering process injecting a spurious pattern of noise into the filtered series. We show that prior deterministic filtering procedures are special cases of the autoregressive conditional filtering process presented here. Lagrange multiplier tests prove that the stochastic seasonal variance component is statistically significant. Specification tests using the correlogram and cross-spectral analyses prove the reliability of the autoregressive conditional filtering process. In essay 2 we develop a new methodology to decompose return variance in order to examine the informativeness embedded in the return series. The variance is decomposed into the information arrival component and the noise factor component. This decomposition methodology differs from previous studies in that both the informational variance and the noise variance are time-varying. Furthermore, the covariance of the informational component and the noisy component is no longer restricted to be zero. The resultant measure of price informativeness is defined as the informational variance divided by the total variance of the returns. The noisy rational expectations model predicts that uninformed traders react to price changes more than informed traders, since uninformed traders cannot distinguish between price changes caused by information arrivals and price changes caused by noise. This hypothesis is tested in essay 3 using intraday data with the intraday seasonal volatility component removed, as based on the procedure in the first essay. The resultant seasonally adjusted variance series is decomposed into components caused by unexpected information arrivals and by noise in order to examine informativeness.

This dissertation includes three chapters. The first chapter studies the impact of financial shocks and financial frictions on business cycle dynamics in China's economy. The second and third chapters focus on the driving force of structural change and its impact on aggregate fluctuations using an input-output network approach. In the second chapter, I study two questions: (i) How has the U.S. production network structure changed from 1970 to 2017? (ii) What impact does that have on aggregate fluctuations? This paper shows that a few industries, like Finance and Insurance and Professional Services, have become much more central input suppliers over time, while others, like Paper Manufacturing, have become far less important. Therefore, the third chapter considers the driving force behind such structural change. In particular, I study the question of what determines the size of an industry in a production network. China has been one of the world's fastest-growing economies over the past several decades and emerged quickly from the global financial crisis of 2008. Chapter 1, titled DO FINANCIAL SHOCKS DRIVE REAL BUSINESS FLUCTUATIONS IN CHINA, investigates to what extent financial shocks can shape business cycle fluctuations in China. Specifically, I document the cyclical properties of China's macroeconomy and financial market and show the procyclicality of dividend payout and the countercyclicality of debt repurchases with real GDP. To account for these features, I use the real business cycle model incorporating debt and equity financing developed by Jermann and Quadrini (2012) to study how the dynamics of macroeconomic and financial variables are affected by financial shocks in China. This paper finds that financial shocks contribute significantly to business cycle fluctuations in China and can account for over 60% of the variations in the growth rate of output, investment, hours worked, and debt repurchases. Hulton's Theorem states that the impact of an industry-specific shock on the aggregate economy is entirely captured by the size of this industry, regardless of its position in the production network. Chapter 2, titled THE IMPORTANCE OF INPUT-OUTPUT NETWORK STRUCTURE IN THE US ECONOMY, proposes the idea that the network structure in isolation plays an essential role in shaping GDP growth and growth volatility. First, I introduce a new measure of network structure named centrality dispersion and document that the U.S. production network has become sparsely connected from 1970 to 2017, where many industries relied on a few central input suppliers for production. Such changes are associated with slower GDP growth and higher volatility. To account for this evidence, I embed input-output linkages into a multisector real business cycle model and provide a nonlinear characterization of the impact of network structure quantified using centrality dispersion on the macroeconomy. Finally, I study model-implied relationships between production network structure, GDP growth, and growth volatility. The calibrated model accounts for approximately one-quarter of the variation in real GDP growth and 40% of GDP volatility, as observed in the data. Chapter 3, titled THE NETWORK ORIGIN OF INDUSTRY SIZE VARIATIONS, quantifies the origin of industry size variations using the features of a production network. In the analysis, I perform an exact variance decomposition of industry total sales into the supplier, buyer, and final demand components. The findings suggest that matching with many buyers in the network, especially many large buyers is essential in understanding industry size variations. More importantly, these buyer characteristics have become increasingly important in contributing to industry size variations over the 1967-2012 period. Finally, I provide new empirical evidence related to the decomposition results. The evidence reveals a strengthening negative correlation between industry size and the concentration of customer networks in the long run. / Economics

In this master thesis, the impact of forward-looking macroeconomic information under IFRS 9 is studied using fictional data from a Swedish mortgage loan portfolio. The study employs a time series analysis approach and employs vector autoregression models to model expected credit loss parameters with multiple incorporated macroeconomic parameters. The models are analyzed using impulse response functions to study the impact of macroeconomic shocks and the results show that the unemployment rate, USD/SEK exchange rate and 3-month interest rates have a significant impact on expected credit losses. / I detta examensarbete studeras effekterna av framåtblickande makroekonomisk information enligt IFRS 9 med fiktiv data baserad på en svensk bolåneportfölj. Studien använder sig av tidsserieanalys och vektorautoregressionsmodeller för att modellera förväntade kreditförlust-parametrar med flera inkorporerade makroekonomiska parametrar. Modellerna analyseras med hjälp av impulsresponsfunktioner för att studera effekterna av makroekonomiska chocker. Resultaten visar att arbetslöshet, USD/SEK växelkurs och 3-månaders räntor har en signifikant inverkan på förväntade kreditförluster.

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