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Este memorial investiga os processos composicionais de quatro peças compostas durante o curso de mestrado em composição na Universidade Federal do Rio Grande do Sul entre 2004 e 2005. São feitas considerações sobre as motivações estéticas e estruturais dessas peças, especialmente as relacionadas com o princípio oriental denominado jo-ha-kyu, o teatro nô japonês e a arte marcial japonesa iaijutsu. O princípio jo-ha-kyu, bem como sua manifestação no teatro nô e no iaijutsu, foi utilizado como impulso criativo e norma global para o seccionamento interno, o caráter e a ordem das peças para o recital de mestrado. Este trabalho também apresenta as conseqüências dessas motivações estéticas e estruturais para a coerência formal das peças.

Drawing on research and theory (discussed in Chapter 1) emphasising cognitive-ecological interaction and sampling processes in judgment (e.g., Fiedler, 2000), the present research investigated the role of social sampling (Galesic, Olsson & Reiskamp, 2012) in preferences for wealth redistribution. Two studies (Ch. 2) provide evidence that social sampling leads wealthier people to oppose redistributive policies. Wealthier participants reported higher levels of wealth in their social circles (Studies 1a and 1b) and, in turn, estimated wealthier population distributions, perceived the distribution as fairer and were more opposed to redistribution. Study 2 (Ch. 2), drawing data from a nationally representative survey, revealed that neighbourhood-level deprivation – an objective index of social circle wealth – mediated the relation between income and satisfaction with the economic status quo. In Studies 3a and 3b (Ch. 3), participants experimentally presented with a low (high) wealth income sample subsequently estimated poorer (wealthier) population distributions, demonstrating reliance upon the novel samples. The effect of the manipulation on redistributive preferences was sequentially mediated via estimated population distributions and fairness, such that participants shown a high wealth sample estimated less unequal (3a) or wealthier (3b) distributions, perceived the distribution as fairer and were more opposed to redistribution. Studies 4a and 4b (Ch. 4) tested whether warning against social sampling, providing an alternative sample or both interventions together might serve to reduce social sampling. Whereas providing an alternative sample alone was sufficient to eliminate social sampling (4a and 4b), providing a warning had no effect (4a), and providing both an alternative sample and a warning lead to an increase in social sampling (4a and 4b). Taken together, the findings suggest that a) social sampling produces systematic differences in wealthier and poorer peoples’ perceptions of the income distribution, b) social sampling contributes to divergence in the economic preferences of wealthy and poor and c) social sampling is likely immune to deliberate control efforts.

Este memorial investiga os processos composicionais de quatro peças compostas durante o curso de mestrado em composição na Universidade Federal do Rio Grande do Sul entre 2004 e 2005. São feitas considerações sobre as motivações estéticas e estruturais dessas peças, especialmente as relacionadas com o princípio oriental denominado jo-ha-kyu, o teatro nô japonês e a arte marcial japonesa iaijutsu. O princípio jo-ha-kyu, bem como sua manifestação no teatro nô e no iaijutsu, foi utilizado como impulso criativo e norma global para o seccionamento interno, o caráter e a ordem das peças para o recital de mestrado. Este trabalho também apresenta as conseqüências dessas motivações estéticas e estruturais para a coerência formal das peças.

Understanding the ways in which practitioners can identify and manage undernutrition is important within developing world countries. There is still much uncertainty when it comes to understanding which measures of undernutrition are the most effective predictors of adverse outcomes. This thesis explores how children grow and applies statistical methodology to three longitudinal growth datasets with frequent measurements in the first two years, seeking new insights into how measures of undernutrition can be used to predict future adverse outcomes. The three datasets are diverse - from Malawi, South Africa and Pakistan, the latter of which contains 4 subsets of different socioeconomic groups. The large number of children within the sets made it possible to test several different hypotheses. Growth charts (or reference charts) are charts which allow practitioners to compare a given infant’s anthropometric measurements with a reference population. We developed growth charts from the available datasets using Generalised Additive Models for Location Scale and Shape (GAMLSS), a method which allows users to flexibly model distributions of measurements over time. The reference charts we developed describe the growth of samples of children, many of whom will not have grown at a healthy rate. It is preferable to compare children with healthy infants from a composite external standard. The World Health Organization (WHO) growth standard was developed from a variety of populations from across the globe which describes the growth of a ‘healthy’ population. This suggests an aspirational model, as opposed to a reference, which describes how a sample of children actually grow. In this thesis GAMLSS was used to determine whether real populations of pre-school children from the developing world fit this international standard. We found that relatively affluent populations fit the standard well, or even outperform it, while more deprived populations fall away to varying degrees, then mainly track parallel to the WHO mean beyond 6 months. This suggests that after the first 6 months children from the developing world have rates of weight gain roughly on par with the standard, although the children are much lighter. Plotting measurements on growth charts identifies those whose weight Z score or centile is falling relative to the reference. However, children initially at the extremes tend to regress toward the mean. Conditional weight gain (CWG) takes this expected movement into account, but can only be used within the population in which the child originates, due to certain statistical assumptions. We developed a generalised measure of CWG for use with the WHO external standard. This measure requires the correlation between pairs of groups of measurements at different time points, as the amount of regression to the mean is synonymous with this correlation. If data are not available at these time points, they can be interpolated by firstly computing correlations between all available data, then modelling the resulting matrix. We found that these correlation matrices are heterogeneous within the developing world. Therefore, constructing a generalised correlation model was not possible. This makes the use of the new generalised measure of CWG impractical without access to correlation models computed from local data. However, the measure may be useful within the developed world, where correlation matrices may be less variable. The analysis then explored the ways that children move between different nutritional states, defined as healthy, thin (wasted) and/or short (stunted), over 3-6 month (m), 6-9m and 9-12m timeframes, and the probability these states will lead to death. We used stochastic models to explore the probability of moving state conditional on previous state, exploring the pathways children take through different states over time. Within all timeframes, children who were wasted as well as stunted were more likely to die than wasted children, who were in turn more likely to die than stunted children. Furthermore, as children age, the conditional risk of death in the next time period decreases. However, relative to healthy children, all children were less vulnerable within the middle period (6-9m) regardless of state. Children who were wasted were at significantly higher risk than healthy children of later wasting, or becoming stunted as well as wasted, over all timeframes. However, wasting alone significantly increased the risk of later stunting only in the 3-6m timeframe. Across the 3-6-9m timeframes children were much more likely to move from either healthy to healthy to stunted, or healthy to stunted to stunted, than from healthy to wasted to stunted. This indicates children are more likely to move directly into a stunted state than from healthy to stunted via wasted. Change in weight (growth) has been shown to be a predictor of mortality in populations of children, but it is not clear if this measure is more predictive than the latest weight (size). Using weighted Cox proportional hazards models, we determined which of these measures is the most valuable predictor of mortality for the majority of children within each individual dataset, conducting analyses using variable levels of weightings for children at the extremes. We included weight-for-age and height-for-age as predictors within our models to determine what combination of predictors best predict mortality. In all unweighted analyses, size was the best predictor of time until death. However, as the weighting increased, growth entered as the best predictor in populations with low rates of undernutrition. In contrast, size always remained the strongest predictor within populations with high rates of undernutrition, since in these populations, such a high proportion of children fall away from within the centre of the normal range, making growth pattern non-discriminating. This programme of work applied statistical techniques to three diverse longitudinal datasets, gaining insights into how children grow between different socio-economic backgrounds. We investigated measures of size and measures of growth, utilising methods that control for the inevitable fact that healthy children at the centre of the population distribution tend to dominate analyses. Furthermore, these methods were both multidimensional and time dependant, providing us with a useful framework to assess child growth while controlling for influential factors. The results should improve understanding of both the aetiology of undernutrition and its clinical management.

Este memorial investiga os processos composicionais de quatro peças compostas durante o curso de mestrado em composição na Universidade Federal do Rio Grande do Sul entre 2004 e 2005. São feitas considerações sobre as motivações estéticas e estruturais dessas peças, especialmente as relacionadas com o princípio oriental denominado jo-ha-kyu, o teatro nô japonês e a arte marcial japonesa iaijutsu. O princípio jo-ha-kyu, bem como sua manifestação no teatro nô e no iaijutsu, foi utilizado como impulso criativo e norma global para o seccionamento interno, o caráter e a ordem das peças para o recital de mestrado. Este trabalho também apresenta as conseqüências dessas motivações estéticas e estruturais para a coerência formal das peças.

Many exchange rate papers articulate the view that instabilities constitute a major impediment to exchange rate predictability. In this thesis we implement Bayesian and other techniques to account for such instabilities, and examine some of the main obstacles to exchange rate models' predictive ability. We first consider in Chapter 2 a time-varying parameter model in which fluctuations in exchange rates are related to short-term nominal interest rates ensuing from monetary policy rules, such as Taylor rules. Unlike the existing exchange rate studies, the parameters of our Taylor rules are allowed to change over time, in light of the widespread evidence of shifts in fundamentals - for example in the aftermath of the Global Financial Crisis. Focusing on quarterly data frequency from the crisis, we detect forecast improvements upon a random walk (RW) benchmark for at least half, and for as many as seven out of 10, of the currencies considered. Results are stronger when we allow the time-varying parameters of the Taylor rules to differ between countries. In Chapter 3 we look closely at the role of time-variation in parameters and other sources of uncertainty in hindering exchange rate models' predictive power. We apply a Bayesian setup that incorporates the notion that the relevant set of exchange rate determinants and their corresponding coefficients, change over time. Using statistical and economic measures of performance, we first find that predictive models which allow for sudden, rather than smooth, changes in the coefficients yield significant forecast improvements and economic gains at horizons beyond 1-month. At shorter horizons, however, our methods fail to forecast better than the RW. And we identify uncertainty in coefficients' estimation and uncertainty about the precise degree of coefficients variability to incorporate in the models, as the main factors obstructing predictive ability. Chapter 4 focus on the problem of the time-varying predictive ability of economic fundamentals for exchange rates. It uses bootstrap-based methods to uncover the time-specific conditioning information for predicting fluctuations in exchange rates. Employing several metrics for statistical and economic evaluation of forecasting performance, we find that our approach based on pre-selecting and validating fundamentals across bootstrap replications generates more accurate forecasts than the RW. The approach, known as bumping, robustly reveals parsimonious models with out-of-sample predictive power at 1-month horizon; and outperforms alternative methods, including Bayesian, bagging, and standard forecast combinations. Chapter 5 exploits the predictive content of daily commodity prices for monthly commodity-currency exchange rates. It builds on the idea that the effect of daily commodity price fluctuations on commodity currencies is short-lived, and therefore harder to pin down at low frequencies. Using MIxed DAta Sampling (MIDAS) models, and Bayesian estimation methods to account for time-variation in predictive ability, the chapter demonstrates the usefulness of suitably exploiting such short-lived effects in improving exchange rate forecasts. It further shows that the usual low-frequency predictors, such as money supplies and interest rates differentials, typically receive little support from the data at monthly frequency, whereas MIDAS models featuring daily commodity prices are highly likely. The chapter also introduces the random walk Metropolis-Hastings technique as a new tool to estimate MIDAS regressions.

The resource based view of firms suggests that they should invest into intangible assets such as absorptive capacity, R&D, networks, human capital and internationalisation. In particular, SMEs require more investment in knowledge based assets (e.g., R&D, networks) for higher labour productivity growth. The aim of this study is to identify and analyse the drivers of firm growth and their impact on firm labour productivity growth. Previous studies were limited in scope in terms of analysis (i.e., at firm level) of the software industry. For data collection, owner-managers of software firms were face-to-face interviewed using a structured questionnaire. The data were collected from two regions of Pakistan, Islamabad and Rawalpindi. Information was gathered on variables such as firm size, age, firm innovation activities, business and management factors, exporting, inward/outward FDI and so forth. Prior estimation factor analysis is used to extract core information from Likert scale variables. Lastly, stepwise multiple regression analysis is used to examine the relationship between drivers of firm growth and labour productivity growth. The regression analysis examined firm size, access to finance, internationalisation (exporting and outward FDI), business improvement methods and knowledge management have a positive impact on firm labour productivity growth. In comparison, R&D, absorptive capacity, shortage of skills generally have negative relationship to firm labour productivity growth. In summary, empirical findings emphasise the importance of knowledge based assets for higher firm labour productivity growth as a low level of R&D, lack of access to finance, poor absorptive capacity, high sunk costs (non recoverable) and skills shortage reduced the labour productivity growth of software firms.

This PhD thesis contains three main chapters on macro finance, with a focus on the term structure of interest rates and the applications of state-of-the-art Bayesian econometrics. Except for Chapter 1 and Chapter 5, which set out the general introduction and conclusion, each of the chapters can be considered as a standalone piece of work. In Chapter 2, we model and predict the term structure of US interest rates in a data rich environment. We allow the model dimension and parameters to change over time, accounting for model uncertainty and sudden structural changes. The proposed timevarying parameter Nelson-Siegel Dynamic Model Averaging (DMA) predicts yields better than standard benchmarks. DMA performs better since it incorporates more macro-finance information during recessions. The proposed method allows us to estimate plausible realtime term premia, whose countercyclicality weakened during the financial crisis. Chapter 3 investigates global term structure dynamics using a Bayesian hierarchical factor model augmented with macroeconomic fundamentals. More than half of the variation in the bond yields of seven advanced economies is due to global co-movement. Our results suggest that global inflation is the most important factor among global macro fundamentals. Non-fundamental factors are essential in driving global co-movements, and are closely related to sentiment and economic uncertainty. Lastly, we analyze asymmetric spillovers in global bond markets connected to diverging monetary policies. Chapter 4 proposes a no-arbitrage framework of term structure modeling with learning and model uncertainty. The representative agent considers parameter instability, as well as the uncertainty in learning speed and model restrictions. The empirical evidence shows that apart from observational variance, parameter instability is the dominant source of predictive variance when compared with uncertainty in learning speed or model restrictions. When accounting for ambiguity aversion, the out-of-sample predictability of excess returns implied by the learning model can be translated into significant and consistent economic gains over the Expectations Hypothesis benchmark.

This thesis considers how refugee-led community organisations generate social capital for their service users. The concept of social capital has become popular in policy debates in recent years, and previous research has attributed social capital creation for their service users to refugee community organisations (RCOs). This research aimed to analyse the process by which social capital is created by refugee community organisations, and what this means for the members of these organisations in terms of resources. The potential of the current political and economic climate to affect individual asylum-seekers and refugees, and refugee community organisations is considered, with particular emphasis on the funding situation for RCOs. Data was collected via an eight-month case study with an RCO for ethnic-Albanians in London. Interviews and focus groups with staff, volunteers and service users were held. To further understand the broader context in which RCOs are operating, interviews were also held with professionals that work with refugee community organisations, either as representatives of funding bodies, or as capacity-builders. A questionnaire survey of refugee community organisations with income over a certain threshold in London was also carried out in order to further contextualise the findings from the case study. Data from the researcher’s observation journal, the interviews and focus groups was analysed using software Nvivo 8 software. Woolcock’s work on social capital was used in combination with Rex’s typology of immigrant association functions. It was found that in the case study there was strong evidence of bonding and linking social capital. These social capital connections enabled service users to access a wide range of resources. There was less clear evidence of bridging social capital creation. Data from interviews with professionals and the survey revealed that other RCOs work, or at least, aspire to work, in the same way as the case study RCO to create social capital for their service users. The case study also revealed that working in partnership with specialist agencies was key to the success of the RCO, a finding that was also supported by the other data. Finally, the research found that funding uncertainty is an ongoing difficulty for many RCOs.