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.

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.

Despite numerous Government efforts to tackle the problem of child under-nutrition in Malawi, the levels of child under-nutrition remain high with stunting estimated at 47% and underweight at 12.7% . This thesis investigates whether the levels and patterns of stunting and underweight in Malawi have changed between the years 2000 and 2010 and if so how. It studies how feeding patterns and child immunisation affects child’s nutritional status in Malawi and analyses the different pathways through which household and community level socio-economic factors affect a child’s nutritional status in Malawi. The Malawi Demographic and Health Survey (MDHS) data sets of 2000, 2004 and 2010 are used in the study of levels and patterns of child under-nutrition in Malawi whilst the 2004 MDHS is used to investigate how feeding patterns and child immunisation affect a child’s nutritionals status in Malawi. The 2004 Malawi Integrated Household Survey data is merged with the 2004 Community level to analyse the pathways through which household and community level socio-economic factors affect child nutritional status in Malawi. Results of this study show that children from communities that have a daily market are less likely to be stunted compared to children from communities without a daily market. Children from communities that trace their descendants through their father have a lower likelihood of stunting compared to children from communities that trace their descendants through the mother due to being of relatively higher economic status. The levels of stunting and underweight have gone down significantly from 54.1% and 21.4% respectively in the year 2000 to 47.1% and 12.7% respectively in 2010. However, the percentage of children that are stunted but not affected with other under-nutrition problems has hardly changed, estimated at 37.2% in 2000 and 36.2% in 2010. Although generally female children are less likely to be stunted and less likely to be underweight, female children are more likely to be underweight as they get older. Contrary to what one would expect, children are more likely to be stunted during harvest time compared to the hunger season. Most of the children are fed food from the local grain, whilst in fact children aged between 7 to 36 months who consume food from animal sources are less likely to be undernourished. Children whose mothers are in possession of a child health card1 are less likely to be underweight. The Malawi Government should therefore intensify its efforts of encouraging mothers to attend under-five clinics, feed children that are undergoing weaning food from animal sources and should invest more in programmes that boost socio-economic status such as education and entrepreneurship skills.

A methodology is developed to estimate comparable international migration flows between a set of countries. International migration flow data may be missing, reported by the sending country, reported by the receiving country or reported by both the sending and receiving countries. For the last situation, reported counts rarely match due to differences in defnitions and data collection systems. In this thesis, reported counts are harmonized using correction factors estimated from a constrained optimization procedure. Factors are applied to scale data known to be of a reliable standard, creating an incomplete migration flow table of harmonized values. Cells for which no reliable reported flows exist are then estimated from a negative binomial regression model fitted using the Expectation- Maximization (EM) type algorithm. Covariate information for this model is drawn from international migration theory. Finally, measures of precision for all missing cell estimates are derived using the Supplemented EM algorithm. Recent data on international migration between countries in Europe are used to illustrate the methodology. The results represent a complete table of comparable ows that can be used by regional policy makers and social scientist alike to better understand population behaviour and change.

The main focus of this PhD project is the development and validation of a psychometric instrument for the measurement of individual dispositions towards rules and principles. Literature review and focus groups were used to generate insights into the reasons why individuals prefer rules and principles. On the basis of that review, an initial item pool was created covering the conceptual space of dispositions towards rules and principles. The final instrument consists of 10 items, 5 items each for the rules and principles subscales. The psychometric analysis suggested that it is valid and reliable. The instrument has sound predictive power and was able to significantly predict individuals’ behavioral intentions in relation to rules and principles across contexts. I found there were gender and ethnic differences in the relationship between dispositions towards rules and principles scores and behavioural intentions. This PhD is relevant to an emerging literature in behavioural accounting research that examines how practitioners’ personal characteristics and styles affect financial reporting practice.

This thesis aims to examine a number of issues related to exchange rate movements at different time horizons: long-run, in terms of investigating equilibrium real exchange rates; medium-run, in terms of investigating predictability of exchange rates in out-of-sample forecasting contexts; and short-run, in terms of studying high-frequency exchange rate dynamics in the actual foreign exchange trading. Specifically, we reassess four topics concerning exchange rate movements through macroeconomic fundamental analysis and microstructure approaches to exchange rates. With macro approaches, our study demonstrates, in a panel data setting, the link between real exchange rates and net foreign asset could be through the association between real exchange rates and trade balance. The panel study indicates the heterogeneity, in terms of the association between real exchange rates and trade balance, between the OECD economies and less mature economies. Our study on the monetary exchange rate model indicates the monetary model can describe the long-run behaviour of nominal exchange rates. Furthermore, we find the short-term exchange rate deviation adjustments to equilibrium and nonlinearities involved in the association between exchange rates and monetary fundamentals. With micro approaches, our study demonstrates, in short run, order flow has a significant impact on the contemporaneous exchange rate dynamics. However, we observe the prediction of order flow on the future exchange rate is quite weak. Our study also finds the weak interaction between macro news and private information in the exchange rate volatility study.

This thesis has two main themes: (1) values shift versus cultural particularity and (2) values and democracy. The Postmaterialist thesis and related theories of values shift presented by Ronald Inglehart and others assume that, as a consequence of industrialisation and post-industrialisation, people's values transform in such a way as to increase an emphasis on self-esteem, self-expression and other qualities. Individuals become increasingly capable, autonomous and inclined to public demands, which can be conducive to liberal democratic outcomes. In relation to these, the present study suggests that cultural particularity should be taken into consideration as a factor competing with that of values shift in terms of influence on people's attitudinal conditions. For individualism is often quoted as a core element of Western civilisation, which is not necessarily so in other cultural scenarios. With this enquiry, the study mainly concentrates on the analysis of the World Values Survey. Postmaterialist indexes are closely investigated by comparing the USA, Britain, Russia and Japan. The examination further incorporates broader regions: Western, Postcommunist and East Asian regions. The results indicate a certain validity in the cultural effect. This is especially the case with a Postmaterialist values item on 'freedom of speech', which contrasts with other Postmaterialist item: 'giving people more say in important government decisions'. Their implications for democracy are subsequently considered. These non-Western societies appear to exhibit certain weaknesses in the Postmaterialist transformation and its attitudinal efficacy for polyarchy-like democracy. The attention turns to gaps in perceptions of freedom between the USA, Russia and Japan, which could be applied to the trilateral regions. This national difference also seems to be present in the area of protest, notwithstanding the fact that there are some indications of values shift. Culture seems to matter on popular outlooks vis-à-vis the Postmaterialist effects. Multivariate analysis on this aspect endorses the same conclusion. The outcomes imply variation between the citizens of these societies in ways that they relate to government. The nations are compared with respect to the influences of liberal democratic attitudes on moderate protest and views of governance. After all, American (and probably British) individuals seem to be more compatible with public demands and participatory democracy than those in Russia and Japan. Western cultural emphasis on the particular quality of freedom could be favourable to Postmaterialist values as well as individual attitudes that call for responsive and accountable democracy.