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The paper derives monthly estimates of business sector output in the UK from rolling quarterly value-added tax based turnover data. The administrative nature of the value-added tax data implies that their use could ultimately yield a more precise and granular picture of output across the economy. However, they show two particular features which complicate their exploitation: they are overlapping and subject to substantial noise. This motivates our choice of a multivariate unobserved components model for filtering and disaggregating temporally the aggregate figures. After illustrating our method by using one industry as a case-study, we estimate monthly seasonally adjusted gross output figures for the 75 industries for which the data are available. Our results show material differences from the existing output profile.

This thesis explores new methods for producing economic statistics and their associated uncertainty. A particular focus is placed on techniques for studying conjointly heterogeneous economic series sampled on different frequencies and released asynchronously. Chapters 2 to 4 show how the British survey used to collect data on business turnover, a proxy for short-term GDP, may be replaced with value-added tax returns, which also contain information on business turnover. These chapters tackle a number of statistical issues related to temporal disaggregation, cleaning and forecasting using filtering techniques, specifically state space and score driven methods. There are three important takeaways from this work. First, an approximation to nonlinear temporal aggregation constraints which facilitates modelling and dissemination is illustrated. Second, it shows that a nonlinear approach for cleaning works better than the more-classical outlier detection strategy. Third, the resulting output estimates based on VAT returns exhibit a different profile than the survey currently in use. Tackling a different problem, Chapter 5 presents a new means for updating the uncertainty attached to US GDP nowcasts in a timely way by using prediction errors already observed in series related to economic growth. It shows how dependencies in the dispersion and asymmetry of prediction errors, which typically increase in the onsets of economic recessions, may be modelled across time series when these are not observed on the same frequency. The results show that this approach is particularly useful to capture the forecasting uncertainty observed during the onset of the coronavirus pandemic. While most of the thesis is concerned with economic growth statistics, Chapter 6 concludes with a study on migration statistics. Google queries on national newspapers are exploited to produce a timely indicator of migration flows using a novel quasi score driven model relying on a copula.

The financial crisis has led to a change in the mix of capital and labour employed in the UK and a sharp decline in total factor productivity. This has meant that labour productivity has not recovered to any great degree since the financial crisis. We explore the role of overall and sectoral productivity in explaining the fall in labour productivity, but also question the extent to which productivity in the service sector may be measured with error. We outline the links between a constrained financial sector and a fall in overall productivity – in which intangible capital seems to play an important role – and illustrate how a financial sector providing intermediate services may act to amplify the business cycle impetus from a total factor productivity shock within the context of a calibrated model.

This paper shows that modelling comovement in the asymmetry of the predictive distributions of GDP growth and a timely related series improves nowcasting uncertainty when it matters most : in times of severe economic downturn. Rather than using many predictors to nowcast GDP, I show that it is possible to extract more information than we currently do from series closely related to economic growth such as employment data. The proposed methodology relies on score driven techniques and provides an alternative approach for nowcasting besides dynamic factor models and MIDAS regression where dynamic asymmetry (or skewness) parameters have not yet been explored.

This paper shows that modelling comovement in the asymmetry of the predictive distributions of GDP growth and a timely related series improves nowcasting uncertainty when it matters most : in times of severe economic downturn. Rather than using many predictors to nowcast GDP, I show that it is possible to extract more information than we currently do from series closely related to economic growth such as employment data. The proposed methodology relies on score driven techniques and provides an alternative approach for nowcasting besides dynamic factor models and MIDAS regression where dynamic asymmetry (or skewness) parameters have not yet been explored.

This paper extends the temporal disaggregation approach of Labonne and Weale (2020) to tackle another feature of the VAT data: the delay and highly noisy nature of the early figures. The main contribution of this paper lies in the presentation and illustration of a cleaning method which can deal with non-Gaussian features in the distribution of measurement errors such as asymmetry and extreme observations.

• Distyly is an intriguing floral adaptation that increases pollen transfer precision and restricts inbreeding. It has been a model system in evolutionary biology since Darwin. Although the S-locus determines the long- and short-styled morphs, the genes were unknown in Turnera. We have now identified these genes. • We used deletion mapping to identify, and then sequence, BAC clones and genome scaffolds to construct S/s haplotypes. We investigated candidate gene expression, hemizygosity, and used mutants, to explore gene function. • The s-haplotype possessed 21 genes collinear with a region of chromosome 7 of grape. The S-haplotype possessed three additional genes and two inversions. TsSPH1 was expressed in filaments and anthers, TsYUC6 in anthers and TsBAHD in pistils. Long-homostyle mutants did not possess TsBAHD and a short-homostyle mutant did not express TsSPH1. • Three hemizygous genes appear to determine S-morph characteristics in T. subulata. Hemizygosity is common to all distylous species investigated, yet the genes differ. The pistil candidate gene, TsBAHD, differs from that of Primula, but both may inactivate brassinosteroids causing short styles. TsYUC6 is involved in auxin synthesis and likely determines pollen characteristics. TsSPH1 is likely involved in filament elongation. We propose an incompatibility mechanism involving TsYUC6 and TsBAHD.

The neural crest is a vertebrate-specific stem cell population that helped drive the origin and evolution of vertebrates. A distinguishing feature of these cells is their multi-germ layer potential, which has parallels to another stem cell population—pluripotent stem cells of the vertebrate blastula. Here, we investigate the evolutionary origins of neural crest potential by comparing neural crest and pluripotency gene regulatory networks of a jawed vertebrate, Xenopus , and a jawless vertebrate, lamprey. We reveal an ancient evolutionary origin of shared regulatory factors in these gene regulatory networks that dates to the last common ancestor of extant vertebrates. Focusing on the key pluripotency factor pou5, we show that a lamprey pou5 orthologue is expressed in animal pole cells but is absent from neural crest. Both lamprey and Xenopus pou5 promote neural crest formation, suggesting that pou5 activity was lost from the neural crest of jawless vertebrates or acquired along the jawed vertebrate stem. Finally, we provide evidence that pou5 acquired novel, neural crest-enhancing activity after evolving from an ancestral pou3-like clade. This work provides evidence that both the neural crest and blastula pluripotency networks arose at the base of the vertebrates and that this may be linked to functional evolution of pou5. Comparison of neural crest and pluripotency gene regulatory networks of Xenopus and lamprey reveals shared regulatory factors in the last common ancestor of extant vertebrates and suggests common molecular features of blastula and neural crest stem cells.

Our understanding of how microbiome signatures are modulated in wild fish populations remains poorly developed and has, until now, mostly been inferred from studies in commercial and farmed fish populations. Here, for the first time, we have studied changes in the skin and blood microbiomes of the Salmo trutta population of the volcanic Kerguelen archipelago located at the northern limit of the Antarctic Ocean. The Kerguelen Islands present a natural framework of population expansion and reveal a likely situation representing further climate change in distribution areas. Our results showed that S. trutta of the Kerguelen Islands has a microbiome signature distinct from those of salmonids of the Northern Hemisphere. Our study also revealed that the skin and blood microbiomes differ between sedentary and migratory S. trutta. While 18 phyla were shared between both groups of trout, independent of the compartment, 6 phyla were unique to migratory trout. Further analyses showed that microbiome signatures undergo significant site-specific variations that correlate, in some cases, with the peculiarity of specific ecosystems. Our study also revealed the presence of potential pathogens at particular sites and the impact of abiotic factors on the microbiome, most notably due to the volcanic nature of the environment. This study contributes to a better understanding of the factors that modulate the microbiome signatures of migratory and sedentary fish populations. It will also help to better monitor the impacts of climate change on the colonization process in the sub-Antarctic region.

Small populations establishing on colonization fronts have to adapt to novel environments with limited genetic variation. The pace at which they can adapt, and the influence of genetic variation on their success, are key questions for understanding intraspecific diversity. To investigate these topics, we performed a reciprocal transplant experiment between two recently founded populations of brown trout in the sub-Antarctic Kerguelen Islands. Using individual tagging and genetic assignment methods, we tracked the fitness of local and foreign individuals, as well as the fitness of their offspring over two generations. In both populations, although not to the same extent, gene flow occurred between local and foreign gene pools. In both cases, however, we failed to detect obvious footprints of local adaptation (which should limit gene flow) and only weak support for genetic rescue (which should enhance gene flow). In the population where gene flow from foreign individuals was low, no clear differences were observed between the fitness of local, foreign, and F1 hybrid individuals. In the population where gene flow was high, foreign individuals were successful due to high mating success rather than high survival, and F1 hybrids had the same fitness as pure local offspring. These results suggest the importance of considering sexual selection, rather than just local adaptation and genetic rescue, when evaluating the determinants of success in small and recently founded populations.