This thesis presents an investigation into the population geography of Jewish residents of England and Wales in the twenty-first century. The aims of the study are to understand the spatial distribution of the group; identify whether there are distinct differences between groupings in different parts of the country; identify whether the demographics and nature of these groups is changing over time; and to examine whether the pattern for Jews is similar to those for other minority groups of comparable size. Most importantly, the thesis theorises what the patterns found may mean for the demographic future of Anglo-Jewry. The results provide a clearer foundation for organisations responsible for the social welfare of Jewish groups in various parts of the country. In addition, as Jews have been present in Britain in significant numbers for longer than other minority groups, it provides useful insights into future trajectories for more-recently arrived groups. Thus, the findings provide an improved basis for policy formulation by the public authorities with wider responsibilities for combating disadvantage and improving social cohesion. Building on an understanding of the history of Jewish settlement in Britain, and existing demographic studies, the analysis presented takes advantage of the inclusion of a question on religion in the 2001 and 2011 censuses. The principal data sources are census outputs, including Special Migration Statistics, individual microdata, and the Longitudinal Study. The analysis investigates the heterogeneity of the group through the development of a novel geodemographic classification methodology that addresses weaknesses in other approaches and the particular needs of small, unevenly distributed sub-populations. It finds evidence of seven distinct classes, with a strong spatial clustering to their distribution. The spatial distribution of Anglo-Jewry is examined in the context of other minority groups, including previously under-studied Arabs and Sikhs; that analysis finds a strong commonality to the pattern for Jews and some other small groups – their trajectories demonstrating a tension between the benefits of group congregation (apparently driven by religion, even in sub-populations defined by ethnic group) and a desire for suburbanisation. It also identifies the strong impact of geographic scale when drawing conclusions based on distribution indices. The underlying drivers of internal migration, an important contributor to changes in spatial distribution, are examined using logistic regression, having first legitimated the use of (post-move) census-derived characteristics in migration analysis. The assessment finds a broad consistency in underlying determinants of migration and, for the Jewish group, an absence of a group penalty inhibiting the propensity to move home, present for other small groups. The patterns of recent internal migration are analysed using spatial interaction modelling and multi-nominal logistic regression; longer term (1971 onwards) patterns are also examined. Based on these analyses, and allowing for potential future patterns of births and longevity, population trends found through an innovative application of the 2011-based geodemographic analysis to 2001 census data are extrapolated to produce estimates of the Jewish population of England and Wales for future decades. The novel approach used takes account of group heterogeneity and absence of group-specific fertility and mortality data. The projection demonstrates an increasing Jewish population, in contrast to the reduction seen during the second half of the twentieth century, but with a growing proportion being found in strictly orthodox enclaves, which gives rise to a number of societal and policy implications.

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Governments require information about population counts and characteristics in order to make plans, develop policies and provide public services. The main source of this information is the traditional population censuses. However, they are costly, and the information collected by the decennial censuses goes out-of-date easily. For this reason, this thesis has two main aims: to develop methodologies to combine administrative data sources to estimate population counts in the absence of both a traditional census, and to produce uncertainty estimates for the estimated population counts. Although, the methodologies are illustrated using administrative data sources from England and Wales, they can easily be applied to other countries' administrative data sources. The most comprehensive administrative sources in England and Wales are the NHS Patient Register and the Customer Information System. However, it is known that both of these sources exceed the census estimates. Therefore, it is crucial to use another source to adjust the bias to estimate population counts using these administrative sources. Three substantial chapters assessing methodologies to combine administrative sources with the auxiliary information are presented. The first of these chapters presents a basis methodology, log-linear models with offsets, which is extended in the following chapters. The second chapter extends these models by using individually linked administrative sources. The third chapter improves on the basis models to produce measures of uncertainty. This thesis evaluates different log-linear models in terms of their capacity for producing accurate population counts for age group, sex and local authority groups both within the classical and the Bayesian framework. On the other hand, it also presents a detailed perspective to understand which population groups tend to be missed by the administrative data in England and Wales, and how much they can be improved just by combining them with the specific association structures obtained from auxiliary data sources.

This thesis examines the patterns and determinants of the marriage postponement and fertility decline experienced by Iranian women during the last two decades of the twentieth century. The thesis accounts for temporal changes in the socio-economic context of marriage and childbearing (e.g. improvement in education, urbanisation, economic fluctuations, etc.) and examines the marriage timing and fertility patterns of the cohorts of women who contributed to the recent marriage and fertility changes in order to provide more insight into the demographic behaviour of women with specific life course experiences. A topic of specific interest is the variation between the ethnic groups in Iran. The findings suggest that the recent marriage postponement was related to improvements in women's education and restrictions in the availability of suitable spouses (marriage market), with the former being the only factor contributing to the marriage delay of consecutive (1971-75 and 1976-80) birth cohorts. The recent decline in the probability of second and third conceptions was related to improvements in women's educational level, reductions in child mortality, and improvements in children's enrolment in education. The contribution of son preference to the probability of conception of a second child and the specific impact of urbanisation and industrialisation on the recent marriage and fertility changes were also notable. Different socio-economic factors were found responsible for the decline in the probability of a second conception across consecutive cohorts. of women (those who became exposed to the risk of childbearing in 1986-90 and 1991-95), whereas cohort differences in the probability of a third conception was not generally related to socio-economic forces, probably reflecting a common preference for stopping at two children. The findings also highlight the role of cultural factors associated with ethnicity in shaping differential patterns of marriage timing and suggest that ethnic differences in fertility are strongly related to ethnic differences in socio-economic attributes.

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The collection of census data is an important task with respect to providing support for decision makers. However, the collection of census data is also resource intensive. This is especially the case in areas which feature poor communication and transport networks. In this thesis a number of methods are proposed for collecting census data by applying prediction techniques to relevant satellite imagery. The test site for the work is a collection of villages lying some 300km to the northwest of Addis Ababa in Ethiopia. The idea is to build a predictor that can label households according to “family” size. To this end training data has been obtained by collecting “on ground” census data and matching this up with satellite imagery. The fundamental idea is to segment satellite images so as to obtain satellite sub-images describing individual households and representing these segmentations using a number of proposed representations: graph-based, histogram based and texture based. By pairing each represented household with the collated census data, namely family size, a predictor can be constructed to predict household sizes according to the nature of each representation. The generated predictor can then be used to provide a quick and easy mechanism for the approximate collection of census data that does not require significant resource.

The mortality patterns of human populations reflect several inherent biological attributes and other external factors including social, medical and environmental conditions. Mathematical modelling, in addition to experiments and simulations, is an important tool for the analysis of those patterns. One of the main observed characteristics of mortality patterns in human populations is the age-specific increase in mortality rate after sexual maturity. This increase is predominantly exponential and satisfies the well-known Gompertz law of mortality. Although the exponential growth in mortality rate is observed over a wide range of ages, it excludes early- and late-life intervals. The heterogeneity of human populations is a common consideration in describing and validating their various age-related features. In this study we develop a mathematical model that combines (i) the assumption of heterogeneity within each human population, where different subpopulations are distinguished for their certain mortality dynamics and (ii) the assumption that the mortality of each constituent subpopulation increases exponentially with age (in the same way as described by the Gompertz law). The proposed model is used to fit available observational data in order to analyse the dynamics of mortality across the lifespan and the evolution of mortality patterns over time. We first explore the effects of the variation of the model parameters to the dynamics of mortality and use the model to fit actual age-specific mortality data. We show that the model successfully reproduces the entire age-dependent mortality patterns explaining the peculiarities of mortality at young and very old ages. In particular, we show that the mortality data on Swedish populations can be reproduced fairly well by a model comprising of four subpopulations. Besides the confirmation that heterogeneity can explain the irregularities of mortality patterns at young ages and the deceleration of mortality at extremely old ages, we analyse the influence of stochastic effects on mortality and we conclude that evident effects due to stochasticity are manifested at the age intervals (early and late life ages) where only few individuals contribute to mortality. We then analyse the evolution of mortality patterns over time by fitting the proposed model to (Swedish) mortality data of consecutive periods across the 20th century. The evolution of mortality is described in terms of the changes of model parameters estimated by fitting the model to data from different time periods. We show that the evolution of model parameters confirms the applicability of the compensation law of mortality to each constituent subpopulation separately. The compensation law states an inverse relationship between the scale and the shape parameter of Gompertz law. Our analysis also indicates a change in the structure of this population over time in a way that the population tends to become more homogeneous by the end of the 20th century. This change in structure is reflected in changes to the initial proportions of the constituent subpopulations. These two observations, namely the validity of the compensation effect and the homogenisation of the population, imply that the alteration of model parameters (which reflect demographic terms) can explain the decrease of the overall mortality over time. It is shown that the decrease in mortality across the 20th century is mainly due to changes in the structure of the population, and to a lesser extent, to a reduction in mortality for each of the subpopulations. The outcomes of our research show that the consideration of heterogeneity is efficient for the description of various features of a population’s mortality. The idea of “pure” subpopulations, such that in each of them exponential law is held for all ages, has been used as a convenient mathematical constraint which allows very accurate reproduction of the entire mortality patterns. This provides a justification for the deviation of mortality from its exponential increase at young and very-old ages and for the decrease of mortality over time. In the last part of this thesis we propose that the proposed heterogeneity is not only a convenient tool for fitting mortality data but indeed reflects the true heterogeneous structure of the population. Particularly we demonstrate that the model of a heterogeneous population fits mortality data better than most of the other commonly used models if the data are taken for the entire lifespan and better than all other models if we consider only old ages. Also, we show that the model can reproduce seemingly contradicting observations in late-life mortality dynamics like deceleration, levelling-off and mortality decline. Finally, assuming that the differences between subpopulations reflect genetic variations within the population and using the Swedish mortality data for the 20th century, we show that evolutionary processes resulting in changes of allele frequencies, can explain the homogenisation of the population as predicted by the model.

This century the population of Bangladesh will increase from 150m to 250m, with 70% of this growth concentrated in urban areas primarily due to rural-urban migration by the poor. The family planning programme aims to reduce fertility rates in Chittagong. The poor have the highest fertility rates in Chittagong. The aim of the study was to develop an explanation for why some couples within the urban poor of Chittagong have a low fertility outcome of ≤ 2 living children whilst other very similar couples have a high fertility outcome of ≥ 4 living children, in order to inform family planning programmatic interventions. A new small-N comparative approach, Counterfactual Mechanism Analysis, was developed for context-specific operationalisation of theorised causal chains leading to the fertility outcome and producing a causally symmetric explanation under a Ready, Willing and Able framework. The result from the small-N investigation suggests that some couples with low/high fertility outcomes formulate initial fertility preferences in response to the congruence of the husband's and wife's individual perceptions of social approval regarding the number and sex composition of children. Readiness to limit fertility can adjust dynamically for both husband and wife based on the importance of sex composition and whether it is being attained. For the wife, stillbirths and miscarriages can also adjust Readiness. The wife's Willingness to limit fertility and use modern family planning methods depends on the norm of her social network. The wife's Ability to acquire modern family planning methods depends on subjective cost. The relevancy of the explanation to similar couples within the population of interest is supported by patterns exhibited in secondary data. Interventions based on the current priorities of the family planning programme are considered unlikely to succeed in reducing the fertility outcomes of the urban poor in Chittagong.