Testing local versions of correlation coefficients

The aim of this paper is to define and test local versions of standard correlation coefficients in statistical analysis. This research is motivated by the increasing number of applications using local versions of exploratory and explanatory spatial data analysis methods. A common example of the latter is local regression. Methods such as the Geographically Weighted Regression argue that it is necessary to check spatial non-stationarity in the relationships between a geographic phenomenon and its determinants. This is because the response to a stimulus could vary across space. For example the relationship between education level and unemployment could vary across the EU regions. Local regression claims to account for local relationships that may be hidden or missed when a global regression is applied. However, the statistical inference in local regression methods is still an open field for basic research. In this paper a local version of Pearson correlation coefficient is defined and tested in spatial data. By doing this a simple tool for statistical inference is provided assisting a more careful interpretation of the results of a local regression model. Furthermore, this could be a technique for testing the existence of local correlation among two variables representing spatial data in the absence of a global correlation and vice versa. The application of this technique includes pairs of usually correlated variables, such as income and high levels of education as well as not correlated variables

Spatial Trends of unpaid caregiving in Ireland

elderly population, mean that the number and proportion of people in need of assistance with everyday activities is expected to increase considerably in coming decades. Nowadays, most of this assistance is provided by voluntary caregivers, predominantly close relatives. There is an increasing need for statutory authorities to work with and support these caregivers. In fact, caregivers support not only elderly people but also those with a long-term illness, health problem or disability, regardless of age. The number of elderly people is predicted to increase dramatically in the future due to population ageing. Ireland has a relatively younger population compared to other western European countries due to high birth rates (CSO, 2004). However, it is important to raise these issues (of population ageing) and plan for those days when an aged society will be a fact. We believe that there is a strong geographical element in the study of voluntary care giving. In this paper we examine the spatial distribution of unpaid care providers, the disabled and the elderly people. We aim to identify areas of high and low probability of provision of voluntary (domestic) care to the people in need. We build on past experience (Young et al., 2005; Foley, 2007) and we attempt to conduct a more advanced geographical analysis on a finer geographical scale

The statistical analysis and modelling of internal migration flows within England and Wales

Migration flows in recent decades suggest that Britain is a nation of people on the move. The combination of information technology and structured data collection allow today a very close and detailed examination of trends in internal migration in England and Wales. However, there has been a relative dearth in the analysis of migration data using quantitative techniques. In this thesis I attempt to analyse migration patterns and to model migration moves in order to explain the main factors affecting individuals' migration decisions. I try to link this work to existing research in this research field by revising and applying recently developed quantitative methods. My main aim in this thesis is to provide empirical evidence that the effects of many socio-economic factors on individuals' migration decisions are non-stationary across space. More specifically, there are four sections of data analysis in this thesis: the exploration of migration flows using data visualization and local statistics; the analysis of the effects of socio-economic factors on out-migration rates; the analysis of the attraction of migrants from areas with varying socio-economic profiles via the construction of global and local models; and the examination of model residuals. The main objectives of this work are twofold: the first is to provide a thorough investigation of internal migration using a rich dataset on annual migration during the 1980s and the 1990s; the second is to remove the inaccuracy traditional global models introduce by assuming that the processes being examined are stationary over space. I do this through the use of newly developed local statistical methods. Former attempts made to provide local forms of statistical analysis have limitations. Geographically Weighted Regression is used in this thesis to allow for local modelling. This method provides not only a technique for best model fit but also for the evaluation of the results using modem goodness of fit statistics such as the Akaike Information Criterion. The temporal dimension of my data allows the examination of the stability in migration flows over time. It also provides a means of checking the consistency of the significance of the spatial variation of local parameter estimates derived from each annual set of migration data. The migration data themselves are disaggregated in 14 sex/age groups.The age disaggregation reflects the stage of life individuals are at (e.g . people forming a family are young adults aged 25 - 29 years old). In order to facilitate the examination of migratory moves over time, I introduce a new way of visualising in-, out- and net migration rates, the heat map. The results for the migration models show that the parameter estimates of some of the migration deterininants exhibit significant spatial variation. This suggests that the effect of some determinants on migration decisions in both origin and destination of a migratory move vary across space. The spatial patterns of the local parameter estimates usually show a North-South or a Northwest - Southeast divide. When out-migration models are concerned, there is strong evidence for a spatially variable effect of employment rate for all migrant groups and percentage non-white population along with percentage long-distance commuters for mature male adults. When destination choice models are concerned, there is strong evidence for a spatially variable effect of destination accessibility, house prices, listed buildings, vacant and derelict dwellings, distance and total population. These new findings on local migration modelling are of high interest and potential benefit to policy makers. The spatial and temporal migration trends confirm the continuation of the counterurbanisation phenomenon in England and Wales. The local out-migration models suggest the effect of some ecological conditions on out-migration is associated with the location of the origin. The local destination choice models suggest that there are differences on what determines short migration moves and longer moves. They also suggest that the behaviour of those leaving an area is not stationary for all England and Wales. Finally, similarly to out-migration, there are instances where the effect of some ecological conditions on destination choice is associated with the location of the destination. This thesis also presents an attempt for constructing more robust migration models, signalling the need for additional migration determinants.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Assessing spatial variation and heterogeneity of fertility in Greece at local authority level

In the absence of spatial fertility analysis for Greece this paper aims at assessing spatial variations and underlying relationships between fertility and selected socio-demographic indicators at local authority level. The analysis is based on the 2001 census data for the 325 local authorities of the country. The results reveal the presence of significant spatial autocorrelation and the existence of spatial heterogeneity of structural interrelationship between fertility and predictors. The application of local models out-performs the standard OLS approach. However, the relationship between socioeconomic indicators and fertility is not always clear and further investigation is needed

Assessing spatial variation and heterogeneity of fertility in Greece at local authority level

In the absence of spatial fertility analysis for Greece this paper aims at assessing spatial variations and underlying relationships between fertility and selected socio-demographic indicators at local authority level. The analysis is based on the 2001 census data for the 325 local authorities of the country. The results reveal the presence of significant spatial autocorrelation and the existence of spatial heterogeneity of structural interrelationship between fertility and predictors. The application of local models out-performs the standard OLS approach. However, the relationship between socioeconomic indicators and fertility is not always clear and further investigation is needed

Rencontres entre parents âgés et enfants: quelles différences en Europe? : Les exemples de la Finlande, de la France et de l’Italie

Peer reviewe

Contacts between elderly parents and their children in four European countries : current patterns and future prospects

Peer reviewe

Spatial Analysis of internal migration in Luxembourg

The aims of this paper are to look at the spatial patterns and to model internal migration in Luxembourg. Between 2010 and 2011, 17344 people or 3.7% of the total population moved from one municipality (commune) to another within Luxembourg, showing a very dynamic migratory system. Luxembourg City is a net migration looser in terms of internal migration: 3128 people moved out of Luxembourg and 1428 people moved in to the capital in the same period. This paper presents an innovative migration flow map while attempting to explain, for the first time in Luxembourg, the driving forces of migratory moves at a fine geographical scale, most of the literature being focussed on the strong international migration, thus hiding local residential processes. The data analysed refer to the migration flows between the 116 local authorities (communes) in Luxembourg and the 12-months migration question. We present models for out-migration, in-migration and migration flows. For the latter, we fit unconstrained gravity models using Poisson, and Negative Binomial (NB) regressions, and their Zero Inflated variants in order to account for overdispersion and the large number of zero flows. The empirical results are very interesting and show processes that differ from other countries. It appears that cultural and urban planning factors rather than labour force factors affect the decision to migrate within Luxembourg, which is plausible given the location, the size and the ethnic background of the population residing in Luxembourg

SpatialML, R package

info:eu-repo/semantics/publishe