Dimitris Ballas

Happy people or happy places? a multilevel modeling approach to the analysis of happiness and well-being

This article aims to add a regional science perspective and a geographical dimension to our understanding of substantive questions regarding self-reported happiness and well-being through the specification and use of multilevel models. Multilevel models are used with data from the British Household Panel Survey and the Census of UK population to assess the nature and extent of variations in happiness and well-being to determine the relative importance of the area (district, region), household, and individual characteristics on these outcomes. Having taken into account the characteristics at these different levels, we are able to determine whether any areas are associated with especially positive or negative feelings of happiness and well-being. Whilst we find that most of the variation in happiness and well-being is attributable to the individual level, some variation in these measures is also found at the household and area levels, especially for the measure of well-being, before we control for the full set of individual, household, and area characteristics. However, once we control for these characteristics, the variation in happiness and well-being is not found to be statistically significant between areas.

GIS and microsimulation for local labour market analysis

This paper outlines the findings of ongoing research on ways of employing and combining geographical information systems (GIS) and microsimulation methodologies for the evaluation and analysis of local labour market problems and policies. First, it is shown how data sets from different sources are integrated to create an urban labour market GIS. In the context of this information system, ways of mapping thematically the local labour market demand and supply are presented. In addition, travel-to-work flows are mapped and it is demonstrated how this data can be used to build local labour market Spatial Interaction Models. Further, it is shown how GIS can be combined with microsimulation techniques to highlight urban problems and enhance the analysis and evaluation of potential social and employment policies. In particular, it is shown how GIS and microsimulation can be used as tools in order to analyse a regions economy and labour market and to estimate the degree of labour market segmentation and socio-economic dualism within an urban system. Also, it is outlined how what-if spatial policy analysis of local labour markets can be performed (i.e. simulating new policy initiatives, firm closures, changes in benefit policies and performing regional multiplier analysis). Finally, the paper presents outputs from SimLeeds, which is a spatial microsimulation model for the Leeds labour market, and explores the potential of GIS combined with microsimulation modelling to create a new framework for the formulation, analysis and evaluation of socio-economic policies at the individual or household level.

Using geographical information systems and spatial microsimulation for the analysis of health inequalities.

The paper presents a spatial microsimulation approach to the analysis of health inequalities. A dynamic spatial microsimulation model of Britain, under development at the Universities of Leeds and Sheffield, uses data from the censuses of 1971, 1981 and 1991 and the British Household Panel Survey to simulate urban and regional populations in Britain. Geographical information systems and spatial microsimulation are used for the analysis of health inequalities in British regions in a 30 year simulation. The interdependencies between socio-economic characteristics and health variables such as limiting long-term illness are discussed. One of the innovative features of the model is the estimation of variables such as household income at the small area level, which can then be used to classify individuals. The health situation of different simulated individuals in different areas is investigated and the role of socio-economic characteristics in determining health is evaluated.

Combining microsimulation and spatial interaction models for retail location analysis

Although the disaggregation of consumers is crucial in understanding the fragmented markets that are dominant in many developed countries, it is not always straightforward to carry out such disaggregation within conventional retail modelling frameworks due to the limitations of data. In particular, consumer grouping based on sampled data is not assured to link with the other statistics that are vital in estimating sampling biases and missing variables in the sampling survey. To overcome this difficulty, we propose a useful combination of spatial interaction modelling and microsimulation approaches for the reliable estimation of retail interactions based on a sample survey of consumer behaviour being linked with other areal statistics. We demonstrate this approach by building an operational retail interaction model to estimate expenditure flows from households to retail stores in a local city in Japan, Kusatsu City.

‘Truncate, replicate, sample’: A method for creating integer weights for spatial microsimulation

Abstract Iterative proportional fitting (IPF) is a widely used method for spatial microsimulation. The technique results in non-integer weights for individual rows of data. This is problematic for certain applications and has led many researchers to favour combinatorial optimisation approaches such as simulated annealing. An alternative to this is ‘integerisation’ of IPF weights: the translation of the continuous weight variable into a discrete number of unique or ‘cloned’ individuals. We describe four existing methods of integerisation and present a new one. Our method – ‘truncate, replicate, sample’ (TRS) – recognises that IPF weights consist of both ‘replication weights’ and ‘conventional weights’, the effects of which need to be separated. The procedure consists of three steps: (1) separate replication and conventional weights by truncation; (2) replication of individuals with positive integer weights; and (3) probabilistic sampling. The results, which are reproducible using supplementary code and data published alongside this paper, show that TRS is fast, and more accurate than alternative approaches to integerisation.

Building a Spatial Microsimulation-Based Planning Support System for Local Policy Making:

This paper presents a spatial microsimulation modelling and predictive policy analysis system called Micro-MaPPAS, a Planning Support System (PSS) constructed for a local strategic partnership in a large metropolitan area of the UK. The innovative feature of this system is the use of spatial microsimulation techniques for the enhancement of local policy decision making in connection with the neighbourhood renewal strategy. The paper addresses the relevant data issues and technical aspects of the linkage of spatial microsimulation modelling frameworks to PSS and deals with the wider implications that such a linkage may have to local policy and planning procedures. Finally, the paper presents some illustrative examples of the policy relevance and policy analysis potential of the software.

Spatial microsimulation for rural policy analysis

The aim of this book is to explore the challenges facing rural communities and economies and to demonstrate the potential of spatial microsimulation for policy and analysis in a rural context. This is done by providing a comprehensive overview of a particular spatial microsimulation model called SMILE (Simulation Model of the Irish Local Economy). The model has been developed over a ten year period for applied policy analyis in Ireland which is seen as an ideal study area given its large percentage of population living in rural areas. The book reviews the policy context and the state of the art in spatial microsimulation against which SMILE was developed, describes in detail its model design and calibration, and presents example of outputs showing what new information the model provides using a spatial matching process. The second part of the book explores a series of rural issues or problems, including the impacts of new or changing government or EU policies, and examines the contribution that spatial microsimulation can provide in each area.

A Spatial Microsimulation Model for Social Policy Evaluation

Evaluation is a critical step in the analysis of social policies which, itself, can influence public thinking (Unrau, 1993; Manski and Garfinkel, 1992). Policy-relevant spatial modelling is an expanding area of research, which has a lot of potential for the evaluation of the socio-economic and spatial effects of major national social policy programmes. However, traditional modelling approaches to social policy analysis usually focus on the impact on the socio-economic structure of the population and they have tended to ignore the geographical dimensions of social policies. In particular, the focus has usually been on the redistributive effects of government policies (such as budget changes and social security benefit policies etc.) between households, but there has generally been a paucity of studies that investigate the spatial impacts of these policies.

Analysing the regional geography of poverty, austerity and inequality in Europe: a human cartographic perspective

ABSTRACT Analysing the regional geography of poverty, austerity and inequality in Europe: a human cartographic perspective. Regional Studies. This paper presents a human cartographic approach to the analysis of the impact of austerity and the economic crisis across Europe’s regions. It reflects on past insights and debates on the analysis and mapping of poverty and wealth, and of the effects of austerity in particular. It then presents a wide range of cartograms highlighting social and spatial inequalities across Europe. Finally, the paper highlights the increasingly important role of the field of regional studies in current debates about the future of the European project and of the possibility of a Europe of regions rather than a Europe of nation-states.

Mortality inequalities: Scotland versus England and Wales

This paper is an observational study of particular historical trends in mortality inequality within Great Britain, comparing England and Wales with Scotland for the period 1925-2005. The inequalities in mortality within Great Britain have become more apparent over time. Growing inequality in premature mortality in Britain affected young Scottish men most severely after 1995. It would appear that something dramatic happened to the Scottish population in early 1970s which accelerated these broad and very important mortality differentials within Great Britain. The divergence in mortality within Great Britain is notable in successive male cohorts and to a lesser extent in women.