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1. Ojo, A., Vickers, D. and Ballas, D. (2013): Creating a Small Scale Area Classification for Understanding the Economic, Social and Housing Characteristics of Small Geographical Areas in the Philippines, Regional Science Policy and Practice, 5(1), 1-24. [article].
The Philippines is one of the most populous countries in the world. In terms of population, it ranks twelfth globally and seventh in Asia behind China, India, Indonesia, Pakistan, Bangladesh and Japan. The estimated population of the country in 2010 was 94 million people. Using data from the Philippines 2000 Census, this paper presents a discussion of the creation of a 3-tier hierarchical geodemographic system for the country at Barangay scale. Barangays are the smallest spatial entities in the structure of the administrative geography of the country. Most popular geodemographic systems are typically developed from continuous datasets. In this paper, we discuss how a geodemographic classification system can be created by combining categorical and continuous datasets. The first level of the Philippines geodemographic hierarchy ensures the population can be profiled broadly at Barangay level into seven super-groups. The super-groups are further subdivided into 24 groups and finally into 66 subgroups.
The significance of microfinance in driving important aspects of the Nigerian Vision 20-2020 and other national policy programs like the Millennium Development Goals (MDGs) cannot be over-emphasized. The Vision 20-2020 seeks to position Nigeria in the league of world's top 20 economies by the year 2020. The alleviation of poverty remains pivotal if this dream is to be achieved. Microfinance is therefore considered a veritable tool for mitigating the problems of poverty particularly amongst the rural poor, for stimulating economic growth, supporting human development and empowering women. NIGECS is used to illustrate the extent to which spatial analysis and geodemographic modeling may be of benefit for expounding real issues affecting the citizenry at localized spatial scales. Such benefit can complement the efforts of local and international stakeholders within the Nigerian microfinance footprint, in their endeavours to address a variety of issues associated with financial equity, access, demand and supply. The analysis yields the following results: The current footprint of microfinance banks is below target levels. Reaching targets would require roughly doubling the geographic footprint of these banks by 2015; Microfinance banks are currently disproportionately represented in urban areas, especially affluent urban areas; Similarly, the location of the poorest and poor households is negatively associated with the supply of microfinance services; Microfinance banks are most likely to reach poor populations by concentrating in the North-East of the country or on rural areas; There is a strong positive relationship between formal employment in the private sector and microfinance supply. Overall, we can see that there is ground to cover to meet goals for financial inclusion and that using geodemographic data can help to monitor and target expansion to meet development goals.
3. Ojo, A. and Ezepue, P. O. (2012): Modeling and Visualising the Geodemography of Poverty and Wealth across Nigerian Local Government Areas, The Social Sciences, 7(1), 145-158. [article].
Numerous researchers, commentators and policy makers have described poverty and inequality as the greatest challenges facing the Nigerian populace. Successive governments have pursued different policy initiatives with a view to mitigating the problem. In spite of large scale investment committed to poverty alleviation programmes, >50% of Nigerians still live in relative poverty with over a third of the population languishing in extreme poverty. To date, there is no published work examining the scale of inequality in poverty and prosperity amongst Nigerians at local spatial scales. In this study, we demonstrate the first attempt to exemplify the potential of geodemographics and spatial analysis in exposing poverty and wealth differences within and between Nigerian Local Government Areas (LGAs). We use a recently developed Nigerian LGA geodemograpic system to analyse data for five poverty quintiles. We discover that different local community types would be better suited to different initiatives as the magnitudes and direction of their predisposition for poverty and wealth vary. The findings reinforce the view that there is value in using geodemographic modeling techniques to better target local populations and to support poverty alleviation programmes in developing countries.
4. Ojo, A., Vickers, D., Ballas, D. (2012): The Segmentation of Local Government Areas: Creating a New Geography of Nigeria, Applied Spatial Analysis and Policy.5(1), 25-49. [article].
Social area classifications group areas on the basis of social or socio-economic similarity into cluster units which define their demographic and social characteristics. The methods used to create these systems combine geographic thought and theory with statistical manipulations of multivariate data. The development and use of geodemographic systems appear to be restricted within developing countries. Some commentators suggest that area classifications may not offer benefits to these countries. This paper argues that the developing world has a lot to benefit from this type of geography. It presents the case of Nigeria where a classification system has been developed for the 774 Local Government Areas (LGA) of the country. Insight is provided into the variables and methodological approach that has been used to create the Nigerian system.
5. Ojo, A. and Ezepue, P. O. (2011): How Developing Countries Can Derive Value from the Principles and Practice of Geodemographics, and Provide Fresh Solutions to Millennium Development Challenges, Journal of Geography and Regional Planning, 4(9), 505-512. [article].
Geodemographic segmentation systems are area classifications that use multi-criteria and geo-statistical analytics to group places and people into clusters of similarity. The benefits of these geocomputation techniques have been largely embraced by countries in the developed world where the origins of geodemographics lie. In spite of identified value of segmentation techniques for driving efficacy in policy making in developed societies, numerous developing countries still lack these systems. At the very basic level, some of the reasons for this paucity may appear obvious; however some more pertinent issues like the misunderstanding of the significance of data infrastructure has often been overlooked. In this paper, we provide some background on the antecedents of geodemographics and focus on the challenges and benefits of spatial segmentation as an option for driving evidence-based policy making within developing countries.
6. Abbas, J., Ojo, A. and Orange, S. (2009): Geodemographics – A Tool for Health Intelligence?, Public Health, 123(1), 35-39. [article].
In recent years, social marketing principles and techniques have featured at the heart of government proposals for improving health and tackling health inequalities. This, in part, has led to a shift in the type of information and intelligence needed to support service planning at all levels. In particular, there has been increasing interest in the use of commercial geodemographic classification systems. Despite the amount of activity and associated investment in this area, there is evidence of a real lack of understanding among users about the tools themselves, and the added value they are providing in the National Health Service. This paper describes some of the potential applications of geodemographic tools in the health sector, and explores issues for consideration when selecting or using a system. This paper also describes a potentially cost-effective and sustainable model for utilizing geodemographic tools as part of a regional insight function within the health service.