Quality of Life spatial statistical modelling
Since 2009, the Gauteng City-Region Observatory has bi-annually conducted Quality of Life (QoL) surveys. The four surveys (2009, 2011, 2013 and 2015) present fascinating snapshots of the quality of life, socio-economic circumstances, attitudes to service delivery and other characteristics of the Gauteng City-Region (GCR). The fourth survey interviewed over 30 000 respondents and is possibly one of the largest surveys of social attitudes undertaken in Gauteng. The data are geocoded at the point of interview, with ward-level representative data available for all the municipalities. The availability of individual geocoded interviews presents an opportunity for a detailed analysis at a fine-scale that is spatially-based. The GIS software utilised by GCRO, Esri Arcmap 10.3, contains a spatial statistics toolbox for analysing spatial distributions, patterns, processes, and relationships. According to Esri’s help file: “While there may be similarities between spatial and non-spatial (traditional) statistics in terms of concepts and objectives, spatial statistics are unique in that they were developed specifically for use with geographic data. Unlike traditional non-spatial statistical methods, they incorporate space (proximity, area, connectivity, and/or other spatial relationships) directly into their mathematics.”
This project explores the use of spatial statistical tools to analyse the QoL survey data. It explores the following questions: Why is there a disjuncture between the relatively high satisfaction to government-provided services and dissatisfaction with government performance? What factors may explain the pattern and the level of dissatisfaction with government performance? Is there a spatial pattern to the dissatisfaction with government performance? Is there a spatial pattern to the significant factors that explain dissatisfaction with government performance?
It employs several spatial (multivariate) statistical techniques and GIS mapping in the analysis. It is envisaged that GIS mapping will identify hot spots and trends in the data, and in so doing, assist both provincial and local government with a spatial picture of the current issues facing the Gauteng-City Region based on a spatial statistical analysis of the QoL survey data, allowing for more spatially-targeted interventions by government.
Cheruiyot, K., Wray, C. & Katumba, S. (2015), ‘Satisfaction with local government performance’, Map of the month, April.
Cheruiyot, K. (2015). ‘Presentation and discussion on GCRO’s preliminary spatial statistical analysis of satisfaction with government’, City GCR Seminar, organised by the Gauteng City-Region Observatory (GCRO), at UJ on 6 March 2015.
Cheruiyot, K. (2015). ‘Spatial Statistical Analysis of Dissatisfaction with the Performance of Local Government in the Gauteng City-Region, South Africa’, presented at the 2nd International Conference on Applied Methods in Social Sciences: People, Goods and Regions in a Globalized World, in Poznan, Poland on 22-23 May 2015.
Wray, C. (2015). ‘Spatial Statistical Analysis of Dissatisfaction with the Performance of Local Government in the Gauteng City-Region, South Africa’, presented at the Geomatics Indaba 2015 Conference, in Kempton Park, South Africa on 11-13 August 2015.
Cheruiyot, K., Wray, C. & Katumba, S. (2015) (forthcoming), ‘Spatial Statistical Analysis of Dissatisfaction with the Performance of Local Government in the Gauteng City-Region, South Africa’ South African Journal of Geomatics, 4 (3), pp. 224 - 239.