Abstract
Ph.D. (Economics)
In this thesis the primary research objective is to construct quality of life measures to measure and compare the quality of life across the Gauteng City-Region in South Africa, while considering the diversity of the population residing in the region. In addressing the primary research question we also investigate secondary research objectives, namely to validate a new instrument of quality of life, to determine the interrelationships between the dimensions of quality of life, to construct a composite index with fixed weighting to measure and compare the quality of life across different demographic and socio-economic groups, to measure and compare the quality of life within diverse municipalities, each with its own unique character, and to analyse the factors that influence the wellbeing of a unique group of people in Gauteng, namely refugees and asylum seekers.
A validated measuring instrument of quality of life contributes to the construction of robust composite indices, which can give a good estimate of quality of life in a region. Furthermore, identifying the interrelationships between the dimensions of quality of life can assist in the formulation of integrated policies aimed at improving quality of life. The measurement and comparison of quality of life of different socio-economic groups and different municipal regions can contribute to identifying the groups and municipal areas with low levels of quality of life, as well as the dimensions of quality of life that are below average and should be attended to in order to increase quality of life in the region. Lastly, determining the factors that influence the wellbeing of urban refugees and asylum seekers can contribute to better understanding of this unique group of people.
To address the primary and the secondary research aims various novel methodologies are utilised. The methodologies used include Confirmatory Factor Analysis (CFA) to validate an instrument of quality of life and determine the interrelationships between the quality of life dimensions; Nicoletti et al.’s method based on Principal Component Analysis (PCA) to build a fixed weighted composite index of quality of life; Data Envelopment Analysis (DEA) and Value Efficiency Analysis (VEA) as weighting methodologies to construct composite indices with flexible weighting that considers the unique characteristics of the municipalities in the region; and cross-sectional regressions to analyse the determinants of the subjective wellbeing of refugees and asylum seekers.
In the analysis of the primary and the secondary research questions two data sets were used. In Chapter 2 to 4 a data set collected by the Gauteng City-Region Observatory (GCRO) on quality of life in the Gauteng City-Region (GCR) was used. In Chapter 5 we used a data set collected by the Forced Migration Studies Program (FMSP) on Migration in New African Cities. A key finding of Chapter 2 is that the indicator variables of the dimensions ‘housing and infrastructure, ‘social relationships’, ‘socio-economic status’, ‘health’, ‘governance’ and ‘safety’ were found to be good measures of the dimensions of quality of life. Positive relationships were found between all the dimensions of quality of life, with the exception of the relationship between ‘housing and infrastructure’ and ‘health’, which was found to be statistically insignificant.
Using the newly constructed composite index, in Chapter 3 we found the quality of life among African, lower-income groups, females and older people to be lower than that of other socio-economic and demographic groups. In addition, we found that ‘housing and infrastructure’ contributes most to the variance in the data set of the group with lower levels of quality of life.
Using the flexible weighted composite indices to measure the quality of life within the different municipal regions of the GCR in Chapter 4, we found that the municipalities with the highest levels of quality of life to be Johannesburg and Midvaal, with, overall, above-average scores on all the dimensions of quality of life. The municipalities with the lowest quality of life in the GCR are Nokeng, Westonaria, Madibeng, Matlosana and Merafong. In the municipalities with the lowest quality of life scores, for those municipalities in the Gauteng Province, the ‘housing and infrastructure’ dimension was below average, while for the municipalities outside the Gauteng Province’s borders, it was found that the ‘health’ dimension was below average. In all the municipalities with low levels of quality of life it was found that the income variable is relatively low, except in Nokeng, which has relatively high income levels.
Chapter 5 analyses the determinants of the subjective wellbeing of refugees and asylum seekers. It was found that additional factors to the standard determinants that explain the wellbeing of people in general should be added to the model to explain the wellbeing of urban refugees and asylum seekers.