
The relationship between technology and individual welfare is not well understood, and as we progress into a future in which technology invades almost every aspect of life, the importance of this relationship must be recognised and an improved understanding reached. In this study, we attempt to lay a foundation for such an understanding. Using an approach based on Sen’s theory of Capabilities and the South African National Income Dynamic Survey (NIDS), it estimates the effects of the ownership of technological assets on self-reported measures of well-being, both subjective and objective. Any empirical analysis of this relationship needs to control for several confounding factors. The estimation procedure employed is based on a dynamic panel approach, one that is capable of controlling for individual effects, as well as potential sources of endogeneity such as reverse causality. The results indicate that there is a statistically significant relationship between changes in the composition and value of one’s technological asset portfolio and measures of social and economic well-being. Specifically, they show that increased ownership of technological assets improves one’s overall life satisfaction and health status, but has little effect on one’s positivity about the future. This study has found evidence that technology can improve lives when controlling for confounders such as increased wealth and status. Future work can improve upon this by better understanding the dynamics of this relationship, and disaggregating further by type of technology.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
