The positive association between income and subjective well-being (SWB) is undisputed; there remains scope, however, to expand our understanding of the explanatory mechanisms at work. The theoretical framing is formed from economics and psychology which have been the traditional homes of happiness research. However, the stance taken here is sociological in its attention to social networks and social status. I also emphasise psychological benefits as an explanatory mechanism for the money-happiness relationship. Following Layard (1981) and Easterlin (2001), it is posited that above the level at which basic needs are met, higher SWB results from the higher rank in society that money brings. I argue that rank and status inform how individuals feel about themselves (self-esteem, self-worth) and their environment (perceived control) and that it is these factors that bring about SWB. Furthermore, social connectedness is an alternative source of these benefits and it is thus hypothesised that connectedness will intervene in the money-happiness relationship. Secondary or "weak" ties are expected to have an additional and separable effect to close ties alone. I use the term resilience as a framing concept as it allows the stressor (financial situation) and outcome (SWB) to be discussed in a single term. The thesis has three empirical aims. The first is to determine whether connectedness influences the money happiness relationship, where 'money' refers to household income, perceived financial situation and being worse off than the previous year. Secondly, I aim to separate the effect of connectedness from the effect of personal characteristics by observing outcomes before and after a change in connectedness. Third, I aim to unravel the potentially paradoxical role of networks for those on low incomes as both a resilience resource and therefore greater happiness, and as a source of wider social comparison and therefore greater unhappiness.I use data from seven waves of the British Household Panel Survey. A latent class analysis establishes a measurement schema of connectedness based on strong and weak ties. Growth curve models are used to measure the effect of money on SWB and differential effects by connectedness are demonstrated with interaction terms. Resilience before and after network changes are explored using multiple group linear regression at two time points, and neighbourhood social comparison is examined in multilevel models. The findings are that income has no bearing on the SWB of the socially-integrated (those with both strong and weak ties) while the isolated have a lot to gain. The SWB of the integrated does suffer in difficult financial circumstances as subjectively reported but less so than the isolated or those with only strong ties. Further, when individuals expand their network it is accompanied by a decrease in the importance of income for SWB. These patterns can in part be explained by the fact that the SWB of the well-connected is less influenced by their position relative to those living around them, at least where the income gap is not too large. Therefore, the assumption of happiness as a zero-sum game is mistaken; social comparison is not inevitable and SWB can be maintained through social integration providing the level of inequality is not too high.