Does taking to our neighbours enhance our satisfaction with life?

Research has found a strong link between social capital and subjective measures of well-being (Helllwell and Putnam, 2005). Such findings have exciting policy potential, however there are important issues to be addressed before these research findings can be translated into a policy agenda. Although the conceptual breadth of 'social capital' has some advantages in terms of uniting an array of different research areas it is arguably too vague and as a consequence can be used to justify contradictory policies (Woolcock, 1998). Recent research has begun to address this by breaking down the concept of social capital into distinct elements which are found to have separate relationships with personal and social characteristics (Bjornskov, 2006). In addition to greater specificity, policy makers need researchers to show them that relationships between subjective well-being (SWB) and elements of social capital are not spurious, and are causal. However, since much of the research into SWB and social capital has used cross section data (e. g. Li et al., 2005) it is open to the criticism that unobserved, time invariant variables (such as personality) or unobserved, time variant variables (such as current mood) may be biasing findings. Furthermore, little has been done to establish causality. Panel datasets allow within-person analysis to be performed which controls for the unobserved, time invariant individual effects. Increasingly such fixed effects models are being used and these continue to show significant relationships between social capital variables and SWB (Powdthavee, 2007). Fixed effects models address the issue of time invariant omitted variables, however they still leave open the problem of time variant omitted variables, and potential reversed causality. This potential endogeneity of social capital variables may be addressed through the use of Instrumental Variables (IV), if adequate instruments (variables which correlate with the social capital variables yet not with SWB) can be found. The aim in this paper is to produce findings which can inform policy. The analysis models the impact on life satisfaction of one very specific aspect of social capital the frequency of talking to ones neighbours using the British Household Panel Survey (BHPS). The panel nature and extensive detail available in the BHPS allows controls for individual fixed effects and for most factors which have been shown in the literature to influence SWB (Dolan et al, 2006). The BHPS data shows a shows a clear positive bivariate relationship between the frequency of talking to neighbours and life satisfaction. This relationship remains robust even when controlling for those factors which may have caused a spurious finding (e. g. age, presence of children in the household, health, marriage status, employment status, hours worked, neighbourhood harmony, length of time the individual has lived in their current house, and the unobserved individual fixed effect). However, both reports of life satisfaction and frequency of talking to neighbours may be subject to similar measurement error. For example, if the respondent is in a particularly good mood and painting a non representative favourable picture of their life then measurement error on the life satisfaction variable may be correlated to measurement error on the frequency of talking to neighbours variable. Furthermore, the assumption that the direction of causality runs from frequency of talking to neighbours to life satisfaction is brought into doubt by the fact that lagged life satisfaction enters positively into regression predicting the frequency of talking to neighbours. Both these factors suggest that frequency of talking to neighbours may be endogenous. Using an instrumental variable model to overcome the potential endogeneity of talking to ones neighbours is considered. Firstly, this involves a search for instruments, or variables which have a strong correlation with talking to neighbours, yet no relationship to life satisfaction except that which is fully mediated via talking to neighbours. The frequency of talking to neighbours is reasonably well predicted by house type (terrace, detached etc. ), satisfaction with finances, length of time in neighbourhood, the number of children and adults in the household, time at work, employment status, age, marriage status, and the average frequency of talking to neighbours in the district. However, many of these variables also share a direct relationship with life satisfaction, making them unsuitable instruments. The very complexity of the web of social capital relationships seems to make identifying valid instruments for one attribute of social capital problematic. The use of average frequency of talking to neighbours in the district and a lagged value for talking to neighbours are used as instruments in a fixed effects IV model. The coefficient on talking to neighbours is no longer significant within this model. Unfortunately, although these findings indicate that a relationship may remain even when endogeneity is accounted for, the use of IV techniques are not found to be a solution to problems of endogeneity of social capital variables. Talking to neighbours is positively associated with life satisfaction. But we cannot know with certainty that the causality runs from talking to neighbours to life satisfaction. Nevertheless, the evidence of association justifies the evaluation of a programme of intervention to stimulate increased interaction between neighbours. This would establish clearer evidence on the direction of causality. The factors predicting the frequency of talking to neighbours suggests that it can be influenced by house and street design and public levels of noise. These are areas within the remit of local government.