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Tessa Peasgood Centre for Well-being in Public Policy Sheffield University Modelling Subjective Well- being. Do strong social relations lead to increases.

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Presentation on theme: "Tessa Peasgood Centre for Well-being in Public Policy Sheffield University Modelling Subjective Well- being. Do strong social relations lead to increases."— Presentation transcript:

1 Tessa Peasgood Centre for Well-being in Public Policy Sheffield University Modelling Subjective Well- being. Do strong social relations lead to increases in well-being?

2 SWB in the British Household Panel Survey Please tick the number which you feel best describes how dissatisfied or satisfied you are with the following aspects of your current situation….......…….your life? 1 2 3 4 5 6 7 Not satisfied Completely satisfied 12-item General Health Questionnaire (GHQ) - used to detect the presence of non-psychotic psychiatric morbidity in community settings

3 THE GHQ a) been able to concentrate on whatever you're doing ? c) felt that you were playing a useful part in things ? d) felt capable of making decisions about things ? g) been able to enjoy your normal day-to-day activities ? h) been able to face up to problems ? l) been feeling reasonably happy, all things considered ? More so than usual (1), Same as usual (2), Less so than usual (3), Much less than usual (4) b) lost much sleep over worry ? e) felt constantly under strain ? f) felt you couldn't overcome your difficulties ? i)been feeling unhappy or depressed ? j)been losing confidence in yourself ? k) been thinking of yourself as a worthless person ? Not at all (1), No more than usual (2), Rather more than usual (3), Much more than usual (4)


5 Why use both life satisfaction and GHQ? May measure different aspects of SWB Different time period (4 weeks vs.1 year+) Life satisfaction more evaluative GHQ externally determined affects, may not be what is important to the individual Different measures have different problems, if results are similar, or we understand why they vary, should give confidence in results.

6 How valid are these SWB measures? Interpretation problems Not clear what time period are people using for life satisfaction Not clear if people are including non self-referencing concerns e.g. others well-being GHQ compares to usual but may be using scale absolutely a third of respondents who answer better than, or less than usual to the general happiness question in wave 12 also do so in wave 13 Measurement error Situational factors & question ordering – what attention is drawn to at the time Life satisfaction influenced by mood - BUT life satisfaction more stable than mood Culturally appropriate responses problematic if adjusting responses is linked to circumstances e.g. unemployment

7 Are life satisfaction responses internally consistent? Actual change in life satisfaction score Would you say that you are more satisfied with life, less satisfied or feel about the same as you did a year ago? IncreasedDecreasedSame More satisfied34%18%48% Less satisfied17%52%31% Same25%26%48%

8 Why the inconsistency? Poor memory for what life was like a year ago Measurement error (current year, previous year or both) Not a clear concept Revaluate past based on new information Need to assume people use the scales in the same way & that current evaluation of current time is privileged

9 Some confidence derived from: SWB correlates with informant reports, smiling and interviewer ratings SWB predicts suicide Other subjective measures have predictive powers Job satisfaction predicts quitting job Subjective health predicts suicide and longevity Life satisfaction & GHQ will tell use something about SWB but will have considerable measurement error.

10 Social capital and well-being Has been found to be linked to beneficial outcomes e.g. lower crime rates, child welfare, public health, market performance, education performance (Helliwell & Putnam 2004) Some evidence of direct link social capital to individual well-being/happiness (Putman 2000, Helliwell 2004, Diener and Seligman 2002), using range of measures for social capital Focus here on social and personal relationships Intimate relationship & marriage status How often meet friends and family How often talk to neighbours Average level of social relationship scale for the district

11 The Model SWBit = βXit + αi + uit SWB (Life satisfaction or GHQ score) for individual i at wave t Matrix of explanatory variables e.g. income & health of individual i at wave t Individual effect Shifts SWB up/down but doesnt change how much Xs effect Y (β same for everyone) If happy disposition would shift Y upward in all time periods Error term All change in SWBit not captured by Xit and αi

12 SWBit = βXit + αi + uit To estimate β need to either remove or estimate αi Fixed effects Using deviations from individual means individual effect (αi) drops out (αi is the same as the individual mean αi) Comparing individual to themselves at different time periods Cant say much about variables which dont vary within the individual over the time period Can use OLS fixed effects on life satisfaction and GHQ but assumes cardinality

13 Ordered logit Treat life satisfaction as latent, continuous variable LS* LSit = 1 if - <= LS* <= μ1 = 2 if μ1 < LS* < μ2 = 3 if μ2 < LS* < μ3 etc. Probability of an outcome (e.g. Life sat = 5) calculated as linear function of explanatory variables plus set of thresholds or cut points. Control for unobserved individual effects by including individual level means of all explanatory variables (Mundlak approach) Since model uses logit assumption on error term the log odds of being in higher life satisfaction category are linearly dependent on the explanatory variables.

14 Explanatory Variables: Social relationshipsOrdered Logit on life satisfaction (All) Base category: sees friends or family and talks to neighbours most days, married, no accommodation problems Odds ratioP value Sees friends or family once or twice a week0.9540.018 Sees friends or family once or twice a month0.9550.154 Sees friends or family less than once a month0.8980.086 Never sees friends or family0.6110.043 Talks to neighbours once or twice a week0.9250.000 Talks to neighbours once or twice a month0.7730.000 Talks to neighbours less than once a month0.8400.000 Never sees neighbours0.8300.007 Mean social relationships scale of district1.2960.011 Divorced/Separated0.7640.002 Co-habiting1.0270.647 Widowed0.6210.001 Never married and not co-habiting0.8230.021 Living alone0.9980.969 Problem with accommodation: noisy neighbours0.9710.354 Problem with accommodation: street noise0.9940.822 Problem with accommodation: vandalism / crime0.9600.108

15 Explanatory variables: IncomeOrdered Logit on Life satisfaction (all) Base category: top income quintile, living comfortably, no problems paying for accommodation Odds ratioP value Bottom income quintile0.9460.204 Second income quintile0.9730.476 Third income quintile0.9510.127 Fourth income quintile0.9830.524 Doing OK financial0.8340.000 Just financial0.6390.000 Difficult financial0.4660.000 Very difficult financial0.2950.000 Problems paying for accommodation0.8390.000 Mean equivalent household net income for the individuals district and age group 1.0000.566

16 Explanatory variables: HealthOrdered Logit on Life satisfaction (All) Base category: Subjective health good, not disabled, no problems walking Odds ratioP value Subjective health poor or very poor0.5020.000 Subjective health fair0.7170.000 Subjective health excellent1.2230.000 Problems walking0.7210.000 Disabled0.9030.092 Days hospital stays (excl. births)0.9280.027 Problems with sleep0.6500.000

17 Explanatory variables: Employment statusOrdered Logit on Life satisfaction (All) Base category: employedOdds ratioP value Long term sick0.6160.000 Retired1.0870.203 Unemployed0.7280.000 Maternity leave1.5190.000 Self-employed0.9720.617 Family carer0.9100.099 Student 1.070 0.281 Government training0.7880.331 Other employment status0.9390.670

18 Explanatory variables: Education and demographicsOrdered logit on Life satisfaction (All) Base category: No education, not high burden carerOdds ratio P value Commercial qualification1.2400.223 O level1.0180.889 A level1.1760.201 Degree or higher education1.1430.282 Cares for someone > 50 hours a wk0.7860.024 Number children in household 12-180.9350.012 Number children in household 5-110.9730.349 Number children in household 0-40.9490.107 Age0.8230.000 Age squared / 1001.3630.000 Age cubed / 10000.9780.000

19 Results Broadly the same using for life satisfaction, GHQ, not at all unhappy, and modelling as ordered variable or cardinal, and for males and females Social relationships important Financial coping and health biggest knock to well-being Financial coping related but not identical to income 50% of top income, and 15% of bottom quintile living comfortably 14% of those in the top income quintile think they are just about getting by or are finding it difficult or very difficult financially. Need to look at real household income, accounting for the costs of living, where those costs of living may be influenced by geographical costs differences, or individually held (and socially driven) expectations of necessary expenditures.

20 Direction of causality? IncomeSWB HealthSWB Social relationships SWB May be other factors influencing SWB and Xs e.g. life events like having sick child Could address endogeneity using Instrument Variables but hard to think of truly exogenous variables Likely that route from SWB to Xs slower. Some evidence that cheerfulness in college students predicted higher income 19 years later (Diener et al 2002)

21 Still confident people matter.. A lot One very clear message from this range of different modelling techniques on different SWB measures is that the people around you really matter. Those times when we have people who we see regularly and who create a friendly and peaceful local environment are the times when we are more satisfied with our lives and less likely to experience unhappiness. But is this a policy concern?

22 Some indication of positive externalities, social connectedness not entirely private good - role for intervention Indirect impact on social relationships of other policies (e.g. flexible labour force, hours worked) should be considered Increasing income may reduce social connectedness. Income quintileMean social relationships 1 (bottom)6.56 26.54 36.40 46.27 5 (top)6.07

23 Fixed effects OLS on social relations scale When other variables are controlled for, the negative relationship between income and social relationships scale remains. Being in the bottom two income quintiles is significantly related to having a higher social relationships scale, although perceived inability to cope financially is associated with reduced social relationships

24 Conclusion Cant say income isnt important to SWB, financially difficulties very important Increased income may contribute to other sources of SWB e.g. health BUT Policies which focus on increasing income risk undermining other sources of SWB Policies shouldnt confuse means to well-being as ends

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