Does Volunteering Make Us Happier, or Are Happier People More Likely to Volunteer? Addressing the Problem of Reverse Causality When Estimating the Wellbeing Impacts of Volunteering

Abstract

Evidence of the correlation between volunteering and wellbeing has been gradually accumulating, but to date this research has had limited success in accounting for the factors that are likely to drive self-selection into volunteering by ‘happier’ people. To better isolate the impact that volunteering has on people’s wellbeing, we explore nationally representative UK household datasets with an extensive longitudinal component, to run panel analysis which controls for the previous higher or lower levels of SWB that volunteers report. Using first-difference estimation within the British Household Panel Survey and Understanding Society longitudinal panel datasets (10 waves spanning about 20 years), we are able to control for higher prior levels of wellbeing of those who volunteer, and to produce the most robust quasi-causal estimates to date by ensuring that volunteering is associated not just with a higher wellbeing a priori, but with a positive change in wellbeing. Comparison of equivalent wellbeing values from previous studies shows that our analysis is the most realistic and conservative estimate to date of the association between volunteering and subjective wellbeing, and its equivalent wellbeing value of £911 per volunteer per year on average to compensate for the wellbeing increase associated with volunteering. It is our hope that these values can be incorporated into decision-making at the policy and practitioner level, to ensure that the societal benefits provided by volunteering are better understood and internalised into decisions.

Appendix: Model Equations Used for Estimation

Note. X_it includes:

• The natural logarithm of equivalised household income (monthly)

• Age in years

• Age (in years) squared)

• Gender (1 for being male, 0—female)

• Marital status (dummies for married, divorced, widowed, separated, single [base group], cohabiting)

• Education (dummies for no qualification [base level], A level or GCSE qualifications, other qualifications, degree or higher degree)

• Employment (dummies for self-employed, in paid employment, unemployed [base level], retired, on maternity leave, looking after family or home, full-time student, long-term sick or disabled, on a government training scheme, unpaid worker in family business, doing something else)

• Self-rated general health (dummies for 1—poor [base level], 2—fair, 3—good, 4—very good, 5—excellent)

• Number of children (dummies for 0 [base level], 1, 2, 3, 4 or more)

• Whether respondent is religious (dummies for No [base level], Yes, Unknown)

• Whether respondent is a carer for someone in the household

• Region of England/UK (dummy for each of the 9 regions + Wales, Scotland, NI)

• House ownership (dummies for owned outright [base level], being bought on mortgage, shared ownership, rented, rent-free, other)

• Whether the respondent would like to move house

• Ethnicity broad categories (White [base], Mixed, Asian, Black, Other, Unknown)

• Wave of survey (dummy for each included wave—6, 8, 10, …, 24)

• Interview month (dummy for each month)

Xnoh_it includes the same as above but without self-rated health, as it is used as an outcome variable in those models.

Table 4.

Pooled OLS (column 2):

$$LifeSat_{it} = \alpha + \beta_{1} Vol12m_{it} + X_{it} \beta + \varepsilon_{it} \quad \left( {{\text{row }}2} \right)$$

$$SelfRatedHealth_{it} = \alpha + \beta_{1} Vol12m_{it} + Xnoh_{it} \beta + \varepsilon_{it} \quad \left( {{\text{row }}3} \right)$$

$$GHQ_{it} = \alpha + \beta_{1} Vol12m_{it} + Xnoh_{it} \beta + \varepsilon_{it} \quad \left( {{\text{row }}4} \right)$$

Fixed effects (column 3):

$$(LifeSat_{it} - \overline{{LifeSat_{i} }} ) = \alpha + \beta_{1} \left( {Vol12m_{it} - \overline{{Vol12m_{i} }} } \right) + \left( {X_{it} - \overline{X}_{i} } \right)\beta + \varepsilon_{it} \quad \left( {{\text{row }}2} \right)$$

$$\left( {SelfRatedHealth_{it} - \overline{{SelfRatedHealth_{i} }} } \right) = \alpha + \beta_{1} \left( {Vol12m_{it} - \overline{{Vol12m_{i} }} } \right) + \left( {Xnoh_{it} - \overline{{Xnoh_{i} }} } \right)\beta + \varepsilon_{it} \quad \left( {{\text{row }}3} \right)$$

$$\left( {GHQ_{it} - \overline{{GHQ_{i} }} } \right) = \alpha + \beta_{1} \left( {Vol12m_{it} - \overline{{Vol12m_{i} }} } \right) + \left( {Xnoh_{it} - \overline{{Xnoh_{i} }} } \right)\beta + \varepsilon_{it} \quad \left( {{\text{row }}4} \right)$$

First differences:

$$\left( {LifeSat_{it} - LifeSat_{i,t - 1} } \right) = \alpha + \beta_{1} \left( {Vol12m_{it} - Vol12m_{i,t - 1} } \right) + X_{it} \beta + \varepsilon_{it} \quad \left( {{\text{row }}2} \right)$$

$$\left( {SelfRatedHealth_{it} - SelfRatedHealth_{i,t - 1} } \right) = \alpha + \beta_{1} \left( {Vol12m_{it} - Vol12m_{i,t - 1} } \right) + Xnoh_{it} \beta + \varepsilon_{it} \quad \left( {{\text{row }}3} \right)$$

$$\left( {GHQ_{it} - GHQ_{i,t - 1} } \right) = \alpha + \beta_{1} \left( {Vol12m_{it} - Vol12m_{i,t - 1} } \right) + Xnoh_{it} \beta + \varepsilon_{it} \quad \left( {{\text{row }}4} \right)$$

Table 5.

Column 2:

$$LifeSat_{it} = \alpha + \beta_{1} Vol12m_{it} + X_{it} \beta + \varepsilon_{it} ;$$

Column 3:

$$LifeSat_{it} - \overline{{LifeSat_{i} }} ) = \alpha + \beta_{1} \left( {Vol12m_{it} - \overline{{Vol12m_{i} }} } \right) + \left( {X_{it} - \overline{{X_{i} }} } \right)\beta + \varepsilon_{it} ;$$

Column 4:

$$\left( {LifeSat_{it} - LifeSat_{i,t - 1} } \right) = \alpha + \beta_{1} \left( {Vol12m_{it} - Vol12m_{i,t - 1} } \right) + X_{it} \beta + \varepsilon_{it} ;$$

Table 6.

Column 2:

$$(LifeSat_{it} - \overline{{LifeSat_{i} }} ) = \alpha + \beta_{1} \left( {Volfreq1_{it} - \overline{{Volfreq1_{i} }} } \right) + \beta_{2} \left( {Volfreq2_{it} - \overline{{Volfreq2_{i} }} } \right) + \beta_{3} \left( {Volfreq3_{it} - \overline{{Volfreq3_{i} }} } \right) + \beta_{4} \left( {Volfreq4_{it} - \overline{{Volfreq4_{i} }} } \right) + \left( {X_{it} - \overline{X}_{i} } \right)\beta + \varepsilon_{it} ;$$

Column 3:

$$\left( {SelfRatedHealth_{it} - \overline{{SelfRatedHealth_{i} }} } \right) = \alpha + \beta_{1} \left( {Volfreq1_{it} - \overline{{Volfreq1_{i} }} } \right) + \beta_{2} \left( {Volfreq2_{it} - \overline{{Volfreq2_{i} }} } \right) + \beta_{3} \left( {Volfreq3_{it} - \overline{{Volfreq3_{i} }} } \right) + \beta_{4} \left( {Volfreq4_{it} - \overline{{Volfreq4_{i} }} } \right) + \left( {X_{it} - \overline{X}_{i} } \right)\beta + \varepsilon_{it} ;$$

Column 4:

$$\left( {GHQ_{it} - \overline{{GHQ_{i} }} } \right) = \alpha + \beta_{1} \left( {Volfreq1_{it} - \overline{{Volfreq1_{i} }} } \right) + \beta_{2} \left( {Volfreq2_{it} - \overline{{Volfreq2_{i} }} } \right) + \beta_{3} \left( {Volfreq3_{it} - \overline{{Volfreq3_{i} }} } \right) + \beta_{4} \left( {Volfreq4_{it} - \overline{{Volfreq4_{i} }} } \right) + \left( {X_{it} - \overline{X}_{i} } \right)\beta + \varepsilon_{it} ;$$

where Volfreq is:

• 1—volunteering at least once a week

• 2—volunteering at least once a month

• 3—volunteering several times a year

• 4—volunteering once a year or less

• 5—volunteering never or almost never [base group]

Table 7.

Pooled OLS (column 2):

$$LifeSat_{it} = \alpha + \beta_{1} Vol12m_{it} + X_{it} \beta + \varepsilon_{it} ; \, \quad \left( {{\text{row }}2} \right)$$

$$LifeSat_{it} = \alpha + \beta_{1} Vol12m_{it} *Male_{it} + \beta_{2} Vol12m_{it} *Female_{it} + X_{it} \beta + \varepsilon_{it} ;\quad \, \left( {{\text{rows}}\;3{-}4} \right)$$

$$LifeSat_{it} = \alpha + \beta_{1} Vol12m_{it} *Age16\_34_{it} + \beta_{2} Vol12m_{it} *Age35\_54_{it} + \beta_{3} Vol12m_{it} *Age55\_74_{it} + \beta_{4} Vol12m_{it} *Age75plus_{it} + X_{it} \beta + \varepsilon_{it} ;\quad \, \left( {{\text{rows }}5{-}8} \right)$$

$$LifeSat_{it} = \alpha + \beta_{1} Vol12m_{it} *HINC1_{it} + \beta_{2} Vol12m_{it} *HINC2_{it} + \beta_{3} HINC3_{it} *Age55\_74_{it} + \beta_{4} HINC4_{it} *Age75plus_{it} + X_{it} \beta + \varepsilon_{it} ;\quad \left( {{\text{rows}}\;9{-}11} \right)$$

where:

• HINC1—household income below £1500/month

• HINC2—household income between £1500/month and £3000/month

• HINC3—household income between £3000/month and £5000/month

• HINC4—household income above £5000/month

Fixed effects (column 3): same as above but all variables demeaned.

First differences (column 4): same as above but all dependent variables and the volunteering variable taken as first differences.