Valuation Techniques for Social Cost-Benefit Analysis: - HM Treasury

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Data
The British Household Panel Survey (BHPS) is a nationally representative sample of British
households, conducted on 10,000 individuals each year. Since 1997 1 individuals have been
asked ―How dissatisfied or satisfied are you with your life overall?‖ and then asked to score their
level of satisfaction on a scale of 1 (not satisfied at all) to 7 (completely satisfied).
The BHPS has a rich list of variables so it is possible to analyse the value of a wide range of nonmarket
goods and control for a wide range of other influences on well-being 2 .
From April 2011, the Office for National Statistics (ONS) will include four questions on
subjective well-being in the Integrated Household Survey (IHS). The IHS is a composite
household survey combining the answers from a number of ONS household surveys to
produce a dataset of core variables. The well-being module will include a question on
overall life satisfaction rated on an 11 point scale (0 - 10). With approximately 200,000
people interviewed each year, this will be the largest regular survey on well-being in the
UK and it provides an opportunity for analysts to use the Life Satisfaction Method on a
much larger dataset.
Where there are variables that we are interested in valuing which do not feature in the BHPS or
IHS, it may be possible to derive a value estimate using other national panel datasets, for
example:
- Household, Income and Labour Dynamics in Australia (HILDA)
- German Socio-Economic Panel (GSOEP)
- Eurobarometer (Europe-wide)
- US General Social Survey (GSS)
- Gallup (Worldwide)
Alternatively, it is possible to administer a well-being survey on the target population of interest.
Dolan and Metcalfe (2008) is an example of this. They collect data on the life satisfaction (and
other determinants of well-being) for a sample that experienced an urban regeneration project
in their neighbourhood. Data was also collected from a similar neighbourhood, which did not
benefit from the intervention to use as a control group.
5.2 Recent methodological developments
Dolan et al. (2011b) develop a method for accounting for the indirect effects of income. Groot
and van den Brink (2006) and Welsch (2007, 2008b) develop methods for accounting for the
indirect effects of non-market goods and ‗bads‘, including health, air pollution and public sector
corruption.
These methods are only required when the explanatory variables are not exogenously
determined through either an instrumental variable or randomisation. Thus for example if the
health variable is exogenous then income cannot have an indirect effect through health in the
model. If all explanatory variables are exogenously determined in the life satisfaction model then
it is not necessary to use methods to account for indirect effects (Dolan et al., 2011b).
Dolan et al. (2011b) and Groot and van den Brink (2006) assess the indirect effects of income
and health on well-being by dropping in piece-wise fashion variables from the model that are
1 2001 did not include the life satisfaction question and so this year is usually dropped in the analysis.
2 A list of all variables included in the BHPS can be found here: http://www.iser.essex.ac.uk/survey/bhps/documentation/volume-b-codebooks/thesaurus