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

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As already discussed in section 4.2.4 part of the reason for the high valuations is likely to be that
income is often not instrumented. Using an instrumental variable for income tends to increase
the income coefficient, thus reducing the income compensation values.
Relative income
There is a theoretical justification for the inclusion of relative income in the utility function to
account for reference group effects (Duesenberry, 1949; Frank, 1997). There is empirical
evidence that relativities in income matter to well-being (Blanchflower and Oswald, 2004;
Easterlin, 1974; Easterlin, 1995, 2001a; Ferrer-i-Carbonell, 2005; Graham and Felton, 2006;
Luttmer, 2005; McBride, 2001). Relative income effects can be controlled for by including a
measure of the average income for the reference group as an additional explanatory variable.
Controlling for relative income in the LS function tends to have the effect of increasing the
impact (ie, coefficient) of income on LS (eg, Alpizar et al., 2005; Clark et al., 2008; Easterlin,
1995; Frank, 2005). This is because in essence the ‗price‘ of status is held constant as other
people‘s incomes do not change.
There is no consensus on whether relative income should be included when estimating income
compensations. In theory Stated Preference techniques implicitly hold others‘ income constant
as people are asked to think about their own finances only. This could be seen as an argument
for including relative income in the LS function and this is likely to reduce the levels of income
compensation required for non-market goods. However, including relative income in the LS
function is not an easy task as assumptions need to be made in the empirical analysis as to what
group is used as the reference group (Pischke, 2010). For example is the appropriate reference
the incomes of work colleagues, wage levels in the region or GDP per capita? The effect on the
income coefficient will vary depending on the reference group used (Dolan and Peasgood,
2006).
Indirect effects of income
As well as affecting our utility directly (for example, the pleasure of having more money in the
bank), income affects utility indirectly through the goods and services it allows individuals to
purchase (Dolan et al., 2011b; Dolan and Peasgood, 2006). Income may have a positive effect
on a number of variables that are held constant in the life satisfaction regression, such as health,
social relationships, marital status and place of residence. Controlling for these effects therefore
subdues the impact of income on well-being and inflates the monetary values derived (Dolan et
al., 2011b). In Stated Preference surveys people are often urged to think about the value of
money when stating a WTP figure. In other words, they should consider the opportunity costs or
everything else they could do with the money, and so in line with the above argument, in
theory, people are asked to think about how income impacts on their health, relationships and
place of residence.
The indirect effects of income have generally been ignored by the LS approach literature. One
exception is Ferrer-i-Carbonell and van Praag (2002), who model the impacts of income on life
satisfaction through its effects on a set of domain satisfactions, including leisure, housing and
job satisfaction. A problem with this approach is that the final LS function does not include
controls for many of the explanatory variables that have been shown to impact on SWB, such as
age and marital status, thus biasing the model. We discuss some solutions to this problem
below.
Counter-effects of income
When calculating EV or CV we essentially consider exogenous changes in income required to
hold utility constant. For example, if we are interested in estimating the level of compensation
that would be required to return people to their original levels of utility after the loss of a good
or service (ie, the compensating variation) this compensation is essentially an exogenous increase
in income for those affected. However, the income variable used in the life satisfaction function
is usually a measure of household income, which is in large part derived from labour income.