Shadow Pricing

Where price does not reflect the actual value of a good or commodity, or no market value for a good or commodity exists, shadow pricing can be used. Shadow pricing is a proxy value of a good, often defined by what an individual must give up to gain an extra unit of the good. The value of a good or impact resulting from a project when measured using shadow pricing may, however, differ from the value of that or similar goods or impacts when measured using market prices. This occurs due to market failure in real markets which impacts on the shadow value of certain goods and impacts. A number of examples of this are given in the table below which has been adapted from Stiglitz (2000, 283).


Difference between Market and Shadow Price



Shadow wage is less than market wage when there is unemployment.

No loss in output elsewhere when individual gains employment, so marginal social cost of hiring this individual is lower than market wage.


Shadow interest rate is greater than market interest rate when there is rationing in capital markets.

Expected return is greater than interest rate as firms wish to borrow more at given interest rate than they can. Opportunity cost of funds is greater than interest rate.


Shadow price is greater than market price.

Steel producer does not account for marginal social cost of pollution in production costs.

In some cases shadow pricing can be used to obtain a valuation of the impacts of a project, whether benefits or costs, using stated and revealed preferences. The UK Department for Transport, for example, collect data on revealed and stated preferences for use in their COBA project appraisal.

‘Stated’ or ‘Expressed’ Preferences

Collecting data on stated or expressed preferences involves asking individuals directly to express how they feel about the impacts of a project. This method is usually applied where impacts are involved which either do not have a market price, or a market price is deemed inappropriate. Stated or expressed preferences are a contingent valuation method of data collection which involve the use of either willingness to pay or willingness to accept measures of a good or commodity (see Boardman et al, 2001, 30-36).

Willingness to Pay
If collecting data on benefits this measure will usually involve asking an individual, using a survey or questionnaire, about their willingness to pay for some sort of benefit, for example improved journey times, or the preservation of a local park. The willingness to pay method has been used in the UK to evaluate the ‘use value’ of an amenity to individuals.

Willingness to Accept
Equally a willingness to accept measure can be used. This involves asking individuals how much they would be willing to accept in compensation to consume more undesirable goods or commodities. For example, what monetary compensation would a fisherman accept to continue living along a coastline impacted by an oil spill.

Total Economic Value

The total economic value (TEV) of a resource or amenity reflects not only the value we associate with our current use of the amenity (the ‘use value’) but also the potential future value we consider the amenity to have, and the value we associate simply with the existence of the resource or amenity.  

This can be expressed as follows:

TEV = Use Value + Option Value + Existence Value

Use Value

The Use Value is the value we consider a resource or amenity to currently have in reference to our current use of it. For example, we may value a park based on walking a dog around it, playing football one night per week, and having picnics on it during the summer months.

Option Value

The option value of a resource or amenity reflects the value we would give to our potential or optional future use of the resource or amenity. For example, we may consider our local park would be a good place to start playing cricket on the weekends, which would increase our overall future use of the park and therefore our value of it.

Existence Value

The existence value is the value which reflects our willingness to pay for a resource or asset to be preserved simply because we wish for it to continue to exist. In the case of our park regardless of current use value and future option value, we would also wish it to continue to exist because of the aesthetic and ambience it provides to the area.

The Bias Problem

Collecting data from individuals using a questionnaire method can suffer from a key problem relating to bias. When attempting to apply a valuation to some cost or benefit of a project two potential biasing problems may be encountered:

(1) Bias in the sample: In most cases the researcher involved in the CBA will have limited resources (time and financial). This means that a sample will have to be chosen to collect the stated preference data on the costs/benefits associated with a project. However, in collecting data using only a sample of the wider population potential bias can be found. This will be a particular problem if only a small sample of individuals is surveyed as part of the data collection. For example, if a survey samples only 100 individuals, and within this sample 12 are members of a local environmental action group, the responses of these individuals could bias the overall results. This problem can be addressed, at least to a certain extent, by collecting data from a large sample, and through use of sampling methods which ensure a representative cross-section of individuals. 

(2) Bias in responses: Asking individuals directly about their willingness to pay or willingness to accept may illicit a stronger view from the individuals than they actually have. For example, when asking individuals how much they would be willing to pay to preserve an area of local parkland they may apply a significantly larger monetary valuation than they would really be willing to pay, knowing that they would not actually be asked to pay this amount should the parkland be preserved. Moreover, individuals may state a willingness to pay to preserve an amenity such as a local park, even though they actually never visit the park and may consider it a nuisance at night when children hang around on the park.


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This resource was created by Dr Dan Wheatley. The project was funded by the Economics Network and the Centre for Education in the Built Environment (CEBE) as part of the Teaching and Learning Development Projects 2010/11.


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