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Data is understood to be a key digital economy resource, and yet one that is difficult to value, as there are relatively few market prices for data. In addition, its non-rival nature and pervasive externalities mean there will also be a wedge between any market price and the social value of the data.
This paper proposes an approach to estimating the social value of certain kinds of data sets using a discrete choice approach, and a methodology that could for example be used by public bodies to understand the value of their data investments. The authors test this approach on a specific data set as proof of concept.