Benefit transfers of cultural heritage values - how far can we go?
Assessing the economic values attached to alternative land uses, when cultural heritage goods are at stake, makes the valuation process more articulated. Economic elicitation of cultural heritage values is quite a recent practice. Not many case studies have applied non-market valuation techniques, such as contingent valuation methods or travel cost methods, to derive monetary estimates of cultural goods attribute and even fewer applications have been policy oriented. Being a relatively recent research field, the first applications have mainly dealt with the challenges faced by the valuation techniques and the validity and reliability of results. These studies, particularly contingent valuation ones, have very high implementation costs. Hence, to obtain primary estimates of cultural values, agencies need to spend a great deal of money and time. Since these resources are scarce, there is an impinging need to consider the possibility of transferring benefit estimates from a specific “study site” for which data has been collected, to a “policy site” for which there is little or no information. An important question often addressed in the literature is what we can learn from individual case studies for a next case study. How general are the results of case study research? Can we transfer findings from a set of rather similar case studies to a new case study? This question is known as the benefit transfer (or value transfer) issue and seeks to investigate under which (general and specific) conditions common findings from various case studies are more or less valid for a new given case at a distinct site. Knowledge acquisition in the social sciences, and hence also in economics, is usually based on a reductionist approach, which eliminates many person-specific, object-specific or site-specific characteristics of a phenomenon, but the major advantage is that it allows for generalization through a common standardized approach that is applicable to a larger population. This methodology lies also at the heart of meta-analysis, which seeks to synthesize research findings from different case studies (van den Bergh et al. 1997, van den Bergh and Button 1997, 1999). Through the use of common relevant descriptors (behavioural, methodological, contextual) it is possible to draw inferences from a large sample of cases. For value transfer (also commonly named ‘benefit transfer’) the possibility of using meta-analysis is of major importance (Bal and Nijkamp 1998a). The basic idea of value transfer is that knowledge accumulated over time may be subjected to a transfer to a new, similar type of study. For the use of knowledge on a new similar study, it would be ideal if almost identical site characteristics could be transferred without any manipulation and if, at the same time, typical site-unique characteristics could be taken into account: that is, if it were possible to adapt derived variables for these site-unique characteristics.Value transfer studies in cultural heritage economics are rather rare, and the idea itself is quite controversial. In this paper we offer a concise – and certainly not exhausting – review of some recent value transfer studies in this area, with a particular view to spatial variability and transferability. We discuss limits and potentialities of benefit transfer approach for cultural values, aiming to raise debate on the topic. We acknowledge the local nature of cultural values and the strict relationship with the population to which the specific heritage belongs, but we focus on the more universally shared values that are embedded in cultural heritage and on possible ways of expressing them in terms of priorities and clusters. More research is needed in this direction before dismissing the possibility to apply benefit transfer in the case of cultural values estimates.
|Date of creation:||Aug 2005|
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- Brouwer, Roy, 2000. "Environmental value transfer: state of the art and future prospects," Ecological Economics, Elsevier, vol. 32(1), pages 137-152, January.
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