Value of Coastal Areas
Attributes
Medium: Land
Country: Thailand
Analytical Framework(s): Damage Schedule
Unit(s): Monetary Estimate
Study Date: 1997
Publication Date: 1998
Major Result(s)
| Resource/Environmental Good | THB (1997) |
THB (2014)1 |
USD (2014)2 |
|---|---|---|---|
| Monetary estimate for partial damage to mudflats | 1,350.00 | 1,929.92 | 58.64 |
| Monetary estimate for partial damage to sandy beaches | 850.00 | 1,215.13 | 36.92 |
| Monetary estimate for severe damage to sandy beaches | 2,850.00 | 4,074.27 | 123.79 |
About the Inflation Adjustment: Prices in Thailand (THB) changed by 42.96% from 1997 to 2014 (aggregated from annual CPI data), so the study values were multiplied by 1.43 to express them in 2014 prices. The study values could be expressed in any desired year (for example, to 2025) by following the same inflation calculation and being sensitive to directional (forward/backward) aggregations using your own CPI/inflation data.
Study Note: In an attempt to obtain monetary values of the resource losses using the method of paired comparisons (wherein respondents were asked to choose between a loss of resource and a loss of money), the author mentioned that a considerable number of respondents (approximately 48% in Ban Don Bay and 35% in Phangnga Bay) was not willing to make any trade-offs between the resource loss and the monetary loss. The proponent said that this unwillingness could be due to the very low amount of money included in the study. Another reason may also be that the respondents considered the resource losses to be much greater than any amount of money. As such, the quoted estimates are based only on the responses of those who were willing to make the trade-off. The author, however, mentioned that the monetary estimates were agreeable with the importance of the resources indicated by the importance scales produced by the alternative valuation method used.
Study Details
Summary: The study proposed an alternative valuation method known as 'damage schedules' in response to the growing concern over environmental degradation which has heightened the role of environmental economics and the valuation of natural resources as analytical tools to facilitate policy design for sustainable management. As defined in the study, damage schedules are constructed based on scales of relative importance obtained from people's judgments about values of various resource losses and activities causing the losses. Since people are asked to indicate their preferences and values about the resources without any reference to monetary values, the damage schedule method is a non-monetary approach. The responses of people to a series of paired comparison questions provide the basis for the construction of scales of relative importance. In each question pair people are simply asked to choose one item that they consider more important. As such, the damage schedules reflect community values which should be considered in the management of and policymaking for natural resources. Four main steps were followed in the study. First, a questionnaire containing series of paired comparison questions was designed and used as the instrument to elicit people's judgments about the relative importance of activities and resources. Second, to obtain scale values and rankings for various groups of respondents, Dunn-Rankin's variance stable rank sum method was applied to the paired comparison responses. Afterwards, the results were tested for their association using Kendall rank-order correlation coefficient T and Kendall coefficient of agreement u (these statistical tests determine the number of importance scales necessary for proper representation of responses from all the respondents). The scales of relative importance were then constructed and later used to develop damage schedules. The study was conducted on two coastal areas of Thailand, namely Ban Don Bay on the southeastern coast of the Gulf of Thailand, and Phangnga Bay on the southwestern coast of the Andaman Sea. The study concluded that using damage schedules is a practical and effective way of aiding policy makers in managing dynamic and complex ecosystems such as those of coastal areas.
Site Characteristics: The two coastal areas examined provided good comparative sites to test the approach since the sites differed in resource characteristics and in economic importance to the region. Ban Don Bay was experiencing the long-term effects of mangrove forest clearing for shrimp farming, while Phangnga Bay was undergoing tourism-related activities, particularly hotel development. The study included four resources and three activities in each site. In Ban Don Bay, the resources were mangrove forests, mudflats, shellfish culture grounds and fishing grounds, while the activities were shrimp farming, housing development and oil spills. In Phangnga Bay, the four resources were mangrove forests, sandy beaches, seagrass beds and coral reefs, while the activities included shrimp farming, hotel development and oil spills. Eight resource losses and eight activities were constructed from different levels of damages to the resources and different sizes of activities, and were separately administered in the questionnaire such that no comparison was made between a resource loss and an activity. Approximately 200 people answered the questionnaire in each study area, 20% of which was formal experts (researchers and scientists knowledgeable about the resources in the study areas, as well as policy makers and administrators who had the responsibility in the management of the coastal resources). The remaining 80% was equally distributed among the four groups of lay experts (resource users, other stakeholders and people who lived in the study areas. These people were grouped according to occupation: fishers, shrimp farmers, and others in both sites, plus shellfish culturers in Ban Don Bay, and tourism-related business entrepreneurs in Phangnga Bay). The study showed that the respondents were able to provide consistent judgments about the resource losses and the activities in consideration. The two damage schedules developed in each study area (a loss schedule based on the scale of importance of resource losses, and an activity schedule based on the scale of importance of impacting activities) carefully captured the differences in the resource characteristics and the economic importance of the resources in the two sites. Clear-cutting of mangrove forests was considered to be the most important loss in both study areas, caused by shrimp farming involving clear-cutting of mangroves in Ban Don Bay, and hotel development involving clear-cutting in Phangnga Bay.
Comments: Damage schedules have a wide range of application for the management of natural resources, since based on these damage schedules, different policy responses could be assigned in accordance with the relative importance of the resources or the human activities affecting them. The author also claimed that damage schedules offer certain advantages over traditional valuation methods, because they provide predictability and enforceability by specifying in advance the payments that will be required in the event of a loss, rather than waiting until the damage has taken place. Such a feature is essential especially when transaction costs due to typical post-incident assessment are unaffordable. Moreover, announced damage schedules also provide clear incentives to resource users whose activities may damage the resource. When other losses or activities of different form or magnitude occur, the damage schedules could be adjusted/fine-tuned over time by interpolating or extrapolating from the initial scales. Moreover, the proponent stressed that the method is open to future experience and further knowledge of resources.