The Economic Value of Water and Ecosystem Preservation

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expenditures indicating a high value of freshwater inflows. Further analysis could be undertaken to calculate an aggregate value for the region, but was unable to be conducted here. Production Function Approach A key goal of the research was to provide useful economic information to inform the debate on freshwater inflows in Texas rivers. The debate is especially concerned with competing uses for freshwater inflows. Therefore, it is important to try to relate the value of ecotourism to quantities of freshwater inflows. A core tool in economics is the production function which mathematically relates known inputs to the production of outputs. Economists have also adapted production function analysis to estimate the value of irrigation water in the production of crops. This study adopts a similar approach with the assumption that freshwater inflows are an input into the production of ecotourism. An ecotourism production function is estimated as a function of inflows and other key variables. This function was then used in conjunction with the ecotourism values estimated using the Travel Cost Method to calculate a marginal value for freshwater inflows. For this study, the freshwater inflows are the only input to ecotourism included in the model. The output, ecotourism, is equated with the number of visitors to the Aransas National Wildlife Refuge. This implies that ‘units’ of ecotourism are not produced until consumed. Finally, various factors are included to account for likely sources of correlation between input and output. These included precipitation, summer holiday period, nesting period for whooping cranes, and period for ‘winter Texans’. There are several problems with using a production function approach to estimating the value of freshwater inflows to the production of ecotourism. The primary problem is the complex relationship between inflows and the status of the ecosystem. It is known that freshwater inflows have a highly significant impact on the ecosystem, but this is through a complex interaction with the other elements of the ecosystem. The inflow regime poses particular problems because: • Inflows are continual rather than applied in discrete amounts; • Inflows vary across the year with important high and low flow periods; • Inflows experience periods of flood and drought which are also useful to maintaining the ecosystem; and, • The resulting ecosystem services are not simply an increasing function of freshwater inflows Thus, there is a fundamental question in how to best incorporate the inflows into a production function. The present model is viewed as an initial step in this direction. Average inflow rates were taken on a monthly basis. These flows were then compared to visitor data lagging the flows by one month up to 18 months. 74
This implicitly assumes that flows in a single month would have a significant impact on attracting tourists. The estimated tourism-water production function indicated that freshwater inflows have a positive relationship with visitor numbers up to a flow rate of 2,400 cfs. The average flow rate from the data was calculated as 1,995 cfs. This should be interpreted as an early indicator that freshwater inflows have a positive impact on the ecosystem services that tourists use. However, more work needs to be done to address the timing and magnitude of flow variations and their respective impacts on freshwater inflows. This type of approach will be highly useful in analyzing tradeoffs from allocating water between competing uses. Multiplying the estimated number of visitors with the average expenditures as reported in the travel cost data ($508) yields a total travel expenditure of $2.39 million. An incremental increase of 100 cfs is modeled as an increase of 25 visitors for an incremental increase of $12,700 in eco-tourism expenditures. Assuming a 30 day month, 100 cfs converts to 22,442 gallons, which results in a value of $565 per 1,000 gallons. This is very high rate relative to water rates of alternative uses with market prices. Socio-economic Environment of the San Antonio Bay This study examined the socio-economic environment of the San Antonio Bay, with a particular concern on the status of the fishing industry. The socioeconomic analysis examined Aransas, Calhoun, and Refugio counties. The analysis used Shift-Share analysis and an input-output model. Shift-Share Shift-Share analysis was conducted to study the competitiveness and growth and decline of local industries. This study used employment changes from 2001 to 2005 to identify the sources of growth and decline in local areas. It decomposes local employment growth into three components: 1. National share (NS); 2. Industry Mix (IM); and 3. Competitive share (CS). 1. The National share component explains the share of the change in total local employment that can be attributed to the rate of the total national employment growth. 2. The Industry Mix component focuses on the national growth of each specific industry. T 3. The Competitive Share component is extremely relevant since it identifies the leading and lagging industries in our study region. After deconstructing the various reasons for employment change using shiftshare analysis, the question becomes: What impact does this change in employment have. Input-output Analysis Input-output modeling was used to reveal the complete impact on the economy of employment change in a particular sector. The input-output model uses a matrix representation of a nation’s (or a region’s) economy to predict how 75
Page 1 and 2:
Final Report to the Texas Coastal M
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5.2.2. Sources / Data .............
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Executive Summary The San Antonio B
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ecotourism included in the model. T
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1. Overview of San Antonio Bay Regi
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and shellfish species and estuarine
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According to the Rockport-Fulton Ch
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effect is limited by assimilative c
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freshwater inflow acts as a mechani
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sulfide. Heavy metals bounds to sed
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inflow levels and populations of se
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and could potentially make the cran
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3. Characterization of Ecotourism i
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Contributes actively to the conserv
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Figure 3-1. Public Protected Areas
Page 31 and 32: 1987 and then purchased in 1991. Pr
Page 33 and 34: 3.3.2. The Economics of Multiple Na
Page 35 and 36: Table 3-2. Average Willingness to P
Page 37 and 38: Table 3-3. Personal Income and Prod
Page 39 and 40: impact. It is necessary to conduct
Page 41 and 42: 4.2. Key Site Details for the Analy
Page 43 and 44: approach allows examination of ques
Page 45 and 46: This average number of trips from t
Page 47 and 48: occasional flood and drought events
Page 49 and 50: The results of the regression yield
Page 51 and 52: gallons, which results in a value o
Page 53 and 54: Aransas distinguishes itself from C
Page 55 and 56: thresholds vary according the size
Page 57 and 58: The total number of full-time and p
Page 59 and 60: The County also shows a lower educa
Page 61 and 62: Refugio shows a rapid decrease in t
Page 63 and 64: IM t+ n ic = E t ic ⎡⎛ E × ⎢
Page 65 and 66: included an economic analysis of th
Page 67 and 68: Table 5-5. Employment Shift-Share A
Page 69 and 70: Fishing and related activities. The
Page 71 and 72: Figure 5-15. Employment change by s
Page 73 and 74: 5.3.2. Input-Output Analysis The in
Page 75 and 76: Calhoun Calhoun County’s experien
Page 77 and 78: an advantage, particularly in oyste
Page 79 and 80: Impacts on the Freshwater Inflows t
Page 81: However, due to the lack of consist
Page 85 and 86: for fresh product. This fishery wil
Page 87 and 88: Elliot, D. (2007). Competitive Adva
Page 89 and 90: Pearce, D. W. (1994). The MIT Dicti
Page 91 and 92: The Nature Conservancy. (2002). "Na
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