Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 12345678 9 10 11 12 13 14 15 16 17 18 19 20 21 22 A B 316b Non Use Benefits Meta Analysis This working file presents the data and analysis for EPA's meta analysis of non use benefits for the 316( b) NODA.

Date: 3/ 12/ 2003 Worksheet Summary Worksheet Description Studies Table Presents summary information for each study in the meta analysis; used to create appendix A in the March 12th, 2003 memorandum " Comparison of Non Use and Use Values from Surface Water Valuation Studies"

WTP Values Table  NU Presnts WTP values resulting from meta analysis for non user samples for each study, in 2002 dollars ( see worksheet " CPI" for inflation index).

WTP Values Table  U Presnts WTP values resulting from meta analysis for user samples for each study, in 2002 dollars ( see worksheet " CPI" for inflation index).

WTP Values and Ratios  concise Presents semi aggregated WTP value components for each study, inflated to 2002 dollars ( see worksheet " CPI" for inflation index).

WTP Values and Ratios Presents all WTP estimates presented in valuation studies that were extracted for this meta analysis,

inflated to 2002 dollars ( see worksheet " CPI" for inflation index).

Studies Presents all raw data extracted from valuation studies used in meta analysis.

Codes Presents coding of select variables in " Studies" worksheet.

Calculations Presents peripheral calculations by study ( mostly income estimates for studies that did not report sample income).

Weighted WTP Values Presents aggregated WTP values and calculates values weighted by study in order to derive meaningul estimates of mean and median sample WTP for all meta analysis studies.

Study Characteristics Summary This worksheet pulls select data fields from the worksheet " Studies" by study and calculates summary statistics that tally the number of studies with various characteristics.

State Income Presents Census income data ( Median Household Income by State: 1984 to 2001) used to estimate median income for studies where sample mean or median income was not reported.

State Income Footnotes Contains footnotes for the data presented in the " State Income" worksheet.

County Income Presents Census income data ( Median Household Income by County: 1969, 1979, 1989) used to estimate median income for studies where sample mean or median income was not reported.

CPI Presnts the Consumer Price Index ( CPI) data series used to inflate study values to 2002 dollars.

March 12th, 2003 Page 1 of 157 5 1200  File Info Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 123 4 5 6 7 8 9 10 11 12 13 14 A B C D E F G H I J K L Study Characteristics Appendix Table A  Non Use Analysis Studies and Characteristics Estimate ID Study ID Author & Year Amenity Valued Sampled Population Admin Method &

Response Rate Elicitation Method Mean Annual Non Use WTP/ hh ( 2002$) Nonuse Method Sample Size Mean Annual Use WTP/ hh ( 2002$) Mean Annual User Non Use WTP/ hh ( 2002$)

29 19 Clonts & Malone ( 1990) Preservation of 15 Alabama rivers in a freeflowing state, opposed to rivers which have been altered by dams, infrastructure, diversion or extraction. random sample of AL households phone ( 0.705) IB $ 55.43 value categories

user /

nonuser 733 $ 30.88 $ 82.35 13 7 Croke et al. ( 1986) Improvement in water quality, defined by 3 levels allowing outings, outings & boating, and outings, boating & fishing, respectively. households in Chicago and suburbs personal interview ( na) IB $ 53.31 user /

nonuser total values 296 $ 17.61 14 7 Croke et al. ( 1986) 0 households in Chicago and suburbs personal interview ( 0.73) IB $ 60.91 user /

nonuser total values 279 $ 11.11 15 7 Croke et al. ( 1986) 0 households in Chicago and suburbs phone ( 0.725) IB $ 75.11 user /

nonuser total values 280 $ 6.35 19 11 Cronin ( 1982) Change from useable for recreation to boating.

Incremental WTP for water quality of the Potomac River. Five levels of water quality are based on low flow, high temperature conditions,

differing in 5 physical and biochemical characteristics ( levels of DO, fecal coliform,

nitrogen, phosphorous, and turbidity). representative sample of Washington D. C.

residences mail ( 0.5) OE $ 59.37 user /

nonuser total values 1432 $ 23.75 20 12 Desvousges et al.

( 1983) Various water quality levels on the Monongahela River, using RFF water quality ladder: 1) avoid decrease in quality from boatable to not suitable for recreation, 2)

improve quality from boatable to where game fish could survive, 3) improve quality from fishable to swimmable. 4 elicitation methods used, valuing all 3 levels each. WTP value obtained to avoid decrease, and then incremental values for 2 levels of improvement ( p. 5 25) housholds in five counties in PA mail ( 0.27) PC $ 111.41 assume nonuse  value categories 205 280 $ 89.65 $ 130.59 1 1 Huang et al. ( 1997) restoration of quality of Pamlico and Albemarle Sounds to 1981 level in terms of increase of fish catches and shellfish beds eastern NC households phone ( na) DC $ 59.02 revealed &

stated 511 $ 158.25 2 1 Huang et al. ( 1997) 0 eastern NC households phone ( 0.84571428571428 6) DC $ 119.52 revealed &

stated 511 $ 97.75 24 15 Kaoru ( 1993) Poor to fair. Water quality improvement in 3 coastal ponds to allow them to be open for shellfishing year round ( some were closed at time of survey). random sample of Martha's Vineyard property owners mail ( 0.51) OE $ 112.57 allocation

entire sample 145 $ 77.04 9 5 Lant & Roberts ( 1990) Local river quality on a scale defined by ' poor,'

' fair,' ' good,' or ' excellent,' represented by photographs. The levels of quality framed by the recreational uses they support. residents in 14 towns in IA and IL, drawn from telephone listings mail ( 0.49) PC $ 68.56 value categories

entire sample 195 $ 57.30 March 12th, 2003 Page 2 of 157 5 1200  Studies Table Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 123 4 5 6 7 8 9 10 11 12 13 14 M N O P Mean Annual Household Income ( 2002$) Waterbody Type Geographic Scale of Improvement Year Index $ 39,591 rivers statewide 20 $ 47,402 urban rivers local/ regional 16 $ 47,402 urban rivers local/ regional 16 $ 47,402 urban rivers local/ regional 16 $ 56,896 river single water body 12 $ 38,664 river single water body 13 $ 37,498 estuary single water body 27 $ 37,498 estuary single water body 27 $ 137,693 estuaries multiple water bodies 23 $ 39,016 rivers local/ regional 20 March 12th, 2003 Page 3 of 157 5 1200  Studies Table Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 15 16 17 18 19 20 21 22 23 A B C D E F G H I J K L 10 5 Lant & Roberts ( 1990) 0 residents in 14 towns in IA and IL, drawn from telephone listings personal interview ( 0.407) PC $ 88.40 value categories

entire sample 195 $ 77.04 11 5 Lant & Roberts ( 1990) 0 residents in 14 towns in IA and IL, drawn from telephone listings personal interview ( 0.407) PC $ 85.29 value categories

entire sample 195 $ 78.34 8 4 Magat et al. ( 2000) Water quality is defined as " good" ( safe to swim,

eat fish, supports many plants, fish and other aquatic life) or " not good" ( unsafe to swim & eat fish, only supports small # of plants & aquatic life). water quality in lakes and rivers near hypothetical location respondent ( CO & NC)

might live base on 3 dimensions: aquatic life support, fish consumption, & swimming various populations in CO and NC phone ( 0.75) IB $ 11.49 assume nonuse 348 $ 22.98 28 18 Mitchell & Carson ( 1981) Improvement in nation's water quality ( lakes,

rivers and streams) from qualitatively established baseline, ok for boating, to a level that supports game fish such as bass. Boating

Game fishing. National probability sample of persons 18 or older mail ( 0.61) PC $ 242.34 user /

nonuser total values 695 $ 275.09 16 8 Olsen et al. ( 1991) Doubling the Columbia River Basin salmon and steelhead runs ( framed for users as more fish available for ocean and river basin sport catch,

with assurances of ecological stability and diversity). Pacific Northwest residents with phones personal interview ( na) OE $ 38.475 user /

nonuser total values 1177 # REF!

22 14 Opaluch et al. ( 1999) 3 scenarios for both Eelgrass habitat and wetlands habitat in the Peconic estuary area:

baseline (" no new action") level of degradation by 2020, program to restore, and program to preserve the resource, in terms of acreage. individuals in the east end of Long Island, NY mail ( 0.51) CC $ 0.05 user /

nonuser total values 968 # REF!

23 14 Opaluch et al. ( 1999) 0 individuals in the east end of Long Island, NY mail ( 0.51) CC $ 0.05 user /

nonuser total values 968 # REF!

12 6 Roberts & Leitch ( 1997) Various economic outputs ( recreation, aesthtics,

fish/ wildlife habitat etc.) of Mud Lake, a lacustrine wetland with recreational, aesthetic,

and other uses. " If Mud Lake was managed primarily for water related recreation and fish/ wildlife habitat, what would you be willing to pay through an annual use permit to participate in recreational activities at Mud Lake?"

Additional questions for existence & option values. random sample of housholds within 30 mile radius of Mud Lake personal interview ( 0.407) PC $ 2.09 value categories

entire sample 575 $ 5.17 26 17 Rowe et al. ( 1985) Clean up and protection of eagle mine area of Eagle River and prevent future contamination,

which would raise water quality from a level ok for watering your lawn, or for some industrial uses, to ok for swimming, rafting etc.

( interpreted as very poor to excellent). residents of Eagle County, CO personal interview ( na) OE $ 69.15 revealed &

stated 507 $ 47.88 March 12th, 2003 Page 4 of 157 5 1200  Studies Table Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 15 16 17 18 19 20 21 22 23 M N O P $ 39,016 rivers local/ regional 20 $ 39,016 rivers local/ regional 20 $ 45,283 all freshwater ( lakes &

rivers) local/ regional 30 $ 43,549 all freshwater national 11 $ 39,475 river single water body 21 $ 66,862 estuary single water body 29 $ 66,862 estuary single water body 29 $ 30,396 wetland single water body 27 $ 62,606 river single water body 15 March 12th, 2003 Page 5 of 157 5 1200  Studies Table Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 24 25 26 27 28 29 30 31 32 A B C D E F G H I J K L 27 17 Rowe et al. ( 1985) Clean up of Eagle mine hazardous waste site;

respondent state WTP to cleanup all CO sites,

then allocated by % among 7 sites for which the State was taking legal action, including EM.

Baseline and improvement not well defined, but assumed same as change in other survey version. CO households mail ( 0.76) PC $ 12.46 allocation

entire sample 570 $ 6.54 4 3 Sanders et al. ( 1990) protection of a specific # of CO rivers ( incremental WTP) in, described as " wild" and " scenic" rivers with an array of possible benefits,

which respondents are asked to indicate CO residents; representative of state phone ( 0.84571428571428 6) OE $ 46.91 allocation

entire sample 214 $ 24.96 5 3 Sanders et al. ( 1990) 0 CO residents; representative of state personal interview ( 0.815) OE $ 87.60 allocation

entire sample 214 $ 46.62 6 3 Sanders et al. ( 1990) 0 CO residents; representative of state personal interview ( 0.8059) OE $ 111.99 allocation

entire sample 214 $ 59.61 7 3 Sanders et al. ( 1990) 0 CO residents; representative of state phone ( 0.75) OE $ 115.35 allocation

entire sample 214 $ 63.45 17 9 Sutherland & Walsh ( 1985) Protection of water quality in Flathead Lake and River, MT. Avoid potential degradation. sample drawn from phone directories of four major cities adjacent to rural areas in MT personal interview ( na) OE $ 91.53 allocation

entire sample 171 $ 35.78 18 10 Walsh et al. ( 1978) WTP to postpone mining that would degrade water quality throughout the South Platte Basin ( CO) enough to permanently preclude riparian recreation ( 3 photos used); payments said to be used for water quality improvments to enhance recreational enjoyment. Amenity change is because damages would be irreversible, and preservation level has no heavy metals present/

contamination. random sample of households in Denver and Fort Collins, CO mail ( 0.62) IB $ 132.63 assume nonuse  value categories 174  205 $ 250.66 $ 211.42 25 16 Welle ( 1986) Prevention of acid deposition pollution that results in avoidance of decrease in MN water quality. representative sample of MN adults drawn from list of driver's license holders mail ( 0.61) OE $ 113.69 value categories

user /

nonuser 415 $ 20.06 $ 198.96 21 13 Whitehead & Groothuis ( 1992) Water quality improvement in the Tar Pamlico River due to implementation of Best Management Practices by farmers to reduce non point source pollution ( financed through state fund). Result would be doubled catch rate for anglers and general improvements in fishing,

swimming, boating, and drinking. Eastern NC households the Tar Pamlico River basin mail ( 0.51) OE $ 27.74 user /

nonuser total values 91 $ 18.49 March 12th, 2003 Page 6 of 157 5 1200  Studies Table Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 24 25 26 27 28 29 30 31 32 M N O P $ 45,978 river single water body 15 $ 44,674 rivers multiple water bodies 20 $ 44,674 rivers multiple water bodies 20 $ 44,674 rivers statewide 20 $ 44,674 rivers statewide 20 $ 39,907 river & lake single water body 15 $ 43,941 river basin local/ regional 8 $ 43,470 all freshwater statewide 16 $ 46,164 river single water body 22 March 12th, 2003 Page 7 of 157 5 1200  Studies Table Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 33 A B C D E F G H I J K L 3 2 Whitehead et al. ( 1995) WTP to make sure water pollution does not get worse and wildlife habitat remains the same.

Water quality and fish & wildlife habitat in the Albemarle Pamlico estuary system; benefits of estuaries ( incl. recreational use & nonuse)

described to respondents. 100 counties in NC, 16 counties in VA phone ( 0.84571428571428 6) IB $ 68.08 user /

nonuser total values 1033 $ 29.83 March 12th, 2003 Page 8 of 157 5 1200  Studies Table Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 33 M N O P $ 49,541 estuary single water body 25 March 12th, 2003 Page 9 of 157 5 1200  Studies Table Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 123456789 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 A B C D E Ratio Table for Non Users Table 5.1: Total Use and Non Use Values ( 2002$)

Author Survey Year Non Use Value Mean Total Use Value 29 Clonts & Malone ( 1990) 1987 $ 55.43 $ 30.88 13 Croke et al. ( 1986) 1986 $ 53.31 $ 17.61 14 Croke et al. ( 1986) 1986 $ 60.91 $ 11.11 15 Croke et al. ( 1986) 1986 $ 75.11 $ 6.35 19 Cronin ( 1982) 1973 $ 59.37 $ 23.75 20 Desvousges et al. ( 1983) 1981 $ 111.41 $ 89.65 1 Huang et al. ( 1997) 1995 $ 59.02 $ 158.25 2 Huang et al. ( 1997) 1995 $ 119.52 $ 97.75 24 Kaoru ( 1993) 1989 $ 112.57 $ 77.04 9 Lant & Roberts ( 1990) 1987 $ 68.56 $ 57.30 10 Lant & Roberts ( 1990) 1987 $ 88.40 $ 77.04 11 Lant & Roberts ( 1990) 1987 $ 85.29 $ 78.34 8 Magat et al. ( 2000) 1997 $ 11.49 $ 22.98 28 Mitchell & Carson ( 1981) 1980 $ 242.34 $ 275.09 16 Olsen et al. ( 1991) 1989 $ 38.48 $ 69.12 12 Roberts & Leitch ( 1997) 1996 $ 2.09 $ 5.17 26 Rowe et al. ( 1985) 1985 $ 69.15 $ 47.88 27 Rowe et al. ( 1985) 1985 $ 12.46 $ 6.54 4 Sanders et al. ( 1990) 1983 $ 46.91 $ 24.96 5 Sanders et al. ( 1990) 1983 $ 87.60 $ 46.62 6 Sanders et al. ( 1990) 1983 $ 111.99 $ 59.61 7 Sanders et al. ( 1990) 1983 $ 115.35 $ 63.45 17 Sutherland & Walsh ( 1985) 1981 $ 91.53 $ 35.78 18 Walsh et al. ( 1978) 1976 $ 132.63 $ 250.66 25 Welle ( 1986) 1985 $ 113.69 $ 20.06 21 Whitehead & Groothuis ( 1992) 1991 $ 27.74 $ 18.49 3 Whitehead et al. ( 1995) 1990 $ 68.08 $ 29.83 Median Value 1986 $ 74.41 $ 33.33 Mean Value 1986 $ 79.51 $ 68.61 March 12th, 2003 Page 10 of 157 5 1200  WTP Values Table  NU Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 123456789 10 A B C D E Ratio Table for Users Table 5.2: Total Use and Non Use Values for Resource Users ( 2002$)

Author Survey Year User Non Use Value Mean Total Use Value 29 Clonts & Malone ( 1990) 1987 $ 82.35 $ 30.88 20 Desvousges et al. ( 1983) 1981 $ 130.59 $ 89.65 18 Walsh et al. ( 1978) 1976 $ 211.42 $ 250.66 25 Welle ( 1986) 1985 $ 198.96 $ 20.06 Median Value 1983 $ 164.78 $ 60.27 Mean Value 1982 $ 155.83 $ 97.81 March 12th, 2003 Page 11 of 157 5 1200  WTP Values Table  U Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 1234 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 A B C D E F G H I J K L M WTP Values and Ratios  Concise All values expressed in $ 2002 Identification Pub Info Entire Sample: Users + Non Users User Values Non User Values Estimate ID Study ID Primary Author Survey/

Data Year Total Use Value ( use + option) Recreational Use Value ( direct) Total Non Use Value Total Use Value ( direct) Recreational Use Value ( direct) Indirect Use Value ( off site use) Total Non Use Value Actual / Imputed Non Use Value Total Non Use Value Plus Option Value 1 1 Huang et al. 1995 $ 158.3 $  $ 59.0 $  $  $  $  $

2 1 Huang et al. 1995 $ 97.8 $  $ 119.5 $  $  $  $  $

3 2 Whitehead et al. 1990 $  $  $  $ 29.8 $  $ 76.7 $ 68.1 I $ 68.1 4 3 Sanders et al. 1983 $ 25.0 $ 13.6 $ 46.9 $  $  $  $  $

5 3 Sanders et al. 1983 $ 46.6 $ 25.4 $ 87.6 $  $  $  $  $

6 3 Sanders et al. 1983 $ 59.6 $ 32.5 $ 112.0 $  $  $  $  $

7 3 Sanders et al. 1983 $ 63.5 $ 34.6 $ 115.3 $  $  $  $  $

8 4 Magat et al. 1997 $ 23.0 $  $ 11.5 $  $  $  $  $

9 5 Lant & Roberts 1987 $  $ 57.3 $ 68.6 $  $  $  $  $

10 5 Lant & Roberts 1987 $  $ 77.0 $ 88.4 $  $  $  $  $

11 5 Lant & Roberts 1987 $  $ 78.3 $ 85.3 $  $  $  $  $

12 6 Roberts &

Leitch 1996 $ 5.2 $ 2.4 $ 2.1 $  $  $  $  $

13 7 Croke et al. 1986 $  $  $  $ 17.6 $  $  $ 53.3 I $ 53.3 14 7 Croke et al. 1986 $  $  $  $ 11.1 $  $  $ 60.9 I $ 60.9 15 7 Croke et al. 1986 $  $  $  $ 6.4 $  $  $ 75.1 I $ 75.1 16 8 Olsen et al. 1989 $  $  $  $ 69.1 $ 69.1 $  $ 38.5 I $ 38.5 17 9 Sutherland & Walsh 1981 $ 35.8 $ 14.6 $ 91.5 $  $  $  $  $

18 10 Walsh et al. 1976 $  $  $  $ 250.7 $ 179.2 $  $ 211.4 A $ 132.6 19 11 Cronin 1973 $  $  $  $  $ 23.7 $  $ 59.4 I $ 59.4 20 12 Desvousge s et al. 1981 $  $  $  $ 89.7 $ 39.0 $  $ 130.6 A $ 111.4 March 12th, 2003 Page 12 of 157 5 1200  WTP Values and Ratios  concise Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 26 27 28 29 30 31 32 33 34 A B C D E F G H I J K L M 21 13 Whitehead & Groothuis 1991 $  $  $  $ 18.5 $  $  $ 27.7 I $ 27.7 22 14 Opaluch et al. 1995 $  $  $  $ 0.0 $  $  $ 0.1 I $ 0.1 23 14 Opaluch et al. 1995 $  $  $  $ 0.0 $  $  $ 0.1 I $ 0.1 24 15 Kaoru 1989 $ 77.0 $ 48.9 $ 112.6 $  $  $  $  $

25 16 Welle 1985 $  $  $  $ 20.1 $  $  $ 199.0 A $ 113.7 26 17 Rowe et al. 1985 $  $ 47.9 $ 69.2 $  $  $  $  $

27 17 Rowe et al. 1985 $ 6.5 $  $ 12.5 $  $  $  $  $

28 18 Mitchell &

Carson 1980 $  $  $  $ 275.1 $  $  $ 242.3 I $ 242.3 29 19 Clonts &

Malone 1987 $  $ 12.7 $  $ 30.9 $ 11.9 $  $ 82.3 A $ 55.4 March 12th, 2003 Page 13 of 157 5 1200  WTP Values and Ratios  concise Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 1234 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 A B C D E F G H I J K L M N O P Q R WTP Values and Ratios All values expressed in $ 2002 Identification Pub Info Entire Sample: Users + Non Users Estimate ID Study ID Primary Author Survey/

Data Year Total Sample WTP Total Sample WTP Desc. Total Use Value ( use + option) Total Use Value Desc. Recreational Use Value ( direct) Recreational Use Value Desc. ( direct) Option Value Option Value Desc. Total Non Use Value Total Non Use Value Desc. Existence Value Bequest Value Total User Value ( use +

non use value) Total Use Value ( direct)

1 1 Huang et al. 1995 $  0 $ 158.3 0 $  0 $  0 $ 59.0 0 $  $  $  $

2 1 Huang et al. 1995 $  0 $ 97.8 0 $  0 $  0 $ 119.5 0 $  $  $  $

3 2 Whitehead et al. 1990 $  0 $  0 $  0 $  0 $  0 $  $  $ 97.9 $ 29.8 4 3 Sanders et al. 1983 $  0 $ 25.0 0 $ 13.6 0 $ 11.3 0 $ 46.9 0 $ 20.4 $ 26.5 $  $

5 3 Sanders et al. 1983 $  0 $ 46.6 0 $ 25.4 0 $ 21.2 0 $ 87.6 0 $ 38.1 $ 49.5 $  $

6 3 Sanders et al. 1983 $  0 $ 59.6 0 $ 32.5 0 $ 27.1 0 $ 112.0 0 $ 48.8 $ 63.2 $  $

7 3 Sanders et al. 1983 $  0 $ 63.5 0 $ 34.6 0 $ 28.8 0 $ 115.3 0 $ 50.0 $ 65.4 $  $

8 4 Magat et al. 1997 $  0 $ 23.0 rec. value $  0 $  0 $ 11.5 0 $  $  $  $

9 5 Lant & Roberts 1987 $  0 $  0 $ 57.3 0 $  0 $ 68.6 0 $  $  $  $

10 5 Lant & Roberts 1987 $  0 $  0 $ 77.0 0 $  0 $ 88.4 0 $  $  $  $

11 5 Lant & Roberts 1987 $  0 $  0 $ 78.3 0 $  0 $ 85.3 0 $  $  $  $

12 6 Roberts &

Leitch 1996 $  0 $ 5.2 option + rec. $ 2.4 all respondents mean $ 2.8 all respondents mean, includes bequest value $ 2.1 0 $ 2.1 $  $  $

13 7 Croke et al. 1986 $  0 $  0 $  0 $  0 $  0 $  $  $ 70.9 $ 17.6 14 7 Croke et al. 1986 $  0 $  0 $  0 $  0 $  0 $  $  $ 72.0 $ 11.1 15 7 Croke et al. 1986 $  0 $  0 $  0 $  0 $  0 $  $  $ 81.5 $ 6.4 16 8 Olsen et al. 1989 $  0 $  0 $  0 $  0 $  0 $  $  $ 107.6 $ 69.1 March 12th, 2003 Page 14 of 157 5 1200  WTP Values and Ratios Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 1234 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 S T U V W X Y Z AA AB AC AD AE AF AG AH AI User Values Non User Values Total Use Value Desc. Recreational Use Value ( direct) Recreational Use Value Desc.

( direct) Indirect Use Value ( off site use) Option Value Option Value Desc. Total Non Use Value Actual / Imputed Non Use Value Total Non Use Value Desc. Existence Value Bequest Value Total Non Use Value Non Use Value Desc. Existence Value Bequest Value Option Value Option Value Desc.

$  $  0 $  $  0 $  0 $  $  $  0 $  $  $  0 0 $  0 $  $  0 $  0 $  $  $  0 $  $  $  0 0 $  0 $ 76.7 $  0 $ 68.1 I IMPUTED NON USE VALUE $  $  $ 68.1 0 $  $  $  0 0 $  0 $  $  0 $  0 $  $  $  0 $  $  $  0 0 $  0 $  $  0 $  0 $  $  $  0 $  $  $  0 0 $  0 $  $  0 $  0 $  $  $  0 $  $  $  0 0 $  0 $  $  0 $  0 $  $  $  0 $  $  $  0 0 $  0 $  $  0 $  0 $  $  $  0 $  $  $  0 0 $  0 $  $  0 $  0 $  $  $  0 $  $  $  0 0 $  0 $  $  0 $  0 $  $  $  0 $  $  $  0 0 $  0 $  $  0 $  0 $  $  $  0 $  $  $  0 0 $  0 $  $  0 $  0 $  $  $  0 $  $  $  0 IMPUTED NON USE VALUE $  0 $  $  0 $ 53.3 I IMPUTED NON USE VALUE $  $  $ 53.3 0 $  $  $  0 IMPUTED NON USE VALUE $  0 $  $  0 $ 60.9 I IMPUTED NON USE VALUE $  $  $ 60.9 0 $  $  $  0 IMPUTED NON USE VALUE $  0 $  $  0 $ 75.1 I IMPUTED NON USE VALUE $  $  $ 75.1 0 $  $  $  0 use value portion of total value ( Brown assumption of subtracting non use value from total, 74.16) $ 69.1 0 $  $  0 $ 38.5 I Assumes users to have same non use value as nonusers ( Brown) $  $  $ 38.5 Total value for nonusers with no probability of future use $  $  $  0 March 12th, 2003 Page 15 of 157 5 1200  WTP Values and Ratios Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 1234 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 AJ AK AL AM AN Nonuse Use Ratios Other Group Value Other Desc. Ratio Type ( 1= total pop, 0=

nonuseruser Total Population Ratio ( prioritizes total use as value as denom.) Nonuser User Ratio ( user non use value implied in some cases)

$  0 1 0.37 $  0 1 1.22 $  0 0 2.28 $  0 1 1.88 $  0 1 1.88 $  0 1 1.88 $  0 1 1.82 $  0 1 0.50 $  0 1 1.20 $  0 1 1.15 $  0 1 1.09 $  0 1 0.40 $  0 0 3.03 $  0 0 5.48 $  0 0 11.82 $ 84.96 Non users with some probability of future use 0 0.56 March 12th, 2003 Page 16 of 157 5 1200  WTP Values and Ratios Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 22 23 24 25 26 27 28 29 30 31 32 A B C D E F G H I J K L M N O P Q R 17 9 Sutherland & Walsh 1981 $  0 $ 35.8 Rec. + option values $ 14.6 Rec. value only $ 21.2 0 $ 91.5 existence +

bequest values $ 39.3 $ 52.2 $  $

18 10 Walsh et al. 1976 $  0 $  0 $  0 $  0 $  0 $  $  $  $ 250.7 19 11 Cronin 1973 $  0 $  0 $  0 $  0 $  0 $  $  $ 83.1 20 12 Desvousge s et al. 1981 $  0 $  0 $  0 $  0 $  0 $  $  $  $ 89.7 21 13 Whitehead & Groothuis 1991 $ 33.0 combined user &

nonuser groups $  0 $  0 $  0 $  0 $  $  $ 46.2 $ 18.5 22 14 Opaluch et al. 1995 $ 0.06 combined user &

nonuser groups $  0 $  0 $  0 $  0 $  $  $ 0.1 $ 0.003 23 14 Opaluch et al. 1995 $ 0.06 combined user &

nonuser groups $  0 $  0 $  0 $  0 $  $  $ 0.1 $ 0.015 24 15 Kaoru 1989 $  0 $ 77.0 0 $ 48.9 use of ponds for shellfishing $ 28.2 0 $ 112.6 0 $ 112.6 $  $  $

25 16 Welle 1985 $  0 $  0 $  0 $  0 $  0 $  $  $  $ 20.1 26 17 Rowe et al. 1985 $ 117.0 0 $  0 $ 47.9 verify w/

Elena, used unit estimate from rec.

analysis $  0 $ 69.2 apparently option value $  $  $  $

27 17 Rowe et al. 1985 $ 19.4 0 $ 6.5 0 $  0 $  0 $ 12.5 0 $ 6.5 $ 6.0 $  $

March 12th, 2003 Page 17 of 157 5 1200  WTP Values and Ratios Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 22 23 24 25 26 27 28 29 30 31 32 S T U V W X Y Z AA AB AC AD AE AF AG AH AI 0 $  0 $  $  0 $  0 $  $  $  0 $  $  $  0 Rec. +

option values $ 179.2 0 $  $ 71.5 0 $ 211.4 A existence +

bequest $ 107.1 $ 104.4 $ 132.6 existence +

bequest $ 79.0 $ 53.7 $  0 0 $ 23.7 assumed rec value, FISHER VALUE DEFLATED TO 1973$ $  $  0 $ 59.4 I IMPUTED NON USE VALUE FISHER VALUE DEFLATED TO 1973$ $  $  $ 59.4 FISHER VALUE DEFLATED TO 1973$ $  $  $  0 rec. + option value $ 39.0 p. 4 37 $  $ 50.6 0 $ 130.6 A 0 $ 130.6 $  $ 83.3 0 $ 83.3 $  $ 28.1 current non user option value imputed nonuse value subtracted from use value reported in study $  0 $  $  0 $ 27.7 I IMPUTED NON USE VALUE $  $  $ 27.7 0 $  $  $  0 imputed nonuse value subtracted from use value reported in study $  0 $  $  0 $ 0.1 I IMPUTED NON USE VALUE $  $  $ 0.054 0 $  $  $  0 imputed nonuse value subtracted from use value reported in study $  0 $  $  0 $ 0.1 I IMPUTED NON USE VALUE $  $  $ 0.053 0 $  $  $  0 0 $  0 $  $  0 $  0 $  $  $  0 $  $  $  0 rec value +

deman side option value $  0 $  $  0 $ 199.0 A 0 $ 199.0 $  $ 113.7 0 $ 113.7 $  $  0 0 $  0 $  $  0 $  0 $  $  $  0 $  $  $  0 0 $  0 $  $  0 $  0 $  $  $  0 $  $  $  0 March 12th, 2003 Page 18 of 157 5 1200  WTP Values and Ratios Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 22 23 24 25 26 27 28 29 30 31 32 AJ AK AL AM AN $  0 1 2.56 $  0 0 0.53 $  0 0 2.50 $  0 0 1.24 $  0 0 1.50 $  0 0 16.79 $  0 0 3.48 $ 210.37 total N 1 1.46 $  0 0 5.67 $  0 1 1.44 $  0 1 1.91 March 12th, 2003 Page 19 of 157 5 1200  WTP Values and Ratios Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 33 34 A B C D E F G H I J K L M N O P Q R 28 18 Mitchell &

Carson 1980 $ 423.6 User and Nonuser group combined mean WTP $  0 $  0 $  0 $  0 $  $  $ 517.4 $ 275.1 29 19 Clonts &

Malone 1987 $ 90.3 0 $  0 $ 12.7 0 $ 15.0 0 $  0 $ 35.6 $ 26.9 $ 110.9 $ 30.9 March 12th, 2003 Page 20 of 157 5 1200  WTP Values and Ratios Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 33 34 S T U V W X Y Z AA AB AC AD AE AF AG AH AI imputed nonuse value subtracted from use value reported in study $  0 $  $  0 $ 242.3 I IMPUTED NON USE VALUE $  $  $ 242.3 0 $  $  $  0 0 $ 11.9 0 $  $ 19.0 0 $ 82.3 A 0 $ 45.9 $ 36.4 $ 43.5 0 $ 25.3 $ 18.2 $ 11.9 0 March 12th, 2003 Page 21 of 157 5 1200  WTP Values and Ratios Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 33 34 AJ AK AL AM AN $  0 0 0.88 $  0 0 1.79 March 12th, 2003 Page 22 of 157 5 1200  WTP Values and Ratios Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 12345 6 7 8 9 10 11 12 13 14 A B C D E F G H I J K L M N Meta Data 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Study and Estimate Idenification Publication Information Estimate ID Study ID Study Estimate # Benlit ID Estimate Alpha ID Primary Author Authors Publication Publication Year Survey/ Data Year Survey Type Geographic Area or State State Survey Region 1 1 1 1070 A Huang Huang et al. JEEM 1997 1995 combined revealed &

stated preference NC NC 1 2 1 2 1070 B Huang Huang et al. JEEM 1997 1995 combined revealed &

stated preference NC 1 3 2 1 1160 C Whitehead Whitehead et al. JEEM 1995 1990 CV 100 Counties in NC; 16 counties/

cities in VA NC 1 4 3 1 1251 D Sanders Sanders et al. WRR 1990 1983 CV CO CO 4 5 3 2 1251 E Sanders Sanders et al. WRR 1990 1983 CV CO 4 6 3 3 1251 F Sanders Sanders et al. WRR 1990 1983 CV CO 4 7 3 4 1251 G Sanders Sanders et al. WRR 1990 1983 CV CO 4 8 4 1 1202 H Magat Magat et al. JRU 2000 1997 Iterative referendum Research Triangle Park,

Charlotte, and Cary NC, &

Denver & CO Springs CO/ NC 5 March 12th, 2003 Page 23 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 12345 6 7 8 9 10 11 12 13 14 O P Q R S T U V W X 15 16 17 18 19 20 21 22 23 24 Survey/ Sample Characteristics Admin Method ( i. e. mail, phone etc.) ADMIN METHOD Sample/ Population Desc. Sample Population For Table Sample Size for Table Sample Size Description Response Rate Response Rate for Table Response Rate Not Applicable/ A vailable Users telephone 2 1077 Eastern NC households eastern NC households 511 seems to be regression sample 75% 75%

2 eastern NC households 511 75% 75%

telephone 2 Says 1133 in study, but groups add up to 1033, as in study 1151, which seems to use the same data; 2 groups: on site and off site users 100 counties in NC,

16 counties in VA 1033 total of 3 user groups samples used in 3 regressions ( off site and on site users, and non users) 71% 71% $ 40,325 mail ( 10% of nonrespondents contacted by phone) 1 214; sample of CO residents designed to be rep. of state CO residents; representative of state 214 214 is WTP sample, but 163 responses were used in regression analyses. FOOTNOTE 51% 51%

1 CO residents; representative of state 214 51% 51%

1 CO residents; representative of state 214 51% 51%

1 CO residents; representative of state 214 51% 51%

Personal interviews ( central & intercept) 3 410 ( 409?), 348 used ( 100 in Denver, 101 in CO Springs, 49 in Cary NC, 53 in Charlotte NC, 106 in RTP NC) various populations in CO and NC 348 regression sample, and seems to be nonuse sample, nonuse samples 173 and 121 may be subsets ( p. 37) na 1 March 12th, 2003 Page 24 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 12345 6 7 8 9 10 11 12 13 14 Y Z AA AB AC AD AE 25 26 27 28 29 30 31 Income Non users Entire Sample ( or other) Income Imputed Income Notes Amenity Description Amenity Description for Specific Nonuse Use Estimate ( for Table) Scale $ 31,766 Total sample ( 511) restoration of quality of Pamlico and Albemarle Sounds to 1981 level in terms of increase of fish catches and shellfish beds program to restore quality of Pamlico and Albemarle Sounds to 1981 level in terms of increased of fish catches and shellfish beds 1 $ 31,766 Total sample ( 511) program to restore quality of Pamlico and Albemarle Sounds to 1981 level in terms of increased of fish catches and shellfish beds 1 $ 31,659 $ 35,992 WTP to make sure water pollution does not get worse and wildlife habitat remains the same. Water quality and fish &

wildlife habitat in the Albemarle Pamlico estuary system;

benefits of estuaries ( incl. recreational use & nonuse)

described to respondents. avoid degradation in water quality and fish and wildlife habitat in the Albemarle

Pamlico estuary system, NC 1 $ 24,733.20 1 1984 median income for CO, deflated to 1983 using CPI protection of a specific # of CO rivers ( incremental WTP) in,

described as " wild" and " scenic" rivers with an array of possible benefits, which respondents are asked to indicate program to protect 3 of 11 most valuable wild and scenic CO rivers 2 $ 24,733.20 1 1984 median income for CO, deflated to 1983 using CPI program to protect 7 of 11 most valuable wild and scenic CO rivers 2 $ 24,733.20 1 1984 median income for CO, deflated to 1983 using CPI program to protect 11 wild and scenic CO rivers 4 $ 24,733.20 1 1984 median income for CO, deflated to 1983 using CPI program to protect 11 wild and scenic CO rivers plus an additional 4 other rivers 4 $ 40,400.00 represents " consistent" sample,

full sample mean is $ 38,700 Water quality is defined as " good" ( safe to swim, eat fish,

supports many plants, fish and other aquatic life) or " not good"

( unsafe to swim & eat fish, only supports small # of plants &

aquatic life). water quality in lakes and rivers near hypothetical location respondent ( CO & NC) might live base on 3 dimensions: aquatic life support, fish consumption, &

swimming 15% increase in " good" water quality in lakes and rivers in the region where a respondent may hypothetically live 3 March 12th, 2003 Page 25 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 12345 6 7 8 9 10 11 12 13 14 AF AG AH AI AJ AK AL AM AN AO AP AQ 32 33 34 35 36 37 38 39 40 41 42 43 Resource Characteristics Water Quality Ladder Amenity Change Envr Change Affects All/ Other Recreational Uses Fishery ( rec. comm.

gen.) Envr. Change Introduces/

Avoids Loss of Fishing as Use Envr. Change Affects Game Fish Waterbody Type Waterbody Type Waterbody Type Code Special Significance Other Recreational Uses Increase in Catch Rate/

Quantity Change Ecological Services/ Other Estimated Values 0 1 general? 0 0 estuary E 2 1 0 1 0 0 estuary E 2 1 0 1 general? 0 0 estuary E 2 0 0 1 recreational 0 0 rivers R 3 0 0 1 0 0 rivers R 3 0 0 1 0 0 rivers R 3 0 0 1 0 0 rivers R 3 0 9 1 mostly rec.? 1 0 all freshwater ( lakes &

rivers) B 5 0 March 12th, 2003 Page 26 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 12345 6 7 8 9 10 11 12 13 14 AR AS AT AU AV AW AX AY AZ BA 44 45 46 47 48 49 50 51 52 53 Elicitation Design Payment Mechanism Payment Mechanism for Table Elicitation Method Elicitation Method Non Use Method Non Use Method Desc. Non Use Method Code User Nonuse Value Use Nonuse Design Notes # of Use

Nonuse Estimates policy? 1 DC DB revealed &

stated 5 Questions determined recreation participation, travel cost model combined with CV to estimate consumer surplus and TOTAL use and non use values. 2 1 DC DB revealed &

stated 5 same as above 2 tax increase 2 IB referendum w/ OE for NO votes user /

nonuser total values 1 onsite users had engaged in fishing, swimming, boating,

etc. within the past year, off site users answered " a little,"

" some," or " a lot," to the question " how much have you heard or read about the resources, uses and problems of the A P system?," and who are not on site users. Non users answered " nothing" to this question and are not on site users. 1 earmarked trust fund 3 OE direct question allocation

entire sample 3 All respondents asked to value river protection incrementally, and then asked to allocate WTP across 4 categories, which are phrased to represent recreational uses, option, existence, and bequest values. 4 earmarked trust fund 3 OE direct question allocation

entire sample 3 same as above 4 earmarked trust fund 3 OE direct question allocation

entire sample 3 same as above 4 earmarked trust fund 3 OE direct question allocation

entire sample 3 same as above 4 taxes 2 Iterative bidding referendum? assume nonuse 4 Respondents value water quality in regions other than where they live if the probability of them visiting a site is 0,

1/ 3, or 1/ 10.  Use value seems to be derived from 1/ 2 of total sample, which includes non users and users. 1 March 12th, 2003 Page 27 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 12345 6 7 8 9 10 11 12 13 14 BB BC BD BE BF BG 54 55 56 57 58 59 Model Type/ Specification Elicitation/ Model Notes Amenity / WTP Notes Estimate Desc. Significance of WTP Estimates Metric joint variation function Annual WTP for program to restore A P estuaries, unsure of length. Travel cost model combined with CV to estimate consumer surplus and TOTAL use and non use values. Chose only single bounded model non use estimate ( see study). Need to determine difference between 2 non use estimates calculated by comparing with revealed data, no nonuse WTP estimates given. annual WTP for program,

unsure of length same as above annual WTP for program,

unsure of length Tobit Annual WTP for program to protect A P system in terms of water quality and fish & wildlife habitat; benefits of estuaries ( incl. recreational use & nonuse). Mean WTP of off site users are currently not considered ( see use nonuse design). annual WTP for program to protect A P system separate model for each user group, but likelihood ratior tests for equivalence of vectors of coefficients sare significantly different from each other at p = 0.01 level.

OLS Protection of a specific # of CO rivers ( incremental WTP), described as " wild" and " scenic"

with an array of possible benefits. Annual household WTP for program; 7 ( of 11) most valuable rivers. All WTP estimates are from one sample where each respondent was asked to allocate total among 4 groups. annual household WTP for program; 3 ( of 11) most valuable rivers AHH Protection of a specific # of CO rivers ( incremental WTP), described as " wild" and " scenic"

with an array of possible benefits, which respondents are asked to indicate. Annual household WTP for program; 3 ( of 11) most valuable rivers. All WTP estimates are from one sample where each respondent was asked to allocate total among 4 groups. annual household WTP for program; 7 ( of 11) most valuable rivers AHH Protection of a specific # of CO rivers ( incremental WTP), described as " wild" and " scenic"

with an array of possible benefits, which respondents are asked to indicate. Annual household WTP for program; 11 study rivers. All WTP estimates are from one sample where each respondent was asked to allocate total among 4 groups. annual household WTP for program; 11 study rivers AHH Protection of a specific # of CO rivers ( incremental WTP), described as " wild" and " scenic"

with an array of possible benefits, which respondents are asked to indicate. Annual household WTP for program; 11 study rivers. All WTP estimates are from one sample where each respondent was asked to allocate total among 4 groups. annual household WTP for program; 11 study rivers + 4 additional most common " other" rivers to protect AHH OLS, tobit,

corrected, etc.

( see study) Water quality in lakes and rivers near hypothetical location respondent ( CO & NC) might live base on 3 dimensions: aquatic life support, fish consumption, & swimming. WTP is for 1%

increase in water quality derived from iterative referendum. Low R2 ( 0.13 fo OLS model); may exclude Research Triangle Park sample due to nonrepresentativeness ( income, education,

etc.) and low mean WTP; see other nonuse caveat, p. 37 1% increase in water quality derived from iterative referendum March 12th, 2003 Page 28 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 12345 6 7 8 9 10 11 12 13 14 BH BI BJ BK BL BM BN BO BP BQ BR BS BT BU BV BW 25 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 Willingness To Pay ( means Entire Sample: Users + Non Users Usable Estimate Total Sample WTP Total Sample WTP Desc. Total Use Value ( use + option) Total Use Value Desc. Recreational Use Value ( direct) Recreational Use Value Desc. ( direct) Option Value Option Value Desc. Total Non Use Value Total Non

Use Value Desc. Existence Value Bequest Value Imputed Non use Value Total User Value ( use +

non use value) Total Use Value ( direct)

1 $ 134.06 $ 50.00 1 $ 82.81 $ 101.25 1 X $ 71.13 $ 21.67 1 $ 13.82 $ 7.54 $ 6.28 $ 25.97 $ 11.31 $ 14.66 1 $ 25.81 $ 14.08 $ 11.73 $ 48.50 $ 21.12 $ 27.38 1 $ 33.00 $ 18.00 $ 15.00 $ 62.00 $ 27.00 $ 35.00 1 $ 35.13 $ 19.16 $ 15.97 $ 63.86 $ 27.67 $ 36.19 1 $ 20.50 rec. value $ 10.25 March 12th, 2003 Page 29 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 12345 6 7 8 9 10 11 12 13 14 BX BY BZ CA CB CC CD CE CF CG CH CI CJ CK 76 77 78 79 80 81 82 83 84 85 86 87 88 89 unless otherwise noted) User Values Total Use Value Desc. Recreational Use Value ( direct) Recreational Use Value Desc.

( direct) Indirect Use Value ( off site use) Indirect Use Value Option Value Option Value Desc. Total Non Use Value Total Non Use Value Desc. Existence Value Bequest Value Total Value ( use + nonuse Total Non

Use Value Non Use Value Desc.

$ 55.76 off site users, not currently using $ 49.46 IMPUTED NONUSE VALUE $ 49.46 March 12th, 2003 Page 30 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 12345 6 7 8 9 10 11 12 13 14 CL CM CN CO CP CQ CR CS CT CU CV CW 90 91 92 93 94 95 96 97 98 99 100 101 Non User Values Sample Sizes for WTP Estimation Unless Otherwise Stated Existence Value Bequest Value Option Value Option Value Desc. Use Value Use Value Desc. Other Group Value Other Desc. Use N Non Use N Other Group N Other Group N Desc.

262 192 454 off site users 163 163 163 163 163 163 163 or 214? 163 or 214?

348 348 March 12th, 2003 Page 31 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 15 16 17 18 19 20 21 22 23 A B C D E F G H I J K L M N 9 5 1 1085 I Lant Lant & Roberts EP 1990 1987 CV 14 towns in IA and IL IA/ IL 2 10 5 2 1085 J Lant Lant & Roberts EP 1990 1987 CV IA/ IL 2 11 5 3 1085 K Lant Lant & Roberts EP 1990 1987 CV IA/ IL 2 12 6 1 1128 L Roberts Roberts &

Leitch NDSU DAE 1997 1996 CV Minnesota South Dakota border MN/ SD 2 13 7 1 1168 M Croke Croke et al. JES 1986 1986 CV Cook County, IL ( includes Chicago and surrounding suburbs) IL 2 14 7 2 1168 N Croke Croke et al. JES 1986 1986 CV IL 2 15 7 3 1168 O Croke Croke et al. JES 1986 1986 CV IL 2 16 8 1 1114 P Olsen Olsen et al. RV 1991 1989 CV Pacific Northwest Households ( Washington,

Oregon, Idaho,

W. Montana) Pacific NW ( ID,

MT, OR, WA) 4 17 9 1 1252 Q Sutherland Sutherland &

Walsh LE 1985 1981 CV Flathead River and Lake area,

MT MT 4 March 12th, 2003 Page 32 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 15 16 17 18 19 20 21 22 23 O P Q R S T U V W X Personal interviews 3 200 interviews completed,

drawn from telephone directories residents in 14 towns in IA and IL, drawn from telephone listings 195 regression sample 41% 41%

3 residents in 14 towns in IA and IL, drawn from telephone listings 195 regression sample 41% 41%

3 residents in 14 towns in IA and IL, drawn from telephone listings 195 regression sample 41% 41%

mail 1 Random sample of 1034 households within 30 mile radius of Lake, resulting in 575 respondents random sample of housholds within 30 mile radius of Mud Lake 575 non parametric sample FOOTNOTE 62% 62% NA phone 2 350 households households in Chicago and suburbs 296 user + nonuser non parametric sample  different sample sizes for different quality improvements FOOTNOTE 85% 85% 1 2 households in Chicago and suburbs 279 user + nonuser non parametric sample  different sample sizes for different quality improvements FOOTNOTE 85% 85% 1 2 households in Chicago and suburbs 280 user + nonuser non parametric sample  different sample sizes for different quality improvements FOOTNOTE 85% 85% 1 phone 2 2907 ( 695 usable nonuse,

700 use), sampled from Pacific Northwest residents with phones Pacific Northwest residents with phones 1177 Non  parametric FOOTNOTE; 695 usable nonuser questionnaires and 482 usable user questionnaires 73% 73% NA mail 1 171 usable of 280 sent surveys; drawn from phone directories of 4 major cities adjacent to rural areas in the state. sample drawn from phone directories of four major cities adjacent to rural areas in MT 171 regression sample 61% 61%

March 12th, 2003 Page 33 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 15 16 17 18 19 20 21 22 23 Y Z AA AB AC AD AE $ 24,637.00 1 average of IL and IA 1987 median income ( census) Local river quality on a scale defined by ' poor,' ' fair,' ' good,' or ' excellent,' represented by photographs. The levels of quality framed by the recreational uses they support. improvement in local river water quality from poor to fair in selected river basins in IA & IL 3 $ 24,637.00 1 average of IL and IA 1987 median income ( census) improvement in local river water quality from fair to good in selected river basins in IA & IL 3 $ 24,637.00 1 average of IL and IA 1987 median income ( census) improvement in local river water quality from good to excellent in selected river basins in IA & IL 3 NA $ 26,509.77 1 average of 1989 county median income for counties assumed to be surveyed, inflated 10 1996 w/ CPI Various economic outputs ( recreation, aesthtics, fish/ wildlife habitat etc.) of Mud Lake, a lacustrine wetland with recreational, aesthetic, and other uses. " If Mud Lake was managed primarily for water related recreation and fish/ wildlife habitat, what would you be willing to pay through an annual use permit to participate in recreational activities at Mud Lake?" Additional questions for existence & option values. water related recreation and fish and wildlife habitat at Mud Lake, MN SD 1 $ 28,878.72 1 1989 Cook Co. IL median income deflated to 1986 w/ CPI ( census) Improvement in water quality, defined by 3 levels allowing outings, outings & boating, and outings, boating & fishing,

respectively. water quality improvement from unusable to a level suitable for outings in urban Chicago rivers 3 $ 28,878.72 1 1989 Cook Co. IL median income deflated to 1986 w/ CPI ( census) water quality improvement from unusable to a level suitable for outings & boating in urban Chicago rivers 3 $ 28,878.72 1 1989 Cook Co. IL median income deflated to 1986 w/ CPI ( census) water quality improvement from unusable to a level suitable for outings, boating, &

fishing in urban Chicago rivers 3 NA $ 27,209.00 1 Average of 1989 state median income of ID,

MT, OR, & WA Doubling the Columbia River Basin salmon and steelhead runs ( framed for users as more fish available for ocean and river basin sport catch, with assurances of ecological stability and diversity). doubling the Columbia River Basin salmon & steelhead runs with the assurance of ecological stability and diversity 1 $ 20,164.21 1 Average of 1979 median income for 4 MT counties where survey was thought to be administered.

Inflated to 1981 w/ CPI. Protection of water quality in Flathead Lake and River, MT.

Avoid potential degradation. protection of water quality in Flathead Lake and River, MT, to avoid potential degradation 1 March 12th, 2003 Page 34 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 15 16 17 18 19 20 21 22 23 AF AG AH AI AJ AK AL AM AN AO AP AQ 3 0 1 0 rivers R 3 no 0 4 0 1 1 rivers R 3 0 5 1 0 0 rivers R 3 0 0 1 rec. 0 0 wetland W 4 0 flood control, water supply, drinking water quality 1 1 0 0 urban rivers R 3 0 2 1 0 0 urban rivers R 3 0 3 0 1 0 urban rivers R 3 0 0 0 0 0 river R 3 1 regional sport values for increasing marginal catch in various waterbodies 0 1 0 0 river & lake B 1 0 March 12th, 2003 Page 35 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 15 16 17 18 19 20 21 22 23 AR AS AT AU AV AW AX AY AZ BA state sales tax 4 Payment card? value categories

entire sample 2 All respondents asked valuation questions to elicit both recreation and intrinsic values for water quality changes. 3 state sales tax 4 Payment card? value categories

entire sample 2 same as above 3 state sales tax 4 Payment card? value categories

entire sample 2 same as above 3 Use permit for use value, voluntary donation fro option/ bequest values and existence values 4 Payment card? value categories

entire sample 2 Three separate questions asked for a choice of $ 0 WTP or 5 other categorise for each of the value components: use,

option/ bequest, existence. 1 2 Iterative Bidding user /

nonuser total values 1 Respondents were questioned on their frequency of river use and the types of activities engaged in, and separated into user & non user groups accordingly. 3 2 Iterative Bidding user /

nonuser total values 1 same as above 3 2 Iterative Bidding user /

nonuser total values 1 same as above 3 Increased cost of monthly power bill ( contribution to state fishery agency for payment vehicle protests or those concerned about involvement of power industry) 3 OE ( modified) user /

nonuser total values 1 Resource nonuseres defined as " individuals who have not been involved in the commercial fishing industry and who have not participated in the sport fishery during the past 2 years." Those who answered " no" or " uncertain" to the relevant question were considered to have a zero probability of furture use. Individuals who stated they did not expect to fish for these species in the next 5 years according to Brown, 1992, were considered to have some probability of future use. 1 Earmarked fund. 3 OE allocation

entire sample 3 One sample group: All responents first asked to state max WTP, then to allocate across recreational use, option,

existence, and bequest demands. 1 March 12th, 2003 Page 36 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 15 16 17 18 19 20 21 22 23 BB BC BD BE BF BG WTP for change in quality from poor to fair. Local river quality on a scale defined by ' poor,'

' fair,' ' good,' or ' excellent,' represented by photographs. The levels of quality framed by the recreational uses they support. Need to account for scope differences in multiple estimates. WTP for change in quality from poor to fair YES  not available, but model adjusted R squared =

.309, and F= 0.0001, with reasons for protecting resource associated with intrinsic values significant,

see p. 1382.

WTP for change in quality fair to good. Local river quality on a scale defined by ' poor,' ' fair,'

' good,' or ' excellent,' represented by photographs. The levels of quality framed by the recreational uses they support. Need to account for scope differences in multiple estimates. WTP for change in quality fair to good WTP for change in quality from good to excellent. Local river quality on a scale defined by ' poor,' ' fair,' ' good,' or ' excellent,' represented by photographs. The levels of quality framed by the recreational uses they support. Need to account for scope differences in multiple estimates. WTP for change in quality from good to excellent WTP for water related recreation and fish/ wildlife habitat ( and other economic outputs incl.

flood control, DW quality) of Mud Lake, a lacustrine wetland. Estimates are from 3 separate Q's, and were obtained from 1 group of respondents. Is option/ bequest estimate a use or nonuse value? ( currently included as use). Question: " What is the maximum amount you would be willing to pay through an annual voluntary donation to ensure that recreational activities and fish/ wildlife habitat at Mud lake are available in the future to you or your descendants?" WTP for water related recreation and fish/ wildlife habitat WTP for improved water quality to allow outings. User WTP includes nonuse ( intrinsic) values,

as groups were separated by frequency of use questioning. WTP for improved water quality to allow outings. NA, but "  users and nonusers constitute distinct populations who react differently to the expanding opportunity set in the contingent market."" p. 21 WTP for improved water quality to allow outings & boating. User WTP includes nonuse ( intrinsic) values, as groups were separated by frequency of use questioning. WTP for improved water quality to allow outings &

boating.

WTP for improved water quality to allow outings, boating, & fishing. User WTP includes nonuse ( intrinsic) values, as groups were separated by frequency of use questioning. WTP for improved water quality to allow outings,

boating, & fishing.

Doubling the Columbia River Basin salmon and steelhead runs ( framed for users as more fish available for ocean and river basin sport catch, with assurances of ecological stability and diversity). All estimates are assumed to be " total value" estimates by author. We could use a non use/ use ratio for users as Brown did ($ 26.52/$ 47.64). Brown only included WTP of nonusers's with some probability of future use in footnote. Annual WTP for doubling size of fish run NA Protection of water quality in Flathead Lake and River, MT. Annual WTP for protection of water quality March 12th, 2003 Page 37 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 15 16 17 18 19 20 21 22 23 BH BI BJ BK BL BM BN BO BP BQ BR BS BT BU BV BW 1 $ 36.18 $ 43.29 1 $ 48.65 $ 55.82 1 $ 49.47 $ 53.86 1 $ 4.51 option +

rec. $ 2.08 all respondents mean $ 2.43 all responde nts mean,

includes bequest value $ 1.82 $ 1.82 1 X $ 43.21 $ 10.73 1 X $ 43.88 $ 6.77 1 X $ 49.63 $ 3.87 1 X $ 74.16 $ 47.64 1 $ 18.08 Rec. +

option values $ 7.37 Rec. value only $ 10.71 $ 46.25 existence +

bequest values $ 19.88 $ 26.37 March 12th, 2003 Page 38 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 15 16 17 18 19 20 21 22 23 BX BY BZ CA CB CC CD CE CF CG CH CI CJ CK IMPUTED NON USE VALUE $ 32.48 IMPUTED NONUSE VALUE $ 32.48 IMPUTED NON USE VALUE $ 37.11 IMPUTED NONUSE VALUE $ 37.11 IMPUTED NON USE VALUE $ 45.76 IMPUTED NONUSE VALUE $ 45.76 use value portion of total value ( Brown assumption of subtracting non use value from total,

74.16) $ 47.64 $ 26.52 Assumes users to have same non use value as non users ( Brown) $ 26.52 Total value for nonusers with no probability of future use March 12th, 2003 Page 39 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 15 16 17 18 19 20 21 22 23 CL CM CN CO CP CQ CR CS CT CU CV CW 28 268 27 252 27 253 $ 58.56 Nonusers with some probabili ty of future use 171 171 March 12th, 2003 Page 40 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 24 25 26 27 28 29 30 A B C D E F G H I J K L M N 18 10 1 1242 R Walsh Walsh et al. EPA 1978 1976 CV South Platte River Basin, CO CO 4 19 11 1 1288 ( 1194) S Cronin Cronin PNL 1982 1973 CV Washington D. C., along Potomac River DC 1 20 12 1 1289 ( 1194) T Desvousges Desvousges et al. AAM 1983 1981 CV 5 counties in PA PA 1 21 13 1 1295 U Whitehead Whitehead &

Groothuis RV 1992 1991 CV Eastern N.

Carolina NC 1 22 14 1 1314 V Opaluch Opaluch et al. URID 1999 1995 CJ East End of Long Island, NY NY 1 23 14 2 1314 W Opaluch Opaluch et al. URID 1999 1995 CJ NY 1 24 15 1 1262 X Kaoru Kaoru EREC 1993 1989 CV Martha's Vineyard MA 1 March 12th, 2003 Page 41 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 24 25 26 27 28 29 30 O P Q R S T U V W X personal interviews ( household) 3 202 random resident households in Denver &

Fort Collins, CO. random sample of households in Denver and Fort Collins, CO 174  205 FOOTNOTE, doesn't seem to be parametric; sample size varies for estimates of different value types 174 for recreation use, 177 for option value, and 203 for existence value, and 205 for bequest value na 1 personal interview 3 1579 of 1844 attempted interviews were completed;

drawn from Council of Gov's Metopolitan Parcel File of residential properties, intended to be representative of pop. representative sample of Washington D. C.

residences 1432 p. 6.9 82% 82%

personal interview in respondents homes 3 301 households housholds in five counties in PA 205 280 FOOTNOTE, existence  205,

option  211, rec  280 81% 81% $ 20,833.00 mail 1 109 responses of 179 sample ( 97 usable WTP responses); households in counties in the Tar Pamlico River basin. Eastern NC households the Tar

Pamlico River basin 91 full regression sample ( 26 users and 65 nonusers) 61% 61%

personal interview 3 967 individuals in the east end of Long Island, NY 968 total completed surveys na 1 3 individuals in the east end of Long Island, NY 968 total completed surveys na 1 mail 1 559 property owners,

randomly selected from property tax assessor's books, 274 returned. random sample of Martha's Vineyard property owners 145 regression sample 49% 49%

March 12th, 2003 Page 42 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 24 25 26 27 28 29 30 Y Z AA AB AC AD AE $ 13,898.00 Average of average income for Ft. Collins and Denver area ($ 14958; $ 12838;

same N for both groups). Study stated " a comparison of sample and population demographic characteristics showed little sample bias." WTP to postpone mining that would degrade water quality throughout the South Platte Basin ( CO) enough to permanently preclude riparian recreation ( 3 photos used);

payments said to be used for water quality improvments to enhance recreational enjoyment. Amenity change is because damages would be irreversible, and preservation level has no heavy metals present/ contamination. postpone mining to avoid degradation in water quality throughout the South Platte River Basin, CO, to avoid permanent preclusion of riparian recreation ( to a level absent of heavy metals / contamination) 3 $ 14,042.26 1 DC MSA income in 1969, inflated to 1973 w/ CPI ( study stated that sample stratified to represent MSA's income) Change from useable for recreation to boating. Incremental WTP for water quality of the Potomac River. Five levels of water quality are based on low flow, high temperature conditions, differing in 5 physical and biochemical characteristics ( levels of DO, fecal coliform, nitrogen,

phosphorous, and turbidity). prevent the degradation of water quality in the Potomac River from boatable to unusable for recreation 1 $ 18,867.00 $ 19,536.00 MEAN INCOME User & non user incomes not statistically different from each other. From table 4 3,

what year dollars? Various water quality levels on the Monongahela River, using RFF water quality ladder: 1) avoid decrease in quality from boatable to not suitable for recreation, 2) improve quality from boatable to where game fish could survive, 3) improve quality from fishable to swimmable. 4 elicitation methods used, valuing all 3 levels each. WTP value obtained to avoid decrease, and then incremental values for 2 levels of improvement ( p. 5 25) prevent the degradation of water quality in the Monongahela River from boatable to unusable for recreation 1 $ 34,950 Water quality improvement in the Tar Pamlico River due to implementation of Best Management Practices by farmers to reduce non point source pollution ( financed through state fund). Result would be doubled catch rate for anglers and general improvements in fishing, swimming, boating, and drinking. water quality improvement in the Tar

Pamlico River due to program to reduce non point source pollution, resulting in double catch rate for anglers & general improvements in fishing, swimming,

boating, and drinking 1 $ 56,641 1 3 scenarios for both Eelgrass habitat and wetlands habitat in the Peconic estuary area: baseline (" no new action") level of degradation by 2020, program to restore, and program to preserve the resource, in terms of acreage. wetlands protection in the Peconic estuary system, NY 1 $ 56,641 1 eelgrass protection in the Peconic estuary system, NY 1 $ 94,908 after tax income;

mean value for 145 responses used for WTP functions Poor to fair. Water quality improvement in 3 coastal ponds to allow them to be open for shellfishing year round ( some were closed at time of survey). improvement in water quality of 3 coastal ponds on Martha's Vineyard, MA to allow them to be open year round for shellfishing ( poor to fair) 2 March 12th, 2003 Page 43 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 24 25 26 27 28 29 30 AF AG AH AI AJ AK AL AM AN AO AP AQ 7 1 0 0 river basin R 3 0 2 1 rec 0 0 river R 3 swimming,

boating 0 Type & extent of fish species,

presence & extent of odor, river appearance, &

ecological outputs.

6 1 0 0 river R 3 0 0 1 rec. 0 0 river R 3   boating, swimming 1 0 1 rec.

( indirect &

direct?) 0 0 estuary E 2 birdwatching shellfishing 1 farmland, undeveloped land,

shell fishing areas 0 1 0 0 estuary E 2 1 4 0 1 0 estuaries E 2 0 shellfishing is main use March 12th, 2003 Page 44 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 24 25 26 27 28 29 30 AR AS AT AU AV AW AX AY AZ BA general sales tax and residential watersewer fee 2 IB assume nonuse  value categories 4 X separate user and non user populations 1 Two sample groups:

one using local taxes,

the other is told that " the Federal Government will finance the cost of the pollution control" and that their taxes will not be affected. 3 OE user /

nonuser total values 1 A user is a member of a household with any member using the Potomac, other rivers or lakes, seashore, or local pools for swimming, boating, fishing, hiking, camping, picnicking,

etc. REGARDLESS OF LOCATION. 80% of the respondents are users. This strict definition of non user ( doesn't use any waterbody for recreation) may justify Fisher & Raucher's statement: "... nonusers' option price can be interpreted as intrinsic benefits..." 1 Combination of higher taxes and prices of products, in general. 4 PC ( called " direct question" in report, 3 other methods used, but did not estimate existence value) assume nonuse  value categories 4 X Users are those engaged in recreation along the Monongahela ( 1 of 13 sites) or who gave positive use values ( presented w/ list of activities and asked if engaged in last year, p. 4 10). Concepts of use, option and existence value explained on a value card ( p. 4 14, Q. B 2).

Each respondnet reported option price, and apportioned amount between present and expected future use. Use amount is expected CS, remaining is option value ( pure?).

There are no income, age, race, sex differences between user nonuser groups ( p. 4 22). 1 Voluntary contribution to a hypothetical " Tar

Pamlico preservation"

fund. 3 OE user /

nonuser total values 1 Survey pop. split into 2 groups, expected rec. users and expected non users. Users reported that they would fish th river after an improvement that would double catch rates,

but their responses may include use and non use value. 1 ? 5 contingent choice user /

nonuser total values 1 Users state that they either fish or shellfish, thus deriving indirect use values from the fish habitat services of eelgrass & wetlands. Non users were those who stated they do not fish or shellfish. 2 5 contingent choice user /

nonuser total values 1 same as above 2 private contribution 3 OE allocation

entire sample 3 All respondents allocated total WTP among existence,

option, and use value. 1 March 12th, 2003 Page 45 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 24 25 26 27 28 29 30 BB BC BD BE BF BG WTP to postpone mining that would degrade water quality throughout the South Platte Basin ( CO) enough to permanently preclude riparian recreation ( 3 photos used); payments said to be used for water quality improvments to enhance recreational enjoyment. Authors believe user non use values ( existence & bequest) should not be added to recreation use and option values because of the high probability of upward bias. All estimates based on Sales Tax payment vehicle. Additional estimates/ ratios possible using Water Fee vehicle, and estimates for Denver & Ft. Colins sub populations. non user non use value / user use value ?? YES, not really available?

nonuse WTP estimates statistically different from 0 Incremental WTP to prevent water quality decline in the Potomac River. Five levels of water quality are based on low flow, high temperature conditions, differing in 5 physical and biochemical characteristics ( levels of DO, fecal coliform, nitrogen, phosphorous, and turbidity).

Values from Fisher & Raucher table 5 ( 1985), values not directly reported in Cronin 1982. Not sure how these values were calculated. All values include Option Value, and thus may be interpreted as upper bounds of total value for users and non users ( i. e. users option value is expected to include some intrinsic value and non users option value is expected to include some expected use value). WTP to prevent loss, from Fisher & Raucher table 5 YES  several WTP values were calculated based on different design variations, but the joint null hyp that all nonuse estimates are the same as all use estimates is strongly rejected for the relevant quality change ( p.

6.14)

Various water quality levels on the Monongahela River, using RFF water quality ladder: 1)

avoid decrease in quality from boatable to not suitable for boating, 2) improve quality from boatable to where game fish could survive, 3) improve quality from fishable to swimmable.

WTP value obtained to avoid decrease, as well as incremental values for 2 levels of improvement ( p. 5 25). Option prices ( which should be total of option & user values), option values, user values, were estimated for each of 3 levels using 4 different elicitation techniques, but existence value was only estimated with a direct OE question for a lossavoidance welfare change, resulting in one usable ratio. If we considered option value a nonuse value, we could have several more estimates. YES  users have estimated existence values significantly different from non users at the 5% level ( p. 5 32), and the results fro opotion value regression include user variable, which is also significant.

Tobit Annual WTP for water quality improvement in the Tar Pamlico River due to implementation of Best Management Practices by farmers to reduce non point source pollution ( financed through state fund). Result would be doubled catch rate for anglers and general improvements in fishing, swimming, boating, and drinking. User WTP value likely includes use and non use value, thus non use value is an underestimate ( Brown assumed non use portion of user WTP to be same as that for non users). Brown uses 21/ 14 ratio for users, and author says non use value accounts for at least 84% of total WTP, implying ratio of 21/ 25 ( see p. 176). Annual WTP for improvement. YES  expected use variable significant at the 5% level conditional logit Annual WTP per household per acre for wetlands protection in the Peconic estuary area under 3 scenarios: baseline (" no new action") level of degradation by 2020, program to restore, and program to preserve the resource, in terms of acreage. Annual WTP per household per acre for wetlands protection AHH Annual WTP per household per acre for eelgrass protectionin the Peconic estuary area 3 scenarios: baseline (" no new action") level of degradation by 2020, program to restore, and program to preserve the resource, in terms of acreage. Annual WTP per household per acre for eelgrass protection AHH tobit Annual household WTP for improvement in water quality of 3 coastal pounds to allow them to be open year round for shellfishing. Annual HH WTP AHH March 12th, 2003 Page 46 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 24 25 26 27 28 29 30 BH BI BJ BK BL BM BN BO BP BQ BR BS BT BU BV BW 1 $ 79.28 1 X $ 20.51 1 $ 45.30 1 $ 25.00 combined user &

nonuser groups X $ 35.00 $ 14.00 1 $ 0.05 combined user &

nonuser groups X $ 0.05 $ 0.00 1 $ 0.05 combined user &

nonuser groups X $ 0.06 $ 0.01 1 $ 53.10 33.69 use of ponds for shellfishing $ 19.41 $ 77.59 $ 77.59 March 12th, 2003 Page 47 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 24 25 26 27 28 29 30 BX BY BZ CA CB CC CD CE CF CG CH CI CJ CK Rec. + option values $ 56.68 $ 22.60 $ 66.87 existence +

bequest $ 33.86 $ 33.01 $ 41.95 existence + bequest $ 5.86 assumed rec value, FISHER VALUE DEFLATED TO 1973$ $ 14.65 IMPUTED NONUSE VALUE FISHER VALUE DEFLATED TO 1973$ $ 14.65 FISHER VALUE DEFLATE D TO 1973$

rec. + option value $ 19.71 p. 4 37 $ 25.59 $ 65.99 $ 65.99 $ 42.12 imputed non use value subtracted from use value reported in study $ 21.00 IMPUTED NONUSE VALUE $ 21.00 imputed non use value subtracted from use value reported in study $ 0.05 IMPUTED NONUSE VALUE $ 0.046 imputed non use value subtracted from use value reported in study $ 0.04 IMPUTED NONUSE VALUE $ 0.045 March 12th, 2003 Page 48 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 24 25 26 27 28 29 30 CL CM CN CO CP CQ CR CS CT CU CV CW $ 24.98 $ 16.97 174/ 177 for rec.

and option 24 $ 42.12 $ 14.18 current non user option value 26 65 91 total sample 145 total N March 12th, 2003 Page 49 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 31 32 33 34 35 36 37 38 A B C D E F G H I J K L M N 25 16 1 1312 Y Welle Welle UW DIS 1986 1985 CV MN 2 26 17 1 1310 Z Rowe Rowe et al. ERC 1985 1985 CV Eagle County,

CO CO 4 27 17 1 1310 AA Rowe Rowe et al. ERC 1985 1985 CV CO, Non Eagle County CO 4 28 18 1 1292 AB Mitchell Mitchell &

Carson EPA 1981 1980 CV national National 5 29 19 1 1287 AC Clonts Clonts & Malone SSNRRM 1990 1987 CV AL 3 March 12th, 2003 Page 50 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 31 32 33 34 35 36 37 38 O P Q R S T U V W X mail w/ phone follow up 1 N= 669; random selection from list of drivers license holder; designed to be representative of MN pop.

18 and older. representative sample of MN adults drawn from list of driver's license holders 415 p. 251 non parametric WTP sample, not sure what associated regression N is FOOTNOTE? 76% 76%

mail 1 residents of Eagle County, CO 507 FOOTNOTE  represents usable surveys, not the item response for the question used to calculate WTP 50% 50%

mail 1 Response rate is applicable for responses included in analysis; 45.5% if including response after cutoff date CO households 570 FOOTNOTE  this is max usable surveys ( w/ data); 439 WTP question responses, max 356 used in calculating WTP 27% 27%

household interviews 3 N= 1576; WTP data for 832,

695 in regression. National probability sample of persons 18 or older. National probability sample of persons 18 or older 695 regression sample 73% 73%

telephone 2 random survey of 733 Alabama households random sample of AL households 733 surveyed households na 1 March 12th, 2003 Page 51 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 31 32 33 34 35 36 37 38 Y Z AA AB AC AD AE $ 26,000 median income for entire sample ( N= 669) Prevention of acid deposition pollution that results in avoidance of decrease in MN water quality. avoid degradation in MN water quality from " unpolluted" to " severely polluted"

due to reduction in acid deposition 4 $ 37,445 average income Clean up and protection of eagle mine area of Eagle River and prevent future contamination, which would raise water quality from a level ok for watering your lawn, or for some industrial uses, to ok for swimming, rafting etc. ( interpreted as very poor to excellent). clean up and protection of the Eagle Mine area of the Eagle River, CO from very poor quality ( watering lawn, industrial use)

to excellent quality ( swimming, washing) 1 $ 27,500 average income Clean up of Eagle mine hazardous waste site; respondent state WTP to cleanup all CO sites, then allocated by % among 7 sites for which the State was taking legal action, including EM. Baseline and improvement not well defined, but assumed same as change in other survey version. clean up Eagle Mine hazardous waste site, which may currently preclude safe recreation use 1 $ 19,947 mean income of regression sample ( N= 695) Improvement in nation's water quality ( lakes, rivers and streams) from qualitatively established baseline, ok for boating, to a level that supports game fish such as bass.

Boating  Game fishing. improvement in nation's water quality from boatable to a level that " supports game fish such as bass" 5 $ 25,000.00 mean of the averages of the mean range of income for river users and non users Preservation of 15 Alabama rivers in a free flowing state,

opposed to rivers which have been altered by dams,

infrastructure, diversion or extraction. preservation of 15 AL rivers in a freeflowing state, free of alterations by dams,

infrastructure, diversion, or extraction 4 March 12th, 2003 Page 52 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 31 32 33 34 35 36 37 38 AF AG AH AI AJ AK AL AM AN AO AP AQ 10 1 1 1 all freshwater 5 0 7 1 1 1 river R 3 0 7 1 1 1 river R 3 0 8 0 1 1 all freshwater 5 0 0 1 0 0 rivers R 3 0 6 March 12th, 2003 Page 53 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 31 32 33 34 35 36 37 38 AR AS AT AU AV AW AX AY AZ BA higher taxes and prices for total value question; not specified for existence value question 3 OE value categories

user /

nonuser 2 X all surveyed respondents were characterized by certainty of future use: extremely likely, likely, somewhat likely,

extremely unlikely 1 state earmarked fund 3 OE revealed &

stated 5 Total value obtained from survey for all eagle county residents and recreational value estimated using unit day values from U. S. Forest Service, Rocky Mtn. Region 1985. 2 not specified, " How much would you be WTP to fund clean up of hazardous waste sites?" 4 Payment card allocation

entire sample 3 Respondent allocated WTP among 3 reasons by %. 2 higher taxes and prices 4 Payment card user /

nonuser total values 1 Nonusers reported they had not boated, fished, or gone swimming in freshwater in the past 2 years ( 323 of 832 respondents who provided WTP). 1 na 2 IB, not sure of details (' bidding procedure") value categories

user /

nonuser 2 X Households identified as either river user or non user households. User households had at least one member who had visited a free flowing river for the purpose of outdoor recreation in the past 3 years. 1 March 12th, 2003 Page 54 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 31 32 33 34 35 36 37 38 BB BC BD BE BF BG Annual WTP ( assumed household, but not explicit in WTP questions; income is HH, use characterization is largely by HH) to avoid reduction in MN water quality from " unpolluted" to " severely polluted" due to reduction in acid deposition. Estimated for certain users, likely,

somewhat likely, and certain non users. Mean WTP values used are those for respondents who answered both TWTP and EX value Q's. Existence value for both users and nonusers may include bequest value. Annual HH WTP YES  likelihood of recreation was significant at the 1% level in the regrression results for existence value, and demandside option price model AHH Annual HH WTP to clean up and protect eagle mine stretch of Eagle River from very poor quality ( ok for watering lawn/ some industrial uses) to excellent quality ( ok for swimming,

washing). Annual HH WTP AHH Annual HH WTP to clean up eagl mine hazardous waste site, which currently may preclude safe recreation use ( air, water, land). 1 of 7 sites respondents allocated TWTP for all CO sites among ( non Eagle County CO residents). Annual HH WTP AHH OLS Annual WTP ( HH or individual?) to improve nation's water quality from " boatable" to a level that " supports game fish such as bass." Study measures WTP for boatable ( compensting surplus), fishable ( equivalent variation), and swimmable ( equivalent variation) water quality. Annual WTP YES  whether or not a respondent is a user is highly significant in the regression of this variable on total intrinsic WTP A Average annual HH WTP for preserving 15 AL rivers in a free flowing state, free of dams,

diversion, extraction, or other infrastructure. Annual HH WTP A chi square analysis of contingency bid values and attitudes regarding river preservation indicates several relationships between bid value and attititude that are very different ( unsure of statistical interpretation). AHH March 12th, 2003 Page 55 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 31 32 33 34 35 36 37 38 BH BI BJ BK BL BM BN BO BP BQ BR BS BT BU BV BW 1 $ 12.00 1 $ 70.00 $ 28.64 verify w/ Elena,

used unit estimate from rec. analysis $ 41.36 apparently option value $ 11.62 $ 3.91 $ 7.45 $ 3.87 $ 3.58 1 $ 194.00 User and Nonuser group combined mean WTP X $ 237.00 $ 126.00 1 $ 57.00 8 9.5 22.5 17 70 $ 19.50 March 12th, 2003 Page 56 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 31 32 33 34 35 36 37 38 BX BY BZ CA CB CC CD CE CF CG CH CI CJ CK rec value + deman side option value $ 119.00 $ 119.00 $ 68.00 imputed non use value subtracted from use value reported in study $ 111.00 IMPUTED NONUSE VALUE $ 111.00 $ 7.50 $ 12.00 $ 52.00 $ 29.00 $ 23.00 $ 43.00 $ 27.50 March 12th, 2003 Page 57 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 31 32 33 34 35 36 37 38 CL CM CN CO CP CQ CR CS CT CU CV CW $ 68.00 158 34 509 323 $ 16.00 $ 11.50 $ 7.50 $ 8.50 Unsure of context of use value.

March 12th, 2003 Page 58 of 157 5 1200  Studies Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 1234567 89 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 A B C Study Characteristics Coding CODE DESCRIPTION NOTES Publication AAM Advances in Applied Micro Economics EE Ecological Economics EP Environment and Planning JEEM Journal of Environmental Economics and Management JES Journal of Environmental Systems JRU Journal of Risk and Uncertainty LE Land Economics NDSU DAE North Dakota State University, Department of Agricultural Economics PNL Battele Pacific Northwest Laboratory, PNL 4255 QJE The Quarterly Journal of Economics RV Rivers WRR Water Resources Research URID University of Rhode Island Dissertation EREC Environemental and Resource Economcis EPA Environmental Protection Agency Report UW DIS University of Wisconsin Dissertation ERC Energy & Resource Consultants SSNRRM Book: Social Science and Natural Resource Recreation Management Elicitation Method 2 IB iterative bidding 1 DC dichotomous choice 3 OE open ended 4 PC payment card 5 CC contingent choice Administration Method 1 mail 2 phone 3 personal interview Waterbody Type 1 river( s) & Lake( s)

2 estuary( ies)

3 river( s)

4 wetland( s)

5 all freshwater possibly collapse into 1 Amenity Change 0 water quality ladder not applicable incremental change not defined 1 visibly contaminated to very poor no use to outings 2 very poor to poor outings to boating 3 poor to fair boating to rough fishing 4 fair to good rough fishing to game fishing 5 good to excellent game fishing to swimming 6 visibly contaminated to poor no use to boating 7 very poor to excellent outings to swimming 8 poor to good boating to game fishing 9 poor to excellent boating to swimming 10 fair to excellent rough fishing to swimming Geographic Region 1 east March 12th, 2003 Page 59 of 157 5 1200  Codes Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 53 54 55 56 57 58 59 60 61 62 A B C 2 midwest 3 south 4 west 5 national or > 1 region Amenity Scale 1 single water body 2 multiple water bodies 3 local/ regional 4 statewide 5 national March 12th, 2003 Page 60 of 157 5 1200  Codes Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 123456789 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 A B C D E F G H I Calculations Lant Geographic Split Pop Category Iowa Towns Illinois Towns < 5,000 pop 4 4 5,000  25,000 pop 1 1 > 25,000 pop 2 2 Roberts Surveyed Counties State/ County Year MN 1989$ 1996$

Big Stone 19,408 $ 24,557 $

Grant 19,773 $ 25,019 $

Stevens 21,921 $ 27,737 $

Traverse 20,746 $ 26,250 $

Wilkin 23,081 $ 29,205 $

SD Roberts 17,480 $ 22,118 $

ND Richland 24,248 $ 30,682 $

Average Income 20,951 $ 26,510 $

WTP Values Housing Units Total WTP Average Household WTP Non Use to Use Ratios Use Value Low High Low Midpoint High Low Midpoint High 16,179 22,699 $ 44,736 $ 1.40 $ 2.08 $ 2.77 $ 0.38 0.40 0.41 Option/ Bequest Value 16,179 25,795 $ 52,750 $ 1.59 $ 2.43 $ 3.26 $

Existence Value 16,179 18,508 $ 40,451 $ 1.14 $ 1.82 $ 2.50 $

Olsen Average State Income State 1989$

Idaho 24,654 $

Montana 23,692 $

Oregon 28,529 $

Washington 31,961 $

Average State Income 27,209 $

Sutherland Surveyed Counties for Income Imputation MT County 1979$ 1981$

Flathead 16,099 $ 20,157 $

Missoula 16,269 $ 20,370 $

Silver Bow 14,591 $ 18,269 $

Yellowstone 17,460 $ 21,861 $

Average County Income 16,105 $ 20,164 $

March 12th, 2003 Page 61 of 157 5 1200  Calculations Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 A B C D E F G H I Cronin Income Imputation Median Household Income by Metropolitan Statistical Areas ( MSA): 1969, 1979, and 1989 source: http:// www. census. gov/ income/ ftp/ decennial/ historical/ msa/ msa1. prn 1969$ 1973$

D. C. MSA Median Income ( DC, MD 11,607 $ 14,042 $

Opaluch Income Estimation source: table VI. 6, p. 105 Income Category Category Midpoin Freq CF Percent of Sample <$ 15,000 7,500 $ 43 43 5.1%

$ 15,000$ 24,999 20,000 $ 77 120 9.1%

$ 25,000$ 34,999 30,000 $ 102 222 12.1%

$ 35,000$ 49,999 42,500 $ 111 333 13.2%

$ 50,000$ 74,999 62,500 $ 201 534 23.8%

$ 75,000$ 99,999 87,500 $ 113 647 13.4%

$ 100,000$ 149,999 80,000 $ 86 733 10.2%

$ 150,000 or more 150,000 $ 111 844 13.2%

Did Not Answer 124 12.8%

Total 844 100.1%

Median income 51,355.72 $ = 42500+( 422 333)/( 201)* 20000 Median income 56,641.29 $

Mitchell Income Estimation Income Category Freq Percent of Sample < $ 9,999 485 33%

$ 10,000$ 14,999 260 18%

$ 15,000$ 24,999 439 30%

$ 25,000 or more 298 20%

Did Not Answer 94 6%

TOTAL 1482 Rowe Recreation Value Estimation U. S. Forest Service Unit Day Value  Wiildlife & Fish 14.00 $

County Average Days Per Person Per Year 12.25 Minturn & Red Cliff Days Per Person Per Year 18.5 Rest of County Days Per Person Per Year 6 2/ 12 Hours Per Visit Adjustment for Unit Day Assumption 0.167 March 12th, 2003 Page 62 of 157 5 1200  Calculations Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 A B C D E F G H I Annual Recreation Value of Eagle County Resident 28.64 $

March 12th, 2003 Page 63 of 157 5 1200  Calculations Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 A B C D E F G H I March 12th, 2003 Page 64 of 157 5 1200  Calculations Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 A B C D E F G H I March 12th, 2003 Page 65 of 157 5 1200  Calculations Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 A B C D E F G H I March 12th, 2003 Page 66 of 157 5 1200  Calculations Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 A B C D E F G H I March 12th, 2003 Page 67 of 157 5 1200  Calculations Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 A B C D E F G H I March 12th, 2003 Page 68 of 157 5 1200  Calculations Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 A B C D E F G H I March 12th, 2003 Page 69 of 157 5 1200  Calculations Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 A B C D E F G H I March 12th, 2003 Page 70 of 157 5 1200  Calculations Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 12 3456789 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 A B C D E F G H I J K L M N O Ratio Calculations Estimate ID AUTH Number of Estimates Weight Pub Year Survey Year Total Non Use Value Total Use Value Non User Non

Use Value Estimate Non

Use Value *

Weight Study

Weighted Non

Use Value Estimate Use Value *

Weight Study

Weighted Use Value Estimate Non

Use Value for Users *

Weight Study Weighted Non Use Value for Users 29 Clonts & Malone 1 1.00 1990 1987 55.43 $ 30.88 $ 82.35 $ 55.43 $ 55.43 $ 30.88 $ 30.88 $ 82.35 $ 82.35 $

13 Croke et al. 3 0.33 1986 1986 53.31 $ 17.61 $ 17.77 $ 63.11 $ 5.87 $ 11.69 $

14 Croke et al. 3 0.33 1986 1986 60.91 $ 11.11 $ 20.30 $ 3.70 $

15 Croke et al. 3 0.33 1986 1986 75.11 $ 6.35 $ 25.04 $ 2.12 $

19 Cronin 1 1.00 1982 1973 59.37 $ 23.75 $ 59.37 $ 59.37 $ 23.75 $ 23.75 $

20 Desvousges et al. 1 1.00 1983 1981 111.41 $ 89.65 $ 130.59 $ 111.41 $ 111.41 $ 89.65 $ 89.65 $ 130.59 $ 130.59 $

1 Huang et al. 2 0.50 1997 1995 59.02 $ 158.25 $ 29.51 $ 89.27 $ 79.13 $ 128.00 $

2 Huang et al. 2 0.50 1997 1995 119.52 $ 97.75 $ 59.76 $ 48.88 $

24 Kaoru 1 1.00 1993 1989 112.57 $ 77.04 $ 112.57 $ 112.57 $ 77.04 $ 77.04 $

9 Lant & Roberts 3 0.33 1990 1987 68.56 $ 57.30 $ 22.85 $ 80.75 $ 19.10 $ 70.89 $

10 Lant & Roberts 3 0.33 1990 1987 88.40 $ 77.04 $ 29.47 $ 25.68 $

11 Lant & Roberts 3 0.33 1990 1987 85.29 $ 78.34 $ 28.43 $ 26.11 $

8 Magat et al. 1 1.00 2000 1997 11.49 $ 22.98 $ 11.49 $ 11.49 $ 22.98 $ 22.98 $

28 Mitchell & Carson 1 1.00 1981 1980 242.34 $ 275.09 $ 242.34 $ 242.34 $ 275.09 $ 275.09 $

16 Olsen et al. 1 1.00 1991 1989 38.48 $ 69.12 $ 38.48 $ 38.48 $ 69.12 $ 69.12 $

22 Opaluch et al. 1999 1995 $ 0.05 $ 0.00 23 Opaluch et al. 1999 1995 $ 0.05 $ 0.02 12 Roberts & Leitch 1 1.00 1997 1996 2.09 $ 5.17 $ 2.09 $ 2.09 $ 5.17 $ 5.17 $

26 Rowe et al. 2 0.50 1985 1985 69.15 $ 47.88 $ 34.58 $ 40.80 $ 23.94 $ 27.21 $

27 Rowe et al. 2 0.50 1985 1985 12.46 $ 6.54 $ 6.23 $ 3.27 $

4 Sanders et al. 4 0.25 1990 1983 46.91 $ 24.96 $ 11.73 $ 90.46 $ 6.24 $ 48.66 $

5 Sanders et al. 4 0.25 1990 1983 87.60 $ 46.62 $ 21.90 $ 11.65 $

6 Sanders et al. 4 0.25 1990 1983 111.99 $ 59.61 $ 28.00 $ 14.90 $

7 Sanders et al. 4 0.25 1990 1983 115.35 $ 63.45 $ 28.84 $ 15.86 $

17 Sutherland & Walsh 1 1.00 1985 1981 91.53 $ 35.78 $ 91.53 $ 91.53 $ 35.78 $ 35.78 $

18 Walsh et al. 1 1.00 1978 1976 132.63 $ 250.66 $ 211.42 $ 132.63 $ 132.63 $ 250.66 $ 250.66 $ 211.42 $ 211.42 $

25 Welle 1 1.00 1986 1985 113.69 $ 20.06 $ 198.96 $ 113.69 $ 113.69 $ 20.06 $ 20.06 $ 198.96 $ 198.96 $

21 Whitehead & Groothuis 1 1.00 1992 1991 27.74 $ 18.49 $ 27.74 $ 27.74 $ 18.49 $ 18.49 $

3 Whitehead et al. 1 1.00 1995 1990 68.08 $ 29.83 $ 68.08 $ 68.08 $ 29.83 $ 29.83 $

Total 18.00 Median 1990 1986 69.15 $ 46.62 164.78 $ 74.41 $ 33.33 $ 164.78 $

Mean 1989 1986 78.53 $ 63.01 155.83 $ 79.51 $ 68.61 $ 155.83 $

Stdev 5.33 5.68 48.12 $ 67.42 60.52 $ 54.69 $ 77.52 $ 60.52 $

Min 1978 1973 2.089 $ 5.17 82.35 $ 2.09 $ 5.17 $ 82.35 $

Max 2000 1997 242.34 $ 275.09 211.42 $ 242.34 $ 275.09 $ 211.42 $

March 12th, 2003 Page 71 of 157 5 1200  Weighted WTP Values Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 12 3456789 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 P Q R S T U V Total Pop. / User Group Method Adjusted Use Value Based on Imputed User Non Use Value group group X group X group X group X group component component component component component component component group X group X group X group X component component component component component component component component group group group X group X March 12th, 2003 Page 72 of 157 5 1200  Weighted WTP Values Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 1 2 34 56 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 A B C D E F G H I J Study Summary Summary Data Non Use Study ID Authors Pub Year Data Year Admin Method Response Rate State Region Waterbody Type Elicitation Method 1 Huang et al. 1997 1995 phone 75% NC east estuary( ies) dichotomous choice 2 Whitehead et al. 1995 1990 phone 71% NC east estuary( ies) iterative bidding 3 Sanders et al. 1990 1983 mail 51% CO west river( s) open ended 4 Magat et al. 2000 1997 personal interview na CO/ NC national or >

1 region all freshwater iterative bidding 5 Lant & Roberts 1990 1987 personal interview 41% IA/ IL midwest river( s) payment card 6 Roberts & Leitch 1997 1996 mail 62% MN/ SD midwest wetland( s) payment card 7 Croke et al. 1986 1986 phone 85% IL midwest river( s) iterative bidding 8 Olsen et al. 1991 1989 phone 73% Pacific NW ( ID, MT,

OR, WA) west river( s) open ended 9 Sutherland & Walsh 1985 1981 mail 61% MT west river( s) & Lake( s) open ended 10 Walsh et al. 1978 1976 personal interview na CO west river( s) iterative bidding 11 Cronin 1982 1973 personal interview 82% DC east river( s) open ended 12 Desvousges et al. 1983 1981 personal interview 81% PA east river( s) payment card 13 Whitehead & Groothuis 1992 1991 mail 61% NC east river( s) open ended 14 Opaluch et al. 1999 1995 personal interview na NY east estuary( ies) contingent choice 15 Kaoru 1993 1989 mail 49% MA east estuary( ies) open ended 16 Welle 1986 1985 mail 76% MN midwest all freshwater open ended 17 Rowe et al. 1985 1985 mail 50% CO west river( s) open ended 18 Mitchell & Carson 1981 1980 personal interview 73% National national or >

1 region all freshwater payment card 19 Clonts & Malone 1990 1987 phone na AL south river( s) iterative bidding Summary Statistics Response Rate not including 27% including 27%

Average: 66% 63%

Min: 41% 27%

Max: 85% 85%

TOTAL 15 16 Not applicable for 3 studies and not available for 1 March 12th, 2003 Page 73 of 157 5 1200  Study Characteristics Summary Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 1 2 34 56 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 K Non Use Method revealed & stated user / non user total values allocation  entire sample assume non use value categories

entire sample value categories

entire sample user / non user total values user / non user total values allocation  entire sample assume non use

value categories user / non user total values assume non use

value categories user / non user total values user / non user total values allocation  entire sample value categories  user / non user revealed & stated user / non user total values value categories  user / non user March 12th, 2003 Page 74 of 157 5 1200  Study Characteristics Summary Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 A B C D E F G H I J Median Response Rate Calculation 27% 1 of 2 surveys for study 17 41% 49% 50% 51% 61% 61% 62% 66%

71%

73% 73% 75% 76% 81% 82% 85%

Administration Method Number of Studies Mail 7 Phone 5 Personal Interview 7 Elicitation Method Number of Studies Contingent Choice 1 Dichotomous choice 1 Iterative bidding 5 Open ended 8 Payment Card 4 Unique States Where Survey Was Conducted AL CO DC IA ID IL MA MN MT NC OR PA SD WA 14 Waterbody Types Number of Studies all freshwater 3 estuary( ies) 4 river( s) 10 river( s) & Lake( s) 1 wetland( s) 1 March 12th, 2003 Page 75 of 157 5 1200  Study Characteristics Summary Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 K March 12th, 2003 Page 76 of 157 5 1200  Study Characteristics Summary Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 90 91 92 93 94 95 96 97 98 99 100 101 A B C D E F G H I J Non Use Value Method Number of Studies Allocation 3 allocation  entire sample 3 4  2nd approach by Rowe allocation  user / non users 0 Assume Non Use 3 Assume non use 1 Assume non use  value categories 2 Revealed & stated 2 User / non user total values 7 Value categories 4 value categories  entire sample 2 value categories  user / non user 2 March 12th, 2003 Page 77 of 157 5 1200  Study Characteristics Summary Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 90 91 92 93 94 95 96 97 98 99 100 101 K March 12th, 2003 Page 78 of 157 5 1200  Study Characteristics Summary Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 123 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 A B C D E F G H I J K L M N O P Q U. S. Census Bureau Source: http:// www. census. gov/ hhes/ income/ histinc/ h08. html Table H 8. Median Household Income by State: 1984 to 2001 ( Households as of March of the following year. Income in current and 2001 CPI U RS adjusted dollars28/)

INCOME IN CURRENT DOLLARS 2001 2000 30/ 2000 1999 29/ 1999 1998 1997 1996 Median Standard Median Standard Median Standard Median Standard Median Standard Median Standard Median Standard Median Standard State income error income error income error income error income error income error income error income error United States $ 42,228 $ 129 $ 41,990 $ 132 $ 42,022 $ 196 $ 40,696 $ 190 $ 40,816 $ 192 $ 38,885 $ 230 $ 37,005 $ 171 $ 35,492 $ 179 Alabama 35,160 1,006 35,424 1,072 33,013 1,954 36,251 1,189 36,213 1,185 36,266 1,307 31,939 1,607 30,302 1,258 Alaska 57,363 2,012 52,847 1,159 50,637 1,632 51,396 2,226 51,509 2,198 50,692 2,124 47,994 1,258 52,779 1,907 Arizona 42,704 1,441 39,783 1,210 41,432 1,315 36,995 1,133 37,119 1,206 37,090 1,255 32,740 1,297 31,637 1,274 Arkansas 33,339 1,144 29,697 772 30,179 926 29,682 1,026 29,762 1,062 27,665 1,160 26,162 1,154 27,123 978 California 47,262 727 46,816 686 46,604 924 43,629 703 43,744 697 40,934 577 39,694 864 38,812 818 Colorado 49,397 1,190 48,240 1,237 48,322 1,722 48,177 1,483 48,346 1,490 46,599 1,086 43,233 1,944 40,950 1,329 Connecticut 53,347 1,240 50,172 1,357 50,152 2,016 50,593 2,296 50,798 2,333 46,508 2,728 43,985 1,989 42,119 3,087 Delaware 49,602 1,468 50,365 1,508 50,043 2,730 46,628 2,281 46,839 2,318 41,458 1,753 43,033 2,062 39,309 1,402 D. C. 41,169 1,023 41,222 1,072 38,599 1,724 38,670 1,599 38,686 1,625 33,433 1,311 31,860 984 31,966 1,578 Florida 36,421 417 38,856 743 37,942 794 35,831 627 35,876 641 34,909 767 32,455 583 30,641 513 Georgia 42,576 1,073 41,901 831 42,863 957 39,425 1,355 39,433 1,382 38,665 1,179 36,663 916 32,496 1,666 Hawaii 47,439 1,256 51,546 1,193 48,018 2,083 44,504 1,832 44,373 1,750 40,827 2,369 40,934 1,399 41,772 1,893 Idaho 38,241 966 37,611 1,192 37,273 1,660 35,800 1,413 35,906 1,405 36,680 1,090 33,404 1,339 34,709 1,341 Illinois 46,171 879 46,064 966 46,371 1,168 46,330 1,028 46,392 1,029 43,178 1,234 41,283 782 39,554 1,107 Indiana 40,379 948 40,865 679 39,396 1,635 40,838 1,719 40,929 1,721 39,731 1,589 38,889 1,183 35,147 1,298 Iowa 40,976 1,133 40,991 811 42,777 1,435 41,098 1,130 41,238 1,125 37,019 1,202 33,783 1,282 33,209 1,527 Kansas 41,415 1,115 41,059 1,168 37,529 1,990 37,348 2,078 37,476 2,123 36,711 1,617 36,471 1,614 32,585 1,460 Kentucky 38,437 1,009 36,265 848 37,079 1,660 33,738 1,484 33,901 1,497 36,252 1,511 33,452 1,659 32,413 1,439 Louisiana 33,322 1,195 30,718 828 30,122 1,280 32,654 1,244 32,695 1,255 31,735 1,660 33,260 1,551 30,262 1,290 Maine 36,612 952 37,266 853 41,624 1,174 38,862 1,319 38,932 1,328 35,640 1,049 32,772 1,301 34,696 1,211 Maryland 53,530 1,652 54,535 1,400 51,494 2,047 52,205 2,217 52,310 2,212 50,016 2,161 46,685 1,476 43,993 2,565 Massachusetts 52,253 1,518 46,753 1,357 46,695 1,678 44,005 2,023 44,192 2,088 42,345 1,961 42,023 1,383 39,494 1,932 Michigan 45,047 868 45,512 1,095 46,046 1,445 46,089 1,026 46,238 1,031 41,821 917 38,742 1,108 39,225 1,143 Minnesota 52,681 1,134 54,251 1,703 50,648 1,699 47,038 1,527 47,240 1,565 47,926 2,115 42,564 1,510 40,991 1,225 Mississippi 30,161 1,186 34,299 1,354 31,512 943 32,478 1,408 32,540 1,402 29,120 1,158 28,499 1,386 26,677 1,316 Missouri 41,339 1,204 45,097 1,187 47,391 1,752 41,383 1,191 41,466 1,231 40,201 1,868 36,553 2,060 34,265 1,513 Montana 32,126 737 32,777 1,001 31,912 1,234 31,038 966 31,244 961 31,577 1,133 29,212 1,145 28,684 1,566 Nebraska 43,611 1,116 41,750 1,018 38,327 1,915 38,626 1,366 38,787 1,380 36,413 1,549 34,692 1,528 34,014 1,500 Nevada 45,403 1,130 45,758 1,011 44,624 1,348 41,461 1,764 41,680 1,880 39,756 1,225 38,854 1,576 38,540 1,615 New Hampshire 51,331 719 50,926 1,243 48,784 2,319 46,055 1,952 46,167 1,963 44,958 1,866 40,998 1,604 39,407 1,734 New Jersey 51,771 933 50,405 991 50,892 881 49,734 1,405 49,930 1,390 49,826 1,436 48,021 1,424 47,468 1,217 New Mexico 33,124 1,238 35,093 1,248 35,258 1,934 32,574 1,746 32,475 1,761 31,543 1,398 30,086 1,157 25,086 1,091 New York 42,114 600 40,744 581 41,482 854 39,989 879 40,058 882 37,394 777 35,798 634 35,410 746 North Carolina 38,162 951 38,317 806 38,693 1,331 37,254 960 37,340 1,016 35,838 1,022 35,840 917 35,601 1,008 North Dakota 35,793 804 35,996 1,065 35,066 1,617 32,663 1,383 32,877 1,349 30,304 1,179 31,661 1,361 31,470 1,184 Ohio 41,785 661 42,962 732 43,782 1,080 39,489 989 39,617 986 38,925 1,576 36,134 894 34,070 1,063 March 12th, 2003 Page 79 of 157 5 1200  State Income Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 123 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 R S T U V W X Y Z AA AB AC AD AE AF AG AH AI AJ 1995 25/ 1994 24/ 1993 23/ 1992 22/ 1991 1990 1989 1988 1987 21/ 1986 Median Standard Median Standard Median Standard Median Standard Median Standard Median Standard Median Standard Median Standard Median Standard Median income error income error income error income error income error income error income error income error income error income $ 34,076 $ 197 $ 32,264 $ 147 $ 31,241 $ 146 $ 30,636 $ 145 $ 30,126 $ 144 $ 29,943 $ 153 $ 28,906 $ 159 $ 27,225 $ 139 $ 25,986 $ 127 $ 24,897 25,991 1,266 27,196 1,559 25,082 1,088 25,808 1,058 24,346 1,068 23,357 1,037 21,284 1,070 19,948 912 19,734 1,147 19,132 47,954 2,008 45,367 1,494 42,931 1,643 41,802 1,156 40,612 1,822 39,298 1,627 36,006 1,378 33,103 1,183 33,233 1,497 31,356 30,863 1,360 31,293 773 30,510 1,120 29,358 1,088 30,737 897 29,224 1,141 28,552 1,210 26,435 843 26,749 892 25,500 25,814 999 25,565 944 23,039 847 23,882 1,398 23,435 783 22,786 981 21,433 915 20,172 706 18,827 1,008 18,730 37,009 723 35,331 619 34,073 651 34,903 629 33,664 685 33,290 565 33,009 618 30,287 634 30,146 538 29,010 40,706 1,552 37,833 1,446 34,488 1,569 32,484 1,471 31,499 1,245 30,733 906 26,806 1,398 26,214 1,285 26,476 1,075 27,192 40,243 2,269 41,097 1,595 39,516 1,660 40,841 1,972 42,154 1,944 38,870 2,097 42,321 1,592 36,213 1,293 32,862 1,362 32,721 34,928 1,848 35,873 1,191 36,064 849 35,678 1,393 32,585 1,111 30,804 1,113 32,068 1,133 30,505 1,167 29,244 875 25,626 30,748 1,182 30,116 1,107 27,304 1,726 30,247 1,124 29,885 1,903 27,392 1,562 26,752 1,015 26,741 748 27,455 1,285 24,322 29,745 612 29,294 632 28,550 707 27,349 526 27,252 475 26,685 454 26,085 475 25,406 475 24,489 476 22,849 34,099 897 31,467 1,238 31,663 1,254 28,797 1,228 27,212 1,088 27,561 1,186 27,542 1,021 26,566 896 26,714 1,380 24,370 42,851 1,292 42,255 2,423 42,662 1,759 42,113 1,435 37,246 1,630 38,921 1,414 35,035 1,328 33,024 1,482 35,022 1,074 29,003 32,676 1,116 31,536 1,278 31,010 1,323 27,704 874 26,116 1,029 25,305 975 24,654 953 23,450 1,004 20,755 834 20,749 38,071 875 35,081 799 32,857 810 31,551 752 31,884 714 32,542 724 31,300 623 29,524 754 27,084 536 26,511 33,385 1,444 27,858 1,032 29,475 1,361 28,530 1,315 27,089 922 26,928 1,099 25,898 1,022 26,293 931 22,519 944 22,728 35,519 942 33,079 1,280 28,663 1,240 28,743 972 28,553 1,012 27,288 986 26,265 792 24,305 1,078 22,190 912 22,459 30,341 921 28,322 1,064 29,770 1,144 30,346 1,137 29,295 934 29,917 1,179 26,862 908 25,566 1,153 25,583 900 23,926 29,810 1,149 26,595 1,028 24,376 1,091 23,485 1,259 23,764 1,046 24,780 1,213 23,283 1,206 19,907 801 20,673 939 19,874 27,949 1,090 25,676 1,501 26,312 1,164 25,439 1,142 25,299 1,156 22,405 1,580 22,861 1,857 20,497 1,474 21,349 858 20,890 33,858 1,088 30,316 1,537 27,438 1,203 29,617 1,026 27,868 1,253 27,464 1,572 28,221 1,389 26,402 942 23,600 1,019 23,424 41,041 1,627 39,198 1,400 39,939 1,282 37,203 1,626 36,952 1,417 38,857 1,596 36,016 1,187 36,552 1,196 34,970 1,388 30,604 38,574 1,475 40,500 1,060 37,064 949 36,359 738 35,714 790 36,247 828 36,086 704 33,213 839 32,241 716 30,339 36,426 994 35,284 685 32,662 682 32,267 761 32,117 689 29,937 663 30,775 790 29,472 607 27,702 724 26,605 37,933 1,848 33,644 1,360 33,682 1,212 30,981 1,297 29,479 1,146 31,465 1,028 30,185 1,278 29,087 1,041 28,082 1,113 26,443 26,538 1,028 25,400 752 22,191 1,229 20,570 1,074 19,475 1,053 20,178 802 19,917 947 18,166 888 18,513 901 16,513 34,825 1,373 30,190 1,442 28,682 1,466 27,361 1,451 27,926 1,415 27,332 1,394 26,497 746 23,443 1,088 23,720 1,167 21,925 27,757 1,105 27,631 1,246 26,470 965 26,525 728 24,827 890 23,375 983 23,692 1,311 22,231 829 20,474 799 20,328 32,929 1,155 31,794 1,116 31,008 833 30,048 1,071 29,549 1,007 27,482 1,128 26,319 1,521 25,159 960 23,268 761 21,772 36,084 1,314 35,871 1,534 35,814 1,078 31,908 796 32,937 1,564 32,023 1,179 29,340 948 27,983 956 26,878 1,128 26,217 39,171 1,556 35,245 1,837 37,964 1,620 39,436 1,922 36,032 1,339 40,805 1,313 37,532 1,371 34,625 1,129 32,338 1,450 30,548 43,924 1,400 42,280 1,064 40,500 986 39,000 841 40,049 1,033 38,734 864 39,120 948 36,287 658 34,241 794 31,715 25,991 1,100 26,905 1,382 26,758 853 25,860 1,347 26,540 1,195 25,039 1,048 22,602 1,029 19,296 833 20,758 621 19,845 33,028 716 31,899 477 31,697 556 31,051 529 31,794 538 31,591 511 31,496 453 28,915 668 26,384 456 25,025 31,979 888 30,114 670 28,820 653 27,771 616 26,853 510 26,329 556 26,406 517 24,415 536 22,760 542 21,861 29,089 1,217 28,278 1,115 28,118 835 26,959 901 25,892 932 25,264 1,003 25,229 903 24,092 1,009 22,576 905 21,508 34,941 988 31,855 584 31,285 658 31,404 587 29,790 759 30,013 720 29,021 655 27,740 636 25,773 555 25,115 March 12th, 2003 Page 80 of 157 5 1200  State Income Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 123 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 AK AL AM AN AO 1985 20/ 1984 19/

Standard Median Standard Median Standard error income error income error $ 129 $ 23,618 $ 128 $ 22,415 $ 102 885 18,333 760 17,310 605 1,017 34,782 1,089 32,356 1,473 718 23,877 744 21,425 609 765 17,451 764 15,674 748 570 26,981 350 25,287 364 926 28,182 850 25,801 805 1,605 31,090 1,129 29,951 1,238 1,212 22,980 1,366 25,819 1,027 1,252 21,076 756 20,408 860 540 21,343 437 19,785 468 1,112 21,049 788 19,984 815 1,206 28,961 1,446 28,877 1,216 680 20,761 598 21,092 963 634 24,870 523 23,752 567 709 22,675 626 22,770 710 750 20,927 604 19,863 745 782 22,788 1,033 24,629 912 1,006 17,361 748 17,680 1,079 956 21,179 728 18,949 880 970 20,519 803 20,648 884 1,036 30,136 966 29,708 1,151 735 28,207 810 26,959 693 648 24,242 838 22,965 635 1,150 23,856 1,022 24,436 914 639 16,413 619 15,430 732 772 21,939 608 20,775 715 749 20,236 800 19,536 720 814 21,799 914 21,397 765 895 23,274 1,005 25,776 1,018 829 26,403 1,074 25,914 735 842 30,980 643 27,776 800 693 20,423 1,025 20,630 1,029 474 23,639 523 22,027 417 698 21,451 585 20,569 641 785 21,205 809 20,771 1,038 588 25,174 564 23,123 492 March 12th, 2003 Page 81 of 157 5 1200  State Income Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 A B C D E F G H I J K L M N O P Q Oklahoma 35,609 690 32,432 709 32,347 993 32,683 1,491 32,919 1,559 33,727 1,232 31,351 1,025 27,437 1,089 Oregon 41,273 752 42,499 936 42,426 1,598 40,619 1,252 40,713 1,242 39,067 1,927 37,247 1,788 35,492 1,274 Pennsylvania 43,499 723 42,176 704 43,438 1,254 37,758 1,141 37,995 1,207 39,015 1,080 37,517 964 34,899 974 Rhode Island 45,723 1,147 42,197 1,018 42,698 2,498 42,719 1,980 42,936 2,012 40,686 2,657 34,797 2,235 36,986 1,036 South Carolina 37,736 1,023 37,570 937 37,072 1,307 36,462 1,728 36,563 1,746 33,267 1,310 34,262 1,609 34,665 1,405 South Dakota 39,671 856 36,475 687 35,939 1,260 35,828 944 35,982 917 32,786 1,013 29,694 1,145 29,526 1,003 Tennessee 35,783 791 34,096 930 33,908 1,518 36,522 1,310 36,536 1,326 34,091 1,307 30,636 1,358 30,790 1,087 Texas 40,860 512 38,609 785 39,655 858 38,688 1,020 38,978 1,025 35,783 662 35,075 880 33,072 763 Utah 47,342 1,601 47,550 1,041 45,064 1,251 46,050 1,615 46,094 1,631 44,299 1,375 42,775 1,785 37,038 1,330 Vermont 40,794 944 39,594 921 38,059 1,876 41,584 1,407 41,630 1,422 39,372 1,591 35,053 1,727 32,358 1,250 Virginia 50,241 1,148 47,163 1,065 49,790 2,232 45,693 1,770 45,750 1,787 43,354 2,195 42,957 1,897 39,211 1,459 Washington 42,490 1,264 42,525 1,211 41,869 1,558 45,473 2,080 45,639 2,027 47,421 1,379 44,562 1,715 36,676 1,608 West Virginia 29,673 674 29,411 645 28,973 751 29,297 1,149 29,433 1,140 26,704 780 27,488 1,315 25,247 1,301 Wisconsin 45,346 1,123 45,088 952 45,156 1,712 45,667 1,878 45,825 1,883 41,327 1,271 39,595 1,150 40,001 1,780 Wyoming 39,719 1,166 39,629 1,056 38,883 1,797 37,248 1,285 37,395 1,298 35,250 1,316 33,423 1,441 30,953 858 March 12th, 2003 Page 82 of 157 5 1200  State Income Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 R S T U V W X Y Z AA AB AC AD AE AF AG AH AI AJ 26,311 880 26,991 1,213 26,260 1,492 25,284 1,075 25,462 1,079 24,384 1,044 23,667 1,236 23,667 756 21,691 884 20,948 36,374 970 31,456 1,128 33,138 1,160 31,927 2,039 30,190 1,087 29,281 966 28,529 1,435 27,748 1,150 25,038 1,092 24,773 34,524 683 32,066 654 30,995 694 29,882 667 30,367 614 29,005 688 28,690 684 26,742 497 25,424 541 23,807 35,359 1,373 31,928 1,321 33,509 1,547 30,432 1,433 30,836 1,091 31,968 1,175 30,124 1,354 29,842 1,584 28,292 1,440 26,540 29,071 1,400 29,846 1,139 26,053 960 27,578 1,434 27,463 1,137 28,735 1,383 23,798 1,059 25,533 1,150 25,049 1,136 21,968 29,578 1,610 29,733 1,185 27,737 1,040 26,259 669 24,639 780 24,571 858 24,108 999 22,294 703 21,151 597 19,898 29,015 1,268 28,639 1,028 25,102 831 24,318 913 24,453 915 22,592 869 22,611 1,305 20,856 1,017 21,179 795 18,256 32,039 634 30,755 655 28,727 613 27,953 634 27,733 626 28,228 716 25,886 559 24,963 582 24,721 637 24,162 36,480 919 35,716 1,041 35,786 1,242 34,251 1,145 28,016 1,359 30,142 1,018 30,717 1,014 26,313 909 26,529 1,194 26,281 33,824 1,242 35,802 1,906 31,065 956 32,755 1,333 29,155 1,222 31,098 1,331 31,295 1,136 28,988 1,077 25,415 1,374 24,599 36,222 1,391 37,647 1,531 36,433 1,387 38,198 1,359 36,137 1,336 35,073 1,048 34,118 1,205 32,648 1,319 29,996 1,013 29,715 35,568 1,252 33,533 1,190 35,655 1,111 33,900 1,247 33,970 1,185 32,112 1,239 31,961 1,472 32,327 1,030 27,319 1,108 26,881 24,880 870 23,564 1,217 22,421 981 20,271 892 23,147 918 22,137 1,142 21,677 843 19,353 930 17,207 778 16,464 40,955 1,318 35,388 1,272 31,766 1,340 33,308 1,097 31,133 1,018 30,711 897 29,123 1,240 29,575 978 26,369 1,410 26,430 31,529 1,136 33,140 1,848 29,442 1,167 30,209 1,420 29,050 1,382 29,460 991 29,521 1,289 26,419 1,095 27,590 1,458 23,559 March 12th, 2003 Page 83 of 157 5 1200  State Income Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 AK AL AM AN AO 871 21,205 764 21,148 718 1,002 21,894 1,042 21,399 745 495 22,877 538 20,346 499 1,060 24,625 900 21,612 848 864 20,036 862 20,309 934 664 18,142 702 19,409 928 884 17,778 557 16,782 576 514 23,743 546 23,024 533 810 25,238 702 23,057 735 1,003 26,000 942 22,578 983 1,074 28,429 1,324 26,525 874 950 24,000 756 25,017 823 905 15,983 828 16,843 608 803 23,246 1,161 20,743 821 863 22,081 1,049 23,816 731 March 12th, 2003 Page 84 of 157 5 1200  State Income Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 123 4 5 6 789 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 A B U. S. Census Bureau Source: http:// www. census. gov/ hhes/ income/ histinc/ ftnotes. html Historical Income Tables Footnotes for Historical Income Tables from the Current Population Survey ( CPS)

Please note that not all footnotes apply to all tables NA Not available.

B Base less than 75,000.

X Not applicable.

 Zero or rounds to zero.

1/ Before 1983, based on CPI U X1 2/ Before 1967, CPI factors are extrapolated.

3/ Before 1967, data are for " Black and other races" combined 4/ People of Hispanic origin may be of any race.

5/ Data based on 1940 census population controls.

6/ Data reflect implementation of expanded income questions to show wage and salary, farm self employment, nonfarm self employment, and all other nonearned income separately.

7/ Data reflect implementation of 1950 census population controls.

8/ Data reflect implementation of first hotdeck procedure to impute missing income entries ( all income data imputed if any missing). Data also reflect introduction of 1960 census based sample design.

9/ Data reflect full implementation of 1960 census based sample design and population controls.

10/ Data reflect implementation of new procedures to impute missing data only.

11/ Questionnaire expanded to ask eight income questions.

12/ Data reflect implementation of a new March CPS processing system.

13/ Data reflect introduction of 1970 census based sample design and population controls.

14/ Data reflect full implementation of 1970 census based sample design.

15/ Data reflect implementation of a new March CPS processing system. Questionnaire expanded to ask 11 income questions.

16/ Some of these estimates were derived using Pareto interpolation and may differ from published data which were derived using linear interpolation.

17/ First year medians were derived using both Pareto and linear interpolation. Before this year, all medians were derived using linear interpolation.

18/ Data reflect implementation of 1980 census population controls. Questionnaire expanded to show 27 possible values from 51 possible sources of income.

19/ Data reflect implementation of Hispanic population weighting controls and introduction of 1980 census based sample design.

20/ Recording of amounts for earnings from longest job were increased to $ 299,999. Data reflect full implementation of 1980 census based sample design.

21/ Data reflect implementation of a new March CPS processing system.

22/ Data reflect implementation of 1990 census population controls.

23/ Data collection method changed from paper and pencil to computer assisted interviewing. In addition, the March 1994 income supplement was revised to allow for the coding of different income amounts on selected questionnaire items.

Child support and alimony limits decreased to $ 49,999. Limits increased in the following categories: earnings to $ 999,999; social security to $ 49,999; supplemental security income and public assistance income to $ 24,999; and veterans' benefits to $ 99,999.

24/ Data reflect introduction of 1990 census based sample design.

25/ Data reflect full implementation of the 1990 census based sample design and metropolitan definitions, 7,000 household sample reduction, and revised race edits.

26/ Starting in 1999, alternative income definition 7 includes federal EIC and EIC for the nine states that use federal eligibility rules to compute the state credit as a percentage of the federal EIC. The nine states are: Iowa, Kansas,

Massachusetts, Maryland, New York, Oregon, Rhode Island, Vermont, and Wisconsin.

March 12th, 2003 Page 85 of 157 5 1200  State Income Footnotes Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 39 40 41 42 43 A B 27/ Starting in 1999, 50th percentile is based on micro sorted data.

28/ The CPI U RS is a price index of inflation that incorporates most of the improvements in methodology made to the current CPI U since 1978 into a single, uniform series. See Money Income in the United States: 1999 or the appendix of Money Income in the United States: 1998 for more information. Before 1977 the CPI U RS is extrapolated.

29/ Data reflect implementation of Census 2000 based population controls.

30/ Sample expanded by 28,000 households.

31/ Based on November 2001 weighting correction. See March 2001 CPS Weighting Correction User Note http:// www. bls. census. gov/ cps/ ads/ 2001/ susenote. htm March 12th, 2003 Page 86 of 157 5 1200  State Income Footnotes Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 123 4 56 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 A B C D E F Median Household Income by County: 1969, 1979, 1989 Source: http:// www. census. gov/ income/ ftp/ decennial/ historical/ county/ c1. prn ( In current and 1989 CPI U adjusted dollars1/) 1989 1979 1969 County/ State current 1989 current 1989 United States $ 30,056 $ 16,841 $ 28,220 $ 8,486 $ 26,707 Alabama $ 23,597 $ 13,669 $ 22,905 $ 6,419 $ 20,202 Autauga County, AL 28,337 16,524 27,689 6,808 21,426 Baldwin County, AL 25,712 14,614 24,488 6,430 20,237 Barbour County, AL 19,389 10,058 16,854 4,318 13,590 Bibb County, AL 19,775 12,299 20,609 4,935 15,531 Blount County, AL 22,382 12,657 21,209 5,572 17,536 Bullock County, AL 14,745 8,204 13,747 3,088 9,719 Butler County, AL 16,054 10,206 17,102 4,479 14,096 Calhoun County, AL 23,802 13,665 22,898 6,536 20,570 Chambers County, AL 21,256 12,304 20,618 6,092 19,173 Cherokee County, AL 21,368 12,004 20,115 5,522 17,379 Chilton County, AL 21,627 11,879 19,905 4,940 15,547 Choctaw County, AL 17,115 10,134 16,981 4,550 14,320 Clarke County, AL 19,067 12,091 20,261 5,215 16,413 Clay County, AL 19,252 10,984 18,406 5,109 16,079 Cleburne County, AL 21,158 12,782 21,418 5,792 18,229 Coffee County, AL 23,905 14,148 23,707 6,200 19,513 Colbert County, AL 22,378 15,445 25,881 6,803 21,410 Conecuh County, AL 15,992 9,211 15,435 3,846 12,104 Coosa County, AL 20,279 10,968 18,379 5,600 17,624 Covington County, AL 18,394 11,209 18,783 5,052 15,900 Crenshaw County, AL 16,460 8,906 14,924 3,740 11,771 Cullman County, AL 21,672 12,117 20,304 5,581 17,565 Dale County, AL 24,091 12,627 21,159 7,066 22,238 Dallas County, AL 16,493 10,565 17,704 4,987 15,695 DeKalb County, AL 20,135 11,475 19,228 4,715 14,839 Elmore County, AL 26,341 14,985 25,110 5,993 18,861 Escambia County, AL 18,472 11,580 19,404 5,497 17,300 Etowah County, AL 22,314 13,320 22,320 6,717 21,140 Fayette County, AL 19,844 11,878 19,904 4,822 15,176 Franklin County, AL 17,907 12,112 20,296 5,402 17,001 Geneva County, AL 20,027 10,866 18,208 5,030 15,830 Greene County, AL 11,990 7,406 12,410 2,569 8,085 Hale County, AL 14,508 8,236 13,801 3,248 10,222 Henry County, AL 22,130 11,627 19,483 4,429 13,939 Houston County, AL 24,813 14,075 23,585 6,424 20,218 Jackson County, AL 21,910 13,772 23,077 5,684 17,889 Jefferson County, AL 25,858 15,656 26,234 7,518 23,661 Lamar County, AL 20,618 12,695 21,273 4,329 13,624 Lauderdale County, AL 23,690 15,093 25,291 6,788 21,363 March 12th, 2003 Page 87 of 157 5 1200  County Income Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 A B C D E F Lawrence County, AL 21,519 12,097 20,271 5,524 17,385 Lee County, AL 21,227 11,655 19,530 6,615 20,819 Limestone County, AL 26,875 14,223 23,833 6,133 19,302 Lowndes County, AL 15,584 8,383 14,047 3,288 10,348 Macon County, AL 15,642 8,843 14,818 4,161 13,096 Madison County, AL 33,048 16,957 28,414 9,788 30,805 Marengo County, AL 18,663 10,494 17,585 4,137 13,020 Marion County, AL 18,455 11,964 20,048 5,413 17,036 Marshall County, AL 21,458 12,433 20,834 5,830 18,348 Mobile County, AL 22,994 14,702 24,636 6,968 21,930 Monroe County, AL 21,140 11,596 19,431 4,476 14,087 Montgomery County, AL 26,551 14,877 24,929 7,075 22,266 Morgan County, AL 28,364 15,790 26,459 7,533 23,708 Perry County, AL 13,769 7,856 13,164 3,871 12,183 Pickens County, AL 17,879 10,436 17,487 4,444 13,986 Pike County, AL 17,312 9,748 16,334 4,568 14,376 Randolph County, AL 19,440 10,398 17,424 5,052 15,900 Russell County, AL 20,995 11,344 19,009 5,347 16,828 St. Clair County, AL 24,106 14,485 24,272 5,876 18,493 Shelby County, AL 36,852 18,272 30,618 6,323 19,900 Sumter County, AL 12,811 9,185 15,391 3,413 10,741 Talladega County, AL 21,378 12,625 21,155 6,225 19,591 Tallapoosa County, AL 22,020 12,476 20,906 5,636 17,738 Tuscaloosa County, AL 23,056 13,119 21,983 6,307 19,849 Walker County, AL 20,464 13,185 22,094 5,451 17,155 Washington County, AL 20,082 12,745 21,356 5,093 16,029 Wilcox County, AL 12,437 8,261 13,843 3,274 10,304 Winston County, AL 17,936 11,995 20,100 5,622 17,694 Alaska $ 41,408 $ 25,414 $ 42,586 $ 11,817 $ 37,191 Aleutians East Borough, AK 42,384 NA NA NA NA Aleutians West Census Area, 35,187 19,389 32,490 8,465 26,641 Anchorage Borough, AK 43,946 27,375 45,872 12,928 40,687 Bethel Census Area, AK 25,402 13,656 22,883 4,468 14,062 Bristol Bay Borough, AK 51,112 33,516 56,162 11,125 35,013 Dillingham Census Area, AK 28,779 18,977 31,799 NA NA Fairbanks North Star Borough 37,468 23,647 39,625 NA NA Haines Borough, AK 36,048 20,893 35,010 12,216 38,446 Juneau Borough, AK 47,924 30,834 51,668 13,841 43,561 Kenai Peninsula Borough, AK 42,403 23,660 39,646 NA NA Ketchikan Gateway Borough, A 45,172 27,015 45,268 NA NA Kobuk Census Area NA 17,756 29,753 6,215 19,560 Kodiak Island Borough, AK 44,815 26,421 44,273 NA NA Lake and Peninsula Borough, 25,231 NA NA NA NA Matanuska Susitna Borough, A 40,745 23,483 39,350 9,155 28,813 Nome Census Area, AK 30,144 14,550 24,381 6,875 21,637 North Slope Borough, AK 50,473 31,378 52,579 NA NA March 12th, 2003 Page 88 of 157 5 1200  County Income Record for the 316( b) Notice of Data Availability: Non Use Benefits Meta Analysis Literature Review 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 A B C D E F Northwest Arctic Borough, AK 33,313 NA NA NA NA Outer Ketchikan Census Area NA 18,964 31,778 8,125 25,571 Prince of Wales Census Area NA 25,144 42,133 11,440 36,004 Prince of Wales Outer Ketchi 39,495 21,947 36,776 NA NA Sitka Borough, AK 43,337 31,133 52,169 12,473 39,255 Skagway Yakutat Angoon Censu 38,583 21,396 35,853 NA NA Southeast Fairbanks Census A 30,222 15,903 26,648 9,239 29,077 Valdez Cordova Census Area, 47,500 27,469 46,029 NA NA Wade Hampton Census Area, AK 20,586 11,373 19,057 3,320 10,449 Wrangell Petersburg Census A 42,020 24,403 40,892 10,377 32,659 Yukon Koyukuk Census Area, A 23,945 12,371 20,730 11,367 35,774 Arizona $ 27,540 $ 16,448 $ 27,562 $ 8,199 $ 25,804 Apache County, AZ 14,100 11,057 18,528 4,612 14,515 Cochise County, AZ 22,425 13,668 22,903 7,480 23,541 Coconino County, AZ 26,112 15,962 26,747 7,779 24,482 Gila County, AZ 20,964 13,828 23,171 7,021 22,097 Graham County, AZ 18,455 12,479 20,911 6,148 19,349 Greenlee County, AZ 27,491 21,396 35,853 9,589 30,179 La Paz County, AZ 16,555 ( NA) ( NA) ( NA) ( NA)