| Literature DB >> 29568707 |
Lin Shu1,2.
Abstract
A gambling or "game" phenomenon can be observed in the complex relationship between sources and receptors of ecological compensation among multiple stakeholders. This paper investigates the problem of gambling to determine payment amounts, and details a method to estimate the ecological compensation amount related to water resources in the Wuxijiang River reservoir area in China. Public statistics and first-hand data obtained from a field investigation were used as data sources. Estimation of the source and receptor amount of ecological compensation relevant to the water resource being investigated was achieved using the contingent valuation method (CVM). The ecological compensation object and its benefit and gambling for the Wuxijiang River water source area are also analyzed in this paper. According to the results of a CVM survey, the ecological compensation standard for the Wuxijiang River was determined by the CVM, and the amount of compensation was estimated. Fifteen blocks downstream of the Wuxijiang River and 12 blocks in the water source area were used as samples to administer a survey that estimated the willingness to pay (WTP) and the willingness to accept (WTA) the ecological compensation of Wuxijiang River for both nonparametric and parametric estimation. Finally, the theoretical value of the ecological compensation amount was estimated. Without taking other factors into account, the WTP of residents in the Wuxi River water source was 297.48 yuan per year, while the WTAs were 3864.48 yuan per year. The theoretical standard of ecological compensation is 2294.39-2993.81 yuan per year. Under the parameter estimation of other factors, the WTP of residents in the Wuxi River water source area was 528.72 yuan per year, while the WTA was 1514.04 yuan per year. The theoretical standard of ecological compensation is 4076.25-5434.99 yuan per year. The main factors influencing the WTP ecological compensation in the Wuxi River basin are annual income and age. The main factors affecting WTA are gender and attention to the environment, age, marital status, local birth, and location in the main village.Entities:
Keywords: Ecological compensation; Ecological services; Gambling; Wuxijiang River reservoir area
Year: 2018 PMID: 29568707 PMCID: PMC5845578 DOI: 10.7717/peerj.4475
Source DB: PubMed Journal: PeerJ ISSN: 2167-8359 Impact factor: 2.984
Figure 1Administrative region division of the Wuxijiang River.
The county, city, and district referred to herein in this article are all county-level units the Wuxijiang River reservoir was chosen as the research region. Its administrative region mainly involves the four townships of Hunan, Jucun, Lingyang, and Huangtankou, in the Qujiang district of Quzhou.
Figure 2Location of research region on Map of China.
Hangzhou is the capital city of Zhejiang province.
Figure 3Watershed system of Wuxijiang River.
WTP samples distribution.
| Layer | Block | Sampling proportion (%) | Sample size |
|---|---|---|---|
| 1st layer | Baidu village | 5.25 | 29 |
| 2nd layer | Qiaotouwang village | 5.43 | 30 |
| 3rd layer | Xiajiang village | 5.43 | 30 |
| 4th layer | Shangjiang village | 5.25 | 29 |
| 5th layer | Wang village | 7.61 | 42 |
| 6th layer | Zaojiao village | 5.07 | 28 |
| 7th layer | Yejia village | 5.80 | 32 |
| 8th layer | Meijia village | 6.88 | 38 |
| 9th layer | Zijing residential area (community) | 8.15 | 45 |
| 10th layer | Jingui residential area (community) | 7.25 | 40 |
| 11th layer | Wenjingyuan (community) | 7.43 | 41 |
| 12th layer | Yulongwan area (community) | 9.60 | 53 |
| 13th layer | Chongwenguolv (community) | 7.61 | 42 |
| 14th layer | Juhuabin first residential area (community) | 7.07 | 39 |
| 15th layer | Juhuabin second residential area (community) | 6.16 | 34 |
| Total | 15 blocks | 100.00 | 552 |
Note:
The survey on WTP covered 15 blocks in the Wuxijiang River water source.
Socio-economic characteristics of sample of willingness to pay.
| Features | Items | Sample size | Ratio (%) |
|---|---|---|---|
| Gender | Male | 281 | 50.91 |
| Female | 271 | 40.09 | |
| Age (years old) | Under 20 | 39 | 7.07 |
| 20–30 | 74 | 13.41 | |
| 30–40 | 102 | 18.48 | |
| 40–50 | 117 | 21.2 | |
| 50–60 | 97 | 17.57 | |
| Over 60 | 123 | 22.28 | |
| Family annual income (thousand yuan) | Less than 20 | 118 | 21.38 |
| 20–30 | 94 | 17.03 | |
| 30–40 | 63 | 11.41 | |
| 40–50 | 45 | 8.15 | |
| 50–60 | 74 | 13.41 | |
| 60–70 | 29 | 5.25 | |
| 70–80 | 35 | 6.34 | |
| Above 80 | 94 | 17.03 | |
| Occupation | State organizations, persons in charge in enterprises and institutions | 59 | 10.69 |
| Professional and technical personnel | 42 | 7.61 | |
| Clerks and related personnel | 17 | 3.08 | |
| Commercial staff | 22 | 3.99 | |
| Service industry staff | 44 | 7.97 | |
| Agriculture, forestry, animal husbandry, and fishery workers | 51 | 9.24 | |
| Civil servants, teachers, journalists | 35 | 6.34 | |
| Medical staff, lawyers, financial practitioners | 24 | 4.35 | |
| Soldiers | 2 | 0.36 | |
| Other | 256 | 46.38 | |
| Educational level | Primary school and below | 150 | 27.17 |
| Junior middle school | 108 | 19.57 | |
| High school (including secondary school, vocational school) | 112 | 20.29 | |
| Junior college | 62 | 11.23 | |
| Undergraduate | 110 | 19.93 | |
| Graduate students (Master’s) and above | 10 | 1.81 |
Socio-economic characteristics of sample of willingness to accept.
| Features | Option | Sample size | Ratio (%) |
|---|---|---|---|
| Gender of interviewee | Male | 206 | 54.21 |
| Female | 357 | 45.79 | |
| Gender of householder | Male | 352 | 92.63 |
| Female | 28 | 7.37 | |
| Age of interviewee (years old) | Children (0–6) | 0 | 0.00 |
| Juveniles (7–17) | 3 | 0.79 | |
| Youth (18–40) | 30 | 7.89 | |
| Middle age (41–65) | 247 | 65.00 | |
| Seniors (more than 66) | 100 | 26.32 | |
| Education level of householder | Primary school and below | 194 | 51.05 |
| Middle school | 134 | 35.26 | |
| High school | 43 | 11.32 | |
| University | 9 | 2.37 | |
| Age of the householder (years old) | Children (0–6) | 0 | 0.00 |
| Juveniles (7–17) | 0 | 0.00 | |
| Youth (18–40) | 9 | 2.37 | |
| Middle age (41–65) | 257 | 67.63 | |
| Seniors (more than 66) | 114 | 0.30 | |
| Work situation | Fixed job | 243 | 63.95 |
| Unfixed job | 123 | 36.05 | |
| Have modern toilet | Yes | 204 | 53.68 |
| No | 176 | 46.32 | |
| Head of householder a local born | Yes | 349 | 91.84 |
| No | 31 | 8.16 | |
| Moved within five years | Yes | 18 | 4.74 |
| No | 362 | 95.26 | |
| Dwell near the main road | Yes | 347 | 91.32 |
| No | 33 | 8.68 | |
| Marital status | Unmarried | 11 | 2.90 |
| Married | 336 | 88.42 | |
| Widowed | 33 | 8.68 | |
| Home’s exterior | Mud room | 75 | 19.74 |
| Single layer brick tile room | 137 | 36.05 | |
| Buildings | 168 | 44.21 | |
| Is it cash from non-farm industry | Yes | 24 | 6.32 |
| No | 356 | 93.68 |
Note:
The detailed socio-economic characteristics of WTA interviewees.
WTP for water source ecological compensation of Wuxijiang River.
| WTP (Yuan/household·month) | WTP (Yuan/household·year) | Frequency (household) | Positive WTP rate (%) | Total positive WTP rate (%) | WTP rate (%) | Total WTP rate (%) |
|---|---|---|---|---|---|---|
| 0 | 0 | 255 | – | – | 46.2 | 46.2 |
| 10 | 120 | 111 | 37.37 | 37.37 | 20.11 | 66.3 |
| 20 | 240 | 54 | 18.18 | 55.56 | 9.78 | 76.09 |
| 30 | 360 | 23 | 7.74 | 63.3 | 4.17 | 80.25 |
| 50 | 600 | 56 | 18.86 | 82.15 | 10.14 | 90.4 |
| 80 | 960 | 4 | 1.35 | 83.5 | 0.72 | 91.12 |
| 100 | 1,200 | 35 | 11.78 | 95.29 | 6.34 | 97.46 |
| 120 | 1,440 | 1 | 0.34 | 95.62 | 0.18 | 97.64 |
| 160 | 1,920 | 1 | 0.34 | 95.96 | 0.18 | 97.83 |
| 200 | 2,400 | 1 | 0.34 | 99.33 | 0.18 | 99.46 |
| 300 | 3,600 | 9 | 3.03 | 98.99 | 1.63 | 99.64 |
| 500 | 6,000 | 2 | 0.67 | 100 | 0.36 | 100 |
WTA of water source ecological compensation of Wuxijiang River.
| WTA Yuan/(household·year) | Frequency (household) | Positive WTA rate (%) | Total positive WTA rate (%) | WTA rate (%) | Total WTA rate (%) |
|---|---|---|---|---|---|
| 0 | 179 | – | – | 47.11 | 47.11 |
| 300 | 1 | 0.50 | 0.50 | 0.26 | 47.37 |
| 400 | 3 | 1.49 | 1.99 | 0.79 | 48.16 |
| 450 | 3 | 1.49 | 3.48 | 0.79 | 48.95 |
| 500 | 4 | 1.99 | 5.47 | 1.05 | 50.00 |
| 550 | 3 | 1.49 | 6.96 | 0.79 | 50.79 |
| 600 | 1 | 0.50 | 7.46 | 0.26 | 51.05 |
| 700 | 1 | 0.50 | 7.96 | 0.26 | 51.31 |
| 750 | 1 | 0.50 | 8.46 | 0.26 | 51.57 |
| 800 | 4 | 1.99 | 10.45 | 1.05 | 52.62 |
| 1,000 | 9 | 4.48 | 14.93 | 2.37 | 54.99 |
| 1,200 | 7 | 3.48 | 18.41 | 1.85 | 56.84 |
| 1,440 | 1 | 0.50 | 18.91 | 0.26 | 57.10 |
| 1,500 | 4 | 1.99 | 20.90 | 1.05 | 58.15 |
| 1,800 | 4 | 1.99 | 22.89 | 1.05 | 59.20 |
| 2,000 | 11 | 5.47 | 28.36 | 2.90 | 62.10 |
| 2,400 | 5 | 2.49 | 30.85 | 1.32 | 63.42 |
| 2,500 | 3 | 1.49 | 32.34 | 0.79 | 64.21 |
| 3,000 | 3 | 1.49 | 33.83 | 0.79 | 65.00 |
| 3,350 | 1 | 0.50 | 34.33 | 0.26 | 65.26 |
| 3,600 | 5 | 2.49 | 36.82 | 1.32 | 66.58 |
| 4,000 | 5 | 2.49 | 39.31 | 1.32 | 67.90 |
| 4,200 | 1 | 0.50 | 39.81 | 0.26 | 68.16 |
| 4,500 | 1 | 0.50 | 40.31 | 0.26 | 68.42 |
| 4,800 | 8 | 3.98 | 44.29 | 2.11 | 70.53 |
| 5,000 | 5 | 2.49 | 46.78 | 1.32 | 71.85 |
| 5,500 | 1 | 0.50 | 47.28 | 0.26 | 72.11 |
| 6,000 | 10 | 4.98 | 52.26 | 2.63 | 74.74 |
| 7,000 | 1 | 0.50 | 52.76 | 0.26 | 75.00 |
| 7,200 | 4 | 1.99 | 54.75 | 1.05 | 76.05 |
| 8,400 | 1 | 0.50 | 55.25 | 0.26 | 76.31 |
| 9,600 | 1 | 0.50 | 55.75 | 0.26 | 76.57 |
| 10,000 | 6 | 2.99 | 58.74 | 1.58 | 78.15 |
| 10,800 | 2 | 1.00 | 59.74 | 0.53 | 78.68 |
| 12,000 | 11 | 5.47 | 65.21 | 2.90 | 81.58 |
| 14,400 | 6 | 2.99 | 68.20 | 1.58 | 83.16 |
| 15,000 | 1 | 0.50 | 68.70 | 0.26 | 83.42 |
| 16,200 | 1 | 0.50 | 69.20 | 0.26 | 83.68 |
| 18,000 | 5 | 2.49 | 71.69 | 1.32 | 85.00 |
| 19,200 | 2 | 1.00 | 72.69 | 0.53 | 85.53 |
| 20,000 | 5 | 2.49 | 75.18 | 1.32 | 86.85 |
| 21,600 | 7 | 3.48 | 78.66 | 1.84 | 88.69 |
| 24,000 | 8 | 3.98 | 82.64 | 2.11 | 90.80 |
| 25,000 | 1 | 0.50 | 83.14 | 0.26 | 91.06 |
| 28,000 | 1 | 0.50 | 83.64 | 0.26 | 91.32 |
| 28,800 | 4 | 1.99 | 85.63 | 1.05 | 92.37 |
| 30,000 | 8 | 3.98 | 89.61 | 2.11 | 94.48 |
| 36,000 | 9 | 4.48 | 94.09 | 2.37 | 96.85 |
| 36,500 | 1 | 0.50 | 94.59 | 0.26 | 97.11 |
| 38,400 | 3 | 1.49 | 96.08 | 0.79 | 97.90 |
| 43,200 | 4 | 1.99 | 98.07 | 1.05 | 98.95 |
| 48,000 | 2 | 1.00 | 99.07 | 0.53 | 99.48 |
| 50,400 | 1 | 0.50 | 99.57 | 0.26 | 99.74 |
| 72,000 | 1 | 0.50 | 100.00 | 0.26 | 100 |
| Tot up | 380 | 100.00 | – | 100.00 | – |
WTP of the interviewee in the Wuxijiang River water source and the regression results of the related variables.
| Variable | (1) Forward selection stepwise regression Ln WTP | (2) Backward selection stepwise regression Ln WTP | (3) Least square method Ln WTP |
|---|---|---|---|
| Annual income | 0.112 | 0.112 | 0.102 |
| Concern for the environment | −0.128 | −0.128 | −0.111 [−1.61] |
| Age | −0.00780 | −0.00780 | −0.00733 [−1.59] |
| Gender | 0.196 | 0.196 | 0.197 |
| Education level | – | – | 0.0370 [0.71] |
| Occupation | – | – | −0.000680 [−0.04] |
| Water price | – | – | 0.0538 [0.32] |
| Water consumption | – | – | 0.0189 [0.11] |
| _cons | 3.348 | 3.348 | 3.112 |
| 552 | 552 | 552 | |
| 0.6837 | 0.6837 | 0.149365 |
Notes:
The value in [] is the value of t.
p < 0.1,
p < 0.05,
p < 0.01.
WTA of the interviewee in the Wuxijiang River water source and the regression results of the related variables.
| Variable | (1) Forward selection stepwise regression Ln WTA | (2) Backward selection stepwise regression Ln WTA | (3) Least square method Ln WTA |
|---|---|---|---|
| Age | 0.000130 | 0.000130 | 0.000115 |
| Gender | 0.0000445 | 0.0000445 | 0.0000487 |
| Marital status | −0.0000412 | −0.0000412 | −0.0000452 |
| Family population | 0.000593 [1.46] | 0.000593 [1.46] | 0.000607 [1.46] |
| Born locally | −0.0000736 | −0.0000736 | −0.000101 |
| In the main village | −0.0419 | −0.0419 | −0.0368 |
| Immigrated in five years | − | − | 0.0000104 [1.23] |
| Education level | − | − | 0.0000765 [1.13] |
| Number of acres of land | − | − | 0.000000775 [0.52] |
| _cons | 4.391 | 4.391 | 4.585 |
| 380 | 380 | 380 | |
| 0.896 | 0.896 | 0.88784 |
Notes:
The value in [] is the value of t.
p < 0.1,
p < 0.05,
p < 0.01.