7th Sino-German Workshop on Biodiversity Conservation Challenges in Water Quality and Quantity Evaluation of Inland River Basin Restoration Policy: Quantifying Full Values, Public Preference Heterogeneity and Regional Decision Support Minjuan Zhao 1, Liuyang Yao 1, Tao Xv 1 1. Applied Economic Center, Northwest A&F University July 8, 2014
1 Introduction 2 Framework and Model 3 Empirical Study 4 Conclusions and Implication
Ecosystem of Inland River Watershed Providing multi-functions non-market goods and services that are generally viewed as a positive externality are often underestimated or ignored, if left to market forces (Turner and Daily 2008). In past fifties years, more than half of ecosystem functions in China turned into fragile and deteriorative status (Development Research Center of State Council, 2007).
Ecosystem Restoration The accelerating deterioration, along with the presence of positive externalities, provide a strong rationale for government intervention (e.g. Pacini et al. 2004). restoration main contents ecological restoration and water utilization (Hu et al., 2012). the goals To meet the demands of economic and social development, To control pollution To adapt uncertainties of accompany climate change To balance ecosystem goods and services
Ecosystem Restoration The goals of restoration policy were not always be achieved as expected (Gao, et al., 2011). e.g., water allocation: ecological use was taken by economy issue water quality: run-off decreased sharply and dried up simultaneously, multi-source pollution shortage in ecosystem services and goods provided. Something was ignored or missed in policy evaluation and making.
Questions Without comprehensive information on economic benefits, costs and tradeoffs can contribute to unpredictable and unsustainable. (Holland et al., 2010). Consequently, the real value of ecosystem usually cannot be recognized and captured in evaluation. Regulatory agencies worldwide are increasingly being called upon to assess the full economic benefit and costs of legislation and development projects that impact the natural ecosystem (MA, 2005). Quantifying the full value of ecosystem including non-market values provided by ecosystem services and goods that are of primary concern to policymakers and the public (Yohe et al. 2010).
Questions The willingness of stakeholders in restoration would influence directly implement and effects of restoration policies. However, their willingness does not involve enough into policy evaluation and policymaking, which cause a lack of regional decision support (Giupponi, 2007).
Questions Economists use how much people are willing to pay to assess the non-market welfare provided by ecological policy, which is defined as willingness to pay (WTP). WTP -- subjective definition -- Personal characteristics (e.g., age, education, gender, job) and psychological characteristics (e.g., confidence in agent) vary across people, which possibly lead to heterogeneity in willingness to identity restoration policy (Zhao et.al. 2013).
Related Studies Water demand-oriented or supply-oriented to assess water policies (Chen, 2004; Su, 2008) to assess effects of single goal policy (Feng, 2006) or strategic policies(guo, 2009) on equilibrium of water demand and supply. Oriented on regional development (Wei, 2011; Xv, 1999), some studies use ecological indicators by AHP to measure the nonmarket value of ecological goods, and services and assess the ecological contribution to regional development (Ye et al.,2012; Su et al., 2006).
CEs and WTP WTP is a measure of the value of the commodity to individual and also reflects the welfare that commodity provides. In econometrics, WTP is described as a function of policy outcomes represented by ecological attributes in the related evaluation studies. Choice experiments (CEs) is considered the most promising approach to assess WTP (Hanley et al. 2006; Holland et al. 2010; Johnston et al. 2005; 2011)..
CEs and Public Supports In terms of linkages of potential variation of ecosystem caused by restoration and the public welfare, CEs designed multiple policy options. The choice set consists at least two options, one of which is the status quo option (Adamowicz et al. 1998), providing respondents ecosystem improvement of policy and costs for improvements. Respondents would choose their most preferred option from a choice set (Adamowicz et al. 1998) that maximize their utility with given constraints (McFadden & Rund 1994).
CEs and Public Supports These options provide respondents ecosystem improvement of policy and costs for improvements. to provide ability to reveal the public preferences (similar to vote) and supports to the restoration policies. to obtain the public preference function and generates an empirical estimate of a utility function to indicate marginal utility of ecological goods and services, and public preferences and supports, according to the choice of numerous respondents
Mixed logit and Preference Heterogeneity To discover preference heterogeneity may help policymaker better understand the public willingnes. In econometrics, mixed logit model to estimated public s preference deviation coefficients of given variable are in certain statistical distributions. mean and variance estimated of coefficients refer mean value, deviation from mean value of the public preference, respectively.
Utility Function and Heterogeneity of Different Population The utility that respondent n obtains from option j in choice situations t is (Hensher & Greene 2003): U ntj b' x ntj x ' n * where, n b n with density f ( jn ), if the coefficient * vector n is varies in the population, where is the true parameters of this distribution. Based on these assumptions and the choice situation t, the probability of respondent n chooses the option j from scenario J is (Train 2003): ' exp( nx ntj) Lntj( j ntj) ' exp( x ) j ntj ntj n ntj
Marginal WTP & Heterogeneity in Different Populations The implicit price usually was defined as the WTP of single good of service. That is, publics WTP for the marginal changes of a single indicator (mainly is improvement), namely, MWTP. For example, the formula of the marginal WTP of a non-monetary variable k th is: MWTP km cost The heterogeneous level of different populations WTP deviating from the mean value can be represented as: MWTP kd km kd / / cost
WTP for Entire Restoration Policy The meaning of entirety WTP is the consumers highest willingness to pay or the minimum compensation he want to keep the welfare level before changes under the changed price system, it is also known as compensating surplus (Morrison & Bergland 2006): 1 CS ( V0 V1 ) cost where, V 1 is the mean coefficient of monetary variable (cost), V is the initial normal utility, 0 cos t is the utility after the implementation of the restoration policy.
Shiyang River Watershed
Shiyang River Watershed
Shiyang River Watershed A good case for study provided by Shiyang watershed one of the biggest four inland river in arid and semi-arid Scarcity in water has remained a long history. Underground water was overused seriously Xerophytes of downstream is almost extinct The areas of Qingtu Lake at downstream reduced.
Shiyang River Watershed A good case for study provided by Shiyang watershed land desertized, salinized and water pollution The comprehensive restoration in the watershed has became an important investment of the central and local government.
Questionnaire: Attributes and variables Attributes/Variables Landscape (X 1 ) Tour (X 2 ) Sand storm (X 3 ) Forest (X 4 ) Grassland (X 5 ) Xerophyte (X 6 ) Water quantity (X 7 ) Water quality (X 8 ) Cost (X 9 ) Ecological functions Enjoy the scenery Leisure and recreation Prevent weathering and erosion Habitat Vegetation restoration Vegetation restoration Agriculture and industrial water; habitat of wildlife Agriculture and industrial water; habitat of wildlife The annual cost of ecological improvement per household
Questionnaire: Attributes Levels Attributes The levels of attributes Landscape (X 1 ) 9.8*; 15; 20; 25; 30 Tour (X 2 ) 30*; 35; 40; 45; 50 Sand storm (X 3 ) 139*;100; 75; 55; 40; 35; 20 Forest (X 4 ) 46.3*; 50; 57; 63; 67 Grassland (X 5 ) 55*; 60; 70; 75 Xerophytes (X 6 ) 0*; 10; 35; 50; 62; 70; 80 Water quantity (X 7 ) 2.5*;2.6; 2.7; 2.8; 2.9 Water quality (X 8 ) 5*;4; 3; 2 Cost (X 9 ) 0*;50; 150; 250; 300; 400; 500
Questionnaire Design D-optimal experimental method The questions were constructed with all levels of attributes orthogonally arranged. Each attribute could form 128 random cognitive option sets The option sets was contain by 60 versions of questionnaires Each choice involves three alternatives: a status quo option and, two alternative restoration options (labeled as Plan A and Plan B) that varied across the three discrete choices
Questionnaire Sample
Survey The survey was complimented by households interview. During each survey, the respondents were told that three choice sets are independent. The survey was complimented by households interview, and finished 1012 questionnaires, including 900 (88.9%) of them are valid.
Data Management The valid/distributed questionnaires upstream Gulang County, 227/253, 89.7% Jinchuan District, 146/191, 76.4% Midstream Liangzhou District, 52 / 285, 88.4% Downstream Minqin County, 275/283, 97.2% A total number of 8100 samples (900*3*3 =8100) get into the estimation.
Variables Data Summarized Mean Standard Dev. Minimum Maximum Landscape (X 1 ) 16.867 7.444 10 30 Tour (X 2 ) 36.948 7.481 30 50 Sand storm (X 3 ) 82.964 51.279 20 139 Forest (X 4 ) 53.261 8.113 46 67 Grassland (X 5 ) 61.90 8.049 55 75 Xerophytes (X 6 ) 4.496 4.823 0 12 Water quantity (X 7 ) 2.648 0.154 2.5 2.9 Water quality (X 8 ) 2.046 1.164 1 4 Cost (X 9 ) 165.741 151.772 0 500
Random Coefficients Variables Coefficient Standard Deviation positive share Landscape (X 1 ) Tour (X 2 ) Sand storm (X 3 ) Forest (X 4 ) Grassland (X 5 ) Xerophytes (X 6 ) Water quantity (X 7 ) Water quality (X 8 ) Cost (X 9 ) 0.0710*** (0.0118) 0.0249 *** (0.0102) 0.0183 *** (0.0022) 0.0697 *** (0.0109) 0.0544 *** (0.0096) 0.1428 *** (0.0208) 3.1635 *** (0.5355) 0.7975 *** (0.0925) - 0.0196 *** (0.0017) 0.1107*** (0.0195) 0.1361 *** (0.021) 0.0266 *** (0.0033) 0.1015 *** (0.0172) 0.0845 *** (0.0174) 0.2549 *** (0.0311) 6.1220 *** (0.9801) 1.1164 *** (0.1292) LL Function - 2394 74% 57% 75% 75% 74% 71% 70% 76% / /
Results: Random Coefficients All the mean coefficients of non-monetary are significant positive that are all assumed in normal distributions. Coefficient of monetary (cost) variable (X 9 ) is significant negative that is set as a fixed one (Scarpa et al. 2007; Louviere 2006). Standard deviation refers to the degree of the deviation that the estimated marginal utilities of different population from the mean value. Heterogeneous preference is caused possibly by, such as, regional social economy, natural resource endowment and the specific household characteristics, and so on.
Variable Landscape (X 1 ) Tour (X 2 ) Sand storm (X 3 ) Forest (X 4 ) Grassland (X 5 ) Xerophytes (X 6 ) Water quantity (X 7 ) Water quality (X 8 ) MWTP MWTP 3.60 (0.49) 1.27 (0.50) 0.93 (0.11) 3.56 (0.44) 2.79 (0.42) 7.29 (0.82) 160.79 (25.91) 40.57 (3.44) Standard deviation 5.66 (0.90) 6.89 (0.91) 1.36 (0.15) 5.15 (0.71) 4.31 (0.78) 13.06 (1.30) 313.42 (44.76) 57.19 (5.17) Cumulative WTP 72.72 25.40 110.67 73.69 55.80 583.20 64.32 121.71
Results: MWTP MWTP for all ecological attributes are significantly positive. Deviation of the WTP from the mean value among different populations is significant. The cumulative WTP of per household to achieve the program objectives by 2020 is also showed in Table A finding is, the relative high willingness of the public for ecological goods and services are that directly related to households production and living, e.g. water quality (RMB49.57/HH, year), water quantity(rmb160.79/hh, year) Also, the most concerned on ecological restoration is on xerophytes restoration (e.g. Populus, Seabuckthorn).
Compensating Surplus(CS) Situation Degree Land scape (X 1 ) Indicator levels of different scenarios Tour (X 2 ) Sand storm (X 3 ) Forest (X 4 ) Grass land (X 5 ) Xerophyte (X 6 ) Water quantity (X 7 ) Water quality (X 8 ) CS (yuan/ HH. year) 1 2 3 Smaller (1%) 11 31 100 50 60 1 2.6 Moderate (10%) 20 40 55 57 65 10 2.7 Great (20%) 30 50 20 67 75 80 2.9 Level Ⅲ Level Ⅱ Level Ⅲ Level Ⅱ Level Ⅲ Level Ⅱ 173.70 *** (10.44) 192.57 *** (13.09) 378.05 *** (19.89) 419.34 *** (21.48) 1064.14 *** (68.33) 1105.01 *** (69.66)
The biggest improvement of Level Ⅲ is consistent with the goals of SRRP <Shiyang River Restoration Plan> by 2020. The annual WTP is as high as 1064.14 yuan/household to realize the objective of SRRP (by 2020). According to the discount rate of 4%,the cumulative present value (based on 2012) CS of per household to realize the goals of SRRP (by 2020) is 8228.72 yuan, the total WTP is RMB 3.954 billion. Notes: The total households are 530.66 thousands (population in 2003 is the baseline and increase rate is 0.57%).
Conclusions and Implications The preferences across attributes are obviously different, referring to various willingness to ecological attributes. Consequently, the restoration policies should firstly focus on investment in ecological functions with higher marginal utility and MWTP. For Shiyang River Watershed, the MWTP of the ecological goods and services directly related to the inhabitants production and living (e.g. water quality and quantity, xerophytes of downstream, sandstorms, etc.) that will bring about more benefits for the publics.
Conclusions and Implications There are significant heterogeneity preferences across populations on each ecosystem attributes. So, the restoration policy may balance the allocation of every ecological good and service in different river section and populations. Especially, the allocation of water quantity in different populations in this case.
Conclusions and Implications Shiyang River Restoration Program planned to invest 1.645 billion yuan during 2010~2020, which is lower than the estimated CS in this paper (the total accumulative WTP of public was 3.954 billion yuan). So, the current restoration policy investment is in marginal return increasing return in marginal utility, in general.
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