International Journal of Sustainable Development & World Ecology, 2015 Vol. 22, No. 3, 242–250, http://dx.doi.org/10.1080/13504509.2015.1004379
Applying contingent valuation to measure the economic value of forest services: a case study in Northern Jordan Amani Abdullah Al-Assaf* Faculty of Agriculture, Department of Agricultural Economics and Agribusiness, The University of Jordan, PO Box 791, Amman 11910, Jordan (Received 1 October 2014; final version received 30 December 2014) This paper reports an attempt to apply the contingent valuation method (CVM) to value ecosystem services in Jordan’s northern forests. I employed the CVM to obtain an estimate for the population’s willingness to pay (WTP) for restoration and conservation of services in this area. I sampled 300 rural households through in-person interviews, then applied two econometric models to examine the incentives for WTP. The aggregate present value benefit is 3,569,556 Jordanian Dinar for the whole of Jordan’s northern forests; this valuation is based on the amount participants were willing to contribute to maintain forest ecosystem services. The conservation cost is assumed to reflect the direct value gained from human utilization of forest services. Results suggest a correlation between WTP and household income, as well as WTP and classification of services. I assess that income and forest service type most directly shaped participants’ WTP for forest conservation. The study also indicates that the CVM can successfully be applied to Jordan and may be a viable and potentially useful direction for future research on environment valuation in other developing countries in the Middle East. Keywords: forest services; contingent valuation method; conservation; economic value; Jordan
Introduction The field of ecosystem services (ESs) is emerging as a dominant theme for sustainable natural resource management and land use policy. Since the release of Millennium Ecosystem Assessment (2005), researchers and policymakers have been leading a global movement to use ES as a guiding framework for merging science and action for conservation purposes. The health of ecosystem functions has declined in recent years due to the combined influence of natural disasters and human activity, highlighting the need to establish adaptable practices of risk prevention – avoiding unreasonable human activities and protecting ecosystems (Wang et al. 2014). Such practices will ensure that human activities do not damage necessary ecological processes and ensure continuity of the ESs flow upon which the welfare of future generations will depend (MEA 2005; Turner et al. 2010). The Millennium Ecosystem Assessment’s approach emphasizes both the direct and indirect values of ESs to human welfare (MEA 2005). This approach placed an emphasis on economic valuation, which can be used to (a) estimate the relative importance of various ecosystems, (b) justify or evaluate particular conservation decisions in particular places, (c) identify how the benefits of a particular conservation decision are distributed, and (d) identify potential sources of sustainable financing (Turner et al. 2007; Plummer 2009; Stenger et al. 2009; Ferraro et al. 2012). Linking ES with conservation can often provide practitioners with access to economic development funds from
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international donors and national governments (Ferraro et al. 2012). The Mediterranean forest ecosystem – the ecosystem evaluated in this study – has evolved under continuous pressure from both the natural environment and human society. This has impacted the derived essential services from these ecosystems (Wang et al. 2014). Despite the low portion of forest area out of the total land area (around 1%), the Food and Agriculture Organization (FAO) observed relative stability in Jordan’s forest cover between 2000 and 2005 (FAO 2010); this reflects the success of national efforts in preserving sylvan ecosystems. Forests in Jordan are a key component in providing a variety of ES: provisioning services (i.e. grazing, wood and non-wood products), regulating services (i.e. land stabilization, watershed management), supporting services (i.e. carbon sequestration), and cultural services (i.e. recreation, tourism). The main objective of this study is to identify the true economic value of forest services to the surrounding communities. The ideology behind this valuation is to identify the direct and indirect benefits of forest ecosystems in monetary terms. Quantifying this value could encourage people to contribute to conservation and restoration programs in an economically logical way. I employed the contingent valuation method (CVM) to place an economic value on environmental goods within the study area, that is conservation activities, endangered species conservation, and protection of habitats. (Sodhi et al. 2010; Loomis
International Journal of Sustainable Development & World Ecology et al. 2000; Farber et al. 2002; Baral et al. 2008; Awad & Holländer 2010; Rosenberger et al. 2012). The CVM is adopted as a comprehensive valuation method for ESs that discovers the specific geographical scope of larger ecosystems with a broad range of ESs to be valued. I seek to explore management options within these ecosystems, providing crucial information to policy-makers and land use mangers alike. In order for forest conservation and restoration projects to be most effective, local communities should be incorporated (Xu et al. 2009; Boström 2012; Cheung & Jim 2013). This community involvement can reduce poverty and ensure that populations derive benefits (services) from forest ecosystems in a sustainable manner. Thondhlana et al. (2012) concluded that different types of services require varying sustainable management plans and emphasized the consideration of disparities in patterns of natural resource dependence among different locals’ income groups (Negi et al. 2013; Al-assaf 2014).
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estimated 87,000 ha in addition to about 2405 km of roadside growth. However, the forests are generally low density, slow growing, degraded, and consequently of low commercial value. Commercial forests are only viable in areas receiving more than 400 mm of precipitation annually. Such plots constitute only 9% of the forestlands (MoA 2011). I selected three northern Mediterranean forests as research sites (Figure 1).
Deciduous oak forests Jordan’s deciduous oak forests are mostly located at altitudes of 100–750 m. There are 419.4 km2 classified as deciduous oak forest, located at the lower borders of the evergreen oak forests; they mix together within a limited area between the pure stands of each type. Deciduous oak forest is mostly found in areas around the Yarmuk River, Ishtafaina area in Ajloun, Al-Alouk area near Jarash, and King Talal Dam northwest of Amman. The rainfall range is about 200–500 mm (Al-eisawi 2012).
Study area Pine forests Found only in the northern region at 550–1000 m above sea level, pine forest covers 190 km2. This forest contains the southernmost native Pinus halepensis forest in the world (Al-eisawi 2012). This ecosystem is located in Ajloun, along the road between the Sakib and Jarash, Dibbeen, Zie, and Salt districts. The Royal Society for Conservation of Nature (RSCN) established the Dibbeen
The forested region in Jordan is limited, extending from Irbid in the north to Ras En-Naqab in the south. The altitude ranges from 100 to 1250 m above sea level, while rainfall ranges from 200 to 700 mm. The region with the highest rainfall is the most fertile and exhibits the most productive climate for this forest ecosystem. Forests in Jordan consist of both natural and man-made woods – including windbreaks and shelterbelts – that cover an 35°0′E
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reserve to protect the last remaining stand of old pine forest in Jordan from fires, urbanization, overgrazing, and the other threats (Al-eisawi 2012).
Evergreen oak forests Evergreen forests are characterized by Quercus calliprinos. This type of northern Jordanian forest ecosystem is located at 500–1250 m above sea level and covers about 1912 km2 with a rainfall range of 500–700 mm. It is located up north in Ammani, Irbid, and Ajloun, as well as in the southern parts of Tafila and Shobak. Evergreen forest comprises a major portion of the forest vegetation in Jordan and appears in both northern and southern areas (Al-eisawi 2012).
Methods Survey instruments and sampling I, along with a team of researchers, surveyed households between August and November 2012, including the presurvey and the formal investigation. I chose an open-ended (OE) questionnaire for the pre-survey, conducting 15 interviews within local communities and with forestry experts. I used a stratified random sampling technique, selecting villages out of those within the forests’ surrounding area. I defined the sample size proportionally to the number of households in each community surrounding the forest. For each forest type, I randomly selected a hundred households – in total, I interviewed 300 households in Jordan’s northern forest region using a face-to-face interviewing method. Using the pre-survey results, I designed a detailed three-part household questionnaire. The first part covered demographic information about the households, such as age, education, occupation, income, and household size. The second part focused on household interaction with the surrounding forest, such as frequency and duration of visits, household activities at the forests, and the purposes of visits to the forests. The respondents ranked the importance of the forest to the whole region and to their own households; I discussed this at length with respondents, ensuring that they were able to distinguish different functions of forest services at different levels (i.e. regional and household levels). The third part was the investigation of willingness to pay (WTP) for forest’s restoration and conservation. I posed questions about a hypothetical fund to restore and conserve forests ecosystems. The core question was, ‘What would be the maximum yearly amount your household would pay for five years?’ The information from this part was used to estimate WTP for restoring forest ecosystems in northern areas.
Contingent valuation method The CVM is a hypothetical direct valuation method that is used to value the use and non-use values of natural
resources and ESs. The CVM is a standardized survey method for estimating maximum WTP – or willingness to accept (WTA) compensation – for use, existence, and bequest values for resources and ESs by individual users (Loomis et al. 2000; Gürlük 2006; Baral et al. 2008; Awad & Holländer 2010; Kosoy & Corbera 2010). In the CVM, researchers propose a hypothetical market to elicit valuations for environmental and public goods. Researchers directly ask people to report their WTP for a benefit. Participants value this benefit based on a Hicksian welfare measure called ‘compensating variation’ (CV). CV is the maximum amount of money that a household can contribute while leaving it just as well-off as it was before environmental quality increase (Haab & McConnell 2002). A wide range of researchers have employed the CVM in forest valuation studies, whose studies have been appropriate and effective in providing either an estimated economic value or a conservation value (e.g. Gürlük 2006; Baral et al. 2008; Bernard et al. 2009; Kosoy & Corbera 2010; Cranford & Mourato 2011). Bateman et al. (2000) and other researchers have presented two formats to acquire the maximum amount of WTP by respondents. In the OE format, the respondent is directly asked the amount he/she is willing to pay. In the dichotomous choice (DC) format, the respondent is asked to choose between pre-specified amounts of money. In this study, the OE format was used to investigate rural WTP for restoring and conserving northern forest in Jordan. I provided open choice to pay, or not to pay, for a conservation fund that would reflect personal interest in preserving forest services. Logistic regression model To estimate the economic value, I developed a responsibility scenario utilizing a hypothetical conservation fund. This scenario is based on the current situation of forestry in northern area of Jordan. I conducted a deep discussion during the interview about the current threats to forests: drought, overgrazing, urbanization, and overharvesting of firewood (influenced by high fuel prices in Jordan). Following the conversation, I asked the participant whether he/she was willing to support a conservation fund for forestry in Jordan. I articulated the assumption that this contribution would not apply any economic burden on his/her household. I hypothesized that a relationship existed between social characteristics of interviewees, their location among the three different types of forest, and WTP. This influenced their willingness to support the hypothetical forestry fund, and thus their affinity for financial participation. This study used a binary logistic regression to model the relationship of the binary dependent variable (support of forestry fund = 1; other = 0) to the independent variables. I included all variables suggested by economic theory in the preliminary logistic regression, such as income, gender, education, or age. The final model includes only those variables that had proven effective in building a robust
International Journal of Sustainable Development & World Ecology logistic regression model. Other contingent valuation studies for natural resources have shown most of these variables to be significantly predictable (Zbinden & Lee 2005; Gürlük 2006; Baral et al. 2008; Bernard et al. 2009; Kosoy & Corbera 2010; Sodhi et al. 2010; Cranford & Mourato 2011; Maes et al. 2012). I used the following explanatory variables in the logit regression model for households supporting conservation fund in the northern areas of Jordan:
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● ●
● Forest type: this is a binary variable, where decid-
uous oak = 1, pine = 2, evergreen oak = 3 (mean ± SD = 2.0000 ± 0.81786). ● Gender: this explanatory variable refers to males = 1 and females = 0 (mean ± SD = 0.1933 ± 0.39557). ● Education level: this variable was designed on an ordinal scale (1–6): primary education = 1, secondary education = 2, diploma degree = 3, bachelor’s degree = 4, postgraduate degree = 5 (mean ± SD = 1.8500 ± 1.11279). I generated the following equation for the logistic regression model Equation (1): Logðp=1 pÞ ¼ α þ β1 forest type þ β2 gender þ β3 education level þ ε;
(1)
where α is a constant, βi are the coefficients for the explanatory variables, while ε is the error. The goodnessof-fit of the model was estimated using the maximum loglikelihood ratio. The logit model did not include respondents’ incomes in order to make a statistical model compatible with the economic hypothesis suggested by Hanemann (1984) and subsequently applied by Baral et al. (2008).
WTP econometric models The individual WTP values were estimated using the ordinary least square (OLS) model in order to determine the hidden factors that affect stated WTP. One indicator of the results’ validity is whether WTP was influenced by the variables suggested by economic theory (e.g. socioeconomic variables and attitudes regarding forests’ ecosystems) (Martín-López et al. 2007; Adekunle et al. 2008; Awad & Holländer 2010; Pan et al. 2012). WTP values were related through econometric analysis to respondents’ characteristics, perceptions, and benefits derived from their surrounding forest ecosystems. I used the following explanatory variables in the WTP regression model for a hypothetical forestry conservation fund: ● Income: household monthly income (JD) were
Income 1: Less than 200, Income 2: 200–300, and Income 3: 301–400, and the expected signs for these income levels were negative, while Income 4:
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401–500 and Income 5: 501–600 were expected to have positive marks. Collected plants: which refers to number of herbal and medicinal plants collected from the forest per year and the expected sign is positive. Forest visits: the estimated number of forest visits and the expected sign is positive. Forest’s valuation: this refers to how households value forests, and the valuation was based on the following: 1 – ‘not important’, 2 – ‘somewhat important’, 3 – ‘important’, 4 – ‘very important’, and 5 – ‘extremely important’ and the expected sign is positive. Livestock hold size: it is about the number of livestock owned by the household, and the expected sign is negative.
The model included those variables that had displayed a significant relationship. I hypothesized that the respondents with the following characteristics would display the highest WTP for the conservation fund: visit the forest most frequently, collect the most forest plants, have the smallest flock size, and have the highest income. The OLS model for a general individual WTP function can be expressed as: WTP ¼ α þ β1 income þ β2 collected plants þ β3 forest visits þ β4 forest0 s valuation þ β5 livestock hold size þ ε;
(2)
where βi’s are the coefficient being estimated, α is the constant, and ε is error term.
Results Characteristics of the interviewees Demographic data displayed several trends. About 80% of respondents were female; this was due to interview timing, when most of the households’ heads were at work. The average age was 41, with localized averages from 37 to 45 (age 37 for those nearest to the pine forest, and 45 for those living next the deciduous oak forest). There is a direct relationship between respondents’ ages and their period of time living in a forested area – that period ranged between 23 and 35 years for those living near the pine and deciduous oak forests, respectively. With regard to education, 53.7% of the interviewees declared that they had finished primary school, 22% had obtained the high school certificate, and 10.3% had acquired a diploma degree. About 11.7% had attended university, and 1.7% had acquired a post graduate degree. The most frequent family income bracket was JD 200–300 (39.3%). About 23.7% indicated the bracket JD 301–400, 6.7% the bracket JD 401–500, 3.3% the bracket JD 501–600, and only 6.3% the bracket above JD 600. The rest of interviewees (20.7%) indicated the lowest income bracket (less than JD 200).
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Participants can generally be characterized as middleaged long-term residents with close proximity to the forest. About 80% of the interviewed sample consisted of women with primary schooling whose household income was between JD 200 and JD 300.
The type of forest nearest to the households had a great impact upon the probability for supporting conservation. Type and availability of direct benefits derived from different forest types explain this finding. The supporters of conservation fund are characterized as female and well-educated respondents. Those living near pine or evergreen oak forests were also more likely to participate in environmental programs for forestry conservation and rehabilitation. Previous research has not produced a consensus on the determinant factors affecting a person’s WTP. Studies have shown various social and economic factors that can affect WTP (i.e. Loomis et al. 2000; Cranford & Mourato 2011; Baral et al. 2013), and such variation emphasizes the need to consider the significant factors in designing and implementing polices and management plans for each specific ecosystem. For this case, policy-makers should consider the needs of less-educated females through the decisionmaking process for northern forestry management plans. Recently, researchers have examined ecological factors for biodiversity conservation as factors that affect a person’s WTP. An interaction between socioeconomic factors and the ecosystem have an effect on social preferences toward ES (Martín-López et al. 2012; Al-assaf et al. 2014) and thus its economic valuation. This kind of interaction is based on the individuals’ understanding of the roles that species play in ecosystems (Martín-López et al. 2007). The trade-offs between forests are attributed to the ESs supplied by each forest type (Al-assaf et al. 2014).
Conservation responsibility for sustainability About 295 of the 300 respondents expressed their ultimate support for any environmental program for forest conservation and rehabilitation. Just over half (58.3%) were willing to financially support this conservation and rehabilitation program. The logit regression model was effective in fitting the data, correctly classifying 67.2% cases (X42 = 37.384, p < 0.001, Table 1). Before coming up with the short list of predictable variables, I examined a wide range of socioeconomic data. The model includes only variables that significantly contributed in a final robust regression model. The significant predictors in the model for support of the conservation fund were type of forest, gender, and education level. The logistic regression equation is: logðp=1 pÞ ¼ 0:914 1:066 forest type ð1:deciduous oakÞ þ 0:11 forest type ð2: pineÞ 1:613 male 0:526 education level
The negative signs of the coefficients for the deciduous oak forest type, gender, and education level indicated that male interviewees, those with a lower level of education, and those living in the vicinity of deciduous oak forest have a lower probability of financially supporting the fund for forest conservation and rehabilitation. The positive sign of the pine forest type implies the high probability of interviewees living next to this forest supporting a conservation forest fund.
Analysis of stated willingness to pay: amount, determinants, and time value In a developing country such as Jordan, the payment mechanism – such as a tax increase – can introduce barriers to successfully conducting the survey. Therefore, due to lack of confidence about government policies and the weak performance of nongovernmental organizations (NGOs) in Jordan, I did not discuss the mechanisms of donation collection during this scenario. I asked each respondent the amount they would pay for a conservation fund, which was met by wide range of stated payment (JD 0–600). From these answers, I sorted stated payments into three different levels (Table 2). About 82% of respondent were willing to pay an annual amount of JD 0–10 for a 5-year period. Only 15% of the respondents were willing to pay a yearly sum of JD 12–50, and just 3.2% were willing to pay higher than JD 60. This wide range of stated bid amount raises the need for more investigation into hidden factors that affect WTP. I used the OLS statistical method to estimate the
Table 1. The regression model for households supporting conservation fund in the northern areas of Jordan. Variables Intercept Forest type (1): deciduous oak Forest type (2): pine Gender (1): male Education level (yearslevel)
Coefficient
SE
Significant Exp(B)
−0.914 −1.066
0.187 0.323
0.000** 0.001**
0.401 0.344
0.011 −1.613 −0.526
0.303 0.376 0.253
0.971 0.000** 0.038*
1.011 0.199 0.591
Notes: **Significant at 0.01 level. *Significant at 0.05 level.
Table 2.
Frequency distribution of bid amount per year for a 5-year term.
Bid amount
0
1
2
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9
13
8.7
3
4
2.3 0.3 81.6
5
6
10
12
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25
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35
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100
31
0.3
17
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1.3 15.2
1
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3.7
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200
600
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International Journal of Sustainable Development & World Ecology relationship between household characteristics and WTP, which reflects the relationship between total economic value of the forestry and the characteristics of households. I estimated a preliminary multiple-linear model including all survey demographic and attitude variables by maximum likelihood regression. Demographic variables such as age, gender, and social status had insignificant impact on respondents’ WTP for this conservation fund. Table 3 shows the results of econometric modeling including all explanatory variables that contributed to building a robust model. This model presents only the independent variables significant at a 0.05 level or better. Although the adjusted coefficient R2 is low (0.391), the results of the statistical relevance for the explanatory variables were very good. As expected, respondents with lower income levels displayed low WTP, supporting Martín-López et al. (2007), Adekunle et al. (2008), and Pan et al. (2012). Unexpectedly, income level 5 (JD 501–600) had a negative relation with the declared bid. Respondents with lower professed WTP are expected to be, in most cases, ‘free riders.’ This is especially true with regard to open access resources, as the forest is in this case. Table 3.
The results of the WTP regression model. Northern forest (N = 300)
Variable
Coefficient (SE)
Constant 6.416 (2.870) Income level 2 −6.936 (3.471) Income level 3 −0.047 (3.9041) Income level 4 17.061 (5.751) Income level 5 −11.557 (7.04) Number of plants collected 2.049 (0.825) The estimated number of 0.005 (0.002) forest visits Average valuation of forest −2.209 (0.816) Livestock herd size 1.379 (0.11) 0.407 R2 0.391 Adjusted R2 F-value (significance) 24.950 (0.000)
t-Statistic 2.237 (0.026)* −1.998 (0.047)* −0.012 (0.99) 2.967 (0.003)** −1.64 (0.102) 2.485 (0.014)* 1.997 (0.047)* −2.740 (0.007)** 12.512 (0.000)**
Notes: **Significant at 0.01 level. *Significant at 0.05 level.
Table 4.
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The WTP model included one tourist ES, though Johnson et al. (2001) acknowledges other non-tourist services for influencing the conservation support decision. Among the factors found to influence amount paid for conservation fund is the number of wild plants collected from forest. This factor was strongly and positively linked with the dependent variable (WTP). Livestock herd size was the second major factor associated with respondents’ WTP. It was a positive factor that reflects the importance of forests’ roles for grazing. These factors represent the substantial role of noneconomic motives for conservation. These results are compatible with previous research results, where researchers explored the importance of ecological and ethnobotanical knowledge and practices to support conservation plans specifically for forest ecosystems (Martín-López et al. 2007; Nawash et al. 2014).
The economic value of the northern forest: expanding from sample to population According to the economic theory, there is a discount rate whereby the utility of lump sum payments and/or a series of annual payments should be equal. The economic value of the northern forest is based on periodic payments with implicit discount rates. I used 15% as an environmental discount rate – applying a higher discount rate results in better estimates and lower uncertainties (Martín-López et al. 2007). The average annual WTP of respondents is JD 13.2 per household for the northern forest. I used the median value of the voted amount (as it is presented in Table 2) to calculate the discounted annual payments. I extrapolated this annual value of payments from the household level to the region level; this step’s accuracy is dependent on how representative the sample is, so the discreet estimate of WTP the zero’s value will be considered in estimating an aggregate value. In the annual WTP estimation, I applied the median WTP value to the proportion of respondents who were willing to pay, extrapolating about the region at large. I then aggregated WTP on a timescale using the 15% discount rate (Table 4). The resulting median annual
The economic values of the northern forests.
Median WTP (JD) Sample size (person) Urban households (house) Rural households (house) Total number of households (house) % of households that have WTP Number of WTP’s households Annual aggregate WTP from rural areas (JD) Discount rate (15%) Timescale (year) Present value of aggregate benefits from rural areas (JD)
Oak N = 100 Irbid
Pine N = 100 Jerash
Evergreen oak N = 100 Ajloun
Northern forest
16 100 26,548 38,301 64,849 90 34,470.9 612,816.00 3.352 5 2,667,070.3
10 100 13,519 12,203 25,722 89 10,860.67 122,030.00 3.352 5 531,093.5
13.5 100 13,940 6491 20,431 94 6101.54 87,628.50 3.352 5 2,311,401.2
13.2 300 54,007 56,995 111,002 91 51,433.11 822,474.5 3.352 5 3,579,536.6
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WTPs are JD 16, 10, and 13.5 for households living by deciduous oak, pine, and evergreen oak forests, respectively. The conservation value reflects how the rural people in this region value the forests from an economic point view. The aggregate present benefits of the economic value are JD 3,569,556 for the whole northern forest area. This valuation is based on the amount individuals were willing to contribute to sustain forest ESs. I assumed the conservation cost to reflect the direct value gained from utilizing forest services by the people. However, these results are restricted by (1) the limitations of using a WTP as a paybased method in developing countries. People in developing countries such as Jordan are not convinced of the importance of community participation in the management and conservation of natural resources. (2) The need to determine and examine additional potential benefits from forests. Conclusions and policy implications The results from the rural household survey displayed the spiritual value of forests for the surrounding community. Participants appreciated forest services for their contribution in providing some essential requirements for rural families. Provisioning and cultural services were mostly appreciated by visitors and local residents (Al-assaf et al. 2014). Rationally, a respondent would be willing to pay for a constant flow of forest services – the money would be designated to the suggested forestry conservation fund for the implementation of forest management sustainability plans. Supplying this information for policy use requires a measure of individual variation and determinate. This study expands upon previous work showing that forest communities would pay for forest services’ enhancement as a result of socialeconomic interaction (Schaafsma et al. 2012; Al-assaf et al. 2014). This study also demonstrates that even in such small and fragmented forest areas, rural people – and in particular sylvan communities – still value forest ecosystems. The estimated conservation value will be useful for future governmental decision making and assists with the inclusion of ES principles in policies (MEA 2005). Different studies have recognized that, in general, biodiversity has an economic value that should be considered when evaluating changes in ecosystems (Bernard et al. 2009). This must also be integrated in policy decision making and management planning (Ferraro et al. 2012). The results of this study complement results from previous studies that indicated the need to provide substantial fund to support biodiversity enhancement (e.g., Raunikar & Buongiorno 2006; Yao et al. 2014) and also that the general public would be willing to financially support such initiatives to enhance forest ecosystems (Yao et al. 2014). Furthermore, this study builds on previous studies in identifying the socioeconomic determinates of WTP (e.g., Campbell 2007 – socioeconomic effects; Schaafsma et al. 2012; – socio-demographic characteristics and
directional distance effects), and the noneconomic attributes, for example social prominence by forestry community (Baranzini et al. 2010), and the ecological benefits (Martín-López et al. 2007). The study has shown that with appropriate econometric tools, monetary values can be attached to nonmarket ESs – specifically forest services, which should be included throughout the policy decision-making process in Jordan. The paper also illustrates the importance of engaging the beneficiaries and stakeholders in a meaningful dialogue about forest ecosystems management. Participatory forest management strategies are optimal for the sustainable utilization of forest resources (Adekunle & Agbaje 2012). The concept of total economic value should be employed at the time of policy design. This concept reflects the value of direct and indirect market value of forestry. Forest conservation could be done though different means: effective regulations, afforestation, ex-situ and in-situ conservation, and tax incentives. Such approaches should be put in place by policy-makers. Three conclusions can be made from this study. First, this study demonstrated that the carefully structured and pretested CVM can be applied successfully in a developing country such as Jordan. Second, the study illustrated significant information about the importance of forest ecosystems to forest-based communities. This valuation method combined multidimensional information and interactions in one single number. The aggregate present benefit is JD 3,569,556 for the whole northern forest area; the valuation information can be used by the government policy-makers in its evaluation of restoration actions. This research suggests that contingent valuation may be a potentially useful direction for future research on environmental valuation in Jordan.
Acknowledgments The author would like to thank Abdul Hameed Shoman Fund for Supporting Scientific Research in Jordan for their kind financial support of the study. I am also grateful to the University of Jordan, scientific research fund [grant number 1441] for providing the support of field trips. Thanks are also extended to Yolla Alasmar and Marwan Alraqqad for preparing the map using the GIS tools. I am very grateful to the informants of the villages surrounding the three forest types who provided us time and information.
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