Microcredit and willingness to pay for environmental quality: Evidence from a randomized-controlled trial of finance for sanitation in rural Cambodia

Low willingness to pay (WTP) for environmental quality in developing countries is a key research question in environmental economics. One explanation is that missing credit markets may suppress WTP for environmental improvements that require large up-front investments. We test the impact of microloans on WTP for hygienic latrines via a randomized controlled trial in 30 villages in rural Cambodia. We find that microcredit dramatically raises WTP for improved latrines, with 60% of households in the Financing arm willing to purchase at an unsubsidized price, relative to 25% in the Non-financing arm. Effects on latrine installation are positive but muted by several factors, including a negative peer effect: randomly induced purchases by neighbors reduce a household's probability of installing its own latrine. On methodological grounds, this paper shows that a “decision-focused evaluation” can be integrated into academic analysis to provide insight into questions of general interest.     

The economic impact of the invasion of Acacia saligna in Israel

This paper illustrates the use of alternative, non-market valuation methods to estimate the economic value of ecological damage caused by the invasive plant Acacia saligna. We discuss the motivation to perform an economic valuation for bio-invasion in general and then examine the costs and benefits of conservation management programmes that reduce the risk of A. saligna invasion at the Nizzanim Long-Term Ecosystem Research (LTER) nature reserve in Israel. The study found that the annual mean willingness to pay (WTP) for containment or eradication of A. saligna was US$8.41 and US$8.83, respectively. The value placed on conserving the nature reserve was then compared to the cost of containment or eradication of the species, enabling a standard economic benefit–cost analysis. The result of this analysis showed that, using the most conservative method of valuation of the nature reserve, eradication of A. saligna gave a net benefit.     

Using virtual environments to improve the realism of choice experiments: A case study about coastal erosion management

Choice experiment surveys are commonly used to assess the general public׳s willingness to pay for different levels of environmental quality. However, respondents need to understand what they are valuing or they will make potentially wrong assumptions based on different experiences and frames of reference. Three-dimensional computer generated models or Virtual Environments (VE) have so far seen little use in economics research, probably due to the complexity and cost of developing and delivering them to study participants. The few studies that have used them find that VE are superior to static image presentations in helping people evaluate complex data. For this study we developed virtual environments for a choice experiment about coastal erosion management using free, easy-to-use software and Google Earth© satellite imagery and presented these to respondents as video tours. Our results indicate that the VE treatment reduced choice error, reduced left-right bias and improved respondent engagement and retention when compared with static images. There were also differences in WTP between the two groups.     

Three reasons to use annual payments in contingent valuation surveys: Convergent validity,discount rates,and mental accounting

We present three arguments for using ongoing annual payments in contingent valuation (CV) surveys that estimate the benefit of a long-lasting environmental improvement. First, by matching the duration of the payments with the duration of the environmental benefits, survey respondents are spared from performing complicated present value calculations. Second, willingness to pay (WTP) estimates from CV surveys that include ongoing annual payments best match WTP estimates obtained using travel cost surveys. Third, respondents are less likely to face binding mental budget constraints with ongoing annual payments than with a larger one-time payment. In addition, respondents’ discount rates may be estimated by collecting non-hypothetical, individual time preference data as part of the valuation survey.     

A new meta-analysis on the WTP/WTA disparity

This study reports a new meta-analysis of papers that elicit willingness-to-pay (WTP) and willingness-to-accept compensation (WTA) measures of value for the same good. We investigate the effects of type of good and several survey-design features on the WTP/WTA disparity, measured as the logarithm of the ratio of mean WTA to mean WTP. Confirming Horowitz and McConnell?s (2002) pioneering meta-analysis, we find the disparity is smaller for ordinary private goods than for public and non-market goods, that it is not solely an artifact of using hypothetical transactions or other weak experimental or survey methods, and that it is smaller for studies using student subjects. In addition, we find that the disparity is smaller when subjects have experience valuing the good in real markets or through repeated experimental trials. In contrast to Horowitz and McConnell, we find the disparity is significantly smaller in studies using incentive-compatible elicitation mechanisms. The disparity is smaller in more recent studies, an effect that is attributable only in part to changes in study characteristics.     

A framework for allocating conservation resources among multiple threats and actions

Land managers decide how to allocate resources among multiple threats that can be addressed through multiple possible actions. Additionally, these actions vary in feasibility, effectiveness, and cost. We sought to provide a way to optimize resource allocation to address multiple threats when multiple management options are available, including mutually exclusive options. Formulating the decision as a combinatorial optimization problem, our framework takes as inputs the expected impact and cost of each threat for each action (including do nothing) and for each overall budget identifies the optimal action to take for each threat. We compared the optimal solution to an easy to calculate greedy algorithm approximation and a variety of plausible ranking schemes. We applied the framework to management of multiple introduced plant species in Australian alpine areas. We developed a model of invasion to predict the expected impact in 50 years for each species-action combination that accounted for each species’ current invasion state (absent, localized, widespread); arrival probability; spread rate; impact, if present, of each species; and management effectiveness of each species-action combination. We found that the recommended action for a threat changed with budget; there was no single optimal management action for each species; and considering more than one candidate action can substantially increase the management plan's overall efficiency. The approximate solution (solution ranked by marginal cost-effectiveness) performed well when the budget matched the cost of the prioritized actions, indicating that this approach would be effective if the budget was set as part of the prioritization process. The ranking schemes varied in performance, and achieving a close to optimal solution was not guaranteed. Global sensitivity analysis revealed a threat's expected impact and, to a lesser extent, management effectiveness were the most influential parameters, emphasizing the need to focus research and monitoring efforts on their quantification.     

Testing the Internal Consistency of Contingent Valuation Surveys

For an internal consistency check, one can examine WTP responses to different surveys. Holding an environmental problem constant, concave preferences imply WTPconcavein the success of a remedy. The same preferences imply WTPconvexin the magnitude of an environmental problem, assuming a successful remedy. Having opposite signed curvature of these two WTP patterns is general, not requiring concave preferences. For an adding-up test, an environmental commodity can be divided. Then, WTP for one part plus WTP for the second part, conditional on already having the first part, equals WTP for the whole, adjusted by an income effect.     

Contingent valuation of ecotourism development in country parks in the urban shadow

To optimise the use and management of Hong Kong's country parks, ecotourism has recently been promoted by the government and echoed by the leisure sector. Visitors' valuation of ecotourism development hitherto remains scant and could add a new dimension to the knowledge and management base. This study estimated the potential value of ecotourism development using the contingent valuation method (CVM). A total of 613 visitors in three country parks were interviewed. The results showed that the bid amounts and the motives to experience and learn more about nature were significant predictors of willingness-to-pay (WTP). The mean and median WTP were, respectively, HK$101.1 and HK$85.0 annually, varying slightly between parks. The differences were associated with the special ecological and accessibility characteristics of individual parks. The results could justify financial support from the government for ecotourism development and associated nature conservation endeavours and promote the incorporation of natural resource valuation in formulation of public policies in Hong Kong and other developing regions.     

Valuing non-market benefits derived from allotments in southeast England: A contingent valuation study

The English derive a wide range of values from allotments, but nearly 35% of allotments have disappeared in the last 20 years. The real value of allotments has probably been underestimated. The contingent valuation method (CVM) was used to give a monetary value to benefits derived from allotments by allotment holders and local residents. The study was conducted in southeast England (Wye and Ashford, Kent and Greater London). A postal survey with open-ended questions was filled in by 124 allotment holders and 74 residents. Respondents were asked to express their maximum willingness to pay for allotments (WTP) and the minimum willingness to accept (WTA) compensation for loss of allotments. The mean annual WTP for keeping allotments of allotment holders were £78.93, £35.64 and £79.43, and for local residents were £41.66, £46.14 and £283.57, in Wye, Ashford and London, respectively. The allotment holders' WTP was strategically more than WTA compensation and they were only willing to pay rent for using allotments, not for retaining them.     

A density projection approach for non-trivial information dynamics: Adaptive management of stochastic natural resources

We demonstrate a density projection approximation method for solving resource management problems with imperfect state information. The method expands the set of partially-observed Markov decision process (POMDP) problems that can be solved with standard dynamic programming tools by addressing dimensionality problems in the decision maker's belief state. Density projection is suitable for uncertainty over both physical states (e.g. resource stock) and process structure (e.g. biophysical parameters). We apply the method to an adaptive management problem under structural uncertainty in which a fishery manager's harvest policy affects both the stock of fish and the belief state about the process governing reproduction. We solve for the optimal endogenous learning policy—the active adaptive management approach—and compare it to passive learning and non-learning strategies. We demonstrate how learning improves efficiency but typically follows a period of costly short-run investment.     

The influencing factors of the WTP for the risk reduction of chemical industry accidents in China

To explore the factors that influence respondents’ willingness to pay (WTP) for the risk reduction of chemical industry accidents, a questionnaire survey combined with contingent valuation and psychometric paradigm methods were conducted in the city of Yancheng, Jiangsu Province, China. Both traditional socioeconomic variables and perceived characteristics of the hazards were considered in this study, and a Tobit model was used to find the factors influencing WTP under three risk reduction scenarios. The results showed that three demographic characteristics, age, gender, and income, significantly affected the WTP for chemical risk reduction. In addition, three extracted public risk perception factors, effect, knowledge, and trust, also strongly affected the WTP. The mean WTP value increased as the magnitude of the risk reduction increased. The number of factors influencing the WTP decreased as the reduction level improved, and only the effect factor had a significant influence on the WTP for a higher level (80%) of risk reduction. The cost for chemical safety management of Yancheng was calculated, and the optimized risk reduction level was determined. These findings can assist governments and policy makers to formulate suitable strategies for risk control, to reach target groups of people to develop effective communication, and to provide specific references for the best investment for the security of local residents.     

Assessment of the conservation value of Munseom area in Jeju Island,South Korea

The ecosystem of munseom area (MA) in Jeju Island, one of the marine protected areas in South Korea, has been continuously threatened by lack of management and pollution of the surrounding sea area. As a result, the South Korean government is trying to implement the systematic management plan to conserve the marine ecosystem of the MA. This article tries to obtain information about the conservation value of the MA. To this end, this study examines household willingness to pay (WTP) for conserving the MA employing the contingent valuation (CV) approach. A total of 1000 South Korean households were involved in the CV survey using a dichotomous choice question. The mean yearly WTP for the conservation is estimated as KRW 1763 (USD 1.50) per household. The national value expanded from the sample to the population is worth KRW 34.0billion (USD 29.0 million) per year. The results imply that the conservation is supported by South Korean households.     

Reducing over-reporting of deterministic co-occurrence patterns in biotic communities

Null models of species co-occurrence are widely used to infer the existence of various ecological processes. Here we investigate the susceptibility of the most commonly used of these models (the C-score in conjunction with the sequential swap algorithm) to type 1 and type 2 errors. To do this we use simulated datasets with a range of numbers of sites, species and coefficients of variation (CV) in species abundance. We find that this model is particularly susceptible to type 1 errors when applied to large matrices and those with low CV in species abundance. As expected, type 2 error rates decrease with increasing numbers of sites and species, although they increase with increasing CV in species abundance. Despite this, power remains acceptable over a wide range of parameter combinations. The susceptibility of this analytical method to type 1 errors indicates that many previous studies may have incorrectly reported the existence of deterministic patterns of species co-occurrence. We demonstrate that in order to overcome the problem of high type 1 error rates, the number of swaps used to generate null distributions for smaller matrices needs to be increased to over 50,000 swaps (well beyond the 5000 commonly used in published analyses and the 30,000 suggested by Lehsten and Harmand, 2006). We also show that this approach reduces type 1 error rates in real datasets. However, even using this solution, larger datasets still suffer from high type 1 error rates. Such datasets therefore require the use of very large numbers of swaps, which calls for improvements in the most commonly used software. In general, users of this powerful analytical method must be aware that they need surprisingly large numbers of swaps to obtain unbiased estimates of structuring in biotic communities.     

Improving multi-site benefit functions via Bayesian model averaging: A new approach to benefit transfer

A benefit function transfer obtains estimates of willingness-to-pay (WTP) for the evaluation of a given policy at a site by combining existing information from different study sites. This has the advantage that more efficient estimates are obtained, but it relies on the assumption that the heterogeneity between sites is appropriately captured in the benefit transfer model. A more expensive alternative to estimate WTP is to analyze only data from the policy site in question while ignoring information from other sites. We make use of the fact that these two choices can be viewed as a model selection problem and extend the set of models to allow for the hypothesis that the benefit function is only applicable to a subset of sites. We show how Bayesian model averaging (BMA) techniques can be used to optimally combine information from all models.The Bayesian algorithm searches for the set of sites that can form the basis for estimating a benefit function and reveals whether such information can be transferred to new sites for which only a small data set is available. We illustrate the method with a sample of 42 forests from U.K. and Ireland. We find that BMA benefit function transfer produces reliable estimates and can increase about 8 times the information content of a small sample when the forest is ‘poolable’.     

Optimized quantity-within-distance models of spatial welfare heterogeneity

Spatial welfare heterogeneity is frequently modeled within stated preference analysis as a function of discrete or continuous distance between households and affected resources. A common example is distance-decay analysis. Although distance-based models such as these are easily estimated, the ubiquity of this paradigm can lead to analyses that overlook other forms of analysis with equal or greater relevance. This paper develops an alternative approach to spatial heterogeneity in stated preference willingness to pay (WTP) based on the quantity or area of an affected resource surrounding each respondent at an optimized distance band or radius, with distance bands optimized using a grid-search algorithm that maximizes model likelihood. Methods and results are illustrated using a choice experiment on riparian land restoration in Maine, USA. The resulting quantity-within-distance model identifies systematic spatial patterns that are undetectable using distance-based analysis and directly relevant for welfare analysis.     

Quantifying Preferences for the Natural World Using Monetary and Nonmonetary Assessments of Value

Given that funds for biodiversity conservation are limited, there is a need to understand people's preferences for its different components. To date, such preferences have largely been measured in monetary terms. However, how people value biodiversity may differ from economic theory, and there is little consensus over whether monetary metrics are always appropriate or the degree to which other methods offer alternative and complementary perspectives on value. We used a choice experiment to compare monetary amounts recreational visitors to urban green spaces were willing to pay for biodiversity enhancement (increases in species richness for birds, plants, and aquatic macroinvertebrates) with self‐reported psychological gains in well‐being derived from visiting the same sites. Willingness‐to‐pay (WTP) estimates were significant and positive, and respondents reported high gains in well‐being across 3 axes derived from environmental psychology theories (reflection, attachment, continuity with past). The 2 metrics were broadly congruent. Participants with above‐median self‐reported well‐being scores were willing to pay significantly higher amounts for enhancing species richness than those with below‐median scores, regardless of taxon. The socio‐economic and demographic background of participants played little role in determining either their well‐being or the probability of choosing a paying option within the choice experiment. Site‐level environmental characteristics were only somewhat related to WTP, but showed strong associations with self‐reported well‐being. Both approaches are likely to reflect a combination of the environmental properties of a site and unobserved individual preference heterogeneity for the natural world. Our results suggest that either metric will deliver mutually consistent results in an assessment of environmental preferences, although which approach is preferable depends on why one wishes to measure values for the natural world. Preferencias de Cuantificación para el Mundo Natural Usando Estudios de Valor Monetario y No Monetario.     

Population Viability Analysis with Species Occurrence Data from Museum Collections

Abstract: The most comprehensive data on many species come from scientific collections. Thus, we developed a method of population viability analysis (PVA) in which this type of occurrence data can be used. In contrast to classical PVA, our approach accounts for the inherent observation error in occurrence data and allows the estimation of the population parameters needed for viability analysis. We tested the sensitivity of the approach to spatial resolution of the data, length of the time series, sampling effort, and detection probability with simulated data and conducted PVAs for common, rare, and threatened species. We compared the results of these PVAs with results of standard method PVAs in which observation error is ignored. Our method provided realistic estimates of population growth terms and quasi‐extinction risk in cases in which the standard method without observation error could not. For low values of any of the sampling variables we tested, precision decreased, and in some cases biased estimates resulted. The results of our PVAs with the example species were consistent with information in the literature on these species. Our approach may facilitate PVA for a wide range of species of conservation concern for which demographic data are lacking but occurrence data are readily available.     

Semi-nonparametric Distribution-Free Dichotomous Choice Contingent Valuation

We apply a semi-nonparametric distribution-free estimator for binary discrete response data to the estimation of a dichotomous choice contingent valuation model. Using this estimator, mean and median compensating and equivalent variation can be consistently estimated without making nontheoretically motivated assumptions on consumer' preferences. The approach is illustrated using a contingent valuation survey of willingness to pay for reduction of risk of premature death due to exposure to hazardous waste. We find that a conventional parametric estimator and the proposed estimator give similar estimates of unconditional WTP, but that conditional on explanatory variables the estimates are quite different.     

Using revealed preferences to estimate the Value of Travel Time to recreation sites

The opportunity Value of Travel Time (VTT) is one of the most important elements of the total cost of recreation day-trips and arguably the most difficult to estimate. Most studies build upon the theoretical framework proposed by Becker (1965) by using a combination of revealed and stated preference data to estimate a value of time which is uniform in all activities and under all circumstances. This restriction is relaxed by DeSerpa's (1971) model which allows the value of saving time to be activity-specific. We present the first analysis which uses actual driving choices between open access and toll roads to estimate a VTT specific for recreation trips, thereby providing a value which conforms to both Becker's and DeSerpa's theoretical models. Using these findings we conduct a Monte Carlo simulation to identify generalizable results for subsequent valuation studies. Our results indicate that 3/4 of the wage rate provides a reasonable approximation of the average VTT for recreation trips, while the commonly implemented assumption of 1/3 of the wage rate generates downward biased results.     

Income inequality and willingness to pay for environmental public goods

We study how the distribution of income among members of society, and income inequality in particular, affects social willingness to pay (WTP) for environmental public goods. We find that social WTP for environmental goods decreases (increases) with income inequality if and only if environmental goods and manufactured goods are substitutes (complements). We derive adjustment factors for benefit transfer to control for differences in income distributions between a study site and a policy site. For illustration, we quantify how social WTP for environmental public goods depends on the respective income distributions for empirical case studies in Sweden and the World at large. We find that the adjustment for income inequality can be substantial.