Skip to main content
SpringerLink
Log in

Guidance to Enhance the Validity and Credibility of Environmental Benefit Transfers

  • Published:
Environmental and Resource Economics Aims and scope Submit manuscript

Abstract

Benefit transfer is the use of pre-existing empirical estimates from one or more settings where research has been conducted previously to predict measures of economic value or related information for other settings. These transfers offer a feasible means to provide information on economic values when time, funding and other constraints impede the use of original valuation studies. The methods used for applied benefit transfers vary widely, however, and it is not always clear why certain procedures were applied or whether alternatives might have led to more credible estimates. Motivated by the importance of benefit transfers for decision-making and the lack of consensus guidance for applied practice, this article provides recommendations for the conduct of valid and reliable transfers, based on the insight from the combined body of benefit transfer research. The primary objectives are to: (a) advance and inform benefit-transfer applications that inform decision making, (b) encourage consensus over key dimensions of best practice for these applications, and (c) focus future research on areas requiring further advances. In doing so, we acknowledge the healthy tension that can exist between best practice as led by the academic literature and practical constraints of real-world applications.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

Notes

  1. https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NRMRL&dirEntryId=340067, accessed April 8, 2020. Also see discussion by Newbold et al. (2018a).

  2. For example, recent benefit transfers applied by the U.S. EPA to support regulatory impact analyses have used procedures ranging from scaled unit-value transfers (e.g., U.S. EPA 2011) to benefit-function transfers from meta-analysis (e.g., U.S. EPA 2010, 2012, 2015), with “surprisingly little discussion of the academic literature on benefit transfer” (Wheeler 2015, p. 111). Review of benefit transfer applications by other governmental and intergovernmental organizations reveals similar heterogeneity and opacity on why certain methods were applied.

  3. The term “benefit(s) transfer” did not become common until the 1990s.

  4. See Water Resources Research, Vol. 28, No. 3, 1992.

  5. For additional discussion of the divergences between academic research and practitioner needs, see McComb et al. (2006), Loomis and Rosenberger (2006), Boyle et al. (2010), Johnston and Rosenberger (2010), Johnston et al. (2015c), Richardson et al. (2015), Rosenberger and Loomis (2017), and Johnston et al. (2018).

  6. This terminology is used as shorthand only; the target for a benefit transfer need not be a new, unstudied (geospatial) site; it may be a new policy question at a site where a study has already been conducted.

  7. Within the benefit transfer literature, a transfer is typically considered valid if it provides a statistically unbiased estimate of the true value at the policy site. Reliable transfers, in contrast, are associated with lower transfer errors or variances (Bishop and Boyle 2019; Rosenberger 2015). Both are elements of the accuracy of transfer estimates.

  8. See Boyle et al. (2010), Brouwer and Navrud (2015), Griffiths et al. (2012), Griffiths and Wheeler (2005), Iovanna and Griffiths (2006), Johnston et al. (2015a, 2018), Johnston and Rosenberger (2010), Loomis (2015), Rolfe et al. (2015a), Wheeler (2015) and Newbold et al. (2018a).

  9. Updated guidance in US EPA (2014) includes similar acknowledgement of benefit transfer.

  10. See https://ec.europa.eu/environment/water/water-framework/index_en.html, accessed April 12, 2020.

  11. Other papers in the issue included Blow and Blundell (2018), Kuminoff (2018), McConnell and Siikamaki (2018), Smith (2018), and Turner (2018).

  12. For example, see Freeman (1984), Boyle and Bergstrom (1992), Brouwer (2000), Boyle et al. (2009, 2010), Bateman et al. (2011a), Johnston et al. (2015b), Richardson et al. (2015), and Rosenberger and Loomis (2003, 2017).

  13. For example, Hines (1999) notes that “… to quantify the economic costs of (taxes, regulations, externalities, monopolistic practices, etc.) … it is standard practice … to use a small number of assumptions and selected elasticities to estimate areas of the relevant ‘Harberger triangles’” (p. 167). Other economic data transfers include replacement cost (De Groot, Wilson and Boumans, 2002) and resource (habitat) equivalency (Flores and Thacher, 2002). Multiple types of economic information transfers are used within national accounting efforts such as the UK Office for National Statistics extended GDP Household Satellite Account, which accounts for the contribution of unpaid household production activity (https://www.ons.gov.uk/economy/nationalaccounts/satelliteaccounts, accessed March 31, 2021). Beyond economics, engineers use “steam tables” to predict pressure and flow in power facilities, “weight-load” tables to predict weight holding capacity of floors and roofs, and the U.S. government publishes an actuarial table of the “probability of death.” Other examples include dose–response functions used by physical scientists to identify the health effects of changes in environmental quality (see Spash and Vatn 2006).

  14. For example, a real estate appraisal is a type of economic transfer that has two important differences from the transfer of a typical neoclassical welfare estimate (such as consumer surplus). First, the appraisal is grounded in actual observed sales, not estimated sales prices. Second, the appraisal estimate can be validated by a subsequent sale of the subject property.

  15. Another alternative is expert elicitation such as Delphi approaches. While these approaches have not been extensively investigated and are not directly based on affected peoples’ preferences, some recent studies suggest potential for benefit transfers applied to global public goods (Strand et al. 2017, Navrud and Strand 2018, Dugstad and Navrud 2019, Siikamaki et al. 2019).

  16. Even if the direction of the bias is suspected the magnitude of bias can rarely be determined.

  17. For example, the study-site population may be from a high-income majority group and the policy-site population is a low-income minority group, and the analyst may not be able to control for these differences in the transfer process. Alternatively, a meta-function might be specified as a linear function while the true underlying value relationship is nonlinear. A preference calibration transfer might assume a utility function that does not match policy-site population preferences. As a final example, values may differ between study and policy sites due to factors that are unobservable to the analyst, and hence remain uncorrected within the transfer.

  18. As another example, some study sites used to estimate a meta-equation might provide estimates with upward biases while others provide estimates with downward biases. In such cases, the meta-equation coefficients could lead to a policy-site value estimate that is an overestimate or underestimate, with a bias that is likely not as large as the over- and under-estimation that occurs in some study-site estimates.

  19. Although we frame the subsequent discussion primarily around the content validity of benefit-transfer procedures, it is also important to consider the content validity of the study-site value estimates that may be used to support the transfer. This consideration takes place as part of study-site information selection as discussed below.

  20. Related behaviors may be observable. Hence, some criterion validity tests can be conducted by evaluating the extent to which an economic procedure predicts observable behaviors that are related to welfare estimates (e.g., voting, Vossler and Kerkvliet 2003; Johnston 2006; Vossler and Watson 2013).

  21. Consider the example of convergent validity tests. When these tests are applied to benefit transfers, the study-site and policy-site studies are often designed simultaneously by the researchers and have identical features. This is not the case when an actual transfer is conducted, because no study is available at the policy site. This type of convergent-validity test therefore abstracts from reality. It is also possible to confirm convergent validity for two estimates that are equally biased. As a final example, the outcome of these tests can vary depending on whether a classical null hypothesis of equality is assumed or whether one begins instead with a presumption that prior value estimates are different (Muthke and Holm-Mueller 2004; Kristofersson and Navrud 2005). Thus, convergent-validity investigations are informative but additional evidence is needed to draw strong conclusions on validity.

  22. As an illustration, discoveries made during the literature search may guide the selection of a transfer method—for example uncovering a large study-site literature that facilitates the estimation of a meta-equation to support computation of transfer estimates. Subsequent screening and coding may then lead the analyst to revisit and update the original methods used to search the literature or may encourage a rethinking of intended transfer method. For example, upon closer inspection and screening of the data, the analyst may determine that the previously discovered literature is too heterogeneous or poorly documented to support a meta-regression analysis. Such a determination can then prompt a return to earlier steps in the benefit transfer process.

  23. Multiple spatial dimensions of the policy site and policy-site values can be important. For example, where will changes in the studied good or service occur relative to the individuals who might value those changes? How large is the geospatial area affected by environmental quality improvements? What is the relevant extent of the market for the analysis? What are the geospatial dimensions of relevant substitute and complements? Works such as Hanley et al. (2003), Bateman et al. (2006, 2011a, 2011b, 2013), Johnston and Duke (2009), Martin-Ortega et al. (2012), Perino et al. (2014), Schaafsma (2015), Kuminoff (2018), Artell et al. (2019), and Johnston et al. (2017a, 2019) discuss these and other issues related to spatial dimensions of benefit transfer.

  24. See: https://www.epa.gov/sites/production/files/2017-09/documents/ee-0568-07.pdf, p. 7–46, accessed April 13, 2020.

  25. For example, in some settings it might be defensible to use otherwise identical Hicksian and Marshallian estimates interchangeably within a benefit transfer (as they are for practical purposes in many applied studies), whereas in other cases the anticipated differences between these estimates might be large enough that such practices could jeopardize validity. See discussions in Londoño and Johnston (2012) and Johnston and Moeltner (2014).

  26. Some original valuation studies estimate WTP when property rights suggest that a WTA measure is more applicable, due to the complexities involved in estimating WTA (e.g., Bishop et al. 2017).

  27. Discussions of this topic are provided in sources such as Brouwer (2000), Bergstrom and Taylor (2006), Nelson and Kennedy (2009), Boyle and Wooldridge (2018), and Vedogbeton and Johnston (2020).

  28. For example, in some cases model specifications designed to ensure desirable theoretical properties may lead to inferior empirical performance (Newbold et al. 2018b; Moeltner 2019).

  29. See Loomis and Rosenberger (2006), Nelson and Kennedy (2009), Rosenberger and Johnston (2009), Boyle et al. (2013, 2015), Stanley et al. (2013), Nelson (2015), Boyle and Wooldridge (2018), and Newbold et al. (2018a).

  30. For example, see discussions in Bergstrom and Taylor (2006), Nelson and Kennedy (2009), Johnston and Moeltner (2014), Moeltner and Rosenberger (2014), Moeltner (2015), Boyle and Wooldridge (2018) and Vedogbeton and Johnston (2020).

  31. Consider, for example, an otherwise identical increase in bowhead whale populations used for subsistence harvest by Native communities in the Arctic, compared to the same biophysical population change used for recreational whale watching. Even though the biophysical change might be identical (e.g., an increase in X whales within a population stock), these changes influence welfare through fundamentally different channels, and would therefore be unlikely to have sufficient consistency to support valid benefit transfer.

  32. Relevant contextual considerations will vary across settings and the types of values considered. As an example, the value of otherwise similar environmental quality improvements may vary depending on whether public access is permitted to improved areas, so that legal access provisions can represent an important socioeconomic dimension of similarity in some cases (Olander et al. 2018). Another illustrative example is that the value of a riparian buffer for treatment of water pollution depends on the extent to which that buffer is located downstream of pollution sources—a purely biophysical characteristic that is central to the values provided by a given buffer area. Biophysical features such as these can also represent relevant contextual dimensions of site similarity for benefit transfers (Simpson 2016).

  33. Section 4.9 in Johnston et al. (2018) reviews past findings on international benefit transfers.

  34. Some papers conclude that “international benefit transfer is as valid as intra-country transfer” (Ready and Navrud 2006, p. 434), although there does not appear to be consensus on this issue.

  35. For example, study sites may be excluded because of insufficient correspondence to the policy site across one or more potentially important dimensions, because study documentation lacks information on key variables involved in the transfer (Moeltner et al. 2007), because the valuation approach is inconsistent with established practices (Newbold et al. 2018a), or due to other considerations that may render a study unsuitable for a benefit transfer application.

  36. For example, this work seems to suggest that transfers of contingent valuation estimates are more accurate than transfers of other types of value information.

  37. For example, accurate characterization and modeling of the biophysical dimensions of the environmental good(s) or service(s) to be valued are important dimensions of validity for many types of valuation studies, beyond economic methods that are applied (Mendelsohn and Olmstead 2009; Bateman et al. 2011b; Johnston et al. 2012; Schultz et al. 2012; Boyd et al. 2016; Simpson 2016).

  38. https://sweep.ac.uk/portfolios/natural-environment-valuation-online-tool-nevo/, accessed April 1, 2021.

  39. https://naturalcapitalproject.stanford.edu/software/invest, accessed April 1, 2021.

  40. For example, InVEST provides online documentation which may be used to evaluate the extent to which economic components rely on best practices applicable to specific benefit-transfer applications. See https://naturalcapitalproject.stanford.edu/software/invest, accessed April 1, 2021. Similar documentation for NEVO is available at https://www.leep.exeter.ac.uk/nevo/documentation/, accessed May 20, 2021.

  41. The benefit transfer literature frequently overlooks the distinction between estimating a new meta-regression analysis to support a benefit transfer and using an existing meta-analysis. There are important differences between these two types of benefit transfer. For example, the latter does not require the compilation of new metadata but does require that the properties of the already-existing meta-analysis be evaluated with respect to policy-site conditions and benefit-transfer needs. In addition, the quality of meta-regression models and suitability for value prediction vary (Boyle and Wooldridge 2018).

  42. For example, when estimating a single benefit function using primary data from multiple study sites, one assumes implicitly that the function can provide a valid representation of conditions and behavior across all sites. Similar assumptions are implied when estimating and using meta-functions.

  43. For example, an initial data search may suggest the availability of data suitable for development of a meta-regression analysis. Once an initial decision is made to pursue this type of transfer, additional data collection may be required to complete the metadata, especially in terms of regressors specified in the meta-equation, necessitating a return to data search and review of coding procedures. If sufficient study-site meta-data are not ultimately available to estimate a meta-function, then the analyst must revisit the transfer-method decision—for example, considering a value- or single-site function transfer instead.

  44. Some evidence suggests that adjustments for income inequality may also be relevant within some contexts (Baumgärtner et al. 2017; Meya et al. 2021).

  45. The value of statical life estimates are drawn from analysis of many study-site values but, once estimated, the same VSL is used in many policy analyses, sometimes with simple adjustments (Aldy and Viscusi, 2008; De Blaeij et al. 2003; Hammitt and Robinson 2011; Viscusi and Aldy 2003).

  46. For example, see Boyle et al. (2009, 2010), Rosenberger and Phipps (2007), Johnston and Rosenberger (2010), Johnston and Thomassin (2010), Kaul et al. (2013), Lindhjem and Navrud (2015), Rolfe et al. (2015b), and Boyle and Wooldridge (2018).

  47. See Smith et al. (2002, 2006), Smith and Pattanayak (2002), Phaneuf and Van Houtven (2015), Newbold et al. (2018b), and Moeltner (2019).

  48. For example, see discussions in Boyle et al. (2009, 2010), Johnston and Rosenberger (2010), Johnston and Moeltner (2014), Moeltner and Rosenberger (2014), Kling and Phaneuf (2018), Newbold et al. (2018b), Smith et al. (2002, 2006), Smith (2018), and Moeltner (2019).

  49. For discussions of precision needs for benefit transfer in different policy contexts, see Bergstrom and De Civita (1999), Navrud and Pruckner (1997) and Olander et al. (2017).

  50. For example, water quality valuation studies have used many different types of water quality measures when estimating values, including different types of water quality indices or ladders (Johnston et al. 2005, 2017a, 2019; Van Houtven et al. 2007; Walsh and Wheeler 2013). As described by Johnston and Bauer (2020), various steps are typically required to reconcile water-quality measurements available for the policy site with the measures used to qualify water quality within valuation studies or meta-analyses. Similar steps are required when comparing values across studies, for example as part of a meta-regression analysis.

  51. For example, some studies might report value estimates per household whereas others might provide estimates per person for a common unit of change but for different years.

  52. For example, transformations between values per household and values per person require information on the number of persons per household, along with assumptions on how to consider adults versus children when making this transformation.

  53. For example, structural benefit transfer methods can include mechanisms to calibrate between otherwise identical Marshallian and Hicksian welfare measures. Meta-regression analyses often include moderator variables that identify inconsistencies across included value measures (e.g., values measured as recurring annual payments versus lump-sum payments), allowing the model to estimate systematic differences associated with different measurement units. Model-based procedures of this type can at least partially reduce the need for some types of data adjustments.

  54. For example, a study-site benefit function might incorporate water quality change measured via a standardized water quality index (Walsh and Wheeler 2013), whereas quality data at the policy site might be available in other units (e.g., changes in Secchi depth).

  55. See, e.g., https://www3.epa.gov/airnow/aqi_brochure_02_14.pdf, accessed April 19, 2020.

  56. The literature provides insight into the relevance of concepts such as these for benefit transfer (e.g., Bateman et al. 2006, 2011a; Brouwer 2006; Zandersen et al. 2007; Rolfe and Windle 2008; Rosenberger and Johnston 2009; Boyle et al. 2010; Johnston and Rosenberger 2010; Bliem and Getzner 2012; Fetene et al. 2014; Schaafsma et al. 2014; Schaafsma 2015; Lew and Wallmo 2017; Loureiro and Loomis 2017; Johnston et al. 2017a, 2018; He and Poe 2020).

  57. As a case in point, choice experiments often produce linear utility functions based on an implied assumption that considered changes are sufficiently close to the margin. Analysts should consider this issue when determining whether a choice-experiment benefit function is suitable for policy-site transfers, but this type of linearity should not be used as a prima facie litmus test to automatically exclude such functions (Carson et al. 2015).

  58. Johnston et al. (2018) review the recent meta-analysis literature with respect to best practices such as these. A similar review of earlier meta-analyses in the literature is provided by Nelson and Kennedy (2009).

  59. As described by Boyle and Wooldridge (2018), econometric requirements for meta-analyses used to predict values can differ from similar models used to synthesize and characterize a literature. For example, the former implies greater attention to consistent measurement of the dependent variable, the importance of specifications that allow for potential nonlinearities, and can imply that different regression techniques should be used (e.g., OLS is generally preferred to WLS when the goal is value prediction).

  60. Older reviews are provided by Brouwer and Spaninks (1999) and Brouwer (2000), among others. Also see Boyle et al. (2010). Recent evidence suggests that median transfer errors are in the general vicinity of 35–45%, with Kaul et al. (2013) reporting a median error of 39% and Rosenberger (2015) finding median errors of 36% for function transfers and 45% for value transfers. These errors vary widely over different applications.

  61. For example, see the guidance of Johnston et al. (2017b) applicable to the aggregation of stated-preference estimates. Theoretical issues related to welfare aggregation are discussed by Just et al. (2004).

  62. For example, within recreation demand modeling, the use of on-site versus general population sampling, together with the type of model that was estimated, influence sample representativeness and the ability to aggregate estimates in various ways (Lupi et al. 2020).

  63. For example, within a hedonic property value study, do homes that sold during the studied period represent all homes within the studied area? Within a stated preference study, do survey respondents represent the studied population?

  64. We use the term “quantities” in a general sense to reflect the scope or magnitude of change in environmental conditions, realizing that these changes can represent environmental qualities (e.g., water quality) or quantities (e.g., hectares of forest).

  65. Studies such as Johnston et al. (2006), Moeltner et al. (2007) and Stapler and Johnston (2009) explore how value predictions vary depending on the treatment of study methodology within meta-functions used for benefit transfer.

  66. For example, some types of value transfers may not permit one to calculate expected error bounds, if insufficient study-site reporting is available.

  67. For example, see Wilson and Hoehn (2006), Rosenberger and Johnston (2009), Boyle et al. (2010), Johnston and Rosenberger (2010), Johnston et al. (2015c, 2018), and Smith (2018).

  68. The issue is also discussed by Newbold et al. (2018a).

  69. These issues can be addressed by evaluating the value of information (VOI) provided by a benefit transfer. Existing VOI studies suggest that the use of original valuation studies to inform environmental decisions is often warranted, but that benefit transfers nonetheless enhance the efficiency of environmental decisions (Barton 2007; Allen and Loomis 2008; Newbold and Johnston 2020).

References

  • Addicott ET, Fenichel EP (2019) Spatial aggregation and the value of natural capital. J Environ Econ Manag 95:118–132

    Article  Google Scholar 

  • Aldy JE, Viscusi WK (2008) Adjusting the value of a statistical life for age and cohort effects. Rev Econ Stat 90(3):573–581

    Article  Google Scholar 

  • Allen BP, Loomis JB (2008) The decision to use benefit transfer or conduct original valuation research for benefit-cost and policy analysis. Contemp Econ Policy 26(1):1–12

    Article  Google Scholar 

  • Ahtiainen H, Artell J, Czajkowski M, Hasler B, Hasselström L, Huhtala A, Meyerhoff J, Smart JCR, Söderqvist T, Alemu MH, Angeli D, Dahlbo K, Fleming-Lehtinen V, Hyytiäinen K, Karlõševa A, Khaleeva Y, Maar M, Martinsen L, Nõmmann T, Pakalniete K, Oskolokaite I, Semeniene D (2014) Benefits of meeting nutrient reduction targets for the Baltic Sea – A contingent valuation study in the nine coastal states. J Environ Econ Policy 3(3):1–28

    Article  Google Scholar 

  • Andreopoulos D, Damigos D (2017) To transfer or not to transfer? Evidence from validity and reliability tests for international transfers of non-market adaptation benefits in river basins. J Environ Manage 185:44–53

    Article  Google Scholar 

  • Artell J, Ahtiainen H, Pouta E (2019) Distance decay and regional statistics in international benefit transfer. Ecol Econ 164:106383

    Article  Google Scholar 

  • Bagstad KJ, Semmens DJ, Waage S, Winthrop R (2013) A comparative assessment of decision-support tools for ecosystem services quantification and valuation. Ecosyst Serv 5:e27–e39

    Article  Google Scholar 

  • Barbier EB, Czajkowski M, Hanley N (2017) Is the income elasticity of the willingness to pay for pollution control constant? Environ Resource Econ 68:663–682

    Article  Google Scholar 

  • Barton D (2007) How much is enough? The value of information from benefit transfers in a policy context. In: Navrud S, Ready R (eds) Environmental value transfer: issues and methods. Springer, Dordrecht, The Netherlands, pp 261–282

    Chapter  Google Scholar 

  • Barton DN (2002) The transferability of benefit transfer: contingent valuation of water quality improvements in Costa Rica. Ecol Econ 42:147–164

    Article  Google Scholar 

  • Bateman IJ, Day BH, Georgiou S, Lake I (2006) The aggregation of environmental benefit values: welfare measures, distance decay and total WTP. Ecol Econ 60:450–460

    Article  Google Scholar 

  • Bateman IJ, Brouwer R, Ferrini S, Schaafsma M, Barton DN, Dubgaard A, Hasler B, Hime S, Liekens I, Navrud S, De Nocker L, Ščeponavičiūtė R, Semėnienė D (2011a) Making benefit transfers work: deriving and testing principles for value transfers for similar and dissimilar sites using a case study of the non-market benefits of water quality improvements across Europe. Environ Resource Econ 50(3):365–387

    Article  Google Scholar 

  • Bateman IJ, Harwood A, Mace GM, Watson R, Abson DJ, Andrews B, Binner A, Crowe A, Day BH, Dugdale S, Fezzi C, Foden J, Haines-Young R, Hulme M, Kontoleon A, Lovett AA, Munday P, Pascual U, Paterson J, Perino G, Sen A, Siriwardena G, van Soest D, Termansen M (2013) Bringing ecosystem services into economic decision making: land use in the UK. Science 341(6141):45–50

    Article  Google Scholar 

  • Bateman IJ, Kling CL (2020) Revealed preference methods for nonmarket valuation: an introduction to best practices. Rev Environ Econ Policy 14(2):240–259

    Article  Google Scholar 

  • Bateman IJ, Mace GM, Fezzi C, Atkinson G, Turner K (2011b) Economic analysis for ecosystem service assessments. Environ Resource Econ 48:177–218

    Article  Google Scholar 

  • Bateman IJ, Lovett AA (1998) Using geographical information systems (GIS) and large area databases to predict yield class: a study of Sitka spruce in Wales. Forestry 71(2):147–168

    Article  Google Scholar 

  • Baumgärtner S, Drupp MA, Meya JN, Munz JM, Quaas MF (2017) Income inequality and willingness to pay for environmental public goods. J Environ Econ Manag 85:35–61

    Article  Google Scholar 

  • Bergstrom JC, De Civita P (1999) Status of benefit transfer in the United States and Canada: a review. Can J Agric Econ 47:79–87

    Article  Google Scholar 

  • Bergstrom JC, Taylor LO (2006) Using meta-analysis for benefits transfer: theory and practice. Ecol Econ 60:351–360

    Article  Google Scholar 

  • Bishop KC, Kuminoff NV, Banzhaf HS, Boyle KJ, von Gravenitz K, Pope JC, Smith VK, Timmins CD (2020) Best practices for using hedonic property value models to measure willingness to pay for environmental quality. Rev Environ Econ Policy 14(2):260–281

    Article  Google Scholar 

  • Bishop RC, Boyle KJ (2019) Reliability and validity in nonmarket valuation. Environ Resource Econ 72(2):559–582

    Article  Google Scholar 

  • Bishop RC, Boyle KJ, Carson RT, Chapman D, Hanemann WM, Kanninen B, Kopp RJ, Krosnick JA, List J, Meade N, Paterson R (2017) Putting a value on injuries to natural assets: the BP oil spill. Science 356(6335):253–254

    Article  Google Scholar 

  • Bliem M, Getzner M (2012) Willingness-to-pay for river restoration: differences across time and scenarios. Environ Econ Policy Stud 14:241–260

    Article  Google Scholar 

  • Blow L, Blundell R (2018) A nonparametric revealed preference approach to measuring the value of environmental quality. Environ Resource Econ 69:503–527

    Article  Google Scholar 

  • Bockstael NE, Freeman AM, Kopp RJ, Portney PR, Smith VK (2000) On measuring economic values for nature. Environ Sci Technol 34:1384–1389

    Article  Google Scholar 

  • Boyd J, Ringold P, Krupnick A, Johnston RJ, Weber MA, Hall K (2016) Ecosystem services indicators: improving the linkage between biophysical and economic analyses. Int Rev Environ Resour Econ 8:359–443

    Article  Google Scholar 

  • Boyle KJ, Bergstrom JC (1992) Benefit transfer studies: myths, pragmatism and idealism. Water Resour Res 28:657–663

    Article  Google Scholar 

  • Boyle KJ, Kuminoff NV, Parmeter CF, Pope JC (2009) Necessary conditions for valid benefit transfers. Am J Agr Econ 91:1328–1334

    Article  Google Scholar 

  • Boyle KJ, Kuminoff NV, Parmeter CF, Pope JC (2010) The benefit-transfer challenges. Annual Review of Resource Economics 2:161–182

    Article  Google Scholar 

  • Boyle KJ, Parmeter CF, Boehlert BB, Paterson RW (2013) Due diligence in meta-analyses to support benefit transfers. Environ Resour Econ 55:357–386

    Article  Google Scholar 

  • Boyle KJ, Kaul S, Parmeter CF (2015) Meta-analysis: econometric advances and new perspectives towards data synthesis and robustness. In: Johnston RJ, Rolfe J, Rosenberger RS, Brouwer R (eds) Benefit transfer of environmental and resource values: a guide for researchers and practitioners. Springer, Dordrecht, The Netherlands, pp 383–418

    Chapter  Google Scholar 

  • Boyle KJ, Kotchen MJ, Smith VK (2017) Deciphering dueling analyses of clean water regulations. Science 358:49–50

    Article  Google Scholar 

  • Boyle KJ, Wooldridge JM (2018) Understanding error structures and exploiting panel data in meta-analytic benefit transfers. Environ Resour Econ 69:609–635

    Article  Google Scholar 

  • Brookshire D, Neill H (1992) Benefit transfers: conceptual and ethical issues. Water Resour Res 28:651–655

    Article  Google Scholar 

  • Brander LM, Bräuer I, Gerdes H, Ghermandi A, Kuik O, Markandya A, Navrud S, Nunes PALD, Schaafsma M, Vos H, Wagtendonk A (2012) Using meta-analysis and GIS for value transfer and scaling up: valuing climate change induced losses of European wetlands. Environ Resour Econ 52:395–413

    Article  Google Scholar 

  • Brander LM, van Beukering P, Cesar HSJ (2007) The recreational value of coral reefs: a meta-analysis. Ecol Econ 63:209–218

    Article  Google Scholar 

  • Brent RJ (2006) Applied cost-benefit analysis. Edward Elgar Publishing, Camberley

    Google Scholar 

  • Brent R (2009) Handbook of research on cost-benefit analysis. Edward Elgar Publishing, Camberley

    Book  Google Scholar 

  • Brouwer R (2000) Environmental value transfer: state of the art and future prospects. Ecol Econ 32:137–152

    Article  Google Scholar 

  • Brouwer R (2006) Do stated preference methods stand the test of time? A test of the stability of contingent values and models for health risks when facing an extreme event. Ecol Econ 60:399–406

    Article  Google Scholar 

  • Brouwer R, Bateman IJ (2005) Benefits transfer of willingness to pay estimates and functions for health-risk reductions: a cross-country study. J Health Econ 24:591–611

    Article  Google Scholar 

  • Brouwer R, Navrud S (2015) The use and development of benefit transfer in Europe. In: Johnston RJ, Rolfe J, Rosenberger RS, Brouwer R (eds) Benefit transfer of environmental and resource values: a guide for researchers and practitioners. Springer, Dordrecht, The Netherlands, pp 71–83

    Chapter  Google Scholar 

  • Brouwer R, Spaninks FA (1999) The validity of environmental benefits transfer: further empirical testing. Environ Resource Econ 14(1):95–117

    Article  Google Scholar 

  • Brouwer R, Martin-Ortega J, Dekker T, Sardonini L, Andreu J, Kontogianni A, Skourtos M, Raggi M, Viaggi D, Pulido-Velazquez M, Rolfe J, Windle J (2015) Improving value transfer through socio-economic adjustments in a multi-country choice experiment of water conservation alternatives. Aust J Agric Resour Econ 59:458–478

    Article  Google Scholar 

  • Brouwer R, Bliem M, Getzner M, Kerekes S, Milton S, Palarie T, Szerényi Z, Vadineanu A, Wagtendonk A (2016) Valuation and transferability of the non-market benefits of river restoration in the Danube River Basin using a choice experiment. Ecol Eng 87:20–29

    Article  Google Scholar 

  • Carolus JF, Jacobsen JB, Olsen SB (2020) The impacts of three dimensions of (dis)similarities on water quality benefit transfer errors. Water Resourc Econ 32:100164

    Article  Google Scholar 

  • Champ PA, Boyle KC, Brown TC (eds) (2017) A primer on nonmarket valuation. Springer Science and Business Media, Netherlands

    Google Scholar 

  • Carson RT, Louviere JJ, Rose JM, Swait J (2015) Frontiers in modeling discrete choice experiments: a benefit transfer perspective. In: Johnston RJ, Rolfe J, Rosenberger RS, Brouwer R (eds) Benefit transfer of environmental and resource values: a guide for researchers and practitioners. Springer, Dordrecht, The Netherlands, pp 209–236

    Chapter  Google Scholar 

  • Colombo S, Hanley N (2008) How can we reduce the errors from benefits transfer? An investigation using the choice experiment method. Land Econ 84:128–147

    Article  Google Scholar 

  • Corona J, Doley T, Griffiths C, Massey M, Moore C, Muela S, Rashleigh B, Wheeler W, Whitlock SD, Hewitt J (2020) An integrated assessment model for valuing water quality changes in the United States. Land Econ 96(4):478–492

    Article  Google Scholar 

  • Czajkowski M, Ščasný M (2010) Study on benefit transfer in an international setting. How to improve welfare estimates in the case of the countries’ income heterogeneity? Ecol Econ 69(12):2409–2416

    Article  Google Scholar 

  • Czajkowski M, Ahtiainen H, Artell J, Meyerhoff J (2017) Choosing a functional form for an international benefit transfer: evidence from a nine-country valuation experiment. Ecol Econ 134:104–113

    Article  Google Scholar 

  • De Blaeij A, Florax RJ, Rietveld P, Verhoef E (2003) The value of statistical life in road safety: a meta-analysis. Accid Anal Prev 35(6):973–986

    Article  Google Scholar 

  • De Groot RS, Wilson MA, Boumans RMJ (2002) A typology for the classification, description and valuation of ecosystem functions, goods and services. Ecol Econ 41:393–408

    Article  Google Scholar 

  • Desvousges WH, Johnson FR, Banzhaf HS (1998) Environmental policy analysis with limited information: principles and applications of the transfer method. Edward Elgar, Cheltenham, UK

    Book  Google Scholar 

  • Diamond PA, Hausman JA (1994) Contingent valuation: is some number better than no number? Journal of Economic Perspectives 8(4):45–64

    Article  Google Scholar 

  • Dugstad A, Navrud S (2019) How reliable are expert predictions of households´ willingness-to-pay to preserve the Amazon rainforest. Comparing contingent valuation, Delphi surveys and benefit transfer. Paper presented at the European Association of Environmental and Resource Economists (EAERE) 24th annual conference, Manchester, UK, 26–29 June 2019

  • Eiswerth ME, Shaw WD (1997) Adjusting benefits transfer values for inflation. Water Resour Res 33:2381–2385

    Article  Google Scholar 

  • Engel S (2002) Benefit function transfer versus meta-analysis as policy tool: a comparison. In: Florax RJGM, Nijkamp P, Willis KG (eds) Comparative environmental economics assessment. Edward Elgar, Chelthenham

    Google Scholar 

  • Farrow S, Zerbe RO (eds) (2013) Principles and standards for benefit-cost analysis. Edward Elgar, Camberley

    Google Scholar 

  • Ferrini S, Schaafsma M, Bateman IJ (2014) Revealed and stated preference valuation and transfer: a within-sample comparison of water quality improvement values. Water Resour Res 50:4746–5475

    Article  Google Scholar 

  • Ferrini S, Schaafsma M, Bateman IJ (2015) Ecosystem services assessment and benefit transfer. In: Johnston RJ, Rolfe J, Rosenberger RS, Brouwer R (eds) Benefit transfer of environmental and resource values: a guide for researchers and practitioners. Springer, Dordrecht, The Netherlands, pp 275–305

    Chapter  Google Scholar 

  • Fetene GM, Olsen SB, Bonnichsen O (2014) Disentangling the pure time effect from site and preference heterogeneity effects in benefit transfer: an empirical investigation of transferability. Environ Resour Econ 59:583–611

    Article  Google Scholar 

  • Fezzi C, Bateman IJ (2011) Structural agricultural land use modeling for spatial agro-environmental policy analysis. Am J Agr Econ 93(4):1168–1188

    Article  Google Scholar 

  • Florax RJGM (2002) Methodological pitfalls in meta-analysis: publication bias. In: Florax RJGM, Nijkamp P, Willis KG (eds) Comparative environmental economics assessment. Edward Elgar, Chelthenham

    Chapter  Google Scholar 

  • Florax RJGM, Nijkamp P, Willis KG (eds) (2002) Comparative environmental economics assessment. Edward Elgar, Chelthenham, UK

    Google Scholar 

  • Flores NE, Thacher J (2002) Money, who needs it? Natural resource damage assessment. Contemp Econ Policy 20(2):171–178

    Article  Google Scholar 

  • Freeman AM III (1984) On the tactics of benefit estimation under Executive Order 12291. In: Smith VK (ed) Environmental policy under Reagan’s Executive Order: the role of benefit-cost analysis. University of North Carolina Press, Chapel Hill

    Google Scholar 

  • Freeman AM, Herriges JA, Kling CL (2014) The measurement of environmental and resource values: theory and methods, 3rd edn. Resources for the Future, Washington, DC

    Book  Google Scholar 

  • Griffiths C, Wheeler WJ (2005) Benefit-cost analysis of regulations affecting surface water quality in the United States. In: Brouwer R, Pearce D (eds) Cost-benefit analysis and water resources management. Edward Elgar, Cheltenham

    Google Scholar 

  • Griffiths C, Klemick H, Massey M, Moore C, Newbold S, Simpson D, Walsh P, Wheeler W (2012) US Environmental Protection Agency valuation of surface water quality improvements. Rev Environ Econ Policy 6:130–146

    Article  Google Scholar 

  • Hammitt JK, Robinson LA (2011) The income elasticity of the value per statistical life: transferring estimates between high and low income populations. J Benefit Cost Anal 2(1):1–29

    Article  Google Scholar 

  • Hanley N, Colombo S, Tinch D, Black A, Aftab A (2006) Estimating the benefits of water quality improvements under the Water Framework Directive: are benefits transferable? Eur Rev Agric Econ 33(3):391–413

    Article  Google Scholar 

  • Hanley N, Schläpfer F, Spurgeon J (2003) Aggregating the benefits of environmental improvements: distance-decay functions for use and non-use values. J Environ Manage 68:297–304

    Article  Google Scholar 

  • He X, Poe GL (2020) Exploring the shelf-life of travel cost methods of valuing recreation for benefits transfer. Resour Energy Econ 63:101123

    Article  Google Scholar 

  • Hines JR (1999) Three sides of Harberger Triangles. J Econ Perspect 13(2):167–188

    Article  Google Scholar 

  • Hoehn JP (2006) Methods to address selection effects in the meta regression and transfer of ecosystem values. Ecol Econ 60:389–398

    Article  Google Scholar 

  • Huntington-Klein N, Arenas A, Beam E, Bertoni M, Bloem JR, Burli P, Chen N, Grieco P, Ekpe G, Pugatch T, Saavedra M, Stopnitzky Y (2021) The influence of hidden researcher decisions in applied microeconomics. Econ Inq 59:944–960

    Article  Google Scholar 

  • Horowitz JK, McConnell KE (2002) A review of WTA/WTP studies. J Environ Econ Manag 44(3):426–447

    Article  Google Scholar 

  • Hynes S, Norton D, Hanley N (2013) Adjusting for cultural differences in international benefit transfer. Environ Resour Econ 56:499–519

    Article  Google Scholar 

  • Iovanna R, Griffiths C (2006) Clean water, ecological benefits, and benefits transfer: a work in progress at the U.S. EPA Ecol Econ 60:473–482

    Article  Google Scholar 

  • Johnston RJ (2006) Is hypothetical bias universal? Validating contingent valuation response using a binding public referendum. J Environ Econ Manag 52:469–481

    Article  Google Scholar 

  • Johnston RJ (2007) Choice experiments, site similarity and benefits transfer. Environ Resour Econ 38:331–351

    Article  Google Scholar 

  • Johnston RJ, Besedin EY, Iovanna R, Miller CJ, Wardwell RF, Ranson MH (2005) Systematic variation in willingness to pay for aquatic resource improvements and implications for benefit transfer: a meta-analysis. Can J Agric Econ 53:221–248

    Article  Google Scholar 

  • Johnston RJ, Besedin EY, Ranson MH (2006) Characterizing the effects of valuation methodology in function-based benefits transfer. Ecol Econ 60:407–419

    Article  Google Scholar 

  • Johnston RJ, Duke JM (2009) Willingness to pay for land preservation across states and jurisdictional scale: implications for benefit transfer. Land Econ 85:217–237

    Article  Google Scholar 

  • Johnston RJ, Duke JM (2010) Socioeconomic adjustments and choice experiment benefit function transfer: evaluating the common wisdom. Resource and Energy Economics 32:421–438

    Article  Google Scholar 

  • Johnston RJ, Rosenberger RS (2010) Methods, trends and controversies in contemporary benefit transfer. J Econ Surv 24:479–510

    Google Scholar 

  • Johnston RJ, Thomassin PJ (2010) Willingness to pay for water quality improvements in the United States and Canada: considering possibilities for international meta-analysis and benefit transfer. Agric Resour Econ Rev 39:114–131

    Article  Google Scholar 

  • Johnston RJ, Schultz ET, Segerson K, Besedin EY, Ramachandran M (2012) Enhancing the content validity of stated preference valuation: the structure and function of ecological indicators. Land Econ 88(1):102–120

    Article  Google Scholar 

  • Johnston RJ, Moeltner K (2014) Meta-modeling and benefit transfer: the empirical relevance of source-consistency in welfare measures. Environ Resour Econ 59:337–361

    Article  Google Scholar 

  • Johnston RJ, Rolfe J, Rosenberger RS, Brouwer R (eds) (2015a) Benefit transfer of environmental and resource values: a guide for researchers and practitioners. Springer, Dordrecht, The Netherlands

    Google Scholar 

  • Johnston RJ, Rolfe J, Rosenberger RS, Brouwer R (2015) Introduction to benefit transfer methods. In: Johnston RJ, Rolfe J, Rosenberger RS, Brouwer R (eds) Benefit transfer of environmental and resource values: a guide for researchers and practitioners. Springer, Dordrecht

    Chapter  Google Scholar 

  • Johnston RJ, Rosenberger RS, Rolfe J, Brouwer R (2015) Benefit transfer: the present state and future prospects. In: Johnston RJ, Rolfe J, Rosenberger RS, Brouwer R (eds) Benefit transfer of environmental and resource values: a guide for researchers and practitioners. Springer, Dordrecht

    Chapter  Google Scholar 

  • Johnston RJ, Besedin EY, Stapler R (2017a) Enhanced geospatial validity for meta-analysis and environmental benefit transfer: an application to water quality improvements. Environ Resource Econ 68:343–375

    Article  Google Scholar 

  • Johnston RJ, Boyle KJ, Adamowicz W, Bennett J, Brouwer R, Cameron TA, Hanemann WM, Hanley N, Ryan M, Scarpa R, Tourangeau R, Vossler CA (2017b) Contemporary guidance for stated preference studies. J Assoc Environ Resour Econ 4:319–405

    Google Scholar 

  • Johnston RJ, Rolfe J, Zawojska E (2018) Benefit transfer of environmental and resource values: progress, prospects and challenges. Int Rev Environ Resour Econ 12(2–3):177–266

    Article  Google Scholar 

  • Johnston RJ, Besedin EY, Holland BM (2019) Modeling distance decay within valuation meta-analysis. Environ Resour Econ 72(3):657–690

    Article  Google Scholar 

  • Johnston RJ, Bauer DM (2020) Using meta-analysis for large-scale ecosystem service valuation: progress, prospects and challenges. Agric Resour Econ Rev 49(1):23–63

    Article  Google Scholar 

  • Johnston RJ, Zawojska E (2020) Relative versus absolute commodity measurements in benefit transfer: consequences for validity and reliability. Am J Agr Econ 102(4):1245–1270

    Article  Google Scholar 

  • Just RE, Hueth DL, Schmitz A (2004) The welfare economics of public policy: a practical approach to project and policy evaluation. Edward Elgar, Cheltenham, UK

    Google Scholar 

  • Kaul S, Boyle KJ, Kuminoff NV, Parmeter CF, Pope JC (2013) What can we learn from benefit transfer errors? Evidence from 20 years of research on convergent validity. J Environ Econ Manag 66:90–104

    Article  Google Scholar 

  • Klemick H, Griffiths C, Guignet D, Walsh P (2018) Improving water quality in an iconic estuary: an internal meta-analysis of property value impacts around the Chesapeake Bay. Environ Resource Econ 69:265–292

    Article  Google Scholar 

  • Kling CL, Phaneuf DJ (2018) How are scope and adding up relevant for benefits transfer? Environ Resource Econ 69:483–502

    Article  Google Scholar 

  • Kosenius AK, Markku O (2015) Ecosystem benefits from coastal habitats: a three-country choice experiment. Mar Policy 58:15–27

    Article  Google Scholar 

  • Kristofersson D, Navrud S (2005) Validity tests of benefit transfer: are we performing the wrong tests? Environ Resource Econ 30:279–286

    Article  Google Scholar 

  • Kuminoff NV (2018) Can understanding spatial equilibria enhance benefit transfers for environmental policy evaluation? Environ Resource Econ 69:591–608

    Article  Google Scholar 

  • Lew DK, Wallmo K (2017) Temporal stability of stated preferences for endangered species protection from choice experiments. Ecol Econ 131:87–97

    Article  Google Scholar 

  • Lindhjem H, Navrud S (2008) How reliable are meta-analyses for international benefit transfers? Ecol Econ 66:425–435

    Article  Google Scholar 

  • Lindhjem H, Navrud S (2015) Reliability of meta-analytic benefit transfers of international value of statistical life estimates: tests and illustrations. In: Johnston RJ, Rolfe J, Rosenberger RS, Brouwer R (eds) Benefit transfer of environmental and resource values: a guide for researchers and practitioners. Springer, Dordrecht

    Google Scholar 

  • Lloyd-Smith P, Adamowicz W (2018) Can stated measures of willingness-to-accept be valid? Evidence from laboratory experiments. J Environ Econ Manag 91:133–149

    Article  Google Scholar 

  • Londoño LM, Johnston RJ (2012) Enhancing the reliability of benefit transfer over heterogeneous sites: a meta-analysis of international coral reef values. Ecol Econ 78:80–89

    Article  Google Scholar 

  • Loomis JB (1992) The evolution of a more rigorous approach to benefit transfer: benefit function transfer. Water Resour Res 28:701–705

    Article  Google Scholar 

  • Loomis JB (1996) How large is the extent of the market for public goods: evidence from a Nationwide Contingent Valuation Survey. Appl Econ 28:779–782

    Article  Google Scholar 

  • Loomis JB (2000) Vertically summing public good demand curves: an empirical comparison of economic versus political jurisdiction. Land Econ 76:312–321

    Article  Google Scholar 

  • Loomis JB (2015) The use of benefit transfer in the United States. In: Johnston RJ, Rolfe J, Rosenberger RS, Brouwer R (eds) Benefit transfer of environmental and resource values: a guide for researchers and practitioners. Springer, Dordrecht

    Google Scholar 

  • Loomis J, Roach B, Ward F, Ready R (1995) Testing transferability of recreation demand models across regions: a study of corps of engineer reservoirs. Water Resour Res 31:721–730

    Article  Google Scholar 

  • Loomis JB, Rosenberger RS (2006) Reducing barriers in future benefit transfers: needed improvements in primary study design and reporting. Ecol Econ 60:343–350

    Article  Google Scholar 

  • Loureiro ML, Loomis JB (2017) How sensitive are environmental valuations to economic downturns? Ecol Econ 140:235–240

    Article  Google Scholar 

  • Lovell S, Newbold SC, Owens N, Wyatt TJ (2004) How academic economists can improve benefit transfers at EPA. Assoc Environ Resour Econ AERE Newslett 24:25–28

    Google Scholar 

  • Lupi F, Phaneuf DJ, von Haefen RH (2020) Best practices for implementing recreation demand models. Rev Environ Econ Policy 14(2):302–323

    Article  Google Scholar 

  • Martin-Ortega J, Brouwer R, Ojea E, Berbel J (2012) Benefit transfer and spatial heterogeneity of preferences for water quality improvements. J Environ Manage 106:22–29

    Article  Google Scholar 

  • McComb G, Lantz V, Nash K, Rittmaster R (2006) International valuation databases: overview, methods and operational issues. Ecol Econ 60:461–472

    Article  Google Scholar 

  • McConnell KE, Siikämaki JV (2018) Seeking external evidence to assess benefit transfers for environmental policy. Environ Resour Econ 69:555–573

    Article  Google Scholar 

  • Mendelsohn R, Olmstead S (2009) The economic valuation of environmental amenities and disamenities: methods and applications. Annu Rev Environ Resour 34:325–347

    Article  Google Scholar 

  • Meya JN, Drupp MA, Hanley N. (2021) Testing structural benefit transfer: the role of income inequality. Resour Energy Econ 64: 101217

  • Moeltner K (2015) Optimal scope and Bayesian model search in benefit transfer. In: Johnston RJ, Rolfe J, Rosenberger RS, Brouwer R (eds) Benefit transfer of environmental and resource values: a guide for researchers and practitioners. Springer, Dordrecht

    Google Scholar 

  • Moeltner K (2019) Bayesian nonlinear meta regression for benefit transfer. J Environ Econ Manag 93:44–62

    Article  Google Scholar 

  • Moeltner K, Boyle KJ, Paterson RW (2007) Meta-analysis and benefit transfer for resource valuation-addressing classical challenges with Bayesian modeling. J Environ Econ Manag 53:250–269

    Article  Google Scholar 

  • Moeltner K, Rosenberger RS (2014) Cross-context benefit transfer: a Bayesian search for information pools. Am J Agr Econ 96:469–488

    Article  Google Scholar 

  • Moeltner K, Balukas JA, Besedin E, Holland B (2019) Waters of the United States: upgrading wetland valuation via benefit transfer. Ecol Econ 164:106336

    Article  Google Scholar 

  • Morrison M, Bergland O (2006) Prospects for the use of choice modelling for benefit transfer. Ecol Econ 60:420–428

    Article  Google Scholar 

  • Morrison M, Bennett J, Blamey R, Louviere J (2002) Choice modeling and tests of benefit transfer. Am J Agr Econ 84(1):161–170

    Article  Google Scholar 

  • Mrozek JR, Taylor LO (2002) What determines the value of life? A meta-analysis. J Policy Anal Manage 21:253–270

    Article  Google Scholar 

  • Muthke T, Holm-Mueller K (2004) National and international benefit transfer with a rigorous test procedure. Environ Resource Econ 29:323–336

    Article  Google Scholar 

  • Navrud S, Pruckner GJ (1997) Environmental valuation-to use or not to use? A comparative study of the United States and Europe. Environ Resource Econ 10:1–26

    Article  Google Scholar 

  • Navrud S, Ready RC (eds) (2007) Environmental value transfer: issues and methods. Springer, Dordrecht, The Netherlands

    Google Scholar 

  • Navrud S, Strand J (2018) Valuing global ecosystem services - what do European experts say? Applying the Delphi method to contingent valuation of the Amazon rainforest. Environ Resource Econ 70(1):249–269

    Article  Google Scholar 

  • Nelson JP (2015) Meta-analysis: statistical methods. In: Johnston RJ, Rolfe J, Rosenberger RS, Brouwer R (eds) Benefit transfer of environmental and resource values: a guide for researchers and practitioners. Springer, Dordrecht

    Google Scholar 

  • Nelson JP, Kennedy PE (2009) The use (and abuse) of meta-analysis in environmental and resource economics: an assessment. Environ Resource Econ 42:345–377

    Article  Google Scholar 

  • Newbold S, Walsh PJ, Massey DM, Hewitt J (2018a) Using structural restrictions to achieve theoretical consistency in benefit transfers. Environ Resour Econ 69:529–554

    Article  Google Scholar 

  • Newbold S, Simpson RD, Massey DM, Heberling MT, Wheeler W, Corona J, Hewitt J (2018b) Benefit transfer challenges: perspectives from U.S. practitioners. Environ Resour Econ 69:467–482

    Article  Google Scholar 

  • Newbold SC, Johnston RJ (2020) Valuing non-market valuation studies using meta-analysis: a demonstration using estimates of willingness-to-pay for water quality improvements. J Environ Econ Manag 104:102379

    Article  Google Scholar 

  • Olander LP, Johnston RJ, Tallis H, Kagan J, Maguire LA, Polasky S, Urban D, Boyd J, Wainger L, Palmer M (2018) Benefit relevant indicators: ecosystem services measures that link ecological and social outcomes. Ecol Ind 85:1262–1272

    Article  Google Scholar 

  • Olander L, Polasky S, Kagan JS, Johnston RJ, Wainger L, Saah D, Maguire L, Boyd J, Yoskowitz D (2017) So you want your research to be relevant? Building the bridge between ecosystem services research and practice. Ecosyst Serv 26:170–182

    Article  Google Scholar 

  • Östberg K, Håkansson C, Hasselström L, Bostedt G (2013) Benefit transfer for environmental improvements in coastal areas: deneral versus best-fitting models. Can J Agric Econo/revue Canadienne D’agroeconomie 61:239–258

    Article  Google Scholar 

  • Parsons GR, Kealy MJ (1994) Benefits transfer in a random utility model of recreation. Water Resour Res 30:2477–2484

    Article  Google Scholar 

  • Perino G, Andrews B, Kontoleon A, Bateman I (2014) The value of urban green space in Britain: a methodological framework for spatially referenced benefit transfer. Environ Resour Econ 57:251–272

    Article  Google Scholar 

  • Phaneuf DJ, Van Houtven G (2015) Structural benefit transfer using Bayesian econometrics. In: Johnston RJ, Rolfe J, Rosenberger RS, Brouwer R (eds) Benefit transfer of environmental and resource values: a guide for researchers and practitioners. Springer, Dordrecht

    Google Scholar 

  • Ready R, Navrud S (2006) International benefit transfer: methods and validity tests. Ecol Econ 60:429–434

    Article  Google Scholar 

  • Ready R, Navrud S, Day B, Dubourg R, Machado F, Mourato S, Spanninks F, Xosé M, Rodriquez V (2004) Benefit transfer in Europe: how reliable are transfers between countries? Environ Resource Econ 29:67–82

    Article  Google Scholar 

  • Richardson L, Loomis J, Kroeger T, Casey F (2015) The role of benefit transfer in ecosystem service valuation. Ecol Econ 115:51–58

    Article  Google Scholar 

  • Rolfe J, Bennett J (eds) (2006) Choice modelling and the transfer of environmental values. Edward Elgar, Cheltenham, UK

    Google Scholar 

  • Rolfe J, Wang X (2011) Dealing with scale and scope issues in stated preference experiments. In: Bennett J (ed) The international handbook on non-market environmental valuation. Edward Elgar, Cheltenham

    Google Scholar 

  • Rolfe J, Windle J (2008) Testing for differences in benefit transfer values between state and regional frameworks. Aust J Agric Resour Econ 52:149–168

    Article  Google Scholar 

  • Rolfe J, Windle J (2012) Testing benefit transfer of reef protection values between local case studies: the Great Barrier Reef in Australia. Ecol Econ 81:60–69

    Article  Google Scholar 

  • Rolfe J, Bennett J, Kerr G (2015) Applied benefit transfer: an Australian and New Zealand policy perspective. In: Johnston RJ, Rolfe J, Rosenberger RS, Brouwer R (eds) Benefit transfer of environmental and resource values: a guide for researchers and practitioners. Springer, Dordrecht

    Chapter  Google Scholar 

  • Rolfe J, Brouwer R, Johnston RJ (2015) Meta-analysis: rationale, issues and applications. In: Johnston RJ, Rolfe J, Rosenberger RS, Brouwer R (eds) Benefit transfer of environmental and resource values: a guide for researchers and practitioners. Springer, Dordrecht

    Chapter  Google Scholar 

  • Rolfe J, Windle J, Johnston RJ (2015) Applying benefit transfer with limited data: unit value transfers in practice. In: Johnston RJ, Rolfe J, Rosenberger RS, Brouwer R (eds) Benefit transfer of environmental and resource values: a guide for researchers and practitioners. Springer, Dordrecht

    Chapter  Google Scholar 

  • Rosenberger RS (2015) Benefit transfer validity and reliability. In: Johnston RJ, Rolfe J, Rosenberger RS, Brouwer R (eds) Benefit transfer of environmental and resource values: a guide for researchers and practitioners. Springer, Dordrecht

    Google Scholar 

  • Rosenberger RS, Johnston RJ (2009) Selection effects in meta-analysis and benefit transfer: Avoiding unintended consequences. Land Econ 85:410–428

    Article  Google Scholar 

  • Rosenberger RS, Loomis JB (2003) Benefit transfer. In: Champ PA, Boyle KJ, Brown TC (eds) A primer on nonmarket valuation. Springer, Dordrecht, The Netherlands, pp 445–482

    Chapter  Google Scholar 

  • Rosenberger RS, Loomis JB (2017) Benefit transfer. In: Champ PA, Boyle KJ, Brown TC (eds) A primer on nonmarket valuation, 2nd edn. Springer, Dordrecht

    Google Scholar 

  • Rosenberger RS, Stanley TD (2006) Measurement, generalization and publication: sources of error in benefit transfers and their management. Ecol Econ 60:372–378

    Article  Google Scholar 

  • Rosenberger RS, Phipps TT (2007) Correspondence and convergence in benefit transfer accuracy: meta-analytic review of the literature. In: Navrud S, Ready RC (eds) Environmental value transfer: issues and methods. Springer, Dordrecht

    Google Scholar 

  • Schaafsma M (2015) Spatial and geographical aspects of benefit transfer. In: Johnston RJ, Rolfe J, Rosenberger RS, Brouwer R (eds) Benefit transfer of environmental and resource values: a guide for researchers and practitioners. Springer, Dordrecht

    Google Scholar 

  • Schaafsma M, Brouwer R, Liekens I, De Nocker L (2014) Temporal stability of preferences and willingness to pay for natural areas in choice experiments: a test-retest. Resour Energy Econ 38:243–260

    Article  Google Scholar 

  • Schultz ET, Johnston RJ, Segerson K, Besedin EY (2012) Integrating ecology and economics for restoration: using ecological indicators in valuation of ecosystem services. Restor Ecol 20(3):304–310

    Article  Google Scholar 

  • Siikamaki JV, Krupnick AJ, Strand J, Vincent J (2019) International willingness to pay for the protection of the Amazon rainforest (March 11, 2019). World Bank Policy Research Working Paper No. 8775. Available at SSRN: https://ssrn.com/abstract=3360132

  • Simpson RD (2016) The simple but not-too-simple valuation of ecosystem services: basic principles and an illustrative example. J Environ Econ Policy. https://doi.org/10.1080/21606544.2016.1184594

    Article  Google Scholar 

  • Smith VK (2018) Benefits transfer: current practice and prospects. Environ Resour Econ 69:449–466

    Article  Google Scholar 

  • Smith VK, Huang JC (1995) Can markets value air quality? A meta-analysis of hedonic property value models. J Polit Econ 103:209–227

    Article  Google Scholar 

  • Smith VK, Pattanayak SK (2002) Is meta-analysis a Noah’s Ark for non-market valuation? Environ Resour Econ 22:271–296

    Article  Google Scholar 

  • Smith VK, Van Houtven G, Pattanayak SK (2002) Benefit transfer via preference calibration: ‘Prudential algebra’ for policy. Land Econ 78:132–152

    Article  Google Scholar 

  • Smith VK, Pattanayak SK, Van Houtven G (2006) Structural benefit transfer: an example using VSL estimates. Ecol Econ 60:361–371

    Article  Google Scholar 

  • Spash CL, Vatn A (2006) Transferring environmental value estimates: issues and alternatives. Ecol Econ 60:379–388

    Article  Google Scholar 

  • Stanley TD (2005) Beyond publication bias. J Econ Surv 19(3):309–345

    Article  Google Scholar 

  • Stanley TD (2008) Meta-regression methods for detecting and estimating empirical effect in the presence of publication selection. Oxford Bull Econ Stat 70:103–127

    Google Scholar 

  • Stanley TD, Doucouliagos H (2012) Meta-regression analysis in economics and business. Routledge, New York, NY

    Book  Google Scholar 

  • Stanley TD, Doucouliagos H, Giles M, Heckemeyer JH, Johnston RJ, Laroche P, Nelson JP, Paldam M, Poot J, Pugh G, Rosenberger RS, Rost K (2013) Meta-analysis of economics research reporting guidance. J Econ Surv 27:390–394

    Article  Google Scholar 

  • Stapler RW, Johnston RJ (2009) Meta-analysis, benefit transfer, and methodological covariates: implications for transfer error. Environ Resour Econ 42:227–246

    Article  Google Scholar 

  • Strand J, Carson R, Navrud S, Ortiz-Bobea A, Vincent JT (2017) Using the Delphi method to value protection of the Amazon rainforest. Ecol Econ 131:475–484

    Article  Google Scholar 

  • Tallis H, Polasky S (2009) Mapping and valuing ecosystem services as an approach for conservation and natural resource management. Ann N Y Acad Sci 1162:265–283

    Article  Google Scholar 

  • Treasury Board of Canada Secretariat (2007) Canadian cost-benefit analysis guide regulatory proposals. Her Majesty the Queen in Right of Canada

  • Tunçel T, Hammitt JK (2014) A new meta-analysis on the WTP/WTA disparity. J Environ Econ Manag 68(1):175–187

    Article  Google Scholar 

  • Turner MA (2018) Benefit-transfer and spatial equilibrium. Environ Resource Econ 69:575–590

    Article  Google Scholar 

  • U.S. Environmental Protection Agency (U.S. EPA) (2011) Economic and benefits analysis for proposed section 316(b) Existing Facilities Rule. EPA 821-R-11–002. Washington, DC, March 28

  • United States Environmental Protection Agency (U.S. EPA) (2010) Economic analysis of final water quality standards for nutrients for lakes and flowing waters in Florida. U.S. EPA, Office of Water, Office of Science and Technology, Washington, DC

  • United States Environmental Protection Agency (U.S. EPA) (2012) Economic analysis of proposed water quality standards for the State of Florida’s estuaries, coastal waters, and South Florida inland flowing waters. U.S. EPA, Office of Water, Office of Science and Technology, Washington, DC

  • United States Environmental Protection Agency (U.S. EPA) (2015) Benefit and cost analysis for the proposed effluent limitations guidelines and standards for the steam electric power generating point source category. U.S. EPA, Office of Water, Office of Science and Technology, Washington, DC, EPA-821-R-15–005

  • US EPA (Environmental Protection Agency) (2000) Guidance for preparing economic analyses. EPA 240-R-00–003. September. US EPA, Office of the Administrator, Washington, DC

  • US EPA (Environmental Protection Agency) (2014) Guidance for preparing economic analyses. National Center for Environmental Economics, Office of Policy, U.S. Environmental Protection Agency, Washington, DC

  • Vajjhala SP, John AM, Evans DA (2008) Determining the extent of market and extent of resource for stated preference survey design using mapping methods. RFF Environmental Economics Working Paper Series. no. 2008–09. Resources for the Future, Washington, DC

  • Van Houtven G, Pattanayak SK, Patil S, Depro B (2011) Benefits transfer of a third kind: an examination of structural benefits transfer. In: Whitehead J, Haab T, Huang J-C (eds) Preference Data for environmental evaluation: combining revealed and stated approaches. Routledge, New York

    Google Scholar 

  • Van Houtven G, Powers J, Pattanayak SK (2007) Valuing water quality improvements in the United States using meta-analysis: is the glass half-full or half-empty for national policy analysis? Resour Energy Econ 29:206–228

    Article  Google Scholar 

  • Van Houtven GL, Pattanayak SK, Usmani F, Yang J-C (2017) What are households willing to pay for improved water access? Results from a meta-analysis. Ecol Econ 136:126–135

    Article  Google Scholar 

  • Vedogbeton H, Johnston RJ (2020) Commodity consistent meta-analysis of wetland values: an illustration for coastal marsh habitat. Environ Resour Econ 75(4):835–865

    Article  Google Scholar 

  • Viscusi WK (2015) The role of publication selection bias in estimates of the value of a statistical life. Am J Health Econ 1:27–52

    Article  Google Scholar 

  • Viscusi WK, Aldy JE (2003) The value of a statistical life: a critical review of market estimate throughout the world. J Risk Uncertain 27(1):5–76

    Article  Google Scholar 

  • Vossler CA, Kerkvliet J (2003) A criterion validity test of the contingent valuation method: comparing hypothetical and actual voting behavior for a public referendum. J Environ Econ Manag 45:631–649

    Article  Google Scholar 

  • Vossler CA, Watson SB (2013) Understanding the consequences of consequentiality: testing the validity of stated preferences in the field. J Econ Behav Organ 86:137–147

    Article  Google Scholar 

  • Walsh JP, Wheeler WJ (2013) Water quality indices and benefit-cost analysis. J Benefit-Cost Anal 4:81–105

    Article  Google Scholar 

  • Wheeler WJ (2015) Benefit transfer for water quality regulatory rulemaking in the United States. In: Johnston RJ, Rolfe J, Rosenberger RS, Brouwer R (eds) Benefit transfer of environmental and resource values: a guide for researchers and practitioners. Springer, Dordrecht, The Netherlands, pp 101–115

    Chapter  Google Scholar 

  • Wilson MA, Hoehn JP (2006) Valuing environmental goods and services using benefit transfer: the state-of-the-art and science. Ecol Econ 60:335–342

    Article  Google Scholar 

  • World Bank (2020) Purchasing power parities and the size of world economies: Results from the 2017 International Comparison Program. World Bank. © World Bank, Washington, DC

  • Zandersen M, Termansen M, Jensen FS (2007) Testing benefits transfer of forest recreation values over a 20-year time horizon. Land Econ 83:412–440

    Article  Google Scholar 

  • Zerbe RO, Bellas AS (2006) A primer for benefit-cost analysis. Edward Elgar, Cheltenham, UK, Northampton, MA

    Google Scholar 

  • Zhai G (2011) International differences in willingness to pay for reduced risks due to risk representation: evidence from cross-country surveys in Northeast Asia. J Risk Res 14:1177–1190

    Article  Google Scholar 

  • Zhao J, Kling CL (2001) A new explanation for the WTP/WTA disparity. Econ Lett 73(3):293–300

    Article  Google Scholar 

  • Zhao M, Johnston RJ, Schultz ET (2013) What to value and how? Ecological indicator choices in stated preference valuation. Environ Resource Econ 56(1):3–25

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. George Perkins Marsh Institute, Clark University, 950 Main St, Worcester, MA, 01610, USA

    Robert J. Johnston

  2. Virginia Tech, Blacksburg, USA

    Kevin J. Boyle

  3. University of Santiago de Compostela, Santiago de Compostela, Spain

    Maria L. Loureiro

  4. School of Economics and Business, Norwegian University of Life Sciences, Ås, Norway

    Ståle Navrud

  5. School of Business and Law, CQUniversity, Rockhampton, Australia

    John Rolfe

Authors
  1. Robert J. Johnston
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kevin J. Boyle
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Maria L. Loureiro
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ståle Navrud
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. John Rolfe
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Robert J. Johnston.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

We express our thanks to Ian Bateman and two anonymous reviewers for helpful suggestions and to Lu Ann Pacenka for technical editing assistance. Ståle Navrud acknowledges support by the Research Council of Norway; projects no. 280393 (Valuechange), 255777 (Coast-benefit), and 267834 (MarES). Any remaining errors or omissions are the sole responsibility of the authors.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Johnston, R.J., Boyle, K.J., Loureiro, M.L. et al. Guidance to Enhance the Validity and Credibility of Environmental Benefit Transfers. Environ Resource Econ 79, 575–624 (2021). https://doi.org/10.1007/s10640-021-00574-w

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10640-021-00574-w

Keywords

Search

Navigation