Introduction

Motivation

Research Contribution

  • Develop and apply spatially explicit valuation approach accounting for endowment with natural capital using a discrete choice experiment

  • Use GIS data and real-time computation via API to ensure that all proposed changes in the choice scenario are feasible

  • Improve understanding of heterogeneity of natural capital values across space and groups

  • Map distribution of demand for natural capital (protected areas and high nature value farmland) across Germany

Research Questions & Hypotheses

Research Questions:

  1. How do people value changes in the stock of natural capital, in the form of protected areas and high nature value farmland, across space?

  2. How can we aggregate willingness to pay (WTP) values to provide spatially explicit natural capital values?

  • H1: People place significant value on natural capital in the form of protected areas and high nature value farmlands.

  • H2: Marginal diminishing returns: The marginal value of natural capital decreases as endowment increases.

  • H3: Use-related values of natural capital are higher than non-use-related values.

  • H4: Distance Decay: The marginal value of natural capital decreases as distance to it increases.

Survey Structure

Survey Structure

Spatially Explicit Choice Experiment

  • Coupling discrete choice experiment (DCE) with GIS data displayed on interactive leaflet-based maps

  • Referendum on proposed regional program by local municipalities

  • Natural capital related attributes: protected areas (PA) & high nature value farmland (HNV)

  • Show respondents status quo endowment around place of residence with natural capital + proposed changes

  • Use CORINE land cover data and R algorithm to ensure that all proposed changes are feasible

  • Vary distance of proposed changes (for both), accessibility (for PA), and visibility from path and roads (for HNV) to partly disentangle use and non-use values

Example Choice Card

Example Choice Card

Example Choice Card

Sample

Endowment Natural Capital

Methodology

Methodology

General utility specification:

\[U_i = -\beta_c \cdot \bigl[\sum_{NC} \bigl((1 + \delta_{NC} \cdot log(\text{D})+ \gamma \cdot log(\text{I})) \cdot f(\text{NC},\Phi)\bigr) +\beta_Y \cdot Y - C \bigr] + \epsilon_i\]

with: \(NC = \{\text{PA}_{a}, \text{HNV}_{v}\}\) and \(a=\{1, 2, 3\}\) and \(v=\{1, 2\}\)

Different functional forms:

Function Type Function \(f(\text{NC},\Phi)\) Parameters (‘\(\Phi\)‘)
Linear \(\beta_{\text{NC}} \cdot \text{NC}\) \(\{\beta_{\text{NC}}\}\)
Quadratic Utility \(\beta_{\text{NC}} \cdot \text{NC} + \beta_{\text{NC}_{\text{sq}}} \cdot \text{NC}^2\) \(\{\beta_{\text{NC}}, \beta_{\text{NC}_{\text{sq}}}\}\)
Logarithmic \(\beta_{\text{NC}} \cdot \log(\text{NC})\) \(\{\beta_{\text{NC}}\}\)
Box-Cox \(\beta_{\text{NC}} \cdot \frac{\text{NC}^\lambda - 1}{\lambda}\) \(\{\beta_{\text{NC}}, \lambda\}\)
Log-Linear \(\beta_{\text{NC}} \cdot \text{NC} + \beta_{\text{NC}_{\text{log}}} \cdot \log(\text{NC})\) \(\{\beta_{\text{NC}}, \beta_{\text{NC}_{\text{log}}}\}\)

Results

Mixed Logit Model

Mean SD Distance
Protected Areas NA 11.34 (1.03)*** -8.51 (0.78)*** -0.37 (0.22)*
Protected Areas NA Squared -0.08 (0.03)*** 0.07 (0.03)**
Protected Areas HA 16.99 (0.80)*** -1.22 (0.24)*** -0.28 (0.14)**
Protected Areas HA Squared 0.03 (0.03) -0.18 (0.02)***
Protected Areas FA 21.76 (0.74)*** -4.82 (0.40)*** -0.29 (0.10)***
Protected Areas FA Squared -0.09 (0.02)*** 0.30 (0.01)***
HNV NV 12.21 (0.44)*** -8.46 (0.28)*** -0.36 (0.07)***
HNV NV Squared -0.09 (0.01)*** -0.07 (0.01)***
HNV V 15.60 (0.68)*** -4.31 (0.27)*** -0.25 (0.12)**
HNV V Squared -0.10 (0.01)*** -0.02 (0.01)**
Annual Payment -3.25 (0.03)*** -1.97 (0.04)***
Scope high 6.46 (0.89)*** -79.50 (0.26)***
ASC SQ -50.57 (0.63)*** 121.13 (0.40)***
ASC Distance Interaction 14.85 (2.10)***
ASC Income Interaction -21.22 (0.36)***
Income Scale Factor 0.24 (0.02)***
No Observations 131,440
No Respondents 13,144
Log Likelihood (Null) -91,107.27
Log Likelihood (Converged) -59,821.95
*** p < 0.005; ** p < 0.025; * p < 0.05. Robust standard errors in parentheses.

Estimated WTP Functions: Endowment

Estimated WTP Functions: Distance

  • Use split sample variation in maximum distance of new areas

  • \(\text{WTP}_{PA_i} = (1 + \delta_{PA_i} \cdot log(\text{D}))\left(\beta_{\text{PA}_i} + 2 \cdot \beta_{\text{PA}_{i,sq}} \cdot \text{PA}_i\right)\)

Estimated WTP Functions: Income

  • Use GIS data on available income to incorporate differences in income

  • \(\text{WTP}_{PA} = (1 + \delta_{PA} \cdot log(\text{D}) + \gamma \cdot log(\text{I}))\left(\beta_{\text{PA}} + 2 \cdot \beta_{\text{PA}_{sq}} \cdot \text{PA}\right)\)

Aggregation

Aggregation of willigness to pay values

  • Results are useful if aggregated to spatial scales

  • Each raster cell has a unique value

  • Value depends on status quo endowment and the number and characteristics of beneficiaries close to the cell

Steps to Aggregate WTP values

  1. Calculate the status quo endowment

  2. Compute estimated marginal WTP per person

  3. Multiply it with the population in the cell

  4. Compute for each cell all other cells where people would benefit from the change

  5. Aggregate WTP by summing up associated cells

Example: Protected Areas (No Access)

Conclusion

Summary of Main Results

  • Willingness to pay for natural capital is positive but decreases with increasing endowment and distance

  • Use values higher than non-use values

  • Values differ substantially across space

Policy Implications

  • Implementation of biodiversity policies should incorporate spatial heterogeneities

  • Endowment, income and number of beneficiaries are important drivers of aggregated values

Making Spatial Preferences Actionable for Policy

Improve communication of spatially explicit welfare measures:

  1. Making results more accessible to policymakers, e.g. by interactive visualisations

  2. Enhance credibility and communicate limitations

  3. Incorporate justice concerns

Thanks for Listening

  • Joint work within the ValuGaps Team since 2020

  • Several institutions and collaborators involved

  • Visit https://valugaps.de/en/ for more information

References

Addicott, Ethan T, and Eli P Fenichel. 2019. “Spatial Aggregation and the Value of Natural Capital.” Journal of Environmental Economics and Management 95: 118–32.
Brandon, Carter, Katrina Brandon, Alison Fairbrass, and Rachel Neugarten. 2021. “Integrating Natural Capital into National Accounts: Three Decades of Promise and Challenge.” Review of Environmental Economics and Policy 15 (1): 134–53.
Chiesura, Anna, and Rudolf De Groot. 2003. “Critical Natural Capital: A Socio-Cultural Perspective.” Ecological Economics 44 (2-3): 219–31.
Costanza, Robert. 2020. “Valuing Natural Capital and Ecosystem Services Toward the Goals of Efficiency, Fairness, and Sustainability.” Ecosystem Services 43: 101096.
Dasgupta, Sir Partha. 2021. “The Economics of Biodiversity the Dasgupta Review Abridged Version.”
Glenk, Klaus, Robert J Johnston, Jürgen Meyerhoff, and Julian Sagebiel. 2020. “Spatial Dimensions of Stated Preference Valuation in Environmental and Resource Economics: Methods, Trends and Challenges.” Environmental and Resource Economics 75: 215–42.
Guerry, Anne D, Stephen Polasky, Jane Lubchenco, Rebecca Chaplin-Kramer, Gretchen C Daily, Robert Griffin, Mary Ruckelshaus, et al. 2015. “Natural Capital and Ecosystem Services Informing Decisions: From Promise to Practice.” Proceedings of the National Academy of Sciences 112 (24): 7348–55.

Appendix

Attributes and levels in the DCE

Attribute Levels Description
Size of protected areas Vector A*: Status quo, +100, +200, +300, +500, +800; hectares The total area designated as protected area. Levels indicate the expansion in hectares from the current status.
High nature value farmland Vector B*: Status quo, +200, +400, +600, +1000, +1600; hectares The total area of high nature value farmland. Levels indicate the expansion in hectares from the current status.
Accessibility of new protected areas Not accessible, Half accessible, Fully accessible The extent to which the public can access newly designated protected areas, ranging from no access to full access.
Visibility of new high nature value farmland Barely visible, Clearly visible Indicates how visible the new areas of high nature value farmland are from public roads or paths.
Annual payment into a nature conservation fund , 10, 20, 40, 80, 60, 120, 150, 200, 250; euros The amount each household contributes annually to a fund dedicated to nature conservation efforts.

*Note: For the size of protected areas and high nature value farmland the attribute levels are either vector A or vector B for a respondent for both attributes.

Results Functional Forms

Model Fit of Mixed logit models

Model AIC BIC LLout
Quadratic Utility Function 128533.25 128809.48 -64238.63
Log Utility Function 128773.39 128950.97 -64368.7
Linear Utility Function 128574.99 128752.57 -64269.5
Box Cox Utility Function 128548.7 128775.6 -64251.35
Log-Linear Utility Function 128554.29 128830.52 -64249.15
Cubic Utility Function 128565.43 128940.32 -64244.72

Plot and Map WTP

Different Functional Forms: HNV Example

Compare WTP Estimates