Introduction

Motivation

  • Natural capital plays a critical role in sustaining human life and economic activities (Chiesura and De Groot 2003; Dasgupta 2021)

  • Natural capital values still poorly understood (Guerry et al. 2015; Costanza 2020)

  • Important to assess natural capital values to track nations’ wealth and guide policymakers (Brandon et al. 2021)

  • Values of stocks and flows of natural capital are highly spatially dependent (Addicott and Fenichel 2019)

  • Spatial complexities in the values of natural capital are not (fully) incorporated in most valuation approaches (Glenk et al. 2020)

  • Current studies do not include endowment (status quo) with natural capital in the valuation task

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 Question & Hypotheses

Research Question:
How do people value changes in the stock of natural capital, in the form of protected areas and high nature value farmland, across regions?

  • Hypothesis 1: People place significant value on natural capital in the form of protected areas and high nature value farmlands.

  • Hypothesis 2: The marginal value of natural capital decreases as endowment in- creases, suggesting diminishing returns.

  • Hypothesis 3: Use-related values of natural capital are higher than non-use-related values.

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:

\[U_i = f(\text{NC},\Phi) + \beta_c \cdot C +\beta_Y \cdot Y + \epsilon_i\]

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 \(\beta_{\text{NC}} \cdot \text{NC} + \beta_{\text{NC}_{\text{log}}} \cdot \log(\text{NC})\) \(\{\beta_{\text{NC}}, \beta_{\text{NC}_{\text{log}}}\}\)

Example: Quadratic model with interaction effects:

\[U = \beta_{NC} \cdot \text{NC} + \beta_{NC_{sq}} \cdot \text{NC}^2 + \beta_{NCX} \cdot \text{NC} \cdot X + \beta_{NCX_{sq}} \cdot \text{NC}^2 \cdot X + \beta_{C} \cdot C + \beta_{Y} \cdot Y + \epsilon\]

with: \(X\) capturing socio-demographic and spatial factors

Results

Mixed Logit Model

Results quadratic mxl model.
  Mean SD
Protected Areas NA 9.32 (0.65)*** -3.44 (0.14)***
Protected Areas NA Squared -0.06 (0.01)*** 0.16 (0.01)***
Protected Areas HA 15.64 (1.08)*** -2.72 (0.34)***
Protected Areas HA Squared 0.02 (0.02) 0.02 (0.01)**
Protected Areas FA 20.84 (1.18)*** 6.31 (0.19)***
Protected Areas FA Squared -0.11 (0.03)*** -0.05 (0.01)***
HNV NV 12.11 (0.55)*** -5.96 (0.14)***
HNV NV Squared -0.11 (0.01)*** 0.01 (0.01)
HNV V 15.53 (0.66)*** -5.53 (0.21)***
HNV V Squared -0.11 (0.01)*** -0.02 (0.00)***
ASC SQ -52.26 (0.45)*** -133.03 (0.62)***
Annual Payment -3.25 (0.03)*** -1.92 (0.04)***
Radius -1.03 (0.04)*** -1.40 (0.01)***
Scope high 0.44 (0.64) -9.79 (0.27)***
No Observations 142250  
No Respondents 14225  
Log Likelihood (Null) -98600.19  
Log Likelihood (Converged) -64239.65  
***p < 0.005; **p < 0.025; *p < 0.05 (one-sided). Robust standard errors in parentheses.

MXL Plots

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)

Outlook

First Insights

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

  • Use values higher than non-use values

  • Values differ substantially across space

Next Steps

  • Test different utility specifications and compare

  • Integrate income and distance decay in the WTP function and aggregation

  • Identify measure for substitutes and include it in WTP function

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 5, 10, 20, 40, 80, 60, 120, 150, 200, 250; euros The amount each household contributes annually to a fund dedicated to nature conservation efforts.

Results Conditional Logit

Model Fit of Conditional Logit Models

Model AIC BIC LLout
Quadratic Utility Function 215034.38 215154.74 -107505.19
Log Utility Function 215289.66 215359.87 -107637.83
Linear Utility Function 215162.56 215232.77 -107574.28
Box Cox Utility Function 215096.13 215216.49 -107536.07
Log-Linear Utility Function 215095.06 215215.42 -107535.53

Plot and Map WTP

Different Functional Forms: HNV Example

Compare WTP Estimates