About this presentation

  • A map with economic values of high nature value farmland and protected areas

  • A new valuation approach based on choice experiments

  • How spatially explicit valuation can improve policy decisions

The Research Project

  • Joint work within the ValuGaps Project since 2020

  • Several institutions and collaborators involved

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

Motivation

The Challenge

  • Agricultural policies balance protection of natural capital and agricultural production

  • Balancing out different policy goals requires an understanding of trade-offs

  • Optimal agricultural policies require an understanding of its costs and benefits

Monetizing non-market goods

Research gap

Research Contribution

  • Develop and apply spatially explicit valuation approach using stated preferences

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

  • Map distribution of willingness to pay (WTP) for natural capital (protected areas and high nature value farmland) across Germany

Hypotheses

🌱 Hypothesis 1
People place significant value on natural capital

📊 Hypothesis 2
The marginal value of natural capital decreases as endowment increases

🏕️ Hypothesis 3
Use-related values of natural capital are higher than non-use-related values

Survey Structure

The Choice Experiment

  • Referendum on proposed regional program by local municipalities

  • Increase in areas of high nature value (HNV) farmland and protected areas

  • Program financed by a mandatory annual payment per household

Example Choice Card

Example Choice Card

Example Choice Card

Endowment Natural Capital

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

Visualizing Results HNV

Aggregation of willingness to pay

  • Results are useful if aggregated to spatial scales

  • Each raster cell has a unique value

  • Value depends on endowment and the number and characteristics of beneficiaries

Steps to Aggregate

  1. Calculate the endowment
  2. Compute willingness to pay per person
  3. Multiply with population in the cell
  4. For each cell, identify affected cells
  5. Sum up willingness to pay for associated cells

High Nature Value Farmland

Further analyses

  • Integrate income and distance in the WTP function

  • Identify measure for substitutes and include it in WTP function

  • Incorporate fairness concerns and protest responses

Conclusions

  • 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

Potential policy applications

  • Design of Agri-Environmental Schemes

  • Justification of protected area expansion

  • Guide land-use planning decisions

  • Cost benefit analysis of conservation policies

  • Cost effectiveness assessment

Thank you very much

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.
Buschke, Falko T., Claudia Capitani, El Hadji Sow, Yvonne Khaemba, Beth A. Kaplin, Andrew Skowno, David Chiawo, et al. 2023. “Make Global Biodiversity Information Useful to National Decision-Makers.” Nature Ecology & Evolution 7: 1953–56. https://doi.org/10.1038/s41559-023-02226-2.
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.”
European Commission. 2019. “The European Green Deal.” https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:52019DC0640.
———. 2020. “EU Biodiversity Strategy for 2030: Bringing Nature Back into Our Lives.” https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:52020DC0380.
European Union. 2021. “Regulation (EU) 2021/2115: CAP Strategic Plans Regulation.” https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32021R2115.
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.
Johnston, Robert J., and Dana Marie Bauer. 2020. “Using Meta-Analysis for Large-Scale Ecosystem Service Valuation: Progress, Prospects, and Challenges.” Agricultural and Resource Economics Review 49 (Special Issue 1): 23–63. https://doi.org/10.1017/age.2019.22.
Newbold, Tim, Lawrence N. Hudson, Andrew P. Arnell, Sara Contu, Adriana De Palma, Simon Ferrier, Samantha L. L. Hill, et al. 2015. “Global Effects of Land Use on Local Terrestrial Biodiversity.” Nature 520 (7545): 45–50. https://doi.org/10.1038/nature14324.
United Nations. 1992. “Convention on Biological Diversity.” https://www.cbd.int/doc/legal/cbd-en.pdf.
———. 1994. “United Nations Convention to Combat Desertification.” https://www.unccd.int/convention/about-convention.
———. 2015a. “Paris Agreement Under the United Nations Framework Convention on Climate Change.” https://unfccc.int/sites/default/files/english_paris_agreement.pdf.
———. 2015b. “Transforming Our World: The 2030 Agenda for Sustainable Development.” https://sdgs.un.org/2030agenda.

Sources from Logos

Teaching

Introductory Lectures

  • Teaching economic theory exemplified by different utility concepts

  • The limits of economic valuation

  • Survey design

  • Visualizing and communicating results

  • Understanding the steps from survey design to a spatially explicit value database

Seminar on valuation methods

  • Introduce ecosystem services and natural capital in agriculture

  • Methodological overview of valuation techniques

  • Use ValuGaps data to explore different valuation methods

  • Group work with different valuation methods

  • Learn how to plot values on a map and combine with other layers

Seminar on Environmental Economics & Policy

  • Discuss current agricultural policies and biodiversity goals

  • Explore current weaknesses and gaps

  • Introduce valuation methods and how they can improve decision-making

Case Study on Agri Environmental Schemes

  • Design an agri-environmental scheme to promote biodiversity

  • Use valuation methods to estimate costs and benefits

  • Combine citizens willingness to pay with compensation payments to farmers

Methodical and theoretical lectures

  • When discussing economic valuation, use the data for exercises and examples

  • Use the results to discuss different agricultural policies

  • Discussion on the use and abuse of economic valuation

Valuation Methods as Learning Tools

  • Market & cost–benefit analysis: compare priced vs. unpriced benefits
  • Contingent valuation: survey willingness to pay for nature
  • Hedonic & travel cost: link property values and recreation to ecosystems

High Nature Value Farmland & Protected Areas

  • Case studies: traditional farming & Natura 2000 sites
  • Role-play: farmers, policymakers, conservationists
  • Linking valuation results to EU and local policies

Student Competencies

  • Critical thinking: questioning assumptions & trade-offs
  • Quantitative skills: applying valuation techniques
  • Policy & ethics: limits of monetizing nature

Appendix

EU Biodiversity Strategy for 2030

  • 10% farmland in high-diversity features (hedgerows, ponds, flower strips)
  • 25% of EU farmland organic by 2030
  • 50% reduction in pesticide use by 2030

These measures integrate habitats into farmland, protect pollinators, and enhance soil and water quality (European Commission 2020).

European Green Deal

  • Farm to Fork nutrient management: 50% nutrient loss reduction, 20% less fertiliser use
  • Agroecology & carbon farming: legumes, agroforestry, permanent pastures
  • Sustainable livestock systems: reduce antimicrobials, better manure management

Supports systemic agricultural change and strengthens natural capital in farming landscapes (European Commission 2019).

Common Agricultural Policy (CAP)

  • Eco-schemes: crop diversification, cover crops, soil cover
  • Permanent grasslands: protection of high-nature-value pastures
  • Agri-environment payments: hedgerows, tree lines, buffer strips

Provides the financial mechanisms to deliver biodiversity and ecosystem service benefits on farms (European Union 2021).

International Agreements

  • Convention on Biological Diversity (CBD)
    – Promotes sustainable agriculture practices that conserve biodiversity.

  • Paris Agreement (UNFCCC)
    – Encourages climate-smart agriculture and soil carbon sequestration.

  • UN Convention to Combat Desertification (UNCCD)
    – Focus on land degradation neutrality and sustainable land management.

These treaties provide global governance frameworks guiding national and EU agricultural policies (United Nations 1992, 2015a, 1994).

Sustainable Development Goals (SDGs)

  • SDG 2: Zero Hunger – Sustainable food production and resilient agricultural practices.
  • SDG 12: Responsible Consumption and Production – Efficient use of natural resources in farming.
  • SDG 15: Life on Land – Protect, restore, and sustainably use terrestrial ecosystems.

The SDGs link natural capital protection directly to agricultural sustainability and global equity (United Nations 2015b).

Study Design: Spatially Explicit Choice Experiment

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

  • 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

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

  • 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

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.

Sample

Variable Mean/Share Median SD Min Max Germany
Age 51.41 52.00 16.08 19.00 93.00 44.70
Share of Females 0.51 - - - - 0.51
Higher Education 0.35 - - - - 0.33
Net Household Monthly Income 3192 3250 1464 250 5500 3650
Share with children 0.56 - - - - -
Life Satisfaction 6.66 7 2.12 0 10 -
N 13964 - - - - -

Spatially Explicit Choice Experiment

  • Coupled with questions on socio-demographics, well-being, nature-relatedness and political preference

  • Several split samples to account for different research questions

    • Distance

    • Implementation timing

    • Equity considerations

    • Embedding and scope effects

Strengths of our approach:

  1. Incorporate respondent’s endowment in valuation task
  2. Increase realism & relevance
  3. Enhance understanding of proposed changes by visualization
  4. Clear and clean definition of good(s) to be valued

Results Conditional Logit

Model Fit of Conditional Logit Models

Model AIC BIC LLout
Quadratic Utility Function 77188.62 77296.64 -38582.31
Log Utility Function 77308.98 77371.99 -38647.49
Linear Utility Function 77268.21 77331.22 -38627.11
Box Cox Utility Function 77231.68 77339.7 -38603.84
Log-Linear Utility Function 77254.71 77362.73 -38615.35

Key Results

  • People place significant value on natural capital

  • Use values are significantly higher than non-use values

  • Marginal value of natural capital decreases if endowment increases

Plot and Map WTP

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.

Different Functional Forms: HNV Example

Compare WTP Estimates

Visualizing Results PA

Aggregation Details

All steps

A stylized example

Focus on one cell

People and extent of the market

WTP of one Person

WTP of more persons

WTP of more persons

WTP of more persons

WTP of more persons

Aggregated willingness to pay