ValuGaps Grassland Survey

Nino Cavallaro, Maxi Föhl, Johannes Lange, Julian Sagebiel et al.*

German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig

Leipzig University

2025-03-26

Introduction

Motivation

Natural capital, which includes ecosystems, biodiversity, and other natural resources, 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 with natural capital in the valuation task

Research Contribution

Develop and apply spatially explicit valuation approach accounting for endowment with natural capital using stated preferences
Improve understanding of heterogeneity of natural capital values across space and groups
Assess differences in values between use and non-use related natural capital values
Map distribution of demand for natural capital (protected areas and high nature value farmland) across Germany

Research Question & Hypotheses

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 value of natural capital is significantly influenced by socio- demographic characteristics and spatially explicit factors, leading to variations in values across different groups and regions.
Hypothesis 3: The marginal value of natural capital decreases as endowment in- creases, suggesting diminishing returns.
Hypothesis 4: Use-related values of natural capital are higher than non-use-related values.

Methodological Research Questions

Does the scope (i.e. regional extent) of a measure to protect natural capital impact the value (scope and embedding effects)?
Are elicited values constant over different methods (choice experiment, travel cost method, life satisfaction)?
How do the distributional consequences of the payment vehicle impact choices and values?
How do different time horizons of the payment period impact choices and values?

Survey Structure

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

Study Design: Spatially Explicit Choice Experiment

Online survey with N = 15,000 respondents all over Germany
Setting: referendum for proposed regional program by local municipalities to change land use in favor of environment and biodiversity
Include knowledge questions and feedback on goods to be valued to enhance information processing and recall
Coupled with questions on socio-demographics, well-being, nature-relatedness and political preference

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.

Study Design: Example Choice Card

Strengths of our spatially explicit valuation approach:

Incorporate respondent’s endowment in valuation task
Increase realism & relevance as all proposed changes are feasible and relatively close in distance to respondents’ homes
Enhance understanding of proposed changes by visualization
Clear and clean definition of good(s) to be valued
Large sample size with N = 15,000 enables extensive analysis of spatial and socio-demographic variation

Sample

Currently still in the process of data collection, current sample N = 6,000 + (including pre-test data)
Current progress: https://ninocav.shinyapps.io/VG_survey_monitor/

Variable	Mean/Share	Median	SD	Min	Max	Germany
Age	49.86	50.00	16.33	19.00	91.00	44.70
Share of Females	0.44	-	-	-	-	0.51
Higher Education	0.35	-	-	-	-	0.33
Net Household Monthly Income	3199	3250	1460	250	5500	3650
Share with children	0.55	-	-	-	-	-
Life Satisfaction	6.7	7	2.11	0	10	-
N	6807	-	-	-	-	-

Endowment Natural Capital

NSG and HNV Distribution

Political Preference

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

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

Plot and Map WTP

Different Functional Forms: HNV Example

Mixed Logit Model

Results quadratic mxl model.
	Mean	SD
Protected Areas NA	12.67 (0.77)^***	0.48 (0.57)
Protected Areas NA Squared	-0.14 (0.03)^***	-0.15 (0.03)^***
Protected Areas HA	22.83 (0.83)^***	3.06 (0.23)^***
Protected Areas HA Squared	-0.18 (0.06)^***	-0.13 (0.02)^***
Protected Areas FA	26.43 (1.07)^***	-10.27 (0.22)^***
Protected Areas FA Squared	-0.26 (0.02)^***	0.17 (0.00)^***
HNV NV	12.44 (1.80)^***	5.95 (0.32)^***
HNV NV Squared	-0.06 (0.05)	-0.07 (0.03)^**
HNV V	15.38 (1.20)^***	-8.13 (0.21)^***
HNV V Squared	-0.02 (0.03)	-0.09 (0.01)^***
ASC SQ	-63.88 (0.58)^***	119.25 (0.60)^***
Annual Payment	-3.43 (0.04)^***	2.10 (0.06)^***
Radius	-1.63 (0.02)^***	-4.37 (0.04)^***
Scope high	10.69 (0.98)^***	-99.16 (0.37)^***
No Observations	64220
No Respondents	6422
Log Likelihood (Null)	-44513.91
Log Likelihood (Converged)	-30238.45
^*p < 0.005; ^p < 0.025; ^*p < 0.05 (one-sided). Robust standard errors in parentheses.

Compare WTP Estimates

MXL Plots

First Insights

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
Marginal value of natural capital depends on use and non-use

Next Steps

Test different utility specifications and compare
Integrate income and distance in the WTP function
Identify measure for substitutes and include it in WTP function
Compute WTP values on raster grid and aggregate with population density

Aggregation

Aggregtion is not straightforward as WTP depends on the area where the change takes place
Each raster cell has a unique value, depending on the status quo endowment and the number and characteristics of beneficiaries
Advantage: spatially explicit value estimates per rastercell.
Allows for a very detailed post estimation analysis.

Aggregation approaches: Administrative Unit

Aggregate per administrative unit
Easy to do
Oversimplified with strong assumptions of equal land distributions.

WTP Map for Protected Areas

Mean WTP for 1000 ha increase in PA for all German counties

Aggregation approaches: Cell value

Decide the cell size for which a value is required.
Each cell contains 1ha cells which are either in good status (1) or in bad status (0)
For example 0 = Normal farmland, 1 = HNV farmland

A stylized example

Focus on one cell

People and extent of the market

WTP of one Person

WTP of more persons

Actual aggregation

In reality, we do not know exactly where people live
We use data on extrapolated population density on 250x250 m grid.
For each cell, we calculate the status quo endowment, the estimated WTP per person and multiply it with the population.

Density Map

Outlook

Publication strategy

Data Publication: Preparing submission to Scientific Data
A Novel Approach to Determining Spatially Explicit Values of Natural Capital: Submitted to EAERE
The impact of nature relatedness (NR) and health/wellbeing on the economic value of natural capital: Interdisciplinary paper with Marie and Kevin
Estimate recreation demand and economic use value of recreation in local natural environments using the travel cost method
Left-right bias and ordering effects in choice experiments
Comparison of methods to estimate the implicit price of natural capital: Choice experiments, travel cost and life satisfaction

Qualitative Analysis

Most Frequent Stems and Word Cloud

Following Ferrario and Stantcheva (2022)

Post-DCE Open-Ended Question

Top 20 Most Frequent Stems with English Translations
Rank	Stem	English	Count
1	geld	money	158
2	natur	nature	151
3	flächen	areas/land	117
4	bezahlen	pay	86
5	naturschutz	nature conservation	71
6	maßnahm	measures	63
7	haushalt	household	57
8	sinnvoll	reasonable/sensible	55
9	leisten	afford	53
10	nutzen	benefit	51
11	artenvielfalt	biodiversity	49
12	sehen	see	48
13	landschaftsveränderung	landscape change	47
14	preis	price	44
15	finanziell	financial	43
16	beitragen	contribute	41
17	finanzieren	fund	40
18	meinung	opinion	39
19	Staat	state/government	39
20	wohnort	place of residence	39

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.”

Ferrario, Beatrice, and Stefanie Stantcheva. 2022. “Eliciting People’s First-Order Concerns: Text Analysis of Open-Ended Survey Questions.” In AEA Papers and Proceedings, 112:163–69. American Economic Association 2014 Broadway, Suite 305, Nashville, TN 37203.

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.