Min. 1st Qu. Median Mean 3rd Qu. Max.
5.084 17.125 25.165 36.677 41.627 398.891
Appendix of Spatial Explicit Economic Values of Natural Capital in Germany: Pretest Descriptive Results
Meta data
Device types/Mobile device
Quality checks
Randomizations
uhh dce_version equity arm block radius
uhh NA 0.90372002 0.6073494 0.4938393 0.44618093 0.48464898
dce_version 0.9037200 NA NaN 0.3190113 0.66204702 0.58184243
equity 0.6073494 NaN NA 0.7641136 0.90877061 0.68726914
arm 0.4938393 0.31901132 0.7641136 NA 0.67388995 0.52081681
block 0.4461809 0.66204702 0.9087706 0.6738899 NA 0.32678003
radius 0.4846490 0.58184243 0.6872691 0.5208168 0.32678003 NA
order 0.1099973 0.07124681 0.7626644 0.6676202 0.04314137 0.07655792
order
uhh 0.10999735
dce_version 0.07124681
equity 0.76266437
arm 0.66762022
block 0.04314137
radius 0.07655792
order NA
Socio-demografics
# A tibble: 7 × 3
educ n percentage
<fct> <int> <dbl>
1 Hochschulabschluss (Universität, FH) 139 32.8
2 Mittlere Reife (Realschulabschluss) 132 31.1
3 Abitur 88 20.8
4 Hauptschulabschluss 53 12.5
5 Sonstiges 6 1.42
6 Von der Schule abgegangen ohne Schulabschluss 5 1.18
7 Will ich nicht beantworten 1 0.236
Attention questions
Access of Additional Information
1
66
1
62
NSG and HNV Distribution
Spatial Distribution
Choice Experiment
Choice Pattern Plots
200 300 400 500 600 700 800 900 1000 1100 1200 1300 1400 1600 1800 2000
5 22 0 22 42 42 42 43 0 106 43 21 21 0 39 42 66
10 22 42 107 22 61 0 42 42 43 43 40 21 20 0 22 20
40 0 0 66 42 44 64 43 42 21 85 22 21 44 21 20 45
80 22 43 22 0 107 0 81 44 42 43 0 42 20 22 42 21
120 21 65 63 21 104 0 60 42 64 0 22 43 0 0 0 62
150 0 42 42 0 45 107 23 65 44 43 0 66 41 0 22 21
200 0 0 0 0 0 0 41 0 0 0 58 0 20 22 19 0
250 0 0 22 0 44 0 20 0 44 0 20 0 21 23 22 21
2200 2600 3200
5 44 0 0
10 45 41 0
40 38 0 0
80 0 0 19
120 0 0 22
150 20 86 0
200 18 0 88
250 22 43 0
arm
equity 5 10 20 indefinitely
No Info 0.4125000 0.4052632 0.3722222 0.4588235
All same 0.3352941 0.6000000 0.3812500 0.1500000
income tax 0.5391304 0.4368421 0.6000000 0.5133333
Protester
Utility Functions
Quadratic
\[ \begin{equation} U = \beta_{NC} \cdot \text{NC} + \beta_{NC_{sq}} \cdot \text{NC}^2 +\beta_{C} \cdot C + \beta_{Y} \cdot Y + \epsilon \label{mxl_base2} \end{equation} \]
with: \(NC = \{\text{PA}_{a}, \text{HNV}_{v}\}\) and \(a=\{1, 2, 3\}\) and \(v=\{1, 2\}\)
Linear Terms
\[ \begin{equation} U = \beta_{NC} \cdot \text{NC} + \beta_{C} \cdot C + \beta_{Y} \cdot Y + \epsilon \label{linear_model} \end{equation} \]
Logarithmic Terms
\[ \begin{equation} U = \beta_{NC} \cdot \log(\text{NC}) + \beta_{C} \cdot C + \beta_{Y} \cdot Y + \epsilon \label{log_nc_model} \end{equation} \]
Box-cox
\[ \begin{equation} U = \beta_{NC} \cdot \frac{\text{NC}^\lambda - 1}{\lambda} + \beta_{C} \cdot C + \beta_{Y} \cdot Y + \epsilon \quad \text{for } \lambda \neq 0 \label{box_cox_model} \end{equation} \]
Log-Linear
\[ \begin{equation} U = \beta_{NC} \cdot \text{NC} + \beta_{NC_{log}} \cdot \log(\text{NC}) + \beta_{C} \cdot C + \beta_{Y} \cdot Y + \epsilon \label{log_linear_model} \end{equation} \]
Conditional Logit Models
Estimate | s.e. | t.rat.(0) | Rob.s.e. | Rob.t.rat.(0) | |
beta_pa | 4.47 | 1.87 | 2.39 | 2.48 | 1.80 |
beta_hnv | 5.48 | 1.54 | 3.55 | 2.19 | 2.50 |
beta_pa_sq | -0.01 | 0.01 | -1.90 | 0.01 | -1.30 |
beta_hnv_sq | -0.01 | 0.005 | -1.42 | 0.01 | -0.79 |
pa_half_access | 8.47 | 2.16 | 3.92 | 2.62 | 3.23 |
pa_full_access | 5.46 | 2.02 | 2.71 | 2.58 | 2.11 |
pa_half_access_sq | -0.03 | 0.01 | -3.64 | 0.01 | -2.81 |
pa_full_access_sq | -0.02 | 0.01 | -2.32 | 0.01 | -1.75 |
hnv_visible | 6.19 | 1.64 | 3.76 | 2.15 | 2.89 |
hnv_visible_sq | -0.01 | 0.01 | -1.70 | 0.01 | -1.12 |
beta_cost | -0.01 | 0.0005 | -16.33 | 0.001 | -11.45 |
ASC_sq | -20.88 | 8.37 | -2.49 | 14.27 | -1.46 |
Estimate | s.e. | t.rat.(0) | Rob.s.e. | Rob.t.rat.(0) | |
beta_pa | 91.58 | 41.04 | 2.23 | 58.28 | 1.57 |
beta_hnv | 151.11 | 50.54 | 2.99 | 96.00 | 1.57 |
pa_half_access | 162.98 | 42.02 | 3.88 | 65.34 | 2.49 |
pa_full_access | 134.35 | 41.96 | 3.20 | 63.68 | 2.11 |
hnv_visible | 164.64 | 55.16 | 2.98 | 87.46 | 1.88 |
beta_cost | -0.01 | 0.0005 | -16.28 | 0.001 | -11.44 |
ASC_sq | -27.19 | 6.84 | -3.97 | 13.43 | -2.02 |
Estimate | s.e. | t.rat.(0) | Rob.s.e. | Rob.t.rat.(0) | |
beta_pa | 1.58 | 1.19 | 1.32 | 1.42 | 1.11 |
beta_hnv | 3.95 | 1.10 | 3.58 | 1.26 | 3.14 |
pa_half_access | 2.27 | 1.36 | 1.67 | 1.33 | 1.71 |
pa_full_access | 1.59 | 1.30 | 1.23 | 1.45 | 1.10 |
hnv_visible | 4.23 | 1.21 | 3.51 | 1.29 | 3.28 |
beta_cost | -0.01 | 0.0005 | -16.23 | 0.001 | -11.36 |
ASC_sq | -22.62 | 8.39 | -2.70 | 14.33 | -1.58 |
Estimate | s.e. | t.rat.(0) | Rob.s.e. | Rob.t.rat.(0) | |
beta_pa | 22.21 | 37.71 | 0.59 | 47.28 | 0.47 |
beta_hnv | 22.32 | 20.81 | 1.07 | 30.64 | 0.73 |
pa_half_access | 135.73 | 127.26 | 1.07 | 190.58 | 0.71 |
pa_full_access | 376.79 | 552.50 | 0.68 | 992.44 | 0.38 |
hnv_visible | 24.38 | 26.05 | 0.94 | 34.33 | 0.71 |
beta_cost | -0.01 | 0.0005 | -16.44 | 0.001 | -11.66 |
ASC_sq | -18.09 | 8.06 | -2.24 | 13.98 | -1.29 |
lambda_pa | 0.43 | 0.48 | 0.90 | 0.57 | 0.74 |
lambda_hnv | 0.61 | 0.23 | 2.69 | 0.31 | 1.94 |
lambda_pa_half | 0.04 | 0.32 | 0.13 | 0.44 | 0.09 |
lambda_pa_full | -0.37 | 0.56 | -0.66 | 0.97 | -0.38 |
lambda_hnv_vis | 0.60 | 0.26 | 2.27 | 0.33 | 1.82 |
Estimate | s.e. | t.rat.(0) | Rob.s.e. | Rob.t.rat.(0) | |
beta_pa | 0.66 | 1.49 | 0.44 | 1.88 | 0.35 |
beta_hnv | 2.96 | 1.46 | 2.02 | 2.16 | 1.37 |
beta_pa_sq | 60.50 | 52.07 | 1.16 | 70.50 | 0.86 |
beta_hnv_sq | 70.81 | 68.41 | 1.04 | 130.31 | 0.54 |
pa_half_access | -0.91 | 1.69 | -0.54 | 1.93 | -0.47 |
pa_full_access | -1.08 | 1.64 | -0.66 | 2.00 | -0.54 |
pa_half_access_sq | 169.25 | 53.24 | 3.18 | 82.09 | 2.06 |
pa_full_access_sq | 152.09 | 54.33 | 2.80 | 78.98 | 1.93 |
hnv_visible | 2.90 | 1.67 | 1.73 | 2.12 | 1.37 |
hnv_visible_sq | 93.38 | 78.50 | 1.19 | 120.12 | 0.78 |
beta_cost | -0.01 | 0.0005 | -16.35 | 0.001 | -11.57 |
ASC_sq | -20.25 | 8.38 | -2.42 | 14.34 | -1.41 |
Mixed Logit Models
Estimate | s.e. | t.rat.(0) | Rob.s.e. | Rob.t.rat.(0) | |
beta_pa | 31.929 | 3.377 | 9.454 | 1.537 | 20.774 |
beta_hnv | 24.244 | 3.445 | 7.037 | 1.640 | 14.787 |
beta_pa_sq | -0.399 | 0.110 | -3.640 | 0.052 | -7.625 |
beta_hnv_sq | -0.056 | 0.106 | -0.525 | 0.037 | -1.510 |
pa_half_access | 6.864 | 3.127 | 2.195 | 1.532 | 4.480 |
pa_full_access | 1.063 | 0.322 | 3.301 | 0.178 | 5.977 |
hnv_visible | 1.163 | 2.100 | 0.554 | 0.859 | 1.355 |
beta_cost | -3.395 | 0.168 | -20.172 | 0.171 | -19.810 |
ASC_sq | -27.274 | 1.995 | -13.668 | 1.010 | -26.999 |
sig_pa | -11.753 | 1.457 | -8.064 | 0.586 | -20.071 |
sig_hnv | 6.739 | 0.924 | 7.297 | 0.272 | 24.755 |
sig_pa_sq | -1.139 | 0.053 | -21.566 | 0.014 | -79.033 |
sig_hnv_sq | 1.131 | 0.060 | 18.753 | 0.016 | 69.024 |
sig_pa_half_access | 26.670 | 3.071 | 8.685 | 1.173 | 22.746 |
sig_pa_full_access | 1.949 | 0.211 | 9.259 | 0.083 | 23.493 |
sig_hnv_visible | -1.906 | 2.520 | -0.756 | 0.557 | -3.419 |
sig_cost | -2.236 | 0.285 | -7.847 | 0.287 | -7.780 |
sig_ASC_sq | 145.214 | 2.490 | 58.309 | 1.116 | 130.113 |
Estimate | s.e. | t.rat.(0) | Rob.s.e. | Rob.t.rat.(0) | |
beta_pa | 42.092 | 5.328 | 7.901 | 2.407 | 17.491 |
beta_hnv | 20.515 | 2.581 | 7.948 | 0.857 | 23.948 |
beta_pa_sq | -0.702 | 0.194 | -3.622 | 0.080 | -8.826 |
beta_hnv_sq | 0.351 | 0.067 | 5.224 | 0.014 | 24.926 |
pa_half_access | 82.600 | 4.909 | 16.827 | 1.890 | 43.710 |
pa_full_access | 51.196 | 4.287 | 11.942 | 1.444 | 35.463 |
hnv_visible | 27.964 | 4.102 | 6.817 | 1.356 | 20.627 |
pa_half_access_sq | -2.312 | 0.182 | -12.679 | 0.068 | -33.823 |
pa_full_access_sq | -0.652 | 0.146 | -4.474 | 0.050 | -13.165 |
hnv_visible_sq | -0.193 | 0.179 | -1.080 | 0.058 | -3.332 |
beta_cost | -3.316 | 0.194 | -17.067 | 0.216 | -15.372 |
ASC_sq | -48.047 | 2.261 | -21.251 | 0.688 | -69.877 |
beta_radius | -3.389 | 0.244 | -13.885 | 0.103 | -32.773 |
sig_pa | -6.169 | 2.080 | -2.967 | 0.627 | -9.840 |
sig_hnv | -29.072 | 1.088 | -26.727 | 0.182 | -160.013 |
sig_pa_sq | 1.342 | 0.051 | 26.198 | 0.012 | 110.067 |
sig_hnv_sq | 0.162 | 0.057 | 2.866 | 0.011 | 14.466 |
sig_pa_half_access | 45.248 | 3.271 | 13.835 | 1.101 | 41.098 |
sig_pa_full_access | 12.970 | 1.262 | 10.281 | 0.403 | 32.161 |
sig_hnv_visible | -0.415 | 2.500 | -0.166 | 0.972 | -0.428 |
sig_pa_half_access_sq | -0.347 | 0.087 | -4.015 | 0.019 | -17.861 |
sig_pa_full_access_sq | -0.431 | 0.092 | -4.670 | 0.024 | -18.175 |
sig_hnv_visible_sq | -0.041 | 0.086 | -0.479 | 0.013 | -3.253 |
sig_cost | -2.321 | 0.329 | -7.046 | 0.367 | -6.331 |
sig_ASC_sq | -132.037 | 2.234 | -59.097 | 0.782 | -168.777 |
sig_radius | -9.029 | 0.258 | -35.040 | 0.120 | -75.439 |
Model | AIC | BIC | LLout |
---|---|---|---|
Quadratic Utility Function | 5523 | 5599.23 | -2749.5 |
Log Utility Function | 5527.5 | 5571.97 | -2756.75 |
Linear Utility Function | 5543.48 | 5587.95 | -2764.74 |
Box Cox Utility Function | 5528 | 5604.23 | -2752 |
Log-Linear Utility Function | 5530.87 | 5607.1 | -2753.43 |
Plot and Map WTP
Plot WTP function for HNV.
Plot WTP for 100ha increase in HNV for all German counties. (based on MXL estimates)
Plot WTP function for PA.
Plot WTP for 100ha increase in Protected Areas for all German counties. (based on MXL estimates)
MXL Plots
CV
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
0 0 30 1333 100 250000 161
Comments
Choice Behaviour
General Comments