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Commit 568da154 authored by nc71qaxa's avatar nc71qaxa
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WONV adjustments

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......@@ -100,13 +100,13 @@ ggsave("Figures/treatment_time_bxplt.png", width=7, height = 5, dpi="print")
table(database_full$Treatment_C)
### Create boxplot for interview time per group #
### Create boxplot for interview time per group #, remove quiz group 1776
database_full <- database_full %>% mutate(groupTime1774 = case_when(is.na(groupTime1774) ~ 0, TRUE ~ groupTime1774),
groupTime1784 = case_when(is.na(groupTime1784) ~ 0, TRUE ~ groupTime1784),
groupTime1775 = case_when(is.na(groupTime1775) ~ 0, TRUE ~ groupTime1775),
groupTime1785 = case_when(is.na(groupTime1785) ~ 0, TRUE ~ groupTime1785),
groupTime1786 = case_when(is.na(groupTime1786) ~ 0, TRUE ~ groupTime1786)) %>%
mutate(interviewtime_net = interviewtime - groupTime1774 - groupTime1784 - groupTime1775 - groupTime1785- groupTime1786 )
mutate(interviewtime_net = interviewtime - groupTime1774 - groupTime1784 - groupTime1775 - groupTime1785- groupTime1786 - groupTime1776)
# Calculate the cutoff values for the lowest and highest 1 percent
lower_cutoff <- quantile(database_full$interviewtime_net, 0.01)
upper_cutoff <- quantile(database_full$interviewtime_net, 0.95)
......
......@@ -47,7 +47,7 @@ list_ols <- list("(Intercept)" = "Intercept", "as.factor(Treatment_A)Treated" =
- **Stated preference** methods are frequently applied in **environmental valuation** to estimate economic values of policies, goods, and services that cannot be valued otherwise.
- Stated preference methods face **validity challenges**.
- Valid value estimation requires **sufficient information** provision about the good being valued.
- Still unclear **what formats of information** and **how much information** are optimal for valid preference elicitation.
- Still unclear **what formats of information provision** and **how much information** are optimal for valid preference elicitation.
:::
## Motivation (2)
......@@ -57,6 +57,8 @@ list_ols <- list("(Intercept)" = "Intercept", "as.factor(Treatment_A)Treated" =
- Too **little information** may lead respondents to **not** being able to make an **informed choice**.
- Valid preference elicitation depends not only on the provision of information, but also on the **appropriate processing and recall** of the information by the respondent.
- **Optional information** allows the respondents to gather required information if needed and might increase efficiency of information provision
- Providing optional information should enhance optimal information seeking leading to less heterogeneity in good-specific knowledge between the respondents
:::
## Literature
......@@ -64,7 +66,7 @@ list_ols <- list("(Intercept)" = "Intercept", "as.factor(Treatment_A)Treated" =
::: incremental
- There is **little research** on the effects of **optional information provision** on choice behavior and information recall.
- In their study, @tienhaara2022information surveyed preferences for agricultural genetic resources, allowing respondents the option to access detailed information on the valued goods prior to preference elicitation.
- Similarly, @hu2009consumers offered respondents the opportunity to access voluntary information about genetic modified food before participating in a choice experiment.
- Similarly, @hu2009consumers offered respondents the opportunity to access optional information about genetic modified food before participating in a choice experiment.
- Both studies conclude that, on average, respondents who voluntary retrieve information have **larger willingness to pay** for the good to be valued.
- Their study design, however, does not allow comparing the optional information retrieval to a version where the additional information was shown obligatory.
:::
......@@ -81,8 +83,16 @@ list_ols <- list("(Intercept)" = "Intercept", "as.factor(Treatment_A)Treated" =
::: incremental
1. Do obligatory and optional information provision affect **survey engagement**, **information recall**, **consequentiality**, and **stated preferences**?
- OLS and MXL with interactions
2. Do **socio-demographic** or **attitudinal** variables influence the decision to **access optional information**?
- Logit regression
3. Do **survey engagement**, **information recall**, **consequentiality**, and **stated preferences** differ between respondents who **voluntary access information** and those who do not?
- OLS and MXL with interactions
:::
# Survey & Data
......@@ -151,58 +161,56 @@ list_ols <- list("(Intercept)" = "Intercept", "as.factor(Treatment_A)Treated" =
![](Grafics/FlowChart_4_groups.png){width="300"}
## Methods (1) {auto-animate="true"}
<!-- ## Methods (1) {auto-animate="true"} -->
- OLS regression (survey engagement, information recall, consequentiality):
<!-- - OLS regression (survey engagement, information recall, consequentiality): -->
```{=tex}
\begin{equation}
Y = \beta_0 + \beta_{Treat} \cdot v_{Treat} + \beta_{Control} \cdot v_{Control} + \epsilon
\label{ols}
\end{equation}
```
- Mixed logit model with interactions in WTP space:
<!-- ```{=tex} -->
<!-- \begin{equation} -->
<!-- Y = \beta_0 + \beta_{Treat} \cdot v_{Treat} + \beta_{Control} \cdot v_{Control} + \epsilon -->
<!-- \label{ols} -->
<!-- \end{equation} -->
<!-- ``` -->
<!-- - Mixed logit model with interactions in WTP space: -->
```{=tex}
\begin{equation}
U_i = -(\beta_{C_i} + \beta_{TreatC_i} \cdot v_{Treat}) \cdot (\beta_{X_i} \cdot v_{X_i} + \beta_{TreatX_i} \cdot v_{X_i} \cdot v_{Treat} - C_i) + \epsilon_i
\label{mxl_base}
\end{equation}
```
## Methods (2) {auto-animate="true"}
- Mixed logit model with interactions in WTP space:
<!-- ## Methods (2) {auto-animate="true"} -->
```{=tex}
\begin{equation}
U_i = -(\beta_{C_i} + \beta_{TreatC_i} \cdot v_{Treat}) \cdot (\beta_{X_i} \cdot v_{X_i} + \beta_{TreatX_i} \cdot v_{X_i} \cdot v_{Treat} - C_i) + \epsilon_i
\end{equation}
```
with
<!-- - Mixed logit model with interactions in WTP space: -->
```{=tex}
\begin{equation}
v_{X_i} = \{ASC_{sq_i}, Nat_i, WD_i\}
\end{equation}
```
and
<!-- ```{=tex} -->
<!-- \begin{equation} -->
<!-- U_i = -(\beta_{C_i} + \beta_{TreatC_i} \cdot v_{Treat}) \cdot (\beta_{X_i} \cdot v_{X_i} + \beta_{TreatX_i} \cdot v_{X_i} \cdot v_{Treat} - C_i) + \epsilon_i -->
<!-- \end{equation} -->
<!-- ``` -->
<!-- with -->
<!-- ```{=tex} -->
<!-- \begin{equation} -->
<!-- v_{X_i} = \{ASC_{sq_i}, Nat_i, WD_i\} -->
<!-- \end{equation} -->
<!-- ``` -->
<!-- and -->
<!-- ```{=tex} -->
<!-- \begin{equation} -->
<!-- v_{Treat_A} = \{Treated, Optional Treatment\} -->
<!-- \end{equation} -->
<!-- ``` -->
<!-- ```{=tex} -->
<!-- \begin{equation} -->
<!-- v_{Treat_B} = \{Treated, Vol. Treated, No Info\} -->
<!-- \end{equation} -->
<!-- ``` -->
```{=tex}
\begin{equation}
v_{Treat_A} = \{Treated, Optional Treatment\}
\end{equation}
```
```{=tex}
\begin{equation}
v_{Treat_B} = \{Treated, Vol. Treated, No Info\}
\end{equation}
```
# Case A: Obligatory vs. Optional Information
## Case A
1. Do obligatory and optional information provision affect **survey engagement**, **information recall**, **consequentiality**, and **stated preferences**?
![](Grafics/FlowChart_4_groups_A.png){width="300"}
<!-- ::: {style="font-size: 45%;"} -->
......@@ -227,17 +235,52 @@ and
## OLS: Engagement
::: panel-tabset
### OLS Specification
```{=tex}
\begin{equation}
Y = \beta_0 + \beta_{Treat} \cdot v_{Treat} + \beta_{Control} \cdot v_{Control} + \epsilon
Y = \beta_0 + \beta_{Treat} \cdot v_{Treat} + \beta_{SocDem} \cdot v_{SocDem} + \epsilon
\label{olss}
\end{equation}
```
with
```{=tex}
\begin{equation}
Y = \left\{
\begin{aligned}
&\text{Net Interview Time, Mean Choice Card Time} \\
&\text{Percentage of correct quiz statements, Consequentiality Score}
\end{aligned}
\right\}
\end{equation}
```
```{=tex}
\begin{equation}
v_{Treat} = \{\text{Treated, Optional Treatment}\}
\end{equation}
```
```{=tex}
\begin{equation}
v_{SocDem} = \{\text{Age, Gender, Income, Education, NR-Index}\}
\end{equation}
```
### Results
```{r}
ggpubr::ggarrange(plot_interview_A, plot_cc_A)
```
:::
## OLS: Information Recall & Consequentiality
```{r}
......@@ -246,7 +289,38 @@ ggpubr::ggarrange(plot_mani_A, plot_cons_A)
## MXL: Effects on Stated Preferences
::: {style="font-size: 80%;"}
::: panel-tabset
### MXL Specification
```{=tex}
\begin{equation}
U_i = -(\beta_{C_i} + \beta_{TreatC_i} \cdot v_{Treat}) \cdot (\beta_{X_i} \cdot v_{X_i} + \beta_{TreatX_i} \cdot v_{X_i} \cdot v_{Treat} - C_i) + \epsilon_i
\label{mxl_base}
\end{equation}
```
with
```{=tex}
\begin{equation}
v_{X_i} = \{ASC_{sq_i}, Nat_i, WD_i\}
\end{equation}
```
```{=tex}
\begin{equation}
v_{Treat} = \{\text{Treated, Optional Treatment}\}
\end{equation}
```
```{=tex}
\begin{equation}
C_i = \{Rent_i\}
\end{equation}
```
### Results
::: {style="font-size: 68%;"}
```{r, results='asis'}
htmlreg(c(case_A_cols[1], remGOF(case_A_cols[2:4])),
custom.coef.map = list("natural" = "Naturalness", "walking" = "Walking Distance", "rent" = "Rent",
......@@ -259,17 +333,24 @@ htmlreg(c(case_A_cols[1], remGOF(case_A_cols[2:4])),
```
:::
:::
# Case B: Voluntary Information Access
## Case B
## Voluntary Information Access
2. Do **socio-demographic** or **attitudinal** variables influence the decision to **access optional information**?
![](Grafics/FlowChart_Optional_only.png){width="300"}
![](Grafics/FlowChart_4_groups_B.png){width="300"}
## Logit Regression: Who chooses Optional Information?
```{=tex}
\begin{equation}
Y = \beta_0 + \beta_{Control} \cdot v_{Control} + \epsilon
Y = \beta_0 + \beta_{SocDem} \cdot v_{SocDem} + \epsilon
\label{simple_logit}
\end{equation}
```
......@@ -289,6 +370,13 @@ htmlreg(l=list(logit_choice_treat_uni), stars = c(0.01, 0.05, 0.1), float.pos="t
```
:::
## Case B
3. Do **survey engagement**, **information recall**, **consequentiality**, and **stated preferences** differ between respondents who **voluntary access information** and those who do not?
![](Grafics/FlowChart_4_groups_B.png){width="300"}
## OLS Engagement: Interview & Choice Card Time
```{r}
......@@ -340,13 +428,11 @@ htmlreg(c(case_B_cols_NR[1], remGOF(case_B_cols_NR[2:6])),
1. Do obligatory and optional information provision affect survey engagement, information recall, consequentiality, and stated preferences?
::: incremental
- Obligatory and voluntary treatments do not increase survey engagement measured via time spend on the survey
- Small negative effect for obligatory treatment on survey engagement
- Obligatory and optional treatments do not increase survey engagement measured via time spend on the survey
- Both treatments increase information recall, stronger effect for obligatory treatment
- No effect on consequentiality
- No effects on consequentiality
- Strong effects on stated preferences for both treatments, more pronounced effect for the obligatory treatment
:::
......@@ -368,27 +454,21 @@ htmlreg(c(case_B_cols_NR[1], remGOF(case_B_cols_NR[2:6])),
3. Do survey engagement, information recall, consequentiality, and stated preferences differ between respondents who voluntary access information and those who do not?
::: incremental
- Respondents that voluntary access information do engage more in the survey & have a higher consequentiality score
- Respondents that voluntary access information do not engage more in the survey, but perform best in the quiz
- Voluntary information access is negatively correlated with number of status quo choices
- Respondents that decide to not access additional information engage less in the survey, have a lower consequentiality score and do not perform different in the quiz than the non-treated respondents
- Higher willingness to pay values in groups that voluntary access information
- Highest willingness to pay values in the group that voluntary accesses information
:::
## Conclusion
::: incremental
- Obligatory and voluntary information treatments increase information recall and willingness to pay for naturalness of and proximity to urban green spaces
- Exogenous treatments do not affect consequentiality
- Voluntary information access is correlated with increased consequentiality, higher survey engagement and higher willingness to pay
- Obligatory information treatment is more effective than optional on the cost of slightly reduced survey engagement
- Providing optional information does not lead to optional information seeking
- Voluntarily accessed treatment shows strongest effects, but is highly endogenous
- Optional information is mostly accessed by people that are interested in the good to be valued
- Providing optional information seem to rather increase inequality in good-specific knowledge than decreasing it
- We recommend to use obligatory information provision rather than optional one
:::
## References
......
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