diff-in-diff vis w ggplot

class: center, middle, inverse, title-slide

# diff-in-diff vis w ggplot
### Evangeline Reynolds
### 5/18/2018

---

```r
knitr::opts_chunk$set(warning = F, message = F)
library(flipbookr)
```

Using a difference-in-difference framework to look at the effect of policy interventions is a popular research design.  A binary exlanatory variable that turns on and stays on lends itself to ease of interpretation!

In the context of such a design, what is the essential visual inspections?  Below I suggest four plots that researchers and their audiences may find useful in visually inspecting the timing of interventions and the relationships between a policy intervention and outcomes.

I use ggplot2 to implement the visualization. The ability to overwrite global aesthetics, using the aes() function, means that we move from one plot to another with little additional code.  A little over a year ago I learned about declaring the aes() on it's own line and maybe novelty bias is at work here, but I find the capability to be a lot of fun to play with!

---

The five plots are as follows:

- two plots showing the timing of intervention and the cross-sectional cases (one aligning the moments of interventions)
- two plots showing how the intervention relates to the response variable of interest (one aligning the moments of interventions)
- a plot that breaks up the data into individual time-series for the response variable for each cross-sectional unit

Another option for visualizing such data is using the new package [panelView](http://yiqingxu.org/software/panelView/panelView.html), which certainly gave me additional inspiration for this exercise and looks useful!

```r
library(tidyverse)
library(gapminder)
```

# Simulating interventions

We'll just use

---

```r
min_year <- min(gapminder$year)
max_year <- max(gapminder$year)
span <- max_year - min_year
gapminder %>% 
  select(country) %>% 
  distinct() %>% 
  sample_frac(.5) %>% 
  mutate(intervention_year = runif(n = n(), 
                 min = min_year, 
                 max = max_year + span)) %>% 
  mutate(intervention_year = ifelse(max_year < intervention_year, 
                                    NA, 
                                    intervention_year)) %>% 
  mutate(intervention_year = 
           round(intervention_year)) %>% 
  sample_n(16) ->
synthetic_interventions
```

---

```r
synthetic_interventions %>% 
  inner_join(gapminder) %>% 
  mutate(treatment = 
           case_when(
             year >= intervention_year ~ "treated",
             year < intervention_year ~ "not treated",
             is.na(intervention_year) ~ "not treated")) %>%
  group_by(country) %>% 
  mutate(mean_treated = mean(treatment == "treated")) %>% 
  arrange(mean_treated) %>% 
  ungroup() %>% 
  mutate(country = forcats::fct_inorder(as.character(country))) -> 
panel_prepped
```

---

class: split-40
count: false
.column[.content[

```r
*ggplot(panel_prepped)
```
]]
.column[.content[
![](difference_in_difference_files/figure-html/essential_plots_user_1_output-1.png)
]]
---
class: split-40
count: false
.column[.content[

```r
ggplot(panel_prepped) +  
* aes(x = year)
```
]]
.column[.content[
![](difference_in_difference_files/figure-html/essential_plots_user_2_output-1.png)
]]
---
class: split-40
count: false
.column[.content[

```r
ggplot(panel_prepped) +  
  aes(x = year) +  
* aes(y = country)
```
]]
.column[.content[
![](difference_in_difference_files/figure-html/essential_plots_user_3_output-1.png)
]]
---
class: split-40
count: false
.column[.content[

```r
ggplot(panel_prepped) +  
  aes(x = year) +  
  aes(y = country) +  
* aes(group = country)
```
]]
.column[.content[
![](difference_in_difference_files/figure-html/essential_plots_user_4_output-1.png)
]]
---
class: split-40
count: false
.column[.content[

```r
ggplot(panel_prepped) +  
  aes(x = year) +  
  aes(y = country) +  
  aes(group = country) +  
* labs(caption = "Four essential plots for diff-in-diff | Gina Reynolds")
```
]]
.column[.content[
![](difference_in_difference_files/figure-html/essential_plots_user_5_output-1.png)
]]
---
class: split-40
count: false
.column[.content[

```r
ggplot(panel_prepped) +  
  aes(x = year) +  
  aes(y = country) +  
  aes(group = country) +  
  labs(caption = "Four essential plots for diff-in-diff | Gina Reynolds") +  
* geom_line(alpha = .5)
```
]]
.column[.content[
![](difference_in_difference_files/figure-html/essential_plots_user_6_output-1.png)
]]
---
class: split-40
count: false
.column[.content[

```r
ggplot(panel_prepped) +  
  aes(x = year) +  
  aes(y = country) +  
  aes(group = country) +  
  labs(caption = "Four essential plots for diff-in-diff | Gina Reynolds") +  
  geom_line(alpha = .5) +  
* geom_point(size = 1.5)
```
]]
.column[.content[
![](difference_in_difference_files/figure-html/essential_plots_user_7_output-1.png)
]]
---
class: split-40
count: false
.column[.content[

```r
ggplot(panel_prepped) +  
  aes(x = year) +  
  aes(y = country) +  
  aes(group = country) +  
  labs(caption = "Four essential plots for diff-in-diff | Gina Reynolds") +  
  geom_line(alpha = .5) +  
  geom_point(size = 1.5) +  
* aes(color = treatment)
```
]]
.column[.content[
![](difference_in_difference_files/figure-html/essential_plots_user_8_output-1.png)
]]
---
class: split-40
count: false
.column[.content[

```r
ggplot(panel_prepped) +  
  aes(x = year) +  
  aes(y = country) +  
  aes(group = country) +  
  labs(caption = "Four essential plots for diff-in-diff | Gina Reynolds") +  
  geom_line(alpha = .5) +  
  geom_point(size = 1.5) +  
  aes(color = treatment) +  
* theme_minimal()
```
]]
.column[.content[
![](difference_in_difference_files/figure-html/essential_plots_user_9_output-1.png)
]]
---
class: split-40
count: false
.column[.content[

```r
ggplot(panel_prepped) +  
  aes(x = year) +  
  aes(y = country) +  
  aes(group = country) +  
  labs(caption = "Four essential plots for diff-in-diff | Gina Reynolds") +  
  geom_line(alpha = .5) +  
  geom_point(size = 1.5) +  
  aes(color = treatment) +  
  theme_minimal() +  
  scale_color_manual(values = c("lightgrey", "steelblue4")) +  
  labs(color = NULL) +  
  labs(x = NULL) +  
  labs(y = "country") +  
  labs(title = "Plot 1: Treatment-control summary") +  
  # overwriting y position mapping
  aes(y = gdpPercap) +  
  scale_y_log10() +  
  labs(y = "GDP per cap") +  
  labs(title = "Plot 2: Treatment-control response overlaid summary") +  
* # overwriting x position mapping
* aes(x = year - intervention_year) +
* labs(x = "year from intervention year") +
* labs(title = "Plot 3: Treatment-control response overlaid summary, aligned intervention")
```
]]
.column[.content[
![](difference_in_difference_files/figure-html/essential_plots_user_16_output-1.png)
]]
---
class: split-40
count: false
.column[.content[

```r
ggplot(panel_prepped) +  
  aes(x = year) +  
  aes(y = country) +  
  aes(group = country) +  
  labs(caption = "Four essential plots for diff-in-diff | Gina Reynolds") +  
  geom_line(alpha = .5) +  
  geom_point(size = 1.5) +  
  aes(color = treatment) +  
  theme_minimal() +  
  scale_color_manual(values = c("lightgrey", "steelblue4")) +  
  labs(color = NULL) +  
  labs(x = NULL) +  
  labs(y = "country") +  
  labs(title = "Plot 1: Treatment-control summary") +  
  # overwriting y position mapping
  aes(y = gdpPercap) +  
  scale_y_log10() +  
  labs(y = "GDP per cap") +  
  labs(title = "Plot 2: Treatment-control response overlaid summary") +  
  # overwriting x position mapping
  aes(x = year - intervention_year) +  
  labs(x = "year from intervention year") +  
  labs(title = "Plot 3: Treatment-control response overlaid summary, aligned intervention") +  
* # overwriting x position mapping again
* aes(x = year) +
* labs(x = NULL) +
* scale_y_continuous() +
* labs(title = "Plot 4: Treatment-Response faceted") +
* facet_wrap(~ country)
```
]]
.column[.content[
![](difference_in_difference_files/figure-html/essential_plots_user_17_output-1.png)
]]