CSSR_Project/Appendix.Rmd at master · torbatschow/CSSR_Project · GitHub

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---
title: "Appendix"
output: pdf_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)

# Setting Working directory
try(setwd("/home/torben/GIT/Pair_Assignment_2"), silent = TRUE)
try(setwd("D:/Eigene Datein/Dokumente/Uni/Hertie/Materials/Collaborative Social Science Data Analysis/CSSR_Project"), silent = TRUE)

# load data / models / graphs
source("main.R")
```

#Appendix


```{r descriptive, echo=FALSE}
# select diagnoses data for state comparison
DS.A <- TOTAL %>% filter(GENDER == "all", AGE=="all") %>%
  select(STATE, YEAR, F100_p1000, F102_p1000, K70_p1000, GDP_P_C, UR.LF, YUR, BTAX_P_C, PP)

# Youth unemployment rate
#ggplot(data=DS.A, aes(x = YEAR, y = YUR, group = STATE, colour = STATE)) +
#  geom_line() +                              # line plot
#  theme_bw() +                               # bw background
#  xlab("Years") +
#  ylab("Youth unemployment rate") +
#  ggtitle("Youth unemployment in German states 2000-2014")

# Beer Tax
# REMARK: Beer TAX might be a bad proxy for beer consumption.
# According to this statistic Bremen is the largest consumer, but it probably just hints at Becks
#ggplot(data=DS.A, aes(x = YEAR, y = BTAX_P_C, group = STATE, colour = STATE)) +
#  geom_line() +                              # line plot
#  theme_bw() +                               # bw background
#  xlab("Years") +
#  ylab("Beer tax revenue per capita") +
#  ggtitle("Beer tax in German states 2000-2014")

# German wide beer tax revenue
#BTAX.G <- TOTAL %>% filter(GENDER == "all", AGE == "all") %>%
#                    select(YEAR, STATE, BTAX)
#BTAX.G <- aggregate(as.numeric(BTAX.G$BTAX), by = list(BTAX.G$YEAR),
#          FUN = sum)
#colnames(BTAX.G) <- c("YEAR","BTAX")

# Beer tax revenue in Germany 2000-2014
#ggplot(data=BTAX.G, aes(x = YEAR, y = BTAX)) +
#  geom_line(colour="blue", size=1.5) +       # line plot
#  theme_bw() +                               # bw background
#  xlab("Years") +
#  ylab("Beer Tax Revenue in Tsd. Euro") +
#  ggtitle("Beer Tax Revenue 2000-2014")
```

## Robustness Tests


```{r robustness, results="asis", echo=FALSE}
mod1.labels <- c("GDP per capita", "Unemployment rate", "Population density", "(Intercept)")
mod1.modellist <- as.character(c(2000:2014))
stargazer::stargazer(mod1.list[1:5],
                     covariate.labels = mod1.labels,
                     column.labels = mod1.modellist[1:5],
                     model.numbers  = FALSE,
                     dep.var.labels = "F10.0 Diagnoses per 1000 capita",
                     title = 'Robustness test model 1 for the years 2000-2004',
                     digits = 2, type = 'latex', header = FALSE)
stargazer::stargazer(mod1.list[6:10],
                     covariate.labels = mod1.labels,
                     column.labels = mod1.modellist[6:10],
                     model.numbers  = FALSE,
                     dep.var.labels = "F10.0 Diagnoses per 1000 capita",
                     title = 'Robustness test model 1 for the years 2005-2009',
                     digits = 2, type = 'latex', header = FALSE)
stargazer::stargazer(mod1.list[11:15],
                     covariate.labels = mod1.labels,
                     column.labels = mod1.modellist[11:15],
                     model.numbers  = FALSE,
                     dep.var.labels = "F10.0 Diagnoses per 1000 capita",
                     title = 'Robustness test model 1 for the years 2010-2014',
                     digits = 2, type = 'latex', header = FALSE)
```

```{r, results="asis", echo=FALSE}
stargazer::stargazer(mod2.F100, mod2.F102, mod2.K70,
                     column.labels = c("F10.0", "F10.2", "K70"),
                     covariate.labels = c("GDP Change", "Unemployment Change",
                                          "Beer Tax Change", "(Intercept)"),
                     model.numbers  = FALSE,
                     dep.var.labels = c("Change in F10.0","Change in F10.2",
                                        "Change in K70"),
                     title = 'Regression results for Model 2 with first differenced data',
                     digits = 2, type = 'latex', header = FALSE)
# Results Model 3
stargazer::stargazer(mod3.16, mod3.13,
                     column.labels = c("(3) All states + ages", "(3) non-city states + all ages"),
                     covariate.labels = c("BW night sale ban", "Post-ban dummy",
                                          "Interaction dummy", "(Intercept)"),
                     model.numbers  = FALSE,
                     dep.var.labels = c("F10.0 cases per 1000 PP (all ages)"),
                     title = 'Model 3 Simple Diff-in-Diff',
                     digits = 2, type = 'latex', header = FALSE)
stargazer::stargazer(mod3.age15.16, mod3.age15.13,
                     column.labels = c("(3) All states + 15-19y", "(3) non-city states + 15-19y"),
                     covariate.labels = c("BW night sale ban", "Post-ban dummy",
                                          "Interaction dummy", "(Intercept)"),
                     model.numbers  = FALSE,
                     dep.var.labels = c("F10.0 cases per 1000 PP among 15-19 year olds"),
                     title = 'Model 3 Simple Diff-in-Diff for 15-19 year old',
                     digits = 2, type = 'latex', header = FALSE)
```

```{r, results="asis", echo=FALSE}
stargazer::stargazer(mod4, mod4.age15, mod4.age15.13,
                     column.labels = c("(4) All states + ages","(4) All states + 15-19y",
                                       "(4) non-city states + 15-19y"),
                     covariate.labels = c("BW night sale ban", "Post-ban dummy",
                                          "GDP per capita", "Youth unemployment",
                                          "Interaction dummy", "(Intercept)"),
                     model.numbers  = FALSE,
                     dep.var.labels = c("F10.0 cases per 1000 PP (different age groups)"),
                     title = 'Model 4 Simple Diff-in-Diff with controls',
                     digits = 2, type = 'latex', header = FALSE)
```