Untitled

#Post WWI (1900-1920)
democracy_counts_1900_1920 <- vdem |> 
  filter(year >= 1900, year <= 1920, e_boix_regime == 1) |> 
  group_by(year) |> 
  summarise(num_democracies = n())

ggplot(data = democracy_counts_1900_1920, aes(x = year, y = num_democracies)) +
  geom_line() +
  labs(x = "Año", y = "Número de Democracias", 
       title = "Evolución del Número de Democracias (1900-1920)")

#Collapse USSR (1986-1994)
democracy_counts_1986_1994 <- vdem |> 
  filter(year >= 1986, year <= 1994, e_boix_regime == 1) |> 
  group_by(year) |> 
  summarise(num_democracies = n())

ggplot(data = democracy_counts_1986_1994, aes(x = year, y = num_democracies)) +
  geom_line() +
  labs(x = "Año", y = "Número de Democracias", 
       title = "Evolución del Número de Democracias (1900-1920)")

#To generate a regression coefficient it is first necessary to create a new 
#variable with 20-year-periods from 1860 to 1879 for both variables. 
vdem <- vdem |> 
  mutate(period = cut(year, breaks = seq(1859, max(year), by = 20), labels = FALSE))

#Once we have the variable, we can run a regression for each of those periods:
reg11 <- vdem |> 
  group_by(period) |> 
  summarise(
    coefficient = coef(lm(e_migdppcln ~ v2x_polyarchy))[2],
    period_start = min(year),
    period_end = max(year)
  )

reg12 <- vdem |> 
  group_by(period) |> 
  summarise(
    coefficient = coef(lm(v2x_polyarchy ~ e_migdppcln))[2],
    period_start = min(year),
    period_end = max(year)
  )

print(reg11)
print(reg12)

ggplot(data = reg11, aes(x = period_start, y = coefficient)) +
  geom_line() +
  labs(
    x = "Start Year of Period",
    y = "Coefficient",
    title = "Evolution of Coefficients Over Time (Regression 1.1)"
  ) 

ggplot(data = reg12, aes(x = period_start, y = coefficient)) +
  geom_line() +
  labs(
    x = "Start Year of Period",
    y = "Coefficient",
    title = "Evolution of Coefficients Over Time (Regression 1.2)"
  )


reg21 <- vdem |>
  group_by(e_regionpol_6C) |>
  do(model = lm(e_migdppcln ~ v2x_polyarchy, data = .)) |>
  summarise(
    region = e_regionpol_6C,
    coefficient = coef(model)[2],
    r_squared = summary(model)$r.squared
    )

print(reg21)

region_names <- c("E. Europe/C. Asia", "Latin America", "Middle East", "Sub-Saharan Africa", "Europe/America", "Asia & Pacific")

ggplot(reg21, aes(x = factor(region, levels = 1:6, labels = region_names), y = coefficient)) +
  geom_bar(stat = "identity") +
  labs(x = "Region", y = "Coefficient") +
  ggtitle("Corr. Coefficient (reg21) by Region")