##  [1] "country_list_bis_debt_securities.csv"  
##  [2] "country_list_combined_bond_indices.csv"
##  [3] "country_list_em_dm.csv"                
##  [4] "emissions_dataset.csv"                 
##  [5] "emissions_dataset.rds"                 
##  [6] "emissions_dataset_full.csv"            
##  [7] "emissions_dataset_full.rds"            
##  [8] "imf_wb_country_groups.csv"             
##  [9] "imf_wb_country_groups.rds"             
## [10] "wb_income_groups.csv"                  
## [11] "wb_income_groups.rds"                  
## [12] "weo_world_income_population.csv"       
## [13] "weo_world_income_population.rds"

Debt by Market Type

Debt restructuring in developing countries is back in the news, but we see with this fairly simple graph that the preponderance of debt is still held overwhelmingly by developed markets.

em_debt <- bis_gov_securities %>%
  group_by(em_dm)%>%
  summarize(total_debt = sum(total_debt_securities))
em_debt %>%
  ggplot(aes(x = em_dm, y = total_debt)) + 
  geom_col(fill = "brown3", colour = "black") + 
  labs(x = "Market Type", 
       y = "Total Debt",
       title = "Total Debt by Market Type",
       subtitle = "$mn",
       caption = "Source: World Bank Data") +
  scale_y_continuous(breaks = seq(10000,50000, by = 5000)) +
  theme_economist()

Comparing CO2 Emissions Among Select Asian Countries

The following graph observes the rise of CO2 among select Southeast Asian countries and includes Australia and India. We see that India, besides already emitting at a higher level, experienced a sharp increase in cumulative emissions starting around 2007. This greatly contrasts with other Asian nations that have seen fairly steady, though comparatively smoother, increases in emissions.

emissions_dataset_full %>%
  rename(Country = iso3c) %>%
  filter(Country %in% c("SGP","AUS","PHL","BGD","IND","IDN","MYS")) %>%
    ggplot(emissions_dataset_full, mapping = aes(x = year, y = cumulative_co2, group = Country)) +
    geom_line(aes(color = Country), size = 2) +
    labs(x = "Year", 
       y = "Cumulative CO2",
       title = "Cumulative CO2 by Year",
       caption = "Source: IMF") +
    scale_y_continuous(breaks = seq(10000,1500000, by = 10000)) +
    scale_x_continuous(breaks = seq(1990,2020, by = 5)) + 
    theme_bw()

Cumulative CO2 by Sub-Region

The following graph looks at cumulative CO2 by region. As might be expected, the more developed regions of North America, East Asia, and Europe make up the largest portion of total output.

sub_region_emissions <- bis_emissions_w_features %>%
  group_by(sub_region) %>%
  filter(characteristic == "cumulative_co2") %>%
  summarize(total_co2 = sum(value)) %>%
  arrange(desc(total_co2))
fix(sub_region_emissions)
sub_region_emissions %>%  
  ggplot(aes(x = reorder (sub_region, -total_co2), y = total_co2)) +
  geom_col(fill = "brown") +
   labs(x = "Sub Region", 
       y = "Total CO2",
       title = "Total CO2 Emissions by Sub-Region",
       caption = "Source: IMF") +
  scale_y_continuous(breaks = seq(1000,1000000, by = 50000)) +
  theme(axis.text.x = element_text(angle = 90, vjust = 0 , hjust=.5),
        panel.background = element_rect(fill = "lightblue",
                           colour = "lightblue",
                           size = 0.5, 
                           linetype = "solid"))