The World Bank Data
The Word Bank Open Trade and Competitiveness Data
Load the required packages
library(pacman) p_load(data360r, widgetframe, plotly, tidyverse, tidyselect)
Data is from Worldwide Governance Indicators: here
The WGI measure six broad dimensions of governance:
- Voice and Accountability (VA) – capturing perceptions of the extent to which a country’s citizens are able to participate in selecting their government, as well as freedom of expression, freedom of association, and a free media.
- Political Stability and Absence of Violence/Terrorism (PV) – capturing perceptions of the likelihood of political instability and/or politically-motivated violence, including terrorism.
- Government Effectiveness (GE) – capturing perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government’s commitment to such policies.
- Regulatory Quality (RQ) – capturing perceptions of the ability of the government to formulate and implement sound policies and regulations that permit and promote private sector development.
- Rule of Law (RL) – capturing perceptions of the extent to which agents have confidence in and abide by the rules of society, and in particular the quality of contract enforcement, property rights, the police, and the courts, as well as the likelihood of crime and violence.
- Control of Corruption (CC) – capturing perceptions of the extent to which public power is exercised for private gain, including both petty and grand forms of corruption, as well as “capture” of the state by elites and private interests. question_answer
Download and process data with data360r
df <- get_data360(dataset_id = 51) %>% as_tibble() # df %>% glimpse() # names(df) %>% vars_select(contains("20"))
df_corruption <- df %>% pivot_longer(cols = contains("20"), names_to = 'year') %>% janitor::clean_names() %>% mutate(year = as.numeric(year)) %>% filter( year > 2003) df_corruption %>% group_by(subindicator_type) %>% tally()
## # A tibble: 5 x 2 ## subindicator_type n ## <chr> <int> ## 1 Estimate 18450 ## 2 Lower 18450 ## 3 Rank 18450 ## 4 StdErr 18450 ## 5 Upper 18450
df_corruption_est <- df_corruption %>% filter(subindicator_type == "Estimate") df_corruption_est %>% group_by(indicator) %>% tally()
## # A tibble: 6 x 2 ## indicator n ## <chr> <int> ## 1 Control of Corruption 3060 ## 2 Government Effectiveness 3060 ## 3 Political Stability No Violence 3090 ## 4 Regulatory Quality 3060 ## 5 Rule of Law 3090 ## 6 Voice and Accountability 3090
df_corruption_est %>% group_by(country_iso3, country_name) %>% tally() %>% DT::datatable(rownames = FALSE, fillContainer = FALSE, options = list(pageLength = 10)) %>% widgetframe::frameWidget(width = "100%", height = "100%")
p <- df_corruption_est %>% filter(country_iso3 %in% c("USA", "RUS")) %>% ggplot(aes(x = year, y = value, color = country_name)) + geom_point() + geom_line() + labs(title = "Worldwide Governance Indicators", subtitle = "Source: http://info.worldbank.org/governance/wgi") + scale_x_continuous(breaks = seq(from = 2004, to = 2016, by = 4)) + facet_wrap(~indicator) + hrbrthemes::theme_ipsum() + hrbrthemes::scale_color_ipsum() ggplotly(p) %>% widgetframe::frameWidget()