Quality of government and governance outcomes
Readings and class materials for Thursday, September 12, 2024
Readings
Bo Rothstein, “Creating Political Legitimacy,” American Behavioral Scientist 53, no. 3 (November 2009): 311–30, https://doi.org/10.1177/0002764209338795.
Bo Rothstein and Jan Teorell, “What Is Quality of Government? A Theory of Impartial Government Institutions,” Governance 21, no. 2 (April 2008): 165–90, https://doi.org/10.1111/j.1468-0491.2008.00391.x.
Christoph Jindra and Ana Vaz, “Good Governance and Multidimensional Poverty: A Comparative Analysis of 71 Countries,” Governance 32, no. 4 (October 2019): 657–75, https://doi.org/10.1111/gove.12394.
Plan for the day
How to discuss an article in a seminar
- Who wrote the article? What’s their background?
- General summary of the article
- Strengths
- Weaknesses
- How does it connect to other readings?
- How does it connect to the broader course themes?
- How does it connect to current events?
- What does it add to our Global Bureaucracy Toolkit™?
Defining and measuring governance
- Francis Fukuyama, “What Is Governance?” Governance 26, no. 3 (July 2013): 347–68, https://doi.org/10.1111/gove.12035.
- Sören Holmberg, Bo Rothstein, and Naghmeh Nasiritousi, “Quality of Government: What You Get,” Annual Review of Political Science 12, no. 1 (June 2009): 135–61, https://doi.org/10.1146/annurev-polisci-100608-104510.
Legitimacy and governance and impartiality
- Rothstein, “Creating Political Legitimacy.”
- Rothstein and Teorell, “What Is Quality of Government? A Theory of Impartial Government Institutions.”
- Jindra and Vaz, “Good Governance and Multidimensional Poverty.”
Playing with actual governance-related data
- Quality of Government (QoG) Institute data (R package)
- Varieties of Democracy (V-Dem) Institute data (R package; R example)
- World Bank data (R package; R example)
- The World Bank’s Worldwide Bureaucracy Indicators database
- The Worldwide Governance Indicators (WGI) project
- Global Multidimensional Poverty Index (MPI)
R code example: Posit.cloud example (V-Dem doesn’t work though)
---
title: "Examples of working with governance-related data"
---
```{r setup, warning=FALSE, message=FALSE}
library(tidyverse)
# remotes::install_github("ropengov/rqog")
library(rqog)
# remotes::install_github("vdeminstitute/vdemdata")
library(vdemdata)
library(WDI)
```
# Quality of Government (QoG) project
```{r}
qog_basic <- read_qog(which_data = "basic", data_type = "time-series")
```
```{r}
afg_alb <- qog_basic |>
filter(cname %in% c("Afghanistan", "Albania")) |>
filter(year >= 2007, year <= 2020)
ggplot(data = afg_alb,
mapping = aes(x = year, y = wbgi_gee, color = cname)) +
geom_line()
```
# Varieties of Democracy (V-Dem) project
```{r}
vdem_small <- vdem |>
select(country_name, country_text_id, year, region = e_regionpol_6C,
public_sector_corruption = v2x_pubcorr, impartial_pa = v2clrspct) |>
filter(country_name %in% c("Afghanistan", "Albania")) |>
filter(year >= 2007, year <= 2020)
ggplot(data = vdem_small,
mapping = aes(x = year, y = impartial_pa, color = country_name)) +
geom_line()
```
# World Bank data
```{r}
wdi_raw <- WDI(
country = "all",
# indicator = c("NY.GDP.PCAP.KD", "BI.PWK.PUBS.FE.ZS"),
indicator = c("NY.GDP.PCAP.KD"),
start = 2007,
end = 2020,
extra = TRUE
)
wdi_small <- wdi_raw |>
filter(country %in% c("Afghanistan", "Albania"))
ggplot(data = wdi_small,
mapping = aes(x = year, y = NY.GDP.PCAP.KD, color = country)) +
geom_line()
```