Quality of government and governance outcomes

Readings and class materials for Tuesday, January 24, 2023

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()
```