Teaching with TwoRavens:
The Quality of Government Data
The Quality of Government is a fantastic resource for researchers of all levels of qualitative and
quantitiative expertise (Teorell et al., 2015). It contains country-level variables, some from data
collections such as the World Values Survey, and others from well-known articles such as Bueno de
Mesquita et al. (1999). The variables contain information on the economy, health and social services,
government institutions, the environment, conflict, and more. There is both a time-series dataset and a
cross-sectional dataset using mostly data from 2010.
This document will guide you through some simple regressions testing plausible hypotheses with TwoRavens. We will be using the QoG cross-sectional data.
Follow the link to the Teaching with TwoRavens dataverse. Click on the Quality of Government dataset. Inside this dataset are two files: qog_std_cs_jan15.tab and qog_std_jan15.pdf. Download and open the PDF; this is the QoG codebook. Next to the “Download” button for the file qog_std_cs_jan15.tab, click “Explore.” This should open a page in your browser, as shown in figure 1.1
Due to its breadth of variables, the Quality of Government dataset can be used to assess hypotheses across many fields of social science. In the following section, one hypothesis is proposed and tested in preliminary, exploratory fashion.
Studies such as Reitsma, Scheepers and Grotenhuis (2006), Graham and Haidt (2010), and Sablosky (2014) have examined the relationship between religiosity and charity in the individual. Others, such as Paxton and Knack (2011) and Hook (2008), have examined the role between religion and foreign aid. Suppose a student has developed a theory relating findings in this literature, and is now interested in exploring the statistical relationship between religion and foreign aid.
Alternatively, perhaps a politician states that individuals who are more religious give more to charity, and by extension religious countries are more charitable. Suppose an individual wishes to fact-check that politician.
In either situation, a first step is likely a simple statistical test. In the QoG data, there is an aid variable aid_cpsc, and a measure of religiousness wvs_rel. These variables are easily discoverable in the QoG codebook. Let’s estimate a simple regression to test this hypothesis.
After loading the data:
The results from this regression appear in figure 2. As we can see, the effect of religiousness is positive and significant at the 0.1 level, but not significant at the 0.05 level. Exploring the relationship a bit further, we might also include variables for a country’s GDP and population.
The results from this better-specified model appear in figure 3. As we can see, the effect of religiousness is still positve, but not statistically significant at any conventional level.
The following classroom exercises are designed to encourage quantitative reasoning in the classroom. Begin by breaking the class into groups and providing the class with a link to the TwoRavens dataverse.
Reitsma, Jan, Peer Scheepers and Manfred Te Grotenhuis. 2006. “Dimensions of individual religiosity and charity: cross-national effect differences in European countries?” Review of Religious Research pp. 347–362.
Teorell, Jan, Stefan Dahlberg, Sren Holmberg, Bo Rothstein, Felix Hartmann and Richard Svensson. 2015. “The Quality of Government Standard Dataset, version Jan15.”. University of Gothenburg: The Quality of Government Institute, http://www.qog.pol.gu.se.