An NPR story carried the headline, "Study: Commuting Adversely Affects Political Engagement." The verb in the headline, "affects" makes this a causal claim. Is there evidence in the story that commuting causes changes in political engagement?
In an interview, researcher Joshua Johnson stated the relationship in causal terms, too:
We found that when people spent more time commuting [or spending] extra hours on their commute, that made them less likely to be engaged in politics.
a) Think for a moment: What are the variables in this research? Would they most likely be measured or manipulated?
b) Sketch a scatterplot that would show the relationshiop between commuting time and political engagement.
c) Can the researchers really support a causal claim from these data, at least as decribed here?
Shankar Vedantam, the NPR host who described the study, explained:
There's something about commuting in particular that seems to affect engagement, and the researchers are drawing here on this paper on earlier work by the behavioral economist Daniel Kahneman. He's found that commuting ranks among the most unpleasant parts of people's day. There's something uniquely stressful about commuting, and so when you get home after a hellacious day, you really have nothing to give to other people in terms of civic engagement, in terms of getting involved in your neighborhood politics.
Here's a reminder to my readers–just because you can offer a good explanation for a correlation, that doesn't change the fact that a correlational study cannot definitively support causation!
But back to the story. The correlational pattern gets more complex–it involves a moderator! I'll quote the transcript of the NPR report:
INSKEEP: Are all people affected the same way by this stress?
VEDANTAM: So this is a really important point, Steve, because it turns out that even though there's a general connection between political engagement and commuting, the effect is not experienced evenly by everyone. Commuting disproportionately seems to cause the poor to disengage from politics. And as we go up the income ladder, the effects that commuting have on political engagement actually decrease….
Commuting is stressful for everyone, but the poor find it harder to buffer themselves against the effects of the stress. When you're well off, you come home from a terrible day, you can go out for dinner. You can buy yourself a treat. When you're poor, you have less access to those kinds of safety nets.
d) In this example, we can say that social class moderates the relationship between commuting and political engagement. Sketch a moderator table that would capture this pattern.
Suggested Answers:
a) Think for a moment: What are the variables in this research? Would they most likely be measured or manipulated?
The two variables are time spent commuting and degree of political engagement. These are both measured variables, because it would be practically and ethically impossible to assign people to have a long commute.
b) Sketch a scatterplot that would show the relationshiop between commuting time and political engagement.
Your scatterplot should have Time spent commuting on one axis, and Degree of political engagement on the other. The dots should be spread in a negatively sloping pattern, because the more time people spend commuting, the less politically engaged people are.
c) Can the researchers really support a causal claim from these data, at least as decribed here?
No. There is covariance here: time spent commuting goes with less political engagement. Temporal precedence seems ambiguous: Which variable came first? Did commuting come first, followed by less engagement? Or do less politically engaged people prefer to work farther from the center of things? Finally, internal validity isn't clear–there may be third variables that explain this relationship. Perhaps younger people tend to commute further, and they are also less politically engaged. Perhaps less educated people commute further and are also less engaged. We would want to see Johnson's original research report–he probably statistically controlled for several such variables. His report would tell us which of these possible third variables were statistically controlled for, to help rule out third variable explanations.
d) In this example, we can say that social class moderates the relationship between commuting and political engagement. Sketch a moderator table that would capture this moderation pattern.
Here's one possible pattern (These data are fabricated, but I made them to fit the pattern described):
Social class level Relationship between commuting time and engagement
Lower SES -0.21*
Middle SES 0.03
Note: Initially, to make the moderator easier to understand, I oversimplified the quote. But in fact, the moderation pattern was a little more complex:
Commuting disproportionately seems to cause the poor to disengage from politics. And as we go up the income ladder, the effects that commuting have on political engagement actually decrease until we get to the very wealthy, where the longer your commute, the more likely you are to be politically engaged.
To represent the full pattern, you might show this (again, I fabricated the data to illustrate):
Social class level Relationship between commuting time and engagement
Lower SES -0.21*
Middle SES 0.03
Highest SES 0.17*