The essence of Lott and Hassett’s case that newspapers are biased against Republicans is given in their presentation:
“In the case of unemployment, 44 percent of the headlines under the Clinton administration were positive while that same number was only 23 percent under Bush II. By comparison, the average unemployment rates were fairly similar, 5.2 percent under Clinton s eight years and 5.5 percent under Bush during the sample.”
Their argument is that Clinton got more positive headlines and that this is not explained by differing economic conditions. To test this they do a whole pile of regressions, but these just obscure what is going on. To understand what is happening, all you have to do is look at some headlines of stories reporting the unemployment rate. Here are some typical examples:
- Unemployment rate falls to 5.4%
- US Economy Creates 144,000 Jobs; Unemployment Rate Drops Slightly
- Missouri unemployment rate holds at 5.5 percent
- Colorado unemployment rate steady
Almost all of the headlines for stories reporting on the latest unemployment rate told you whether the rate had increased, decreased or stayed the same. Lott and Hassett counted a headline about unemployment as positive if it reported that the unemployment rate had gone down. So if headlines just follow the pattern above, what percentage of positive headlines would you expect to see? You won’t find the answer in their paper—they don’t even include a control for whether unemployment increased.
I downloaded the relevant unemployment data from the Bureau of Labour Statistics and calculated what percentage of the time the unemployment rate decreased.1 The results are in the third column of the table below. For example, it shows that under Bush I, 21% of the time, the rate decreased. The second column shows the percentage of positive stories that Lott and Hassett report in their paper. For Bush I, this is 20%, almost exactly the number you would expect if all headlines just reported whether the rate had gone up or down. Clinton doesn’t do as well, with only 42% positive headlines despite unemployment decreases 48% of the time, a 6 point gap, while Bush II does even worse with an 11 point gap. Clearly there is no bias for or against Republicans here—the gap for Clinton is exactly half way between that for Bush I and Bush II.
Why is there a gap for Clinton and for Bush II? The correct way to answer this is to go back to the news stories and look at the ones that did not have positive headlines when the unemployment rate went down. I suspect that the ones that weren’t positive included some negative news as well. For example, if unemployment fell, but jobs also fell, Lott and Hassett would count this as “mixed” rather than positive. The incorrect way to answer this is to run more regressions2. The actual words in the headline tell you why it was positive or not. Lott/Hassett’s methodology throws away this information and then tries to work out why the headline was positive by doing lots of regressions. This approach seems to be driven solely by the need to express the data in a form suitable for the application of linear regression.
The last two columns of the table show how unemployment had changed over the previous three months and over the previous year. This probably gives a better idea of trends in unemployment since it smooths out small fluctuations. These show that the focus on the short term in the headlines made the headlines better for Bush I and II and worse for Clinton. Clinton only got 42% positive headlines even though there was a one-year decline 92% of the time, while Bush I managed 20% positive headlines despite never having a one-year decline in unemployment.
2. The title of this post comes from the saying “If the only tool you have is a hammer, then everything looks like a nail.”. If the only tool you have is linear regression … Update: D squared reminds me that they actually used tobit regression, which isn’t even the right kind of regression for their data. So I’m going to make regression equal hammer in my analogy, and say that they didn’t even use the right kind of hammer.
Update 2: I searched Factiva to see what the headlines were when a decrease in unemployment did not generate a positive headline and in those cases it seems that while unemployment had fallen, the number of jobs had also fallen. The headline then either reported both things, which they count as a “mixed” headline or the fall in jobs, which is a negative headline. I added data for the change in the number of jobs to my spreadsheet and worked out how many positive headlines you would get if both unemployment had to fall and jobs have to increase to get a positive headline. The results are in the table below.
My new model predicts the results for Clinton and Bush II almost perfectly. For Bush I, the previous model fits better. It appears that after Clinton came to power headlines switched from just reporting the unemployment rate to reporting the unemployment rate and the number of new jobs. And once again we see no evidence of partisan bias in the headlines.