Sleep is an essential human function and getting more sleep is associated with improved mood, cognitive performance, and physical performance. Therefore, it might make sense that sleep would improve people's productivity and ability to earn money. That's the topic of a Freakonomics episode on the "Economics of Sleep." You can read the transcript or listen to the 45 minute episode here. (The section I focus on starts around minute 10.)
Freakonomics' hosts interviewed a set of economists (including Matthew Gibson, Jeff Shrader, Dan Hamermesh, and Jeff Biddle) about their research on sleep, work hours, and income. The economists mentioned that, in order to establish a causal link between sleep and income:
What we need is something like an experiment for sleep. Almost as though we go out in the United States and force people to sleep different amounts and then watch what the outcome is on their wages.
While it is theoretically possible to conduct such an experiment, it is practically difficult to assign people to different sleep conditions for a long enough period of time to notice an impact on their wages. So the economists took an alternative path and used quasi-experimental data. In a creative twist, they compared wages at two ends of a single American time zone. The example they gave is Huntsville, AL and Amarillo, TX. Here's why. Gibson stated:
It turns out that ever since we’ve put time zones into place, we’ve basically been running just that sort of giant experiment on everyone in America.
The story continued. You'll see the transcript version quoted below:
Consider two places like Huntsville, Alabama — which is near the eastern edge of the Central Time Zone — and Amarillo, Texas, near the western edge of the Central zone. [...]
...even though Amarillo and Huntsville share a time zone, the sun sets about an hour later in Amarillo, according to the clock, and since the two cities are at roughly the same latitude as well, they get roughly the same amount of daylight too.
So you’ve got two cities on either end of a time zone, roughly the same size — just under 200,000 people each — where, according to the clock time, sunset is an hour apart. Now, what good is that to a pair of economists interested in sleep research?
GIBSON: It turns out that the human body, our sleep cycle responds more strongly to the sun than it does to the clock. People who live in Huntsville and experience this earlier sunset go to bed earlier.
And the people of Amarillo go to bed quite a bit later. You can see this in data from the American Time Use Survey.
GIBSON: If we plot the average bedtime for people as a function of how far east they are within a time zone, we see this very nice, clean nice straight line with earlier bedtime for people at the more eastern location.
But since Huntsville and Amarillo are in the same time zone, people start work at roughly the same time, which means alarm clocks go off at roughly the same time.
GIBSON: That means if you go to bed earlier in Huntsville, you sleep longer.
The economists didn't use only Huntsville and Amarillo--they also conducted multiple comparisons of cities around the U.S. that were similarly on each end of a single time zone. Using "city of residence" as their quasi-experimental operationalization of "amount of sleep", the economists were ready to report the results for wages:
So now Gibson and Shrader plugged in wage data for Huntsville vs. Amarillo and other pairs of cities that had a similar sleep gap.
GIBSON: We find that permanently increasing sleep by an hour per week for everybody in a city, increases the wages in that location by about 4.5 percent.
Four and a half percent — that’s a pretty good payout for just one extra hour of sleep per week. If you get an extra hour per night, Gibson and Shrader discovered — here, let me quote you their paper: “Our main result is that sleeping one extra hour per night on average increases wages by 16%, highlighting the importance of restedness to human productivity.”
a) What is the independent variable in this time zone and wages study? What is the dependent variable?
b) Is the IV independent groups or within groups?
c) Which of the four quasi-experimental designs is this? Non-equivalent control group posttest only, Non-equivalent control group pretest-posttest, Interrupted time series, or Non-equivalent control group interrupted time series?
d) The economists asserted, "sleeping one extra hour per night on average increases wages by 16%" (italics added). What do you think? Can their study support this claim? Apply the three causal rules, especially taking note of internal validity issues that this study might have.
e) If you consider only one pair of cities, there are multiple alternative explanations, besides sleep, that can account for wage differences. Name two or three such threats (considering Huntsville and Amarillo as an example). Now consider, how might many of these internal validity threats be reduced by conducting the same analysis over many other city pairs?
f) This Freakonomics episode was aired in 2015, but the study (about time zones) they reviewed is not yet published. What do you think about that?
Answers to selected questions
a) The IV is "Hours of sleep" (but you could also call it "location on the time zone: East or West") and the DV is "Wages".
b) The IV is independent-groups.
c) Non-equivalent control group posttest only.
d & e) The results of the study support covariance: People in cities in the Eastern portion of time zones get more sleep and have higher wages than people in the Western portions. Temporal precedence is unclear, I think: Because the data were collected at the same time, it's not clear if the timezone came first, leading to more sleep and higher wages, or if people began to earn higher wages first, and then systematically moved Eastward. (However, the second direction certainly seems less plausible than the first.)
As for internal validity, if we consider only the city pair of Huntsville and Amarillo, we could come up with several alternative explanations. The two cities have different historical trajectories and different ethnic diversities; they are in two different states that have different fiscal policies and industry bases. Perhaps Amarillo has poorer wages in general and people are losing out on sleep there because they are working more than one job. However, these internal validity threats become less of an issue when you consider multiple pairs of cities. It is less plausible that internal validity threats that apply to one city pair would also, coincidentally, apply to all the other city pairs that are at opposite ends of a time zone.
Even though the method is fairly strong, psychologists would be unlikely to make a strong causal claim simply from quasi-experimental data like these, because the independent variable is not truly manipulated. Nevertheless, the method and results of this quasi-experiment are certainly consistent with the argument that getting more sleep may be a factor in earning higher wages.