More sleep is usually positively correlated with beneficial variables such as increased cognitive ability, better weight management, and overall wellbeing. But can the amount we sleep explain important health and economic indicators?
Lauren Hale, a sleep researcher at Stony Brook University uses sleep as a social justice issue:
“Generally, people who have more opportunities, more control over their lives, are also better sleepers. … Is it true that either racial minorities, low-educated, low job-security individuals, people who live in high-risk neighborhoods, who experience fear at night, are these people who clearly have some sort of social disadvantage, are also not sleeping as well? And is this impaired sleep affecting not only their ability to function the next day but their longer-term health outcomes?”
In a paper called “Time Use and Productivity: The Wage Returns to Sleep”, the authors kind that if you sleep more you will likely earn more money. In the past economists haven’t really paid that much attention to sleep since the data is so hard to come by, and often not very trustworthy.
But the interesting point here is that there is a misconception in society that if you stay up and work long hard hours, you will be rewarded with a higher wage than your counterpart who spends more time sleeping and less working.
It was found that wealthier people on average have lower sleep latency, the time it takes to fall asleep, which means that they are more efficient sleepers. Another study found that higher income people generally sleep more than lower income people.
In addition, low socioeconomic status is commonly linked with poor health, for example a study showed that pediatric sleep apnea, a breathing disorder that makes it difficult to sleep, is more common in poor neighborhoods.
The question many economists are currently stuck at is whether being poor makes you sleep worse or whether sleeping worse makes your poor. Once there is empirical evidence to back up one side of this conundrum, there will be an entirely new stream of variables to take into account when assessing variables such as health, income, and unemployment.