A few years/weeks ago, my boyfriend asked me “what happens during a recession?”, and I realized that while I knew the technical definition- GDP shrinks, unemployment grows- I didn’t really know what the human effects were. So as part of my temp job as “something something coronavirus” at LessWrong, I went looking.
All data is for the United States unless otherwise specified.
- Unemployment increases in a recession. This creates a long lasting negative effect on people who enter the labor force during a recession (unemployment scarring).
- Women’s employment is more stable than men’s
According to Have employment patterns in recessions changed? (which was published in 1981), recessions universally (for n=4) concentrate employment in the service sector, by 1-3 percentage points
Looked at in more detail, from the Bureau of Labor Statistics
From 1953-1980, women have a higher unemployment rate than men, during both expansions and recessions. From 1980 on, men and women have nearly identical unemployment rates in good times, but men’s unemployment has higher peaks during recessions.
Unemployment over time, by gender
At first I thought this was because men are more likely to work in manufacturing, which is more procyclic (see next section), but the pattern holds even within sectors
But unemployment typically means ‘is looking for work’. Perhaps women who lose their jobs are more likely to call themselves Stay-At-Home-Parents and stop looking for work. What happens to the labor force participation rate?
So that’s not it either.
Black and Latino people typically have a higher unemployment rate than white people (I did not find equivalent data for Asians over a long enough time period), and are hit harder during recessions
Unfortunately I could only find comparative data going back to 1990, but it looks like youth unemployment is continually higher than older adults, by a similar amount over time.
This isn’t the whole story though, because unemployment can have long term negative effects when you’re young, and especially when you’re just entering the workforce. This is known as unemployment scarring. People who enter the workforce during recessions have lowered employment, wages, and job fit, an effect that lasts for at least 15 years and possibly more. Here are some papers covering the effect. Obviously the longest term data is available only for older recessions, and I could imagine that things aren’t as bad now given the loss of the one-employer-for-life model… but here’s one paper covering the Great Recession that says it’s still quite bad.
My prediction: divorces are postponed during a recession, leading to an apparent drop and then catch-up bounce
Reality: Trends in divorce continue basically unabated
This paper, the only long-time-scale survey I could find, reports a minor negative correlation between unemployment rates and divorce. However looking at their graph, the relationship is obviously mild.
My prediction: religious participation increases during a recession.
Reality: Religious Service Attendance Stays Flat
I was really surprised to find only one academic paper in the last 40 years on religiosity and economic conditions, which was not available online. It reports a “strong” countercyclic effect in religious participation in evangelical Protestants but procyclic effect in mainline Protestants, in the 2001 recession. Meanwhile a Pew poll and a Gallup poll show no change in religious participation during the 2008 recession.
I googled this before making a prediction, but do not believe I would have predicted the results.
People die a little less often, especially in nursing homes.
Deaths go down during recessions; according to Ruhm 2002, a 1% decrease in the unemployment rate is associated with an average 0.4% rise in total mortality (about 13,000 deaths, relative to the average of ~2.8m). This is counterintuitive, because wealth is associated with longevity (e.g. Chetty et al. 2016) . There were a lot of potential explanations for this centering on how work was dangerous and didn’t leave time for health, but it turns out most of the additional deaths are concentrated among groups that were unlikely to be employed in the first place, such as those over 70 (70% of the total) or under 4. Fewer than 10% of the additional deaths occur among those between the ages of 25 and 64 (Stevens et al 2011).
Why does employment of working-age adults have such an impact on elderly mortality? Stevens et almake a compelling case that it’s because widespread unemployment increases the relative number of people willing to take unpleasant, low-paying nursing home jobs, particularly entry level “aide” positions, and this improves care of residents.
My prediction: recessions lead to a moderate drop in number of live births
The effect of economic downturns on births is surprisingly complicated. On one hand, people have less money and kids are expensive*, which you would expect to lead to fewer children. On the other hand, a reduction in employment expectations reduces the opportunity cost of children, which you would expect to lead to more.
Based primarily on Economic recession and fertility in the developed world and spot checking its sources, my conclusion is that modern recessions temporarily decrease per capita births, but by and large do not change cohort fertility (i.e. women have the same number of total children they would have had without the recession, but later). Some trends:
- The reduction in births is seen mostly in younger women (20-24), not older women (30-34), suggesting this is a voluntary decision incorporating knowledge of ability to have children in the future.
- The effect is much larger for first births than subsequent births, suggesting this may be more about union formation than post-union decisions to have children (this could also explain the age-related effects)
- The change seems to be driven more by change in situation than by absolute status, i.e. there isn’t a strict relationship between per capita GDP or unemployment and fertility that holds across countries, but in countries where children and women have the same status, people will react similarly to a change in circumstance.
- Male unemployment is universally bad for fertility.
- Female unemployment depends on the era (used to be positively associated with fertility, now is negatively) and on a woman’s socioeconomic status (richer/better educated women’s fertility is more procyclic than poorer/worse education women’s).
- Generous unemployment insurance or non-employment-linked maternity benefits unsurprisingly raise the birth rate during a recession.
Specific numbers are hard to give because every country, demographic, and recession is different, but as an example, this article estimates ~9% decrease in fertility in 2013 in the US.
* This is in societies where children are economic sinks. In situations where they are assets, you would expect the reverse.
Thanks to Eli Tyre for research assistance on this section.
My prediction: Suicide rises in a recession
Reality: Suicide rates rise, primarily in unemployed men
A review found that out of 38 studies:
- 31 of them found a positive association between economic recession and increased suicide rates.
- 2 studies reported a negative association,
- 2 articles failed to find any association
- 3 studies were inconclusive.
Unfortunately they didn’t share the effect size for most of these studies. Looking at other sources (notes here), I found anywhere from a 4% increase (across Europe and the Americas during the 2008 recession) to 60% (among men in Russia during the 1991 crisis). Studies typically found a much larger effect in men than women, sometimes finding no change in the female suicide rate at all. Different studies found different effects on different age groups; these felt too subdivided to me and I ignored them. Unsurprisingly, unemployment was positive correlated with suicide.
That 60% increase in Russia corresponded to an additional 30 deaths per 100,000 people per year, at a time when the overall death rate was 1300 deaths per 100,000 people. That 4% Europe/Americas increase represents 5000 deaths total, across three continents.
I was 3 for 5 on predictions, 3 for 6 if you include the one I didn’t formally predict ahead of time.
My full notes on this are available here.
Many thanks to my Patreon patrons who also supported this work.