Why did fertility fall in so many countries, often without any population policy? One of the strongest patterns in population geography links fertility to girls' schooling and women's work.
Key idea
Where more girls finish secondary school and more women work for pay, women tend to marry later and have fewer children, later in life. This pattern holds across regions and religions, though the size of the effect varies.
Why it works
Several things happen together. Years in school delay marriage and first births. Education raises what a woman can earn, so time away from paid work costs more. Educated parents often know more about health and family planning, and their children are more likely to survive, so families need fewer births to reach the size they want. Cities, where schooling and paid work are easier to find, push the same way: children cost more there and are less often needed on a farm.
Worked examples
Worked example: Reading a pattern
In a set of regions, the share of women with secondary schooling rises from 20% to 80%, and TFR falls from 5.5 to 2.0. What can you conclude?
- The two measures move in opposite directions: a negative correlation.
- That fits the pattern, but correlation alone does not prove one causes the other.
- Other changes, such as cities and health care, often rise along with schooling.
Answer: More schooling goes with lower fertility; schooling is likely one of several causes.
Worked example: Two explanations
Give two reasons girls' schooling could lower fertility.
- Staying in school delays marriage and first births.
- Education raises earnings, so having many children costs more in lost income.
Answer: Later marriage and higher earnings (also better health knowledge).
Common mistake
Students reverse cause and effect, or assume one factor explains everything. It is true both that schooling tends to lower fertility and that having fewer children can make it easier for women to stay in school and work. Schooling, health care, cities and jobs usually change together, so researchers try to separate their effects. Say "is associated with" unless you have evidence about cause.