1. Harvard School of Public Health
Evidence on how Population and Reproductive Health Impact Economic Growth and Poverty Reduction
David Canning
Harvard School of Public Health
November 2, 2006

2. Theory and Evidence
Theoretical models tell us what evidence to look for.
There are many mechanisms that potentially link population to growth and poverty reduction.
Evidence of a narrow focus in the past on the effect of population growth rate on economic growth.

3. Theory: Population Effects on economic growth
Malthusian
exhaustible resources (climate)
Neo-classical growth theory
capital dilution
Positive scale effects
technological progress and agglomeration externalities

4. Impact of population growth on economic growth
Use cross-national data.
Standard finding was of little effect of population growth on economics growth (NAS Report 1986).
Result still holds today.

5. The 1986 Report in Historical Context
The report was “revisionist” (Kelley 2001) as opposed to other “population-alarmist” reports.
The authors were economists and allowed for market and institutional mechanisms that may alleviate the negative consequences of population growth.

6. Critiques
We have been looking at the wrong level of aggregation. Many effects may occur only at the global or city level.
Other theoretical models would make us look at different evidence.
Test conflates several different effects.

7. Other Theories Quality- quantity tradeoff
health and education of children
Maternal health and productivity
Female labor market participation
Transition from family support to saving for old age
Age structure effects –
Labor supply and saving vary with age.
Differential effects of fertility, mortality and migration

8. Components of Population Growth
Population growth can be decomposed into the crude birth rate, minus the crude death rate, plus inward migration.
Looking at effects of population growth as a whole assumes these components have exactly equal effects - the effect of a birth is the same as an inward migrant or a death avoided.
The economic impact of changes the birth rate, death rate, and migration rate are likely to be very different.

9. Mortality and Health
Low death rates are associated with healthier populations; evidence has emerged for such an effect in both the micro and macro literature.
It is common to capture health in growth regressions by life expectancy
This “health productivity” can be separated from the population effect

11. Demography and Growth
Low birth rate and low death rate are both associated with faster economic growth.
A high (and rising ) ratio of working age to dependent population is associated with economic growth.
The effect is robust in growth models and help forecast economic growth.
Identification – timing. Past demography is uncorrelated with future growth shocks.

12. Age Structure and Accounting
There is an accounting effect of age structure, where we take age specific behavior to be constant and look at the effect of a changing age pattern.
This gives large effects of age structure change on labor supply and saving.
Age structure can be written as a function of past fertility, mortality and migration rates.

15. Demography and Saving
Investment rates in most countries are closely tied to domestic savings rates.
Savings rates vary with age. Changing age structure towards the older working age groups (who have high savings rates) tends to increase national savings rates.
Macro effects are larger than those found by calibration based on micro data – perhaps due to the fact that aging populations have longer life expectancy generating higher savings rates for retirement at all ages.

17. East Asia: Age Structure

18. Sub-Saharan Africa: Age Structure

20. Interactions
High rates of growth of the working age population produce an increase in labor supply.
This supply must be met by demand if it is to be employed.
We have evidence that the beneficial effects of age structure change only occur in countries with good institutions and economic policies
Estimation different from calibration

21. Poverty Reduction
Cross country poverty and inequality data is very low quality.
Little evidence of an effect of fertility on inequality in macro data (poor get proportional benefits).
Some evidence that demographic transition occurs first among the better off, widening income inequality.
The poorer families “catch up” later in the transition.

22. Economic Growth, Welfare, and Population Policy
We find that lower fertility promotes growth in GDP per capita. However, GDP per capita is not a welfare measure. A broader notion of welfare is required.
If the benefits and costs of fertility fall entirely on the family, we should aim to achieve desired fertility. We do not have evidence here of externalities (need to compare effect within and across families).

23. Poverty Trap
The temporary boost in GDP per capita due to the demographic transition may help countries escape from a poverty trap.
The feedbacks from income, health and education to fertility are a technical problem for identifying the direction of causality.
They are conceptually important in understanding the process of development since they set up a self reinforcing, positive feedback, system
Points to research on determinants of desired fertility, and the system, as well as the consequences of filling unmet need.

24. Casual Effects in Microdata
Determining the effects of mortality, fertility, and migration pose quite different problems
Desired fertility is a choice and is the product of a joint decision.
Random shocks (unplanned births, infertility) identify the effect of fertility on behavior.
Access to family planning for unmet need is a good instrument as it is also the likely policy intervention.
Changing desired fertility is likely to have different effect from providing services to reduce unmet need.

25. Micro Evidence Large family size is associated with poverty.
Few studies try to get at causality
Twins and sex composition (with male preference) are not good instruments.

26. Microeconomic evidence: the economic effects of lowering fertility – determining causality
Miller, 2005, quasi-random placement of family planning services in Columbia, effects of women’s education and labor supply.
Joshi and Schultz, 2006, MATLAB family planning experiment in Bangladesh, effect on child health, woman’s health, and income.

27. Focus: Theory
Which mechanism (theoretical effect) is to be focused on?
Can we determine causality rater than association.