INSIGHTS INTO CAUSES OF REAL WORLD PHENOMENA

Models have, however, provided insights into the causes of change in the demographic variables. For example, using the simple multivariate regression analysis with total fertility rate as dependent variable and GDP per capita, life expectancy and gross primary and secondary school enrolment rate percent urban, and agriculture as percent of GDP as independent variables, Bryant drew the following conclusions:

1. Decline of fertility declines in countries with low scores on development indicators cannot be explained by socioeconomic theories
2. The relationship between development indicators and fertility is weaker than that predicted by socioeconomic theories
3. The relationship between development indicators and fertility has shifted over time

Some of the above conclusions would not be possible to make if the appropriate data did not exist or if the technique of multivariate regression analysis was not known. In an interesting article using data on homicide rates Cole and Gramajo (2009) showed that as female education increases, the homicide rates also increase. It was an unexpected finding. Then they posited a number of factors that explain this unexpected relationship.

MAXIMUM LONGEVITY

It has been a matter of great interest to establish how much gain in life expectancy is ever possible. Can a person live for 500 years, or 200 years, or 100 years? Is it possible to improve further the life expectancy in the present day developed countries? If so, by how many years? How can it be done? In one such attempt Bongaarts (2006) built a model of life expectancy and showed that by reducing mortality due to causes related to smoking it should be possible to increase further the life expectancy in the high income countries further. His model is discussed below.