Modeling The Effects Of Interference In Fertility Rate: A Case Study Of Rwanda, Indonesia And Kenya

ABSTRACT

Many studies have been done on fertility for many years. However, very little has

been documented in the existing literature concerning modeling of fertility in the presence

of interference, yet interference to fertility is a common phenomenon. In this study

fertility data sets for Rwanda, Indonesia and Kenya were modeled before and after interference.

The parameters of the model were estimated by the maximum likelihood

estimation method. The model life table approach was used to determine the Net Fertility

Value, F0. A relationship between fertility rate in the presence of interference and

population growth was also determined. Using Akaike’s Information Criteria, (AIC), it

was established that amongst the distributions fitted; Gamma, Weibull and Lognormal,

Gamma gave the best fit for the fertility rate data, for all the countries studied, and

interference simply shifts the Gamma distribution parameters. The result of this study

would help the Governments to understand fully the effect of interference on fertility rate

and plan for it. Demographers would also benefit from this study since it can be used to

project population growth after an interference.