MODELING THE EFFECTS OF INTERFERENCE IN FERTILITY RATE: A CASE STUDY OF RWANDA, INDONESIA AND KENYA
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Date
2016
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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 ted by
the maximum likelihood
estimation method. The model life table approach was used to determine the Net Fertility Value, Fo. A relationship between fertility rate in the presence of interference and population growth was also determined Using Akaiko's Information Criteria (AIC) population growth was also determined. Using Akaike's Information Criteria, (AIC), it
was established that amongst the distributions fitted; Gamma, Weibull and Lognormal, 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.