Modelling age specific fertility rate in India through fertility curves

One of the important demographic features of any population is the fertility rate which has a direct relationship with both the social and the biological environment. Demographic factors like age at marriage, present family size, gender preference (Mahadevan [27], Bhasin [3], Asari and John [2], Chachra and Bhasin [18], Bhasin and Nag [19]) and socio economic factors like education, occupation, religion, contraceptive practice, etc. (Bhatia [20], Asari and John [2]) are the determinants of desired family size and all these are considered as the cause of the variation of fertility. So far researchers have proposed a variety of reproductivity measures and mathematical models to describe the reproductivity pattern of human population (Islam and Ali [21], Peristera and Kostaki [22] and Nasir et al. [23]). The objective of this study is to examine the current pattern of Age Specific Fertility Rate(ASFR) and to study the trend in fertile age groups by fitting non linear models to the ASFR data for all the states in India obtained from the sample registration system [1], of India. Cross Validity Prediction Power (CVPP), Shrinkage, and R² are used to identify the best model for the states. Model identification for Forward Age Specific Fertility Rate (FASFR) and Backward Age Specific Fertility Rate (BASFR) along with validity measures are also presented in this paper.