Abstract
A basic assumption concerned with general linear regression model is that there is no correlation (or no multicollinearity) between the explana tory variables. When this assumption is not satisfied, the least squares estimators have large variances and become unstable and may have a wrong sign. Therefore, we resort to biased regression methods, which stabilize the parameter estimates. Ridge regression (RR) and principal component regression (PCR) are two of the most popular biased regression methods which can be used in case of multicollinearity. But the r-k class estimator, which is composed by combining the RR estimator and the PCR estimator into a single estimator gives the better estimates of the regression coefficients than the RR estimator and PCR estimator. This paper explores the multiple regression technique using r-k class estimator between TFR and other socio-economic and demographic variables and the data has been taken from the National Family Health Survey-III (NFHS-III): 29 states of India. The analysis shows that use of contraceptive devices shares the greatest impact on fertility rate followed by maternal care, use of improved water, female age at marriage and spacing between births.
Highlights
In developing countries, overpopulation is considered to be one of the most basic cause of underdevelopment
There are lot of problems associated with high birth rate
Additional problems faced by a country with a high birth rate include educating a growing number of children, creating jobs for these children when they enter to the workforce, and dealing with the environmental effects that a large population can produce
Summary
Overpopulation is considered to be one of the most basic cause of underdevelopment. Piyush Kant Rai, Sarla Pareek and Hemlata Joshi other large population related problems Given this situation, the governments of developing countries, along with non-government organizations, are trying to address this problem by conducting research on the determinants of fertility. Available evidence showing that the India has considerable fertility as well as contraceptive use differentials among the various states These differentials can well be attributed to the fact that socio-economic factors are often differentially distributed across social groups that exists in a society or between societies. It is believed that socio-economic and other development factors do exert significantly independent as well as the joint impact on fertility after eliminating the effect of the family planning programs and policies. The importance of the study derives from the fact that it is necessary to identify those population groups whose fertility is high but reducible through changes in government policies and the redistribution of available resources
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