Estimation of Total Fertility Rate and Birth Averted due to Contraception: Regression Approach

Abstract

Fertility plays an important role in any demographic transition and total fertility rate (TFR) is one of the basic measurements of fertility. Due to non-availability of complete and reliable data, a large number of indirect techniques have been developed to estimate the demographic parameters with incomplete data. Some of these techniques are based on utilizing the data from stable population theory while others are based on the regression technique in which the parameters are estimated through regression equations between the dependent variable which is the TFR and the independent variables which is the socio economic well as demographic variables. In the present paper an indirect method has been proposed to estimate the TFR using regression analysis. In these types of analysis the most serious problem is the choice of predictor variable. If the choice of predictor variable is good then it gives the better estimate for the dependent variable (TFR). Using new predictor variable (proposed in this paper), the improved model explained about 85 percent of the variation in TFR. The findings reveal that the values of TFR calculated by the present method are quite close to the observed values of the TFR without involving much computational complexities at state level for different background characteristics. By using this modified estimate of TFR, the demographers can easily calculate the birth averted for different regions as well as states also.