Abstract
Fertility is one of the important components of population change, the other two being mortality and migration. When vital statistical data on number of births is readily available it is estimated directly using various direct measures of fertility such as the crude birth rate (CBR). When the information on number of births is not directly available, fertility is measured using the census information on child woman ratios (CWR) of various types. CWR has several limitations, but gained importance with the attempts made by Rele in 1963, and followed by several other researchers such as Hauer and his co-authors in 2013 deriving TFR from it. In the present study yet another attempt is made to use CWRs to derive not only TFR but also other summary indicators such as the TMFR. A set of simple mathematical formula have been used to estimate the fertility and marital fertility using the CWR of the ages 0-9. The 2011 census age-sex data of districts in India was used to derive a set of fertility estimates for total, rural and urban areas of all districts. Further, these estimates of 2011 have been compared with the estimates of 2011 earlier made by Guilmoto and Rajan to analyse the robustness of the estimates. Keywords : Fertility, Child Women Ratio, Indirect Estimation, Age-sex data, TFR, TMFR, India.
Highlights
The commonly used measures such as rates, ratios, percentages and probabilities in mathematics and statistics play a great role in understanding various demographic phenomenon’s such as fertility
When using the child woman ratio (Children 0-4/ Women 15-49) as an indicator of fertility we assume that children enumerated by the time of the census in the age group 0-4 are the actual number of children born 5 years ago and those surviving
Testing the Validity of the Estimates Validity of the derived estimates of crude birth rate (CBR) and TFR is made by comparing them with that of the indirect estimates of CBR and TFR earlier derived by Guilmoto and Rajan (2013)
Summary
The commonly used measures such as rates, ratios, percentages and probabilities in mathematics and statistics play a great role in understanding various demographic phenomenon’s such as fertility. When vital statistical data on number of births is readily available it is estimated directly using various direct measures of fertility such as the crude birth rate (CBR). When the information on number of births not directly available fertility is measured using the census information on child woman ratios (CWR) of various types. When using the child woman ratio (Children 0-4/ Women 15-49) as an indicator of fertility we assume that children enumerated by the time of the census in the age group 0-4 are the actual number of children born 5 years ago and those surviving. The logic behind is that it is assumed that mortality is negligible on the Children 0-4 and the Women 15-49, and assume that no migration during the last five years of the census enumeration date; the children 0-4
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
