A scale- and time-independent technique for estimating total fertility rates from age-sex distributions
This project is an extension of a previously published fertility estimation method called the Implied Total Fertility Rate or iTFR.
This repository contains the data and code to verify these findings. If you find any problems, let me know!
Recent advances in migration and mortality estimation for small populations have revealed important patterns, but accurate estimation of fertility for small or specialized populations remains elusive.The primary fertility index for a population, the total fertility rate (TFR), requires accurate data on births disaggregated by mother’s age. TFR is thus incalculable for the many areas and time periods that lack such information. Here we discuss a universal methodological framework for estimating TFR that uses inputs as minimal as the age-sex structure of a population. The implied total fertility rate (iTFR) accurately estimates fertility from a population's age-sex structure in a wide range of scales, time periods, and even species. We also discuss two extensions of the iTFR, called xTFR and BayesTFR, that offer improved accuracy with minimal additional data requirements. To demonstrate the utility of this approach, we produce the first complete county-level map of US fertility, reconstruct historical TFRs for three European countries up to 150 years prior to the collection of any birth records, and estimate TFR for the United States conditioned on household income, a variable that is not recorded in US birth records. Given its parameter-free nature, the method captures fundamental qualities that govern fertility with a near universal applicability across space and time. We anticipate that our methodological framework will be a starting point for more sophisticated fertility analyses in previously inestimable sub-populations, time periods, and geographies, significantly expanding our ability to understand the nature of fertility.