ABSTRACT OF THE THESIS
Estimating Fertility Rates at Subnational Levels in the Philippines
by Marjorie B. Villaver (2019)
Most fertility studies are limited to national and regional levels. While the National Demographic and Health Survey (NDHS) provides reliable fertility estimates at the regional level every five years, the provincial level fertility estimates are often made in conjunction with the preparation of census-based population projections every ten years. With the increasing demand of up to date indicators at lower administrative levels in view of the localization of the Sustainable Development Goals, this study intends to fill this gap by providing provincial level fertility estimates, which in turn enables appraisal of the completeness of birth registration in the country. Using data that are available at lower levels of disaggregation, three methods on fertility estimation, namely Palmore, Rele and the implied Total Fertility Rate, were explored. Results show that there were differences in the fertility estimates generated so the "best" method to estimate the provincial level fertility rates were selected following a set of criteria. The Palmore method produced a national estimate equal to the total fertility rate computed from two NDHSs. The estimates using the implied total fertility rate were close to those from the Palmore method. The Rele equation produced total fertility rates that are higher compared to the other two methods. Using the national and regional estimates from the NDHSs and the selected TFRs for each province, the level of completeness of birth registration was computed. Comparing the national estimate with that from the 2015 Census of Population data on birth registration, it was revealed that there is a need to improve our civil registration system and promote awareness on the importance of registration of vital events. The results of the study can serve as baseline estimates for monitoring the quality of our civil registration system in the Asian and Pacific Civil Registration and Vital Statistics Decade (2015-2024).