Calculating age-specific death rates by sex in the Philippines from life expectancy at birth using the linear link model

• Main Authors: Chua, Janelle Ong, Ng, Kyla Camille Vesagas
• Format: text
• Language: English
• Published: Animo Repository 2022
• Subjects: Mortality—Statistics; Mortality—Tables; Linear models (Statistics); Life expectancy; Statistics and Probability
• Online Access: https://animorepository.dlsu.edu.ph/etdb_math/2; https://animorepository.dlsu.edu.ph/cgi/viewcontent.cgi?article=1001&context=etdb_math
• Institution: De La Salle University

Life tables are extensively used in the design of sustainable government support systems and valuation of insurance products, leading to increased interest in mortality modelling and forecasting. However, despite various available methods, such research in the Philippine setting is clearly lacking. Hence, this study proposes to apply the linear link (LL) model of Pascariu et al. (2020) to forecast age-specific Philippine central death rates by sex with life expectancy at birth as the sole predictor. To do so, abridged life tables from 1970 to 2010 were obtained from the Developing Countries Mortality Database (DCMD). The 1970 to 2000 abridged life tables were then expanded using the Heligman-Pollard (HP) and equivalent construction (EC) method. An LL model was then built from each of the two sets of expanded life tables, and named as HP-LL and EC-LL model following the expansion method used. These two models were then tested by inputting the 2001 to 2010 life expectancy at birth to yield forecasts of the age-specific central death rates. Comparisons were done graphically and through sum of squares. Since the original dataset from DCMD is of the abridged form, the forecasts were also abridged for comparison with the 2001 to 2010 DCMD values. Additionally, since insurance companies currently rely heavily on the 2017 life table from the Philippine Intercompany Mortality (PICM) Study, model forecasts for 2017 were also made. However, since PICM 2017 only provides death probabilities, the central death rate forecasts were first converted to death probabilities to allow comparison. From these comparisons of model forecasts and values in the DCMD and PICM 2017, the EC-LL model consistently worked better for females. Meanwhile, for males, the HP-LL model is overall better, but the EC-LL is more suggested for insurance companies since this better reflected the PICM data.