New life tables methods in order to get some ambitous objectives

Towards advanced methods on computing life tables

Sixto Muriel de la Riva, Margarita Cantalapiedra Malaguilla and Federico Lpez Carrin

Directorate of Population StatisticsNational Statistics Institute of Spain

Joint Eurostat-UNECE Work Session on Demographic Projections. Lisbon, 28-30 April 2010.

New life tables methods in order to get some ambitous objectivesMaximum use of available information.

Methodological consistency and rigor in definitions of biometric functions of the life table.

Capturing the annual incidence of mortality.

Accuracy on measuring mortality risks at advanced ages.

Regular measures of mortality incidence over subpopulations.

International comparability.

Easier interpretation of life tables results for users.


Three methods tested for national level


Option1: uniform distribution of deaths on Lexis squaresSpecific mortality rate by sex and age:Probability of death by sex and age:Uniform time distribution of deaths within a year: a(x,s)=1/2


Option 2: uniform distribution of deaths on Lexis trianglesSpecific mortality rate by sex and age (following HMD protocols):Probability of death by sex and age:


Option 3: real time distribution of death eventsWhy do not we use all available information we have?


Differences in mortality curve are negligibles...


except for advanced ages


Deviations in mortality risk are due to the different estimation of a(x) too


In spite of all, life expectancy shows a robust behaviour


but options 1 and 2 shows a light underestimation of life expectancy


Conclussions related to national life tablesThe three options capture annual incidence of mortality.

The three options keep methodological consistency.

Option 3 maximizes the use of all available data.

Option 3 reachs the highest accuracy in measuring mortality incidence and life expectancies.


Three methods tested for regions and provinces


Option 1: abbreviated life tables by five years age intervalsSpecific mortality rate by sex and age:Average number of year lived in the last group of years of life:


Option 2: aggregated results by five years of age groups from complete life tablesFrom a complete life table survivors function (l(x,s)) and stationary population (L(x,n,s)Deaths serie:Probability of dying:Average number of year lived in the last goup of years of life:


Option 3: complete life tables adjusted by the Brass logits methodRelation between regional and national survivors (logits): Deaths serie:Probability of dying:


Option 1 does not avoid the effect of the age structure within each age group


and, consequently, option1 overestimates life expectancies


Neverthelles, sometimes the randomness of deaths data distorts the analysis


Option 3 provides detailed results, assuming light deviations from real data


however, option 3 imports distortions in life expectancy at advanced ages


Conclussions related to regional life tables

The three options avoid problems of small sizes populations: randomness of deaths data and lower accuracy of population estimates. Option 1 does not clean the effect of age estructure of population within each age interval.

Option 3 provides detailed results by simple ages, but causes distorsions in advanced ages.

Option 2 keeps complete consistency with a complete life table, avoiding problems of small sizes populations.


Thank you for your attention

Sixto Muriel de la RivaDeputy Director of Population StatisticsNational Statistics Institute of [email protected]


Documents

New life tables methods in order to get some ambitous objectives