A mortality table, also known as a life table or actuarial table, reveals the rate of deaths in a specified population over a particular time interval, or shows survival rates from birth until death. It generally indicates the likelihood of an individual dying before their next birthday, dependent on their present age. These tables are extensively used in designing insurance policies and managing liabilities across various sectors.
Key Takeaways
- Mortality tables show the rate of death within a specific population.
- They integrate numerous factors to predict the likelihood of death within the current year for an individual.
- Mortality tables are crucial for insurance companies and social security administrations.
- These tables are broadly divided into “period” life tables and “cohort” life tables.
- Actuaries often prefer using “cohort” life tables for their applications.
How a Mortality Table Works
Mortality tables are intricate systems of numerical values that elucidate the probability of death for members of a specified population during a set period. This prediction is based on a myriad of variables such as gender, age, smoking status, occupation, and socio-economic class. Occasionally, actuarial tables also assess longevity in relation to weight.
The insurance industry heavily relies on mortality tables to structure their policies, just as social security administrations do to organize their coverage details. Mortality tables were first introduced by Raymond Pearl in 1921 to push forward ecological studies.
Types of Mortality Tables
There are primarily two types of mortality tables.
- Period Life Table: This type of table determines mortality rates for a specific timeframe within a particular population.
- Cohort Life Table: Also known as the generation life table, it represents the overall mortality rates across an entire lifetime for a certain population. Cohort life tables are more commonplace in actuarial applications due to their broader applicability.
Requirements for Mortality Tables
Mortality tables are founded on parameters like age and gender. They display the probabilities as deaths-per-thousand, predicting the number of people per 1,000 expected to die within a year. Life insurance companies use this information to determine premiums and ensure their financial stability.
Typically, mortality tables span from birth up to the age of 100 in yearly increments. They can be used to locate the probability of death at any given age. Unsurprisingly, this probability escalates with age.
For instance, a mortality table will show that a newborn male has a near negligible (less than 0.01%) chance of dying in comparison to the rest of the group, translating to a life expectancy of about 75 years. Contrarily, according to a 2005 mortality table used by the Social Security Administration, a 119-year-old man has over a 90% likelihood of dying within the year, giving him a life expectancy of just over six months.
Related Terms: life insurance, actuarial science, life expectancy, insurance premium.
