Chapter 6 Flashcards
Who uses projected mortality rates?
Life companies and pensions companies - need to set correct premiums to make money and remain competitive.
Governments - need to know future trend to fund state pensions and healthcare social care etc
How has the view on mortality projection changed?
In the past view was that past trends in mortality improvements would continue. Also there was a high element of judgement and consultation with experts. These methods generally underestimated mortality - Interest now is more in extrapolation of past trends by fitting models - less reliance on judgement
Explain extrapolation
Extension of a graph, curve or range of values by inferring unknown values from trends in the known data
Whats a key point about mortality trends
A positive rate of improvement in mortality rates is always evident! Also our projections will always be wrong even our best estimates.
describe the two deterministic models we will study
CSO method projecting mortality rates in Ireland: two factor model incorporating age and period. Its extrapolative, deterministic and targeting
UK ONS method to forecast UK population mortality: three factor model incorporating age, cohort and period. Its extrapolative, deterministic and targeting
Explain in the context of mortality what a deterministic model tells us
Means for each age x I have one mortality rate
Name the two stochastic models for projecting mortality
Lee- Carter Stochastic model for mortality projections
Coherent (Bayesian) forecasting - the UN stochastic model
What are three possible methods to forecast mortality - which si most commonly used
Mathematical model of ageing process
From a projection of factors known to significantly impact mortality
From an atheoretical extrapolation of historical patterns
Why do we not use method of mathematical model or projection of factors influencing mortality to project mortality rates
Mathematical model - No reliable model is available
Factors method - Such variables are nearly as difficult to forecast as the mortality rates. We often don’t have enough data to understand these factors association with mortality also.
Explain the method of extrapolation of historical patterns to project mortality rates
Can be stochastic or deterministic
Aggregate trend or pattern based on past data then use targetting methods
Assume a target mortality table in some future year and interpolate values between current and targeted values
Then use the parametric method to fit a curve and project trends in best-fitting parameters over time.
Why do we not use methods based on froecasting by underlying cause very often?
Its difficult to achieve success in decomposition of mortality by cause of death:
Cause of death reporting is unreliable, especially at older ages
Causes of death often act synergistically - not realistic to limit to one caus of death
Time series of data are often rather short - only been collecting data since the 1950s so for older ages there’s not much to draw on
What common features does evolution of mortality rates share across different countries
Near log linear decline of mortality rates at any age with time and the rate of decline of the mortality rate with age diminished with increasing age (it goes flat)
Wht does the extrapolative technique of projecting future rates do?
Finds and fits a relationship to past data and projects mortality assuming the relationships hold into the future with the knowledge that rates of improvement tend to increase
What is the interpretation of q x,t
The rate of mortality at age x at future time t
What two factors if q x,t usually defined on
Age and period (future year)
What is a third g=factor that can also be combiend (even though there are other variations)
Cohort - (year of birth) combination of age and period so the three factors are not independent
Summarise a one two and three factor model example
- Age
- Age and period or less commonly age and cohort
- Age period and cohort - or in actuarial applications might replace cohort with size of pension
Why is using the cohort factor tricky
Makes heavy data demands - for recent cohorts we do not have alot fo records of deaths
Cohort effects on mortality are much smaller than period effect in majority of cases, though the factor is not negligible
What was the smoking cohort?
Males born 1890 to 1910
What disadvantages does age, period, cohort model have?
Any one factor is linearly dependent on other two
Cohort effects in a model have heavy data demands - requires nearly 100 years of data to observe mortality of a cohort over all ages