Chapter 4 Flashcards
(40 cards)
What are three things to examine in relation to mortality
- Data from a mortality investigation
- a Probabilistic model for the data generating process - poisson/binomial
- Standard mortality/ graduated table
Explain what published life tables/ standard tables are
Based on large amounts of data from life insurance companies - Tables are usually based on mortality experience over a 3 year period where there is a reliable census and record of deaths. Describes mortality experience of a group
Given observed deaths and exposed to risk for each age and our crude estimates what do we want to check with standard tables
- Is our crude estimates consistent with our own past mortality experiences or is it changing?
Is it consistent with published life tables and if not how much does it differ?
What if you cannot find a suitable standard table to compare your data
You will have to graduate the crude rates yourself.
Why is there a need to graduate the crude estimates?
They tend to be erratic as they have been estimated independently and so have independent sampling errors. we want the true rates to be a smooth function in x
How do we know its a smooth function? For reasons learnt :)
Used for forecasting
How do we know the true mew x is a smooth function of age x
Observed that number of lives increasing in an investigation then typically the crude rates estimated trend to become smoother
Aging is a smooth process so age related mortality inherits this
Crude rates estimated at age x+1 and x-1 tell us something about true mortality rate at x
We want to forecast future mortality so we need a smooth function for this
Explain graduation
Aims to produce a smooth set of rates from the crude rates that are suitable for a particular purpose. It doesn’t make the rates more accurate or remove bias - just makes function smooth
Why in life assurance is having a smooth mortality estimate fucntion improtant?
These estimates are used to calculate premiums and reserves for policies. Irregular jumps in mortality are hard to justify to customers
What are three desirbale features of a graduation
Smoothness, Adherence to data and graduated rates that are suitable for purpose
smoothness – the graduated rates should progress smoothly, So third differences of
graduated rates small and progress regularly.
- adherence to data – the graduated rates are consistent with the crude estimates of
mortality. They give a close fit.
- the graduated rates are suitability for the purpose for which we wish to use them.
What si the criterion for smoothness of graduated quanitties
If the third differences of the graduated quantities are small in magnitude compared to the quantities themselves and progress smoothly and regularly
Explain undergraduated
Insufficient smoothing has been carried out
Explain overgraduated
Graduation process results in rates that are smooth but show little adherence to the data
Name six goodness of fit or adherence to data tests
Chi squared test
Standard deviations test
Sign test
Cumulative deviations test
Stevens sign test
Serial correlations test
When comparing the crude estimates of mortality against a standard table what is the null hypothesis
The true underlying mortality rates at each age x are the rates in the standard table
When comparing the crude estimates of mortality against a graduation what is the null hypothesis
The true underlying mortality rates at each age x are the graduated rates
What minimum amount of data do you need to use the tests to compare crude rates with standard table/ graduation
You need more than 5 deaths in each age group
What is the purpose of the whittaker-henderson method of graduation
States to choose a graduated rates that minimise the WH expression. It assigned weights to ensure the result is fit for purpose (allows for more weight on fit or smoothness as the person requires)
In life assurance vs pensions how does the suitability of a graduation change
In life assurance losses happen with premature deaths so we do not want to underestimate mortality, In pensions or annuity work losses happen with delayed deaths so we do not want to overestimate mortality
What do we also assume under H0 for tests
We assume the distribution of Dx under the null hypothesis
What is the deviation at age x
Actual deaths at age z - expected deaths at age x
What do we know about the standardised deviations?
Zx is approx standard normal for all x under CLT
The Zx’s at different ages are mutually exclusive
What is the purpose of the chi squared test
Tests for fit over age range - tests if the crude mortality rates are consistent with a standard table or the graduated rates overall goodness of fit.
What are the degrees of freedom in the chi squared test
X can be assumed to have a chi squared distribution with m degrees of freedom where m is the number of age groups - each age group has to have at least 5 death recorded. If we are testing adherence to a graduation rather than a standard table the degrees of freedom will reduce and they depend on the method of graduation
What are the problems with the chi squared test
Could be satisfied where data do not satisfy the distributional assumptions underlying it ex: few large deviations offset by a lot of small ones)
Chi squared test may fail to spot is significant groups of consecutive ages that are biased up or down
Test may fail to detect a consistent small bias in the graduation