Chapter 19-Set assumptions Flashcards
- Outline five key considerations in setting assumptions for actuarial work.
As in all actuarial work, when setting assumptions it is important to:
* consider the use to which the assumptions will be put
* take care over the choice of the assumptions that will have the most financial significance
* achieve consistency between the various assumptions
* consider any legislative or regulatory constraints
* consider the needs of the client.
* consider the market practice in the country
- Give four examples of where historical data can be useful in setting future assumptions.
Historical data can be helpful when choosing demographic assumptions. For example, historical levels of mortality in a country, industry or company may help with the choice of assumptions for the number of individuals who will survive to receive pensions, or for the extent to which contingent benefits will be payable. In many countries this data will have been analysed and used to produce a graduated decrement table. Past data can also be used to project future improvements in mortality.
Similarly, past data can be used when determining the probability of individuals leaving employment, becoming ill, retiring, being married or other significant life events.
In determining an assumption for future investment returns, past data on dividend yields on equities and on the total returns on relevant classes of investment may be useful. Where dividends are linked to an inflation index, past data on that index may be useful.
Past data on salary levels in a particular country, industry or company may be useful when making an assumption about future levels of salary growth. The history of an inflation index may also be useful in determining an assumption for future benefit growth that is linked either fully or partially to that inflation index.
- Give three examples of where current data can be useful in setting future assumptions.
The relationship between current yields for fixed-interest and indexlinked bonds may provide some indication of the market’s view of future levels of the inflation index to which the bonds are related.
Policy statements by governments or controlling banks may also be useful when making assumptions about economic factors.
A scheme sponsor may be able to provide information on planned future salary increases or likely future rates of withdrawal.
- In some instances, what will assumptions be defined by?
In some instances, assumptions may be defined in regulations or legislation.
- Explain why is it usually inappropriate to take an average rate from the past data and use this for projecting into the future.
It is unlikely to be sensible to take an average rate from past data and assume that it will be appropriate for projecting future experience. Past data does not provide the answer as to what will happen in the future, but simply provides information that can be considered when determining the most likely future experience.
The social and economic conditions are likely to have changed over any period of history. The actuary therefore needs to consider the conditions that will apply in the future period to which the projections will relate and how those conditions will lead to differences from the past data that is being used.
- When analysing past data, what must the relevance of that past data to future projections be balanced against?
The relevance of past data to future projections must also be balanced against the need for sufficient data for its analysis to be statistically credible. In making a judgement about future experience this conflict between credibility and relevance must be managed.
- List seven possible features of past data that the actuary may need to adjust for.
When using past data it is necessary to consider how to deal with:
* abnormal fluctuations
* changes in the experience with time
* random fluctuations
* changes in the way in which the data was recorded
* potential errors in the data
* changes in the mix of homogeneous groups within the past data
* changes in the mix of homogeneous groups to which the assumptions apply.
- Why is past economic data usually unsuitable for estimating future levels? Why is it not sensible to use economic data from a short time-frame? How might past data be amended to overcome these problems?
Economic data fluctuates with changes in economic and fiscal policy as well as with the general economic cycle. Past data for investment returns, salary levels and dividend yields in most countries fluctuate significantly over an extended time-frame. It could be thought that economic and fiscal changes mean that most past data are irrelevant and so only data that relate to a period after any recent significant change can be used. However, this would reduce the credibility of the data and increase the effect of any random fluctuation. It is necessary to use the earlier data and to try to strip out the fluctuations that relate to economic and fiscal conditions that differ from those that currently exist.
- What might past data for price inflation be used as an indicator for? What measure will give a better indicator of future price inflation?
Past levels of an index to measure price inflation usually fluctuate significantly and are often a useful indicator of the economic conditions that existed. They are therefore unlikely to be very useful in determining an assumption for future levels of inflation. Consequently, current index values may be a better guide to future levels of inflation.
For example, government projections and the ‘risk-free’ real returns indicated by the current yields on long-term index-linked bonds could be used.
- Give an example of when past price inflation data can be useful for setting assumptions.
Past data for price inflation can be very useful in determining other economic assumptions, as conversion of past economic data into real terms will often remove much of the fluctuation.
- Give an example of a fiscal change that should be allowed for when using historical dividend levels to set assumptions for future dividend levels. Explain a potential problem that arises if an explicit adjustment is made.
Dividend levels could be adjusted to allow for changes in taxation applying to those dividends. However, an explicit adjustment may be spurious, as there may be changes to the taxation of companies or individuals that have a more significant effect.
- What significant factor should be borne in mind when projecting mortality experience into the future? How does this affect the analysis?
Much of the demographic data will also be affected by economic changes. Again, explicit adjustment is difficult and so judgement and analysis of fluctuations and trends will be important.
Mortality data is mainly affected by medical advances. Past data should be considered with this in mind. This is likely to result in significant emphasis being placed on the most recent data with consideration of past trends and their underlying reasons being important in determining the extent of future change.
- Why is it important to split data into homogeneous groups? In practice, how is historical data used?
It is important that the past data used is relevant to the group of individuals about whom assumptions are to be made. Levels of salary growth and mortality, for example, usually differ by type of employment or social class. Ideally the past data would be split into homogeneous groups to reflect such differences. In practice the information necessary to split the data reliably is unlikely to be available, and splitting the data would result in a significant reduction in credibility. Therefore, past data will usually need to be adjusted in a subjective manner to allow for differences in the characteristics of the individuals concerned.
In adjusting past data it is important to recognise that the past data may give false results due to changes in the balance of homogeneous groups over time. For example, past levels of salary growth may reflect a change in the overall composition of a workforce (for example production line workers being replaced by mechanisation) rather than just the changes in real salary levels for individuals.
- What particular care needs to be taken when accessing older data produced either by the State or by companies?
Over time, statistics produced by the State or data recorded by companies may change. Such changes distort the past data and could lead to inappropriate assumptions unless these changes are recognised.
Data errors will also cause distortions but may not be as easy to recognise as changes in the ways of recording the data. Generally, the management and verification of data recorded by companies has improved significantly as the capability of computers has improved. Older data may carry a greater risk of data error, perhaps to an extent that outweighs the usefulness of having more data.
- Give two examples of one-off impacts that might invalidate the use of past data.
For example, significant returns in one year on a specific asset could be because of government intervention. High numbers of deaths could be due to an epidemic meaning that mortality experience for that year is unusually high.