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Turning the Tables:

Pension Tables Should Reflect Improving Mortality

by Emily Kessler

PDF version


Contingencies online exclusive

(Editor’s note: This is a longer, more detailed version of Emily Kessler’s article in the November/December 2005 print edition of Contingencies. Table II, Projected Mortality, is corrected from what was incorrectly printed in the online and print editions of the November/December 2005 issue of Contingencies.)


The 1983 Group Annuity Mortality table (GAM-83) is probably the most common mortality table used by pension actuaries; 75 percent of the plans in a 2003 Watson Wyatt survey of actuarial assumptions and funding used GAM-83 for funding calculations. However, there are three more recently published tables that warrant consideration for use in pension valuations: the 1994 Uninsured Pensioner Mortality Table (UP-94), the 1994 Group Annuity Mortality Table (GAM-94) and the RP-2000 Mortality Table (RP-2000).

Which is the most appropriate table to use? Should actuaries be moving to these new tables, or does GAM-83 still represent a reasonable expectation for most plans? What are the consequences if plans don’t use current mortality tables, and what options are open to actuaries?

Pop Quiz

Q. True or false? Most, if not all, of the youngest annuitants whose mortality experience underlies the GAM-83 table have already died.

A. True.
GAM-83 is based on group annuitant experience from 1964 –1968. The youngest annuitants in the experience bracket were age 66 in 1964; if they were alive today, they would be age 107. We don’t know for certain, but most of these annuitants are probably dead.

Unfair question? Consider this: The youngest annuitants used to build the UP-94 and GAM-94 tables were 65 in 1985. They’d be 85 today. It’s likely that half of those youngest annuitants are still alive.

The Tables

GAM-83

The GAM-83 table was constructed after a review of GAM-71 and insurer experience showed that GAM-71 was inadequate. When GAM-83 was developed, there weren’t sufficient credible data available to construct a new table, so the developers used the same annuitant mortality experience on which GAM-71 was based. This is mortality experience from 1964 to1968.

Researchers then reviewed U.S. population statistics to determine mortality improvements from 1966 to 1975. They projected additional mortality improvements to 1983 based on 1966–1975 trends, and, according to the GAM-83 report, added a 10 percent margin for conservatism to add “a degree of safety to reserves. Since mortality experience varies by company, margins should insure that the mortality table can cover the lightest mortality experience of all companies except for truly exceptional cases.”

UP-94 & GAM-94

The UP-94 table is based on uninsured pensioner experience projected to 1994. It was developed by the Society of Actuaries (SOA) to replace UP-84 after a study of 1985–1989 mortality experience of 29 retirement systems found mortality rates were between 82 percent and 86 percent of those expected under UP-84.

Similarly, the GAM-94 table is based on group annuitant experience projected to 1994. This table was developed to replace GAM-83 after a study of 1986–1990 annuitant experience showed steady declines in ratio of actual to expected (GAM-83) mortality, particularly for males.

During the development of the two tables, recent experience for uninsured pensioners was compared to recent experience for group annuitants, and no significant mortality difference was detected. Researchers compared mortality rates at ages 66–95 for group annuitants and for participants in the federal Civil Service Retirement System (CSRS), uninsured plans (24 private and one state), and the Railroad Retirement System.

Researchers found that the group annuitant and uninsured pensioner rates were quite similar (the Railroad Retirement System showed higher mortality rates). Thus, the same underlying data were used for both the GAM-94 and the UP-94 tables. Both tables were constructed as follows:

  • Rates for ages 66–95 were based on group annuitant experience data from 1985 to 1990.
  • Rates for ages 25–65 were based on 1985–1989 (retired) and 1983–1986 (active) CSRS experience. Active and retired experiences were blended for ages 51–65.
  • Rates at extreme ages (over 95 and under 25) were taken from 1990 life tables published in the Social Security Administration’s Actuarial Study No. 107. For ages 96 to 119, a maximum rate of 0.5 was set; at age 120, the rate was set at 1.0.
  • All rates were trended to 1994 based on CSRS experience and benefit weighted in construction of final tables. The CSRS data was used to trend experience because of the large database and CSRS data had been used to extend the table for active lives. The final tables (UP-94 and GAM-94) were published with Projection Scale AA. Projection Scale AA was created for these tables and is based on a blend of the CSRS and Actuarial Study No. 107 mortality reduction trends from 1977 to1993.

The only difference between the final UP-94 and the GAM-94 tables is that the GAM-94 table includes a 7 percent margin. GAM-94 was designed for insurance reserves, which need margins for deviations in blocks of business. For an insurance company, a 5 percent margin provides a 95 percent confidence level on 3,000-life block of business. The additional 2 percent margin was added to account for variations in types of work (white-collar or blue-collar), income, and geography. Also, according to the GAM-94 report, it was felt that an additional margin would be needed as tables are adopted by state insurance commissioners and aren’t changed often thereafter.

Table Nomenclature

GAM-94 Basic and UP-94 are the same table. Most users refer to the UP-94 table instead of the GAM-94 Basic table; however, the Pension Benefit Guaranty Corp. refers to the GAM-94 Basic table in its proposal to replace the GAM-83 mortality table for use with plans in distress or involuntary termination. (For more information on the PBGC’s proposed change to ERISA Section 4044 mortality, see the Federal Register, Vol. 70, No. 48, March 14, 2005.)

GAM-94 Static is the GAM-94 Basic table with a 7 percent margin. If the GAM-94 mortality table is cited without mention of whether it is static or basic, it is likely to be GAM-94 Static.

GAR-94 designates, within the insurance industry, a table used for reserving, and it implies the use of a generational table. Generational tables reflect expected mortality (with improvements) by birth cohort.

Still confused? Table 1 shows the qx, under GAM-94 Basic, UP-94, GAM-94 Static and GAR-94, for a male who is 65 years old in 2005. The GAM-94 Basic and UP-94 rates are identical. The GAM-94 Static rate is 93 percent of the GAM-94 Basic and UP-94 rates. The GAR-94 rate reflects an 11-year generational mortality improvement for the 65-year-old-male (.014535 * (.986)^11).


Male qx, Age 65 in 2005

GAM-94 Basic

UP-94

GAM-94 Static

GAR-94

0.015629

0.015629

0.014535

0.012447


RP-2000

The RP-2000 table is the only table whose underlying rates are based solely on retirement plan mortality experience. It was developed by the SOA specifically for current liability calculations. The Retirement Protection Act of 1994 (RPA 94) allowed the Secretary of Treasury to promulgate a new table for current liability purposes in 2000. The SOA conducted a study of uninsured pension plan mortality to ensure that the Treasury Department would have current information available when considering updating the table. As there was no current table based on uninsured pension data (UP-94 was based partly on group annuity experience) a decision was made to conduct a separate study.

In the construction of the RP-2000 table, data were collected from private employers (those affected by current liability provisions) for plan years ending 1990 through 1994. From the data collected, rates were constructed for employees 30 to 70 years old, healthy annuitants 50 to 100, (based on a blend of retiree and beneficiary data), and disabled retirees 45 to 100. For ages below 30, rates were extended to blend with UP-94, and for ages above 100 they were projected to a value of 0.40 at age 106 for males and 115 for females, with an ultimate rate of 1.0 at age 120.

Rates were adjusted for mortality improvement from 1992 to 2000 using the data underlying Actuarial Study No. 110 and federal CSRS data. The AA scale that had been published with the UP-94 and GAM-94 reports was also published with the RP-2000 report. The committee felt that this scale was reasonably close to what was seen in Social Security trends and consistent with other groups’ data. Although minor adjustments could have been made, they were not considered significant enough to justify a new scale.

Using Collar Type and Annuity Amount

The RP-2000 committee did analyses other than by employee, annuitant and gender; the committee analyzed data by type of collar (blue, white, or mixed), the amount of the annuity, and SIC code. The collar classification was made by plan rather than by individual. A group was considered white collar if 70 percent or more of the participants were salaried or were non-union workers, and blue collar if 70 percent or more received hourly wages or belonged to a union. If the group met neither standard, it was considered mixed-collar. Annuity amounts were classified based on the PBGC’s classification of small, medium, and large annuities: annuity values under $6,000 per year were considered small, between $6,000 and $14,400 were considered medium, and greater than $14,400 were considered large. When the analysis was done, it showed that mortality rates varied significantly by collar or by annuity amount but not by SIC code. Further analysis by SIC classification was dropped, and is not included in the final report.

The discussion of whether collar type or annuity amount (or neither) should be used to adjust mortality rates has generated controversy among actuaries. The committee that oversaw the construction of the RP-2000 table was divided as to whether collar type or annuity amount was the better adjustment factor. “The actuary should consider collar and amount differences as possible explanatory factors but should not adopt them for a specific group without careful consideration of whether the particular difference is the best predictor of mortality for that group,” says the committee’s report.

It has been noted that collar type is easier to observe, but other factors can offset the collar effect. For example, petroleum blue-collar workers have lower mortality rates than other blue-collar workers, probably due to higher income both in working years and in retirement. (And, of course, major-league baseball players and airline pilots are not typical blue-collar workers.) Benefit amounts, on the other hand, are harder to observe and use. The actuary does not know if annuitants have other sources of income. Also, inflation erodes annuity values over time; benefits that are classified as small today could have been relatively large when the annuitant retired.

The American Academy of Actuaries has recommended to the IRS and Treasury Department that tables be adopted adjusted for collar type, but not annuity amount. “Collar is a more practical and sensible proxy for the underlying characteristics that affect mortality experience in the private pension plan arena,” an Academy committee wrote in a letter to the Treasury Department. (This 2001 letter and a 2003 letter to the IRS are available on the Academy website and are cited in the bibliography at the end of this article).


Comparing the Tables

To illustrate how the tables compare, Table 1 shows the change in annuity values, deferred to age 65 (immediate if over age 65) for various ages.

* Deferred annuity (to age 65) for ages below 65; immediate annuity for ages 65 and above


There have been substantial improvements in male mortality since the publication of the GAM-83 table, particularly at the younger ages. Across the board, male annuity factors are higher under these new tables, except possibly at the very oldest ages.

Female mortality rates haven’t decreased; they’re slightly higher in the newer tables than in GAM-83. Partly, this is due to the 10 percent margin in GAM-83 (female mortality didn’t improve as much as was expected). This also reflects that GAM-83 female mortality is based on relatively little actual experience.

What does this mean for the practicing actuary? Is the GAM-83 mortality table still a reasonable mortality table for use in valuation? When considering these questions, we must look to actuarial standards of practice for guidance.

ASOP 35

Actuarial Standard of Practice 35, Selection of Demographic and Other Noneconomic Assumptions for Measuring Pension Obligations, gives very clear, specific guidance on the selection of mortality tables, as well as other demographic assumptions. (Go to www.actuarialstandards.org to read the ASOP; the following limited excerpt in no way is intended to be a substitute for the ASOP’s complete text.) Here’s what ASOP 35 says:

  • In selecting specific assumptions (paragraph 3.3.4), “The actuary should select each demographic assumption from the appropriate assumption universe. In all cases, the actuary should consider the materiality of each assumption selected and the consequences of experience deviating significantly from the selected assumption.” The ASOP goes on to list measurement-specific factors the actuary should consider, such as the purpose and nature of the measurement, any features of the plan design that influence the assumption, plan experience, and known factors that may affect future experience.
  • The “appropriate assumption universe” is described in paragraph 3.3.2 as possibly including “tables or factors particular to the given plan as well as general tables, factors, and modifications to the tables that are available to actuaries. Sources of information relevant to many demographic assumptions include…experience studies or published tables based on experience under uninsured plans and annuity contracts, or based on any other populations considered representative of the group at hand; relevant plan or plan sponsor experience, … studies or reports of the effects of plan design, specific events, … economic conditions, or sponsor characteristics … and studies or reports of general trends relevant to the type of demographic assumption in question (for example, mortality improvement in the United States).
  • Each material demographic assumption is to be evaluated for reasonableness (paragraph 3.3.5), that is, whether it’s “expected to appropriately model the contingency being measured.” It should not be “anticipated to produce significant cumulative actuarial gains and losses over the measurement period.”
  • Each demographic assumption must be individually reasonable (paragraph 3.4).
  • When looking at the mortality assumption, says paragraph 3.5.3, the actuary should consider such factors as
    • — “the possible use of different mortality assumptions before and after retirement”
      — “the likelihood and extent of mortality improvement in the future”
      — “the use of a different mortality assumption for disabled lives”
      — “the use of different mortality table for different participant subgroups and beneficiaries.”

We’ll address mortality projection later. Let’s go back to the question of whether GAM-83 is an appropriate mortality table, based on the guidance provided by ASOP 35.

First, in no way is anyone saying that GAM-83 is never an appropriate table. There are certainly circumstances in which GAM-83 will be the best choice based on the appropriate assumption universe. And there are probably circumstances in which other older, less conservative tables (GA-71, UP-84) are still appropriate.

Can it be argued that GAM-83 is the appropriate table for most plans? Consider what we know, 20 years after the publication of GAM-83:

  • Male mortality has improved significantly, particularly at the younger ages.
  • Female mortality has not improved as much, when compared to GAM-83 before the 10 percent load.

Absolute mortality rates have changed and they’ve improved (or not improved) differently for males and females; and, for each gender, differently by age. In other words, GAM-83 probably doesn’t represent, for most populations, the correct level of mortality, and even if projected, probably won’t reflect the right pattern of mortality. We shouldn’t be surprised; GAM-83 is based on mortality experience from the 1960s projected to 1983, and on mortality improvement trends from the 1960s and 1970s, with the addition of a 10 percent margin.

We recognize that GAM-83 is prescribed for the current liability calculation. And ASOP 35 notes that, when an assumption is prescribed, the actuary is obligated to use it for the purpose for which it was prescribed (paragraphs 2.6, 3.8).

But just because a particular assumption is prescribed in one calculation, ASOP 35 doesn’t say that it therefore becomes the most appropriate assumption for all the other calculations. And for good reason. Consider the following example, using the prescribed mortality for current liability and a completely hypothetical situation:

  • The secretary of the Treasury, under due consultation with those elected officials who are desperate to find ways to offset the cost of Medicare Part D, decides that the “Bubonic Plague Mortality Table, based on Italian experience in the 16th century” is the prescribed table for current liability calculations. Can you state, in your professional opinion, that this table is now a reasonable table to use for your actuarial accrued liability, FAS 87 accrued benefit obligations (ABO) / projected benefit obligations (PBO), and any other calculation for which it is not prescribed?
  • The following year, the secretary of the Treasury, in an amazing Sybil-like turn of events, and after consultation with the Pension Benefit Guaranty Council, decides that the current liability mortality table should now be the “Liberal Arts Professor with-an-increase-in-age-65-life expectancy-to-age-127- Mortality Table.” Are you now also going to state that, in your professional opinion, this table ought to be used for actuarial accrued liability, FAS 87 ABO/PBO, and any other calculation for which it is not prescribed?

This is an exaggerated example, but drawn to make a point: We use prescribed assumptions when they’re prescribed, sometimes criticizing under our breath those who prescribed them. But just because they’ve been prescribed in one circumstance doesn’t make them the best assumption in another. It doesn’t mean they aren’t, but it doesn’t mean they are.

To Project or Not to Project?

It’s not a question; it’s part of your assumptions. Mortality table construction has changed over the past 20 years. When the GAM-83 tables were created, computing systems were limited. Tables were built with substantial margins to allow not only for variation in experience, but also because programming in a new table took significant effort. And static or generational projections were rare.

However, the construction of recent tables has reflected updates in our systems and our abilities to create individual projections. The three most recent tables reflect only mortality improvements through their creation dates (1994 for UP-94 and GAM-94, 2000 for RP-2000). This is because their creators expected users to make explicit assumptions about mortality improvement. So every time actuaries use one of these tables, they must make an explicit decision about whether and how to project mortality improvements beyond the table date. In other words, by not making projections, the actuary has made the explicit decision not to assume any future mortality improvements beyond the date of the table’s creation.

Projecting Mortality: Static vs. Generational

A static table is a projection of the entire table. If the table is projected by X years then X years of mortality improvement is built in at each age. A generational table constructs separate tables for each generation (year of birth) based on expected improvements for that birth cohort. Each birth cohort gets a different projection, as this example of the two types of tables illustrates.

For any given birth cohort, there is a static table that replicates a generational table. However, for any given population, a static projection can only approximate the results from generational table. One problem with any approximation is that a different number of static years are needed to approximate generational results for normal cost versus the actuarial liability, and for different funding methods.


Table Creators’ Views on Projection

In a report on choosing between UP-94 & GAR (group annuity reserving)-94, which coincided with the publication of the UP-94 and GAM-94 tables, the actuaries responsible for their creation noted:

Though the incorporation of explicit projection scales has not previously been standard practice in the valuation of retirement plans, we believe that actuaries should carefully consider using mortality trend projection if adopting a version of the UP-94 Table. The argument for use of mortality improvement trends is bolstered by the following observations:

  • The trend of mortality improvement has been a long and relatively consistent one in the U.S. throughout this century. The length and consistency of this trend separate it from trends affecting the other experience-related decremental assumptions
  • The preponderance of scientific and demographic literature foresees continued mortality improvement, at least at some level
  • Unlike the UP-84 Table, which was issued in 1975 and projected to a future date (1984), the UP-94 Table will be issued in 1994 and incorporates no margin for mortality improvement after that date except as explicitly projected by the actuary using the table.

Similarly, in its issuance of the RP-2000 report, the committee that developed the table recommended that

... in the view of the long history of improvement in non-disabled mortality rates in all of these sets of data, pension valuations should take trends in long-term mortality improvement into account. From a theoretical standpoint, the [committee] believes that the use of generational mortality improvement, as in the GAR-94 table, is an appropriate way of reflecting this improvement. In cases where it is not material or cost effective to incorporate generational mortality improvement into a calculation, the actuary should project mortality improvement on a comparable static basis.

And finally, a recent SOA-commissioned study shows the effects of not taking mortality improvement into account. The paper examined, theoretically, what would happen to a sample plan’s funded status, contributions, and FAS 87 expense (among other measures) given known mortality improvements and different actuarial assumptions, which tracked or lagged actual mortality improvements to varying degrees.

The study by David F. Kays, which defined “ideal” assets as sufficient to cover actual mortality improvement, found that “periodically updating the mortality table assumption to reflect current mortality levels with or without mortality scale projections or using mortality projected beyond the valuation date may accumulate assets closer to the ideal assets. Consistently using mortality tables that are not current will eventually accumulate assets less than ideal.” In particular, when considering whether assets were sufficient to cover ABO with actual mortality improvement, the study said, “the greater the mortality assumption is from the experience, the less chance assets will be large enough to cover [ABO].”

In other words, for assets to accumulate to a relatively level percentage of their ideal, the mortality assumption ought to be updated periodically, and at least projected to the valuation date by the appropriate mortality improvement scales. Tables that were projected beyond the valuation date did a better job of approximating a generational table; the ideal projection point would likely vary by plan population. But as we’ve already seen, in some cases the new factors showed higher mortality than existing tables. Is there really a need to project specific improvements onto the tables?

Note that none of these most recent tables—UP-94, GAM-94 and RP-2000— would be considered to reflect current mortality experience, unless there has been no improvement in mortality between their creation dates and today. We have some evidence that mortality has improved over the past 10 years. (The creators of the RP-2000 table, which was created with data gathered six years after the UP-94 data, noted that there appeared to have been an improvement in mortality in that period that tracked Projection Scale AA; i.e., their year 2000 table tracked well against the UP-94 table with six years’ projection. These tables were based on two different populations, however, so this is a hypothesis, rather than a conclusion.)

If the tables are simply brought up to date — from their creation dates in 1994 and 2000, respectively, to 2005 — the ratio of the differences in annuity factors between GAM-83 and the projected tables comes much closer together for females, and widens even more for males. And if full generational improvements are reflected, then the mortality differences are much wider. Table 3II shows selected rates with improvement.

* Deferred annuity (to age 65) for ages below 65; immediate annuity for ages 65 and above

Note: for the generational annuity factor, the sample annuitant is assumed to be age X in 2005. The factor of 2.80 for a 35-year-old male is for a male who is 35 in 2005. The factor of 13.14 for a 65-year-old female is for a female who is 65 in 2005. Table II, Projected Mortality, is corrected from what was incorrectly printed in the online and print editions of the November/December 2005 issue of Contingencies.

So what should actuaries consider when projecting mortality? The committee that oversaw the UP-94 and GAM-94 tables recognized that many factors influence decisions to project mortality:

... the need to consider mortality improvement trends in setting assumptions should not be taken to imply that the only appropriate model is one in which mortality improvement trends explicitly appear. In determining liabilities, the actuary must also consider the actual population expected to retire under the plan, the interaction of assumptions, the relevance of various assumptions given alternate plan designs, and the significance of a particular assumption given the overall level of precision in the liability model. Thus the decision to project mortality trends explicitly or implicitly should reflect both the actuary’s estimate of the magnitude of future trends and the limitations and approximations inherent in the interaction of these trends with the actuarial model of the benefit plan. Depending on the model, a static table that includes an appropriate degree of mortality projection may be most consistent with the plan benefit and actuarial model.

Does this mean you’re always required to project mortality, and more critically, are you required to use generational mortality? Not necessarily. Each population is different. That’s where your actuarial professional judgment comes in.

Food For Thought

Let’s assume a pension plan has a normal retirement age of 65, unreduced early retirement at 62, and early retirement reduction factors of 5 percent per year before age 62. (The benefit paid at age 55 is 65 percent of the normal retirement benefit). The actuary currently uses 1983 GAM mortality, retirement rates of 5 percent per year before age 62, 50 percent at age 62, 5 percent at 63 and 64, and 100 percent at age 65. The weighted average retirement age is 61.8. Consider three changes to mortality: to RP-2000, to RP-2000 projected to 2025 and to RP-2000 generational, for each of three sample male participants, a 65-year-old (born in 1940), a 45-year-old (born in 1960), and a 25-year-old (born in 1980).

Do these assumptions seem reasonable? Consider what the change in mortality does to life expectancy:

Our sample plan, like many other plans, was designed to help move the war generation out of the work force to make way for the baby boomers. It has provided subsidized early-retirement benefits for anyone wishing to leave the workforce before age 62—subsidies worth as much as 30 percent at age 55. Our actuarial assumptions reflect that prior generations have, and future generations probably will, continue to take this early retirement subsidy.

A man who expects to live to 82 may reasonably be expected to retire at 62, particularly when there are generations of workers ready to take his job. But is it reasonable to expect that someone born in 1980, who with improved mortality would have a life expectancy of 87, to also retire at age 62? If improvements in life expectancy also bring improvements in health at older ages, might our disability rates at older ages (e.g., 50-plus) also decrease?

When projecting mortality, all things must be considered in balance: If mortality improves, what will happen to disability rates? Will retirement ages increase as people work longer, either out of necessity or desire? It’s not all that simple. You need to use your actuarial professional judgment.


Emily Kessler is the staff fellow, retirement systems, at the SOA and acts as SOA liaison to the Academy’s Pension Practice Council and Pension Committee. The views of the author are her own, and are not those of the American Academy of Actuaries, Academy, Actuarial Board of Counseling and Discipline, Actuarial Standards Board, SOA, or the actuarial profession.


Bibliography

American Academy of Actuaries, letter to the Department of Treasury on RP-2000, April 2001.

http://www.actuary.org/pdf/pension/rp2000_043001.pdf

American Academy of Actuaries, letter to the IRS on RP-2000, December 2003.

http://www.actuary.org/pdf/pension/mortality_123103.pdf

Kays, David F., Impact of Mortality Table Projection Scales on Defined Benefit Pension Plan Valuations, Society of Actuaries, 2005.

http://www.soa.org/ccm/content/areas-of-practice/retirement-
pension/research/impact-of-mortality-projection-scales-on-defined-benefit-pension-
plan-valuations/

Society of Actuaries (SOA) Group Annuity Valuation Table Task Force, 1994 Group Annuity Mortality Table and 1994 Group Annuity Reserving Table, Transactions of the SOA 1995, volume 47,865 – 919.

http://library.soa.org/library/tsa/1990-95/TSA95V4722.pdf

SOA, 1999 Annual Meeting discussion of RP-2000 table and projecting mortality.

Online at http://library.soa.org/library/record/1990-99/rsa99v25n339pd.pdf

SOA Committee on Annuities, Development of the 1983 Group Annuity Mortality Table, Transactions of the SOA 1983, volume 35, 859– 899.

SOA Committee on Retirement Systems Research and Committee on Retirement Systems Practice Education, The UP-94 and GAR-94 Tables: Issues in Choosing the Appropriate Table, Transactions of the SOA 1995, volume 47, 795 – 817.

http://library.soa.org/library/tsa/1990-95/TSA95V4720.pdf

SOA Retirement Plans Experience Committee, RP-2000 Mortality Tables, 2000.

http://www.soa.org/ccm/content/research-publications/experience-studies-tools/the-
rp-2000-mortality-tables/

SOA UP-94 Task Force, 1994 Uninsured Pensioner Mortality Table, Transactions of the SOA 1995, volume 47, 819 – 863.

http://library.soa.org/library/tsa/1990-95/TSA95V4721.pdf

Watson Wyatt, 2003 Survey of Actuarial Assumptions and Funding, 2004.


Contingencies (ISSN 1048-9851) is published by the American Academy of Actuaries, 1100 17th St. NW, 7th floor, Washington, DC 20036. The basic annual subscription rate is included in Academy dues. The nonmember rate is $24. Periodicals postage paid at Washington, DC, and at additional mailing offices. BPA circulation audited.

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November/December 2005

Enterprise Risk Management for Insurers: Actuarial Theory in Practice

Operational Risk: The New Frontier

Fundamental Changes

Social Security Reform: What's the Best Fix?

Inside Track:
Tough Love

Letters

Commentary:
Is One Euro of Actuaries Worth the Same as One Euro of Financial Economists?

Policy Briefing:
Mr. Smith Comes to the Academy

Workshop:
Turning the Tables: Mortality Tables Should Reflect Improving Mortality

Tradecraft:
Understanding Insurance, Part I: Comparing Written Premium With Paid Losses

Puzzles:
Tax Season Hiring

Endpaper:
A Tribute to My Father


Past Issues

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