August 13, 2012 

Mr. Larry Shirley 

Pension Benefit Guarantee Corporation 

1200 K Street, NW 

Washington, DC 20005 

Executive Summary 

Background 

The PBGC provides financial assistance to multiemployer (ME) plans upon insolvency to ensure 

the continued payment of benefits to retirees and their beneficiaries. PBGC insures about 1,400 

on-going ME plans and currently provides financial assistance to about ten plans. The maturing 

liabilities in most ME plans, weak portfolio returns, and the declining number of participating 

employers (sometimes the most financially healthy) is putting increasing financial stress on the 

PBGC in terms of the current and projected needs for financial assistance. Total projected 

assistance has been increasing rapidly over the past few years. The critical role of the PBGC in 

ensuring the financial well-being of members in their post-employment years is ever increasing in 

both importance and complexity, and the need for increasingly robust means of risk monitoring is 

essential to the PBGC mission. 

Statement of Work 

The PBCG engaged Buck Consultants to perform a peer review with respect to its ME pension 

insurance modeling system (ME-PIMS) to: 

• evaluate the soundness of the economic and statistical theory and actuarial principles 

that underlie ME-PIMS; 

• assess the accuracy, completeness and consistency of input data, the performance of 

data integrity checks, a review of underlying processes used to obtain the data, and a 

review of critical assumptions (e.g., parameter calibration, to confirm consistency with the 

observable market); 

• perform a robust review of critical actuarial and statistical calculations (e.g., funding 

requirements, projected contributions, plan liabilities, current and projected probability 

distributions); 

• assess the reasonableness of key assumptions used in ME-PIMS (e.g., population 

growth or decline, mass withdrawal assumptions, etc.); 
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• assess the reasonableness and accuracy of model calibration and output, (comparing 

projected vs. realized outcomes for the period that begins with the date from which the 

data is drawn to the present day); 

• benchmark (e.g., comparing the ME-PIMS actuarial valuations to those of an industryestablished actuarial valuation system), 

• stress-test (limiting-case and extreme-value testing) and perform sensitivity analysis 

(examining the degree to which model output is affected by changes in selected input 

parameters); 

• assess the degree to which the methods used to: (i) project demographic and economic 

patterns, (ii) calculate probability distributions and (iii) rank risk are based on robust 

actuarial and statistical techniques and economic theory; 

• assess the accuracy and relevancy of the information reported to management and 

whether the ME-PIMS’s reports provide reasonable and timely results, clearly and 

concisely capture critical elements for decision making, and provide an executive 

summary, a clear statement of the purpose of a particular modeling exercise, and a 

summary of major assumptions to highlight the ME-PIMS limitations; 

• recommend changes, as appropriate, to ME-PIMS data collections, programming, and 

reporting. 

Report Summary 

We would like to commend the PBGC for undertaking this effort to request an independent 

outside review of its ME-PIMS system. We appreciate that this type of examination, while 

important, also has its challenges. It is our hope that the PBGC will view our comments as they 

are intended -- to be constructive and in the spirit of a collaborative effort to improve its ongoing 

risk assessment and risk management efforts. 

As we proceeded through this review, it became apparent that our suggestions for improvement 

had a couple of main dimensions to consider. The first dimension was the necessity of a change 

to the risk measurement and management effort. The second was the feasibility of the change. 

We considered them in tandem and structured our conclusions accordingly into three main 

categories, namely: 

• Category 1 - Changes that we believe every possible measure should be taken to review 

and change the system and that we believe are doable in the short-term. 

• Category 2 - Changes that we think are important and should be made, but where we 

think they are less urgent than Category 1 when the potential effort needed to implement 

them is taken into account. 

• Category 3 – Changes that may be nice to have but that are less critical than the prior 

categories. 
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Category 1 suggestions entail areas where we believe that the ME-PIMS assumptions are not as 

realistic as they could be with respect to trends in the ME universe. The good news here is that 

in-so-far as the PBGC is in agreement with our suggestions, these changes pertain to modeling 

assumptions or reporting items that we believe can generally be made to the existing modeling 

framework and processing without undue burdens. These are areas that we believe have a high 

probability of having a material impact on PBGC’s reported financial position. 

Category 2 suggestions tend to pertain more to areas where ME-PIMS seems outdated and 

needs updating in terms of some of the models employed, and the structure and ease of use of 

the output to facilitate adequate checking of results. These may include suggestions that would 

be much more difficult, time-consuming and expensive to change, and for which we don’t have 

enough of a basis to make a reasonable judgment about whether or not such changes would 

have a material impact on results. 

Category 3 suggestions tend to be ones which, in our judgment, are worthwhile changes, but 

which are not likely to have a material impact on the results. 

It is certainly worth noting that we found many important areas where we believe the current 

system works just fine and for which we had no significant suggestions. We will summarize those 

key areas in the report as well. With respect to our suggested changes, we believe there are a 

number of detailed areas that need improvement; some of which we believe significantly 

understate PBGC’s exposure, and other areas that may well be overstating the exposure. As 

such, it is difficult for us to make a definitive statement at this time as to whether or not in the 

aggregate the current results are likely to be overstated or understated. 

The body of the report will set forth such areas noted above regarding important areas where we 

are in agreement with the current system, followed by details on our suggested improvements to 

the system and our comments regarding PBGC’s reporting of its financial position. 

Related to the above, PBGC asked Buck to comment on issues that had already been selfreported (the “Known Issues under Review for Future Maintenance/Development” document 

dated February 10, 2012). Some of these issues are covered in the main body of our report – 

many are not. However, we have included as Appendix A to the report a detailed commentary on 

these issues, insofar as we encountered such issues in our review and/or felt we had the 

wherewithal to provide such commentary. Also enclosed is Appendix B, which discusses in more 

detail Buck’s Capital Market Modeling tool which was used as the basis of comparison to the 

current modeling approach in ME-PIMS. We did not include this in an attempt to place undue 

emphasis on the capital market modeling aspect of ME-PIMS, but rather to fully inform the PBGC 

regarding the model while maintaining a more streamlined body of the report. 
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Actuarial Certification 

As consulting actuaries, Buck performs actuarial and consulting services for PBGC, both on an 

ongoing and special project basis. However, we do not have any relationship with the PBGC 

which we believe would impair or appear to impair the objectivity of our work. 

We meet the Qualification Standards of the American Academy of Actuaries to render the 

actuarial opinions contained in this report. In addition, Darren French is an Enrolled Actuary and 

an Associate of the Society of Actuaries and Kai Petersen is a Fellow of the Society of Actuaries, 

an Enrolled Actuary, and a Charterholder in the CFA Institute. 

We welcome the opportunity to discuss these results in more detail at your convenience. 

Sincerely, 

 

Kai Petersen, F.S.A., E.A., C.F.A., M.A.A.A Darren French, A.S.A., E.A., M.A.A.A. 

Principal and Investment Consulting Actuary Principal and Retirement Consulting Actuary 
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Important Areas Where We Agree 

i. Plan Sampling Method 

The ME-PIMS program runs complete projection programs on a sample of 150 out of a total 

ME universe of roughly 1,400 ME plans not currently terminated or booked, and on 23 

terminated or booked plans. We focused our review primarily on the sample of 150 on-going 

plans. That sample includes most of the largest plans in the universe of ME plans as well as 

a reasonable sample of various mid-size and smaller plans, with a weighting factor to ratio-up 

the sample results to approximate the universe of all ME plans (larger factors are used for the 

smaller plans and smaller factors are used for the larger plans). Based on the testing that 

Buck performed and our general knowledge of the ME universe, we believe that the sampling 

method provides a good balance between accuracy and efficiency. Also, based on a sample 

of 15 of the 150 plans for which Buck reviewed the results on a detailed basis, and factoring 

that up for the actual 150 plans in PBGC’s sample, we found similar answers in terms of the 

mean projected financial position using just those 15 plans as for the 150 plans. 

ii. Capital Market Models and Asset Mix 

The issues of the capital markets model and asset mix modeling are somewhat intertwined, 

and as such are discussed somewhat in tandem in this report. In general we believe that the 

type of capital markets model used by the PBGC is of the type that has been used historically 

and in that respect it is not an unreasonable approach. That said, we think that changes to 

the portfolio modeling are necessary and will have further comments on this later in the 

report. 
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Category 1 – Commentary/Recommended Changes:

i. Criteria for Booking Claims 

PBGC’s criteria for booking claims for ME plans is if a plan meets one of two tests: (1) for 

terminated plans, projected insolvency in the next 20 years, and (2) for on-going plans, 

projected insolvency within 10 years. We recognize that system constraints may effectively 

limit how many years the program can project out and still be able to run in an acceptable 

amount of time and using acceptable amounts of resources. However, since the program is 

already projecting out 20 years, and recognizing that relatively few on-going plans are likely 

to become insolvent in 10 years, but may well be likely to run dry over a longer period of time, 

it would appear to be a relatively easy improvement to use the 20 year rule for on-going plans 

as well as for terminated plans. The extra 10 years, in fact, is probably much more 

meaningful for ongoing plans than terminated plans. Ideally, we believe that the projection 

period should go beyond 20 years, as we can see many plans that may not run out of assets 

in the next 20 years and yet could represent a large and significant liability to the PBGC. If 

the programming were modernized this might be readily achievable (see the later section on 

“Use of the ME-PIMS” for more details). 

ii. Population Projection Assumptions

Overall, the stochastic model has a mean assumption of essentially no increase and no 

decline in active population in the future. Based on what we have seen historically, and what 

many plans are using for Funding Improvement Plan and Rehabilitation Plan assumptions, a 

decline seems imminent, and at least some significant decline assumption should be the 

mean result of ME-PIMS. We suggest reviewing the movement in active population in both 

the last 10 years for selected plans and for the ME universe in aggregate (if available) as well 

as perhaps select Funding Improvement Plans and Rehabilitation Plans. One assumption 

that we think might be reasonable would be a mean assumption of a 1.5% per year decline in 

future active participants among ME plans in general -- ideally such assumption would vary 

by plan, perhaps as a function of past declines, and future expected contribution increase 

rates). Based on a very simplified model and a small sample, we estimate that such an 

assumption change would increase PBGC’s projected mean net position in years 12-20 by 

something in the ballpark of 15%-20%. 

iii. Contribution Projection Issues 

One issue that we found perplexing was the fact that, while information for most plans had 

been entered into the system from the 2009 Schedule MB, the 2009 contributions from the 

Schedule MB were not used as the basis for the projections. Rather, 2007 contributions 

entered in the past from the 2007 Schedule B were used and 2009 contributions were 

projected from the 2007 actual contributions. In a sample of 15 plans that we reviewed in 

some detail (and which represent a very significant portion of the ME universe – in 2009, 

about 1.0 million active participants, 2.6 million total participants, and $90 billion in assets), 

on average the 2009 projected contributions in ME-PIMS were 23% higher than the actual 

2009 contributions reported on the 2009 Schedule MB. In reviewing the contribution 

projection methodology, we think that the level of increases factored into the programming 

are unrealistically high, especially given that, in many cases, while the contributions are 

increasing two to four fold over the next 10 years or so, the benefit accruals are being 
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drastically reduced or even eliminated. In our experience, Trustees of most ME plans will not 

approve Rehabilitation Plans with such extremes, on the basis that such draconian demands 

would result in mass exodus of employers from the plans. The disconnect stems largely due 

to the fact that ME-PIMS explicitly does not account for the “exhaustion-of-reasonablemeasures clause” (see the following section on Funding Improvement Plan / Rehabilitation 

Plan Hierarchy for more details). 

In our detailed review of 15 plans, we found the following: an average increase in 

contributions of over three-fold during the first 12 years of the projection period, from an 

average per capita of $6,600 per year going to an average of $22,000 per year, and the two 

highest going from $11,300 to $73,100 and from $15,300 to $41,800. (The per capita figures 

were derived from the total annual contributions divided by the total active participant counts.) 

Based on our experience, these figures don’t appear to be realistic, especially if participants 

are accruing little or no benefits during this period.

Our overall conclusion is that the projected contributions far exceeds what we think are likely 

expectations, and thus, based only on this one aspect, the projected PBGC liabilities would 

likely be significantly understated. For example, if the baseline contributions were reset to the 

actual amounts on the Schedule MB (i.e., 23% lower based on the sample of 15 we 

reviewed), and the annual increase rate for the first 12 years were lowered by 2% per annum 

(from an average of about 10% per annum to about 8% per annum based on our sample of 

15), we estimate an increase in PBGC’s projected mean net position in years 12-20 of 

something in the ballpark of 20%-30%. 

 

iv. Funding Improvement Plan/Rehabilitation Plan Hierarchy 

ME-PIMS has a specific six-step hierarchy for determining steps that the trustees of the plans 

are assumed to take when a plan is or is projected to be in endangered or critical status. 

While the steps appear reasonable in theory, in reality the severity of the steps, both in terms 

of annual contribution increases, as well as the benefit reductions, does not appear to us to 

be realistic or in-line with the actions we have seen ME plans actually take. One significant 

issue here is that the projection program is not accounting for the “exhaustion-of-reasonablemeasures clause” (IRC Section 432(e)(3)(A)(ii)) -- whereby the Trustees determine that any 

further “pain” to the employers or the participants will do more harm than good (i.e., if 

contribution increases are too high, companies have too much incentive to attempt to 

withdraw, and if benefits are too low, the union has little incentive to push hard in negotiations 

to keep their participants in the plan), and thus such plans are run allowing for a longer period 

than 10 years to exit critical status -- or might never exit critical status. The determination of 

when a plan’s Trustees will determine that all reasonable measures have been taken and 

thus the plan cannot exit critical status in accordance with the appropriate time frame under 

the law (without taking into account the “exhaustion clause”) is difficult to model. It is not a 

“bright-line” test and in fact is very subjective (at least with no regulations in place). However, 

not taking it into account is likely substantially understating PBGC’s liabilities. This is a key 

area where we suggest further study. 

v. Employer Withdrawal and Mass Withdrawal Methods and Assumptions 

The documentation for ME-PIMS shows a complex series of formulas to determine the 

probably of mass withdrawal occurring, based on PBGC’s experience with incidence of mass 

withdrawal in the past. The formulas seem to provide for reasonable probabilities of mass 
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withdrawal in most situations, but they are not intuitive to follow and may be needlessly 

complex, therefore perhaps resulting at times in unintended anomalies. Moreover, we believe 

that PPA-2006 may have changed the dynamics regarding the incidence of mass withdrawal, 

as PPA allows plans to go temporarily into a funding deficiency without excise tax 

consequences and effectively allows some plans to indefinitely have a funding deficiency. 

The current formulas appear to put heavy emphasis on any funding deficiency in determining 

a high likelihood of mass withdrawal. 

Once a mass withdrawal is projected to occur, ME-PIMS assumes (according to the 

documentation) that 60% of the employers stop making contributions and that only 40% 

proceed to make withdrawal liability payments. Our detailed review of 15 plans seems to 

more or less confirm that the 40% payer rate is being used by the program, though it appears 

to work off of any recent high amount (and in some cases could not be explained based on 

the documentation). While we don’t have significant experience with plans in mass 

withdrawal, we would have expected a much higher initial payment percentage. In normal 

withdrawal situations (which are often caused by bankruptcy or other severe financial 

conditions of individual employers involved), we might expect to see such high rates of nonpayment, but the mass withdrawal situation would not necessarily be triggered by employers 

at all or at least not because of any immediate financial condition of such employers. It may 

in fact be a calculated design that might help save the employers from financial ruin. 

ME-PIMS is determining the mass withdrawal payment amount as if each fund were one 

employer – given the uneven contribution base units typically seen among employer groups 

(and sometimes different contribution rates among various units or employee classes of the 

same employer), this probably understates the payment amount by perhaps 10% to 30%. 

That, combined with the 60% non-payment assumption upon mass withdrawal, would appear 

to significantly understate mass withdrawal liability payments. There does appear to be a 

decay rate after the first year, but the formula has not yet been ascertained by Buck. 

Reviewing a sample of the 15 plans, in some cases it does decay at a reasonable rate; in 

other cases it does not decay at all. The latter assumption, of course, does not appear to be 

realistic. This factor would go in the other direction from the above two factors in terms of 

impact on PBGC’s liabilities – we need to receive more information on this, and in any event, 

we believe this issue needs more study. Finally, in our experience, employers often wish to 

“settle” the withdrawal liability payments in a lump sum and the trustees are typically willing to 

do so in order to avoid any further non-payment risk, and sometimes to help short-term cash 

flow. While each fund handles the lump sum settlement issue differently, and individual 

circumstances are usually taken into account, a general rule of thumb would be for the 

settlements to discount for interest (typically at the valuation rate) and for the non-payment 

risk (at perhaps 1% to 2% per year). 
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Category 2 – Commentary/Recommended Changes: 

i. Capital Market Models and Asset Mix 

We have included a discussion of the capital markets model here in Category 1 because the 

asset modeling currently being used does not reflect current investment trends with respect 

to the breadth of asset classes that pension plans have exposure to. One way to address the 

asset breadth issue would be to buy results from a vendor that has a capital markets model 

that could be loaded into ME-PIMS. This would not require the PBGC to expend extensive 

effort building a model. Further in doing so, the PBGC may be able to upgrade its 

methodology by gaining access to a model that has some desirable features that could 

marginally improve the risk assessment. In so far as the PBGC cannot purchase results from 

a model, and therefore has to buy or build a full model, then we would move this issue to 

Category 2 to reflect the greater financial and/or work effort involved in implementation. 

The discussion below is intended to familiarize the PBGC with the type of model from which 

results could potentially be obtained. 

a. Benchmark Capital Market Model 

Buck models asset returns and interest rate environments using an economic scenario 

generator that forecasts global economic environments in terms of key economic variables, 

and then models asset class returns and term structures using the multifactor model for the 

underlying economic environments being forecasted. See Appendix B for more information 

on this model. 

Key primary simulated variables are depicted below.

b. ME-PIMS Capital Market Model 

In contrast, the ME-PIMS employs what is generally a parameter based process rather than 

an econometric model to simulate asset class returns. This general approach to capital 

market modeling has been common in the past due its relative ease of implementation. In a 

Financial Market Variables

Treasury 

Bonds Corporate 

Bonds

Equity 

Mortgage Derivatives

Backed Bonds

And CMOs

Multiple Correlated 

Common Stock Indices

Real Estate

(REITS)

Municipal 

Bonds Interest Rate 

Derivatives

Macro-Economic Variables

Unemployment 

Rate

Actual and Expected Multiple 

Inflation Indices

Nominal and Real 

GDP Growth Rate 

Market 

Indices

Financial Market Variables

Treasury 

Bonds Corporate 

Bonds

Equity 

Mortgage Derivatives

Backed Bonds

And CMOs

Multiple Correlated 

Common Stock Indices

Real Estate

(REITS)

Municipal 

Bonds Interest Rate 

Derivatives

Macro-Economic Variables

Unemployment 

Rate

Actual and Expected Multiple 

Inflation Indices

Nominal and Real 

GDP Growth Rate 

Market 

Indices
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parametric capital market model a small number of variables are used to define asset class 

returns and inter-relationships which are then processed using a program that will run 

simulations according to the parameters input. Probably the most well-known model is a 

mean variance model in which asset class means, standard deviations (proxy for risk), and 

correlations are specified and from this information, asset class and portfolio returns can be 

simulated. ME-PIMS uses returns that are based on log-normal model which is not an 

atypical parametric modeling approach. 

Chief among the advantages of a parameter based approach is its relative computational 

simplicity and ease of understanding. Also, relative simplicity does not mean that the model is 

inadequate for a particular purpose. 

Probably the most significant disadvantages are: 

1) Model parameters that reasonably reflect future, rather than past, conditions need to 

be established. 

2) Certain “real world” phenomena that may not be as fully capture as possible with an 

econometric model. Examples of this would be “fat tail” events and dynamically 

changing asset class interactions (correlations and variances) in different economic 

and capital market conditions. What we experienced in 2008 would be illustrative of 

this. 

3) It is difficult to link particular economic environments to portfolio returns, which can be 

useful in stress testing and framing discussions about risk around environments of 

varying degrees of likelihood. It is not uncommon to think of future environment in 

terms of macro- economic conditions rather than portfolio outcomes. For example a 

particular viewpoint on interest rates may be embedded with certain scenarios 

produced by the model, but these scenarios would be difficult to identify and access 

directly. One would have to hypothesize a particular impact of an economic 

environment and “mine” for asset return scenarios that match the hypothesized 

impact. 

We are not suggesting that the current model is “wrong” however it may be less robust at the 

margins with respect to accessing certain economic events and their the likelihood and 

quantifying the impact. 

Setting aside the differences in modeling and comparing the Buck and ME-PIMS model asset 

class assumptions, at a macro level we do not see out of the ordinary differences in the 

returns generated in the aggregate over the ME-PIMS modeling time horizon. The table 

below shows side by side the key capital market assumptions for ME-PIMS model and the 

Buck model. 

ME - PIMS Benchmark 20-Year Result

Equities Treasuries Cash Equities Treasuries Cash 

Arithmetic Avg. 8.56% 3.25% 3.32% 9.89% 3.93% 0.81% 

St. Deviation 20.33 7.38 1.29 17.69 6.24 0.58 
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ME-PIMS assumptions are slightly more conservative than Buck’s 2012 20-year 

assumptions. Results obtained by comparing ME-PIMS to other models might result in other 

conclusions about the relative degree of conservatism in the ME-PIMS assumptions. 

ii. Asset Mixes 

ME-PIMS assumes a 60% Equity / 40% Fixed Income asset allocation. From a historical 

perspective, this would not be considered an unreasonable asset allocation to assume if one 

endeavors to select one asset mix that would be reasonably reflective of the long term 

investment strategy of a cross-section of ME plans. However, given current day 

computational capabilities, and trends in pension investing, this approach is suboptimal. 

There is a clear trend in pension investing toward broader diversification to gain the risk 

management and return enhancing benefits of diversification. Equities, which have been 

viewed in the past as having a high potential to drive positive returns are more and more 

being viewed as contributing a disproportionate share of the risk of a portfolio. A pension 

plan’s 60% allocation on a dollar basis could be contributing 90-95% of the portfolio’s risk. 

Hence, the general move away from equities. Fixed income assets have performed relatively 

well in the past due to a secular decline in interest rates, which has given rise to price 

appreciation. This trend could reverse in the future. A view held by many (and reflected in the 

benchmark model) is that given the current low interest rate/inflation environment (by 

historical standards), it is more likely that interest rates will rise rather than fall over the longer 

term. In the shorter term, there is an acknowledgement that monetary policy decisions may 

mitigate this for a period of time. If interest rates rise as many expect them to, this will result 

in bond price depreciation. 

There is a trend toward increased geographic and asset class diversification through global 

investing (e.g. emerging markets) and exposure to various alternative asset classes and 

investment strategies such as real assets, private equity, and hedge fund strategies. This has 

implications for asset modeling in ME-PIMS. Consider the asset mixes and associated 

expected returns of several plans in ME-PIMS based on Buck’s 2012 capital market 

assumptions. As shown in the table below, there are substantial differences in expected 

returns across the various mixes when compared to the 60% equity / 40% fixed income asset 

mix assumed in ME-PIMS. Comparable differences could result when comparing ME-PIMS 

to other models as well. 
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ME-PIMS Plan #1 Plan #2 Plan #3 Plan #4

Equities 60% 52% 45% 41% 56% 

Fixed Income 40% 22% 30% 41% 41% 

Real Estate -- 18% 17% 8% -- 

Private Equity -- -- -- -- -- 

Hedge Funds -- -- -- -- -- 

Other -- 8% 8% 10% 3% 

Total 100% 100% 100% 100% 100% 

Estimated 20-Year 

Geometric (i.e. 

compounded) Average 

Annual Portfolio Return 

6.96% 7.76% 7.41% 6.98% 6.96% 

Assumptions:

Equities – U.S. Large Cap 

Fixed Income – LT Govt/Credit 

Real Estate – 50% REIT/ 50% direct investment 

Other – Hedge fund of funds assumed but could include a variety of alternative 

assets

As noted in the Known Issues Under Review for Future Maintenance /Development, the 

PBGC has access to plan-specific asset allocation data and that data has been loaded into 

ME-PIMS. At a minimum, we believe that the 60% Equity / 40% Fixed Income allocation 

needs to be revised to reflect a more typical ME pension plan asset allocation. Better yet, 

ME-PIMS should reflect plan specific asset allocations (albeit somewhat out of date due to 

changes during the run-up period in ME-PIMS). 

As previously noted, whether this issue is a Category 1 or Category 2 item will depend in part 

on implementation issues. 

iii. Non-Calendar Year Plans 

In the course of our review, we discovered some abnormalities in the projections of one or 

two plans – we were informed that, due to an oversight, the non-calendar-year plans were 

not updated with new data and that the projection results for such plans might be unreliable. 

Our review of one or two such plans bore that out – results for at least one plan did not 

appear consistent with the type of results for similarly situated calendar year plans. We note 

that one of these plans is a very large plan. 

 

iv. The Use of ME-PIMS 

In evaluating the use of the PIMS system we focused on a few primary areas, specifically: 

a. System documentation 

b. Ability to make programming changes 

c. System structure/organization 

d. Output 
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a. System Documentation 

During the course of our review of the ME-PIMS system, it was of course necessary for Buck 

to become very familiar with the use of the system and its functionality, which included 

reading and using the system documentation. The documentation is spread over quite a 

number of separate files and we believe the overall organization needs to be explained to the 

user prior to actually using the materials. Also, partly because the documentation is so widespread, the time required to get even a basic understanding of the system is somewhat 

daunting. Better organization, perhaps more of a user hierarchy and perhaps a master index 

of materials would help considerably. Once pointed in the right direction however, we found 

the documentation reasonably easy to understand and generally very extensive. 

The documentation contains very little in the way of detailed examples, which we think would 

help considerably in our understanding of the methodologies employed. Also, critical details 

were in many cases not included or were somewhat vague. Examples of this would include 

(i) details regarding how new amortization bases are set up each year, (ii) details about how 

the contributions are developed, (iii) details on withdrawal liability payment assumptions, and 

(iv) mortality and other decrement assumptions in the valuation of the liabilities. 

One area that had fairly sparse documentation and difficulty in actually attaining information 

at all is with respect to outputting of detailed interim calculation figures on both an overall 

summary level and on an individual plan level. As a result, an audit of the results is very time 

consuming, cumbersome and, in some instances, not practicable – even, it would appear, for 

internal personnel who regularly use the system. Beyond the documentation issue, we have 

additional comment below on the relative ease of checking results. 

b. Ability to make programming changes 

One fairly common theme in the answers to our questions about the system was that it 

seemed to be difficult and time consuming to make any changes to the programming – even 

changes that on the surface, at least, seem simple. It is not clear if this is due to system 

complexity or availability of programming resources. For example, when questioned on why 

2007 actual contributions were used as the basis of projection when the 2009 actual 

contributions were available, we were told it would be a big job to make such a change. 

c. System structure/organization 

In general ME-PIMS has the feel of a system that was cobbled together over time through 

various “bolt-ons” and modifications to the SE-PIMS system. As a result there seems to be 

obsolete data fields (e.g. legacy SE-PIMS data) and multiple layers of programming spread 

over several discreet jobs and systems. At some point this fragmented and disjointed 

structure can become unmanageable, difficult to follow and increasingly prone to errors. 

d. Output 

The assembling and interpreting the ME-PIMS output was analogous to assembling a jigsaw 

puzzle. First one has to collect all of the correct pieces of information (i.e. the ME-PIMS 

specific pieces) and then one had to assemble them in a way that allowed the user to attempt 

to follow the calculation logic. We realized that given the complexity of the task at hand there 

is a need for numerous data table containing input and output fields. Our system and others 
PBGC - UPDATE 

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that we are familiar with have some of the same characteristics. What would have been 

helpful would have been having a file that assembled all of the key valuation input 

components on an annual basis and then traced the key valuation calculations. This trace file 

would include for both the roll up period and the projection period: 

 Show the ME-PIMS result and the Schedule MB results to confirm adequate 

calibration 

 Year-over -year liability with gain/loss analysis 

 Asset reconciliations with gain/loss analysis and portfolio returns 

 Amortizations schedules 

 Development of contributions (minimum required funding, negotiated, FIPs, RPs, 

shown separately) 

 Funding standard account balance 

 PPA Zone determination 

 Summary plan demographics that are the basis for the liabilities 

It would also be useful to have benefit and liability traces for a given cell in the age/service 

matrix. 

v. Liability Calculation Issues 

Our comments on the liability calculation pertain primarily to the treatment of ancillary 

benefits and the calibration of the liabilities. 

Valuation of Ancillary Benefits 

As a general rule we are proponents of the practice of explicitly valuing all liabilities to the 

greatest extent possible and would suggest that the PBGC value ancillary benefits unless it 

increases runtime to untenable levels. It appears to us that ME-PIMS already calculates the 

decrements, but just does not apply them to the ancillary benefits. Since the calculation is 

substantially underway, we would ask how much additional runtime would result. 

Liability Calibration 

The liabilities in ME-PIMS are initially calculated and then calibrated, which is a common step 

in modeling, and especially necessary with ME-PIMS since the input data available is sparse. 

The current procedure of calibrating the liabilities, however, could be improved to provide 

more accurate results. 

Reviewing this for select plans, the ME-PIMS RPA ’94 current liability does correspond to the 

amounts reported on the Schedule MB. However, the actuarial accrued liability (AAL) and the 

accrued liability normal cost (NC), however, do not match the reported amounts on the 

Schedule MB. 

Our understanding of the calibration is that ME-PIMS calibrates to the RPA ’94 current 

liability due to the fact that the liabilities are reported separately for retired participants and 

beneficiaries receiving payment, terminated vested participants, and active participants. 

Once the initial liability calculation is complete, the first calibration step is to adjust the benefit 
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amount, with an adjustment subject to a maximum (e.g. 2.5%). If this calibration is 

insufficient, the plan population is shifted until the ME-PIMS calculated and calibrated liability 

matches the RPA ’94 current liability for each group. This calibration is then used for the 

actuarial accrued liability (AAL) and the accrued liability normal cost (NC). 

Several issues arise with this calibration methodology. 

1) Calibrating to the RPA ’94 current liability does not ensure calibration to the either the 

AAL or the NC. Several plans reviewed showed the calibration led to a higher AAL 

than reported on the Schedule MB. This may create a bias for higher contributions 

during the run-up years, which ultimately could lead to an overstatement of the funded 

status at time 0. While the RPA ’94 current liability may provide a basis to calibrate 

the plan liability for the various participant statuses, the AAL and NC cost should also 

be calibrated to and match the reported Schedule MB amounts. One possible 

solution, while still being an estimate and would require calibration, follows below. 

i. Use the RPA ’94 current liability to estimate the percentage of the liability for 

each status type. 

ii. These percentages could then be used to estimate the proportion of the 

liability for each status in the AAL. In the case of plans not using unit credit, 

the inactive liability could be estimated from Schedule MB line 1c(3), which is 

a unit credit measure, and then netted out from the AL shown on Schedule MB 

line 1c(1), leaving the active liability for calibration under the chosen actuarial 

cost method. The inactive liability under any cost method will not change and 

can also be calibrated. 

2) ME-PIMS currently values only retirement benefits in the determination of the liability. 

Ignoring benefits before retirement may greatly affect the level of calibration needed 

to match reported Schedule MB values, AAL and NC, and affect the accuracy of a 

plan’s benefit cash flows. Younger participants with lower service amounts show the 

largest discrepancy. A population with a heavier weighting of these participants, 

would be more likely to induce the population shift calibration measure, since the 

liability, normal cost, and the expected benefit payments for the participants will be 

understated. In fact, these participants will have no benefit payments until retirement 

eligibility is reached. Additionally, ME-PIMS allows these participants to leave under 

the other non-valued decrements on the way to reaching retirement eligibility. In doing 

this, the system is building in liability gains each year. For example, if the only preretirement decrement is withdrawal, a percentage of the individual is assumed to 

decrement each year. When moving population forward, this percentage of the 

individual leaving the plan does not receive a deferred benefit and also lowers the 

proportion of the individual remaining by the time retirement eligibility is reached, 

lowering that portion of the liability. Presumably, this proportion is replaced by new 

entrants beginning with a zero liability. 

3) Since much of the liability for the entire system is contained in several large plans, the 

steps described in (1), if possible, should be modified. Given the importance of these 

plans and the importance of the AAL and NC, more recent information should be 

requested during the run-up period for the liabilities, such as the actual split for the 

AAL among the different participant statuses. 
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Category 3 – Commentary/Recommended Changes: 

i. PBGC Financial Assistance Liability Discount Treasury Curve 

To the extent that the PBGC ME plan liability is valued on the basis of yields on fixed income 

securities, we believe that given the variety of ways that exist to approximately model full 

yield curve that liability discounting should employ full yield curves rather than a single rate. 

Further we believe that the best models have full consistency between the yield curve(s) 

used to discount liabilities and the rest of the capital markets model. A dynamic yield curve 

model should be used, and portfolio returns should reflect the yield curve dynamics on a 

scenario by scenario basis as appropriate. 

ii. Administrative Expenses Assumption 

For reasons that are not clear, plan expenses are assumed to be 5% of the benefit payments 

each year, and actual information on current plan expenses is ignored. In general, we think 

that the 5% of benefits rule is probably understating expenses and we think there are better 

methods. While we don’t necessarily expect that this will have a large impact on the results, 

we would suggest projecting from current expenses and perhaps gradually blending into a 

modeled expense, but one that is perhaps a function of participant count rather than benefit 

dollars – which in our experience is much closer to how such expenses are actually 

generated. Based on informal studies we have done, something around $100 to $200 per 

participant per year, plus PBGC premiums, would be in the right ballpark. 

iii. Correctness of Funding Standard Account Calculations 

On the inputs and run-up years, we noted inconsistencies in that the beginning of year 

funding standard account balance did match the 5500 (after rounding), but that the end of 

year balance did not. Part of the reason was the automatic five year amortization extensions 

in certain cases and the PPA-2010 amortization and asset smoothing relief. However, part of 

the reason for the difference was due to various differences within the funding standard 

account reconciliation such as the assumption regarding the timing of and the actual 

employer contribution, the normal cost, amortization charges and expenses, and the change 

in AAL from the valuation figures, as well as a sundry item. Further details can be found in 

Appendix A.
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PBGC’s External Reporting – FY 2011 Draft Report – 

Commentary/Recommended Changes: 

We reviewed the latest draft FY 2011 report which was available as of the end of June, 2012 and 

had the following comments: 

i. The projected net position of PBGC in the report (going out as far as the year 2031) is shown 

as the present value of the actual position at such point (for example, in 2031) discounted 

back to 2011. It is not clear from the presentation that this is a present value figure (as of 

2011), and we think that the natural reading of the text would suggest a non-discounted 

figure at each point in time. While there is an overall note in the appendix stating that all 

values are present values (discounted back to 2011), we think it would be best to clarify this 

important number in the main text – and perhaps even to show the non-discounted value as 

of each point in time (only discounted back to that point in time – not discounted back to 

2011). 

ii. There is no detailed discussion in the report of when claims are booked and what the “claim 

amount” means – that is, the 10 year / 20 year rules for ongoing / terminated plans and that 

the claim amount means the total present value of assistance forever for plans that are 

booked. 

iii. There is an indication in the footnotes that, in addition to information from the 5500 filings, 

that more recent information about critical/endangered status and rehabilitation / funding 

improvement plans and other additional reported information was incorporated into the 

system. While we believe that such information may well be appropriate (particularly for 

some of the larger plans), our understanding is that only one plan was specifically adjusted 

for such information in 2011. 

iv. The benefit improvements footnote should clarify that such increases are not applicable when 

the plans are projected to be endangered / critical and how that ties in with the assumption 

that every plan that ever goes into endangered/critical status is assumed to elect the fiveyear amortization extension under Section 431(d) (as the restrictions under Section 431(d) on 

benefit improvements are in effect for as long as such amortization extensions are in effect), 

and ensure that ME-PIMS programming is adjusting appropriately for these constraints. 

v. As noted earlier, while ME-PIMS appropriately assumes COLA increases in PBGC premiums 

indefinitely into the future, it does not assume any increase in maximum guaranteed benefits 

– while this clearly has a rationale, it might be worth pointing out the potential discrepancy in 

the report and perhaps showing the impact of one or two ad-hoc increases in the future.