November 2015

shared EXPERIENCECanadian construction industry pensioners have higher than average rates of mortality, and therefore don’t live as long as predicted by current Canadian Institute of Actuaries (CIA) mortality tables. The CIA’s 2014 Final Report on Canadian Pensioners’ Mortality included this conclusion among its findings.

However, the report also indicated that the analysis may not be fully reliable due to limited industry-specific data. As you’ll read in our report, Eckler’s Construction Trades Mortality Study came to the same conclusion, drawing on a much larger amount of construction industry pensioner data than was available for the CIA report.

Actuarial professional standards call for the CIA mortality tables to be used in pension plan valuations, unless a plan or industry has better quality and more credible data and analysis which support a different assumption. However, overly conservative mortality assumptions can drive a pension plan’s expected costs up – and could lead plans to inequitably shift costs from one generation of members to another. With this in mind, Eckler undertook a large-scale study to examine the mortality experience of Canadian construction trades pensioners.

Eckler has a long history of working with multi-employer pension plans (MEPPs) in the construction trades and other industries. In fact, we’ve been consulting with MEPPs since the first such plans were introduced in the 1940s. This wealth of experience gives us vital insights into the unique issues – including predicting life expectancy – faced by these plans. Equally important, it provided us with access to the breadth and depth of data needed to more properly study this issue. We compiled information on construction trades pensioners from 43 MEPPs, representing:

• $4,510,000,000 in total annual pension exposure;• $107,000,000 in annual pension for actual deaths;• 390,000 life year exposures; and• 12,400 actual deaths.

The data that Eckler has compiled is roughly four times the size of the construction industry pensioner data included in the CIA’s report. This gives our results significant credibility. And, it gives trustees of participating pension plans valuable analysis to use for adopting appropriate mortality assumptions.

In this report, we present our findings and discuss important implications for plan trustees and actuaries working with construction industry MEPPs. We’re proud to be able to lend our expertise to the industry through this study. And, we’d be pleased to help interested trustees determine how best to apply this analysis to their plans.

Sincerely,

Cameron HunterEckler Ltd.

Mark DavisEckler Ltd.

Domenic BarbieroEckler Ltd.

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TABLE OF CONTENTS

Section 1. EXECUTIVE SUMMARY ....................................................................................................................... 1

Section 2. OUR PURPOSE AND BACKGROUND ................................................................................................ 3

Section 3. THE IMPORTANCE OF CREDIBLE ASSUMPTIONS .......................................................................... 6

Section 4. A BIGGER AND MORE RELEVANT DATA SET ............................................................................... 10

Section 5. OUR FINDINGS .................................................................................................................................. 21

Section 6. ADDITIONAL OBSERVATIONS ......................................................................................................... 30

Section 7. OPINION ............................................................................................................................................. 38

Section 8. REPORT PEER REVIEW .................................................................................................................... 39

Appendix A. LIST OF PARTICIPATING PLANS ..................................................................................................... 40

Appendix B. CREDIBILITY METHODOLOGY ......................................................................................................... 41

Appendix C. PLAN- AND TRADE-SPECIFIC RESULTS ........................................................................................ 43

Canadian pension plan members are living longer than previously estimated. Many have long suspected this. And the Canadian Institute of Actuaries’ (CIA) 2014 Final Report on Canadian Pensioners’ Mortality (CPM) confirmed it, presenting Canadian mortality tables to replace the outdated U.S. information previously used by Canadian actuaries. This is good news for pensioners, and a testament to improvements in public health, medicine and lifestyles. But for pension plans, it means higher future pension costs.

With a better understanding of current and future pensioners’ life expectancy, pension plans can estimate future costs with a greater degree of certainty. Eckler’s study set out to do this for multi-employer pension plans with construction trades members – a group identified in the CIA report as having higher than average mortality rates – and lower than average life expectancies. Our research indicates that, overall, actual construction trades pensioner deaths measured by amounts of pension are almost 15% higher than predicted by the CIA’s new 2014 CPM mortality table for private sector plans (CPM2014Priv mortality table).

Our purpose and backgroundThe CIA report noted that Canadian construction industry pensioners have higher than average rates of mortality, and therefore shorter average lifespans than predicted by the CPM2014Priv table. This suggests it may be reasonable to make adjustments to the mortality rates in the CPM2014Priv table for valuing construction industry plans. However, the report also indicated that the analysis may not be fully reliable due to the limited industry-specific data. Actuarial professional standards call for the use of CIA mortality tables in valuations unless a plan has more credible plan- or industry-specific data which support the use of a different table or an adjustment to the CIA table. Construction trade multi-employer pension plans (MEPPs) that adopt the CIA’s new CPM2014Priv mortality table for their valuations could see their liabilities increased by 10% or more, due to longer expected payout periods. Eckler’s study bridges this gap by measuring the construction industry’s mortality experience using a larger and more credible industry-specific dataset than was included in the CIA’s report.

The importance of credible assumptionsThe CIA report indicated that the actual mortality of construction industry pensioners is, on average, 12.5% higher for males (and 17.5% for females) than predicted by the CPM2014Priv table. Eckler’s study investigates whether a larger amount of industry data leads to similar conclusions, and whether the level of actual mortality varies significantly between different construction trades.

Using a mortality table that does not properly reflect plan members’ expected life spans can lead to inaccurate calculations of a plan’s cost of benefits, liabilities and funding position. Benefit reductions that are implemented to fix a poor funded position driven by higher estimated costs and liabilities could be greater than required. Likewise, if estimated costs and liabilities are lower than they should be, any benefit improvements implemented could end up being too generous. Therefore, a ‘best estimate’ of future mortality is key to effective MEPP management, and to achieving equity between different groups – and generations – of members.

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executive SUMMARY

A bigger and more relevant data setIn any study, credibility of results is linked directly to the relevance, quantity and quality of data used. We received data from 44 defined benefit MEPPs with members in a Canadian Building Trades Unions (CBTU) affiliated union, covering the period 2002 to 2012. We tested all data received for reasonableness and consistency and ultimately accepted data from 43 plans for our study. This gave us a pool of pensioner data roughly four times the size of the industry-specific data included in the CIA report. The participating plans represent 16 trades and pensioners from across Canada, although most are in Alberta, British Columbia and Ontario.

Our findingsOur study confirms that, on average, construction trades pensioners have higher rates of mortality, and therefore shorter life expectancies than predicted by the CPM2014Priv table. We analyzed pensioner deaths based on both annual amounts of pension and number of lives. Our findings show that the overall A/E – or actual/expected – ratio of actual construction industry pensioner deaths to those predicted by the table is 114.9% measured by the former, and 122% by the latter. On the face of it, a 15% increase could be applied to the base CPM2014Priv mortality table for valuing construction industry plans. However, we also found considerable variance in the A/E ratios amongst the different trades. Therefore, in making an adjustment to the CPM2014Priv table for valuation of a particular construction trade MEPP, it may not be appropriate to refer only to the percentage indicated for all construction trades in aggregate. Individual plans can consult the plan- or trade-specific findings in this report when considering whether – and to what extent – mortality table modifications are appropriate for their valuations.

Additional observationsStudying mortality improvements among construction industry pensioners was not the primary focus of our study. We believe proper analysis of this would require an even greater amount of data than we have been able to gather. However, our research indicates that improvements in mortality for construction trades pensioners over our study period were, on average, about 20% lower than predicted by the “CPM scale B” mortality improvement scale presented in the CIA report. This is consistent with other research indicating a widening gap in life expectancy between white collar and blue collar workers. If this observed lower mortality improvement is accurate, it indicates that our study should be updated periodically.

Our analysis also looks at differences between the commuted value amounts calculated for terminating plan members, based on the mortality assumption that will be required to be used in these calculations for all plans, and mortality assumptions that may be considered more appropriate for members of many construction trades MEPPs. We believe the actuarial profession should give further consideration to allowing for reasonable and supportable adjustments to different plans’ commuted value mortality assumptions.

The bottom line is that the CIA’s introduction of Canadian-based mortality information for pension plan valuations is a positive step forward. However, many construction trade plans that adopt one of the new CIA mortality tables without modification will see a greater increase in plan costs and liabilities than may be necessary, given the pensioner longevity they are expected to experience in future. Our analysis allows construction trades plan sponsors to make more accurate mortality assumptions, manage their plan with better information, and better protect pensions for current and future generations.

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Section 2. OUR PURPOSE AND BACKGROUND

Canadian Institute of Actuaries’ Report on Canadian Pensioners’ Mortality In February 2014, the Pension Experience Subcommittee of the Canadian Institute of Actuaries (“CIA”) released its Final Report on Canadian Pensioners’ Mortality (the “CPM Report”).1 The CPM Report presented the findings of a review of a subset of Canadian registered pension plans (“RPP Study”) in conjunction with a separate review of mortality experienced under the Canada Pension Plan and the Quebec Pension Plan2 (“C/QPP Study”). These reviews indicated that Canadian mortality experience is different from the United States experience that had often been referenced to value the liabilities of Canadian pension plans. Based on the RPP Study, the CPM Report presented gender-specific mortality tables constructed from public and private sector data, as well as a combined table. The CPM Report also presented a two-dimensional (by age and year), “generational” mortality improvement scale, referred to as CPM Scale B, based on experience from the C/QPP Study and assumptions in the 26th CPP Actuarial Report.3 Subsequent to the release of the CPM Report, the CIA’s guidance to actuaries for setting mortality assumptions4 has stated that:

“published mortality studies provide substantial information to assist the actuary in determining the best estimate of current levels of mortality, particularly if plan experience is not credible.”

“at this time, use of the UP94, the GAM94 or the RP-2000 table, including Scale AA projections up to the valuation date, as a best estimate of current mortality rates would only be appropriate if supported by credible experience, the characteristics of the specific plan under review, or other quantifiable evidence.” 5

1 Canadian Pensioners’ Mortality; Final Report published the CIA’s Pension Experience Subcommittee – Research Committee, (Canadian Institute of Actuaries, February 2014): https://www.cia-ica.ca/docs/default-source/2014/214013e.pdf?sfvrsn=4. 2 Louis Adam, The Canadian Pensioners Mortality Table, Information on mortality for the triennial period ending December 31, 2007 with data as at December 31, 2008 (Canadian Institute of Actuaries, May2012): http://www.cia-ica.ca/docs/default-source/2013/213003e.pdf 3 Office of the Chief Actuary, Actuarial Report (26th) on the Canada Pension Plan as at 31 December 2012 (Office of the Superintendent of Financial Institutions, Canada, November 2013): http://www.osfi-bsif.gc.ca/Eng/Docs/cpp26.pdf. 4 Canadian Institute of Actuaries’ Committee on Pension Plan Financial Reporting, Selection of Mortality Assumptions for Pension Plan Actuarial Valuations, Revised Educational Note (Canadian Institute of Actuaries, March 2014): https://www.cia-ica.ca/docs/default-source/2014/214029e.pdf?sfvrsn=0. 5 Ibid, p. 5-6.

The CIA report noted that Canadian construction industry pensioners have higher than average rates of mortality, and therefore shorter average lifespans than predicted by the CPM2014Priv table. This suggests it may be reasonable to make adjustments to the mortality rates in the CPM2014Priv table for valuing construction industry plans. However, the report also indicated that the analysis may not be fully reliable due to the limited industry-specific data. Actuarial professional standards call for the use of CIA mortality tables in valuations unless a plan has more credible plan- or industry-specific data which support the use of a different table or an adjustment to the CIA table. Construction trade multi-employer pension plans (MEPPs) that adopt the CIA’s new CPM2014Priv mortality table for their valuations could see their liabilities increased by 10% or more, due to longer expected payout periods. Eckler’s study bridges this gap by measuring the construction industry’s mortality experience using a larger and more credible industry-specific dataset than was included in the CIA’s report.

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In practice, actuaries have taken this to mean that in the absence of quantifiable evidence supporting the use a different assumption, an actuary would currently be expected to reference a mortality table presented in the CPM Report when setting the mortality assumption for a Canadian defined benefit pension plan. In this Construction Trades Mortality Study (CTMS) Report, we refer to the CIA’s public sector, private sector and combined tables as the CPM2014Publ, CPM2014Priv and CPM2014 tables, respectively. Unless otherwise noted, the tables are understood to include generational mortality improvement projection using CPM Scale B. The impact of adopting the CPM2014Priv table as the mortality assumption for the actuarial valuation of a defined benefit MEPP, or any defined benefit pension plan, varies according to the specific characteristics of the plan being valued and the mortality assumption currently being used. For instance, prior to the release of the CPM Report it would be quite common for the mortality assumption adopted for a MEPP’s valuation to be based on the 1994 Uninsured Pensioner (“UP94”) Mortality table, with mortality improvements projected to a certain year using Scale AA, or with generational mortality improvements using Scale AA. The impact of adopting the CPM2014Priv table, without any modification, would typically be an increase in such a plan’s liabilities (present value of benefits earned up to the valuation date) by 4% to 10% or more and an increase in the plan’s current service cost (present value of benefits expected to be earned in the year following the valuation date) by 1% to 2% more than the percentage increase in liabilities. Purpose of This Construction Trades Mortality Study The purposes of this study and CTMS Report are:

to compile a larger and more credible body of construction industry pensioner mortality experience data than was included in the CPM Report, and to compare deaths and survival patterns predicted by the CPM2014Priv table with the actual deaths and survival patterns observed over a particular period of time in the construction industry pensioner mortality experience data we have compiled; and

to analyze and report on information relevant for the actuary in setting the mortality assumption for valuation of a construction trade MEPP, and to the Board of Trustees of such a MEPP in assessing the level of any margins for conservatism included in the mortality assumption.

This analysis is intended to be used to assist actuaries advising construction trades MEPPs and Boards of Trustees of construction trades MEPPs participating in the study and their actuaries when considering whether, and to what extent, modifications to the base CPM2014Priv table are appropriate in the valuation of their plan.

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The analysis includes the calculation of A/E Ratios, which could be referenced for purposes of making an adjustment to the CPM2014Priv table mortality rates. To be clear, our analysis was not undertaken to prepare a customized mortality table as an alternative to CPM2014Priv table for the construction industry, but instead to provide credible support for adjustments to the CPM2014Priv table. Likewise, although there is commentary included in Section 6, in respect of the use of CPM Scale B for purposes of calculating expected construction trades pensioner deaths based on the CPM2014Priv table adjusted to the prior years studied in this CTMS Report, this report makes no commentary and draws no conclusions on the appropriateness of using CPM Scale B to project improvements in mortality beyond 2014. Reliance We have relied on pensioner membership information provided by construction trades plans that participated in the study. This information was generally derived from membership information prepared for valuation purposes for actuarial valuations prepared between December 31, 2001 and December 31, 2012 or, in the case of some participating plans, a subset of that time period. The information submitted by each participating plan was reviewed for internal consistency and reasonableness. Further details on the processes used for compiling and reviewing data submitted are provided in Section 4. A list of participating plans is provided in Appendix A.

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Section 3. THE IMPORTANCE OF CREDIBLE ASSUMPTIONS

Mortality Rates and Rates of Mortality Improvements An individual in receipt of a pension from a pension plan, who we generically refer to as a “pensioner,” has an expectation that their pension will be paid for as long as they are alive. The pension plan itself expects to pay pensions to a cohort of pensioners as long as any member of the cohort is alive (with the total amount paid reducing as time passes and as the number of members expected to be alive is reduced). In measuring the pension plan’s obligations, the pension plan’s actuary must therefore model the survival patterns of cohorts of pensioners, and in preparing such a model the actuary makes use of a mortality table. The mortality table sets out rates at which death is expected to occur among members of the cohort. Prior to the release of the CPM Report, mortality assumptions used in the going concern valuation of construction trades MEPPs have typically been based on the 1994 Uninsured Pensioner Mortality Table, projected forward to a certain year using mortality improvement projection Scale AA to reflect future improvements in mortality (e.g., “UP94@2015” refers to the 1994 Uninsured Pensioner Mortality Table projected forward to 2015 using Scale AA; “UP94 Generational” refers to the 1994 Uninsured Pensioner Mortality Table with future generational mortality improvement projected forward using Scale AA). Other tables or modifications to the “UP94” table (e.g., rates derived from the UP94 table, adjusted by a set percentage or a fixed age set-back or set-forward) have also been used. On a solvency valuation basis, the UP94 Table, with generational mortality improvement projection (“UP94 Generational”) is currently most typically used. A mortality table such as UP94@2015 is referred to as a “static” table, in that mortality rates for pensioners depend solely on the age of the pensioner. A “generational table,” such as UP94 Generational, incorporates improvements in mortality based on a certain scale, such that the resulting mortality rates depend on both the age of the pensioner and the year in which they achieve that age (or, equivalently, the year in which the pensioner was born).

The CIA report indicated that the actual mortality of construction industry pensioners is, on average, 12.5% higher for males (and 17.5% for females) than predicted by the CPM2014Priv table. Eckler’s study investigates whether a larger amount of industry data leads to similar conclusions, and whether the level of actual mortality varies significantly between different construction trades.

Using a mortality table that does not properly reflect plan members’ expected life spans can lead to inaccurate calculations of a plan’s cost of benefits, liabilities and funding position. Benefit reductions that are implemented to fix a poor funded position driven by higher estimated costs and liabilities could be greater than required. Likewise, if estimated costs and liabilities are lower than they should be, any benefit improvements implemented could end up being too generous. Therefore, a ‘best estimate’ of future mortality is key to effective MEPP management, and to achieving equity between different groups – and generations – of members.

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For example, consider two pensioners: one attains age 60 in 2020, while the second attains age 60 in 2030. Assuming the UP94@2015 mortality table, both pensioners are expected to be subject to the same mortality rate (i.e., probability of death in the year) because they are both age 60. Assuming the UP94 Generational table, the pensioner who attains age 60 in 2030 is expected to be subject to a lower mortality rate, reflecting an expectation of improving mortality between 2020 and 2030. The anticipated mortality improvement reflects an extrapolation of past trends and, at a practical level, anticipates continued improvements in health care, medical technology, lifestyle factors, protections from environmental hazards, etc. Consider a group of 1,000 male pensioners, all of whom retire at age 60 in the year 2015. The following graph illustrates the expected pattern of survival, referencing the UP94@2015, UP94 Generational, CPM2014Priv and CPM2014 mortality tables:

The CPM2014Priv table predicts that a larger proportion of the 1,000 original members of the cohort will survive to any later age than the portion assumed to survive according to the patterns predicted by both the UP94@2015 and UP94 Generational tables. For example, the UP94@2015 table predicts the number of pensioners surviving to age 80 at about 657, versus 701 assuming the UP94 Generational table, 755 assuming the CPM2014Priv table and 785 assuming the CPM2014 table. In setting a mortality assumption for valuation of a pension plan, the focus is on how long the particular plan is expected to be required to pay these 1,000 pensioners, and the mortality table is the model used to predict the decline of the cohort. The risk to the pension plan is that if the model’s prediction does not reflect what will actually transpire, then the plan’s liabilities calculated in the actuarial valuation will be (a) too high – and the plan’s funded position consequently understated – if pensioners actually die sooner, on average, or (b) too low – and the plan’s funded position consequently overstated – if pensioners actually survive longer, on average. Similarly, with all non-mortality experience exactly matching the assumptions made, benefit reductions that may be determined to be necessary by a Board of Trustees to remedy a plan’s adverse financial position, may turn out to be (a) too aggressive, if pensioners actually die sooner than the model predicts, or (b) not aggressive enough, if pensioners survive longer than the model predicts. Further, longevity experience takes a long period of time to emerge and to provide complete insight into the accuracy of the mortality assumption made. These factors indicate the importance of mortality assumptions to understanding the funded status of a pension plan, and to related issues such as intergenerational equity between a plan’s current and future membership groups.

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Expected survival of 1,000 males retiring at age 60 in 2015

UP94@2015 UP94 Generational CPM 2014 Private CPM 2014 Combined

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The purpose of this CTMS Report, as stated above, is to compare the expected rates of deaths and survival patterns predicted by the CPM2014Priv table with the actual deaths observed and survival patterns implied over a period of time by the construction industry pensioner mortality experience data compiled. If the actual survival patterns among a construction industry plan’s or plans’ pensioners, or a subset of such plans, are different than those anticipated by the CPM2014Priv mortality table, then it may be appropriate to make an adjustment to that table in determining the mortality assumption to be used in the valuation of such plan or plans. The CPM Report and Construction Industry Plans In the CIA’s RPP Study, pensioner mortality data compiled from a number of single-employer pension plan (“SEPP”) and/or MEPP participants in the construction industry were combined with pensioner mortality data from other private sector pension plans, for purposes of deriving the CPM2014Priv table to predict mortality within the private sector. Construction industry pensioner mortality data submitted in constructing the CPM2014Priv table amounted to exposures of about 90,000 pensioner life-years, or approximately $1,070,000,000 in annual pension exposure, out of a total of about 963,000 pensioner life-year exposures, or approximately $10,519,000,000 in annual pension exposure.6 The CPM Report includes analysis indicating the actual mortality of male construction industry pensioners to be 112.5% (117.5% for females) of the expected mortality based on the CPM2014Priv table, indicating the levels of mortality of construction industry pensioners included in the RPP Study data to be higher – and thus the longevity of those pensioners shorter – than predicted using the CPM2014Priv table. This finding is consistent with analysis from pensioner mortality experience studies that Eckler has conducted for some large construction trades MEPPs in the past, specifically that the levels of mortality observed in these plans was higher than predicted by the standard mortality tables commonly used for Canadian pension plan valuations at the time. Regarding the experience by industry, the CPM Report indicates that:

“Generally, there are insufficient data to develop mortality tables by industry. However, the subcommittee’s observations may be useful to actuaries where specific plan experience or similar plan experience is not available. The subcommittee has prepared a workbook which contains A/E ratios by quinquennial age groups for each sector and industry. Note that the A/E ratios are not equally credible for all industries, nor by age groups within industry. Accordingly the subcommittee urges caution in the use of the information.” 7

6 Supra note 1, Table 2 (data included for private sector pensioners). 7 Supra note 1 “Appendix 2: Experience By Industry.”

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To summarize, there are a number of issues that an actuary should consider in setting the mortality assumption for a construction trade MEPP:

the starting point for setting the mortality assumption for valuing the MEPP is now expected to be mortality rates presented in the CPM Report, most likely the CPM2014Priv table rates;

the actuary may suspect that the MEPP’s pensioners actually experience a materially different level of mortality than that predicted by the CPM2014Priv table rates;

the CPM Report provides data indicating that the mortality of construction industry pensioners included in the RPP Study data was higher than that predicted using the CPM2014Priv table, but notes that such data should be used with caution as it may not be based on a sufficiently large amount of data to be credible; and

in any event, it is not known how similar – or dissimilar – the particular MEPP may be to the construction industry plans whose data were included in constructing the CPM2014Priv table.

Developing Best Estimate of Future Mortality The CIA’s guidance for setting mortality assumptions indicates that the first step in developing an appropriate best estimate of future mortality is to determine the best estimate of current levels of mortality. The best estimate would be developed considering the plan’s actual mortality experience (where available), the credibility of such plan experience, the experience of similar plans, published mortality studies, and possible adjustments based on characteristics such as “collar type,” industry and pension size. If the best estimate of current levels of mortality is derived from an analysis of actual experience, appropriate adjustments would be made to project mortality rates to the valuation date. The guidance also indicates that a key consideration in developing a best estimate of current levels of mortality for a particular pension plan is the size of the plan and the amount of data available to the actuary. While it is preferable to reflect actual credible experience of the plan under review, rather than to rely solely on published mortality studies or adjustments thereto, the guidance recognizes that sufficient plan experience may not be available in all cases. The guidance indicates that:

“very large plans,” for example those with 10,000 or more pensioners, may use mortality tables customized to reflect the experience of the specific plan using percentage adjustments to the standard table mortality rates or may, in some cases, have sufficient data to prepare plan-specific mortality tables.

“mid-sized plans,” for example those with 1,000 to 10,000 pensioners, would not have “fully credible” mortality experience, but would have sufficient data to develop broad adjustments (e.g., 90% or 110% of the standard table rates) or, in some cases, to develop different adjustment factors for a range of ages.

“small plans,” for example those with 100 to 1,000 pensioners, may not have sufficient data to conduct a credible mortality experience study but it may be useful to examine experience gains or losses related to pensioner mortality in prior valuations, for an indication of the validity of the mortality assumption and any trends in mortality experience.

for “very small plans,” for example those with only a few pensioners, an appropriate published mortality table should be selected, adjusting for the characteristics of the plan, if warranted. 8

8 Supra note 4, pages 3-4.

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Section 4. A BIGGER AND MORE RELEVANT DATA SET

In any study, credibility of results is linked directly to the relevance, quantity and quality of data used. We received data from 44 defined benefit MEPPs with members in a Canadian Building Trades Unions (CBTU) affiliated union, covering the period 2002 to 2012. We tested all data received for reasonableness and consistency and ultimately accepted data from 43 plans for our study. This gave us a pool of pensioner data roughly four times the size of the industry-specific data included in the CIA report. The participating plans represent 16 trades, and pensioners from across Canada, although most are in Alberta, British Columbia and Ontario.

Data Collection The CTMS Report analysis is based on data supplied by the plan administrators of Canadian defined benefit MEPPs with members in the construction trades industry. Any Canadian defined benefit MEPP with members in a union affiliated with the Canadian Building Trades Unions (CBTU) and electing to participate and submit data to the study was accepted for participation.9 Data requests and collection occurred between January 2014 and November 2014. We reserved the right to exclude individual records, entire years of exposure, or entire plan datasets if we were not satisfied that the data were sufficient and reliable for the purposes of this study. We received data from 44 participating plans, representing data for construction trades pensioners across Canada. There are some national plans represented in our data (those having members working in more than one province), however, the majority of participating plans have all active members working in the provinces of Alberta, British Columbia and Ontario and are thus registered in those provinces.10 For each year included for observation in the study, we requested details of retiree deaths during the year and retired members alive at the start and end of the year. We did not request data for non-retired members because we believed the number of such pre-retirement deaths would not have been sufficiently large to provide meaningful results. Although we received data for spouses of retired members from some plans, we excluded these data from our analysis because we believed that spouses' dates of death are not always available in those situations where the spouse predeceased the retired member. The exclusion from our data and analysis of pre-retirement member deaths and of pensioners’ spouses is consistent with the development of the CPM tables and thus, we believe, the preferable methodology for this study.

9 Submitted data includes participation of one plan that covers construction industry workers but is a single employer, jointly trusteed plan, and is not a MEPP. See Appendix A for further details. General references made in this report to “MEPPs” are not intended to infer that the results and commentary in this report are not applicable to this plan. 10 Specifically, this means that active plan members are union members of a local whose jurisdiction is solely within one province. Active members in these plans may periodically work in other locals’ jurisdictions, including jurisdictions in another province, through reciprocal arrangements.

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We requested data for calendar years 2002 to 2012 (the “study period”). More specifically, from each participating plan we requested that data include a listing of pensioners in receipt of a pension as of December 31, 2012 (or December 31, 2013, if available), and a listing of pensioners deceased in each year dating back to January 1, 2002. To assist in validating the data provided, we also requested membership extracts from actuarial valuation reports, and, where readily available, data at each actuarial valuation date (or calendar year-end) during the study period. We requested that the data for each retired member include the following items: a unique identifier, gender, date of birth, date of retirement, date of death (if applicable), form of pension payment, amounts of pension payable prior to age 65 and after age 65, province or postal code, an indicator showing if the record is for a member or for a surviving spouse, and an indicator of post-retirement health and/or dental benefit coverage. Some contributors were not able to provide data for all years in the study period. Their partial datasets were included in the study. Amount of Data Compiled in This Study The data compiled for construction trades pensioners in this CTMS Report includes approximately:

$4,510,000,000 in total annual pension exposure, as compared with approximately $1,070,000,000 in the CPM Report from the construction industry

$107,000,000 in annual pension for observed deaths, as compared with approximately $27,000,000 in the CPM Report from the construction industry

390,000 life year exposures, as compared with approximately 90,000 included the CPM Report from the construction industry

12,400 observed deaths, as compared with approximately 3,200 in the CPM Report from the construction industry

As the body of data compiled in this study for construction trades pensioners is roughly four times the size of the construction industry pensioner data included in the CPM Report, the construction industry experience is significantly more credible than that found in the CPM Report. Put another way, if the CIA’s guidance for setting mortality assumptions, described in Section 3, was applied to this construction industry data as representative of a single plan, then that data could be considered fully credible for purposes of developing a best estimate of current levels of mortality. Data Review and Validation The study is based on data supplied by MEPP administrators. We subjected each submitted dataset to a number of tests for reasonableness and consistency, including, without being limited to, the following:

that a retiree’s current age and age at retirement are within a reasonable range;

that a retiree’s age at death (if applicable) is within a reasonable range;

that dates of retirement precede dates of death for deceased pensioners;

that dates of birth and retirement for each retiree remain unchanged from one exposure year to the next;

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that dates of death do not precede the start of the study period or extend beyond the end of the study period;

that amounts of pensions in pay remain unchanged or change by a reasonable amount (e.g. reasonable increases or decreases related to known plan provisions) from one exposure year to the next;

that a retiree’s gender did not change;

that all additions to the retiree exposures observed in a specific exposure year are due to new retirements in that year;

that all deletions from retiree exposures observed in a specific exposure year are due to deaths occurring in respect of retirees alive at the start of that exposure year, or retired in that exposure year prior to the recorded date of death; and

that duplicate records are identified and removed, or combined where appropriate.

Plan administrators were provided with a query report on the results of our data verifications where there were questions resulting from the reasonableness and consistency checks noted above. They either confirmed the data provided or advised of the necessary adjustments to the data. Where such confirmations were not provided or adjustments were not provided, the related data were either excluded or were adjusted (see Data Selection and Modification below). Based on our tests for reasonableness and consistency we were not able to use the data submitted by one participating plan; thus our study included data submitted for 43 plans. We are satisfied that the data are sufficient and reliable for the purposes of this study. However, since the study results are dependent on the accuracy of the data supplied, the results will differ to the extent that the underlying data are inaccurate or incomplete. It should be noted that if any data or other information are found to be materially inaccurate or incomplete, our calculations and conclusions may need to be revised. Data Selection and Modification Each dataset received for the study in respect of a participating plan was appended with a code to indicate plan name and type of construction trade. Records with dates of death prior to January 1, 2002 were excluded from the study. Records for pensioners with ages at retirement less than 50 (fifty) were excluded. These represented approximately 0.7% of pensioner data received, by number of lives, and we believed such records could be primarily related to members receiving a disability pension until normal retirement age or surviving spouses receiving a pre- or post-retirement death benefit but incorrectly coded as pensioners. Unresolved records – those in respect of pensioners that exited the study data without a date of death being provided – were queried with the plan administrator and either resolved or excluded from the study. In instances where an indication of death was provided without a specific date of death, the administrator was asked to confirm that the death had occurred during the study period and to narrow down the period (i.e., calendar year or years) during which the death occurred, to the extent possible. In such cases, we assumed the death occurred at the mid-point of the confirmed period. In the case of one plan’s submission, where we were unable to assign a small portion of the known deaths to a time period more specific than the entire study period, we proportionally increased the actual observed pension amounts of death by the pension amounts of those deceased members. We do not believe that such adjustments, where a specific

13

date of death could not be verified, have resulted in a material impact on the study results, since the total amounts of pension for such deaths is less than 0.02% of total amounts of pension for deaths where a date of death was provided. We received data from study contributors either by each calendar year or each valuation period within the study period, or by data listings that included current and historical pensioners and deaths. In order to improve the consistency of the pension exposure measurements, we chose to focus solely on lifetime pension amounts in pay. Accordingly, to the extent possible we removed any known temporary pension amount (bridge, or similar temporary pension amount under a “notched” or “level income” payment option) in the data provided, both for deceased pensioners and pensioners that survived the study period. The resulting lifetime pension amounts were further modified for deceased pensioners to be consistent with surviving retiree exposures in plan-specific circumstances of full or partial benefit indexation (which do occur but are not common amongst the participating plans), or where pension amount increases or reductions became effective for a particular plan during the study period. In a few cases, a small number of records for pensioners were submitted with no pension amounts indicated. We queried all missing pension amounts with the respective plan administrator and either confirmed the amount or we assigned the average pension amount for that plan. We believe the overall effect on the study results due to these adjustments would be immaterial. Incurred But Not Reported (“IBNR”) For some participating plans, the data that were provided included 2013 exposures and deaths. However, in our preliminary analysis we found that the observed number of deaths in 2013 were materially lower than in the preceding years for most of these plans, which we believe results from there being pensioner deaths that had occurred but had not yet been reported to the administrator when the data were compiled. Therefore, we did not include data for observation year 2013 in our final results. This is consistent with the CPM Report, for which data were submitted in 2010, with the last observation year being 2008. Consistent with the CPM Report as well, we applied IBNR factors to make a provision for deaths which have occurred but were not yet reported at the time that the data were submitted. The IBNR factors which were applied to increase both the number and amount of deaths reported in each observation year are shown in the table below. These factors are the same as referenced in the CPM Report.11

IBNR Factors Year 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 IBNR 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 0.20% 0.40% 0.80% 1.20% 2.00%

11 For the CPM Report, data were contributed in 2010 with 2008 as the last year of experience. In this CTMS Report, data were contributed in 2014 with 2012 as the last year of experience. We have applied the same IBNR factor as used in the CPM Report for a year of experience that is x years before 2010, to a year of experience in the CTMS Report that is x years before 2014. For example the IBNR factor of 2.00% applied to 2012 data in this CTMS Report is the same as the IBNR factor of 2.00% applied to 2008 data in CPM Report.

14

Limitations or Anomalies in Data Submitted We recognize that, for a small number of pensioners, withdrawal from the study prior to the end of the study period for reasons other than death can occasionally occur. For example, when a pensioner returns to work, some plan provisions provide for suspension of the pensioner’s pension for the duration of such resumed employment. In these cases, the plan records submitted for purposes of the mortality study may not be fully updated to indicate the reason for that suspension. However, we believe that such occurrences are relatively rare. Another limitation exists where a pensioner may be receiving benefits from more than one plan (within the same trade or possibly a different trade). If this person then dies, there could be duplication of that exposure. We have no ability to eliminate any such duplication, should it occur, because we could not rely on the existence of consistent unique identifiers being used among the participating plans. However, we believe that such occurrences would have a minimal impact on the results of the study. Codes were included in the data to indicate the form of pension being paid. We did not adjust pension amounts to a common form of payment, nor did we study experience separately by form of payment. This is consistent with the methodology used in the CPM Report. Data Summaries The data compiled for construction trades pensioners in this CTMS Report includes approximately:

$4,510,000,000 in total annual pension exposure

$107,000,000 in annual pension for observed deaths

390,000 life year exposures

12,400 observed deaths We present below a number of detailed summaries of the data compiled, with commentary. For an explanation of terminology such as exposures and observed deaths, please refer to Section 5.

15

Table 4.1 below provides, for each observation year, the number of pensioners (receiving a pension at any time during the year), the average age at retirement and average annual pension. Data for male and female pensioners are aggregated; however, the female pensioners’ data represent only about 0.8% of the total number of lives in this study and this low proportion would be reasonably consistent among all participating plans.

Table 4.1: Retiree data by observation year

Year Number of

Retirees Average Age at

Retirement Average Annual

Pension 2002 22,850 61.6 $8,571 2003 25,086 61.9 $8,879 2004 26,412 61.3 $9,198 2005 31,621 61.7 $9,385 2006 33,151 61.6 $9,736 2007 39,669 61.5 $10,999 2008 41,218 61.6 $11,394 2009 43,031 61.5 $11,777 2010 45,132 61.2 $12,208 2011 46,501 61.6 $12,490 2012 47,957 61.3 $12,731

Table 4.2 below provides the total exposures (by annual pension and number of pensioners) related to pensioners exposed to death in each year of the study and the total deaths (by annual pension and number of pensioners) for those pensioners who died in each year of the study. The charts below Table 4.2 present the same information in graphical form.

Table 4.2: Exposure data by observation year

Exposure Pensioner Deaths Year Annual Pension Number Annual Pension Number 2002 $200,179,097 22,132 $4,988,826 700 2003 $225,746,917 24,220 $5,172,458 719 2004 $247,241,716 25,503 $6,063,133 789 2005 $302,696,070 30,655 $7,463,835 961 2006 $329,959,146 32,146 $7,798,360 996 2007 $445,126,792 38,490 $10,275,860 1,234 2008 $477,381,848 39,940 $10,672,711 1,250 2009 $513,594,521 41,412 $12,176,917 1,322 2010 $559,347,468 43,670 $13,822,206 1,417 2011 $588,430,029 44,998 $13,793,555 1,440 2012 $620,330,742 46,469 $15,179,922 1,548 Total $4,510,034,346 389,633 $107,407,783 12,377

16

The total exposure and deaths, measured by annual pension amount, approximately tripled from 2002 to 2012, while the number of lives exposed and the number of pensioner deaths more than doubled over the same period. The increase in exposures and deaths over the study period, whether measured by amount of pension or number of lives, is a result of both an increasing number of pensioners for all plans and the fact that, for some of the participating plans, the first year for which data were reported was later than 2002. Twenty-one plans, out of the total 43 plans for which data were included, reported data for the entire 2002 to 2012 period. A majority of plans (35) contributed data for the eight-year period 2005 to 2012, or longer. There was a proportionately greater increase in exposures and deaths, measured by amount of pension, than the increase in exposures and deaths, measured by number of lives. This was due to the increase in average pension per pensioner over the period.

$0.0

$2.3

$4.6

$6.9

$9.2

$11.5

$13.8

$16.1

$0

$100

$200

$300

$400

$500

$600

$700

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

Dea

ths

(mill

ions

)

Expo

sure

(mill

ions

)

Pension amount data by year

ExposureDeath

01803605407209001,0801,2601,4401,6201,800

05,000

10,00015,00020,00025,00030,00035,00040,00045,00050,000

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012D

eath

s (li

ves)

Exp

osu

re (

live

s)

Headcount data by year

ExposureDeath

17

Table 4.3 below summarizes the total exposures and deaths (by annual pension and number of pensioners) by age band.

Table 4.3: Data by quinquennial age groups

Exposure Pensioner Deaths Age Annual Pension Number Annual Pension Number < 55 $38,623,948 3,104 $533,046 39 55-59 $370,297,406 24,096 $4,228,684 311 60-64 $1,147,060,694 71,917 $13,799,592 964 65-69 $1,299,143,714 103,582 $18,874,221 1,713 70-74 $857,317,735 84,718 $21,259,091 2,330 75-79 $491,474,289 57,979 $21,075,298 2,713 80-84 $224,270,203 30,657 $16,113,232 2,337 85-89 $67,337,851 10,808 $8,415,905 1,371 90-94 $12,792,426 2,383 $2,620,362 487 >= 95 $1,716,079 390 $488,352 112 Total $4,510,034,346 389,633 $107,407,783 12,377

Approximately 73% of the exposure data by amount of pension (67% by count) is comprised of exposures for pensioners aged 60 to 74. Not surprisingly, the deaths are skewed towards older ages, with approximately 80% of the death data by amount of pension (85% by count) occurring between ages 65 to 89.

18

Exposures and deaths are shown separately by construction trade in Table 4.4. The chart below Table 4.4 presents the exposures and deaths by amount of pension by construction trade in graphical form. Actual names of the trades are not indicated in this report for reasons of confidentiality. All participating plans receive, with their copy of the CTMS Report, Appendix C which summarizes the exposure and death data and related A/E ratio analysis for their plan, and all plans within that plan’s trade.

Table 4.4: Exposure data by construction trade

Exposure Pensioner Deaths

Trade Annual Pension Number Annual Pension Number A $9,637,378 2,266 $337,674 93 B $9,679,756 821 $277,672 28 C $11,458,212 834 $446,142 32 D $55,713,209 15,654 $1,204,638 433 E $70,034,665 8,349 $968,963 175 F $109,327,567 23,996 $3,121,124 864 G $142,093,196 7,939 $4,035,037 337 H $150,827,277 13,675 $3,650,823 425 I $151,726,712 24,026 $4,454,582 836 J $239,722,836 8,147 $6,332,251 278 K $321,796,840 37,732 $7,213,110 1,256 L $529,766,251 31,384 $11,799,953 962 M $571,739,217 48,459 $10,991,792 1,177 N $577,646,380 41,120 $15,772,192 1,419 O $743,233,047 48,621 $16,997,460 1,499 P $815,631,803 76,610 $19,804,371 2,563

Total $4,510,034,346 389,633 $107,407,783 12,377

$0.0$2.5$5.0$7.5$10.0$12.5$15.0$17.5$20.0$22.5

$0$100$200$300$400$500$600$700$800$900

A B C D E F G H I J K L M N O P

Dea

ths

(mill

ions

)

Expo

sure

(mill

ions

)

Pension amount data by trade

ExposureDeath

19

Table 4.5 summarizes the total exposures and deaths (by annual pension and number of pensioners) by province in which the active members are working.12 Plans with active members working in union locals that are situated in more than one province are grouped under “National” in this table. Approximately 51% of the total exposure (by amount of pension) is derived from plans which have all active members working in Ontario and approximately 29% of the total exposure (by amount of pension) is derived from plans which have all active members working in British Columbia or Alberta.

Table 4.5: Exposure data by province of jurisdiction

Exposure Pensioner Deaths Province Annual Pension Number Annual Pension Number AB $666,862,923 78,723 $14,830,216 2,257 BC $639,983,024 77,970 $18,281,090 2,759 NL $43,294,752 5,006 $734,950 110 ON $2,291,832,719 177,617 $52,459,177 5,575 National $868,060,928 50,317 $21,102,350 1,677 Total $4,510,034,346 389,633 $107,407,783 12,377

12 Specifically, this means that active plan members are union members of a local whose jurisdiction is solely within one province. Active members in these plans may periodically work in other locals’ jurisdictions, including jurisdictions in another province, through reciprocal arrangements.

20

Table 4.6 summarizes the total exposures and deaths (by annual pension and number of pensioners) by province in which the pensioners reside. Approximately 65% of the total exposure, by amount of pension (54% by number of lives) is represented by Ontario pensioners and approximately 29% of the total exposure, by amount of pension (38% by number of lives) is represented by British Columbia and Alberta pensioners. It was noted in the CPM Report that data were composed primarily of pensioners located in British Columbia, Nova Scotia and Ontario, although we do not know if that observation applied equally to the construction industry pensioner data. This does not appear to be too dissimilar from the CTMS Report data, although this study includes a relatively greater amount of data for Alberta pensioners and a relatively lesser amount of data for Nova Scotia pensioners.

Table 4.6: Exposure data by province of residence

Exposure Pensioner Deaths Province Annual Pension Number Annual Pension Number AB $722,782,078 78,615 $16,219,798 2,286 BC $601,702,227 68,244 $16,425,501 2,359 MB $32,604,562 4,759 $1,035,653 173 NB $48,810,482 3,268 $690,221 74 NL $25,550,648 3,871 $353,784 90 NS $76,228,862 7,461 $1,318,673 187 NU/NT $206,152 74 $2,443 1 ON $2,920,017,566 211,025 $68,681,409 6,737 PEI $1,889,975 297 $46,779 7 QC $10,093,479 1,407 $311,507 55 SK $46,648,460 5,956 $1,196,733 215 YT $1,387,771 261 $66,129 15 Outside Canada $17,278,384 3,622 $520,367 117 Unknown $4,833,699 775 $538,785 60 Total $4,510,034,346 389,633 $107,407,783 12,377

21

Section 5. OUR FINDINGS

Our study confirms that, on average, construction trades pensioners have higher rates of mortality, and therefore shorter life expectancies than predicted by the CPM2014Priv table. We analyzed pensioner deaths based on both annual amounts of pension and number of lives. Our findings show that the overall A/E – or actual/expected – ratio of actual construction industry pensioner deaths to those predicted by the table is 114.9% measured by the former, and 122% by the latter. On the face of it, a 15% increase could be applied to the base CPM2014Priv mortality table for valuing construction industry plans. However, we also found considerable variance in the A/E ratios amongst the different trades. Therefore, in making an adjustment to the CPM2014Priv table for valuation of a particular construction trade MEPP, it may not be appropriate to refer only to the percentage indicated for all construction trades in aggregate. Individual plans can consult the plan- or trade-specific findings in this report when considering whether – and to what extent – mortality table modifications are appropriate for their valuations.

Methods and Terminology In our analysis, we compared observed pensioner deaths experienced in each study year by participating plans against expected deaths calculated in each study year by applying the CPM2014Priv table mortality rates to the pensioner exposures in that year. More specifically, expected deaths in a given year are based on mortality rates taken from the CPM2014Priv table, which has a base year of 2014, and adjusted to the specific observation year using mortality improvement scale CPM B. Base mortality rates corresponding to the CPM2014Priv table, and applicable for years prior to 2014 (back to 1999) have been provided by the CIA, using a methodology which removes an appropriate amount of mortality improvement from the base year 2014 rates, based on the generational CPM Scale B. Thus, the expected deaths in the periods 2002, 2003, 2004, etc. were based on the CPM2014Priv table rates, adjusted to base years 2002, 2003, 2004, etc. The intent is to provide results of analysis from which a percentage adjustment factor to the CPM2014Priv table could be determined that best reflects the actual experience of a plan or plans under consideration. For instance, a ratio of actual to expected deaths (“A/E Ratio”) equal to 110% for a particular plan indicates that the actual deaths over the period studied were 10% higher for that plan than the deaths predicted by the CPM2014Priv table (adjusted to calculate expected deaths in each observation year, as described above). As noted in Section 2, the analysis is not intended to be used to create plan-specific or industry-specific mortality tables or to develop an adjustment to the improvement scale.

22

We note that the CIA’s guidance on the selection of mortality assumptions for pension plan valuations indicates:

In using experience studies to establish tables for actuarial valuation purposes, determining results weighted on benefit amounts (or liability), rather than on number of lives, generally yields more appropriate results. Results based on number of lives may yield appropriate results for plans with flat dollar benefit formulas and/or with relatively homogeneous membership characteristics. 13

For this study, data have been gathered and analyzed for pensioner deaths and exposures, based on both annual amounts of pension and on number of lives. Given the guidance noted above, we tend to place greater emphasis in this study on results based on amounts of pension. However, the determination of which measure is most appropriate to reference, in relation to a particular plan, is left to the user of this report. Below we provide a brief description of some of the foregoing terminology: Exposure – Exposure is calculated using the “scheduled exposure method” as the amount of pension in pay (where analysis is based on benefit amounts) or the number of person-years (where analysis is based on number of lives) at each age (i.e., the number of people in the data who, during the study period, spend time at that age; or, in the case of analysis based on benefit amounts, the amounts of pension paid to such people). Actual (or Observed) Deaths – The amounts of pension that were being paid to pensioners who died (where analysis is based on benefit amounts) or the number of observed deaths (where analysis is based on number of lives) within the age group based on the data provided. Observed deaths are grouped consistently with the exposure groupings. Expected Deaths – The amount of pension paid to pensioners expected to die (where analysis is based on benefit amounts) or the expected number of deaths (where analysis is based on number of lives) according to the mortality table rates. Expected numbers or amounts of death are calculated by multiplying the exposure at the given age by the probability of death at the given age. In our analysis expected deaths are calculated based on the CPM2014Priv table mortality rates. Again, expected deaths are also grouped consistently with the exposure groupings. A/E Ratio – The ratio of Actual Deaths (by amount of pension or by number) to Expected Deaths (by amount of pension or by number) expressed as a percentage. An A/E Ratio of 100% indicates that actual deaths matched expected deaths. An A/E Ratio greater than 100% indicates that the actual deaths exceeded the deaths predicted by the mortality table rates. Conversely, an A/E Ratio less than 100% indicates that the actual deaths were less than the deaths predicted by the mortality table rates. Unless otherwise indicated, an A/E Ratio displayed in this report is understood to be the ratio of observed deaths to the deaths predicted by the CPM2014Priv table (with mortality rates from that table adjusted to calculate expected deaths in each specific observation year).

13 Supra note 1, page 4.

23

The data for participating plans were analyzed separately, grouped by trade (for each trade represented by one or more participating plans) and for all plans in aggregate. We have observed significant differences in A/E ratios between some of the trades and/or participating plans. Thus, users of this CTMS Report should consider whether the results of this CTMS Report in aggregate are appropriate for purposes of selecting a mortality assumption (e.g., determining an adjustment to the CPM2014Priv table) for any given plan. As well, we note that data submitted for any given plan in our study would generally not be considered fully credible on its own, for purposes of determining an adjustment to the CPM2014Priv table, specific to that plan. For instance, as noted earlier the CIA’s guidance indicates that the experience of very large plans, for example those with 10,000 or more pensioners, could be considered fully credible and the experience of mid-sized plans, for example those with 1,000 to less than 10,000 pensioners, would not be considered fully credible but would nonetheless provide useful information and trends from which broad adjustments to published tables may be developed. There are no plans in our study with more than 10,000 pensioners; however, the study includes 16 plans with more than 1,000 pensioners. To assist the users of this report in assessing the credibility of the data used, our analysis includes credibility measures. A description of the methodology used to determine such credibility factors is provided in Appendix B. Illustrations of possible methods for applying the derived credibility factors, for purposes of setting a mortality assumption, are provided in Appendix C. Approximately 0.1% of the total exposures in our study by amount of pension were in respect of female pensioners. Given the very low proportion of female workers’ pension amounts and lives in the construction trades, and the related low credibility of these data, we have not displayed analysis separately between male and female pensioners. The expected deaths calculated for purposes of the analysis have reflected sex-distinct mortality rates based on the sex of the pensioner indicated in the pensioner record. Appendix C, which is provided to each participating plan, provides the results of our analysis:

for that plan; and

for all plans in that plan’s specific trade,14 including the particular participating plan.

14 where the trade was represented by more than the particular participating plan.

24

Analysis and Observations Data for all participating plans in aggregate and the calculated A/E Ratios (by amount of pension and by number of lives) is shown in Table 5.1 below. The chart below Table 5.1 represents A/E Ratios calculated by year in graphical form.

Table 5.1: Experience by observation year

Amount of Annual Pension Number of Lives

Year Exposure Actual

Deaths Expected

Deaths A/E

Ratio Exposure Actual

Deaths Expected

Deaths A/E

Ratio 2002 $200,179,097 $4,988,826 $4,413,215 113.0% 22,132 700 581 120.5% 2003 $225,746,917 $5,172,458 $4,911,499 105.3% 24,220 719 632 113.8% 2004 $247,241,716 $6,063,133 $5,299,194 114.4% 25,503 789 664 118.9% 2005 $302,696,070 $7,463,835 $6,450,329 115.7% 30,655 961 799 120.2% 2006 $329,959,146 $7,798,360 $7,023,042 111.0% 32,146 996 844 118.0% 2007 $445,126,792 $10,275,860 $9,114,292 112.7% 38,490 1,234 993 124.3% 2008 $477,381,848 $10,672,711 $9,784,548 109.1% 39,940 1,250 1,034 121.0% 2009 $513,594,521 $12,176,917 $10,455,322 116.5% 41,412 1,322 1,074 123.2% 2010 $559,347,468 $13,822,206 $11,387,036 121.4% 43,670 1,417 1,136 124.8% 2011 $588,430,029 $13,793,555 $11,994,802 115.0% 44,998 1,440 1,174 122.7% 2012 $620,330,742 $15,179,922 $12,677,316 119.7% 46,469 1,548 1,215 127.5% Total $4,510,034,346 $107,407,783 $93,510,594 114.9% 389,633 12,377 10,144 122.0%

100%

105%

110%

115%

120%

125%

130%

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

A/E Ratio by year

PensionNumber

Total

PensionNumber

122.0%

114.9%

25

Our analysis indicates an overall A/E Ratio of 114.9%, measured by amount of pension, and 122.0%, measured by number of lives, indicating that the actual deaths (whether measured by pension amount or number of lives) exceeded the deaths predicted by the mortality table rates. In turn, an A/E Ratio of greater than 100% implies a lower expected longevity for construction trades pensioners than that predicted by the CPM2014Priv table. This finding is reasonably consistent with construction industry analysis provided in the CPM Report, which indicated the actual mortality of male construction industry pensioners to be 112.5% (117.5% for females) of the expected mortality based on the CPM2014Priv table.15 Thus, both this CTMS Report analysis and the CPM Report analysis are consistent in indicating the levels of mortality of construction industry pensioners to be higher – and the longevity of those pensioners lower – than predicted using the CPM2014Priv table. As noted in Section 3, the CIA’s CPM Report indicated that, although the data provided on actual to expected (A/E) mortality ratios may be useful to actuaries where specific plan experience or similar plan experience is not available, industry-specific information in the CPM Report should be used with caution due to the limited amount of data it was based on. We note that the findings in this CTMS Report are based on approximately four times the amount of data for construction trades’ pensioners than were referenced in the CPM Report, and thus are substantially more credible in respect of construction industry pensioners in aggregate. Overall, the A/E Ratios by amounts of pension are less than the A/E Ratios by number of lives, which indicates that, in general, lower levels of mortality are associated with higher amounts of pension. This is consistent with the CIA’s CPM Report findings. Further analysis and commentary on this relationship is found in Section 6. We note the CIA’s guidance that it is generally preferable to determine mortality table adjustments or assumptions using experience study results weighted on benefit amounts since the impact is on a plan’s liabilities. Table 5.2 provides the A/E Ratio analysis broken down by age bands. The chart below Table 5.2 provides the derived A/E Ratios graphically for ages 55 and higher.

Table 5.2: Experience by quinquennial age groups

Amount of Annual Pension Number of Lives

Age Exposure Actual

Deaths Expected

Deaths A/E

Ratio Exposure Actual

Deaths Expected

Deaths A/E

Ratio < 55 $38,623,948 $533,046 $166,754 319.7% 3,104 39 13 294.3%

55-59 $370,297,406 $4,228,684 $2,515,850 168.1% 24,096 311 163 191.2%

60-64 $1,147,060,694 $13,799,592 $11,634,611 118.6% 71,917 964 739 130.3%

65-69 $1,299,143,714 $18,874,221 $18,233,334 103.5% 103,582 1,713 1,485 115.4%

70-74 $857,317,735 $21,259,091 $18,527,055 114.7% 84,718 2,330 1,870 124.6%

75-79 $491,474,289 $21,075,298 $18,136,724 116.2% 57,979 2,713 2,177 124.6%

80-84 $224,270,203 $16,113,232 $14,333,761 112.4% 30,657 2,337 1,990 117.4%

85-89 $67,337,851 $8,415,905 $7,218,994 116.6% 10,808 1,371 1,172 117.0%

90-94 $12,792,426 $2,620,362 $2,239,147 117.0% 2,383 487 421 115.8%

>= 95 $1,716,079 $488,352 $504,366 96.8% 390 112 113 99.0%

Total $4,510,034,346 $107,407,783 $93,510,594 114.9% 389,633 12,377 10,144 122.0%

15 Supra note 1, Appendix 2.

26

We observed quite high ratios below age 55. This was also observed in the CPM Report (see Table 4 and Table 5 in the report on that study). These high ratios observed below ages 55 (and possibly below age 60 to some extent), while calculated in respect of a relatively small amount of data, may be influenced by there being plan members included in these data who may be disabled and qualified for a disability pension, or members with impaired health who are unable to work and have elected early retirement. The drop in the A/E Ratio at ages greater than 95, while noteworthy, is based on a relatively small amount of data and therefore not very credible. The A/E Ratios for all groups ages 60 to 94 appear to be reasonably close to the overall A/E Ratio. Therefore, the relative differences between actual mortality rates observed for construction trades pensioners at different ages appear to be consistent with the relative differences between the CPM2014Priv table mortality rates at different ages. In other words, the “slope” of the actual and expected mortality rates by age appear to be similar, with the actual rates being at a higher level than the expected rates. However, we would expect the gap between the higher construction trades’ mortality rates and expected rates to lessen with age, consistent with other research studies. Thus, an actuary may consider whether or not to make adjustment for the expected decline in A/E Ratios at elevated ages, taking into account the A/E Ratio derived over all ages and the related adjustment being considered. Table 5.3 and 5.4 provide the A/E Ratios by jurisdiction and by residence.

Table 5.3: Experience by province of jurisdiction Amount of Annual Pension Number of Lives

Province Exposure Actual Deaths Expected

Deaths A/E

Ratio Exposure Actual

Deaths Expected

Deaths A/E

Ratio AB $666,862,923 $14,830,216 $12,168,132 121.9% 78,723 2,257 1,706 132.3% BC $639,983,024 $18,281,090 $15,479,799 118.1% 77,970 2,759 2,189 126.1% NF $43,294,752 $734,950 $552,088 133.1% 5,006 110 86 126.8% ON $2,291,832,719 $52,459,177 $48,710,871 107.7% 177,617 5,575 4,885 114.1% National $868,060,928 $21,102,350 $16,599,704 127.1% 50,317 1,677 1,278 131.2% Total $4,510,034,346 $107,407,783 $93,510,594 114.9% 389,633 12,377 10,144 122.0%

0%

25%

50%

75%

100%

125%

150%

175%

200%

55-59 60-64 65-69 70-74 75-79 80-84 85-89 90-94 >= 95

A/E Ratio by age

PensionNumber

27

Table 5.4: Experience by province of residence

Amount of Annual Pension Number of Lives

Province Exposure Actual

Deaths Expected

Deaths A/E

Ratio Exposure Actual

Deaths Expected

Deaths A/E Ratio AB $722,782,078 $16,219,798 $13,212,222 122.8% 78,615 2,286 1,746 130.9% BC $601,702,227 $16,425,501 $14,382,859 114.2% 68,244 2,359 1,911 123.5% MB $32,604,562 $1,035,653 $675,064 153.4% 4,759 173 118 147.0% NB $48,810,482 $690,221 $663,727 104.0% 3,268 74 66 112.1% NF $25,550,648 $353,784 $382,257 92.6% 3,871 90 77 118.0% NS $76,228,862 $1,318,673 $1,064,321 123.9% 7,461 187 143 130.8% NU/NT $206,152 $2,443 $4,435 55.1% 74 1 2 51.0% ON $2,920,017,566 $68,681,409 $61,424,508 111.8% 211,025 6,737 5,761 116.9% PEI $1,889,975 $46,779 $41,392 113.0% 297 7 10 71.0% QC $10,093,479 $311,507 $207,451 150.2% 1,407 55 35 160.0% SK $46,648,460 $1,196,733 $921,678 129.8% 5,956 215 151 142.5% YT $1,387,771 $66,129 $29,584 223.5% 261 15 6 255.5% Outside Canada $17,278,384 $520,367 $402,285 129.4% 3,622 117 97 120.4% Unknown $4,833,699 $538,785 $98,810 545.3% 775 60 22 274.1%

Total $4,510,034,346 $107,407,783 $93,510,594 114.9% 389,633 12,377 10,144 122.0% As noted above, the overall A/E Ratios amongst construction trades pensioners is 114.9%, measured by amount of pension. We observe some variance by province of residence, although for the provinces with highest credibility (Alberta, British Columbia and Ontario) the A/E Ratios are rather tightly confined in the range of just over 110% to just over 120%. We cannot say that the types of plans or trades represented by Ontario pensioners are similar in composition to those represented by, for instance, Alberta pensioners. Therefore, because there is not a homogeneous representation of the different plans and trades across all provinces, we don’t believe our analysis should be interpreted to provide a valid mortality adjustment factor by province.

28

Table 5.5 provides the A/E Ratios calculated by trade. The chart below Table 5.5 provides a graphical representation of the A/E Ratios calculated by trade. As previously noted, actual names of the trades are not indicated in the body of this CTMS Report for reasons of confidentiality. Note that the “credibility factor” included in this table is a measure used to quantify the extent to which a particular outcome can be relied upon, as unique from an outcome deemed to be typical. For further discussion and details of the development of credibility factors for this analysis, please refer to Appendix B.

Table 5.5: Experience by trade

Amount of Annual Pension Number of Lives

Trade Exposure Actual Deaths Expected

Deaths A/E

Ratio Credibility

Factor Exposure Actual

Deaths Expected

Deaths A/E

Ratio A $9,637,378 $337,674 $210,842 160.2% 22.3% 2,266 93 62 151.6% B $9,679,756 $277,672 $282,930 98.1% 13.4% 821 28 28 100.4% C $11,458,212 $446,142 $353,828 126.1% 16.0% 834 32 25 128.9% D $55,713,209 $1,204,638 $1,424,556 84.6% 47.9% 15,654 433 444 97.6% E $70,034,665 $968,963 $1,178,925 82.2% 25.7% 8,349 175 177 99.0% F $109,327,567 $3,121,124 $2,237,545 139.5% 56.5% 23,996 864 612 141.3% G $142,093,196 $4,035,037 $3,052,429 132.2% 42.7% 7,939 337 233 144.3% H $150,827,277 $3,650,823 $3,480,697 104.9% 48.6% 13,675 425 381 111.5% I $151,726,712 $4,454,582 $3,545,706 125.6% 66.2% 24,026 836 638 131.0% J $239,722,836 $6,332,251 $5,070,628 124.9% 43.0% 8,147 278 206 134.9% K $321,796,840 $7,213,110 $8,550,504 84.4% 72.1% 37,732 1,256 1,286 97.7% L $529,766,251 $11,799,953 $9,077,751 130.0% 67.3% 31,384 962 729 131.8% M $571,739,217 $10,991,792 $10,924,055 100.6% 79.0% 48,459 1,177 1,071 109.9% N $577,646,380 $15,772,192 $11,752,991 134.2% 83.3% 41,120 1,419 980 144.8% O $743,233,047 $16,997,460 $15,537,544 109.4% 91.4% 48,621 1,499 1,253 119.7% P $815,631,803 $19,804,371 $16,829,662 117.7% 100.0% 76,610 2,563 2,020 126.9%

Total $4,510,034,346 $107,407,783 $93,510,594 114.9% 100.0% 389,633 12,377 10,144 122.0%

0%20%40%60%80%

100%120%140%160%180%

A B C D E F G H I J K L M N O P

A/E Ratio by trade PensionNumber

29

We observe considerable variance in the A/E Ratios amongst the different trades, with these varying from 82.2% to 160.2%, by amount of pension, and from 97.6% to 151.6%, by number of lives. If we ignore trade A and trade E, which have relatively low amounts of exposure data, there is still a range in A/E Ratios of 84.4% to 139.5%, by amount of pension, and 97.6% to 144.8%, by number of lives. These results indicate that it may not be appropriate, in setting the mortality assumption for a particular plan or plans within a particular trade, to solely use a factor adjustment indicated for all construction trades in aggregate. The actuary may consider using a factor adjustment based on the A/E Ratio developed for the plan, other plans within that plan’s specific trade and, possibly, other trades deemed to be similar to that plan’s trade, taking into account, as appropriate, the credibility of the relevant A/E Ratios. For example, consider Trade L in Table 5.5 above, with an A/E Ratio (by amount of pension) of 130.0% and a credibility factor of 67.3%. A credibility-weighted factor adjustment to be applied to the CPM2014Priv table rates could be derived as follows:

CPM2014PrivAdjustment = 𝑍 × 𝐶𝑎𝑡𝑒𝑔𝑜𝑟𝑦 𝑒𝑥𝑝𝑒𝑟𝑖𝑒𝑛𝑐𝑒 + (1 − 𝑍) × 100% = 67.3% × 130.0% + (1 − 67.3%) × 100% = 120.2%

This example is not intended to limit a plan actuary as to the specific credibility-based approach that could be used, and other approaches could be reasonable to use. All participating plans receive Appendix C as part of their copy of the CTMS Report, which summarizes the A/E Ratio and credibility factor analysis for that plan, and all plans within that plan’s trade.

30

Section 6. ADDITIONAL OBSERVATIONS

Studying mortality improvements among construction industry pensioners was not the primary focus of our study. We believe proper analysis of this would require an even greater amount of data than we have been able to gather. However, our research indicates that improvements in mortality for construction trades pensioners over our study period were, on average, about 20% lower than predicted by the “CPM scale B” mortality improvement scale presented in the CIA report. This is consistent with other research indicating a widening gap in life expectancy between white collar and blue collar workers. If this observed lower mortality improvement is accurate, it indicates that our study should be updated periodically.

Our analysis also looks at differences between the commuted value amounts calculated for terminating plan members, based on the mortality assumption that will be required to be used in these calculations for all plans, and mortality assumptions that may be considered more appropriate for members of many construction trades MEPPs. We believe the actuarial profession should give further consideration to allowing for reasonable and supportable adjustments to different plans’ commuted value mortality assumptions.

Mortality Improvements Over the Study Period In reviewing the A/E Ratios for each year in the study period in Table 5.1 and the accompanying graph, we observe that there is a general increasing trend as we move from 2002 to 2012. Recall that the expected deaths for any year in the study are based on the CPM2014Priv table mortality rates, having a base year of 2014, adjusted to the specific study year by removing the appropriate amount of mortality improvement assumed between the study year and 2014, based on generational CPM Scale B. These A/E Ratios are indicated as “Actual” in the graph below. Note that each successive year’s A/E Ratio is not uniformly increasing. However, if we look at the red line in the graph below, which is a “best fit” straight line to the “Actual” A/E Ratios, that “best fit” line is increasing or upward sloping. An upward slope in the A/E Ratios observed from 2002 to 2012 implies that:

the mortality experienced by construction trades pensioners in earlier years of the study period was generally not as high as the mortality experienced by construction trades pensioners in later years of the study period, compared to predicted deaths based on the CPM2014Priv table adjusted to those later years;

mortality improvement experienced for construction trades pensioners over the 2002 to 2012 study period was not as great, on average, as predicted by CPM Scale B over that period; and

the CPM2014Priv table rates, adjusted to the specific study year using CPM Scale B, may not be the most appropriate benchmark for estimating prior year’s expected deaths of construction trades pensioners and the degree of inappropriateness may be greater the further back we look from 2014.

31

We have investigated the factor that would need to be applied to the CPM Scale B mortality improvement rates used to adjust the CPM2014Priv table rates to each year of the study, in order that a “best fit” line to a set of “Modified” A/E Ratios (calculated based on each year’s expected mortality with modifications to CPM Scale B) would have no slope. This factor was calculated to be 76.5%. The “Modified” A/E Ratios, calculated assuming that CPM Scale B factors are multiplied by 76.5%, for purposes of adjusting the CPM2014Priv table rates to each year of the study, are shown in the graph below, along with the “best fit” line to those “Modified” A/E Ratios (shown in green).

Table 6.1 below displays the “Actual” and “Modified” A/E Ratios for each year of the study, as well as the aggregate A/E Ratios for the entire study period and split into 2002-2006 and 2007-2012 segments. Looking at the “Actual” A/E Ratios, we observe that the aggregate A/E Ratio for the first five years of the study was lower than for the last six years of the study. Again, this is consistent with the observation that mortality experienced by construction trades pensioners in the earlier years of the study period was generally not as high as the mortality experienced by construction trades pensioners in later years of the study period, when compared to predicted deaths based on CPM2014Priv table adjusted to those years.

In a supplementary analysis, we have calculated A/E Ratios for each year in the study period, where the expected deaths are based on the CPM2014Priv table rates without any adjustment from 2014 back to the actual observation year. With this particular analysis, we observed a very definite downward slope in the A/E Ratios from 2002 through 2012, and concluded that there has been an improvement in mortality experienced by construction trades pensioners studied over the entire study period on average. However, as indicated above, the average improvement observed over the study period was 76.5% of the mortality improvement built into the CPM2014Priv table rates adjusted to specific prior study years using the CPM Scale B mortality improvement. This analysis indicates that the A/E Ratios derived in earlier years of the study, in particular, are lower than would be calculated if the mortality improvement assumed in the expected mortality rates for those years had been calibrated to the mortality improvement that appears to have occurred in the construction trades pensioner group.

Table 6.1: Experience with modified CPM-B scale backwards projection2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2002-2006 2007-2012 Total

Modified 123.1% 113.8% 122.7% 123.2% 117.3% 118.3% 113.6% 120.4% 124.6% 117.2% 121.2% 119.9% 119.6% 119.6%Actual 113.0% 105.3% 114.4% 115.7% 111.0% 112.7% 109.1% 116.5% 121.4% 115.0% 119.7% 112.1% 116.6% 114.9%

100%

105%

110%

115%

120%

125%

130%

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

A/E Ratio by year with modified CPM-B scale ModifiedActual

32

In preparing these observations, we were aware that the apparent differences between construction trades pensioners’ mortality improvement over the study period and mortality improvement assumed by CPM Scale B could be influenced by the fact that not all participating plans submitted data for the full 2002 to 2012 period. For instance, out of the 43 plans for which data was included in this CTMS Report:

21 plans provided data for the entire 11-year (2002-2012) period

29 plans provided data starting in 2004 or earlier, so for at least the 9-year period 2004-2012

35 plans provided data starting in 2005 or earlier, so for at least the 8-year period 2005-2012

As described above, we estimated the percentage factor that would need to be applied to the CPM Scale B mortality improvement rates used to adjust the CPM2014Priv table rates to each year of the study, in order that a “best fit” line to a set of “Modified” A/E Ratios (calculated based on each year’s expected mortality with modifications to CPM Scale B) would have no slope. If this estimate is done for all participating plans, but:

excluding the 14 plans for which we did not have data for at least nine years, the percentage factor adjustment to the CPM Scale B improvement rates was calculated to be 77.5% (versus 76.5% when estimated for all plans)

excluding the eight plans for which we did not have data for at least eight years, the percentage factor adjustment to the CPM Scale B improvement rates was calculated to be 81.5% (versus 76.5% when estimated for all plans)

In summary, the percentage adjustment to CPM Scale B remains at roughly 80%, even when the analysis on this point is limited only to the participating plans contributing data for all or most of the study period. Therefore, we believe that our observation that the average improvement in mortality appears to have been approximately 80% of the mortality improvement built into the CPM2014Priv table rates adjusted to specific prior study years using the CPM Scale B mortality improvement is not significantly influenced by the fact that not all participating plans submitted data for the full 2002 to 2012 period. The foregoing is not intended to suggest that a modification can be made to the CPM Scale B factors for assumed mortality improvements beyond 2014, based on our analysis. As noted in Section 2, we believe that the amount of data that would be required to derive a mortality improvement scale as an alternative to CPM Scale B, or to support adjustments to CPM Scale B, is far greater than the data we have been able to compile for this report. As well, the analysis is not sufficient to suggest that the use of the CPM Scale B factors, in deriving CPM2014Priv table rates adjusted to the prior study years, is inappropriate for other non-construction pensioner groups or for a very large and diverse population of pensioners. However, it appears that the mortality improvement patterns for construction trades pensioners may be different from – in particular, a lesser improvement on average – than assumed in the CPM Scale B over our study period. To the extent that our analysis indicates mortality improvements for construction trades pensioners over the study period to be roughly 80% of CPM Scale B mortality improvements over that period, we note that this is consistent with other research that has indicated a widening gap in life expectancy between white collar and blue collar workers and between higher and lower socio-economic gradations.

33

Therefore, in referencing the aggregate “Actual” or unadjusted A/E Ratios we have derived over the entire study period for purposes of deriving an adjustment factor to be applied to the CPM2014Priv table for a particular plan/trade, it appears possible that there is some inherent conservatism in the factor that would be used. In other words, the adjustment factor developed in this study may be slightly lower (and thus, assumed longevity slightly higher) than if expected mortality in this study had been analyzed based on benchmark CPM2014Priv table rates adjusted to the years 2002 to 2012 using mortality improvement rates that appear to be a better fit to average mortality improvement for construction trades pensioners over this period. We note that we have not conducted this analysis by plan or by trade, as the amount of data required for any meaningful analysis of mortality improvement over prior periods is much greater than compiled for any individual plan or trade. In general, additional research into construction trades mortality improvements, while beyond the scope of this study, does appear warranted. Mortality Assumptions and Commuted Values Under the CIA’s Standards of Practice, the mortality basis currently used in the calculation of pension commuted values is the 1994 Uninsured Pensioner Mortality Table with generational mortality improvements based on Scale AA. The Actuarial Standards Board (ASB) of the CIA has made a recommendation that, effective October 1, 2015, the mortality assumption be changed to reflect the CPM2014 mortality table rates (“Combined table”) with generational mortality improvements based on CPM Scale B. The ASB recognizes that

“for some plans with higher mortality experience this may increase the disparity that currently exists between commuted values and the funding liabilities for individual plan members, thereby potentially affecting remaining plan members. However, for many plans the effect of the mortality basis on this disparity is very small compared to other factors, most notably differences in the funding versus solvency or wind-up discount rates…the DG (designated group) believes that narrowing the range of practice for commuted value calculations is an important consideration to meet the public interest. The DG did not consider the mortality impact to be material enough when reviewed in aggregate with all other factors to warrant a more complex process that could include a mortality assumption that varies by plan.” 16

Differences between commuted values, which are most typically paid in respect of terminating plan members, and the funding liabilities calculated in respect of remaining plan members are a particular concern for MEPPs, as these plans are often funded on a going concern basis, with no provision explicitly made in the funding for members’ plan wind-up liabilities. The ASB’s analysis included a review of the differences in commuted values that would be attributable to different assumed levels of mortality, including mortality rates based on 115% CPM2014Priv. As part the analysis, it was concluded that

“115% of CPM2014Priv produces a difference in commuted values of less than 5.1% at the ages tested” and that “a difference owing to individual pension plan circumstances of the order of 2.5% to 5% could be deemed reasonable in the search for a uniform basis to apply to all pension plans.” 17

16Actuarial Standards Board, Initial Communication of a Promulgation of the Mortality Table Referenced in the Standards of Practice for Pension Plans (Subsection 3530) (Canadian Institute of Actuaries, December 4, 2014): http://www.cia-ica.ca/docs/default-source/2014/214127e.pdf?sfvrsn=0. 17 Ibid, p. 6.

34

We note that there are some trades included in this study for which a credibility-weighted adjustment factor, to be applied to CPM2014Priv, could be supported at 120% to 130%. In the tables below, we provide illustrative commuted values calculated for a male age at 30, 40 and 50, based on the May 2015 commuted value interest rates and with mortality based on the current commuted value assumption (1994 UP Generational), the assumption proposed by the ASB (2014 CPM Combined, with mortality improvements based on CPM Scale B) and 130% of the CPM2014Priv table’s mortality rates (with mortality improvements based on CPM Scale B). The right-hand column indicates the percentage difference in commuted value, due to changing from the current mortality assumption to 2014 CPM Combined rates and 130% of the CPM2014Priv table’s rates (both with mortality improvements based on CPM Scale B).

Table 6.2: May 2015 commuted value, male age 30 with $1,000 payable at 65

Base Mortality Table Improvement

Scale Commuted Value % Difference 1994 UP Generational Scale AA $59,360 n/a 2014 CPM Combined CPM-B $62,322 4.99%

2014 CPM Private (130%) CPM-B $57,620 -2.93%

Table 6.3: May 2015 commuted value, male age 40 with $1,000 payable at 65

Base Mortality Table Improvement

Scale Commuted Value % Difference 1994 UP Generational Scale AA $82,632 n/a

2014 CPM Combined CPM-B $87,570 5.98%

2014 CPM Private (130%) CPM-B $80,691 -2.35%

Table 6.4: May 2015 commuted value, male age 50 with $1,000 payable at 65

Base Mortality Table Improvement

Scale Commuted Value % Difference 1994 UP Generational Scale AA $114,768 n/a 2014 CPM Combined CPM-B $122,969 7.15%

2014 CPM Private (130%) CPM-B $112,910 -1.62%

35

The analysis above indicates that, for the ages considered, commuted values are increased in the range of about 5.0% to 7.2% when calculated based on the proposed 2014 CPM Combined mortality assumption. Commuted values would be about 8% to almost 9% higher when calculated based on the 2014 CPM Combined table rates, than if calculated based on the 2014 CPM Private table with a 130% factor adjustment, which may be appropriate given the underlying mortality for members of a particular plan or trade. If the factor adjustment to the 2014 CPM Private table is 120%, the commuted values would be about 6% to 7% higher when calculated based on the 2014 CPM Combined table rates, than if calculated based on the 2014 CPM Private table with that factor adjustment. Therefore, there are plans included in this study for whom, individually or in aggregate with other similar plans, differences due to recognizing actual pension plan mortality would exceed the order of magnitude of 2.5% to 5% deemed to be an acceptable range in the ASB’s memorandum. Put another way, for such plans the commuted value calculated based on a mortality assumption reflective of their experience could be about 1.5% to 3% less than the commuted value calculated based on the current 1994 UP Generational mortality assumption, rather than being 5.0% to 7.2% higher, when calculated based on the 2014 CPM Combined mortality assumption. In plans where members are observed to have longer life expectancies, the plan administrator can choose to adopt a mortality basis with longer life expectancy than predicted by the proposed 2014 CPM Combined mortality assumption for commuted value payouts, subject to acceptance that may be required from the Canada Revenue Agency. In plans with shorter life expectancies, such as those exhibiting mortality levels of 110% to 130% of the CPM2014Priv table rates, the administrator is not permitted to adopt a mortality basis with shorter life expectancy. This will further exacerbate a problem for many such MEPPs, that the difference between the going concern funded value and commuted value for a terminating member could be made greater by an additional 5.0% to 7.2%, due to the promulgation of a commuted value mortality basis which is demonstrably too conservative for that plan. Fundamentally, this favours terminating members at the expense of remaining members of such plans. These observations support the case for further consideration by the ASB of reasonable and supportable adjustments to commuted value mortality assumptions.

-2.93% -2.35%

-1.62%

4.99%

5.98%

7.15%

-4.00%

-2.00%

0.00%

2.00%

4.00%

6.00%

8.00%

30 40 50

Member Age

Percent difference in commuted values vs. UP94 Generational

2014 CPM Private (130%)

2014 CPM Combined

Current Standard

UP94 Generational

36

Construction Trades Pensioner Mortality Experience and Size of Pension The CPM Report includes a derivation of “size adjustment factors” that reflect differences in the RPP Study by income band, for males and females separately. The size adjustment factors reflect the observation, in both the C/QPP Study and RPP Study, that mortality rates vary significantly with the size of the pension. Below, we have provided an analysis of the A/E Ratios calculated by size of pension for the data compiled for this CTMS Report.

Table 6.5: Experience by pension amount

Amount of Annual Pension Number of Lives

Monthly income Exposure Actual

Deaths Expected

Deaths A/E Ratio Exposure Actual

Deaths Expected

Deaths A/E

Ratio $0 - $499 $437,938,006 $16,950,706 $13,438,870 126.1% 161,972 6,230 4,910 126.9% $500 - $999 $743,860,009 $26,120,013 $20,992,568 124.4% 84,614 3,004 2,404 125.0% $1,000 - $1,499 $817,859,327 $23,437,303 $20,506,404 114.3% 55,471 1,610 1,399 115.1% $1,500 - $1,999 $728,281,392 $16,066,125 $14,266,116 112.6% 35,066 783 692 113.1% $2,000 - $2,499 $599,079,541 $9,463,123 $9,436,324 100.3% 22,379 356 353 100.9% $2,500 - $2,999 $437,837,777 $5,789,822 $6,126,358 94.5% 13,378 178 187 95.2% $3,000 - $3,499 $299,910,462 $3,545,880 $3,791,196 93.5% 7,756 92 98 93.5% $3,500 - $3,999 $217,380,394 $3,305,917 $2,502,371 132.1% 4,863 75 56 133.2% $4,000 - $4,499 $118,260,522 $1,471,459 $1,303,487 112.9% 2,336 29 26 113.1% $4,500 - $4,999 $60,572,072 $566,640 $644,988 87.9% 1,073 10 11 88.0% $5,000 - $5,499 $25,905,118 $313,610 $252,321 124.3% 413 5 4 125.3% $5,500 - $5,999 $12,141,969 $284,193 $144,929 196.1% 177 4 2 189.6%

>= $6,000 $11,007,756 $92,992 $104,662 88.8% 137 1 1 77.6% Total $4,510,034,346 $107,407,783 $93,510,594 114.9% 389,633 12,377 10,144 122.0%

37

The following chart compares the A/E Ratios displayed above, by size of pension, with size adjustment factors from the CPM Report.

The pattern of A/E Ratios, by size of pension, that we have calculated is reasonably consistent with the size adjustment factors in the CPM Report; generally, slightly higher than the CPM adjustment factors up to $2,000 per month and slightly lower at monthly pension amounts to $3,500. Above $3,500 per month, we find much more variance and, no discernible pattern, in the A/E Ratios we have calculated. However, we believe these variances to be due to the relatively small amount of exposure data (less than 10% of total), and thus larger potential variances in results, at pension amounts greater than $3,500 per month. We have not derived size adjustment factors to be used in place of the size adjustment factors in the CPM Report.

0%

25%

50%

75%

100%

125%

150%

175%

200%A/E Ratio by amount of monthly pension income

CTMS A/E RatioCPM Male FactorsCPM Female Factors

38

Section 7. OPINION

This report is intended to add to the research on mortality experience of Canadian pension plans, specifically in respect of those covering workers in the construction trades. The primary users of this report on the Construction Trades Mortality Study Report (“CTMS Report”) are the Boards of Trustees and actuarial advisors of multi-employer pension plans participating in the study. This report is not intended or necessarily suitable for purposes other than those described in Section 2 of this report. Any party reviewing this report should read this report in its entirety, including all Appendices, and should have their own actuary or other qualified professional assist in their review to ensure that the party understands the data, results and limitations inherent in our analysis and observations. In our opinion, for the purposes of this study and CTMS Report:

the data are sufficient and reliable; the assumptions made are appropriate; and the methods employed are appropriate. It is our understanding that there is no codified actuarial practice in respect of the methodology used to prepare experience analysis to be used for purposes of determining adjustments to standard table mortality rates for purposes of preparing an actuarial valuation for pension plans. In our opinion, this study and CTMS Report is consistent with commentary by the CIA’s Pension Experience Subcommittee in the CPM Report. Respectfully submitted,

Domenic Barbiero Fellow, Canadian Institute of Actuaries

Mark F. Davis Fellow, Canadian Institute of Actuaries

D. Cameron Hunter Fellow, Canadian Institute of Actuaries

39

Section 8. REPORT PEER REVIEW

I have reviewed the Construction Trades Mortality Study (CTMS) Report prepared by Eckler Ltd., including:

the methods of data gathering, review and modification; and the analysis presented, including related methodology and assumptions described, and observations

and interpretations presented.

I believe that the CTMS Report and my related peer review is consistent with commentary by the CIA’s Pension Experience Subcommittee in the CPM Report. Any comments or questions I have had have been discussed with the report authors and addressed to my satisfaction in this report. Respectfully,

Robert L. Brown FCIA, FSA, ACAS

40

Appendix A. LIST OF PARTICIPATING PLANS

Alberta Ironworkers Pension Fund Boilermakers Lodge 359 Production Workers Pension Plan Boilermakers’ National Pension Plan (Canada) Bricklayers & Trowel Trades International Pension Fund – Canada Canadian Elevator Industry Pension Plan Carpenters’ Local 18 Pension Plan Carpenters’ Local 27 Pension Plan Drywall Acoustic Lathing and Insulation Local 675 Pension Plan Electrical Industry Pension Trust Fund of Alberta General Teamsters Local Union 362 Retirement Trust Fund IBEW Local 353 Pension Plan IBEW Local Union 804 Employees Pension Plan Ironworkers Local 721 (Rodmen) Pension Plan Ironworkers Local 764 Pension Plan Ironworkers Ontario Pension Plan I.U.P.A.T. Local 177 Pension Trust Fund Laborers’ Pension Fund of Western Canada Local 213 Electrical Workers Pension Plan Millwright Pension Plan Ontario Provincial Council of Carpenters Pension Programme Operating Engineers’ Pension Plan Pension Plan for Members of IBEW Local 530 Pension Plan for Members of IBEW Local 625 Pension Plan for the Members of the Bricklayers, Masons Independent Union of Canada, Local 1 Pension Plan for Members of the Sheet Metal Workers' International Association, Local Union No. 397 Pension Plan for Members of Shopmen’s Local Union 805 of the International Association of Bridge,

Structural, Ornamental and Reinforcing Ironworkers Pension Plan for Members of United Association of Journeymen and Apprentices of the Plumbing and

Pipefitting Industry of the United States and Canada Local 67 Plumbers’ and Pipefitters’ Local Union 508 Pension Plan Plumbers’ and Pipefitters’ Local Union 800 Pension Plan Plumbers’ and Steamfitters’ Local 527 Pension Plan Plumbing and Pipefitting Workers Local 46 Pension Plan Resilient Floor Workers – Local 27 Pension Plan Sheet Metal Workers (Local 280) Pension Plan Sheet Metal Workers Local Union 30 Pension Plan Teamsters Local 213 Pension Plan Teamsters Prairie Provinces Pension Plan The Cement Workers Trusteed Pension Plan18 The Edmonton Pipe Industry Pension Plan The IUOE Local 793 Pension Plan for Operating Engineers in Ontario The Operating Engineers Local 955 Pension Plan The United Association of Journeymen and Apprentices of the Plumbing and Pipefitting Industry of the United

States and Canada, Local 740, Pension Plan The United Brotherhood of Carpenters and Joiners of America, Local Union No. 494 Pension Plan U.A. Local 71 Pension Plan U.A. Local Union 628 (Plumbing and Pipefitting) Members’ Pension Plan

18 Plan covers construction industry cement workers but is a single employer, jointly trusteed plan, and is not a MEPP. General references made in this report to “MEPPs” are not intended to infer that the results and commentary in this report are not applicable to this plan.

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Appendix B. CREDIBILITY METHODOLOGY

Limited Fluctuation Credibility In this report, we have applied a “limited fluctuation” method to estimate the credibility of actual to expected mortality ratios (A/E Ratios) calculated for a particular participating plan, all plans within a trade or for the aggregate data. The key premise of limited fluctuation credibility is that when a certain sample size of data is achieved, the analytical result from that data can stand on its own (i.e., full credibility). With this limited fluctuation approach, we take our observed A/E Ratio and we postulate that the “true” underlying mortality rates, �̂�, for the particular group being observed are equal to the A/E Ratio calculated for that group multiplied by the CPM2014Priv mortality table rates. We then set the minimum threshold of expected deaths – in this study, measured by amounts of pension – required such that our estimate of the underlying level of mortality is expected to be within a small constant percentage (𝑟) of the “true” level of mortality with

at least a certain level of confidence (𝑝). Observed levels of mortality are assumed to be distributed according to a standard normal distribution. For instance, in deriving the credibility factors presented in this report, we have calculated the minimum amount of deaths (measured by annual amount of pension) so that the observed A/E Ratio is expected to be within 5% of the “true” ratio, with a confidence level of 90%. If the amount of deaths from the data upon which the particular A/E Ratio is based is greater than this minimum threshold then we conclude that the A/E Ratio is “fully credible.” If the amount is less than the minimum threshold, then we calculate a partial credibility factor 𝑍, where:

𝑍 = √𝑇𝑜𝑡𝑎𝑙 𝑜𝑏𝑠𝑒𝑟𝑣𝑒𝑑 𝑑𝑒𝑎𝑡ℎ𝑠 ($)

𝑀𝑖𝑛𝑖𝑚𝑢𝑚 𝑡ℎ𝑟𝑒𝑠ℎ𝑜𝑙𝑑 𝑎𝑚𝑜𝑢𝑛𝑡

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Credibility Factor Adjustments As noted above, for purposes of calculating credibility factors for this report, the parameters of 𝑟 (error

constant) and 𝑝 (confidence level) were set at 5% and 90%, respectively, as we believe these would be common values chosen to achieve a typical desired level of confidence. We recognize that some users of this report may wish to understand the impact of choosing different parameters for 𝑟 and 𝑝. The table below has been constructed to allow a report user to make an adjustment to credibility factors presented in this report, based on the selection of different parameter values. For example, if the parameters of 𝑟 (error

constant) and 𝑝 (confidence level) were set at 10% and 90%, respectively, then the level of error allowed for is higher and the minimum threshold for achieving full credibility is lower; alternatively, the credibility factor for a specific level of observed deaths is higher. The table below indicates that the adjustment to the (5%/90%) credibility factor 𝑍 would be a multiple of 2 in this example. Note that the resulting credibility factor obtained from the use of the adjustment factors below should be no greater than 100% (i.e., fully credible).

Confidence level (𝑝) Error constant ( 𝑟) 90% 95% 99% 0.01 0.2000 0.1678 0.1277 0.02 0.4000 0.3357 0.2554 0.03 0.6000 0.5035 0.3831 0.04 0.8000 0.6714 0.5109 0.05 1.0000 0.8392 0.6386 0.06 1.2000 1.0071 0.7663 0.07 1.4000 1.1749 0.8940 0.08 1.6000 1.3428 1.0217 0.09 1.8000 1.5106 1.1494 0.10 2.0000 1.6785 1.2771

To adjust a credibility factor displayed in this report, take the product of the credibility factor displayed (with parameters 𝑟 and 𝑝 set at 5% and 90%, respectively) and the cell value corresponding to the desired 𝑟 (error constant) and 𝑝 (confidence level) from the table above.

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