Social Security Advisory Board

400 Virginia Avenue, SW Suite 625

Washington, D.C. 20024

T (202) 475-7700

F (202) 475-7715

info@ssab.gov
Members of the Technical Panel

Brigitte C. Madrian, Chair

Aetna Professor of Public Policy and Corporate Management 

Harvard Kennedy School, Harvard University 

Janet Barr

Associate Actuary, Employee Benefits 

Milliman 

John Bongaarts

Vice President and Distinguished Scholar

Population Council

Mark Duggan

Professor of Business and Public Policy

The Wharton School, University of Pennsylvania

Melissa Favreault

Senior Fellow

The Urban Institute

Tim Marnell

Actuary

Tim Marnell, Actuarial & Benefits Consulting LLC

S. Philip Morgan

Professor of Sociology and Norb F. Schaefer Professor of International Studies

Duke University

John Sabelhaus

Chief, Microeconomic Surveys Section, Division of Research and Statistics

Federal Reserve Board

Andrew Samwick 

Sandra and Arthur Irving Professor of Economics 

Dartmouth College

Karen A. Woodrow-Lafield

Research Professor and Faculty Associate, Maryland Population Research Center

University of Maryland
2011

Technical Panel Report

on Assumptions and Methods

report to the Social Security Advisory Board

September 2011

Table of Contents

Panel Charter i

Introduction and Acknowledgments iii

Executive Summary 1

1. Methodology 13

1.1 Presentation of Uncertainty 13

1.2 Actuarial Metrics 23

1.3 Models and Methods 33

1.4 Implications of Health Care Reform 39

2. Demographic Assumptions and Methods 45

2.1 Fertility 45

2.2 Mortality 55

2.3 Immigration 64

2.4 Disability 74

3. Economic Assumptions and Methods 91

3.1 Labor Force Participation Rate 91

3.2 Real Wage Growth Rate 97

3.3 Unemployment Rate 107

3.4 Interest Rates 107

3.5 Inflation 110

3.6 Taxable Share of Covered Wages 110

References 115

Compilation of Technical Panel Recommendations 125

2011 Technical Panel on Assumptions and Methods i

Charter

The Panel of expert actuaries, economists and 

demographers appointed by the Social Security Advisory Board is charged with providing technical assistance to the Board by reviewing the assumptions 

specified by the Board of Trustees of the Old-Age 

and Survivors Insurance Trust Fund and the Disability Insurance Trust Fund and the methods used 

by the Social Security actuaries to project the future 

financial status of the programs. The Panel shall deliver a written report to the Advisory Board within 

nine months of the Panel’s first meeting.

Specifically the Panel is asked to:

■ Review the assumptions regarding key demographic and economic factors – including mortality, fertility, immigration and disability incidence 

and termination, productivity, real wage growth, 

interest rates, price increases, labor force participation, and rates of employment and unemployment.

■ Review and assess current projection methodologies.

■ Review in particular:

p The factors that affect trends in the taxable wage base such as trends in non-wage 

compensation and the growth rate of wages above and below the taxable maximum 

wage.

p Methods of projecting prevalence of disability and labor force participation of older 

workers.

p Evidence of structural economic changes 

as a result of the recent financial crisis that 

would affect key economic assumptions and 

frameworks, both in the short- and longterms. 

p Ways to improve the presentation of key 

concepts in the Trustees Report, including 

the interaction of the funds with the federal 

budget, so as to make them more accessible 

and informative to the public.

■ Review and assess the status of the recommendations of previous Technical Panels appointed by the Advisory Board.

2011 Technical Panel on Assumptions and Methods iii

Introduction and Acknowledgments

The 2011 Technical Panel on Assumptions and 

Methods was convened by the Social Security Advisory Board in September 2010 to review the assumptions specified by the Board of Trustees and 

to evaluate the methods used by the Office of the 

Chief Actuary to project the future financial status 

of the Old-Age and Survivors Insurance and Disability Insurance Trust Funds. We have worked 

diligently over the past year, both individually and 

collectively, to fulfill this mandate.

In addition to several closed-door meetings, the 

Technical Panel held six public meetings at the offices of the Social Security Advisory Board in Washington, DC, on:

■ October 1, 2010

■ November 5, 2010

■ December 13, 2010

■ January 28, 2011

■ February 25, 2011

■ May 5, 2011

We benefited greatly from the presentations 

made at those meetings and from the questions 

and comments of those in attendance and the ensuing discussion.

The staff in the Social Security Administration’s 

Office of the Chief Actuary attended all of our 

public meetings, made several presentations to 

the Technical Panel, answered countless questions 

by e-mail, fielded many requests for data, and ran 

all of the projections presented in this report. We 

appreciate the tireless support of Chief Actuary 

Stephen Goss and recognize the help of many others in the actuary’s office who contributed to our 

work, including Deputy Chief Actuary Alice Wade 

(Long Range), Deputy Chief Actuary Eli Donkar 

(Short Range), Chris Chaplain, Anthony Cheng, 

Karen Glenn, Steve F. McKay, Michael Morris, David Olson, Jason Schultz, and Pat Skirvin. Felicitie 

Bell, Tiffany Bosley, Mark Bye, Danielle Huston, 

Johanna Maleh, Kent Morgan, Bill Piet and Karen 

G. Smith Michael L. Stephens provided assistance 

with data, projections and other technical issues. 

Robert Reischauer and Charles Blahous, the two 

public trustees of the Social Security Trust Fund, 

graciously met with the Technical Panel soon after 

their appointment. We appreciate their time and 

insights and their support of our efforts.

Samuel Preston, co-chair of a National Research 

Council panel on international differences in longevity at older ages, shared the collective wisdom of 

his panel with the Technical Panel, helping us better 

understand the drivers of mortality at older ages. 

Louise Sheiner, a member of the 2010 Medicare 

Technical Review Panel, made a presentation to the 

Technical Panel on the growth in long-term health 

care costs, informing our discussions about the implications of health care reform for Social Security 

finances. Jonathan Schwabish, Julie Topoleski, and 

Michael Simpson from the Congressional Budget 

Office and Karen E. Smith of The Urban Institute 

participated in a thought-provoking discussion on 

microsimulation modeling. Joseph Newhouse, cochair of the Medicare Technical Review Panel, and 

Jonathan Gruber of the Massachusetts Institute of 

Technology were also helpful sounding boards in 

considering the interplay between health care reform and Social Security. Frederick Hollmann and 

Jennifer Ortman from the Census Bureau provided 

useful feedback on immigration and census population projections. Jason Fichtner, David Pattison, 

and Mike Leonesio of the Social Security Administration also provided valuable insight and advice.

In addition to those named above, we owe a debt 

of gratitude to the many individuals who spoke informally with members of the Technical Panel over 

the past year and helped shape our understanding 
iv 2011 Technical Panel on Assumptions and Methods

of key issues. We are indebted to many individuals 

at the Congressional Budget Office, the Census Bureau, the Social Security Administration, and other 

government agencies and to academic and other 

professional colleagues.

Finally, Joel Feinleib, the Technical Panel’s executive director and the Social Security Advisory 

Board’s chief economist, has been “on loan” from 

the Social Security Advisory Board to support the 

Technical Panel over the past year. He has been 

indispensable, doing things both big and small to 

move our work forward and making many substantive contributions along the way. We are also 

grateful for the help of the other staff at the Social 

Security Advisory Board, including Kate Thornton, 

Robin Walker, Beverly Rollins, Debi Sullivan, David 

Warner, Peter Flynn, and Jeremy Elder. Carol Soble 

edited this report expertly and quickly.

As the Chair, I am thankful to the panelists for 

their dedicated service. As we have learned to work 

together as a group, I have come to respect each 

panel member tremendously. Although each panelist brought to the Technical Panel expertise in 

different domains, the report reflects the group’s 

consensus. We agreed to most of our recommendations only after several rounds of discussion and 

debate. We learned much from each other during 

the process.

Brigitte C. Madrian, Chair
2011 Technical Panel on Assumptions and Methods 1

Executive Summary

The 2011 Technical Panel on Assumptions and 

Methods was convened by the Social Security Advisory Board in September 2010 to review the assumptions specified by the Board of Trustees and 

to evaluate the methods used by the Office of the 

Chief Actuary to project the future financial status 

of the Old-Age and Survivors Insurance and Disability Insurance Trust Funds.

As noted by the 2007 Technical Panel, “The Social 

Security actuaries and the Trustees of the Old Age, 

Survivors, and Disability Insurance (OASDI)  Trust 

Funds have perhaps the most difficult analytical 

task in government – projecting demographic and 

economic developments over the next 75 years.” We 

appreciate the enormity of the task and note that 

much of what is done in this process is fundamentally 

sound. We have focused on identifying areas where 

change might be warranted as well as on articulating 

the justifications for such proposed changes.

As part of the process, we have examined the 

assumptions adopted by the Trustees in the 2010 

and 2011 Trustees Reports, along with changes to 

the Trustees’ assumptions since issuance of the 

last Technical Panel report in 2007. We have also 

assessed the status of recommendations made by 

earlier Technical Panels. In cases where the 2011 

Technical Panel concurs with earlier Technical Panel 

recommendations, we have so noted in our report.

Following the 2007 Technical Panel, we begin with 

an assessment of the methods used to evaluate the 

financial status of the OASDI Trust Funds and to 

communicate those results to the government, the 

media, and the public. This includes a section on the 

implications of health care reform for the financial 

status of the OASDI program. We then turn to the 

key demographic and economic assumptions. 

■ Methodology

Presentation of Uncertainty

The baseline projections on system finances in 

the Trustees Report are sensitive to several assumptions that reflect some degree of uncertainty. 

The 1999, 2003, and 2007 Technical Panels all made 

recommendations on how to evaluate and convey 

the impact of uncertainty on system finances, and 

the Office of the Chief Actuary has followed up 

with some important methodological innovations 

in this regard. The Trustees Report now contains 

three types of uncertainty analysis: high- and lowcost scenarios, stochastic simulation, and sensitivity analysis. Although some work remains in the empirical analysis of uncertainty, the Technical Panel 

focused primarily on how uncertainty is presented 

in the Trustees Report. Building on the suggestions of earlier Technical Panels, we set forth recommendations intended to make the presentation 

of uncertainty more useful to a broad spectrum of 

readers.

Summary Table II.C1 in the Trustees Report lists 

the key assumptions used in projecting system finances and evaluating the uncertainty about these 

projections. The Technical Panel recommends expanding the list of key assumptions to include labor 

force participation, disability incidence and termination, and the taxable share of wages. In addition, 

the Technical Panel recommends presenting the 

values for key assumptions in a way that is more 

useful to readers. For example, Table II.C1 currently reports the “average annual percentage reduction 

in total age-sex-adjusted death rates,” a precise concept, but one that is probably lost on most readers. 

Instead, most readers would likely understand the 

increase in life expectancy implied by the assumed 
2 2011 Technical Panel on Assumptions and Methods

average annual  percentage reduction in total agesex-adjusted death rates.

Given that sensitivity analysis is the foundation 

for other types of uncertainty analysis, the Technical Panel recommends that the discussion of 

uncertainty in the Summary chapter focus on sensitivity analysis for each of the key drivers of system finances. The selection of the low- and highcost values should be consistent, in a probabilistic 

sense, both within and across assumptions. The 

low- and high-cost values for any given variable 

should be equally likely relative to the intermediate case even if they imply an asymmetric range 

between the intermediate and high- and low-cost 

assumptions (the 2007 Technical Panel made the 

same point). Further, the likelihood of realizations 

within the range of outcomes should be the same 

across all key assumptions.

The Technical Panel also recommends consolidating all uncertainty analyses into a single chapter on 

uncertainty; currently, such analyses are scattered 

throughout various sections of the Trustees Report 

(including Chapter  II, Chapter  IV, Appendix  D, and 

Appendix E). The uncertainty chapter should explain 

the approaches to evaluating uncertainty: high- and 

low-cost scenarios, integrated scenarios, and stochastic simulation. It should also compare and contrast the results from the various approaches.

Actuarial Metrics

The Technical Panel benefited from the membership of two actuaries; we drew on their expertise to 

help us evaluate the actuarial metrics used in the 

Trustees Report, something not comprehensively 

addressed in the 1999, 2003, or 2007 Technical 

Panel reports. The annual Trustees Report presents 

several actuarial metrics, both short- and longrange, that illustrate the relationship of workers to 

beneficiaries, current and projected funded status, 

and the change in funded status from the previous 

year and historically. We evaluated the metrics and 

concluded that they satisfy the Actuarial Standard 

of Practice for Social Insurance (ASOP 32) as well as 

the Federal Accounting Standards Advisory Board 

Exposure Draft on reporting the financial status of 

the Social Security system in the context of the unified budget. Overall, the Technical Panel’s assessment is that the set of metrics is comprehensive 

and used appropriately and presented clearly.

We also evaluated the metrics used by other experts and organizations, including the Congressional Budget Office (CBO) and Canadian Office of the 

Chief Actuary of the Canada Pension Plan (CPP). 

This review led the Technical Panel to the assessment and recommendation that micro-level financial measures provide another useful way to evaluate the Social Security system and help the public 

relate its financial status to the level of benefits. 

Our report includes specific examples of how the 

Trustees Report could incorporate such metrics.

The Technical Panel also recommends that the 

Trustees Report expand the discussion of sustainable solvency. We present several potential metrics 

that could help illustrate the types of system changes that would be required to achieve sustainable 

solvency. The new metrics will aid readers in understanding the financial status of Social Security. A 

more comprehensive discussion of sustainable solvency would also eliminate the need for the Infinite 

Horizon metric. The uncertainty associated with the 

Infinite Horizon projection is so great – taxes, benefits, taxable payroll, and Gross Domestic Product 

(GDP) are projected hundreds of years into the future – that the results are often misused in policy 

discussions. The Technical Panel agrees that a solid 

assessment of sustainable solvency would be more 

informative than an Infinite Horizon projection.

Models and Methods

The 2007 Technical Panel called for “more transparency in the models and data the actuaries use, 

as well as the assumptions that drive their results.” 

The 2011 Technical Panel applauds the Office of the 

Chief Actuary’s (OACT’s) significant progress in increasing the transparency of its model and methods, including posting to their web site documentation of the approach, assumptions, and methods 

used in the Trustees Report, along with single-year 

tables from the Trustees Report. We recommend 

continued efforts on this front to facilitate comparisons across Trustees Reports and to make the 

documentation more user-friendly. The full report 

contains specific suggestions.

Reliable estimation of Social Security’s longrun finances requires vast amounts of highly detailed and representative data. The Technical 

Panel strongly supports the investments made in 

recent  years by various divisions within the Social Security Administration (SSA)  to institute 
2011 Technical Panel on Assumptions and Methods 3

and maintain data linkages, such as the matched 

survey-administrative data files for the Survey of 

Income and Program Participation (SIPP) and the 

Health and Retirement Study (HRS). OACT’s efforts to share data files developed by members of 

its staff for internal use have helped validate and 

improve models developed by other parts of SSA. 

A prime example is the OACT Microsim database 

file that is based on administrative sources, including the Current Work History Sample (CWHS) and 

Master Earnings File (MEF). The Technical Panel 

recommends continued efforts to facilitate research and analysis within different parts of SSA 

and within the larger research community.

Models of Social Security serve several purposes, 

and different types of models embody different 

strengths and weaknesses. Earlier Technical Panels called for accelerated efforts to use dynamic 

microsimulation techniques to augment findings 

from the segmented model. In recent  years, SSA 

has increased its reliance on dynamic microsimulation models to produce distributional estimates of 

reform proposals. The 2011 Technical Panel recommends that OACT develop a strategic plan for integrating its segmented and microsimulation strategies. One objective of this strategic plan should be 

to increase coordination of dynamic microsimulation efforts within SSA in order to maximize existing resources. The Technical Panel recommends 

that the Social Security Advisory Board monitor 

progress on the development of these plans. The 

Board should consider convening or hosting a regular series of meetings of model developers within 

SSA and across various government agencies to review innovations, challenges, and prospects for collaboration. In deciding how to allocate scarce modeling resources, SSA should assign high priority to 

policies with potentially significant but uncertain 

effects on OASDI’s fiscal position.

The Social Security actuaries are charged with 

projecting the financial status of the program under current law. In several substantive areas, many 

independent analysts view current law as unrealistic or unsustainable over long periods. Uncertainty 

about policy direction should factor into developers’ plans for model investments and maintenance 

and should shape thinking about ongoing specification choices and the plausible bands for high- and 

low-cost assumptions. For example, the real wage 

differential, immigration levels and immigrant 

composition, and income from taxation of benefits 

are all key determinants of system finances that are 

likely to be influenced by policy changes in the coming years. The Technical Panel encourages developers to be forward-looking to ensure that they are 

positioned to adapt to possible policy changes that 

would materially affect Social Security financing.

In making their projections, the OASDI Trustees 

typically assume that current law will remain in effect in most areas. They deviate significantly in 

a few instances, including establishing an income 

tax baseline and, less important, the treatment of 

refugees under immigration law. Since Social Security benefits became subject to income taxation 

in 1984, revenue from taxation of benefits has 

grown steadily and is expected to become an increasingly important share of total OASDI revenue 

in the coming  years. The importance of this revenue source is uncertain, however, and warrants 

additional discussion in the Trustees Report. The 

Technical Panel recommends basing the intermediate projection of revenues from taxation of OASDI 

benefits more closely on the current income tax 

code rather than on historical shares of income subject to federal income taxation. The Technical Panel 

also recommends basing the projections of OASDI’s 

long-range actuarial status on two alternative sets 

of assumptions about future taxation; the assumptions are analogous to “current law”/“extended 

baseline” and “current policy”/“alternative fiscal” 

scenarios, as adopted by other government and private forecasting groups. At a minimum, the Technical Panel strongly recommends that the Trustees 

add sensitivity analysis to the Trustees Report to 

demonstrate how projections of the long-range 

financial status of the OASDI program vary with 

alternative assumptions about laws governing personal income tax.

Implications of Health Care Reform

The 2010 passage of the Patient Protection and 

Affordable Care Act and the Health Care and Education Reconciliation Act represents the most dramatic 

change to the U.S. health care system since the enactment of Medicare in 1965. Although the goals of 

health care reform primarily relate to health care 

– expanded health insurance coverage, increased 

affordability of health care, reduction in long-term 

increases in the cost of health care – the new laws 

also have implications for the financial status of the 

OASDI program.
4 2011 Technical Panel on Assumptions and Methods

The 2010 Trustees Report calculated that health 

care reform would increase the long-range OASDI 

actuarial balance by 0.14 percent of taxable payroll. 

The assumed mechanism was a decline of 0.1 percent in the ratio of earnings to compensation resulting from the excise tax on employer-sponsored 

health insurance that takes effect in 2018. The Technical Panel believes that health care reform could 

affect system finances through several channels, 

not just through the ratio of earnings to compensation. Other potential effects include (1)  changing the level and/or composition of employment, 

(2) changing the taxable share of wages, (3) changing the incentives to apply for Disability Insurance 

(DI), and (4)  changing health. The full report discusses each of these effects in greater detail.

The Technical Panel believes that health care reform generates increased uncertainty around several major assumptions, which leads to our recommendation to increase the range of uncertainty 

around the assumptions likely to be affected by 

health care reform, including labor force participation and the earnings ratio. The expanded range reflects the uncertainty inherent in how health care 

reform will unfold. Over time, the extent of uncertainty is likely to narrow, at which point the recommended ranges for the affected assumptions will 

lend themselves to reduction.

Given the uncertainty about how health care 

reform will play out, the Technical Panel also recommends research into the impacts of health care 

reform on relevant outcomes as reform provisions 

start to take effect. Such outcomes include labor 

force participation, disability receipt, the earnings 

ratio, the taxable share, and mortality. The research 

findings should help determine the need for changes to the relevant assumptions and the need for adjustments to the range of uncertainty.

Specific Assumptions

Table 1 lists the Technical Panel’s recommendations for the key demographic and economic assumptions made by the Trustees and used by OACT 

in its projections of OASDI finances. In some cases, 

we concluded that the Trustees’ intermediate-, low-, 

and high-cost assumptions were all reasonable. In 

other cases, we concluded that the Trustees’ intermediate assumptions were reasonable but that the 

range of uncertainty implied by the low- and highcost assumptions was either too narrow or should 

not be symmetric around the intermediate assumption. In still other cases, we identified the need to 

revise the intermediate assumptions as well as the 

range of uncertainty around those assumptions. 

Where we recommended changes to the intermediate assumptions or the range of uncertainty around 

those assumptions, we have explained our justifications in the body of the report and, more briefly, 

in the rest of the executive summary. We discuss, 

first, our recommendations on the demographic 

models and assumptions and then turn to the economic models and assumptions.

■ Demographic Assumptions and 

Methods

Fertility

The Technical Panel examined historical trends 

in fertility in the United States and internationally as well as the factors that explain both temporal trends in fertility and cross-country differences 

in fertility at a point in time and over time. Even 

though the United States has experienced high fertility for several decades relative to other developed 

countries, the factors driving U.S. fertility have 

been relatively stable  for several decades. We see 

no compelling reason to expect significant changes 

to the currently assumed total fertility rate of 2.0 

in the future. While the Technical Panel views stable fertility rates as the most likely future scenario, 

we agree with the 2007 Technical Panel that asymmetric low- and high-cost assumptions are appropriate, although our current estimate of such asymmetry is modest. In particular, the Technical Panel 

recognizes a greater likelihood of declining rather 

than increasing fertility.

Economic downturns consistently reduce fertility, as is the case with the most recent economic 

downturn. As of December 2009 (the most recent 

data available), the severe recession during 2007–

2009 produced a near doubling of the unemployment rate (4.5 to 9  percent)  and fertility declines 

of roughly 5 percent. The Technical Panel believes 

that the recession effects may persist for three or 

four years but that much of the fertility decline is 

the result of postponed childbearing rather than of 

a reduction in family size. As a consequence, on a 

75-year horizon, the fertility effects of the recent 
2011 Technical Panel on Assumptions and Methods 5

Table 1. Summary of Assumption Recommendations

Assumption Intermediate-Cost Low-Cost High-Cost

Total fertility rate

2011 Trustees Report (TR) 2.0 2.3 1.7

Technical Panel recommendation 2.0 2.2 1.6

Life expectancy in 2085a

2011 TR 85.0 81.3 89.0

Technical Panel recommendation 88.7 83.7 93.7

Net immigration

2011 TR in 2085 (000s) 1,025 1,310 770 

2011 TR in 2085 (per 1,000 population) 2.2 2.8 1.9 

Technical Panel recommendation

In 2085 (000s) 1,628 2140b 950b

In 2085 (per 1,000 population) 3.2 4.2 2.2

Disability incidence ratec

2011 TR 5.2 4.2 6.3

Technical Panel recommendation 5.8 4.8 6.9

Disability termination death rate in 2085 

2011 TR 11.4 19.8 7.3

Technical Panel recommendation 9.9 17.1 6.3

Disability termination- recovery ratec

 in 2085 

2011 TR 10.7 8.5 12.9

Technical Panel recommendation 8.7 6.0 11.4

Labor force participation ratec in 2085 

2011 TR 66.6 66.3 66.3

Technical Panel recommendation 68.2 70.3 64.8

Unemployment rate

2011 TR 5.5 4.5 6.5

Technical Panel recommendation 5.5 4.5 6.5

Components of real wage growth

Productivity

2011 TR 1.7 2.0 1.4

Technical Panel recommendation 1.7 2.0 1.4

Compensation to GDP

2011 TR 0.0 0.0 0.0

Technical Panel recommendation

First 25 years (2011–2035) 0.0 0.1 -0.1

Next 50 years (2036–2085) 0.0 0.0 0.0

Earnings to compensation

2011 TR -0.1 0.0 -0.2

Technical Panel recommendation 0.0 0.1 -0.1

Hours worked

2011 TR 0.0 0.1 -0.1

Technical Panel recommendation 0.00 0.05 -0.15

PGDP-CPI price differential

2011 TR -0.4 -0.3 -0.5

Technical Panel recommendation -0.2 -0.1 -0.3

Net real wage growth

2011 TR 1.2 1.8 0.6

Technical Panel recommendation

First 25 years (2011–2035) 1.50 2.15 0.75

Next 50 years (2036–2085) 1.50 2.05 0.85

CPI

2011 TR 2.8 1.8 3.8

Technical Panel recommendation 2.8 1.8 3.8

Real interest rates

2011 TR 2.9 3.6 2.1

Technical Panel recommendation 2.7 3.6 2.1

Taxable share of payroll

2011 TR 82.9 83.6 82.1

Technical Panel recommendation 82.2 84.3 80.0

a Unisex period life expectancy at birth; b Panel’s estimates; c

 age-sex adjusted.
6 2011 Technical Panel on Assumptions and Methods

recession will exert only a minor effect on Social Security’s fiscal position.

Mortality

The Technical Panel examined historical trends in 

mortality in the United States and internationally, 

focusing on the role of smoking and obesity as drivers of more recent differences in mortality between 

the United States and other developed countries. 

The Technical Panel’s main recommendation with 

respect to mortality is to assume a more rapid increase in life expectancy over the coming decades. 

Earlier Technical Panels made similar recommendations, although our recommendation is for a 

greater upward revision. Specifically, for the intermediate-cost scenario, we assume an increase in life 

expectancy in 2085 to 88.7 years, which is 3.7 years 

higher than the 2011 Trustees Report assumption 

of 85.0 years. Recognizing the high degree of uncertainty about future mortality trends and the lack 

of agreement among experts, the Technical Panel 

also recommends increasing the range between the 

high- and low-cost assumptions to 10 years.

To make the mortality assumptions more understandable to readers of the Trustees Report, the 

Technical Panel recommends summarizing the assumptions about future mortality (as expressed 

here) in terms of life expectancy (at birth) at the end 

of the projection period rather than in terms of the 

ultimate annual reduction in the average  percentage of total age- and sex-adjusted death rates. The 

Trustees Reports before 2001 presented mortality 

assumptions in terms of life expectancy at birth.

In addition, the Technical Panel reiterates the 

recommendations made by earlier Technical Panels 

to abandon separate projections by cause of death; 

such projections add unnecessary complexity and 

are not based on a transparent methodology.

Immigration

Immigration has long accounted for a significant 

share of U.S. population growth. Since 1950, net 

immigration has increased at an average annual 

rate almost three times greater than the overall 

rate of population growth. For most of the past two 

decades, immigration has exceeded levels assumed 

in previous Trustees Reports. The Technical Panel 

commends the Trustees for changes made in the 

2008 Trustees Report that increased assumptions 

on immigration levels, revised the approach for deriving net migration assumptions, and clarified the 

role of the “other than legal” immigrant population. 

Although these changes move in the right direction, some further changes in the methodology for 

projecting immigration are still warranted.

The Technical Panel concurs with the 2003 and 

2007 Technical Panels that, rather than basing immigration on current law, the ultimate assumption 

on net immigration should be linked to population 

size. The demographic and economic asymmetries 

that drive international migration are likely to persist for several decades and result in the continuation of past trends. The Technical Panel recommends that the intermediate assumption should 

ultimately be 3.2 net migrants per 1,000 persons. 

The level of net international migration implied by 

the Technical Panel’s recommendations is about 

1.6 million individuals annually by 2085, which is 

higher than the level assumed in the 2011 Trustees 

Report but not as high as the level implied by the 

recommendations of the 2007 Technical Panel.

Disability

Since the late 1980s, the fraction of non-elderly 

adults between age 25 and 64 receiving DI benefits has more than doubled, rising steadily from 

2.3 percent in 1989 to 4.7 percent by 2010. The increase in DI enrollment is partly a function of the 

changing age structure of the U.S. population, with 

most of the Baby Boom cohort aging into its 50s 

and early 60s over the last 20 years. But the changing age structure of the U.S. population explains 

less than one-fifth of the rise in DI enrollment 

from 1989 to 2010.

The increase in DI enrollment has coincided with 

a steady rise in the share of Social Security expenditures paid out to DI recipients. From 1989 to 2010, 

that share increased from 10 to 18 percent. This 

rise in expenditures has not been matched with a 

corresponding increase in revenue allocated to the 

program. The DI Trust Fund does not satisfy the 

short-range test of financial adequacy, and the 2011 

Trustees Report projects that the DI Trust Fund 

will be exhausted in 2018. This bleak picture may in 

fact be too optimistic, as trends in incidence rates, 

termination rates, and related variables strongly 

suggest that long-run projections significantly understate the program’s future size.
2011 Technical Panel on Assumptions and Methods 7

Population size, the fraction of the population 

that is DI-insured, the disability incidence rate, and 

the termination rate from the program all influence 

the projection of future DI enrollment. The Technical Panel has focused on the last three determinants 

of DI enrollment and recommends changes to both 

the assumed DI incidence and termination rates.

The Trustees currently assume that DI incidence 

will remain stable throughout the 75-year projection period. Given the increasing trend in DI incidence at all ages, the Trustees’ assumption seems 

implausible. Absent a significant change in DI policy, such as a tightening of the program’s medical 

eligibility criteria, a much more likely scenario is 

that the trend toward increasing DI incidence will 

continue for some time. Thus, the Technical Panel 

recommends that the projected age-sex-adjusted 

incidence rates should increase from 5.2 to 5.8 per 

1,000 insured workers.

From 1985 to 2009, the annual exit rate from DI 

fell from 12.0 to 7.7 percent. The average person 

awarded DI benefits now remains in the program 

for much longer than a person in earlier years. Individuals may exit the DI program for one of three 

reasons: (1) conversion to retired worker benefits 

at the full retirement age, (2) death, or (3) recovery. The Technical Panel recommends changes to 

the assumptions about two of the three reasons for 

program termination. Given changes in the underlying health of DI recipients, the Technical Panel 

recommends that projected mortality rates decline 

more rapidly than currently assumed. The Technical Panel also recommends reducing the projected 

recovery rate.

■ Economic Assumptions and 

Methods

Labor Force Participation Rate

The 2003 and 2007 Technical Panels recommended a review and restructuring of the model used to 

project the labor force participation assumptions 

presented in the Trustees Report. We reiterate the 

need for fundamental change. Our suggestions 

might be considered a refinement of earlier Technical Panel recommendations. We acknowledge that 

the philosophy behind the current approach offers 

some merit, but we believe that the current timeseries–based modeling strategy fails to generate 

meaningful projections of either future labor force 

participation rates or the uncertainty surrounding 

the projections.

The Technical Panel recommends moving toward 

a heuristic life-cycle approach to projecting labor 

force participation by age and sex. Ultimately, this 

part of the labor force participation model should 

be driven by life-cycle-specific labor supply measures such as typical age of first entry, percentage 

of the working-age population in the labor force, 

age of primary job exit, and fraction of the retired 

population still working. The Technical Panel’s 

recommended intermediate-, high-, and low-cost 

values are based on consideration of labor force 

participation across eight age/sex groups and thus 

represent a move in the desired direction.

More specifically, the Technical Panel recommends a higher intermediate labor force participation rate of 68.2  percent relative to the currently 

assumed rate of 66.6 percent. The Technical Panel 

also recommends a dramatic increase in the range 

of uncertainty around labor force participation, 

with high- and low-cost values of 64.8 and 70.3 percent, respectively. And, consistent with recommendations on modeling and uncertainty, the Technical 

Panel recommends characterizing labor force participation rates as a basic assumption.

Real Wage Growth Rate

The methodology used in the Trustees Report to 

project real wage growth begins with the productivity growth rate and sequentially considers steps 

that link productivity growth to real wage growth. 

The Technical Panel evaluated all of the components 

that go into calculating real wage growth: annual 

productivity growth, the compensation share of 

GDP, the earnings to compensation ratio, average 

hours of work, and the GDP-CPI price differential.

Productivity Growth. The Technical Panel recommends no changes to the assumptions on productivity growth in the 2011 Trustees Report.

Compensation Share of GDP. The Technical Panel 

recommends maintaining the intermediate assumption for the compensation share at an annual 

growth rate of 0.0 percent. Given variation in the 

compensation share over the past several decades, 

the Technical Panel also recommends introducing 

differences between the low- and high-cost scenarios and the intermediate-cost assumptions. Specifically, starting from a current value of 54.5 percent 
8 2011 Technical Panel on Assumptions and Methods

for the compensation share, the Technical Panel 

recommends that the high- and low-cost scenarios 

should range from 53 to 56 percent over the projection period. Growth rates of -0.1 and 0.1 percent 

per year for 25 years in the high- and low-cost scenarios, respectively, would generate the suggested 

range in the compensation share.

Earnings to Compensation Ratio. The Technical 

Panel recommends increasing the annual rate of 

growth for the earnings to compensation ratio to 

0.0  percent in the intermediate-cost scenario, an 

increase from the current assumption of -0.1 percent. The adjustment for the effects of health care 

reform in the 2010 Trustees Report (an increase of 

0.1  percent per year)  is reasonable and should be 

maintained, pending direct observation of the law’s 

impact in the coming  years. The Technical Panel’s 

recommendation of an intermediate-cost assumption of 0.0 percent incorporates this adjustment.

Average Hours of Work. The Technical Panel recommends maintaining the intermediate-cost assumption for the annual change in hours worked 

at 0.0 percent. The Technical Panel believes that it 

is more likely that hours will decline than substantially increase relative to this benchmark and thus 

recommends an asymmetric range for the highand low-cost assumptions. Specifically, the Technical Panel recommends a low-cost assumption of a 

0.05 percent per year increase in hours worked and 

a high-cost assumption of a -0.15 percent per year 

decline in hours worked.

GDP-CPI Price Differential. Consistent with the 

recommendations of the 2007 Technical Panel, the 

2011 Technical Panel recommends a smaller difference between the inflation rates of the GDP deflator and the CPI than the -0.4 currently assumed by 

the Trustees; specifically, the ultimate price differential assumption should be -0.2 percent per year 

in the intermediate-cost scenario.

Summary of Real Wage Growth. Taken together, 

the Technical Panel’s five recommendations described above generate an intermediate assumption for real wage growth of 1.5 percent per year – a 

level higher than the 1.2 percent per year rate of real 

wage growth assumed in the 2011 Trustees Report.

Unemployment Rate

The Technical Panel recommends no change to 

the assumptions on the ultimate long-run unemployment rate in the 2011 Trustees Report.

Interest Rates

In our assessment of real interest rates, we examined historical data on constant-maturity Treasury Inflation-Protected Securities (TIPS)  and the 

average annual interest rate implied by the TIPS 

yield curve. We concluded that the long-run real 

interest rate of 2.9  percent assumed in the 2011 

and earlier Trustees Reports is too high relative to 

the market-based forecasts implicit in the current 

yields on TIPS. Based on those yields, the Technical Panel recommends a long-run real interest rate 

of 2.7  percent in the intermediate-cost scenario. 

The 2007 Technical Panel also recommended a reduction in the assumed real interest rate, although 

the 2007 recommendation of 2.6 percent is slightly 

lower than our recommendation. We recommend 

maintaining the 3.6 and 2.1  percent assumptions 

for the low- and high-cost scenarios, respectively; 

these assumptions reflect an assessment demonstrating that the range of uncertainty around the 

real interest rate is not symmetric and that the 

risk of a much higher long-run real interest rate is 

greater than the risk of a much lower long-run real 

interest rate.

The Technical Panel also reiterates the recommendation of the 2007 Technical Panel that the 

Trustees place more weight on the forward-looking 

information in recent Treasury yield curves in the 

determination of real and nominal interest rates.

Inflation

The Technical Panel recommended no change to 

the CPI-W growth assumption.

Taxable Share of Covered Wages

Only earnings below the contribution and benefit base (also known as the taxable maximum) are 

subject to OASDI payroll taxes and counted toward 

Social Security benefits. Since 1983, the taxable 

share of all covered wages has trended steadily 

downward, with the only exceptions occurring during economic downturns. Rapid increases in the 

earnings of the very highest earners have driven 

this downward trend. Other contributing factors 

include the aging of the Baby Boomers and changes 
2011 Technical Panel on Assumptions and Methods 9

in the share of compensation spent on employee 

benefits rather than on wages.

The literature and expert judgment are sharply 

divided on the question of whether the earnings of 

the highest earners will continue to outpace earnings at lower points in the distribution. Analysts 

projecting a continuation of the trend toward a 

lower taxable share see few institutional mechanisms that would inhibit further rapid growth in 

earnings for the most highly compensated workers. Those who expect the trend to slow, flatten, or 

reverse point to several factors: the likelihood that 

marginal tax rates will increase, particularly for 

high earners; the potential for health care reform 

to reduce the share of total compensation devoted 

to employer health insurance for middle-income 

workers; and a belief that bubbles fueled much of 

the recent growth in compensation of the highest 

earners and are unlikely to occur again.

The 2011 Trustees Report assumes that the 

taxable share will level off at an ultimate rate of 

82.9 percent of covered payroll for the intermediate-cost scenario. The Technical Panel agrees that 

the arguments in favor of a continued downward 

trend in the taxable share are compelling but recognizes that the trend is unlikely to continue indefinitely. We therefore recommend an ultimate value 

of 82.2  percent for the taxable share of payroll. 

While the evidence supporting a change to the intermediate value of the taxable share is mixed, the 

Technical Panel strongly believes that the uncertainty around earnings variability in the future is 

high and that the currently assumed range between 

the low- and high-cost scenarios is too narrow. The 

Technical Panel also recommends that the Trustees 

Report include the taxable share as one of the key 

assumptions in Table II.C1.

■ Long-Term Financial Status of the 

OASDI Trust Funds under the Technical 

Panel Assumptions

Cumulatively, the Technical Panel’s recommended changes to the Trustees intermediate assumptions would result in slightly improved medium 

Figure 1. Projected Annual Trust Fund Ratio under Intermediate Assumptions: Technical Panel 

Recommendations versus Trustees’ 2011 Assumptions 

Source: 2011 Trustees Report; Projections by the Office of the Chief Actuary, Social Security Administration.

0 

50 

100 

150 

200 

250 

300 

350 

400 

2011 2021 2031 2041 2051 2061 2071 2081 2091 

OASDI Trust Fund balance

Trustees 2011 intermediate cost 

scenario

Technical Panel recommended 

intermediate scenario
10 2011 Technical Panel on Assumptions and Methods

Figure 2. Projected Annual Balances under Intermediate Assumptions: Technical Panel Recommendations 

versus Trustees’ 2011 Assumptions

Source: 2011 Trustees Report; Projections by the Office of the Chief Actuary, Social Security Administration.

-5.0 

-4.0 

-3.0 

-2.0 

-1.0 

0.0 

1.0 

2010 2020 2030 2040 2050 2060 2070 2080 2090 

Percent of taxable payroll

Trustees 2011 intermediate cost 

scenario

Technical Panel recommended 

intermediate scenario

term system finances but a slightly larger 75-year 

actuarial deficit. The Technical Panel believes, however, that the result of these projections is more uncertain than is currently assumed.

Figure 1 compares the projected Trust Fund ratio under the Panel’s recommended assumptions 

with the 2011 projection of the Trustees. The combined OASDI Trust Fund balances remain positive 

only for a single year longer under the Panel’s recommendations, until 2037 rather than 2036.

Figure 2 depicts the trajectory of the projected 

annual balance between the program’s costs and income throughout the projection period. Trust Fund 

balances briefly return to surplus from 2013-2015 

before permanently turning negative, largely because of higher labor force participation assumed 

in the short term. The annual balance between cost 

and income under the Technical Panel’s assumptions is slightly higher (less negative) than assumed 

by the Trustees over the next 50 years, before falling lower (more negative) during the last 15 years 

of the projection horizon. The basic trajectory of 

the system’s finances under either set of assumptions is very similar. Program costs increase much 

more rapidly than income over the next 25 years as 

the baby boom generation retires, and then remain 

between three and four percent of payroll higher 

than income for roughly the next half century. By 

the end of the projection period, the effect of longer 

life spans pushes the annual deficits higher than 

four percent of payroll.

Figure 3 depicts graphically and Table 2 numerically how individual assumptions affect the annual 

and 75-year summarized balances. In the short 

term, the Technical Panel’s assumption of higher 

rates of labor force participation, especially at older 

ages, improves the annual balance by raising income and lower costs as older workers delay retirement. The effects of slightly higher labor force participation on near-term cash flows are significant 

because revenues are higher and outlays are lower. 

Some of this arises because of shifting cash flows 

across time. Younger workers paying more in taxes 

now will receive higher benefits later, which will 

mitigate the positive effect on system finances in 

the future. Also, to the extent that workers eligible 

for benefits delay collecting for a year or two, the 

actuarial adjustment will have an immediate effect 
2011 Technical Panel on Assumptions and Methods 11

Figure 3. Incremental Effect of Individual Technical Panel–Recommended Assumptions on Trustees’ 2011 

Projection of Annual Balances 

Source: 2011 Trustees Report ; Projections by the Office of the Chief Actuary, Social Security Administration.

2010 2015 2020 2025 2030 2035 2040 2045 2050 2055 2060 2065 2070 2075 2080 2085 

Annual balance (percent of taxable payroll)

Trustees 2011 intermediate scenario

Technical Panel Mortality Assumption

Technical Panel Immigration Assumption

Technical Panel Disability Assumption

Technical Panel Real Wage Growth Assumption

Technical Panel Labor Force Participation

Rate Assumption

-6.0

-4.0

-2.0

0.0

Table 2. Summary of Effects of Individual Recommended Assumptions on System Finances

75-year 

balance

Change 

from 

Trustees

25th 

year 

balance 

(2035)

Change 

from 

Trustees

50th 

year 

balance 

(2060)

Change 

from 

Trustees

75th 

year 

balance 

(2085)

Change 

from 

Trustees

Year 

Trust 

Fund 

ratio <0

2011 Trustees Report 

Intermediate -2.22% -3.77% -3.55% -4.24% 2036

Mortality -2.68% -0.46% -3.95% -0.18% -4.33% -0.78% -5.66% -1.42% 2035

Immigration -2.14% 0.09% -3.75% 0.02% -3.36% 0.19% -3.82% 0.43% 2036

Disability -2.37% -0.15% -3.94% -0.17% -3.77% -0.23% -4.45% -0.21% 2035

Labor Force Participation 

Rate -2.14% 0.08% -3.66% 0.11% -3.59% -0.04% -4.30% -0.06% 2037

Real Wage Growth -1.79% 0.44% -3.23% 0.54% -2.67% 0.87% -3.30% 0.94% 2037

Technical Panel 

Intermediate -2.37% -0.15% -3.55% 0.22% -3.52% 0.03% -4.42% -0.18% 2037
12 2011 Technical Panel on Assumptions and Methods

on their benefit level that directly offsets the savings in costs realized in the short-term when they 

delayed collecting

Faster assumed real wage growth raises tax revenues sooner than it raises benefit levels and therefore has a large positive impact on annual balances 

throughout the projection period. Higher net immigration, assumed after 2025, improves annual 

balances in several ways. First, immigrants tend 

to enter the labor force immediately adding to the 

taxable payroll sooner than they begin to collect 

additional benefits. Second, their offspring generate larger future cohorts of workers. Third, some 

proportion of undocumented immigrants, working 

under improper Social Security numbers, may contribute payroll taxes, without ever claiming benefits from those contributions.

Faster growth of the disability system worsens 

annual balances by reducing the amount of taxable 

payroll, increasing the number of beneficiaries, and 

increasing the length of time that disabled beneficiaries are expected to receive benefits. Over the 

75-year projection horizon the assumed increased 

cost of disability raises the actuarial deficit by about 

0.15 percent of payroll and almost offsets the positive impact of higher assumed levels of immigration and rates of labor force participation.

The Technical Panel’s assumption of longer life 

expectancy raises program costs as retirees are expected to collect benefits for longer periods. The impact grows over time, reducing the annual balance 

by -0.18 percent of payroll relative to the Trustees’ 

projection in 2035, by -0.78 percent in 2060, and by 

-1.42% by 2085. Over the entire 75-year projection 

horizon, the assumption of longer life spans has 

the largest effect on system finances of any single 

recommended assumption, followed very closely 

but with the opposite impact on finances, of faster 

growth in real wages.

The effect of lower real interest rates is not reflected in the Figure 3 or Table 2, but lower rates 

reduce interest income from the Trust Fund, raising the 75-year actuarial deficit. In addition, lower 

interest rates make values summarized in present 

value calculations appear larger, and the impact increases with the length of the summarized projection horizon.
2011 Technical Panel on Assumptions and Methods 13

Chapter 1: Methodology

1.1 Presentation of Uncertainty

The three most recent Technical Panels have all 

expressed dissatisfaction with the Trustees Reports’ 

analysis and presentation of uncertainty about 

long-run Social Security finances. Some of that dissatisfaction has led to important methodological 

innovations developed by the Office of the Chief Actuary (OACT). As a result, the Trustees Report now 

contains three types of uncertainty analysis: highand low-cost scenarios, stochastic simulation, and 

sensitivity analysis. Although some work remains 

to be done on the empirical analysis of uncertainty, 

we focus primarily on how uncertainty is presented. 

Building on the suggestions of earlier Technical Panels, we set forth three recommendations that are 

intended to make the presentation of uncertainty 

more useful to a broad spectrum of readers.

Presentation Recommendation P-1. The Technical 

Panel recommends expanding the list of key assumptions in summary Table II.C1 to include missing drivers of long-run Social Security finances. In 

addition, as warranted, the Technical Panel recommends presenting the values for key assumptions in 

a way that is useful to readers. Improved communication will likely involve reporting values for “indicator” variables that are directly determined by the 

more precise (but not easily interpretable  )  basic 

assumptions.

Presentation Recommendation P-2. The Technical 

Panel recommends removing the current presentation of uncertainty from the Summary (Chapter II) and from the section on Long-Run Actuarial 

Estimates (Chapter IV) and recommends replacing 

the Summary chapter  presentation with sensitivity analysis for each of the key drivers of system 

finances. In addition, the Technical Panel recommends basing the selection of the low- and highcost values for key assumptions on consistency – in 

a probabilistic sense – both across and within assumptions. In other words, it is essential to make 

certain that the low- and high-cost values for any 

given variable are equally likely alternatives with 

respect to the intermediate alternative, even if this 

implies an asymmetric range between the intermediate and the high- and low-cost assumptions. 

Further, the Technical Panel recommends ensuring 

that the likelihood of realizations within the range 

of outcomes is the same across all key assumptions.

Presentation Recommendation P-3. The Technical 

Panel recommends adding a chapter on uncertainty 

that explains, compares, and contrasts the highand low-cost scenarios with integrated scenarios 

and stochastic simulation. The Technical Panel also 

recommends emphasizing that sensitivity analysis 

is the starting point for every measure of overall 

uncertainty and noting that any overall measure of 

uncertainty involves varying the combinations of 

key assumptions in particular ways. Each scenario 

and stochastic approach should be presented in a 

comparable way, specify how the key assumptions 

vary in each measure of overall uncertainty, and 

discuss the impact on various measures of system 

financial outcomes.

Key Drivers of Long-Run System Finances

The Trustees Report introduces the concept of 

uncertainty within the first few pages of a lengthy 

document. Such an approach is appropriate in making readers aware that the baseline projections are 

sensitive to a handful of critical assumptions and 

that uncertainty is associated with the values for 

those assumptions. The first reference to uncertainty arises in summary Table  II.C1, which lists 

three sets of long-range values for eight “key” de-
14 2011 Technical Panel on Assumptions and Methods

mographic and economic assumptions. The three 

sets of values pertain to the intermediate-, high-, 

and low-cost projections that reflect the “range of 

possible future experience.”

Tying uncertainty about system finances to uncertainty about input assumptions is an excellent 

starting point. Indeed, the Technical Panel’s first 

recommendation involves two marginal improvements that build on an already successful approach. 

The first recommendation calls for expanding the 

list of assumptions in Table II.C1 in order to provide 

the reader with a comprehensive list of the key drivers of long-run system finances. The second suggestion calls for presenting the assumptions in a more 

user-friendly way that could involve mapping some 

highly specific input assumptions into “indicator” 

variables with which readers enjoy some familiarity.

What Makes an Assumption “Key”?

The eight assumptions listed as key determinants 

in Table II.C1 receive considerable attention in the 

Trustees Report’s deliberations and are the focus of 

quadrennial Technical Panel reports. However, the 

Technical Panel believes that the current list is incomplete and that Table II.C1 should be expanded 

to include other key determinants of system finances. The Technical Panel recognizes the need to balance incremental information against the potential 

for overloading readers, but readers are currently 

left unaware of critical sources of uncertainty about 

long-run system finances. 

A few systematic criteria should be applied to determine if a given assumption should be included in 

the Summary. First, any assumption should have a 

significant exogenous component; that is, it should 

not lend itself to significant prediction by the other 

key assumptions in the projection. Second, the assumption itself should generate significant uncertainty. Third, varying the assumption across the 

range of possible future experience should have a 

noticeable impact on system finances.1

 Even though 

many assumptions could ultimately meet these criteria, the Technical Panel suggests that labor force 

participation, disability incidence and termination, 

and the taxable share of earnings are clear examples 

that may be added with modest effort (Table 3).

The first example of a missing key driver is 

labor force participation. Currently, labor force 

participation is treated as the outcome of a model 

described in Chapter  V of the Trustees Report, 

along with other key elements of the projection. 

1 Interestingly, one of the assumptions on the current list – the 

unemployment rate – would probably not meet these criteria 

because the effect on system finances in the current model is 

second-order. The unemployment rate should remain on the list 

for both historical and evolutionary reasons, however. If and when 

the projection framework shifts to a more “bottom-up” micro-level 

approach for taxable earnings, the unemployment rate will become 

more important.

Table 3. Proposed Replacement for Table II.C1 from 2011 Trustees Report – Long-Range Values of Key 

Demographic, Programmatic, and Economic Assumptions for the 75-Year Projection Period

Intermediate-Cost Low-Cost High-Cost

Long-Range Demographic Assumptions

 Total fertility rate (children per woman), starting in 2035 2.0 2.3 1.7

 Average period life expectancy at birth in 2085 85.0 81.3 89.0

 Average annual net immigration for 2011 – 2085 (000s) 1,075 1,385 785

Long-Range Programmatic Assumptions

 Disability incidence rate in 2030 (per 1,000 exposed, age-sex -adjusted) 5.2 4.2 6.3

 Disability recovery-termination rates 2030 – 2085 (per 1,000) 11.0 9.0 13.0

Long-Range Economic Assumptions

 Age-sex-adjusted labor force participation rate in 2085 66.6% 70.0% 63.3%

 Average annual real wage differential (percent) for 2021 – 2085 1.2 1.8 0.6

 Consumer Price Index (CPI), starting in 2019 2.8 1.8 3.8

 Unemployment rate (percent), starting in 2021 5.5 4.5 6.5

 Annual trust fund real interest rate (percent), starting in 2022 2.9 3.6 2.1

 Taxable share of payroll, starting in 2020 82.9 85 80.7

Note: All values from 2011 Trustees Report, except values for low- and high-cost labor force participation rates and taxable share of payroll are specified 

by Technical Panel.
2011 Technical Panel on Assumptions and Methods 15

Chapter  V also includes the criteria underlying 

the choice of values for the key assumptions in 

summary Table II.C1. However, the discussion in 

Chapter V makes it clear that labor force participation is in effect largely exogenous. Despite a 

structural model that relates labor force participation to (for example)  longevity increases, the 

Trustees Report contains a telling description of 

the inconsistency:

“The projected labor force participation rates 

are not basic assumptions. They are derived 

from a historically-based structural relationship using demographic and economic 

assumptions specific to each alternative. 

However, the participation rates are not 

highly sensitive to most of the demographic 

and economic assumptions. Accordingly, the 

projected labor force participation rates do 

not vary substantially into the future and 

across alternatives.”

In sum, labor force participation is set and held 

fixed across alternatives, thereby eliminating any 

uncertainty about system finances arising from 

uncertainty about labor force participation. In fact, 

labor force participation, especially among the population age 62 and older, matters a great deal for 

Social Security finances. One set of estimates from 

OACT shows, for example, that if labor force participation among those age 45 and older returns to 

1950s levels, half of the long-run summary actuarial balance would be resolved, delaying Trust Fund 

exhaustion by 18 years to 2055.2

 This assumption 

is probably extreme, but it arguably lies within the 

range of “possible future experience.” In any event, 

the criteria outlined above for categorizing labor 

force participation as a key assumption are all satisfied: labor force participations is largely exogenous 

with respect to the other key assumptions, there is 

uncertainty about whether the upward trend in labor force participation for the populations age 62 

and older that has characterized the past two de2 Based on testimony from Stephen C. Goss before the U.S. Senate 

Committee on Finance, July 15, 2010. Full text of the testimony may be found at http://www.ssa.gov/legislation/testimony_071510.htm. Another useful reference on the effects of varying 

the labor force assumption is Maestas and Zissimopoulos (2010). 

They show that continuation of the trend over the last two decades 

toward increasing labor force participation among the population 

age 62 and older would largely abate the projected surge in the 

beneficiary-to-worker ratio.

cades will continue, and the assumption has a firstorder impact on system finances. 

A second example of missing key assumptions 

involves disability incidence and termination. 

Rapid growth in the disability rolls is placing increased pressure on overall system finances, and 

the growth in disability prevalence may be traced 

back to both the incidence of disability and reduced 

rates of disability due to death as the nature of impairments has evolved. Interestingly, Chapter V of 

the Trustees Report devotes considerable attention 

to disability, which is also included in the sensitivity analysis of Appendix D. One complication that 

arises with disability is how to account for the conversion from disabled to retired worker beneficiary 

status that occurs at the Full Retirement Age, but 

that does not eliminate the need to draw out the 

implications of disability for overall system finances at any time point.

The third assumption suggested for inclusion 

in Table II.C1’s list of key assumptions is the taxable share of wages, which captures the effect of 

changes in the earnings distribution across the 

working population, but particularly around the 

statutory taxable threshold. Currently, the Trustees Report assumes that the taxable earnings share 

is effectively fixed at its most recent (cyclically adjusted) value. In fact, the taxable share has fallen in 

the past few decades, and there is no consensus as 

to why or whether the taxable share will continue 

to fall, stabilize, or even return to previous values. 

The assumed value of the taxable share matters a 

great deal for Social Security finances because moving a marginal dollar from just above to just below 

the taxable threshold has a large positive impact 

on system finances: the system collects revenue 

at a flat rate on taxable wages, but the progressive 

payout formula means that the benefits paid on 

earnings just below the taxable threshold are much 

lower than the revenue collected. 

Specific values of ranges for the three inputs discussed above  – labor force participation, disability, and, taxable share of wages – undergo review 

at length in later sections of this Technical Panel 

report. Two subthemes underlying the review are 

the considerable uncertainty associated with the 

three inputs and the notion that these inputs matter significantly for system finances. However, the 

suggestion for adding the inputs to the Summary 

chapter on uncertainty is independent of how the 

Trustees react to the specific suggested values 

presented later; the point is that readers of the 
16 2011 Technical Panel on Assumptions and Methods

Trustees Report should know that system finances 

depend importantly on key input assumptions, 

which in turn embody considerable uncertainty. 

Thus, the following analysis is based on the range 

for these inputs as specified in the 2011 Trustees 

Report and not on the Technical Panel’s recommended values.3

Making Reported Assumption Values UserFriendly

Some of the values for key assumptions in the 

Summary chapter  of the Trustees Report are presented with great precision, but extreme precision 

can make it difficult to interpret both the intermediate assumption and the high- and low-cost range. 

Given the tradeoff between a high level of precision 

and effective communication, the Technical Panel 

believes that the Trustees Report should present a 

readily comprehensible discussion of the assumptions underlying the alternatives.

The best example of a tradeoff between precision 

and ease of interpretation is the presentation of 

mortality assumptions. The values reported in Table II.C1 pertain to the “Average annual percentage 

reduction in total age-sex-adjusted death rates from 

2034 to 2084.” While the table  presents a highly 

precise concept, the interested reader can find the 

more typical measure of longevity improvement – 

the implied increase in life expectancy  – carefully 

derived from the underlying death rate assumption 

in Chapter V of the Trustees Report. Although the 

other key assumptions in Table II.C1 are presented 

as easily interpretable growth rates or levels, some 

other measures in the report recommended for elevation to the level of “key” assumptions, such as 

disability incidence and termination rates and labor 

force participation, could be presented in either a 

more precise but less clear way, or in a less precise 

but more clear way.

Informed readers who have thought deeply about 

modeling mortality improvement will generally 

know exactly what assumptions undergird the table. However, the cost of specificity is that the casual reader – or even experts accustomed to looking 

at life expectancy projections as consumers  – will 

find the age-sex-adjusted death rates uninformative. Thus, inserting the implied life expectancy 

outcomes in the summary table  and moving the 

more detailed underlying assumption to the section 

3 The two exceptions are labor force participation and taxable share 

of earnings in that the current Trustees Report includes no meaningful variation for those inputs.

in Chapter  V intended for in-depth consideration 

will likely improve communication with no loss in 

precision. Indeed, the only objection the Technical 

Panel can foresee is that some might argue that different profiles of decreasing death rates (by age and 

sex)  would lead to the same change in life expectancy. Given that details about how death rates are 

perturbed appear in Chapter  V, such an objection 

should not arise.

The Technical Panel recommends that the modest additions to Table II.C1 should be the first step 

in the Trustees Report’s production and evaluation 

process. One reason for incrementally increasing 

the list of key assumption is that the Technical 

Panel also recommends subjecting each key assumption to sensitivity analysis, which is the second of the three suggestions regarding uncertainty 

as described below.

Sensitivity Analysis Should Be the Starting Point

A focus on sensitivity analysis in the Summary 

section will dovetail tidily with the suggested expansion of key assumptions. The relatively early 

introduction of sensitivity analysis will establish 

a key set of building blocks for the proposed new 

chapter  on measures of overall uncertainty, also 

proposed by the Technical Panel (our third suggestion as described in the next section). In effect, the 

Technical Panel believes that much progress has 

been made on the analysis of uncertainty recommended by previous Technical Panels, but a reordering and change of emphasis is needed to compare, contrast, and reconcile the various measures. 

The Trustees Report currently uses three approaches to presenting uncertainty. Though a case 

may be made for each approach, the current structure of the Report leads to confusion and even 

apparent inconsistencies. Currently, high- and 

low-cost scenarios are used in both the Summary 

(Chapter II) and the long-run section on actuarial estimates (Chapter IV). Stochastic simulation appears 

in the Summary (Chapter II) and in Appendix E, and 

sensitivity analysis is relegated to Appendix D. The 

Trustees Report does not as yet embody other types 

of “integrated” scenarios as recommended by the 

two previous Technical Panels.

Several approaches to presenting uncertainty are 

needed as each is characterized by strengths and 

weaknesses. However, there are several problems 

with how the three presentations are organized 

throughout the document.
2011 Technical Panel on Assumptions and Methods 17

■ In an apparent contradiction between scenario and stochastic results, the summary presentation (Chapter  II)  focuses on Trust Fund ratios. 

Specifically, it appears that the statistical likelihood of the low-cost scenario is negligible.

■ Details are lacking about which input assumptions are varied and how they are varied in order 

to produce a range of possible outcomes for overall system finances.

■ The report has a skewed emphasis on low- and 

high-cost scenarios; for example, only low- and 

high-cost scenarios appear in the long-run section of the actuarial estimates (Chapter IV).

■ The unsubstantiated repudiation of stochastic 

results suggests that further refinement will confirm the low- and high-cost scenario ranges.

■ Most important, the sensitivity of overall 

system finances to varying each key assumption 

across its feasible range, the fundamental building block for all uncertainty analysis, is buried in 

an appendix. 

Most of these problems are the basis for our proposed new chapter on uncertainty, as described in 

the next section. For now, we focus on why and 

how sensitivity analysis should become the starting point for the discussion on uncertainty. 

Any measure of uncertainty about the overall 

outcomes of a complicated model (in this case, the 

output is system finances) begins with varying the 

input assumptions. Scenario analysis involves moving one or more input assumptions in a systematic 

way; for example, the low- and high-cost scenarios 

shift all key assumptions (though again, it is not 

obvious exactly what moves) to their low- or highcost values. For each key assumption, stochastic 

analysis samples from (an estimate of) the underlying probability distribution of that assumption. In 

both cases, the model is perturbed by introducing 

new values for assumptions. In other words, the 

initial step in any uncertainty analysis is to measure 

the model’s sensitivity to changes in the inputs.

The reader interested in understanding uncertainty about system finances should know why uncertainty exists, how it relates to various inputs, 

and when that uncertainty will manifest itself in 

terms of affecting system finances. There are many 

ideas about how to aggregate the sensitivity of finances when varying several inputs in a scenario or 

stochastic framework, but varying any particular 

input across a fixed range and measuring the response of system finances transcends those differences. Sensitivity analysis is the starting point for 

any uncertainty measure.

Many approaches lend themselves to presenting sensitivity analysis in a summary format by 

demonstrating how system finances are affected 

and over what period of time. One approach to reporting the results of sensitivity analysis is to introduce a new table (what would become Table II.

C2) in the Summary section that matches the new 

Table II.C1 along the main rows, shows the effect 

of varying the assumptions from high to low in 

sub-rows, and displays the time dimension across 

columns (Table 4). An alternative approach some 

readers may find more intuitive is to display ranges 

(Figure 4). Both approaches convey the extent to 

which uncertainty about particular assumptions 

leads to uncertainty about system finances and the 

timing of that uncertainty.

What will readers of the Trustees Report learn 

from the new emphasis on sensitivity analysis? 

One important lesson is that, despite uncertainty 

about the various inputs, the uncertainty associated with any input assumption is generally not 

sufficient to reverse the conclusion that system 

finances are expected to deteriorate over the next 

several decades. Another important lesson is that 

uncertainty increases dramatically with the length 

of the projection period, especially for assumptions 

involving cumulative effects such as mortality and 

fertility. A third important message is that some input assumptions such as labor force participation, 

real wage growth, and the taxable share of earnings 

warrant careful observation and could become key 

inputs into the policymaking process. A relatively 

modest improvement in any one of the three inputs would eliminate much of the expected deficit 

in the OASDI Trust Funds for all forecast horizons. 

If, for example, labor force participation increases, 

the positive effect on system finances would suggest the need for a lower near-term reduction in 

benefits or a smaller tax increase.

In addition to providing a more systematic approach to uncertainty, three reasons point to the 

advisability of leading off the Trustees Report with a 

discussion of sensitivity analysis. First, researchers 

inside and outside OACT will be better able to make 

direct comparisons of alternative models in terms 

of both the impact on baselines and how the model 

responds to changing inputs. Second, some observers will inevitably argue that the analysis of uncertainty in the Trustees Report neglected to highlight 

some important insights and therefore will suggest 
18 2011 Technical Panel on Assumptions and Methods

several integrated scenarios. While interaction effects militate against combining sensitivity analysis across two or more inputs, the same observers 

will nonetheless be better able (without direct input 

from OACT) to think about moving several inputs 

in deliberate ways to obtain new insights. Finally, 

sensitivity analysis may help improve coordination 

of uncertainty analysis between the OASDI and 

Medicare Trustees Reports. The two programs share 

many key input assumptions, but one Medicare input (the so-called excess cost growth rate) has only 

a second-order impact on OASDI (through the taxable share of compensation). 4

A New Chapter on Uncertainty Measures

One of the recommendations in the 2003 Technical Report called for adding a chapter on uncertainty to the Trustees Report. With that change yet 

to be made, the 2011 Technical Panel repeats the 

call for a new chapter devoted to a focused discussion on uncertainty. The Technical Panel believes 

that adopting our first two suggestions on presenting uncertainty makes the addition of a chapter on 

4 All values in the table are based on Trustees Report (2011) assumptions, with the exception of labor force participation rate 

and taxable share, which take on the range recommended by the 

Technical Panel (see Table 1).

Table 4. Proposed New Table II.C2. Sensitivity of Actuarial Measures to Variation in Long-Range Values of 

Key Demographic, Programmatic, and Economic Assumptions for the 75-Year Projection Period5

Summary Actuarial Measure

25-Year: 

2011–

2035

50-Year: 

2011–

2060

75-Year: 

2011–

2085

Annual 

Balance 

for 2085

All Assumptions at Intermediate Values -0.60 -1.78 -2.22 -4.24

Effect of Varying Long-Range Demographic Assumptions

Total fertility rate (children per woman), starting in 2035

Low-cost -0.62 -1.70 -1.86 -2.43

High-cost -0.58 -1.88 -2.60 -6.50

Average period life expectancy at birth in 2085

Low-cost -0.37 -1.29 -1.54 -2.75

High-cost -0.77 -2.23 -2.86 -5.58

Average annual net immigration for 2011 – 2085 (000s)

Low-cost -0.49 -1.60 -2.01 -3.88

High-cost -0.70 -1.97 -2.44 -4.66

Effect of Varying Long-Range Programmatic Assumptions

Disability incidence rate in 2030 (per 1,000 exposed, age-sex-adjusted)

Low-cost -0.38 -1.52 -1.95 -3.91

High-cost -0.80 -2.04 -2.49 -4.56

Disability recovery-termination rates 2030 – 2085 (per 1,000)

Low-cost -0.56 -1.73 -2.17 -4.17

High-cost -0.63 -1.82 -2.26 -4.28

Effect of Varying Long-Range Economic Assumptions

Age-sex -adjusted labor force participation rate in 2085

Low-cost -0.21 -1.45 -1.95 -4.15

High-cost -1.03 -2.16 -2.54 -4.34

Average annual real wage differential (percent) for 2021 – 2085 

Low-cost -0.09 -1.01 -1.36 -2.71

High-cost -1.11 -2.58 -3.10 -6.00

Consumer Price Index, starting in 2019

Low-cost -0.48 -1.61 -2.02 -3.97

High-cost -0.73 -1.98 -2.44 -4.54

Annual Trust Fund real interest rate (percent), starting in 2022

Low-cost -0.39 -1.50 -1.89 -4.24

High-cost -0.84 -2.10 -2.60 -4.24

Taxable share of payroll

Low-cost -0.35 -1.54 -2.00 -4.09

High-cost -0.86 -2.05 -2.47 -4.41
2011 Technical Panel on Assumptions and Methods 19

uncertainty both desirable and feasible. Given that 

the early part of the report will present a comprehensive list of key assumptions and a sensitivity 

analysis for each assumption, it makes sense to 

build on that presentation and describe how variation in the assumptions leads to different conclusions about overall uncertainty. In the absence of 

one perfect way to characterize overall uncertainty 

about Social Security system finances, the various 

alternatives will at least work from the same building blocks. 5

The goal of the new chapter  is to consider possible ways of devoting equal attention to measuring 

and presenting overall uncertainty about system 

finances. The new chapter would explain, compare, 

and contrast high- and low-cost scenarios, integrated scenarios, and stochastic simulation and recognize that each approach to characterizing uncer5 All values in the table are based on Trustees Report (2011) 

assumptions, with the exception of labor force participation rate 

and taxable share, which take on the range recommended by the 

Technical Panel (see Table 1).

tainty involves its own strengths and weaknesses 

and thus may be better suited to different applications. In short, the alternative approaches should 

not be presented as simple alternatives without explanation and a discussion of appropriate context. 

The new chapter should address how and why the 

different approaches to varying inputs lead to different conclusions about the uncertainty of overall 

system finances. 

The case for a new chapter on uncertainty begins 

with the apparent contradiction that many readers 

experience when they first encounter the extent to 

which high- and low-cost Trust Fund ratios diverge 

from stochastic projections. That apparent inconsistency stems from the presentation on uncertainty for Trust Fund ratios in the current Trustees 

Report Summary chapter  . The reader encounters 

two charts, both built around the intermediate projection, but with different bands characterizing uncertainty. To highlight the apparent contradiction, 

the Technical Panel has combined the data from the 

two charts into a single chart (Figure 5).

Figure 4. Sensitivity of Summarized Actuarial Balance to Range of Assumptions: 25-, 50-, and 75-Year 

Horizons (as a Percent of Taxable Payroll)4

Source: 2011 Trustees Report, Appendix D; additional estimates provided by Office of the Chief Actuary, Social Security Administration.

-3.50 

-3.00 

-2.50 

-2.00 

-1.50 

-1.00 

-0.50 

0.00 

Fertility 

Mortality 

Net immigration 

Disability incidence 

Disability termination 

Labor force 

Real wage growth 

Consumer Price Index 

Real Interest rate 

Taxable share 

Fertility 

Mortality 

Net immigration 

Disability incidence 

Disability termination 

Labor force 

Real wage growth 

Consumer Price Index 

Real Interest rate 

Taxable share 

Fertility 

Mortality 

Net immigration 

Disability incidence 

Disability termination 

Labor force 

Real wage growth 

Consumer Price Index 

Real Interest rate 

Taxable share 

25-year horizon: 2011-2035 50-year horizon: 2011-2060 75-year horizon: 2011-2085 

High-Cost Low-Cost

Intermediate

Actuarial balance as percent of taxable payroll
20 2011 Technical Panel on Assumptions and Methods

The newly created chart shows that, under the 

high-cost assumptions, the Trust Fund is exhausted in 2029, a little less than a decade earlier than 

in the intermediate case. Under the low-cost assumptions, the Trust Fund remains solvent; in 

fact, the Trust Fund ratio rises after 2055. However, the stochastic analysis yields what appears 

to be a markedly different view of uncertainty. 

The 2.5th  percentile of outcomes shows a Trust 

Fund that is exhausted in 2030, which is roughly 

the same as the high-cost outcome. However, the 

97.5th  percentile shows a Trust Fund that is exhausted in 2049, with a downward trajectory that 

diverges markedly from the low-cost scenario. As a 

summary chapter, the current text presents these 

stark differences with little context or explanation6

6 The only attempt at reconciling the two sets of uncertainty 

measures involves a disproportionate qualification of the stochastic 

projections. The accompanying text states that “. . .the relationship 

between the stochastic results and the low- and high-cost alternatives may change as the methodology for the stochastic simulations 

is further developed. As noted in Appendix E, future improvements 

and refinements are expected to be more likely to expand rather 

than reduce the indicated range of uncertainty.”

and is precisely why the Technical Panel argues for 

a new chapter on uncertainty.

How Do the Scenario and Stochastic Simulation 

Approaches Differ?

The Trustees Report is careful to describe highand low-cost scenarios as a “range of possible future outcomes” while the stochastic projections 

estimate the “probability distribution of future 

outcomes.” This terminology does not reflect the 

substantive similarities and differences between 

approaches. The important similarities tie back 

to sensitivity analysis; that is, both approaches 

change key input assumptions and recalculate the 

trajectory for system finances. The important difference between scenario and stochastic analysis is 

how the key input assumptions vary.

Three dimensions warrant consideration when 

changing the key input assumptions and resolving 

the model for system financial outcomes. The first 

dimension is the typical distance from the means or 

expected values across input assumptions; the second dimension is the persistence of the deviations 

from the means; and the third dimension is the corFigure 5. Comparison of Deterministic Scenarios and Stochastic Trust Fund Ratios,

2011 Trustees Report

Source: 2011 Trustees Report, Figures II.D6 and II.D7.

0% 

50% 

100% 

150% 

200% 

250% 

300% 

350% 

400% 

2011 

2014 

2017 2020 2023 2026 2029 2032 2035 2038 2041 

2044 

2047 2050 2053 2056 2059 2062 2065 2068 2071 

2074 

2077 2080 2083 

Stochastic 2.5%

Stochastic 50%

Stochastic 97.5%

High-Cost

Trust Fund ratio

Year

Intermediate

Low-Cost
2011 Technical Panel on Assumptions and Methods 21

relation in deviations from means across the various input assumptions. Every stochastic simulation 

involves the selection of a unique value of each key 

input assumption in every year of the simulation 

while high- and low-cost scenario analysis involves 

the selection of one new value that will hold for the 

entire projection period. However, that is just the 

starting point: understanding the implications for 

the range of system financial outcomes requires 

characterizing the difference in simulation strategy 

in terms of the three dimensions. 

The first dimension, which is the typical deviation between the baseline input assumption value 

and alternative simulation value(s), turns out not 

to be pivotal to understanding why stochastic simulations diverge from high- and low-cost simulations 

(Table 5). The high- and low-cost values for the key 

input assumptions do not differ significantly from 

Table 5. 75-Year Values for Input Assumptions in Deterministic and Stochastic 

Uncertainty Calculations: 2004

Central Values Deterministic Range Stochastic Range

Deterministic Stochastic Low-Cost High- Cost

2.5th

percentile

97.5th

percentile

Demographic Assumptions

Average total fertility rate 2.0 2.0 2.2 1.8 2.3 1.6

Increase in male period life 

expectancy at birth 6.9 7.4 3.6 11.3 2.9 11.3

Increase in female period life 

expectancy at birth 5.6 5.9 2.6 9.6 2.1 10.2

Increase in male period life 

expectancy at age 65 4.2 4.5 1.7 7.5 1.6 8.3

Increase in female period life 

expectancy at age 65 3.9 4.3 1.4 7.1 0.9 8.6

Average legal immigration 812 811 1,070 685 1,127 491

Average legal emigration 203 203 214 206 210 196

Average net other immigration 320 320 470 570 207 75

Economic Assumptions

Average unemployment rate 5.5 5.6 4.6 6.4 4.7 6.7

Average (geometric) inflation 

rate 2.8 3.0 1.8 3.8 1.8 4.6

Average (geometric) real interest 

rate 3.0 3.0 3.7 2.2 3.9 2.1

Average (geometric) real average 

covered wage 1.1 1.1 1.6 0.6 1.7 0.6

Programmatic Assumptions

Average male disability 

incidence rate 6.1 6.1 5.0 7.3 5.6 6.6

Average female disability 

incidence rate 5.2 5.2 4.2 6.2 4.7 5.7

Average male disability recovery 

rate 11.5 11.5 13.5 8.4 12.4 10.6

Average female disability 

recovery rate 10.4 10.4 12.3 7.7 11.2 9.5

Source: Social Security Actuarial Study No. 117, September 2004.
22 2011 Technical Panel on Assumptions and Methods

the 95 percent confidence intervals for the average 

realizations of the stochastic draws for those variables. Despite some differences between the highand low-cost ranges and the 95 percent confidence 

range for the average of draws across inputs over 

the 75-year projection period, such differences are 

small and not systematic. That is, in some instances, the stochastic range is wider than the high- and 

low-cost range; in other instances, the range is narrower.7

 Ruling out differences in typical deviations from 

central tendencies across input assumptions has a 

testable implication for the system’s financial projections. In any given year of the projection, the 

range of average realized values for every input 

through that particular projection year is similar 

to the range for the high- and low-cost values. In 

other words, in any given projection year, the range 

7 This is actually a reassuring finding because it suggests that, 

although there is no specific probabilistic interpretation assigned to 

the high- and low-cost ranges, the ranges are consistent in practice 

with the time-series decomposition of historical variation that 

underlies the stochastic approach.

for system flows in that particular year should be 

similar. This is distinct from saying that the range 

of cumulative outcomes through that particular 

projection year should be similar; it is effectively a 

flow versus stock concept.

The prediction associated with the similar ranges 

for the key input assumptions is supported by data 

from the Trustees Report (Figure 6). The cost rate 

is effectively benefits paid divided by taxable payroll in any given year. The range of the 95 percent 

confidence interval for cost rates from the stochastic projections is very similar to the high- and lowcost scenario cost rates, especially at long horizons. 

Indeed, had a figure such as Figure 6 been the first 

item a reader encountered, the differences between 

stochastic and high- and low-cost scenario analysis 

might be considered second-order.

Given that the ranges for (average) values across 

the input assumptions are not markedly different 

and that the resulting ranges for annual system 

financial flows are similar, why do the ranges for 

projected Trust Fund ratios differ so dramatically? 

Clearly, it is the approach of cumulating persistent

Figure 6. Comparison of Deterministic Scenarios and Stochastic Cost Rates, 2011 Trustees Report

Source: 2011 Trustees Report, Figures IV.B1 and VI.E2.

0% 

5% 

10% 

15% 

20% 

25% 

30% 

2011 

2014 

2017 2020 2023 2026 2029 2032 2035 2038 2041 

2044 

2047 2050 2053 2056 2059 2062 2065 2068 2071 

2074 

2077 2080 2083 2086 

Percent of taxable payroll

Year

Stochastic 2.5% 

Stochastic 50% 

Stochastic 97.5% 

Low-cost 

Intermediate 

High-Cost 
2011 Technical Panel on Assumptions and Methods 23

and correlated deviations across input assumptions 

in the high- and low-cost scenarios that leads to the 

apparent contradictions about Trust Fund ratios, 

not the range for any given input assumption in 

any given year. This is the crucial message that the 

reader of the Trustees Report never sees. Rather, 

the divergence in ranges for Trust Fund ratios is inappropriately attributed to fundamentally different 

beliefs about the input assumptions.8

Should a reader of the Trustees Report think of 

the low-cost projection for the Trust Fund ratio 

as a serious possibility? The decomposition above 

makes it clear what would be involved. Not only 

would every input assumption need to be realized 

at what can be thought of as its 97.5th  percentile 

low-cost value, it would also have to do so in every

projection year. It is the persistence of and correlation between input assumptions that drives the 

cumulative outcomes such as the Trust Fund ratio, 

not some fundamental disagreement about the 

possible future range for any given input assumption. The low-cost range seems unlikely from the 

perspective of the stochastic simulations because 

it requires an unlikely combination of movements 

in input assumptions, not because any given input 

assumption moves in an unlikely way. 

In addition to comparing and contrasting the 

various approaches to presenting uncertainty, one 

other aspect of the suggestion for adding a new 

chapter on uncertainty is equal treatment. The alternative measures – high- and low-cost scenarios, integrated scenarios, and stochastic analysis – should 

all be presented on an even footing. Establishing 

equality will involve reorganizing some long-standing presentations in the Trustees Report. In particular, although the current Trustees Report presents 

both stochastic and high- and low-cost analysis of 

Trust Fund ratios in the Summary, the discussion 

of uncertainty about long-run actuarial measures 

in Chapter IV presents only high- and low-cost scenarios. That discussion could just as easily address 

95 percent confidence intervals from the stochastic 

analysis, and in a comprehensive chapter on uncertainty, it would be useful to include both (or even 

some integrated scenarios). In effect, a fundamental shift in the presentation of uncertainty can and 

should be the basis for recasting the apparent superiority of the high- and low-cost scenario approach 

that still dominates the Trustees Report.

8 See Footnote 6.

1.2 Actuarial Metrics

Method Recommendation M-1. The Technical Panel 

recommends providing micro-level (individual)  financial measures of the Social Security system in 

conjunction with macro-level (program-wide)  financial measures of the system.

Method Recommendation M-2. The Technical Panel 

recommends adding a subsection to Chapter  IV, 

Section B of the Trustees Report that provides more 

discussion and analysis of sustainable solvency.

Method Recommendation M-3. If the Trustees accept 

Recommendation M-2, then the Technical Panel recommends eliminating the Infinite Horizon metric.

Actuarial Metric Review

The annual Trustees Report presents several actuarial metrics, both short- and long-range, that 

show the relationship of workers to beneficiaries; current and projected funded status; and the 

change in funded status from the previous year and 

historically. Overall, the metrics are comprehensive 

and presented clearly. The Trustees Report provides metrics that satisfy the Actuarial Standard of 

Practice for Social Insurance (ASOP 32) as well as 

the Federal Accounting Standards Advisory Board 

Exposure Draft on reporting the financial status of 

the Social Security system in the context of the unified budget.

The following measures used in the Trustees Report are summarized and discussed below:

■ Worker-to-Beneficiary Ratio

■ Short-Range Measure (Trust Fund ratios)

■ Long-Range Measures

Worker-to-Beneficiary Ratio

A pay-as-you-go (pay-go) system will work if the 

following equation is true for any period of time: 

where B = average annual benefit (in dollars) and 

C = average annual contribution (in dollars). We rewrite the equation as follows:

B x Number of beneficiaries = C x Number of workers

B Number of workers

C Number of beneficiaries =
24 2011 Technical Panel on Assumptions and Methods

If the Worker-to-Beneficiary Ratio is decreasing 

such that the number of beneficiaries is increasing 

faster than the number of workers, then a pay-go 

system will work only if the benefits (B) decrease or 

the contributions (C)  increase by a corresponding 

amount. Figure 7 presents the Worker-to-Beneficiary Ratios as depicted in the 2011 Trustees Report.

The Worker-to-Beneficiary Ratio remained relatively stable  at approximately 3.3 from 1975 to 

2000. Since 2000, the ratio has dropped to 2.9. 

Under the intermediate assumptions, the ratio is 

projected to decrease significantly until 2035 and 

then become stable again at approximately 2.0. For 

a given level of contributions, a dependency ratio of 

2.0 will support only 60 percent (2/3.3) of the benefits that a dependency ratio of 3.3 will support under a pay-go system. Social Security is not a strictly 

pay-go system; therefore, the decrease in benefits 

required to maintain solvency is not 60 percent as 

suggested by the example; the example indicates, 

however, the significance of the dependency ratio 

for a plan that is largely pay-go.

Short-Range Measures (Trust Fund Ratios)

The Actuarial Standards Board (ASB)  establishes professional standards for actuarial work. In 

ASOP 32, the ASB sets forth standards for actuaries practicing in the field of social insurance. For 

social insurance programs whose funding level is 

set through legislation, the standard requires the 

actuary to:

1. Establish a test for financial adequacy, based 

on criteria such as:

p Required Trust Fund levels under bestestimate assumptions

p Positive Trust Fund levels under pessimistic assumptions

p Sufficiently low probability of ruin or an 

acceptable  range of possible outcomes under a stochastic model

2. Apply the test to both short- and long-range 

periods

3. Note significant differences between income 

and cost toward the end of the valuation period

Figure 7. Covered Worker to OASDI Beneficiary Ratio: Historical (1975–2010) and Trustees’ Projection 

(2011–2086)

Source: 2011 Trustees Report, Table IV.B2.

Intermediate 

Low-Cost 

HIgh-Cost 

Historical Projected 

0.0 

0.5 

1.0 

1.5 

2.0 

2.5 

3.0 

3.5 

4.0 

1975 1985 1995 2005 2015 2025 2035 2045 2055 2065 2075 2085 

Ratio of workers to OASDI beneficiaries
2011 Technical Panel on Assumptions and Methods 25

The Trustees Report includes a short-range test 

for financial adequacy based on Trust Fund ratios, 

defined as the assets at the beginning of a year 

(BOY) expressed as a percent of cost during a year. 

A ratio of 100 percent (i.e., enough assets at BOY 

to cover the coming year’s “scheduled” benefit payments) is considered a reasonable “contingency reserve.” The short-range test, applied to OASI and DI 

separately, is satisfied as follows:

■ If the ratio is greater than 100 percent at the 

beginning of the projection period, then it must 

remain above 100 percent for the 10-year projection period; or

■ If the ratio is less than 100  percent at some 

point during the projection period, then it must 

reach 100 percent within five years (without first 

reaching zero) and stay above 100 percent for the 

remainder of the projection period.

As shown in Figure  8, the OASI Trust Fund 

passes the short-range test for financial adequacy 

but the DI Trust Fund fails. This important metric 

sends a strong signal to the readers of the Trustees 

Report that disability benefits are not financially 

secure under the current program of benefits and 

contributions and thus warrant attention.

Long-Range Measures

The Trustees use several metrics for presenting 

the long-range financial status of the Social Security system, including:

A. Trust Fund Ratios

B. Projected Annual Balances

C. Actuarial Balance

D. Open Group Unfunded Obligation

E. Infinite Horizon Unfunded Obligation

F. Closed Group Unfunded Obligation

A. Trust Fund Ratios

For the long range, Trust Fund ratios are indicators of the adequacy of financial resources at a 

point in the future. Of course, a Trust Fund ratio 

of zero indicates the exhaustion of the Trust Fund 

and implies insufficient assets to pay all scheduled 

benefits. The year of exhaustion, the stability during the period, and the trend at the end of the periFigure 8. Projected OASI and DI Trust Fund Ratios: 2011-2020

Source: Trustees Report, Table IV.B3, 2011.

OASI 

DI 

0% 

50% 

100% 

150% 

200% 

250% 

300% 

350% 

400% 

450% 

500% 

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 

Trust Fund assets beginning year/

expenditures during year

OASI assets at

January 1, 2011

are 401% of

expenditures

during 2011
26 2011 Technical Panel on Assumptions and Methods

od are important for assessing the fund’s actuarial 

status. For example:

■ Near-term exhaustion indicates the need 

for immediate action.

■ If the ratio is positive during the period 

and level or increasing at the end of the period, then projected adequacy is likely to continue 

into future periods.

B. Projected Annual Balances

Projected Annual Balances are developed by 

OACT and used to assess the Trust Fund’s financial 

status. Projected Annual Balances are defined as 

the difference between the Annual Income Rate and 

Annual Cost Rate. The Annual Income Rate is the 

income from payroll taxes plus the revenue from 

the taxation of benefits, with the result expressed 

as a percentage of OASDI taxable payroll or Gross 

Domestic Product (GDP)  for the year. The Annual 

Cost Rate is the sum of the scheduled benefit payments for the year, administrative expenses for the 

year, net transfers to Railroad Retirement for the 

year, and payment of vocational rehabilitation services for disabled participants for the year, with the 

result expressed as a percentage of OASDI taxable 

payroll or GDP for the year.

The Annual Balance is then defined as the difference between the Annual Income Rate and Annual 

Cost Rate or the net cash flow rate, without taking 

into account interest earnings on the Trust Fund. 

As with the Trust Fund ratios, the level and trend 

of the Annual Balances at the end of the long-range 

period demand special attention.

C. Actuarial Balance

Related to the Projected Annual Balances, the 

Actuarial Balance presents a present-value analysis 

that compares the Summarized Income Rate to the 

Summarized Cost Rate as defined below.

The Summarized Income Rate is the ratio of the 

sum of the present value of scheduled tax income 

for each year of the period to the sum of the present 

value of taxable payroll for each year of the period. 

The Summarized Income Rate is adjusted to include 

the present value of the Trust Fund’s assets at the 

beginning of the period. 

The Summarized Cost Rate is the ratio of the sum 

of the present value of cost for each year of the period 

to the sum of the present value of taxable payroll for 

each year of the period. The Summarized Cost Rate is 

adjusted to include a targeted ending Trust Fund balance equal to one year of benefit payments in the year 

following the end of the forecast period.

The Actuarial Balance, defined as the difference 

between the Summarized Income Rate and Summarized Cost Rate, is developed for 25-, 50-, and 

75-year periods. The varying periods allow for an 

assessment of the financial adequacy of the Trust 

Fund over different-length periods. One shortcoming of the Actuarial Balance is that it shows funding 

status only at one time point and does not provide 

information about what happens in the interim. 

The Test for Close Actuarial Balance, described below, addresses this shortcoming by looking at 66 

valuation periods.

Test for Close Actuarial Balance. Consistent with 

ASOP 32, the Trustees Report presents a longrange test (Test for Close Actuarial Balance)  for 

financial adequacy as described below. The failure 

of the test indicates that, over the long term, the 

current-law level of financing is not adequate to pay 

for currently scheduled benefits.

The Actuarial Balances over 66 valuation periods 

are useful in developing a test of “close” actuarial 

balance. The 66 separate valuation periods are:

■ The first 10-year period

■ The first 11-year period

■ The first 12-year period

■ Successive periods each longer by one year 

through the full 75-year projection period

The test is met if (1) the Actuarial Balance is not 

less than zero in any valuation period, or (2)  if 

negative, then by no more than a specified  percent of Summarized Cost Rate for the same period. 

The specified percent is zero before 10 years, with 

a maximum of 5 percent at the end of the 75-year 

period. The notion is that the longer the projection 

period, the less certain are the results, with more 

deviation allowed. The 2011 Trustees Report provides the results of the Long-Range Close Actuarial 

Balance test as shown in Figure 9.

D. Open Group Unfunded Obligation

The Open Group Unfunded Obligation, which 

includes all participants (i.e., past, current, and future) projected over a 75-year period, is defined as:

■ The present value of future costs, minus

■ The present value of future taxes, minus

■ The Trust Fund at the beginning of the period.
2011 Technical Panel on Assumptions and Methods 27

Figure 9. Long-Range Test for Close Actuarial Balance: Comparison of Long-Range Actuarial Balances with 

the Minimum Allowable for Close Actuarial Balance, Based on Intermediate Assumptions

Source: Trustees Report, Figure IV.B4, 2011.

-20% 

-15% 

-10% 

-5% 

0% 

5% 

10% 

15% 

20% 

10 15 20 25 30 35 40 45 50 55 60 65 70 75 

Actuarial Balance

Minimum allowable

actuarial balance

During the 75-year period, 

the actuarial balance of 

-2.22 is about 14 percent of 

the summarized cost rate. 

Actuarial balance as a percent of

summarized cost rate

Valuation period (years from first year of projection, 2011)

The 2011 Open Group Unfunded Obligation is 

expressed in dollars (in trillions) and as a percentage of either taxable payroll or GDP as follows (under the intermediate assumptions):

Dollars in Trillions $6.50

Percent of Taxable Payroll 2.1

Percent of Gross Domestic Product 0.7

The difference between the 2011 Trustees Report 

75-year Actuarial Balance of -2.22 percent and the 

Open Group Unfunded Obligation expressed as 

a  percentage of taxable payroll of 2.1  percent (in 

addition to its opposite sign) is that the Actuarial 

Balance includes an additional obligation equal to 

the present value of the ending target Trust Fund.

The Open Group Unfunded Obligation shows another view of the adequacy of funds over a long period. While important, the uncertainty associated 

with a 75-year projection may be large. It can also 

hide some of the shorter-term financial issues if 

not used with short-term metrics.

E. Infinite Horizon Unfunded Obligation

The Infinite Horizon Unfunded Obligation results 

from extending the projection of the unfunded obligation for one thousand years into the future. The 

extension assumes that the current law remains in 

force and that demographic and economic assumptions remain unchanged into the future. Of course, 

even more than a 75-year projection, the uncertainty of such estimates is substantial.

The Trustees use the Infinite Horizon Unfunded 

Obligation to provide an estimate of the immediate increase in the payroll tax rate or immediate decrease in paid benefits that would eliminate the actuarial deficit. The 2011 Infinite Horizon Unfunded 

Obligation under the intermediate assumption is 

3.6 percent of payroll or 1.2 percent of GDP.

F. Closed Group Unfunded Obligation

The Open Group Unfunded Obligation described 

above may be disaggregated into the unfunded obligation for past, present, and future participants. 

The unfunded obligation for past and current par-
28 2011 Technical Panel on Assumptions and Methods

ticipants (limited to individuals who attain age 15 

or older in the valuation year) is then referred to as 

the Closed Group Unfunded Obligation.

Purpose of Metrics

The Trustees Report uses several long-range metrics. The purpose for which a Social Security metric 

is to be used determines the proper group of participants (e.g., current versus current and future 

participants)  for inclusion in a particular calculation of liabilities. The long-range metrics used by 

the Trustees test the adequacy of income during 

the 75-year period against benefits payable during 

the same period. In other words, groups of future 

workers expected to pay into the system any time 

during the period are included in the valuation, 

thereby making the Open Group Unfunded Obligation the relevant metric.

In accounting for the obligations of the Social 

Security system, the revenues generated by the 

group of current workers is intended to be matched 

against the expense incurred for the same group of 

current workers. For this reason, the Closed Group 

Unfunded Obligation is the relevant metric used by 

the Federal Accounting Standards Advisory Board 

for accounting purposes. The Technical Panel believes that Social Security is unique in the longterm nature of its obligations and thus requires the 

separate metrics in the Trustees Report. Accounting metrics should not blur the financial solvency 

perspective of the Trustees Report, which nonetheless provides the projected annual income and 

cost figures used by the General Accounting Office 

(GAO) to develop a unified budget.

Literature Review

We performed a literature review to determine 

what metrics other experts and organizations use 

to describe the financial condition of Social Security or other social insurance systems. We reviewed 

metrics used by:

■ The Congressional Budget Office in its LongTerm Projections for Social Security

■ The Canadian Office of the Chief Actuary in 

its 25th Actuarial Report on the Canada Pension Plan

(December 31, 2009)

Metrics Used by the Congressional Budget Office

The Congressional Budget Office (CBO)  in its 

publication Long-Term Projections for Social Security

relies on several of the same metrics used in the 

Trustees Report, including the following:

■ Tax revenues as a percentage of GDP

■ Outlays as a percentage of GDP

■ Summarized revenue  – present value of revenue divided by present value of GDP (including 

the Trust Fund balance)

■ Summarized outlay – present value of outlay 

divided by present value of GDP (including additional final-year outlay)

■ Trust Fund ratios

CBO Ratios. CBO presents “revenue” and “outlays” as a percentage of GDP, whereas the Trustees 

present “income” and “costs” both as a percentage 

of taxable payroll and a  percentage of GDP. The 

difference in metrics is consistent with the different focus of the two agencies. It is important for 

the Trustees to present the deficit as a percentage 

of the taxable payroll because it gives the order of 

magnitude of the tax rate increase that would be required to eliminate the deficit. The CBO focuses on 

the budget for all federal government programs and 

needs to present Social Security financial results as 

a percentage of GDP in order to compare and combine results with other budget items.

CBO Uncertainty. CBO presents the uncertainty 

related to its financial measures by using a stochastic analysis (500 stochastic trials). The Trustees, 

however, present uncertainty related to their financial measures in several ways, including stochastic 

analysis. The Trustees have chosen high- and lowcost scenarios as their most prominent method for 

presenting uncertainty. In the previous section of 

this report, the Technical Panel provides a detailed 

recommendation for presenting uncertainty.

CBO Individual Metrics. CBO provides the following individual metrics for 10-year birth cohorts, 

separately for men and women and separately for 

low, medium, and high earners:

■ Median first-year Social Security benefits in 

current-year dollars (net of income taxes) assuming age 65 claiming age

■ Median first-year replacement rates

■ Median present value of lifetime Social Security benefits (net of income taxes)

■ Present value of net lifetime benefits and 

present value of payroll taxes paid, by earnings 

quintile
2011 Technical Panel on Assumptions and Methods 29

Table  6 is taken from the individual measures 

provided by CBO in its 2010 projection report.

Table 6. Median Initial Age 65 Benefit for All 

Retirees

10-Year Birth Cohort Benefit

1940s $17,000 

1960s $18,000 

1980s $22,000 

2000s $29,000 

Source: Congressional Budget Office, 2010.

The Trustees also provide individual metrics in 

Appendix F of their report in a section titled “Estimates in Dollars.” Table  7 (excerpted from Appendix F of the 2011 Trustees Report) provides the 

annual scheduled benefit at full retirement age and 

at age 65 for scaled medium earners by year of attainment of age 65.

Table 7. Annual Age 65 Scheduled Benefit for 

Scaled Medium Earner

Year Attain Age 65 Benefit Percent of Earnings

2011 $17,000 41%

2030 $20,000 36%

2050 $25,000 36%

2070 $32,000 36%

Source: 2011 Trustees Report, Appendix F.

Metrics in the 25th Actuarial Report on the 

Canada Pension Plan (CPP)

The Canada Pension Plan uses several different actuarial metrics in evaluating their system finances:

■ Asset-to-expenditure ratios

■ Projected pay-as-you-go rates

■ Net cash flow

■ Contributory earnings (similar to Social Security taxable payroll)

■ Shortfall (defined as expenditures minus contributions) as a percentage of investment earnings

■ Investment earnings as a  percentage of revenue (contributions plus investment earnings)

The CPP report provides financial status metrics in tabular form as both nominal amounts and 

amounts adjusted to 2010 dollars. It presents annual amounts for 35  years and then in 5-year increments for an additional 40  years. The financial 

status metrics are developed for two alternative 

contribution assumptions (minimum rate and 

steady-state rate).

The 2011 Trustees Report provides dollar values in 

Appendix F, Table s VI.F8 and VI.F9. Nominal annual 

amounts are provided for 20 years and then in 5-year 

increments. The Trustees Report does not provide 

pay-as-you-go contribution amounts but otherwise 

provides metrics similar to those in the CPP report.

CPP Uncertainty. The CPP report presents uncertainty in terms of the following alternative scenarios:

■ Younger Population Scenario (higher fertility, 

more immigration, slower mortality improvement, higher unemployment, earlier retirement, 

lower real wage increases, lower inflation, higher 

real rates of return)

■ Older Population Scenario (lower fertility, less 

immigration, faster mortality improvement, lower unemployment, later retirement, higher real 

wage increases, higher inflation, lower real rates 

of return)

■ Investment Policy Alternatives

■ Financial Market Tail Events

■ Economic Slowdown

Financial results (assets-to-expenditure ratios)  for the two alternative population scenarios 

(younger, older) are presented in tabular form for 

representative  years. In addition, sensitivity tests 

on individual assumptions are based on stochastic 

modeling techniques for the individual assumptions listed below.

■ Fertility rate

■ Mortality/life expectancy at age 65

■ Net migration rate

■ Participation rate and unemployment rate9

■ Rate of increase in prices

■ Real-wage differential

■ Real rates of return

■ Disability incidence

Probability distributions quantified a range of 

possible outcomes for each selected assumption. 

The distributions were constructed by using timeseries modeling based on historical data. A minimum of 1,000 outcomes was generated for each year 

9 Deterministic approach rather than stochastic approach.
30 2011 Technical Panel on Assumptions and Methods

in the projection period. The metrics in the sensitivity analysis are pay-go rates for 2025, 2050, and 

2084, identifying the first year that benefits exceed 

contributions and specifying assets-to-expenditure 

ratios. All metrics are presented in tabular form.

CPP Summary Measures. The appendix to the 

CPP report presents closed group actuarial accrued 

liability and unfunded liability as balance sheet 

items and as one indicator of the plan’s financial 

health. Actuarial Balance was reported in the 23rd

report on the CPP (December  31, 2006)  but was 

eliminated in the 25th report. The CPP actuarial valuation places less emphasis on summary measures 

by relegating them to the appendix  and stressing 

the importance of the year-by-year numbers within 

the text. The summary measures, particularly Actuarial Balance, are more prominent in the 2011 

Trustees Report than in the CPP report. The 2007 

Technical Panel recommended placing less emphasis on summary measures. 

CPP Individual Metrics. The appendix  to the 

CPP report provides internal rates of return by 

birth cohort, average monthly pensions payable 

as of December  31, 2009, and projected average 

monthly pensions for representative years. The CPP 

report does not prominently incorporate individual 

metrics.

Recommendations

After completing the actuarial metrics review 

and literature review, the Panel recommends the 

following:

Method Recommendation M-1. The Technical Panel 

recommends providing micro-level (individual)  financial measures of the Social Security system in 

conjunction with macro-level (program-wide)  financial measures of the system.

The Technical Panel’s review of the metrics used 

for Social Security by other experts and organizations revealed that micro-level financial measures 

provide another useful way to evaluate the system 

and help the public relate financial status to the 

level of benefits. Examples of where the Trustees 

could incorporate individual metrics follow:

Figure 10. Projected OASDI Annual Cost Rates (Scheduled and Payable) and Income Rates (With and 

Without Trust Fund Interest) as Percentage of Taxable Wage Base

Source: 2011 Trustees Report.

2036 

0.00% 

5.00% 

10.00% 

15.00% 

20.00% 

25.00% 

2005 2015 2025 2035 2045 2055 2065 2075 2085 

Cost: scheduled

and payable benefits

Income including

interest

Income

excluding

interest

Expenditures: Payable benefits=

income after trust fund exhaustion

in 2036
2011 Technical Panel on Assumptions and Methods 31

■ Add a chart to the Highlights chapter showing 

replacement ratios, accompanied by an explanation that the financial metrics described in the 

chapter are based on providing the level of benefits shown in the chart.

■ Add a table of scheduled and payable benefits 

related to the discussion of what happens when 

either the OASI (in 2036) or DI (in 2018) Trust 

Fund assets are exhausted.

An important concern of the Trustees is that the 

Social Security program meet certain retirement income goals while maintaining financial solvency. If 

the program is solvent but over time does not provide a meaningful benefit, then one aspect of the 

solvency analysis is missing. The presentation of 

individual metrics is one way of relating benefit levels to the solvency analysis. Consider a hypothetical case in which both taxes and benefits increase 

such that the Annual Balance in each year does not 

change from current law. In such a case, the Annual 

Balance and Actuarial Balance would not change, 

but benefits certainly would, as could be easily 

shown by using micro-level measures.

Method Recommendation M-2. The Technical Panel 

recommends adding a new subsection to Chapter IV, 

Section B of the Trustees Report that provides more 

discussion and analysis of sustainable solvency.

Sustainable solvency is defined as positive Trust 

Fund ratios throughout the period, with stable or 

rising Trust Fund ratios at the end of the period. 

One option for achieving sustainable solvency 

would allow the Trust Fund to remain at a sufficiently high level such that interest on the Trust 

Fund plays a significant role in financing benefits. 

On a long-term basis, expenditures can exceed noninterest income only if the interest earnings on the 

Trust Fund are sufficient to make up that difference. Examples of information that might be useful 

in a sustainable solvency section follow:

■ Add a revised version of the Trustees Report’s 

Figures II.D2 and II.D5 showing the role of Trust 

Fund interest. Figures 10 and 11 provide examples of the revised figures.

■ Provide the tax rate increase and benefit percentage reduction amounts that would be reFigure 11. Projected Annual OASDI Cost (Scheduled and Payable) and Income (With and Without Trust Fund 

Interest) as Percentage of GDP

Source: 2011 Trustees Report.

0% 

1% 

2% 

3% 

4% 

5% 

6% 

7% 

8% 

2011 

2014 

2017 2020 2023 2026 2029 2032 2035 2038 2041 

2044 

2047 2050 2053 2056 2059 2062 2065 2068 2071 

2074 

2077 2080 2083 

Income rate,

including interest

Cost rate for 

scheduled 

benefits

Cost rate for

payable benefits

Income rate,

excluding interest

Percentage of projected GDP for year

Year
32 2011 Technical Panel on Assumptions and Methods

quired to achieve sustainable solvency. The “Conclusion” paragraph of the Highlights chapter  of 

the 2011 Trustees Report provides the amounts 

needed to achieve 75-year actuarial balance (i.e., 

a tax increase of 2.15 percentage points or a benefit percentage decrease of 13.8 percent would, if 

adopted in 2011, achieve 75-year actuarial balance). How would the amounts change if sustainable solvency is the goal rather than 75-year actuarial balance?

■ Provide individual metrics showing the impact on benefit replacement ratios of the required 

tax increase or the benefit decrease required to 

achieve sustainable solvency.

■ Provide graphs showing cost and income 

rates, including Trust Fund interest over the 75-

year period for the 2.15  percentage point and 

13.8 percent metrics. Figures 12 and 13 are illustrative.

■ Similarly provide cost and income rates, including Trust Fund interest over the 75-year 

period for sustainable solvency metrics that 

are equivalent to the 2.15 percentage point and 

13.8 percent metrics.

■ Provide graphs showing cost and income 

rates, including Trust Fund interest over the 75-

year period equivalent to the 2.15  percentage 

point and 13.8 percent metrics but assuming that 

any change in income or benefit levels is delayed 

for 10  years and then separately for 20  years, 

30 years, and so forth.

Sustainable solvency is mentioned in the Overview and defined and discussed in Chapter IV.B of 

the Trustees Report. The Technical Panel believes 

that the recommended additional section and metrics will aid the reader in understanding the financial status of Social Security.

Method Recommendation M-3. If the Trustees accept 

Recommendation M-2, then the Technical Panel recommends eliminating the Infinite Horizon metric.

The Infinite Horizon metric requires the projection of taxes, benefits, taxable payroll, and GDP 

hundreds of years into the future. At present, no information is provided on the uncertainty associated with these projections, despite this infinite proFigure 12. Projected Income and Cost Rates, Assuming a Tax Increase of 2.15

Percentage Points

Source: 2011 Trustees Report; Panel calculations.

0% 

5% 

10% 

15% 

20% 

25% 

2011 

2014 

2017 2020 2023 2026 2029 2032 2035 2038 2041 

2044 

2047 2050 2053 2056 2059 2062 2065 2068 2071 

2074 

2077 2080 2083 

Percentage of projected taxable earnings for year

Income rate,

including interest

Income rate

Cost rate
2011 Technical Panel on Assumptions and Methods 33

jection period. When the metric is expressed as a 

ratio to taxable payroll or GDP, some of the concern 

about uncertainty is reduced, as the factors that 

give rise to the uncertainty would often move taxes, benefits, taxable payroll, and GDP in the same 

direction. However, the Infinite Horizon metric is 

most often quoted in policy discussion without this 

scaling – for example, as $17.9 trillion, rather than 

3.6 percent of taxable payroll or 1.2 percent of GDP, 

even though all three are reported in the Trustees 

Report. Further, this projection of $17.9 trillion is 

often compared by analysts to other measures of 

government indebtedness, without recognition of 

the substantial uncertainty inherent in the projection. The Panel believes that the Infinite Horizon 

metric may shift focus away from more useful metrics for determining the finances of the system and 

that the information in the recommended new section on sustainable solvency would eliminate the 

need for an Infinite Horizon metric. 

1.3 Models and Methods

Method Recommendation M-4. The Technical Panel 

commends OACT for its progress in increasing the 

transparency of its methods and in communicating 

detailed information to policymakers and the research community through its web site. The Technical Panel recommends maintaining and expanding 

these efforts in the coming years.

Method Recommendation M-5. The Technical Panel commends the Social Security Administration 

(SSA) for investing in the development of matched 

data files that link survey information with administrative records on earnings and benefit receipt. 

The Technical Panel recommends making continued 

investments a high priority. 

Method Recommendation M-6. The Technical Panel 

recommends that SSA develop a strategic plan for 

expanding its dynamic microsimulation capacity 

and for integrating its segmented and microsimulation strategies. One objective of the strategic plan 

should be to increase coordination of dynamic miFigure 13. Projected Income and Cost Rates, Assuming a 13.8 Percent Benefit Decrease in Each Future Year 

versus Current Law

Source: 2011 Trustees Report; Panel calculations.

0% 

5% 

10% 

15% 

20% 

25% 

2011 

2014 2017 2020 2023 2026 2029 2032 2035 2038 2041 2044 2047 2050 2053 2056 2059 2062 2065 2068 2071 2074 2077 2080 2083 

Percentage of projected taxable earnings for year

Year

Income rate,

including interest

Income rate

Cost rate
34 2011 Technical Panel on Assumptions and Methods

crosimulation efforts within SSA in order to maximize existing resources. The Technical Panel recommends that the Social Security Advisory Board 

monitor progress on the development of these 

plans. The Board should consider convening or 

hosting a regular series of meetings of model developers within SSA and across various government 

agencies to review innovations, challenges, and 

prospects for collaboration. In deciding how to allocate scarce modeling resources, the Technical Panel 

recommends assigning a high priority to policies 

with potentially significant but uncertain effects on 

OASDI’s fiscal position.

Method Recommendation M-7. The Technical Panel 

recommends basing the intermediate projection 

of revenues from taxation of OASDI benefits more 

closely on the current income tax code rather than 

on historical shares of income subject to federal 

income taxation. The Technical Panel also recommends basing the projections of OASDI’s long-range 

actuarial status on two alternative sets of assumptions about future taxation that are analogous to 

“current law”/“extended baseline” and “current 

policy”/“alternative fiscal” scenarios, as is the practice of other government and private forecasting 

groups. At a minimum, the Technical Panel strongly 

recommends adding sensitivity analyses to the 

Trustees Report to demonstrate how projections of 

the long-range financial status of the OASDI program vary with alternative assumptions about laws 

governing personal income tax.

Documentation and Transparency

The Technical Panel applauds OACT’s significant 

progress in increasing the transparency of its model 

and methods. OACT’s posting of documentation, 

including the Long-Range OASDI Projection Methodology, on its web site is a tremendous advance that 

significantly aided the Technical Panel in its work 

and further permits researchers both internal and 

external to SSA to understand more fully the approach, assumptions, and methods in the Trustees 

Report.10 OACT analysts have been highly responsive 

to researcher requests for disaggregated information 

about certain Trustees assumptions and now regularly post single-year tables from the Trustees Report 

on OACT’s web site.11 The Technical Panel encourages 

continued dissemination efforts, especially through 

10 See OACT, 2011.

11 See http://www.ssa.gov/OACT/TR/2011/lrIndex.html.

OACT’s web site, and collaboration with interested 

researchers. Additional efforts to expand OACT’s web 

site to facilitate comparisons across Trustees Reports 

would be especially welcome.

While the documentation of the long-range Trustees Report methodology is comprehensive and lays 

out the basics, it could be presented even more 

clearly and thus require less effort on the reader’s 

part. For example, to enhance rapid comprehension 

of underlying models, the documentation could array coefficients in similarly specified models in a set 

of tables rather than rely on equations presented 

in the Trustees Report’s text. The description of 

the labor force component of the model would especially benefit from such organization. Similarly, 

while the documentation contains complete definitions of key variables, greater use of descriptive 

variable names rather than abbreviations and acronyms could substantially increase clarity in many 

cases. Succinct summary specification tables would 

be another valuable addition to the document. For 

example, a summary specification table could indicate the number of equations used, major stratifying variables, and the data sources from which variables are estimated for each important module in 

the segmented model.

Data Development and Dissemination

Reliable estimation of Social Security’s long-run 

finances requires extensive amounts of highly detailed and representative data. The Technical Panel 

strongly supports the investments made in recent years by various divisions of SSA to institute 

and maintain data linkages. For example, SSA’s 

coordination with the Census Bureau to develop 

matched survey-administrative data files for the 

Survey of Income and Program Participation and 

with the University of Michigan and National Institute on Aging to develop matched survey-administrative data files for the Health and Retirement 

Study is exemplary. The matched longitudinal survey records are extraordinarily valuable tools for 

developing effective distributional models and contributing to basic scientific knowledge that benefits 

developers/estimators who use both actuarial and 

more distributional strategies to understand Social 

Security’s financial position and the effects of proposed changes to the program.

Likewise, the Technical Panel applauds OACT’s 

posting of detailed data on the U.S. earnings dis-
2011 Technical Panel on Assumptions and Methods 35

tribution on its web site.12 The information could 

be even more useful if the current categorical 

presentation were supplemented with quantiles 

(for example,  percentiles, with extra detail in the 

top percentile), given that relatively large brackets 

at the top of the earnings distribution coupled with 

inflation make it difficult to compare these data 

across years. 

Similarly, OACT’s efforts to share data files developed by members of its staff for internal use have 

helped validate and improve models developed in 

other parts of SSA. A prime example is the OACT 

Microsim database file that is based on administrative sources, including the Current Work History 

Sample (CWHS)  and Master Earnings File (MEF). 

The Technical Panel encourages continuation of 

such efforts.

The Technical Panel and many others in the 

research community would welcome additional 

public-use files featuring information on earnings 

histories.13

Model Development

Models of Social Security (and, more broadly, 

of retirement income)  serve several purposes, 

and different types of models embody different 

strengths and weaknesses (e.g., Anderson 1997; 

Burtless 1996; Citro and Hanushek 1991,1997; Favreault 2000).

Earlier Technical Panels called for accelerated efforts to use dynamic microsimulation techniques to 

augment findings from the segmented model (for 

example, to supplement OACT work on the interrelationships between earnings and benefits). The 

same Technical Panels also detailed attractive features of such an approach (for example, straightforward integration of interactions, ability to simulate 

complex policies directly, and capacity for detailed 

distributional analyses). Further, the earlier Technical Panels identified certain modeling and policy 

areas where a microsimulation strategy would be 

particularly useful. For example, integrating differential mortality is extremely straightforward with 

the use of a dynamic microsimulation strategy. In 

the policy arena, proposals to implement earnings 

12 Wage data for 2009, for example, are available at http://www.

ssa.gov/cgi-bin/netcomp.cgi?year=2009.

13 One recent example of such a file is the Earnings Public-Use File, 

2006, which was released in 2011; it is available at http://www.ssa.

gov/policy/docs/microdata/epuf/index.html. An earlier example is 

the Benefits and Earnings Public-Use File, 2004, which was released 

in 2005; it is available at http://www.ssa.gov/policy/docs/microdata/earn/index.html.

sharing are a quintessential example of a type of 

policy that is best examined through dynamic microsimulation. Similarly, proposals tied closely to 

the number and timing of work years, such as minimum benefits and hardship exemptions of the type 

proposed by recent fiscal commissions, readily lend 

themselves to examination and comparison with 

the use of dynamic microsimulation models.

In recent years, SSA has increased its reliance on 

dynamic microsimulation to produce distributional 

estimates of reform proposals. For example, since 

the last Technical Panel report, the Report of the 

Commission on Fiscal Responsibility and Reform 

has cited distributional projections from SSA models in addition to OACT cost estimates (National 

Commission on Fiscal Responsibility and Reform 

2010, Figure 13).

While the Technical Panel applauds the above 

progress, some of these efforts could be more highly coordinated. The Office of Retirement and Disability Policy (ORDP) and, specifically, the Office of 

Research, Evaluation, and Statistics (ORES) within 

ORDP have continued to develop Modeling Income 

in the Near Term (MINT)  and recently completed 

development of MINT6, a version of the model 

that relies on data from the 2001 and 2004 panels 

of the Survey of Income and Program Participation 

matched to administrative earning, benefit receipt, 

and mortality records. (The Office of Retirement 

Policy uses MINT extensively in its policy analyses.)  At the same time, the Office of the Actuary 

has continued (with significant assistance from 

ORDP)  to develop Polisim, a large-scale dynamic 

model that uses extracts from the 1980 Public-Use 

Microdata Sample files from the U.S. Census. 

To date, development efforts for the two models appear to have been fairly independent of one 

another. One rationale for the separate tracks was 

that the models were a response to markedly different objectives. MINT’s horizon was originally the 

“near term”; the model addressed a narrow set of 

birth cohorts (originally the 1926 to 1964 birth cohorts) and distributional issues and placed significant emphasis on income sources other than earnings and Social Security (for example, pensions and 

financial assets). Polisim focused on the 75-year 

projection horizon used by OACT for the Trustees 
36 2011 Technical Panel on Assumptions and Methods

Report, the entire Social Security Area population,14

and distributional estimates coupled with a potential for cost estimation; thus, the model’s income 

projections narrowly addressed earnings and Social 

Security benefits. 

Now that well over a decade of intensive development has passed, the two models have become far 

more similar in scope, particularly as MINT’s projection horizon and cohort coverage have expanded 

with time and its processing structure has moved 

from what was once described as semidynamic to a 

strategy more consistent with an Orcutt-style, fully 

dynamic microsimulation model. As the models 

converge in content, it is appropriate to ask whether each is appropriately leveraging investments in 

the other.15 Given that dynamic microsimulation 

models are time-consuming and expensive to build 

and maintain, each model could almost certainly 

be improved more rapidly and less expensively if 

developers made a concerted effort, as feasible, to 

share knowledge, data extracts, and even parameters from microdynamic equations used to “age” 

the population. Cross-model validation within SSA 

is also likely to be a cost-effective strategy for increasing the models’ reliability.

Further, multidisciplinary cooperation can be 

extremely valuable for a complex endeavor such 

as building a large-scale dynamic microsimulation 

model. SSA staff members command wide-ranging 

background and expertise in fields such as actuarial 

science, computer science, demography, economics, 

sociology, and statistics as well as varying levels of 

familiarity with data availability and limitations and 

programmatic details. High levels of cooperation 

among staff with different areas of expertise could 

14 The Social Security Area population includes residents of the 50 

states and the District of Columbia, members of the U.S. armed 

forces, federal civilian employees overseas as well as their dependents, other citizens overseas, crews of merchant marine vessels, 

and civilian residents of Puerto Rico, the U.S. Virgin Islands, Guam, 

American Samoa, Palau, and the Northern Mariana Islands (OACT 

2011).

15 The question about the appropriateness of maintaining two 

separate models is important. In modeling such a large and complex system as the evolution of the U.S. population and its earnings/income distribution over a 75-year horizon, replication offers 

many important advantages. Development of several models is not 

necessarily wasteful or duplicative given that the “correct” answer 

is inherently unknowable. Comparing output from two models may 

be one of the fastest ways of unearthing problems in either or both. 

It is not uncommon for analysts in large-scale scientific and technical projects to use strategies of “double programming.” SSA may 

analogously deem parallel development an appropriate strategy 

given the importance of sound policy estimates, the various client 

bases served by SSA, and analysts’ investments in model-specific 

knowledge.

help SSA advance its goals of maintaining reliable 

microsimulation models for distributional analysis 

and developing the capacity to use the models to inform cost estimates as soon as possible.

The Technical Panel therefore recommends that 

the Social Security Advisory Board monitor progress in this area and perhaps consider convening 

regular developers’ meetings to explore opportunities to accelerate development and cross-validation 

of SSA distributional models. While convening Social Security employees would be a sufficient first 

step, such meetings could be enhanced by inviting 

modelers from other parts of the government (for 

example, the Congressional Budget Office’s LongTerm Modeling Group)  and private organizations 

that work intensively to develop dynamic microsimulation models.

The Technical Panel recognizes that efforts at 

cooperation are difficult when the relevant parties 

face a host of deliverable requirements. However, 

it makes sense to use resources for collaboration 

rather than for duplication and to avoid reliance 

on outdated parameters in either model. To remain 

valid and produce reliable results, the parameters 

in dynamic microsimulation models must be reestimated regularly, especially if the underlying 

processes (e.g., earnings or marriage)  are subject 

to change or science about a process is advancing. 

Updating equations to include new data and scientific knowledge is almost always preferable to using alignment to meet known targets. The marginal 

cost of re-estimating new equations developed for 

one model to ensure compatibility with another 

model is low relative to completely re-estimating a 

set of equations.

Analogously, the starting databases in dynamic 

microsimulation models, while requiring less frequent updating than equation parameters, should 

undergo periodic review. Collaboration with users 

familiar with candidate databases can help identify 

the most promising strategies for making investment decisions about databases. When making 

choices about starting databases for microsimulation models, modelers should pay special attention 

to the availability of matched earnings history data 

from a period close to the model baseline.

The Technical Panel thus recommends that OACT 

develop a strategic plan for keeping its dynamic 

microsimulation models updated and valid. Ideally, the plan would leverage cross–SSA resources 

where possible. The Retirement Research Consortium (RRC)  provides one instructive example of 
2011 Technical Panel on Assumptions and Methods 37

intra-agency coordination. The RRC has called for 

and funded research in areas that earlier Technical 

Panels identified as understudied and important 

for developing improved Social Security cost and 

distributional estimates. The same approach should 

be replicated and encouraged to advance SSA modeling.

Within OACT, the Technical Panel recommends 

further study and strategic planning to integrate 

the dynamic microsimulation model with the segmented model. Some Technical Panel members 

are concerned that dealing with the two models as 

completely separate entities slows progress toward 

more valid and effective microsimulation projections. An integration plan could reap benefits for 

the segmented model itself by requiring maximal 

automation and linking of existing procedures.

Effects of Policy Changes in a Model Based 

on Current Law: Challenges and Implications for 

Model Development

Social Security actuaries are charged with projecting the financial status of the program under 

current law. For several reasons, the task is enormously challenging. Among other considerations, 

it requires assumptions about future tax law, which 

is subject to frequent changes and contains many 

interacting policies and provisions. In several substantive areas, many independent analysts view 

current law as unrealistic or unsustainable over 

long periods. Analysts note that persistent, large 

annual and long-run deficits will eventually (perhaps sooner rather than later) require legislative action that could change workers’ incentives to work, 

save, and claim Social Security benefits and thus 

pose significant analytic challenges. Similarly, the 

gradual phase-in of legislative changes, including 

those associated with the Affordable Care Act, could 

translate into dramatic changes to work supports 

and incentives linked to various benefits (e.g., both 

OASI and DI). As discussed in section  2.4 on disability, SSA’s policy and capacity relative to the performance of Continuing Disability Reviews appear 

to be significantly associated with DI caseloads and 

changes to the medical eligibility criteria for DI.

Model developers should catalogue the outcomes 

and assumptions embedded in Social Security cost 

estimates that are most amenable to policy change. 

Uncertainty about policy direction should factor 

into developers’ plans for model investments and 

maintenance and should shape thinking about ongoing specification choices and the plausible bands 

for high- and low-cost assumptions. For example, 

the real wage differential, immigration levels and 

immigrant composition, and income from taxation 

of benefits will likely be highly susceptible to policy 

changes in the coming  years. The Technical Panel 

encourages developers to be forward-looking to ensure that they are positioned to adapt to possible 

policy changes that would materially affect Social 

Security financing.

Projecting Income Tax Revenues from Taxation of 

Benefits

Since Social Security benefits first became subject 

to income taxation in 1984, revenue from the taxation of benefits has grown steadily and is expected 

to become an increasingly important share of total 

OASDI revenue in the coming  years (Figure  14). 

The precise importance of the revenue is uncertain, 

however, and thus warrants additional discussion 

in the Trustees Report.

Throughout their annual report, the OASDI Trustees assume that current law generally remains in effect. They break significantly from their assumption 

in just a few places, including the establishment of 

an income tax baseline and, less important, the 

treatment of refugees under immigration law. The 

Trustees currently assume implicitly that Congress 

will continue to make ad hoc adjustments to the tax 

law to maintain a relatively constant tax burden. 

Therefore, projections of income from the taxation 

of Social Security benefits account for the fact that 

the modified Adjusted Gross Income (AGI) thresholds for taxing benefits are not indexed – even for 

inflation – and that an increasing share of beneficiaries will thus be liable for personal income tax on 

their benefits. But the projections do not address 

the “bracket creep” that is implicit elsewhere in current law, whereby most tax parameters are indexed 

to price inflation at the same time that income (and 

thus modified AGI) typically grows at a faster rate 

(because, for example, of the historical real wage 

differential). Current methods also implicitly assume that shares of income of different types will 

be fairly consistent for the beneficiary population 

in the coming decades; such an assumption is worthy of empirical analysis and justification.

Efforts to provide cost and distributional estimates for policy proposals premised on changes to 

current income tax law are exceedingly difficult. Yet, 

as such proposals increase in both frequency and 

prominence, OACT and the Trustees must invest in 

improving the components of the Trustees Report 
38 2011 Technical Panel on Assumptions and Methods

projections that address the taxation of benefits, 

thereby ensuring greater capability and reliability.

Recognizing that it is tremendously complex to 

implement a full-scale tax model and that any single assumption about the future of the tax code is 

likely to be controversial, the Technical Panel unreservedly recommends that the Trustees Report 

assign much higher prominence to the issue of 

Social Security integration with the tax code. Our 

preferred approach would present two projections 

in the top-line findings of the Trustees Report. The 

use of several baselines has become common practice among many forecasting groups as a response 

to how regularly Congress has shifted tax policy 

away from current law (under which many ongoing tax breaks are set to expire in the relative near 

term) and toward extending tax cuts and patching 

the Alternative Minimum Tax (AMT).

The Technical Panel believes that it is important 

to make clear to policymakers and the public that 

changes to federal income tax law have significant 

implications for OASDI’s long-run fiscal balance. 

For example, the Congressional Budget Office projects that the actuarial balance would be 0.42  percentage points of payroll lower (“worse”) under its 

“alternative fiscal scenario”  – which assumes that 

tax revenues remain closer to their historical average share of GDP  – compared to the “extended 

baseline” that assumes current tax rates remain 

unchanged.16 This is a difference of over a quarter 

of the long-range deficit under the 2011 extended 

baseline (Congressional Budget Office 2011). The 

current Trustees Report gives readers no information about the sensitivity of projections to the tax 

policies currently under debate. At a minimum, the 

report should present two plausible tax baselines in 

the spirit of the Congressional Budget Office’s tax 

projections. Similarly, the Office of Management 

and Budget presents two alternative revenue options in its discussion of the long-term budget in 

its Analytical Perspectives (2011).17

16 The alternative fiscal scenario “incorporates several changes to 

current law that are widely expected to occur or that would modify 

some provisions of law that might be difficult to sustain for a long 

period” (CBO 2011).

17 Under the base option, tax receipts reach 21.2 percent of GDP 

by 2085. The alternative scenario allows revenues to increase by an 

additional 2 percentage points of GDP.

Figure 14. Share of Non-Interest Income from Taxation of OASDI BenefitsSource: 2011 Trustees Report; 

Panel calculations.

Source: Office of the Chief Actuary, Social Security Administration, Single-Year Tables Consistent with 2011 Trustees Report, Components of Annual Income 

Rates [see http://www.ssa.gov/oact/TR/2011/lr4b10.html].

Historical Projected 

0% 

1% 

2% 

3% 

4% 

5% 

6% 

7% 

8% 

1984 1994 2004 2014 2024 2034 2044 2054 2064 2074 2084 

Percent of non-interest income
2011 Technical Panel on Assumptions and Methods 39

1.4 Implications of Health Care Reform

Assumption Recommendation A-1. The Technical Panel recommends increasing the range of uncertainty 

around the major assumptions, including those 

regarding labor force participation and the earnings ratio, that are likely to be affected by health 

care reform. The expanded range reflects the uncertainty inherent in how health care reform will unfold. Over time, the extent of uncertainty is likely 

to narrow, at which point the recommended ranges 

for the affected assumptions will lend themselves 

to reduction.

Research Recommendation R-1. The Technical Panel 

recommends research into the impacts of health 

care reform on relevant outcomes as reform provisions start to take effect. Such outcomes include labor force participation, disability receipt, the earnings ratio, the taxable share, and mortality. The 

research findings should help determine the need 

for changes to the relevant assumptions and the 

need for adjustments to the range of uncertainty.

The passage of the Patient Protection and Affordable Care Act (March  23, 2010)  and the Health 

Care and Education Reconciliation Act (March  30, 

2010)  represents the most dramatic change to 

the U.S. health care system since the enactment 

of Medicare in 1965. Although the goals of health 

care reform are primarily related to health care  – 

expanded health insurance coverage, increased 

affordability of health care, reduction in the longterm increases in the cost of health care – the new 

laws also have implications for the financial status 

of the OASDI program. Health care reform could 

affect system finances through several channels: 

(1)  by changing the level and/or composition of 

employment, (2) by changing the share of earnings 

in compensation, (3) by changing the taxable share 

of wages, (4) by changing the incentives to apply for 

DI, and (5) by changing health. The 2010 Trustees 

Report calculated that the two laws increased the 

long-range OASDI actuarial balance by 0.14  percent of taxable payroll (p. 71). As described in that 

report, the higher actuarial balance results from a 

reduction in the assumed average annual rate of decline of 0.1 percent in the ratio of earnings to compensation. The rationale for the change is that the 

excise tax on employer-sponsored health insurance 

that takes effect in 2018 will lead to slower growth 

in the total cost of employer-sponsored health insurance, which will in turn reduce the rate of decline in the ratio of earnings to compensation.18 As 

discussed below, however, health care reform could 

potentially affect OASDI system finances in several 

other ways.

Health Care Reform and Employment

A distinctive feature of the U.S. health care system is the fundamental role of employers in providing insurance to workers and their dependents. 

Figures 15 and 16 show the sources of health insurance coverage for adults age 18 to 64 and for 

children under age 18 from 1994 to 2009.19 For 

both children and adults, the primary source of insurance is employment-based: 60 percent of adults 

and 56  percent of children carried employmentbased coverage in 2009. It is important to note, 

however, that the prevalence of such coverage has 

been falling over the past decade, from a rate of 

69 percent for adults and 65 percent for children in 

1999. About one out of every 10 adults and one out 

of every three children are covered by Medicaid, a 

source of health insurance that has been increasing 

over time, especially for children. And approximately 10 percent of children and 22 percent of adults 

are uninsured. While the fraction of uninsured children has been decreasing (largely because of the 

expanded availability of public health insurance for 

children), the fraction of uninsured adults has been 

increasing. For those over age 65, the situation is 

different, as almost all elderly receive health insurance coverage through Medicare, potentially with 

supplemental coverage from a current or former 

employer, a privately purchased (Medigap)  policy, 

or Medicaid.

A large body of literature has documented the 

relationship between the U.S. system of health 

insurance provision and employment outcomes.20

For older individuals, health insurance affects the 

age of retirement. Individuals who would give up 

employer-sponsored health insurance coverage by 

retiring before age 65 are more likely than individuals with alternative sources of health care (employment-based retiree or COBRA)  coverage to delay 

retirement until they are eligible for Medicare. In 

addition, individuals who would likely lose or face 

more costly health insurance if they left their cur18 See the Trustees Report, 2010, p. 97.

19 The statistics in these figures are taken from Fronstin (2010).

20 See Gruber and Madrian (2004) for a review of the literature.
40 2011 Technical Panel on Assumptions and Methods

rent employer are less likely to change jobs. At the 

same time, individuals with health insurance coverage through a spouse are more likely to work in 

part-time jobs without health insurance, whereas 

individuals without potential coverage as a dependent are more likely to work in full-time jobs that 

offer health insurance. As the costs of health insurance increase, employers either shift demand 

from full-time workers with health insurance to 

part-time workers without health insurance or hire 

fewer workers to work longer hours.

Several features of health care reform could affect employment outcomes relevant to OASDI system finances. First, health care reform requires the 

states to establish health insurance exchanges that 

facilitate health insurance purchases in the individual market and may facilitate small businesses’ 

provision of health insurance. Second, health care 

reform offers premium subsidies to low- and middle-income individuals and families to help them 

purchase health insurance in the individual market 

if they are not covered through their own or a family member’s employment. As shown in Table 8, the 

premium subsidies may be large, and they decline 

with income. The phase-out of premium credits 

with income is effectively an increase in the tax on 

income for individuals and families below 400 percent of the federal poverty line (FPL). Third, health 

care reform involves a “pay or play” mandate for all 

but the smallest employers, requiring them to offer health insurance to their full-time employees or 

pay a fine.21 Fourth, health care reform, if successful in limiting the growth of health care costs and 

increasing the competitiveness of health insurance 

markets, could lower the decades-old upward trend 

in the cost of employer-provided health insurance.

21 Employers with 50 or more full-time employees that do not 

offer coverage and have at least one full-time employee receiving 

a premium credit will face a fine of $2,000 per full-time employee 

(less the first 30 employees). Employers with 50 or more fulltime employees that offer coverage but have at least one full-time 

employee receiving a premium credit will pay the lesser of $3,000 

for each employee receiving a premium credit or $2,000 for each 

full-time employee (less the first 30 employees) (Kaiser Family 

Foundation 2011).

Figure 15. Sources of Health Insurance Coverage for Adults, Age 18–64: 1994–2009

Source: Fronstin, 2010.

0% 

10% 

20% 

30% 

40% 

50% 

60% 

70% 

80% 

90% 

100% 

1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 

Employment-based coverage Uninsured 

Medicaid Other insurance 

Percent of adults age 18-64

Year
2011 Technical Panel on Assumptions and Methods 41

Figure 16. Sources of Health Insurance Coverage for Children under Age 18: 1994–2009

Source: Fronstin, 2010.

0% 

10% 

20% 

30% 

40% 

50% 

60% 

70% 

80% 

90% 

100% 

1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 

Employment-based coverage Uninsured 

Medicaid Other insurance 

Percent of children under age 18

Year

Table 8. Premium Credits for the Purchase of Health 

Insurance on the Exchanges

Income (as a percentage of 

the federal poverty line):

Premium Contributions 

Limited to:

Up to 133% 2% of income

133–150% 3–4% of income

150–200% 4–6.3% of income

200–250% 6.3–8.05% of income

250–300% 8.05–9.5% of income

300–400% of FPL 9.5% of income

Source: Kaiser Family Foundation, 2011.

On the supply side, health care reform is likely 

to reduce the total amount of labor input. The increased availability of non-employment–based 

health insurance coverage through the health insurance exchanges, coupled with premium subsidies to 

low- and middle-income families, will encourage 

some individuals who would have otherwise continued to work until their age-65 Medicare eligibility date to make an early exit from the labor force. 

For the same reason, secondary earners who were 

working primarily to provide health insurance coverage for their families may either leave the labor 

force entirely or cut back on hours worked, choosing part-time work in jobs without health insurance over full-time work in jobs with insurance. The 

unemployed, some of whom feel pressured to find 

a job in order to secure health insurance for themselves and/or their families, may take more time to 

search for a new job. And younger individuals may 

delay the transition from school to employment. 

For individuals and families who receive premium 

subsidies to purchase insurance on the exchanges, 

the phase-out of the subsidies with income will further depress labor supply. 

On the demand side, two countervailing effects 

are at work. The “pay or play” mandate requiring 

employers to offer health insurance to qualifying 

employees (or else pay a penalty)  will increase labor costs (largely among those not currently offering health insurance)  unless employers can pass 

the costs on to workers in the form of lower wages. 

Even though research suggests that employers may 
42 2011 Technical Panel on Assumptions and Methods

be able to pass much of the cost on to workers,22

employers of lower-wage workers may be less likely 

to do so. Lower-wage workers may be less willing 

than higher-wage workers to accept lower wages 

in exchange for health insurance coverage; further, their wages may already be at or near minimum wage. Levy and Baicker (2008) estimate that 

“0.2 percent of all full-time workers and 1.4 percent 

of uninsured full-time workers would lose their jobs 

because of a health insurance mandate.” Such job 

losses would be concentrated among high school 

dropouts, women, and minorities. The “pay or play” 

mandate may also change the composition of labor 

demand as the mandate applies only to full-time 

workers. An alternative to reducing employment 

in the face of the mandate would be to substitute 

part-time for full-time workers.23 Cutler and Sood 

(2010), however, point out that, to the extent that 

health care reform succeeds in slowing the growth 

of health care costs, it could lead to increased labor demand. They estimate that reductions in the 

growth of employer health insurance premiums attributable to health reform would create 250,000 to 

400,000 jobs in the next decade. 

The net effect on employment is difficult to predict. Colla, Dow, and Dube (2011) evaluate a “pay 

or play” health insurance mandate enacted by San 

Francisco in 2006. They conclude that the mandate 

had at most a small negative impact on total employment and earnings, although it did increase 

consumer prices. The Congressional Budget Office 

(2010), in its assessment of the impact of health 

care reform on labor markets, concludes that “the 

legislation, on net, will reduce the amount of labor 

used in the economy by a small amount – roughly 

half a percent – primarily by reducing the amount 

of labor that workers choose to supply” (p. 47). The 

assessment seems plausible in light of the current 

evidence. It is important to note that such a reduction in labor input is relative to what it would 

have been in the absence of health care reform; section 3.1 discusses recent trends in and the Technical Panel’s recommendations on labor supply.

22 See Madrian (2007) for a review of the literature on the extent 

to which employers can pass on the costs of health insurance to 

workers in the form of lower wages.

23 Thurston (1997) and Buchmueller, DiNardo, and Valletta 

(2009) document such an effect in Hawaii, which adopted a health 

insurance mandate in 1975.

Health Care Reform and the Earnings Ratio

If health care reform changes the extent or cost 

of employer-provided health insurance, it will have 

implications for the earnings ratio  – the share of 

compensation represented by earnings rather than 

by non-wage compensation. The share of compensation devoted to employer health insurance is a function of the fraction of employees covered by employer health insurance, the generosity of the insurance 

offered by the employer, and differences in the rates 

of health insurance cost and wage growth.

Health care reform could affect the fraction of individuals covered by employer-provided health insurance by directly changing employer incentives to 

offer health insurance and indirectly changing how 

firms structure the composition of their workforce 

between employees who are eligible and ineligible 

for health insurance. How health care reform will 

change an employer’s offer of health insurance is 

still ambiguous. The law contains provisions that 

encourage an employer’s provision of health insurance, including the “pay or play” mandate for firms 

with 50 or more employees and tax credits for small 

businesses that offer health insurance. In addition, 

the requirement for all individuals to carry health 

insurance may increase the demand for employers 

to offer health insurance. The exchanges may also 

spur the offer of insurance among small businesses. 

In Massachusetts, the fraction of workers covered 

by employer-sponsored health insurance increased 

from 70 to 76  percent from 2005 to 2009 as the 

state implemented its own health care reform, 

which subsequently provided a model for the federal 

law (Gruber 2011). An increase in an employer’s offer of health insurance would decrease the earnings 

ratio by shifting compensation from taxable wages 

to non-taxable expenditures on health insurance.

On the other hand, well-functioning health insurance exchanges that offer individuals a reasonable alternative to employer-provided coverage may motivate some employers to drop their 

health insurance. Singhal, Stueland, and Ungerman 

(2011)  argue that 30  percent of employers would 

benefit by eliminating coverage even if they fully 

compensated employees through higher salaries 

and paid the penalties levied on firms that do not 

offer insurance. Some employers may also find it 

attractive to change the composition of their workforce, substituting part-time employees not under 

the employer “pay or play” mandate for full-time 

workers. Employees, too, may be less interested in 

employer-provided coverage once the exchanges 
2011 Technical Panel on Assumptions and Methods 43

are operational and may be more willing to accept 

either full- or part-time jobs without health insurance. These outcomes would reduce employer expenditures on health insurance and increase the 

earnings ratio.

The Congressional Budget Office (2010) projects 

that health care reform will reduce by 2.5 percent 

the number individuals with employer-provided 

health insurance, although other analysts such as 

Singhal, Stueland, and Ungerman (2011)  believe 

that the decline in employer-sponsored coverage 

could be much larger. And, as the Massachusetts 

experience suggests, it is possible that employer 

coverage could increase, even though none of the 

experts consulted for this report thought that such 

a scenario was highly likely.

Finally, health care reform includes incentives to 

reduce the growth rate of employer expenditures 

on health insurance. Employer-sponsored health 

plans will be subject to an excise tax of 40 percent 

on expenditures in excess of $10,200 for individual 

coverage and $27,500 for family coverage. As noted 

in section 3.2, the threshold for premiums subject 

to the tax grows with the overall rate of inflation, 

which is expected to lag behind the growth per capita in health care costs. As a result, the fraction of 

health plans subject to the excise tax will increase, 

encouraging firms to reduce the generosity of their 

health benefits (or even eliminate coverage)  and 

shifting compensation from health insurance to 

wages. Such a reduction in the growth rate of employer expenditures on health insurance would 

reinforce any increase in the earnings to compensation ratio resulting from a reduction in employersponsored health insurance.

Overall, there are plausible scenarios in which 

health care reform could either increase or decrease 

with the earnings ratio, thus arguing for expanded 

uncertainty around the earnings ratio in the long 

run. Such uncertainty is reflected in our recommendations for the high- and low-cost values for the 

earnings ratio, which increase the range relative to 

current assumptions.

Health Care Reform and the Taxable Share of 

Wages

Health care reform may also affect the taxable 

share of wages. The general decline in the taxable 

share of wages (Figure 59) may be partly attributable to the increasing share of compensation devoted to employer health insurance (Figure  53); increases in employer health insurance expenditures 

have a disproportionate effect on the compensation 

of workers below the taxable maximum relative to 

workers above the taxable maximum. Health care 

reform could reduce the rate of expenditure growth 

for employer-provided health insurance for the reasons discussed above in the context of the earnings 

ratio and, more generally, in response to provisions 

that exert downward pressure on health care cost 

growth. With employer health insurance a fixed 

cost, a reduction in the expenditure growth of employer health insurance could increase the taxable 

share of wages relative to outcomes in the absence 

of health care reform.

Health care reform also includes financing provisions that increase the tax rates on both earned and 

unearned income among higher-income taxpayers, 

and these tax changes could affect the taxable share 

of wages. Specifically, the law increases the Medicare payroll tax by 0.9 percent on earnings above 

$200,000 and imposes a new tax of 3.8 percent on 

unearned income above $200,000.24 These changes 

reduce the work incentive for higher-income tax 

filers, potentially increasing the taxable share of 

wages. On the other hand, the larger increase in 

the tax on unearned income (3.8 percent) relative 

to the change in the tax rate on earned income 

(0.9 percent) could encourage some higher-income 

individuals to restructure their compensation, potentially changing the taxable share of wages. For 

example, if high-income individuals take income 

as earnings rather than as capital income, they decrease their taxable share of wages. Given the small 

number of individuals affected by these tax changes and the relatively small changes in the tax rates, 

the Technical Panel believes that these effects will 

likely be minimal.

Health Care Reform and Disability Insurance 

Incidence

Two features of health care reform could affect 

the incidence of disability insurance receipt. First, 

reductions in employment could reduce the fraction 

of the population insured for DI benefits, although 

we believe that any such effect is likely to be small. 

Second, because DI recipients have a two-year waiting period before becoming eligible for Medicare, 

one of the costs of applying for DI is potentially 

limited access to health insurance for a period of 

time. The creation of health insurance exchanges 

as a part of health care reform could substantially 

24 The $200,000 threshold is for individual tax filers; for marriedfiling-jointly tax filers, the threshold is $250,000.
44 2011 Technical Panel on Assumptions and Methods

reduce the cost of applying for DI, which could, in 

turn, encourage more individuals to apply for DI, 

an outcome that would adversely affect the DI program’s finances. Such an outcome seems possible, 

although it is hard to gauge its magnitude; this is 

another area where health care reform increases 

uncertainty about long-run outcomes.

Health Care Reform and Health

One aim of health care reform is that it will lead 

to improved health. A recent review of the literature on the impact of health insurance on health 

concludes that “policies to expand insurance can 

also promote health” but that “it is difficult to extrapolate from these studies to the potential health 

benefits of completely different policies” (Levy and 

Meltzer 2004). If health care reform does lead to 

improved health, it could affect OASDI finances 

in several ways. One manifestation of improved 

health would be a reduction in mortality, which 

would adversely affect OASI system finances. In addition, the DI system could experience countervailing effects of health improvements. Better health 

would likely reduce DI incidence and thus improve 

system finances, but it could be offset by reductions 

in mortality among DI beneficiaries, leading to longer DI spells for beneficiaries. Given that many 

older individuals cite declining health as a reason 

for retirement, improvements in health could increase the labor force participation of older workers, buoying system finances and delaying the age 

of benefit claiming.

The Technical Panel queried several health experts for their opinions on the impact of health care 

reform on mortality, disability, and the labor force 

participation of older workers. While all acknowledged the potential for the above effects, they 

agreed that any attempt to quantify the effects at 

this stage would be speculative at best. The Technical Panel concurs with the assessment of Holtzblatt 

and Page (2009)  in a Congressional Budget Office 

report on the impact of health reform on the labor 

market:

“The overall impact on labor markets...

is difficult to predict. Although economic 

theory and experience provide some guidance as to the effect of specific provisions, 

large-scale changes to the health insurance system could have more extensive 

repercussions than have previously been 

observed and also may involve numerous 

factors that would interact – affecting labor markets in significant but potentially 

offsetting ways” (p. 1).

Conclusion

The Technical Panel sees significant uncertainty 

about how health care reform will affect many of 

the outcomes discussed in this chapter  : employment, the earnings ratio, the taxable share of 

wages, incentives to apply for DI, and health. This 

uncertainty justifies an increase in the ranges for 

the high- and low-cost scenarios for many of the assumptions discussed in this report. The Technical 

Panel also recommends research into the impact of 

health care reform on these outcomes as reforms 

unfold. Such research would then inform whether 

changes should be made to the relevant assumptions and whether the range of uncertainty should 

be adjusted.
2011 Technical Panel on Assumptions and Methods 45

Chapter 2: Demographic Assumptions and Methods

2.1 Fertility

Assumption Recommendation A-2. The Technical 

Panel recommends retaining the intermediate total fertility rate assumption of 2.0 from the 2011 

Trustees Report. The Technical Panel also recommends low- and high-cost total fertility rates of 2.2 

and 1.6, respectively. We agree with previous Technical Panels that asymmetry in the range between 

the intermediate- and low- and high-cost values is 

appropriate, although our current estimate of such 

asymmetry is modest.

Overview

The fertility assumption is expressed in terms 

of the total fertility rate (TFR), which is defined 

as the average number of births per woman over 

her life time if she experienced the age-specific 

rates of a given year and survived to the end of her 

childbearing years. As a period-based measure, the 

TFR reflects changes in the ages at which women 

bear children (the timing or tempo of childbearing) and/or in the number of births to women (the 

quantity, or quantum). Evidence reviewed below 

shows that increases in ages at childbearing have 

depressed the TFR in recent decades, but the effect 

wanes with projections on a 75-year horizon. The 

quantum component of U.S. fertility has remained 

at near-replacement level (TFR of approximately 

2.1)  for the last two decades, and the most likely 

scenario is continued childbearing at slightly below 

that rate. Specifically, we expect that the impact of 

the Hispanic population’s higher fertility will wane 

in the next two decades, providing some downward 

pressure on fertility. Overall, the underlying components of U.S. fertility are stable and sufficient to 

project near-replacement–level fertility over the 

75-year horizon.

Historical and International Perspective

Figure 17 shows, for a period of more than two 

centuries, estimated trends in U.S. fertility. The 

blue line describes whites as presented in the last 

Technical Panel Report, and the red line, which 

is virtually indistinguishable from the blue line, 

represents all races. The broad contours of the decline are well known  – a decline associated with 

urbanization, economic/social development, and 

improved health and longevity followed by the 

post–World War II Baby Boom (1944–1959)  and 

bust (1960–1980), which were associated with rapid changes in economic growth, impacts on family 

formation, and perceived well-being and security 

(Cherlin 1992).

To put U.S. trends in perspective, we examine 

country-level data covering the last half-century. 

Following Morgan and Rackin (2010a), Figure 18

shows 1960–2005 on the x-axis and TFR changes 

for 103 counties (with requisite data)  on the yaxis. These countries represent 83  percent of the 

world’s 2000 population (Morgan and Rankin 

2010a:Appendix). The bold colored lines show, 

weighted by 2000 population, TFR averages for developing and developed countries while the lighter 

lines show the estimated trend for each of the 103 

countries.

Figure 18 has two impressive features. The first 

is pervasive and secular decline captured by the 

two bold lines that represent aggregate trends for 

developing and developed countries. Over the period, the developing country average declined from 

6.06 births per woman to 2.54, and developed country levels declined from approximately 2.91 births 

to 1.70. The second feature is the TFR range  – in 

1970, from over 8 births to 1.65. A surprisingly 

wide range remains in 2005 (from 7.03 to 0.97).

When mortality is low, as it is now in developed 

countries, a TFR of 2.1 is replacement-level fertil-
46 2011 Technical Panel on Assumptions and Methods

ity. In the long run, given a low- mortality context, 

replacement-level fertility must be achieved in order 

to realize a stable population size. This level of fertility is shown by the bold, horizontal line in Figure 18. In 1960, few countries were below this level; 

by 2005, 41 counties had reached fertility below 2.1.

The TFR changes noted above reflect tempo and 

quantum components. Over the long term, the 

quantum component dominates as reflected in 

smaller families. Figure 19 shows a U.S. time series 

(1917–2007) of the percentage of births by parity. 

Increasingly, births are first or second births. While 

not shown here, this pattern of change holds for all 

countries for which data are available. Over 70 percent of 21st  Century births in the United States 

are first or second births. The rationale for these 

births – the desire to become a parent and to have 

a sibling for the first child – has proven to be a stable rationale for childbearing while the rationale for 

higher-parity births has weakened (Morgan 2001, 

2003).

Overlaid on the quantum changes are tempo 

changes. Figure 20 shows a U.S. time series (1917–

2007) of mean ages at childbearing by parity. Historically, later childbearing is associated with a 

lower quantum of fertility, although rising mean 

ages at childbearing lower the current TFR level. 

Declines in ages at childbearing have the opposite 

effects. We explore these dynamics below. At this 

point, it is important to note that the Baby Boom 

and bust were associated, respectively, with substantial declines followed by substantial increases 

in ages at childbearing.

In sum, the U.S. experience broadly fits international experience. Specifically, fertility has declined 

over time with socioeconomic development, and 

the decrease is driven by the decline in higher-parity births. Both the timing and pace of the decline in 

fertility exhibit substantial variability (Bongaarts 

and Watkins 1996; Morgan and Rackin 2010a) and, 

presumably, are attributable to cultural and institutional factors. 

Disaggregation of Recent Trends

Disaggregation allows for separate projections of 

the components of fertility. We will employ a disFigure 17. Historical Trend in U.S. Total Fertility Rate, by Race: 1800–2007

Source: Human Fertility Database; National Vital Statistics Reports (NVSR), Volume 58, Number 24, August 2010.

1.00 

2.00 

3.00 

4.00 

5.00 

6.00 

7.00 

8.00 

1800 1806 1812 1818 

1824 

1830 1836 1842 1848 

1854 

1860 1866 1872 1878 

1884 

1890 1895 1901 1907 1913 1919 1925 1931 1937 1943 1949 1955 1961 1967 1973 1979 1985 1991 1997 2003 

Whites

All

Total fertility rate (TFR)
2011 Technical Panel on Assumptions and Methods 47

aggregation strategy several times. First, we focus 

on the TFR and the estimation of its tempo and 

quantum components by following two broad strategies for decomposition: (1) reliance on completedcohort fertility that contains no tempo component 

and (2)  adjustment of the period rate to remove 

the tempo effect. Recognizing that the strategies 

involve strengths and weaknesses, we will employ 

both strategies, which lead to the same conclusion 

regarding recent U.S. trends.

The blue line in Figure  21 shows recent trends 

(1960–2008) in the TFR. The red line is a completed-cohort fertility series (CTFR)25 whereby the TFR 

and cohort series are aligned by adding 26 to the 

cohort’s birth year. Clearly, the TFR is lower than 

the CTFR in recent  years, demonstrating that, in 

these years, tempo effects (increasing ages at childbearing) operate to suppress the TFR relative to the 

25 For cohorts that have reached age 35 but cannot be observed 

until the end of the childbearing years (age 50), we project the 

fertility experience for the later years. Specifically, we assume that 

the average age-specific rates for the last two years observed will 

hold at the older ages.

CTFR. The strength of the CTFR approach is that it 

provides a “pure” measure of quantum for a cohort, 

although any particular cohort is only one of many 

contributing to a given period rate. In addition, the 

CTFR may not be estimated reliably for cohorts still 

in the midst of the childbearing years because their 

fertility experience is, by definition, incomplete. 

Thus, no CTFR quantum estimate is available for 

the last decade of the TFR series in Figure 21.

Bongaarts and Feeney (1998) say that the process 

of fertility postponement effectively pushes births 

that would have occurred in year x into year x+1. 

Thus, postponement consistently lowers the TFR 

net of quantum (the opposite case shifts toward 

younger ages at childbearing and increases the TFR 

net of quantum). Bongaarts and Feeney propose a 

simple adjustment to the TFR to capture the quantum component net of timing shifts. The adjustment is parity-specific and a function of the degree 

of postponement. For instance, if the first-birth 

mean age at childbearing increases by 0.1 in year t, 

it implies that 10 percent of first births have been 

postponed to year t+1 and that the appropriate adFigure 18. Total Fertility Rate in High- and Low-Development Countries: 1960–2005

Source: Morgan and Rackin, 2010a.

0.00 

1.00 

2.00 

3.00 

4.00 

5.00 

6.00 

7.00 

8.00 

9.00 

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 

Developed

countries’

average

Replacement

fertility

(TFR=2.1)

Developing

countries’

average

Total fertility rate (TFR)
48 2011 Technical Panel on Assumptions and Methods

Figure 19. Percentage of Births by Parity: United States: 1917–2007

Source: Panel calculations based on data from Human Fertility Data Base at http://www.humanfertility.org/cgi-bin/main.php.

Parity 4+

0% 

10% 

20% 

30% 

40% 

50% 

60% 

70% 

80% 

90% 

100% 

1917 1927 1937 1947 1957 1967 1977 1987 1997 2007

Parity 3

Parity 2

Parity 1

Figure 20. Mean Age at Childbearing by Parity: United States, 1917–2007

Source: Panel calculations based on data from Human Fertility Data Base at http://www.humanfertility.org/cgi-bin/main.php.

20 

22 

24 

26 

28 

30 

32 

34 

36 

1917 1927 1937 1947 1957 1967 1977 1987 1997 2007 

4th

3rd

2nd

1st

Age in years
2011 Technical Panel on Assumptions and Methods 49

justment to estimate first-birth TFR quantum is a 

1.1 factor.26 The green lines in Figure 21 show this 

tempo-adjusted TFR (TFR*).27 AS with the CTFR, 

these TFR* estimates consistently exceed TFR by 

about 10  percent. Thus, the underlying quantum 

component is consistently at or near replacement 

level. The tempo component, however, is a “temporary” effect; the age at childbearing cannot continue to increase indefinitely, but it can exert and 

in fact has exerted downward pressure on the TFR 

since about 1970.

26 Several elaborations of the model (e.g., Zeng and Land 2002; 

Kohler and Ortega 2004) followed the publication of Bongaarts and 

Feeney, 1998.

27 In estimates shown here, the change in mean age at childbearing at parities one and two was smoothed, producing a consistent 

upward drift in mean age at childbearing at these parities. There 

was little evidence of change at higher parities. Taken together, 

these adjustments (using the Bongaarts and Feeney approach) produced a consistent upward shift of TFR* relative to TFR, as shown 

in Figure 5.

In sum, on a 75-year horizon, the most important TFR component is quantum, and it has been 

approximately stable at 2.0 for over three decades. 

Tempo changes may be important over several decades, but continued increases in age at childbearing are time-limited (unless the ability to have children at advanced ages increases dramatically).

The second disaggregation strategy focuses on 

race and ethnicity. We look at the higher Hispanic TFR (e.g., between Hispanics and others)  and/

or changing composition of the population (e.g., 

larger proportion of the population Hispanic). Figure  22 shows strikingly higher fertility for Hispanics over the last 15 years, but convergence for 

whites and blacks. Given the strong likelihood that 

Hispanic population growth will outpace non–Hispanic population growth in the coming decades 

(natural increase, births-deaths, and immigration), 

a higher Hispanic TFR will exert increasing upward 

pressure on the overall U.S. TFR. This explanation 

produces the common claim that U.S. fertility is 

Figure 21. Trend in TFR, CTFR, and TFR*: United States, 1960–2007

Source: Panel calculations based on data from Human Fertility Data Base at http://www.humanfertility.org/cgi-bin/main.php.

Notes: (1) TFR available in database. CTFR estimates include some modest extension of current period age-specific rates to allow for time-series shown. (2) 

TFR* calculated using a smoothed change in age at first (.08 per year), and second births (.06 per year) over years 1963-2005. (3) TFR* assumes no change 

in timing for higher order births.

1.0 

1.5 

2.0 

2.5 

3.0 

3.5 

4.0 

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 

CTFR TFR* 

TFR 

Births per woman
50 2011 Technical Panel on Assumptions and Methods

at or near replacement because of minority group 

fertility. Indeed, in 2007, U.S. fertility was approximately 9 percent higher (2.12 versus 1.94) because 

of the higher fertility among Hispanics. However, 

fertility is near replacement (1.94) even with Hispanics excluded.

Over the next few decades, it is likely that Hispanic fertility will more closely approximate that 

of non–Hispanic whites, as suggested by various 

streams of evidence. First, cross-sectional comparisons of immigrants and first- and second- generation Hispanics often show little evidence of fertility 

decline, an observation interpreted as counter to 

assimilationist expectations. However, Parrado and 

Morgan (2008) show that, if the data are arrayed to 

reflect true generations, then convergence toward 

white non–Hispanic fertility is observed. These 

authors also show via simulation that the crosssectional result obtains when the cross-sectional 

fertility decline is greater than the generational decline. Second, other evidence shows that Hispanics 

are as responsive to socioeconomic change as are 

other groups. For instance, Hispanic fertility differences by education are equal to those of non–Hispanic whites (Parrado and Morgan 2008). Further, 

as shown in Figure 23A, Mexico’s (the source of the 

largest Hispanic immigrant stream) declining TFR 

reached 2.1 in 2005, approximately the same level 

as the United States in the same year. Figure 23B

shows the TFR for the United States and Mexico by 

levels of the Human Development Index (HDI) – a 

commonly used measure of social and economic 

development (discussed below). Mexican fertility 

is declining at a precipitous rate vis-à-vis HDI. In 

fact, by 2000, Mexico’s HDI had reached 0.8, a value 

reached by the United States in 1965–1970. Mexican and U.S. fertility rates are comparable once HDI 

is 0.8 or greater. Thus, we find little evidence that 

Hispanic fertility is resistant to decline with rising 

socioeconomic development. The likely reduction 

of much higher Hispanic fertility over the coming 

decades would reduce U.S. fertility by 5 to 10 percent over the 75-year projection period.

Figure 22. Race/Ethnic Total Fertility Rate Trends in the United States: 1980–2007

Source: U.S. National Center for Health Statistics, National Vital Statistics Reports (NVSR), Volume 54, Number 2; September 8, 2005; Volume 54, Number 

8, December 29, 2005; Volume 58, Number 24, August 2010.

0.0 

0.5 

1.0 

1.5 

2.0 

2.5 

3.0 

3.5 

1980 1983 1986 1989 1992 1995 1998 2001 2004 2007 

Total

White

Black

Hispanic

Total fertility rate (TFR)
2011 Technical Panel on Assumptions and Methods 51

Figure 23A. Total Fertility Rate for Mexico and the United States: 1960–2005

Source: Morgan and Rackin, 2010a.

Figure 23B. Total Fertility Rate by Human Development Index for Mexico and the United States: 1960–2005

Source: Morgan and Rackin, 2010a.

0.0 

1.0 

2.0 

3.0 

4.0 

5.0 

6.0 

7.0 

8.0 

1950 1960 1970 1980 1990 2000 2010 

Mexico 

United States 

Total fertility rate

0.0 

1.0 

2.0 

3.0 

4.0 

5.0 

6.0 

7.0 

8.0 

0.40 0.50 0.60 0.70 0.80 0.90 1.00 

 Mexico 

 United States 

Total fertility rate

Human Development Index
52 2011 Technical Panel on Assumptions and Methods

It is possible to develop decomposition arguments about other sizeable contemporary differences. For instance, the more religious have more 

children (Hayford and Morgan 2008). With respect 

to evidence that the population was becoming less 

religious, we would observe future declines as this 

secular change continued. However, evidence of declining religiosity is mixed at best. Likewise, educational differentials in fertility are cross-national 

and have been clearly visible in U.S. data for decades. But period fertility changes have been pervasive with respect to education, and quantum fertility has remained at roughly 2.0 despite massive 

increases in levels of educational attainment. Thus, 

it is unclear if ongoing increases in education will 

continue; even if they do, their effects on fertility 

are unclear. Finally, married women have higher 

fertility than unmarried women, yet most women 

marry, and rates of non-marital childbearing (and 

the proportion of children born to unmarried mothers) are rising. Experience of the last four decades 

shows that postponed marriage and high levels of 

marital disruption can co-exist with replacementlevel fertility in the United States.

Cross-National Comparisons

Figure  24 displays the TFR values from Figure 18 on the y-axis while the x-axis is an indicator of social and economic development (HDI). As 

noted in discussing Figure 18, social and economic 

development is a main causative factor in fertility 

decline. As in Figure  18, each line in Figure  24

represents a single country; the line is formed by 

connecting TFR/HDI points chronologically (1960–

1964 to 2000–2004). The general tendency for lines 

to slope downward from left to right indicates that 

persistent increases in HDI are associated with persistent TFR declines. We use the HDI to reflect its 

application in some important articles that provide the basis for some of our discussions (noted 

below) and because other socioeconomic indicators 

(or indices) would produce similar results.

HDI is an additive index created from components measuring income per capita, literacy and 

Figure 24. Total Fertility Rate by Human Development Index in High- and Low-Development Countries: 

1960–2005

Source: Morgan and Rackin, 2010a.

0 

1 

2 

3 

4 

5 

6 

7 

8 

9 

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 

3 4 

1 2 

Total fertility rate

Human Development Index
2011 Technical Panel on Assumptions and Methods 53

educational enrollment, and life expectancy.28 As 

in Figure  18, we show replacement-level fertility 

(i.e., TFR = 2.1 for low-mortality populations) with 

a bold horizontal line. Countries with HDI values 

greater than 0.85 typically exhibit fertility at replacement levels and below. We therefore identify 

the 0.85 level with a bold vertical line. The two lines 

generate four quadrants in Figure  24. The great 

majority of data falls in quadrants 1 and 4. Quadrant  1 corresponds to the fertility transition (the 

transition from high to low fertility); it is important to note the strong association between lower 

fertility and increasing HDI. Quadrant  4 demonstrates the remaining variation in TFR with little 

apparent association between further increases in 

the HDI and changes in the TFR.

The data presented thus far give rise to an important question. Does the anti-natalist effect (visible 

in quadrant 1) persist once fertility reaches a level 

of 2.1 and below (quadrant 4)? An affirmative answer strongly suggests further fertility declines. A 

provocative and highly visible article recently published by Myrskyla et al. (2009) suggested that, at 

high levels of development, further development 

produces a reversal in fertility, that is, an increase. 

A subsequent working paper by the same authors 

tempers these claims since much of the observed 

upturn in TFR was attributable  to the cessation 

of fertility postponement. Moreover, the authors 

failed to offer a convincing explanation of why very 

high levels of development would be consistently 

pro-natalist. They state that “given the heterogeneity of institutional, cultural and policy contexts 

across developed countries, further research is required to investigate the different mechanisms that 

may underlie this reversal – particularly in light of 

exceptions such as Japan, Canada and South Korea” 

(p. 742). After reviewing the evidence, the Technical Panel has arrived at a more cautious but important conclusion. At high levels of social and economic development (i.e., HDI in excess of 0.85), no 

consistent evidence demonstrates further development impacts on fertility levels. In Figure 25, we 

show data for a small set of countries with various 

levels of low fertility persistent on a decadal time 

scale. The differences likely result from pervasive, 

sustainable institutional differences. We argue that 

increases in HDI at high levels provide little lever28 See http://hdr.undp.org/en/statistics/indices/hdi/. Articles discussed below (Bongaarts and Watkins 1996; Myrskyla et al. 2009) 

use the HDI.

age on the direction of fertility change in the United States or elsewhere.

Insight into persistent fertility differences 

among low-fertility countries, such as those shown 

in Figures  24 and 25, comes from a conceptual 

“proximate determinants” model proposed by Bongaarts (2001; 2002) and used in a series of recent 

studies (e.g., Hayford and Morgan 2008; Morgan, 

Zhigang, and Hayford 2009; Morgan and Rackin 

2010b). The aggregate model explains TFR levels as 

a function of the population’s family size desires/

intentions conditioned by factors that impede the 

realization of the aggregate intention. The model 

first adjusts for tempo effects and then considers 

significant conditioning factors that lead people to 

exceed intentions. One such factor is birth control 

failure (that is, unwanted births). Other factors can 

produce a fertility shortfall vis-à-vis intentions. For 

instance, sub- or infecundity can vary across populations because of the degree of fertility postponement or other factors. In addition, persons may not 

realize their desired/intended family size because 

of competition with other activities. Thus, the model “explains” population-level differences in low fertility by other macro-level characteristics, thereby 

permitting speculation about trends in these components to assess whether change or convergence 

between countries is likely. 

Taking the United States as an example, we have 

seen that the nation has experienced high fertility for several decades relative to other highly developed countries. Morgan (2003) argues that the 

major components of the country’s higher fertility 

include a strong commitment to both parenthood 

and families with more than one child (fertility 

desires/intentions remain at replacement levels), 

a high level of birth control failure (e.g., 10 to 

15 percent of all births are unwanted), and institutional features that allow women to combine family and work (relatively low competition). Not only 

have these features been relatively stable for several decades, but the Technical Panel does not see 

strong evidence of change in the coming decades. 

In contrast, much lower fertility in other countries 

is a function of more anti-natalist components 

(lower or declining fertility desires/intentions, 

fewer birth control failures, and weak institutional 

support for resolving family/work conflicts). These 

persistent below-replacement fertility levels present significant problems (e.g., rapid population aging and eventual population decline). As a result, 

many low-fertility countries have instituted po-
54 2011 Technical Panel on Assumptions and Methods

lices aimed at increasing fertility. The cumulative 

experience of policies that do and do not succeed 

in raising fertility levels will likely provide developed countries with strategies to increase fertility 

if needed. Thus, we expect to see some international convergence of U.S. fertility rates with other 

low-fertility countries but expect much of the convergence to come from increases among countries 

with very low fertility rates.

While the Technical Panel sees stability in the U.S. 

proximate determinants (and, thus, in fertility) as 

the most likely scenario, it does recognize a greater 

likelihood of fertility falling below a TFR of 2.0 (as 

opposed to increasing). This asymmetry rests on 

several reasonable arguments: (1)  the popularity 

of one-child families may grow as the importance 

of a sibling for one’s first child declines relative to 

investing more heavily in a single child; (2)  new 

contraceptive technologies may reduce unintended 

births more than enough to offset the effects of 

improvements in assisted reproductive technology; and (3)  expanded non-familial opportunities 

may compete with childbearing to an extent greater 

than can be offset by institutional adjustments that 

ease the conflict between non-familial and familial 

pursuits.

Effects of the Recent Economic Downturn

U.S. economic downturns consistently reduce 

fertility (Morgan, Cumberworth, and Wimer 2011). 

Using unemployment as a measure of an economic 

downturn and a less refined measure of fertility, 

the General Fertility Rate (GFR, births per 1,000 

women age 15 to 44), Figure 26 shows that recent 

sharp rises in U.S. unemployment are associated 

with fertility declines. The GFR for a given month 

is associated with the monthly unemployment rate 

of nine months earlier. As of December 2009 (the 

most recent data available), the recession of 2007–

2009 produced a near doubling of the unemployment rate (4.5 to 9  percent)  and fertility declines 

of roughly 5 percent (a GFR decline from approximately 69/1,000 to 65/1,000). We suspect that the 

recession effects may persist for three or four years. 

Figure 25. Total Fertility Rate and Human Development Index for the United States and Other Selected LowFertility Countries: 1960–2005

Source: Data from Morgan and Rackin, 2010a.

0.00 

1.00 

2.00 

3.00 

4.00 

5.00 

6.00 

0.40 0.50 0.60 0.70 0.80 0.90 1.00 

United States 

Japan 

South Korea 

Total fertility rate

Human Development Index
2011 Technical Panel on Assumptions and Methods 55

Some of the decline will be fertility postponement 

and thus not visible in quantum fertility. Therefore, 

on a 75-year horizon, the recent economic downturn will exert only a minor effect on Social Security forecasts.

2.2 Mortality

Presentation Recommendation P-4. The Technical 

Panel recommends summarizing the assumptions 

about future mortality in terms of life expectancy 

at birth at the end of the projection period rather 

than in terms of the average annual percentage reduction in total age- and sex-adjusted death rates.

Method Recommendation M-8. The Technical Panel 

recommends simplifying the mortality projection 

model by eliminating separate projections by cause 

of death.

Assumption Recommendation A-3. The Technical 

Panel recommends increasing the intermediate 

life expectancy assumption to 88.7  years in 2085, 

which is 3.7  years higher than the 2011 Trustees 

Report’s assumption of 85.0  years. The Technical 

Panel also recommends low- and high-cost assumed 

life expectancies of 83.7 and 93.7 years. The difference between these low- and high-cost assumptions 

is 10 years (93.7 minus 83.7 years) compared with 

7.7  years in the 2011 Trustees Report; this range 

reflects the high degree of uncertainty about future 

mortality trends and the lack of agreement among 

experts about such trends.

Overview

For more than a century, life expectancy has 

risen in the United States as well as in several 

other countries. Mortality will likely continue its 

decline with ongoing progress in medicine, biotechnology, public health, nutrition, income, education, and access to medical services. However, 

analysts disagree dramatically about the pace of 

Figure 26. Monthly Fertility Rates and Nine-Month Lagged Unemployment Rates, United States: January 

2007–December 2009

Source: Unemployment data – seasonally adjusted http://data.bls.gov/timeseries/LNS14000000; fertility data – provisional, seasonally adjusted GFR 

(births per 1,000 women age 15–44) from National Vital Statistics Reports, various issues.

62.0 

63.0 

64.0 

65.0 

66.0 

67.0 

68.0 

69.0 

70.0 

71.0 

72.0 

3.0 

4.0 

5.0 

6.0 

7.0 

8.0 

9.0 

Jan-07 Jul-07 Feb-08 Aug-08 Mar-09 Sep-09 

Live births per 1000 women ages 15-44 

Unemployment rate 

General fertility rate

Unemployment rate

(lagged 9 months)

Monthly GFR and unemployment rate lagged 9 months
56 2011 Technical Panel on Assumptions and Methods

future improvements (Bongaarts 2006; Wilmoth 1997, 2001). At one end of the spectrum, the 

pessimists (Olshansky et al. 1990; Carnes et al. 

1996)  believe that the most advanced countries 

are close to a biological limit to longevity. At the 

other end of the spectrum, the optimists (Oeppen 

and Vaupel 2002)  expect life expectancy to continue to rise rapidly, reaching over age 100 later 

this century. Most projections by researchers and 

government agencies fall between these extremes. 

For example, the 2011 Trustees Report projects 

life expectancy to grow from 2006’s 77.7 years to 

82.2 years in 2050. That projection stands in major 

contrast with the figures published by EUROSTAT 

for France, Germany, Italy, Spain, and the United 

Kingdom (EUROSTAT 2011), which are expected 

to reach an average of 86.3 years by 2050.

In 2006, as a consequence of the high prevalence 

of smoking and obesity, the U.S. life expectancy 

of 77.7  years was lower than that of most other 

high-income countries. These behavioral effects 

will likely continue to depress U.S. life expectancy. 

Yet, despite their increase for decades, indicators 

of smoking behavior and obesity have recently plateaued (National Research Council 2011). Therefore, it is reasonable to assume that the adverse 

impact of these behaviors on life expectancy will 

remain at current levels rather than continue to 

rise. Taking these trends into account, the Technical Panel expects life expectancy at birth to reach 

85.5 years in 2060 and 88.7 years in 2085 – somewhat below the European projection but still above 

the Trustees’ current assumptions. 

The Technical Panel’s main recommendation is 

to assume a more rapid increase in life expectancy 

over the coming decades. Previous Technical Panels also made such recommendations, although our 

recommendation is for a larger upward revision. 

In addition, the Technical Panel reiterates recommendations made by previous Technical Panels to 

abandon separate projections by cause of death; 

such projections add unnecessary complexity and 

are not based on a transparent methodology.

Historical Background

Life expectancy in the United States started improving in the 18th Century, reaching 47.7 years in 

1900, 68.4 years in 1950, and 77.7 years in 2006 

(Trustees Report  2011).29 Increases were most 

rapid in the first half of the 20th Century as infec29 Average of male and female life expectancy.

tious diseases were brought under control, thereby 

greatly improving child survival. In contrast, increases in life expectancy since 1950 have been 

largely attributable to declines in adult mortality.

Female life expectancy has exceeded that of males, 

with the gap rising until the 1970s before a modest 

decline (Figure 27).

Trends in life expectancy after 1950 show uneven 

progress over successive decades (Figures 28A and

28B). The  years since 1980 represent a period of 

stagnation for females, but not for males, while the 

1950s and 1960s represent a period of stagnation 

for males, but not for females. As a result, U.S. life 

expectancy has risen at a slower pace than that of 

other large high-income countries (Australia, Canada, France, Germany, Italy, Japan, Spain, and the 

United Kingdom). As shown in Figure  28A, U.S. 

males ranked near the top of this group of highincome countries in 1950 but fell to the bottom 

after 1970 and remain in last place today. U.S. females (Figure 28B) also ranked high in 1950 and 

remained close to the other countries until 1980 

before dropping to last place in 2006.

Why does the United States demonstrate such 

a low current ranking in international mortality 

comparisons? This question has drawn the attention and concern of researchers and policymakers. 

The current situation is especially surprising given 

that the United States spends far more on health 

care than any other country. In response to these 

concerns, the National Research Council (NRC) appointed a panel of leading experts in 2008 to investigate the reasons for the divergence between the 

United States and other high-income countries. In 

its final report, the NRC panel reached several conclusions (National Research Council 2011):

“A history of heavy smoking and current levels of obesity are playing a substantial role in 

the relatively poor longevity performance of 

the United States.”

“The damage caused by smoking was estimated to account for 78 percent of the gap in 

life expectancy for women and 41 percent of 

the gap for men between the United States 

and other high income countries in 2003.”

“Obesity may account for a fifth to a third of 

the shortfall of life expectancy in the United 

States relative to the other countries studied.”
2011 Technical Panel on Assumptions and Methods 57

Figure 27. U.S. Life Expectancy by Gender: 1900–2006

Source: Office of the Chief Actuary, Social Security Administration, 2011.

Males 

Females 

40 

45 

50 

55 

60 

65 

70 

75 

80 

85 

1900 1925 1950 1975 2000 

Age in years

In addition to establishing the roles of smoking 

and obesity as factors in the relatively low U.S. life 

expectancy, the NRC report (2011) examined earlier trends in these factors and concluded:

“After 1964, when the Surgeon General’s 

Office released its authoritative report on 

the adverse effects of cigarette smoking, the 

increase in smoking slowed, stopped and 

eventually reversed in the United States.”

“Recent data on obesity for the United States 

suggest that its prevalence has leveled off 

and some studies indicate that the mortality 

risk associated with obesity has declined.” 

These conclusions have important implications for 

projecting trends in life expectancy and provide the 

basis for Recommendation 3, as discussed below.

Current Trustees’ Assumptions

The methodology for making mortality projections in the 2011 Trustees Report relied on three 

steps as follows:

1. Calculate historical average annual rates of decline in death rates by age, sex, and cause of death 

for the period 1986–2006.

2. Make assumptions about the long-range future rates of decline in death rates by age, sex, 

and cause. According to the 2011  Trustees Report, “[past] [r]eductions in death rates resulted 

from many factors, including increased medical 

knowledge, increased availability of health-care 

services, and improvements in sanitation and 

nutrition. Based on consideration of the expected 

rate of future progress in these and other areas, 

three alternative sets of ultimate annual percentage reductions in central death rates by age group, 

sex, and cause of death are assumed for 2034 and 

later” (Trustees Report 2011, p. 80). For the intermediate scenario, the Trustees make assumptions about 70  rates of decline (5  age groups × 

2  sexes × 7  cause categories). Consideration of 

the low- and high-cost projections increases the 

total number of parameters to 210. The Trustees 

Report does not describe the process for arriving 

at this large number of assumptions.
58 2011 Technical Panel on Assumptions and Methods

Figure 28A. International Comparison of Male Life Expectancy Trends: 1950–2007

Source: Human Mortality Database, Trustees Report, 2011.

Figure 28B. International Comparison of Female Life Expectancy Trends: 1950–2007

Source: Human Mortality Database, Trustees Report, 2011.

60 

65 

70 

75 

80 

85 

1950 1960 1970 1980 1990 2000 2010 

Australia 

Canada 

France 

Germany 

Italy 

Japan 

Spain 

UK 

US 

Life expectancy in years

60 

65 

70 

75 

80 

85 

1950 1960 1970 1980 1990 2000 2010 

Australia 

Canada 

France 

Germany 

Italy 

Japan 

Spain 

UK 

US 

Life expectancy in years
2011 Technical Panel on Assumptions and Methods 59

3. For the period between the last year of the 

historical data (2006) and the first year in which 

the ultimate rates of decline apply (2034), a set of 

formulas is used to produce a smooth transition 

in rates.

The 2011 Trustees Report expects life expectancy 

to reach 83 years in 2060 and 85 years in 2085, according to the intermediate set of assumptions.

Explanation of Panel Recommendations

Recommendation P-4

The overview section of the 2011  Trustees Report presents assumptions about future mortality 

trends in terms of the “[a]verage annual percentage 

reduction in total age-sex-adjusted death rates from 

2010 to 2085.” This variable was first introduced 

in the 2001  Trustees Report while reports issued 

before 2001 presented the Trustees’ mortality assumptions in terms of life expectancy at birth. The 

current Technical Panel believes that the practice of 

earlier reports is preferable because life expectancy 

is the most widely used indicator of mortality; further, readers are already familiar with it. In addition, the assumed life expectancy in 2085 captures 

the impact of assumptions for the transition period 

2007–2035, which is not the case for the ultimate 

rate of decline in the death rate. Recommendation 1 

does not change the fact that trends in age-specific 

death rates are needed to produce estimates of life 

expectancy.

Recommendation M-8

The current Technical Panel joins the 2007 and 

2003 Technical Panels in recommending elimination of the cause-specific component of the Trustees’ methodology. Previous Technical Panels provided a detailed rationale for this recommendation 

(not repeated here), but their findings include the 

following (Technical Panel on Assumptions and 

Methods 2007, 2003):

“A model based on separate projections by 

cause of death over a long time horizon is 

both implausible and inconsistent with historical experience.” [2003, p. 38]

“[Moreover],...the empirical basis for causespecific assumptions seems to be weak 

[2003, p. 38; 2007, p. 35].”

“There is little written explanation of how 

these assumptions were developed.”[2003, 

p. 38]

The process of producing 70 assumptions about 

ultimate rates of decline by age, sex, and cause of 

death for each of three cost scenarios is not documented and appears to be informal. Simplifying the 

mortality assumption will considerably improve 

the transparency of the Trustees Report.

Recommendation A-3

After examining the past and potential future impact of smoking and obesity, the Panel arrived at 

its recommendation for assuming a more rapid increase in life expectancy. In making this recommendation, we paid particular attention to the impact 

of smoking and obesity on life expectancy:

Smoking: Past Trends. The NRC report concluded that smoking has had an enormous influence on mortality in recent decades. To measure the 

impact, observed life expectancy may be compared 

with a hypothetical life expectancy that would be 

observed in the absence of smoking mortality (Glei, 

Preston, and Wilmoth 2010).30 As shown in Figures 29A and 29B, life expectancy without smoking is higher than with smoking for both males and 

females from 1950–2006, although the trends in 

smoking impact (bottom lines in Figure 29A and 

29B)  differ for males and females. For males, the 

smoking effect rose from 1950–1990, at which 

time it reached 3.1 years; it subsequently declined 

by one-fourth. At the peak in 1990, about a quarter 

of all deaths among males were smoking-related. 

Among women, the rise in smoking impact on life 

expectancy occurred later and peaked in 2002 at 

2.3 years. For both males and females, smoking behavior affects smoking mortality with a delay of two 

to three decades (e.g., lung cancer takes many years 

to develop after exposure to harmful smoke). As a 

result, the rise and fall of the mortality impact of 

smoking mirrors the consumption of cigarettes 

in earlier decades. Male smoking began to decline 

in the mid-1960s partly in response to warnings 

about the dangers of tobacco in a U.S. Surgeon General report released in 1964 (U.S. Surgeon General 1964). The resulting decline in smoking led to a 

decrease in its mortality impact after 1990. Among 

females, smoking and its mortality peaked more 

30 Estimates of age- and sex-specific death rates used here and in 

the NRC report are based on Dana Glei, Samuel Preston, and John 

Wilmoth, 2010.
60 2011 Technical Panel on Assumptions and Methods

Figure 29A. The Effect of Smoking on Male U.S. Life Expectancy: 1950–2006

Source: Dana Glei, Samuel Preston, and John Wilmoth, 2010.

Figure 29B. The Effect of Smoking on Female U.S. Life Expectancy: 1950–2006

Source: Dana Glei, Samuel Preston, and John Wilmoth, 2010.

With smoking 

Without smoking 

Smoking effect 

0 

2 

4 

6 

8 

10 

12 

14 

16 

18 

20 

65 

70 

75 

80 

85 

1950 1960 1970 1980 1990 2000 2010 

Life expectancy in yearsSmoking effect in years

Tech

Tech

Tech

Tech

Rate 

With smoking 

Without smoking 

Smoking effect 

0 

2 

4 

6 

8 

10 

12 

14 

16 

18 

20 

65 

70 

75 

80 

85 

1950 1960 1970 1980 1990 2000 2010 

Life expectancy in yearsSmoking effect in years
2011 Technical Panel on Assumptions and Methods 61

than a decade later than among males, and the peak 

remained below the level reached by males.

In addition to its substantial impact on the level 

of life expectancy, smoking influences the rate of 

improvement in life expectancy. For males, the 

observed increase in life expectancy since 1950 is 

9.5 years instead of the 11.0 years that would have 

been observed without smoking. For females, the 

rise in life expectancy with and without smoking is 

estimated at 9.1 and 11.3 years, respectively. Clearly, the effects of smoking have important implications for mortality projections, as discussed below.

Smoking: Future Impact. The Technical Panel 

considered four scenarios that differed primarily in 

the assumed trend associated with the impact of 

smoking:31

Scenario  A. This scenario represents the 

2011  Trustees Report’s intermediate projection, 

which is based on an extrapolation of death rates 

by age, sex, and cause to 2086. The Technical Panel 

31 Scenarios B, C, and D are derived by extrapolating age-specific 

mortality rates for both sexes combined, under conditions specified below.

considered the projection problematic for two main 

reasons. First, the use of 70  parameters without 

a formal procedure raises questions about the reliability of the projection. Second, the projection 

does not explicitly account for trends in the impact 

of smoking. As a result, Scenario  A implicitly assumes a rise in the impact of smoking in the future 

and is based on a comparison to a “no smoking” 

projection (gray line in Figure  30)  that assumes 

no smoking during 1950–2085. The difference between the two projections rises over time and represents the implied growing impact of smoking. The 

Technical Panel believes that it is not plausible to 

project the continued impact of smoking in future 

decades because the smoking epidemic has already 

peaked.

Scenario B. In extrapolating from 1950–2006 with 

age-specific death rates, Scenario  B addresses the 

first two shortcomings of Scenario A by expanding 

the historical basis for the projection to 1950 and 

eliminating cause-specific details. As shown in Figure 31, the log of age-specific death rates shows a 

steady near-linear decline from 1950–2006. A least 

Figure 30. Life Expectancy Projections: Alternative Scenarios

Source: Panel calculations; Technical Panel on Assumptions and Methods (1999, 2003, 2007); Li and Lee (2005); EUROSTAT, 2011. 

65 

70 

75 

80 

85 

90 

95 

1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 2055 2060 2065 2070 2075 2080 2085 

1999 Panel (for 2070) 

2003 Panel (for 2070) 

2007 Panel (for 2085) 

Li and Lee (for 2050) 

EUROSTAT (for 2050) 

No smoking

Observed (with smoking)

Life expectancy in years

Scenario D

Scenario C

Recommended

Scenario B

Scenario A
62 2011 Technical Panel on Assumptions and Methods

squares line fitted to the data for each age group 

provides a good fit and yields slopes close to those 

obtained by the widely used Lee-Carter method (Lee 

and Carter 1992; McNown 1992; Wilmoth 2005; 

Bell 1997). The advantage of this method is its simplicity and good performance in tests on historical 

data (Lee and Miller 2001). Only one parameter is 

required: the duration of the historical period used 

to estimate the slopes for different age groups. Earlier Technical Panels discussed the appropriate historical period and recommended periods starting 

around 1950; the current Technical Panel concurs. 

Scenario B is similar to those recommended by the 

1999, 2003, and 2007 Technical Panels such that 

the resulting future trends in life expectancy are 

also similar (Figure 30). The only drawback is that 

Scenario B ignores smoking trends and, as a result, 

implicitly assumes a rise in the impact of smoking 

for the same reasons as in Scenario A (Figure 30).

Scenario  C. In extrapolating from 1950–2006 

with the smoking impact held constant at 2006 

levels, Scenario C is similar to Scenario B in that it 

bases projections on extrapolation of age-specific 

death rates from 1950–2006. In addition, future 

trends in age-specific death rates are assumed to 

equal trends in historical age-specific death rates 

without – rather than with – smoking. Scenario C 

assumes that the smoking impact remains constant 

at each age from 2006 onward (instead of rising as 

in Scenarios A and B).

Scenario D. In extrapolating from 1950–2006 with 

declining smoking impact after 2006, Scenario D assumes that age-specific mortality rates decline from 

observed 2006 levels to levels projected for 2085 in 

the “no smoking” scenario, implying that mortality 

from smoking will disappear by 2085.

Figure 30 plots trajectories of life expectancies for 

each scenario. Life expectancy rises from 77.7 years 

in 2006 to 83.0  years, 84.4  years, 86.5  years, and 

87.7  years in 2060 and to 85.0  years, 86.9  years, 

89.7 years, and 91.3 years in 2085 in Scenarios A, 

B, C, and D, respectively.

Which of the four scenarios is most plausible? In 

making its recommendation, the Technical Panel 

considered two points. First, the choice of scenario 

depends on likely trends in smoking. As shown in 

Figures 29A and 29B, smoking-related mortality 

has leveled off for females and has started to decline 

Figure 31. Age-Specific Death Rates: United States

Source: Office of the Chief Actuary, Social Security Administration, 2011.

1-4 

5-9 

10-14 

15-19 

30-34 

35-39 

45-49 

55-59 

65-69 

75-79 

80-84 

85-89 

90-94 

95+ 

10 

100 

1000 

10000 

100000 

1950 1960 1970 1980 1990 2000 2010 

Deaths per 100,000 population (log scale)
2011 Technical Panel on Assumptions and Methods 63

for males. It is reasonable to assume that smoking 

mortality will be no higher in the future than it is 

today, suggesting that the most likely future trajectory will be at least as high as that in Scenario C. 

Second, it is useful to compare the above scenarios 

with projections made by earlier Technical Panels 

and other researchers or organizations. Figure 30

includes several data points representing the end 

points of other projections. The three solid red 

markers indicate the projections recommended by 

the 1999 (square)  and 2003 (triangle)Technical 

Panels for 2070 and by the 2007 (circle)  Technical Panel for 2085. The methodology used by these 

Technical Panels is very similar to the one used for 

Scenario B; therefore, it is not surprising that the 

points are located close to that scenario. The black 

hollow diamond represents the projection to 2050 

of Li and Lee (2005) who relied on a variant of the 

Lee-Carter method that accounts for mortality 

trends in other countries. Finally, the black hollow square represents the average 2050 projection 

made by EUROSTAT for the five largest European 

countries (EUROSTSAT 2011). As noted, the projections from the earlier Technical Panels do not account for smoking trends and are therefore biased 

downward. The EUROSTAT and Li and Lee projections make no explicit adjustments for smoking, 

but, given that U.S. men and women smoke more 

heavily than men and women in most European 

countries, the two projections implicitly are less 

distorted by smoking than are Scenarios  A and B 

for the United States. The evidence from these last 

two alternative projections also argues for a likely 

trajectory close to Scenario C.

Obesity: Past Impact. The preceding discussion 

focused on the role of smoking and ignored trends 

in behavioral factors other than smoking that may 

have a detrimental impact on life expectancy trends. 

The best known of such factors is obesity, which has 

a well-established adverse impact on health and 

mortality (Alley, Lloyd, and Shardell 2010). U.S. men 

and women are among the most obese people in the 

world, making obesity one of the major reasons that 

U.S. life expectancy is lower than life expectancy in 

most other high-income countries. 

Olshansky et al. (2005) estimated potential gains 

in life expectancy from eliminating obesity in the 

United States at a fraction of a year, with a slightly 

higher impact among males than among females 

(two first lines in Table 9).

Drawing from three recent studies by Adams et 

al. (2006), Metha and Chang (2010), and Preston 

and Stokes (2010), the 2011 NRC report presents 

additional estimates of the impact of obesity based 

on risk factors. The effects vary substantially, ranging from 0.52 to 1.61 for males and from 0.71 to 

1.28 for females (Table 9).

Despite the uncertainty in these studies, the 

Technical Panel decided  – for purposes of making 

recommendations about future trends – to assume 

that the current impact of obesity in the United 

States is one year. The assumed impact is higher 

than estimated by all but one of the studies listed 

in Table 9.

Obesity: Future Impact. The NRC panel noted 

that obesity levels have reached a (high)  plateau, 

suggesting that current estimates of life expectancy already reflect much of the impact of obesity on 

life expectancy. However, it is possible that obesity 

has delayed effect on mortality that is currently excluded from projections. The Technical Panel considers it likely that obesity has some delayed effect 

but believes it to be no greater than the current impact of obesity on life expectancy, i.e., the impact of 

Table 9. Impact of Obesity on Life Expectancya

Males Females

Olshansky et al. (white population) 0.33–0.99 0.30–0.81

Olshansky et al. (black population) 0.30–1.08 0.21–0.73

NRC based on Adams et al. (2006) 0.52 0.71

NRC based on Metha and Chang (2010) 0.64 0.61

NRC based on Preston and Stokes (2009) 1.61 1.28

a

 Life expectancy at birth for Olshansky and at age 50 for other three studies.
64 2011 Technical Panel on Assumptions and Methods

obesity will at most double from its current level. 

Given that the current impact on life expectancy is 

assumed to be one year, the implication is that the 

additional impact by 2085 will also be one year (for 

a total of two years).

Conclusion

Based on the preceding findings, the Technical 

Panel assumed that, without an adjustment for obesity, Scenario C will prevail in the future. To arrive 

at its intermediate recommendation, the Technical 

Panel made an adjustment by subtracting one year 

from Scenario C in 2085. The recommended trajectory thus falls between Scenarios B and C, with life 

expectancy reaching 84.5 in 2050 and 88.7 in 2085.

In view of the high degree of uncertainty about 

future mortality trends and the lack of agreement 

among experts, the Technical Panel decided to increase the range between the high- and low-cost 

projections to 10 years (i.e., 5 years above and below the intermediate variant). This range is a third 

wider than that adopted by the 2011 Trustees Report (Table  10)  and places the high-cost variant 

above Scenario  D and the low-cost variant below 

Scenario A.

Table 10. Comparison of Trustees Report’s and 

Technical Panel’s Recommended Assumptions

Projected Life Expectancy in 2085

2011 Trustees 

Report

2011 Technical 

Panel

High-cost 88.9 93.7

Intermediate 85.0 88.7

Low-cost 81.3 83.7

High-low range 7.7 10.0

2.3 Immigration

Assumption Recommendation A-4. The Technical 

Panel recommends that immigration scenarios 

should tie the level of net immigration to historical evidence on net immigration and population 

size rather than decreasing or increasing constant 

numbers of immigrants. The Technical Panel recommends that the Trustees express their ultimate 

net migration assumptions as rates of the annual 

number of net migrants divided by population size.

Assumption Recommendation A-5. The Technical 

Panel recommends making the assumptions regarding future immigration more consistent with 

long-range historical averages for earlier periods. 

Specifically, the Technical Panel recommends that 

the intermediate assumption should ultimately be 

3.2 net migrants per 1,000 persons. The Trustees’ 

current intermediate assumptions about net legal 

and net other immigrants in 2015 and assumptions 

about increases for 2015 through 2025 may be appropriate based on current evidence, but the Technical Panel believes that net immigration levels 

beyond 2025 will not decline as reflected in the ultimate assumption for the remainder of the projection period. The Technical Panel also recommends 

that the low- and high-cost assumptions should ultimately be 4.2 and 2.2 net migrants, respectively, 

per 1,000 persons.

Overview

The Technical Panel emphasizes the important 

role of immigration in increasing the number of 

young adults and eventually children in the U.S. 

population and thus immigration’s contribution to 

a younger and growing population. Immigrants, primarily at younger ages, increase the number of covered workers earlier than the number of retiree-beneficiaries and help improve the long-range actuarial 

balance. Since 1950, net immigration has increased 

annually at an average rate of about 4  percent, 

which is almost three times greater than the overall 

rate of population growth (1.4 percent), and immigration has long accounted for most U.S. population 

growth (Gibson 1975; USCB 2009a; Pew Hispanic 

Center 2006). Recent net migration has reflected 

an increase in legal immigration and an increase in 

undocumented or unauthorized migration, both of 

which remained high from 2001 through 2010 despite the recent economic downturn.

The Technical Panel has evaluated available evidence on net international migration in earlier 

decades and found that the United States lacks a 

system for keeping track of international migration, making it difficult both to quantify recent 

net immigration and project immigration for the 

coming decades. No single source of information 

provides data on annual or net immigration to the 

United States. The most clear-cut component of net 

immigration, which is annual legal immigration, 

is not easily predicted, although it is more easily 

measured than its counterpart of annual other immigration. In the past four decades, the two im-
2011 Technical Panel on Assumptions and Methods 65

migration components that are the most difficult 

to measure  – unauthorized migration and return 

migration/emigration of legal immigrants  – have 

become more important in modeling population 

change because they may not be assumed to offset 

the effects of undocumented migration and are not 

easily estimated. The decennial Census no longer 

provides a benchmark of net recent immigration 

or offers a reliable data source for indirect estimation of emigration and net unauthorized migration. 

Moreover, different estimates of the foreign-born 

population may be based on analyses of national 

surveys with varying and unknown coverage. To 

the extent possible, the Technical Panel has drawn 

from available statistics and preliminary results 

for net international migration for 2000 through 

2010. Population projections typically assume either that historical patterns will continue or that 

historical levels will decline because of diminishing 

unlawful migration in response to national enforcement policies or the termination of special lawful 

immigration policies.

Changes in legal immigration are associated with 

major modifications in immigration law since 1952 

while the current legal immigration regime is traceable to major legislative changes in 1965, 1976, 

1980, 1986, and 1990 followed by the passage of 

statutes in 1996 and 2001. These changes not only 

greatly increased the level of legal permanent immigration but also facilitated entry into the U.S. 

economy of larger nonimmigrant flows of tourists, 

business persons, and temporary workers, some of 

whom became long-term residents. As a classic immigration destination, the United States is a liberal 

welfare state that makes naturalization a relatively 

straightforward process and conveys rights similar 

to those enjoyed by native-born citizens (Janoski 

2010). The immigration laws reflect the principle 

of family reunification by specifying numerically 

limited family preference categories and unlimited 

immigration of immediate relatives of U.S. citizens. 

Admissions of immediate relatives averaged slightly more than 500,000 from 2001 to 2010, exceeding 

numerically limited immigration of about 375,000. 

For each principal immigrant, “immigration multiplier” effects refer to the total number of accompanying family members and, later, sponsored family members and any of their family members who 

subsequently immigrate (Jasso and Rosenzweig 

1990; Yu 2007).

In the Trustees’ current population projections, 

net immigration plays a diminishing role in population growth over the projection period, averaging 2.7 net migrants per 1,000 population in 2011 

through 2085, somewhat lower than the historical net immigration of nearly 3.0 net migrants per 

1,000 population from 1900 through 2010. At the 

beginning of the latter period, the United States 

placed no quantitative limits on the entry of immigrants. Although the current immigration system 

and enforcement infrastructure impose some restrictive policies, the historically low immigration 

levels of the mid-20th Century are unlikely to recur. 

The broader contexts of globalization of labor demand, market transitions, and evolving social networks have facilitated migration and settlement 

of both legal and unauthorized migrants. From an 

international standpoint, the United States is expected to remain the major receiving country of net 

international migration. Although national policies may affect the magnitude and directionality of 

international migration, the economic and demographic asymmetries that have primarily generated 

international migration are likely to result in persistence of recent migration patterns among more 

or less developed nations (UN DESA 2009).

Until the recent economic downturn, the increasing trend in immigration during the 1980s, 

1990s, and 2000s suggested that the post–1980 

period would provide a critical basis for projecting immigration into the future, as in the recommendations of earlier Technical Panels. However, 

the best evidence from 2007 through 2010 indicates that circular migration diminished, inflows 

dropped, and return migration declined. The level 

of net immigration in relation to the size of the 

U.S. population seems to have been lower for the 

2000s than for the 1990s (USCB 2010a). With this 

recent reminder of immigration’s volatility with 

economic shifts, it is useful to recall the moderate 

immigration from 1960 through 1980. Therefore, 

the Technical Panel recommends immigration levels that largely reflect the historical record. It bases 

the immigration assumptions for its intermediate recommendations on the long-term historical 

trend of net immigration and legal immigration, 

with assumptions for the low- and high-cost scenarios also drawn from experience.

Historical Background

Legal immigration to the United States has been 

very high at times and very low in other periods. 

The historical peak of U.S. legal immigration occurred between 1905 and 1915, followed by lulls 
66 2011 Technical Panel on Assumptions and Methods

during the Great Depression and the two World 

Wars. Beginning in the early 1920s, immigration 

laws became more restrictive, specifying numeric 

and geographic limitations. The Immigration and 

Nationality Act (INA) took effect in 1952 and provided the organized structure of statutes governing 

immigration law. The 1965 amendments to the INA 

repealed the discriminatory and strict nationalorigins quotas enacted in 1924, lifted the ban on 

Asian immigration, established a preference system 

of family and occupational categories by imposing 

country-specific limits on visas and an overall Eastern Hemisphere cap, and created exempt categories 

for immediate relatives of citizens; later amendments limited immigration from both the Western 

and Eastern hemispheres. Thus, legal immigration 

increased with greater numbers from the Eastern 

Hemisphere and under the numerically unlimited 

categories of immediate relatives of citizens. 

Legal immigration levels accelerated from 1950 

to 2000, but especially between 1990 and 2000. 

The Immigration Reform and Control Act of 1986 

(IRCA) legalized undocumented workers and longterm residents, largely affecting Mexican migration 

and future immigration through family reunification (Woodrow 1995; Durand, Massey, and Parrado 

1999; Clark, Hatton, and Williamson 2007). The 

Immigration Act of 1990 (IA1990)  expanded legal 

immigration, especially employment categories. 

The Personal Responsibility and Work Opportunity 

Reconciliation Act of 1996 (PRWORA) and the Illegal 

Immigration Reform and Immigrant Responsibility Act 

of 1996 (IIRIRA) restricted immigration by making 

enforceable the affidavit of support for individuals 

sponsoring family members for visas and by setting 

income requirements.

Large-scale unauthorized or illegal immigration 

emerged in the 1970s and continued with greater 

demographic and familial diversity over the 1980s 

and early 1990s despite IRCA measures to prevent 

employers from hiring illegal immigrants and efforts to intensify border and interior enforcement 

policies. Unauthorized migration escalated again in 

the late 1990s, with estimates of net legal and unauthorized migration in the 1980s, 1990s and 2000s 

based on demographic studies of national surveys. 

About 50 to 60 percent of unauthorized residents 

crossed without documents, primarily from Mexico 

and other Central American countries, with some 

border-crossers among those originating in nonneighboring countries and others arriving as legal 

temporary visitors and later becoming unlawful. 

Relative to 2000  Census-based unauthorized estimates of between 7.0 and 9.0  million residents 

(Passel 2002; Bean et al. 2001; INS 2003; Costanza 

et al. 2001; DHS 2006), extant unauthorized estimates showed an increase to about 11 to 12 million 

illegal immigrants between 2006 and 2010 (DHS 

2011; Passel and Cohn 2011).

From 1987 through 2010, the annual number 

of legal admissions averaged more than 1 million, 

which was roughly equal to the previous high from 

1900 through 1915. The number of lawful permanent residents between 1987 and 2010 showed 

considerable variability partly because of changes 

in U.S. policies, migrant decision making, and various bureaucratic factors, e.g., changes in application fees, application volumes, processing times, 

and security procedures. In contrast with the period 

1905–1915, the majority of immigrants entering 

the country between 1987 and 2010 were already 

long-term residents who had arrived as temporary 

travelers for tourism, business, diplomacy, and education (Massey and Bartley 2005). Several policies 

eased adjustment from unauthorized status to lawful permanent resident or legal immigrant status. 

These policies led to high legal admissions in the 

1990s and 2000s, e.g., from IRCA legalization provisions (1989 through 1991), the Legal Immigration 

Family Equity Act (LIFE) of 2000 (2001 and 2002), 

resolution of class-action lawsuits over IRCA amnesty application (before and during 2005 through 

2010), the Chinese Student Protection Act, and the 

Nicaraguan Adjustment and Central American Relief 

Act (NACARA) (1997).

Components of Immigration

The Trustees view net immigration as the product 

of three categories of immigrants: (1)  legal immigrants; (2)  other immigrants consisting of unauthorized immigrants (i.e., illegal and undocumented migrants) and certain legal nonimmigrants (i.e., 

temporary legal residents); and (3) emigrants from 

among native-born persons, other immigrants, or 

legal immigrants.32 Certain legal nonimmigrants 

32 All Social Security projections are based on the Social Security 

Area population, which comprises (1) residents of the 50 States 

and the District of Columbia (adjusted for net Census undercount); 

(2) civilian residents of Puerto Rico, the Virgin Islands, Guam, 

American Samoa, and the Northern Mariana Islands; (3) federal civilian employees and persons in the U.S. Armed Forces abroad and 

their dependents; (4) non-citizens living abroad who are insured 

for Social Security benefits; and (5) all other U.S. citizens abroad. 

As a result, emigrants are individuals who are no longer within the 

Social Security Area population, which differs from practices in 

Census population programs.
2011 Technical Panel on Assumptions and Methods 67

are long-term residents with work eligibility who 

are employed in OASDI-covered jobs; some other 

immigrants work without authorization and yet 

may have payroll taxes withheld.

For purposes of perspective, it is useful to note 

that the U.S. population in 2009 (307.7 million) included about one foreign-born person in every 

10  persons (12.5  percent or 38.5  million). Of native-born persons (87.5 percent or 268.5 million), 

about one in 10  persons was second-generation, 

with the remainder third- or higher-generation 

(with two native-born parents)  (USCB  2010b). 

Among foreign-born persons, the large share comprised noncitizens (43.7  percent or 21.7  million, 

or 7.1 percent of the total) rather than naturalized 

citizens (56.3  percent or 16.9  million, or 5.5  percent of the total) (Gryn and Larsen 2010). Among 

post–1980-arrived immigrants in 2010, there were 

nearly as many noncitizens as naturalized citizens 

among about 21.1 million legally resident foreignborn persons (DHS, Rytina 2010; DHS, Hoefer, Rytina, and Baker 2011).

The Trustees Reports’ historical data for legal immigrants are based on official government counts 

of admissions for lawful permanent residence 

(LPR); the U.S. Department of Homeland Security’s 

(DHS)  Office of Immigration Statistics (OIS)  now 

compiles those counts.33 Information on legal immigration is available each year and is representative of admissions to LPR status, including individuals arriving from other countries and individuals 

already living in the United States and adjusting 

from nonimmigrant (i.e., foreign student, guest 

worker, visitor for business or pleasure, refugee, 

asylee, or parolee) or other status, even illegal status. The data for net legal immigrants incorporate 

reductions for legal immigrants’ and native-born 

citizens’ movements out of the country based on 

indirect evidence supporting ratios of one emigrant 

for every three to five immigrants (Warren and Passel 1987; Warren and Kraly 1985; Woodrow 1991a, 

1996; Ahmed and Robinson 1994; Hollmann et al. 

2000; Mulder et al. 2002). Census population programs regularly update emigration rates derived 

from a comparison of foreign-born populations 

over time in order to project emigration levels (Passel and Cohn 2008; USCB 2010a; Grieco 2008).

For net other immigration in the historical data 

series, measures for net change in legal temporary 

33 The data were previously available from the Immigration and 

Naturalization Service (INS) in the U.S. Department of Justice and 

from various other agencies.

migrants and the net or gross flows of unauthorized immigrants are not straightforward. Official 

statistics on unauthorized migration compiled by 

DHS-OIS show an estimated 11 million unauthorized immigrants residing in the United States as of 

January 1, 2010 (DHS, Hoefer, Rytina, and Baker 

2011). Residual estimates of unauthorized migration involve greater uncertainty and sensitivity to 

errors than do estimates of legal immigration. Estimates of unauthorized immigrants are generally 

overstated because they include some legal temporary residents, such as an unknown population of 

long-term H-1B visa workers (GAO 2011), although 

DHS allowed for nearly 2  million nonimmigrant 

residents. Implicit within DHS and other estimates 

of unauthorized immigration is emigration of other 

immigrants and legal immigrants.

The 2011  Trustees Report’s historical data for 

net other immigration from 2005 through 2010 are 

largely based on year-to-year comparisons of DHS 

annual estimates for unauthorized immigrants. In 

principle, the best annual measures of net unauthorized migration are derived as the average annual change in the size of the unauthorized population at different times, although such an approach 

relies on comparability in coverage (DHS, Hoefer, 

Rytina, and Baker 2010, 2011). In fact, national 

survey estimates for 2007 through 2010 were not 

completely comparable, and may be contributing to 

overestimation of change in unauthorized migration (USCB 2009b; Passel and Cohn 2008). For the 

1980s, Census demographers developed estimates 

of unauthorized populations and average annual 

population change attributable  to undocumented 

migration (Passel and Woodrow 1984, 1987; Woodrow and Passel 1990; Woodrow 1991b; WoodrowLafield 1992)  for assumptions in population estimates and used similar assumptions for population 

estimates in the 1990s. For the 2000s, specific assumptions about net population change attributable to undocumented migration are not made for 

population estimates, which are derived from net 

international migration measures from national 

surveys.

Trends in Net International Migration

A look back to 1820 shows that legal immigration 

has historically exceeded net migration because 

emigration or return migration has been greater 
68 2011 Technical Panel on Assumptions and Methods

than unauthorized migration (Figure 32).34 By the 

1980s, unauthorized migration surpassed legal 

emigration such that net international migration 

was greater than legal immigration. In contrast 

with major declines in immigration levels before 

1950 (resulting from the restrictive immigration 

laws enacted between 1917 and 1924 and from 

the effects of the Great Depression and World War 

II), the years after 1970 have seen increased levels 

of legal immigration and large-scale unauthorized 

immigration. The number of immigrants reached 

historic highs by the 1980s, and net international 

migration in every period from 1980 through 1985 

and 2005 through 2010 has exceeded the previous 

high achieved between 1910 through 1915.

34 These series of estimates of net immigration, legal immigrants, 

and net unauthorized immigrants are presented according to the 

2007 Technical Panel’s more consistent focus by five-year period 

of arrival in the United States, updated for 2005 through 2010. 

The earlier report drew on historical projections for 1960 through 

2005 (Passel 2004; Passel and Cohn 2008) and 1900 through 1990 

(Edmonston and Passel 1994).

Legal immigration, on average, increased in recent decades,35 varying with the policies in effect 

and the clearance of backlogs.36 The increases in net 

unauthorized migration were dramatic,37 at average annual levels over 500,000 from 1980 through 

2010, or nearly 600,000 per year.38 With declines 

in the unauthorized population from 2007 through 

35 Average legal immigration levels totaled 634,000 in the 1970s, 

704,000 in the 1980s, 820,000 in the 1990s, and 1.02 million in 

the 2000s. From 1980 to 2010, average legal immigration reached 

851,000. Figure 32 overstates the number of legal immigrants for 

2005 through 2010 because of inadequate information for allocation to earlier periods of arrival and only partially known transfers 

from unauthorized to LPR status (cancellations of removal and 

NACARA adjustments). Better statistics may become available, 

such as Hollmann (2005).

36 Historical data on legal immigrants typically reflect varying 

numbers of immigrants owing to unexpected changes in immigration laws, processing delays, or changes in administrative policies.

37 The 2011 Trustees Report’s historical data showed that net 

other immigration averaged 375,000 per year from 1980 to 1989 

and 550,000 per year from 1990 to 1999.

38 For the period 2005 through 2010 in Figure 32, the updated 

number of net other immigration is set at 250,000 annually (DHS 

2010), which is slightly higher than the historical data in the 2011 

Trustees Report.

Figure 32. Average Annual Migrants in Millions: Net Migration, Legal Immigration, and Unauthorized 

Migration to the United States, 1820–2010, with Projections of Net Migration to 2085 According to 2011 

Trustees Report and Technical Panel Recommendations

Source: Panel estimates; Technical Panel on Assumptions and Methods, 2007.

1.03 

1.31 

0.77 

1.60 

2.10 

0.93 

0.00 

0.50 

1.00 

1.50 

2.00 

2.50 

1820-25 1830-35 1840-45 1850-55 1860-65 1870-75 1880-85 1890-95 1900-05 1910-15 1920-25 1930-35 1940-45 1950-55 1960-65 1970-75 1980-85 1990-95 2000-05 2010-15 2020-25 2030-35 2040-45 2050-55 2060-65 2070-75 2080-85 

Unauthorized Immigration 

Legal Immigration 

Historical Net Immigration 

Trustees Intermediate 

Trustees Low-Cost 

Trustees High-Cost 

Technical Panel Intermediate 

Technical Panel Low-Cost 

Technical Panel High-Cost 

Average annual migrants in millions

ecommended 

ario
2011 Technical Panel on Assumptions and Methods 69

2010 (DHS, Hoefer, Rytina, and Baker 2011), the 

average annual change in the unauthorized population totaled about 250,000 (DHS, Hoefer, Rytina, 

and Baker 2010), or an average annual increase of 

about 3.0 percent during the decade (CBO 2011).39

Overall, annual net immigration from 1980 

through 2010 averaged 1.1 million, although there 

were substantially higher levels from 1995 through 

2000 and substantially lower levels, from 2005 

through 2010.40, 41

Measurements of net immigration in relation to 

population size show that the net migration rate 

(NMR)  was highly variable before 1920, which is 

when restrictive and more defined immigration 

laws took effect. From 1840 through 1915, most 

of the annualized NMR values fell between 3 and 

8 net migrants per 1,000 persons. The average 5.7 

net migrants per 1,000 persons was lower than the 

average rate for legal immigration (8.7) because return migration was substantial.

As shown in Figure  33, the net migration rate 

from 1980 through 2010 averaged about 4.3 

per  1,000 population, well below historically high 

levels. The net migration rate of 2.1 per 1,000 population between 1960 and 1980 was similar to the 

rates between 1915 and 1930 before two decades 

of extremely low immigration. For the 2000s, net 

international migration initially increased, declined after 2001, rose again, and then decreased, 

resulting in declining net migration rates during 

the past decade (USCB 2010c). For the 190  years 

from 1820 through 2010, the average NMR was 

3.6. For the 20th Century, the average was 2.7; from 

1900 through 2010 and for 1945 through 2010, the 

NMR averaged about 2.9.

The net migration rate has demonstrated greater 

stability in the post–1920 period – a period charac39 Omitting the period between 1995 and 2000, net unauthorized immigration averaged 445,000 for the remainder of 1980 

through 2010.

40 For Figure 32, the updated annual average net immigration of 

1.05 million between 2005 and 2010 is based on an estimate of 

10.5 million for the change in the foreign-born population between 

2000 and 2010; an alternative estimate is slightly lower at 10.0 million, as implied by an increase in the foreign-born population 

between 2000 and 2010 (USCB 2010a).

41 From Vintage 2009 Census population estimates, annual 

estimates of net migration dropped from an average 1.0 million 

between 2000 and 2006 to about 870,000 between 2006 and 2009 

(960,000 for 2000 through 2009) (USCB 2010c). Alterations in 

components when the measurement of net international migration 

shifted to the residence-one-year-ago method (Grieco 2008) may 

account for differences in comparison with earlier estimates; Vintage 2006 estimates showed a higher estimate (more than 1.2 million) for average net migration between 2000 and 2006.

terized by quantitative limitations on legal immigration – although many factors led to substantial 

immigration between 1980 and 2010. Apart from 

the legal immigration framework, policies allowed 

status adjustments of formerly unauthorized residents and may have accelerated family migration. 

With Mexico the leading country of origin among 

both legal immigrants and unauthorized immigrants, three decades of intensified border enforcement have led to alterations in the behavior and 

settlement of Mexican migrants. Between 1980 

and 2005, the likelihood of unauthorized migrants 

returning to Mexico within a year of entry dropped 

by more than one-half to record low levels, accounting for the addition of 2  million Mexican settlers 

in the same period (Massey 2009, 2010). Contrary 

to expectations, admissions of immediate relatives 

of U.S. citizens born in Mexico have remained substantially higher than in the early 1990s (Hollmann 

et al. 2000). For these reasons, net immigration 

between 1980 and 2010 may have been unusually 

high. In some respects, the period from 1840 to 

1915 has been suggested as an example for understanding contemporary migration (Massey 1999, 

2000), although today’s immigration restrictions 

probably make a repeat of historical levels unlikely.

Current Trustees Assumptions

The 2008 through 2011 Trustees Reports treat 

net legal immigration and net other immigration 

by considering five sets of annual flows: (1)  legal 

immigration inflows; (2)  legal emigration or outflows of legal immigrants; (3)  other immigration 

inflows, including unauthorized migrants and legal 

temporary workers (not “short-term” temporary 

admissions); (4)  other emigration or outflows of 

other immigrants; and (5) transfers into legal immigration of other immigrants. As summarized in 

Table 11, the assumptions underpinning the level 

of net international migration became more complicated in 1988 when the intermediate scenario 

included an allowance of 200,000 for net other immigrants, as assumed by the Census Bureau. Between 1995 and 2007, the Trustees’ intermediate 

scenario included an ultimate annual net flow of 

900,000 persons based, in principle, on 800,000 legal immigrants and 300,000 net other immigrants, 

minus 200,000 legal emigrants. The assumption 

of 800,000 legal immigrants per year reflected an 

allowance of 80,000 for refugee and asylee admissions and about 10 percent in various other categories added to the 675,000 immigrants permitted 
70 2011 Technical Panel on Assumptions and Methods

under the Immigration Act of 1990’s flexible annual 

world-wide cap. Before 2008, the Trustees’ projections considered legal immigration, legal emigration, and net other migration. In refining the last, 

the modeling accounted for the presence, covered 

work behavior, and beneficiary entitlement of other immigrants.

For the 2008 through 2011 Trustees Reports, 

the ultimate assumptions on net immigration 

are 1.025  million for the intermediate scenario, 

although changes in the 2008 Trustees Report 

increased the ultimate assumption of annual legal immigration from 800,000 to 1  million to be 

consistent with average levels from 2001 through 

2006 (about 1.03 million), which proved to be consistent with average levels for 2000 through 2010 

(1.05  million)  and 1990 through 2000 (980,000). 

Thus, the Trustees recognized that a strict interpretation of current law is insufficient for specifying annual legal immigration. They therefore allow for slightly higher legal immigration levels of 

1.1 million in 2010 and of 1.05 million in 2011 as 

a consequence of the resolution of visa processing 

backlogs. Since the 2008 Trustees Report, the ultimate assumption holds that emigration of legal 

immigrants is 25 percent of the number of annual 

legal immigrants,42 placing the ultimate level of net 

legal immigration at 750,000.

The 2008 Trustees Report implemented new 

methods that separately treat the subcomponents 

of net other immigration, permitting net other 

immigration to be calculated as the difference between annual other immigration inflows and the 

sum of other immigrant emigration43 or outflows 

and other immigrant transfers to legal immigrant 

status. Essentially, one-half of annual legal immigration is assumed to be newly arrived and one-half 

to be adjusting to legal status from other status. 

The ultimate assumption on inflows of annual other immigrants entering the Social Security Area is 

1.5 million, of whom one-third are assumed to be 

transferring or adjusting to legal status. The Trust42 Legal emigration is assumed at 20 and 30 percent in the lowand high-cost scenarios, respectively.

43 Values shown for annual emigration of other immigrants are 

averaged over the period 2011 through 2085.

Figure 33. Annual Migrants per 1,000 Initial Population: Net Migration, Legal Immigration, and 

Unauthorized Migration to the United States, 1920–2010, with Projections of Net Migration to 2085, 

According to 2011 Trustees Report and Technical Panel Recommendations

Source: Panel estimates; SSA’s Office of the Chief Actuary projections 2011; Technical Panel on Assumptions and Methods, 2007.

3.2 

4.2 

2.2 

0.00 

2.00 

4.00 

6.00 

8.00 

10.00 

12.00 

14.00 

16.00 

18.00 

1820-25 1830-35 1840-45 1850-55 1860-65 1870-75 1880-85 1890-95 1900-05 1910-15 1920-25 1930-35 1940-45 1950-55 1960-65 1970-75 1980-85 1990-95 2000-05 2010-15 2020-25 2030-35 2040-45 2050-55 2060-65 2070-75 2080-85 

Unauthorized Immigration 

Legal Immigration 

Historical Net Immigration 

Trustees Intermediate 

Trustees Low-Cost 

Trustees High-Cost 

Technical Panel Intermediate 

Technical Panel Low-Cost 

Technical Panel High-Cost 

Annual migrants per 1000 initial population
2011 Technical Panel on Assumptions and Methods 71

ees also changed the method for emigration of other immigrants, assuming that 10 percent of recent 

new arrivals depart and applying emigration rates 

to the earlier-arrived other immigrant population. 

The Trustees detail these rates – and all immigration components  – by age and sex. The changes 

resulted in an increase to the long-range actuarial 

balance of about 0.30  percent of taxable payroll 

through an increased number of workers and a decreased number of eventual retirees.

The 2011  Trustees Report calculates net other 

immigration at 105,000 in 2011. In contrast with 

2008, annual other immigration inflows were set at 

1.0 million for 2009 through 2010. The 2011 Trustees Report set annual other immigration inflows 

at 1.1 million in 2011, 1.2 million in 2012, 1.3 million in 2013, 1.4 million in 2014, and 1.5 million in 

2015 through 2075. Over the projection period, annual net other immigration declines because of the 

increasing number of other immigrants residing in 

the Social Security Area, resulting in an increase 

in the number emigrating out of the area based on 

rates of departure. Ranging between 300,000 and 

500,000 from 2011 through 2050 and between 

275,000 and 295,000 from 2051 through 2085, net 

Table 11. Assumed Ultimate Levels of Net Migration for Three Scenarios, by Entry Status (legal versus 

other), Trustees Reports: 1981–2011

Ultimate Assumption for Net Migration

(1000’s of persons per year; average across annual reports)

Total Legal Immigration Other Immigration

Years of Reports LowCost

Intermediate

Cost 

HighCostLowCost

Intermediate Cost 

HighCostLowCost

Intermediate Cost

HighCostUltimate

1981–1984 438 400 363 438 400 363 0 0 0 Year 1

1985–1987 667 467 267 667 467 267 0 0 0 Year 1

1988–1990 750 600 450 450 400 350 300 200 100 Year 1

1991–1994 1,050 800 650 700 600 550 350 200 100 Years 

1–8

1995–1999 1,150 900 750 710 610 560 440 290 190 Years 

2–8

2000–2002 1,210 900 655 760 600 455 450 300 200 Years 

2–3

2003–2007 1,300 900 673 850 600 473 450 300 200 Year 21

2008–2011 1,305 1,025 770 960 750 560 350 275 210 Year 2

2011 Trustees Report

Average 2011–2086

Annual immigrants 1,200 1,000 800 1,800 1,500 1,200

Annual emigrants -240 -250 -240 -775 -665 -575

Annual transfers -600 -500 -400

Notes: (1) Trustees Reports have been grouped with those of neighboring years having similar sets of net migration assumptions;( 2) The “ultimate” date 

is defined here as the first year of the projection period for which the ultimate assumption was used for all scenarios. Thus, for the projection beginning in 

2007, the complete set of ultimate assumptions was used from 2027 onward, corresponding to Year 21 of the projection period. In some cases, the speed 

of convergence to ultimate values varied across Trustees Reports for neighboring years. (3) For years 2008-2011, net “other” immigration declines over the 

entire projection period because of constant assumed rates of emigration, and values shown for net other immigration and annual emigrants are average 

values over the projection period.
72 2011 Technical Panel on Assumptions and Methods

other immigration averages about 325,000 annually between 2011 and 2085.44

In combination, all five immigration components 

show an increase in net immigration of 1.25 million 

between 2011 and 2015, primarily as a consequence 

of post-recession increases to net other immigration. Subsequently, net immigration gradually declines to 1.025  million in 2085 largely because of 

declines in net other immigration. Over the projection period, net immigration averages 1.075  million.45 Over time, the Trustees Reports’ projections 

imply ratios of net immigration to the size of the 

population that decline from 3.4 per 1,000 between 

2010 and 2020 to 2.2 per 1,000 between 2075 and 

2085. However, the later figures  are higher than 

allowed in UN long-range projections (UN DESA 

2011).

Technical Panel’s Recommendations and 

Explanation

For most of the past two decades, the rate of immigration exceeded that portrayed in the Trustees 

Reports. The Technical Panel acknowledges that 

future immigration levels are likely to equal or exceed projected levels. The current Technical Panel 

believes that the Trustees should present policymakers with the most likely projections and formulate assumptions that allow for some changes 

in immigration law over the next 75 years and beyond. Assuming that current immigration laws remain unchanged, the net legal immigration levels 

assumed by the Trustees between 2011 and 2025 

are consistent with current evidence. However, the 

trend in future net migration will not necessarily 

be flat or decrease as assumed by the Trustees. We 

concur with the two earlier Technical Panels that the 

ultimate assumption for net immigration should be 

linked to population size. Such an approach is desirable primarily for simplicity and transparency given 

the uncertainties surrounding various components 

of net international migration. While the Technical 

Panel understands that the Trustees regarded “current law” as a useful convention for developing the 

intermediate scenario as a baseline against which to 

measure policy changes, the Technical Panel views 

more complete assumptions about various immigration scenarios as beneficial in projecting Trust 

Fund finances for the projection period.

44 The averages for net other immigration are 425,000 and 225,000 

for the low- and high-cost scenarios, respectively. 

45 The averages for net immigration are 1.385 million and 785,000 

for the low- and high-cost scenarios, respectively.

Rather than an approach based on current law, 

the Technical Panel recommends that the Trustees derive their net migration assumption from 

an analysis of historical trends and careful consideration of theories of international migration 

(Massey et al. 1998). The Technical Panel notes the 

contrasting viewpoints as to the volume of immigration to the United States in future decades. Factors cited in arguing for less immigration include 

slow recovery from the recent economic slowdown; 

deterrence through border enforcement and security measures; changes to immigration policy (e.g., 

termination of diversity visas or visas for adult 

sons and daughters (of aliens or citizens)  or siblings of citizens); diminishing family reunification 

as IRCA, NACARA, and LIFE immigrants complete 

sponsorship; declining labor force entry cohorts in 

Mexico; smaller, more easily supported family sizes 

in sending countries; social and economic development in Mexico and other sending countries; and 

competition from developed countries with aging 

populations and from developing countries with 

growing economies, especially China and India. 

Factors associated with likely increases in future 

immigration include the continuing demand for 

high- and low-skilled labor as the U.S. population 

increases and the economy recovers; perpetuation 

of immigration through family and social networks; globalization of labor and technology that 

facilitates international migration; labor surpluses 

in developing countries; increasing inequality in developing countries and a subsequent “push” on labor migrants; unanticipated effects for settlement 

and reduced return migration resulting from policies for controlling immigration; and policies that 

regularize unauthorized residents and workers.

The Technical Panel also notes that data limitations restrict comprehensive modeling approaches 

for treating various factors in population projections (Cohen 2011; Massey 2007, 2010). However, 

panel-data analytic studies with demographic, geographic, economic, historical, and policy variables 

demonstrate the emergence of a nuanced, empirical 

understanding of how U.S. immigration has been 

structured and perpetuated through the social and 

economic conditions inherent in the contemporary 

global economy (Kim and Cohen 2010; Cohen et al. 

2008; Clark, Hatton, and Williamson 2007; Hatton and Williamson 2002; Greenwood et al. 1999; 

Greenwood and McDowell 1999). For example, 

distance from the United States has a deterrent effect on U.S. immigration. In addition, the smaller 
2011 Technical Panel on Assumptions and Methods 73

the U.S. population cohort age 15 to 29 years, the 

greater is the level of net immigration. English as 

a common language is positively associated with 

U.S. immigration. The drivers of world migration 

may more persistently prove to be income and 

education, perhaps more so than the “friends and 

relatives” effect (Clark et al. 2007). Those most responsive to source-country conditions may be new, 

numerically exempt immigrants, as typified in annual legal immigration (Greenwood et al. 1999).

The Technical Panel supports the linking of immigration assumptions with the size of the U.S. 

population in the expectation that future immigration trends will be extensions of earlier trends. 

The demographic and economic asymmetries that 

drive international migration are likely to persist 

for several decades. The record of the past century 

has considerable plausibility for assuming future 

trends. The Census Bureau 2008 population projections based on stochastic forecasting of historical net international migration implied slight increases in the net migration rate between 2010 and 

2050. Those projections contrast with the declining 

trend in the NMR for the constant immigration scenario (Ortman, Hollmann, and Bhaskar 2010; UN 

DESA 2011), with which the Trustees’ intermediate 

scenario most closely corresponds. With respect to 

world population projections, the United Nations 

treated one scenario based on zero international 

migration between 2051 and 2300 but, in response 

to views that the scenario was neither realistic nor 

conservative (UN DESA 2003), turned to an alternative scenario that used the same net migration 

rates in longer-range modeling for 2045 through 

2050 (UN DESA 2004a, b).

The United States is a classic country of immigration whose liberal policies support family reunification, employment, diversity, and humanitarian 

relief. Accordingly, high legal immigration levels 

under post–1965 immigration laws are likely to 

persist. The contribution of other immigration to 

U.S. population growth remains substantial, if difficult to measure. In contrast with the immigration 

downturn inherent in the Trustees’ assumptions, 

the Technical Panel supports maintaining the importance of immigration in future population projections. Current provisions in immigration law 

have led to the presence of many undocumented 

individuals who may prolong their stays as they 

await immigration visas through documented family members or resolution of their status through 

a class-action lawsuit; their respective timetable s 

vary. Changes in prosecutorial discretion may reduce deportations or facilitate adjustment of status 

for unknown numbers of other immigrants seeking 

hardship relief.

Several indications point to less immigration in 

the 2000s than in the 1990s, emphasizing the volatility of immigration with respect to the U.S. economy and sending countries’ economies. Since 1990, 

the United States has seen a sustained decline in 

the rate of net undocumented migration from Mexico. In fact, Mexican net undocumented migration 

fell to around 200,000 per year in 2000 and then 

to zero by 2008 (Massey 2009, 2010)  partly as a 

result of deportations, especially deportations of 

Mexicans on an historic, massive scale (DHS 2011). 

However, the number of apprehensions of Mexican migrants at the border were still substantially 

higher than zero, dropping from 854,000 in 2007 

to 428,000 in 2010 (DHS 2010, 2011). A decline in 

Mexican undocumented migration may be partially 

explained by the relative labor supplies of Mexico 

and the United States. A simulation of cohort-level migration from Mexico (Hanson and McIntosh 

2009, 2010) showed that the greater U.S. labor supply may account for reduced Mexican emigration 

after 2000.

Given that conclusive answers about net immigration are lacking, the level of net international 

migration between 2000 and 2010 may have been as 

high as 13.5 million based on alternative estimates 

of and assumptions about coverage and emigration 

(USCB 2010a). The Technical Panel concurs with the 

Trustees on likely net immigration between 2011 

and 2025. To assess the effect of the recommendation for the long term, the Technical Panel adopted 

the Trustees’ estimate of 1.15 net migrants in 2025 

as a baseline. The crucial recommendation is that 

the ultimate immigration assumption for the intermediate scenario should be derived from longrun historical averages of the NMR – 2.95 for 1900 

through 2010 and 3.55 for 1820 through 2010. The 

Technical Panel notes that the average of these two 

averages for the NMR – 3.2 migrants per 1,000 – is 

consistent with the NMR of 2.9 per 1,000 for the 

65-year period 1945 through 2010 and with the 

NMRs for two periods that exclude recent high immigration – 3.19 for 1870 through 1990 and 3.27 

for 1965 through 1995. The high immigration levels between 1990 and 2010 led to an increase in the 

NMR from 3.4 per 1,000 between 1820 and 1990 to 

3.6 per 1,000 between 1820 and 2010. The Technical Panel suggests that the NMR of 3.2 per 1,000 
74 2011 Technical Panel on Assumptions and Methods

for 2025 through 2030 in the current Trustees’ 

estimates should be maintained throughout the 

remaining projection period, leading to increases 

in the assumed number of net migrants during the 

later decades of the period. The ultimate assumption in the low-cost scenario should be an NMR of 

4.2 per 1,000 as more consistent with the recent 

high NMR of 4.3 per 1,000 between 1980 and 2010 

while the high-cost assumption should be an NMR 

of 2.2 per 1,000, closer to the NMR of 2.1 per 1,000 

between 1960 and 1980.

The Technical Panel leaves the methodology for 

achieving the desired NMRs to the Trustees but 

notes that current methods may lead to (1) overestimates of emigration of legal immigrants and other immigrants and (2) underestimates of transfers 

to legal status given survey research identifying 

the parameters of lawful or unlawful pre–LPR experience (Massey and Malone 2002; Jasso, Massey, 

Rosenzweig, and Smith 2008), including long visa 

processing times for adjustees (Jasso et al. 2010). 

The Technical Panel sees the need for better empirical measures for overall immigrant inflows.

Future net international migration implied by 

the Technical Panel’s recommendations would total about 1.6 million annually by 2085 (Figure 32). 

For each scenario, levels of net migration are higher 

than those implied by the Trustees’ assumptions 

(Figure 33, yet the Technical Panel notes that the 

levels are not as high as those that would have resulted from the 2007 Technical Panel’s recommendations; those recommendations might have overemphasized the particularly high immigration levels 

between 1990 and 2000. The rationale for these 

“additional” immigrants need not be specified. Certainly, many or all might be legal under current law, 

which does not provide for a fixed number of immigrants, and certain policies and administrative procedures have prolonged the processes of adjustment 

and sponsorship. The differences between the Technical Panel’s recommendations and the Trustees’ 

assumptions would significantly affect projections 

of the total population. The effects in projecting the 

OASDI Trust Funds and evaluating system finances 

are more complicated because some of the additional immigrants would be in the other immigrant 

category and less likely to be in OASDI-covered employment, given their need for immigrant status 

verification for issuance of Social Security numbers. 

According to the Trustees, additional immigrants 

would be likely to improve the long-range actuarial 

balance by 0.07 percent of taxable payroll for each 

100,000 additional net immigrants.

Conclusion

In making the above recommendations for immigration assumptions in the intermediate scenario, 

the Technical Panel stresses the recommendations’ 

basis in long-term historical trends; the assumptions for the low- and high-cost scenarios are similarly grounded in long-term patterns. The Technical 

Panel expects that future immigration will depend 

critically on the growth of the U.S. economy, the fertility of native-born citizens, the resultant demand 

for labor, and the availability of labor surpluses in 

developing countries. Although immigration from 

Mexico may eventually slow, the worldwide trend 

in developed and developing countries’ labor supplies is likely to result in labor migration to developed countries. The U.S. labor force is likely to grow 

more than that of other developed countries, and 

yet continued U.S. demand for international migrants is probable. The Technical Panel commends 

the Trustees for changes in the 2008 Trustees Report that revised assumptions about immigration 

levels and that recast the approach for deriving 

net migration assumptions and implementation in 

order to clarify the impact of the other immigrant 

population.

2.4 Disability

Assumption Recommendation A-6. The Technical Panel recommends increasing the age-sex-adjusted disability incidence rate to 5.8 per 1,000 insured workers, with somewhat larger increases for women and 

smaller increases for men; this is higher than the 

5.2 per 1,000 rate assumed in the 2011 Trustees 

Report. The Technical Panel also recommends lowand high-cost disability incidence rates of, respectively, 4.8 and 6.9.

Assumption Recommendation A-7. The Technical 

Panel recommends a more rapid decline in DI mortality rates for both men and women from 2020 

through 2030 than is currently assumed. The effect 

of the recommended reduction on the age-adjusted 

mortality rate for men is a 15.7 percent lower mortality rate from 2030 through 2085; for women, it 

is a 14.3  percent lower mortality rate during the 

same period. The recommended intermediate ageadjusted DI mortality rate for men in 2085 is 11.10 
2011 Technical Panel on Assumptions and Methods 75

per 1,000 DI beneficiaries, which is lower than the 

currently assumed mortality rate of 13.20. The 

recommended intermediate age- adjusted DI mortality rate for women in 2085 is 8.20 per 1,000 DI 

beneficiaries, which is lower than the currently assumed mortality rate of 9.57. The recommended total age-sex-adjusted mortality rate in 2085 is 9.86, 

which is 13.7 percent lower than the currently assumed 11.42. The Technical Panel also recommends 

ultimate low- and high-cost total age-sex-adjusted 

mortality rates of, respectively, 17.10 and 6.30.

Assumption Recommendation A-8. The Technical 

Panel recommends reducing the assumed DI recovery rate from the currently assumed rate of 10.7 

per 1,000 DI beneficiaries to 8.7 per 1,000 DI beneficiaries. The Technical Panel also recommends 

an increase in the range of uncertainty about the 

recovery rate, with low- and high-cost values of, 

respectively, 11.4 and 6.0 relative to the currently 

assumed low- and high-cost values of, respectively, 

12.9 and 8.5.

Method Recommendation M-9. The Technical Panel 

recommends expanding the discussion of the factors leading to the projected decline in the share of 

DI-insured men and careful monitoring of the share 

to see if the recent declines among younger men 

carry forward to men at older ages. The Technical 

Panel notes that similar discussion and monitoring 

are warranted given the projection that the steady 

rise in the share of DI-insured women will level off 

in the short term.

Method Recommendation M-10. The Technical Panel 

recommends exploring in greater depth the effect 

of diagnoses of DI recipients on program exit rates 

because of recovery or death. The Technical Panel 

recommends similar exploration for the projected 

share exiting DI because of conversion to retired 

worker benefits.

Presentation Recommendation P-5. The Technical 

Panel recommends presenting more detail on the 

programmatic, economic, and health factors that 

drive DI applications and how the factors are assumed to change in the future.

Overview

When estimating the number of individuals receiving DI benefits in future  years, the Trustees 

account for several factors. First, they project the 

number of individuals in each age group, differentiating between men and women. Second, they project the share of men and women in each age group 

insured for DI benefits. For example, a person must 

have worked in at least 5 of the 10 most recent years 

to be potentially eligible for DI benefits. Third, the 

Trustees project the incidence rate for both men 

and women in each age group. The incidence rate 

is equal to the fraction of individuals in each age 

group insured for DI who are awarded benefits during the year. The fourth factor projected by OACT 

is the termination rate for men and women in each 

age group who receive DI. Individuals exit the DI 

program for three main reasons: conversion to retired worker benefits at full retirement age, death, 

and recovery.

The projections of the (1)  population size, 

(2)  fraction of the population that is DI-insured, 

(3) incidence rate, and (4) termination rate in each 

age group drive the projections of DI enrollment 

among men and women. Changes in any one factor translate directly into changes in the projected 

size of the program, though the discussion below 

focuses primarily on the latter three determinants 

of DI enrollment.

The following equation defines the change in the 

number of DI recipients from year t-1 to t within 

age group a and gender g:

DDIagt = POPagt * INSagt * INCagt – DIag,t-1 * TERMagt

where DDI

agt is the change in the number of DI recipients in the given group from the end of year t-1 

to the end of year t46; POPagt

 and INS

agt represent, 

respectively, the population in this group and the 

fraction of that population insured for DI; INCagt

is the incidence rate (awards divided by number 

insured)  in this group in period t; and TERMagt

 is 

the fraction of DI recipients at the end of period 

t-1 who exit the program during period t. Thus, the 

three factors noted above determine the changes in 

DI enrollment from the baseline year.

Background

Since the late 1980s, the fraction of non-elderly 

adults between age 25 and 64  years receiving DI 

benefits has more than doubled, rising steadily 

from 2.3  percent in 1989 to 4.7  percent by 2010. 

46 We abstract from the fact that individuals “age out” of the group 

during the year. For example, individuals who are 54-years-old at 

the end of year t-1 will age out of the group during the year while 

those who are 49-years-old at that time will age in to the group.
76 2011 Technical Panel on Assumptions and Methods

The increase in DI enrollment has been greater 

among women than among men. More specifically 

and as shown in Figure 34, the fraction of women 

between age 25 and 64 years receiving DI benefits 

increased from 0.9 percent in 1970 to 1.6 percent in 

1990 and then to 4.5 percent in 2010. Among men 

in the same age range, the corresponding increase 

in DI enrollment grew from 2.4  percent in 1970 

to 3.1  percent in 1990 to 5.0  percent by 2010.47

While DI enrollment increased by a similar amount 

(0.7  percentage point)  among men and women 

from 1970 to 1990, the growth among women has 

been much greater during the past two decades.

The increase in DI enrollment for both men and 

women is partly a function of the changing age 

structure of the U.S. resident population, with most 

of the Baby Boom generation aging into its 50s and 

47 The decline in DI enrollment during the late 1970s and early 

1980s per the figure was driven by a tightening of the program’s 

medical eligibility criteria and a sharp increase in the number of 

Continuing Disability Reviews (CDR) conducted on existing DI 

recipients. The 1984 law subsequently reversed the changes and liberalized the medical eligibility criteria beyond those in place before 

the clampdown on the program.

early 60s over the last 20 years. Analyses of nationally representative survey data (such as the March 

Supplement to the Current Population Survey issued by the Bureau of Labor Statistics)  indicate 

that the prevalence of self-reported disability rises 

steadily with age. Consistent with the analyses and 

as shown in Figure 35, rates of DI enrollment are 

substantially higher among these age groups than 

among adults at younger ages; therefore, it is reasonable to expect overall rates of DI enrollment to 

increase even if age-specific rates of DI enrollment 

do not change.

But, as the same figure shows, the increase in DI 

enrollment within each age group has been significant. For example, in 1989, the fraction of U.S. residents in their late 40s receiving DI disabled worker 

benefits was 2.2  percent. Twenty  years later, the 

fraction had almost doubled to 4.2  percent. With 

the substantial growth in DI enrollment within 

age groups and as shown by Duggan and Imberman (2009), the changing age structure of the U.S. 

Figure 34. DI Enrollment among Men and Women Age 25 to 64 years: 1970–2010

Source: SSA, Annual Statistical Supplement to the Social Security Bulletin, various years.

0% 

1% 

2% 

3% 

4% 

5% 

6% 

1970 1975 1980 1985 1990 1995 2000 2005 2010 

Percent receiving DI

Calendar Year

Male

Female
2011 Technical Panel on Assumptions and Methods 77

population explains less than one-fifth of the rise 

in DI enrollment from 1989 to 2010.48 Stated differently, if age-specific rates of DI enrollment had not 

changed during the 20-year period, DI enrollment 

would have increased from 2.3 to just 2.7 percent 

versus the actual increase of 2.3 to 4.7 percent.

The increase in DI enrollment has coincided with 

a steady rise in the share of Social Security expenditures paid out to DI recipients. From 1989 to 2010, 

that share increased from 10 to 18 percent but significantly understates the importance of DI to the 

overall Social Security program for at least two reasons. First, the results from earlier research suggest 

that the work incentives created by the DI program 

reduce labor force participation among those both 

applying for and receiving DI benefits.49 Thus, pay48 Following the methodology used by Duggan and Imberman 

(2009) and updating it to use 2009 as the final year.

49 See Parsons 1980; Bound 1989; Parsons 1991; Bound and Waidmann 1992; Gruber and Kubik 1997; Bound and Burkhauser 1999; 

Burkhauser and Daly 2002; Stapleton and Burkhauser 2003; Autor 

and Duggan 2003; Chen and van der Klaauw 2007; von Wachter, 

Song, and Manchester 2011.

roll tax revenue for the Social Security program is 

lower. Second, DI recipients receive a monthly benefit equal to their full Primary Insurance Amount 

(PIA) and continue to receive the benefit after converting to retired worker benefits at full retirement 

age. Accordingly, many former DI recipients receive 

higher retired worker benefits than if they had not 

enrolled in DI.50

OACT Assumptions and Technical Panel 

Recommendations

Fraction Insured for DI Benefits. To be insured for DI benefits, an adult must have worked 

in at least 5 of the 10 most recent years and must 

be less than full retirement age.51 The fraction of in50 Consider a DI recipient born between 1943 and 1954 who would 

have claimed retired worker benefits at age 62 if he had not qualified for DI. Monthly DI benefits are 100 percent of the Primary 

Insurance Amount (PIA) while retired worker benefits would be just 

75 percent of PIA. Thus, monthly retired worker benefits for this 

individual would be 33.3 percent greater if he enrolled in DI before 

receiving retired worker benefits. The exact difference might vary 

somewhat depending on the person’s age at the time of DI award, 

as age determines the number of years of earnings used to calculate 

the DI benefit.

Figure 35. Percent of Adults Receiving DI by Age Group: 1989 and 2009

Source: SSA, Annual Statistical Report on SSDI, various years. 

0% 

2% 

4% 

6% 

8% 

10% 

12% 

14% 

20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 

Percent receiving DI

Calendar Year

1989

2009
78 2011 Technical Panel on Assumptions and Methods

dividuals meeting these criteria varies by both age 

and gender and has changed over time. Most notably, the increase in female labor force participation in recent decades has led to a steady rise in the 

fraction of women insured for DI. For example, the 

fraction of women age 50 to 54  years insured for 

DI increased from 56.0 percent in 1987 to 75.4 percent by 2007 (Figure  36). However, the increase 

was not nearly sufficient to “explain” the increase 

in DI enrollment among women during the same 

period. More specifically, the fraction of women in 

their early 50s receiving DI benefits increased by 

160 percent (from 2.3 to 5.9 percent) from 1989 to 

2009 versus an increase of just 35  percent in the 

share of DI-insured women during the same period.

Figure 36 presents the share of women in their 

early 50s insured for DI at five-year intervals 

through 2007 and the projections at five-year intervals through 2032. After accounting for the 

steady rise through 2007, the share of women who 

are DI-insured is projected to level off over the 

next 25 years, with the projected 2032 fraction of 

75.2 percent almost identical to the actual 75.4 percent share in 2007. The projection partly reflects the 

Trustees’ assumptions that expansion of the female 

labor force will not grow much larger in the years 

ahead, but it may also reflect an increase in the projected share of other-than-legal immigrants in this 

group.52

Figure 36 also permits a comparison of the share 

of DI-insured men and DI-insured women age 50 to 

54 years. The Trustees assume that the share of men 

insured for DI – which has gradually though steadily increased since the 1980s – will fall substantially 

in the coming decades. While just 15.0 percent of 

men in their early 50s are not currently insured for 

DI benefits, that share is projected to increase to 

24.8 percent by 2032. The Trustees Report does not 

discuss this substantial change, along with similar 

changes for many other groups.

The projections for other age groups among both 

men and women are qualitatively similar, with a 

leveling off projected for women and substantial 

declines projected for men. For example, among 

52 Undocumented immigrants are not insured for DI benefits even 

if they have worked a sufficient number of years.

Figure 36. Percentage of DI-Insured Men and Women Age 50 to 54 years: 1977–2032

Source: Office of the Chief Actuary, Social Security Administration, 2011.

40% 

45% 

50% 

55% 

60% 

65% 

70% 

75% 

80% 

85% 

90% 

1977 1982 1987 1992 1997 2002 2007 2012 2017 2022 2027 2032 

Calendar Year

Men age 

50-54

Historical Projected

Women age 

50-54
2011 Technical Panel on Assumptions and Methods 79

women between age 40 and 44 years, the DI-insured 

share is projected to fall from 74.0 to 72.8 percent 

from 2007 to 2032 while, among men in the same 

age group, the projected decline is much greater – 

from 85.3 to 76.8 percent.

Given OACT’s methodology, the assumed declines in the share of DI-insured reduce the number 

of individuals projected to receive DI benefits. More 

careful discussion and scrutiny of the projections 

and the factors responsible for them (e.g., declining 

employment, rising shares of other-than-legal immigrants, and so forth) are warranted in view of the 

sharp departure from recent experience and the importance of the DI-insured shares to the mediumand long-run size of the DI program.53 This forms 

the basis for the Technical Panel’s first method recommendation M-9 above.

53 It is worth noting that the share of men insured for DI has been 

falling at younger ages. For example, among men between age 30 

and 34 years, the fraction insured for DI fell from 85.6 percent 

in 1997 to 79.3 percent in 2007. The Trustees assume that the 

declines will carry forward to successive age groups, though the 

projected magnitude of the decline is even greater than observed 

among men at younger ages.

Incidence Rates. In future years, an important 

determinant of projected DI enrollment is the incidence rate, which is the ratio of DI awards to the 

number insured for DI benefits in each year. Incidence rates have steadily increased in recent years, 

partially reflecting the effect of the aging of the 

Baby Boom generation and the link between incidence rates and age. Figures 37 and 38 depict DI 

incidence rates for men and women, respectively, 

in three age groups: 20 to 34 years, 35 to 49 years, 

and 50 to 64  years.54 Recognizing the significant 

changes in the medical eligibility criteria for the 

DI program that took effect in 1984, we focus on 

the period since 1985. The data from 1985 to 2009 

present actual incidence rates while the data from 

2010 to 2040 are projected incidence rates. Given 

that projected incidence rates remained largely un54 Incidence for these 15-year age groups is the unweighted average 

of the incidence in each of the three component 5-year age groups. 

For example, to calculate incidence among men age 35 to 49 years, 

we take the average of the incidence for men age 35 to 39, 40 to 44, 

and 45 to 49 years in order to reduce the effects of any changes in 

the age structure within these 15-year age groups.

Figure 37. DI Incidence (per 1,000 insured) among Men: 1985–2040

Source: Office of the Chief Actuary, Social Security Administration, 2011.

0.0 

2.0 

4.0 

6.0 

8.0 

10.0 

12.0 

14.0 

16.0 

18.0 

20.0 

1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 

DI awards per 1000 insured

Calendar Year

Age 50-64

Age 35-49

Age 20-34

Historical Projected
80 2011 Technical Panel on Assumptions and Methods

changed between 2040 and 2085, we focus on the 

first 30 projection years rather than on all 75.

An examination of data in the two figures reveals 

that, consistent with previous research (Black, 

Daniel, and Sanders 2002; Autor and Duggan 2003; 

Duggan and Imberman 2009), DI incidence rates 

increase during economic downturns. For example, 

the incidence rate for all three age groups for both 

men and women rose substantially from 1989 to 

1992, a period encompassing the 1991 recession. 

Similar increases were apparent in the early 2000s, 

and DI incidence rates rose substantially again 

from 2007 to 2009 during the most recent recession (the 2010 and later data in Figures 37 and 38

are projections).

The data demonstrate that it is important to control for economic conditions when exploring how 

age-specific DI incidence rates for both men and 

women have evolved in recent  years and whether 

they are relatively stable . Indeed, the Trustees assume that age-specific DI-incidence rates for both 

men and women will stabilize at levels close to 

those of just before the recent economic downturn. 

This can be seen in Table 12, which compares the 

actual age-specific incidence rates in 2007 for both 

men and women with the projected rates in 2037. 

The 50-to-59- and 60-to-64-year age groups are 

listed separately given the somewhat different patterns for these two subgroups.

An examination of the data in Table 12 reveals a 

larger projected increase in incidence for men than 

for women over the long run. For example, while 

incidence for men age 35 to 49  years is projected 

to increase by 3.3 percent from 2007 to 2037, incidence for women in the same age range is projected to decline by 6.1  percent. With the exception of those age 60 to 64 years,55 the projections 

55 The Trustees assume that incidence for both men and women in 

their early 60s will increase by about 25 percent from 2020 to 2030 

(after falling somewhat from 2007 to 2020) and then stabilize. The 

increase may reflect the projected effect of the increase in Social 

Security’s full retirement age, which will enhance the relative financial attractiveness of DI benefits for cohorts born in 1955 and later 

relative to those born from 1943 to 1954. See Duggan, Singleton, 

and Song (2007) for an examination of the effect of the full retirement age on DI enrollment.

Figure 38. DI Incidence (per 1,000 insured) among Women: 1985–2040

Source: Office of the Chief Actuary, Social Security Administration, 2011.

0.0 

2.0 

4.0 

6.0 

8.0 

10.0 

12.0 

14.0 

16.0 

18.0 

20.0 

1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 

DI awards per 1000 insured

Age 50-64

Age 35-49

Age 20-34

Historical Projected

Calendar Year
2011 Technical Panel on Assumptions and Methods 81

of long-run age-specific incidence are highly similar 

to 2007 values.

To determine the appropriateness of the assumptions, an empirical investigation can determine 

whether there is a significant time trend in DI incidence for either men or women by estimating models of the following type for each age group depicted 

in Figures 37 and 38:

Incidencet = g + b * (Year-1985)t + g1 * 

UnempRatet + g2 * UnempRatet-1 + eat

The model controls for both the current year’s 

and previous year’s unemployment rate given that 

economic downturns may have a delayed effect on 

DI application and award. The model includes the 

25 most recent  years (1985 through 2009)  (subtracting 1985 from the calendar year variable so 

that the variable ranges from 0 to 24).56 The coefficient b captures the average annual change in incidence for each age group after controlling for the 

effects of the unemployment rate.

The results reveal that, for all six age*gender 

groups considered in Figures 37 and 38, there is 

a statistically significant positive trend in DI incidence.57 Table  13 summarizes the results, listing 

the estimate for b along with its corresponding 

56 There are two possible concerns with the selection of this time 

period. First, DI incidence was relatively low in the mid-1980s, even 

after the change in DI’s medical eligibility criteria. Second, the effects of the most recent economic downturn have not yet been fully 

felt. Our results are, however, almost identical if we shorten our 

time frame by restricting attention to the 20-year period from 1988 

to 2007 inclusive, which would exclude both the mid-1980s and 

the years since the start of the most recent recession.

57 All 12 estimates for g1

 and g2 in the six models are positive, 

reflecting the increase in DI award rates that tends to occur as the 

unemployment rate rises. In five of the six models, either g1 or g2 

is statistically significant at the 5 or 10 percent level. The one exception is the female group age 50 to 64 years. 

p-value.58 It also lists the 2007 incidence for each 

group in order to facilitate a comparison with the 

estimated annual rates of change.

To gauge the implied magnitude of the estimates, 

it is useful to consider an example. The estimate 

of 0.1143 for b in the model for women age 35 to 

49 years suggests that incidence rose by an average 

of 0.1143 per 1,000 each year from 1985 to 2009. 

If this trend were to continue for just another 

10 years and then stabilize, it would represent an 

increase of approximately 1.14 per 1,000 insured in 

DI incidence for the same group, a 24  percent increase over the 2007 value of 4.71 per 1,000.

For all six groups, DI incidence is trending up 

over time – and especially rapidly for women. Relative to baseline DI incidence, the increases are larger for the younger age groups.59 For example, if the 

trends were to continue for another 10 years, incidence for women age 20 to 34 years would increase 

by 31 percent (equal to 0.51 divided by 1.65) versus 

15 percent for women age 50 to 64 years. The corresponding implied changes for men in the same two 

age ranges would be 12 and 5 percent, respectively.

From the perspective of the DI program specifically and Social Security generally, the relatively 

rapid increase in award rates at younger ages is particularly important for two reasons. First, potential 

time spent in the DI program (and thus the present 

58 Lower p-values represent greater statistical precision. A p-value 

of less than 0.10 (0.05) implies that the estimate is statistically 

significant at the 10 (5) percent level.

59 It is not surprising that DI incidence is growing more slowly at 

older ages when one considers that today’s counterparts to individuals who, in previous years, qualified for DI in their late 50s and 

early 60s may qualify for the program at much younger ages.

Table 12. DI Incidence by Gender and Age: 2007 and 2037

Age Group

Female Incidence Male Incidence 

Actual 2007 Projected 

2037

Percent 

Change Actual 2007 Projected 2037

Percent 

Change

20–34 1.65 1.64 -0.6% 1.81 1.84 +1.8%

35–49 4.71 4.42 -6.1% 4.13 4.26 +3.3%

50–59 11.45 11.39 -0.5% 11.89 12.02 +1.1%

60–64 15.35 16.78 +9.3% 17.57 21.78 +24.0%
82 2011 Technical Panel on Assumptions and Methods

value of potential DI benefits60) is much greater for 

a young or middle-age adult than for a near-elderly 

adult. Second, to the extent that DI reduces labor 

force participation, it translates into a corresponding decrease in tax revenue. Unfortunately, the 

single age-sex-adjusted incidence reported in the 

Trustees Report essentially treats an award at age 

40 no differently than an award at age 60 even 

though the implications for the DI Trust Fund vary 

dramatically.

In light of the empirical results reported above, 

the Trustees’ assumption that DI incidence will remain stable throughout the 75-year projection period seems implausible. Absent a significant change 

in DI policy, such as a tightening of the program’s 

medical eligibility criteria, a much more likely scenario is that the trend toward increasing DI incidence will continue for some time. Even the assumption that the trend will continue for just 10 

more years means that incidence among men and 

women, respectively, for the three age groups noted 

earlier would increase by an average 1.2 and 0.4 per 

1,000. 

This analysis forms the basis for Recommendation  A-6, an increase in the long-run age-sexadjusted incidence rate from 5.2 to 5.8 per 1,000 

insured workers (and identical increases of 0.6 per 

1,000 for the low- and high-cost scenarios), with 

variation in the magnitude of the adjustment by 

gender and age group. The recommended adjustments to DI incidence rates are intentionally conservative in two important respects. First, the 

trend for each age group is assumed to continue 

60 Given that earnings tend to rise with age, at least through the 

20s and 30s, the average monthly benefit for younger individuals 

awarded DI benefits is smaller than for those awarded benefits 

later. This reality is, however, not nearly sufficient to offset the 

effect of a larger number of potential years in the program on the 

present value of benefits.

for only 10 more years. Second, the recommended 

increases are somewhat smaller than the increases 

implied by the 10-year trend projections.

Termination Rates. From 1985 to 2009, the 

annual exit rate from DI fell from 12.0 to 7.7 percent. The average person awarded DI benefits now 

remains in the program for much longer than his 

or her counterparts of earlier  years. Individuals 

may exit the DI program for one of three reasons: 

(1) conversion to retired worker benefits at full retirement age (FRA), (2)  death, or (3)  recovery. Of 

the 617,587 DI recipients exiting the program in 

2009, 55.1 percent exited by converting to retired 

worker benefits, 36.2 percent because of death, and 

8.6 percent because either their earnings exceeded 

the substantial gainful activity level set by SSA or 

they no longer met the program’s medical eligibility 

criteria.

Conversion to Retired Worker Benefits. DI 

recipients who reach the FRA (age 66 for those born 

from 1943 to 1954) convert to retired worker benefits; thus, changes in the exit rate associated with 

the FRA are entirely a function of the DI population’s age distribution. As shown in Figure 39, the 

FRA exit rate trended down during the late 1980s 

and through the late 1990s as DI enrollment rates 

increased especially rapidly among younger adults 

(and a decreasing share of DI recipients was just under the FRA). The rate was fairly stable in the early 

2000s and artificially low from 2003 through 2008 

Table 13. Annual Rate of Change in DI Incidence: 1985–2009

Gender Age Group 2007 Incidence b p-value

Men

20–34 1.81 0.022 0.001

35–49 4.13 0.042 0.003

50–64 13.78 0.063 0.018

Women

20–34 1.65 0.051 0.000

35–49 4.71 0.114 0.000

50–64 12.75 0.193 0.000
2011 Technical Panel on Assumptions and Methods 83

because of the increase in the FRA that occurred 

during that period.61

As shown in Figure  39, the FRA exit rate will 

soon increase as the oldest members of the Baby 

Boom generation (born in 1946)  reach their FRA 

beginning in 2012. OACT projects substantial increases in the exit rate in subsequent  years, with 

eventual stabilization at around 60 per 1,000, a 

rate not seen since the 1980s. OACT projects that 

an increasing share of DI recipients will be in their 

60s, a prediction clearly at odds with the evidence 

above that DI enrollment is increasing more rapidly among younger age groups. Indeed, given the 

absence of 65- and 66-year-old DI recipients in the 

late 1980s and throughout the 1990s, the increase 

61 Only DI recipients born from January 1938 through October 1938 would have converted to retired worker benefits in 2003 

because the full retirement age for the group had increased by two 

months to 65 years and two months. Similarly, only DI recipients 

born from November 1938 through August 1939 would have 

converted to retired worker benefits in 2004. In other words, from 

2003 through 2008, the size of the cohorts converting to retired 

worker benefits were about one-sixth smaller because of the policy 

change, thereby explaining the substantial increase in the exit rate 

from 2008 to 2009 per the figure.

in the FRA will lower the exit rate associated with 

the FRA by increasing the number of DI recipients.

A detailed exploration and discussion of the factors producing the increase in the projected rate at 

which DI recipients will convert to retired worker 

benefits is warranted, as it substantially affects 

OACT’s projections of DI enrollment. This forms 

the basis for the recommendation P-5 above.

Mortality. The mortality rate of DI recipients 

has declined steadily and rapidly in recent  years. 

The age-sex-adjusted mortality rate fell from 

4.70 percent in 1985 to 2.63 percent by 2010. This 

44  percent decline was substantially greater than 

for all non-elderly adults during the same period.62

To some extent, the decline in the mortality rate 

since 1985 reflects the increase in the share of female DI recipients whose mortality rates are much 

lower than those of comparably aged males. In 

1985, just 33 percent of DI recipients were women 

versus 47 percent by 2010.

62 The unadjusted change in the mortality rate was almost identical over this same period, falling from 4.88 percent in 1985 to 

2.80 percent by 2009 (a 43 percent decline).

Figure 39. DI Recipients Converting to Retired Worker Benefits (per 1000 recipients): 1985–2085

Source: Trustees Report, Figure V.C5.

0 

10 

20 

30 

40 

50 

60 

70 

1985 1995 2005 2015 2025 2035 2045 2055 2065 2075 2085 

Calendar Year

Conversions per 1000 DI recipients

Historical Projected
84 2011 Technical Panel on Assumptions and Methods

An even more important factor, however, is the 

shift in program-qualifying conditions. In the early 

1980s, the most common conditions among DI recipients were cancer and heart disorders. Following 

a liberalization of the program’s medical eligibility 

criteria in 1984, individuals with more subjective 

conditions could more easily qualify for the program, resulting in a steady shift to low-mortality 

conditions such as mental disorders and musculoskeletal conditions such as back pain.63 The shift is 

evident in Figure 40, which plots the award rate in 

selected years for the four most common diagnoses 

among DI recipients. The figure shows that award 

rates have risen only slightly since 1983 for cancer 

and heart conditions but dramatically for mental disorders and musculoskeletal conditions. The 

award rate for mental disorders in 2009 was three 

times greater than in 1983 (1.43 per 1,000 in 2009 

63 Rupp and Scott (1996) demonstrate that mortality rates vary 

substantially by diagnosis. DI recipients with mental disorders 

and musculoskeletal conditions as their qualifying conditions have 

much lower mortality rates than the average DI recipient while 

DI recipients with cancer and heart conditions have much higher 

mortality rates.

versus 0.48 per 1,000 in 1983)  while the rate for 

musculoskeletal conditions in 2009 was five times 

greater (2.00 versus 0.40).

As a result of steady changes in award rates, the 

DI program is to some extent “out of equilibrium” 

as the share of DI recipients with a mental disorder 

or musculoskeletal condition increases. For example and as shown in Figure 41, the share of DI recipients age 50 years or older who qualified because 

of a mental disorder or musculoskeletal condition 

has steadily risen from 45.7 to 58.4 percent since 

1996. A similar trend holds for DI recipients under 

age 50. The increase in the share of DI recipients 

with low-mortality conditions seems likely to continue in the years ahead, causing mortality rates for 

this group to decline more rapidly than for the general population. The Technical Panel recommends 

further investigation of the relationship between 

mortality and diagnosis, something that OACT 

does not explicitly consider at present. 

Figure  42 plots the age-sex-adjusted mortality 

rate of both male and female DI recipients since 

1985 and displays the Trustees’ projections of 

Figure 40. DI Awards by Diagnosis per 1,000 DI-Insured: 1983, 1989, 1999, 2009

Source: SSA, Annual Statistical Report on SSDI, various years. 

0.0 

0.5 

1.0 

1.5 

2.0 

2.5 

1983 1989 1999 2009 

DI awards per 1000 insured

Diagnosis category

Mental Musculoskeletal Circulatory Neoplasms Nervous Other
2011 Technical Panel on Assumptions and Methods 85

these rates as well as the Technical Panel’s recommendations through 2085. To facilitate interpretation of the changes over time, the figure presents 

the changes converted to a log scale so that a constant rate of decline in the mortality rate is linear.64

An examination of the data in Figure 42 reveals 

that, from 1985 to 2010, age-adjusted mortality 

rates among male DI recipients fell by an average 

2.20  percent per year versus an average annual 

decline of 2.46 percent for women.65 The Trustees 

project that the rates will continue to decline at a 

similar rate for both men and women during the 

next 10 years. More specifically, in each year during 

this period, the Trustees assume a 2.35 percent an64 The increase in the rates above in the late 1980s and early 1990s 

largely reflects the effects of the HIV/AIDS epidemic; DI recipients 

with HIV/AIDS had very high mortality rates. However, the introduction and diffusion of more effective drugs from 1995 to 1997 

induced a substantial reduction in mortality rates such that mortality rates for DI recipients declined steeply during this period.

65 The age-adjusted mortality rate for DI-recipient males fell from 

51.45 to 29.47 per 1,000 during this 25-year period versus a decline 

from 40.99 to 21.98 per 1,000 for DI-recipient females during the 

same period.

nual decline for male mortality rates and a 2.44 percent decline for female mortality rates. 

However, the assumed annual declines change 

abruptly beginning in 2021, so that from 2020 to 

2030, the average annual decline in the male and 

female mortality rates plummets to just 0.04 and 

0.26 percent, respectively. This substantial change 

in the assumed mortality rate trends may be seen in 

Figure 42. Beginning in 2031, the assumed mortality rates decline by an average of about 1.1 percent per year through 2050 and by about 1.0 percent per year thereafter, which is comparable to the 

decline assumed for the general population during 

the same period.

The assumption that mortality rates will essentially remain flat during the 10-year period from 

2020 to 2030 seems implausible given the ongoing increase in the share of DI recipients with lowmortality conditions such as mental disorders and 

back pain. Thus, the Technical Panel recommends 

(A-7) a more gradual change in the annual rate of 

decline in the mortality rate after 2020, trending 

steadily from the average annual decline assumed 

Figure 41. Percent of DI Recipients Age 50 years and Older with Mental Disorder or Musculoskeletal 

Condition: 1996–2009

Source: SSA, Annual Statistical Report on SSDI, various years. 

40% 

45% 

50% 

55% 

60% 

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 

Percent of DI recipients
86 2011 Technical Panel on Assumptions and Methods

from 2010 to 2020 (2.35  percent for men and 

2.44 percent for women) to the average annual decline assumed after 2030.66 With this revision, projected mortality rates would be a constant 15.7 percent lower for men from 2030 through 2085 and a 

constant 14.3 percent lower for women during the 

same period. The corresponding reductions would 

be somewhat smaller in 2021 through 2029. For example, in 2025, the mortality rates would be lower 

for men by 9.7 percent and for women by 9.0 percent.

Recovery. The third channel through which DI 

recipients exit the program is recovery, which may 

occur if the DI recipient returns to the workforce 

and his or her earnings exceed the substantial 

gainful activity level set by SSA or if SSA conducts 

a Continuing Disability Review (CDR) and deter66 Thus, for example, the assumed male age-adjusted DI recipient 

mortality rate would fall by 2.35 percent in 2020 (from its 2019 

value), 2.24 percent in 2021 (from its 2020 value), 2.14 percent in 

2022 (from its 2021 value), and so forth, until falling by 1.27 percent in 2030 from its 2029 value. The assumed reduction in 2031 

(of 1.17 percent from the 2030 value) and in all subsequent years 

would remain unchanged.

mines that the recipient’s condition has improved 

to a level that he or she no longer meets the program’s medical eligibility criteria.67 Returns to the 

workforce are likely to increase in response to improving economic conditions while the number of 

CDRs conducted by SSA will largely determine involuntary medical recovery exits.68

Figure  43 presents the age-sex-adjusted recovery rate for the DI program from 1985 through 

2009 and the Trustees’ projections of the rate from 

67 In addition to liberalizing the medical eligibility criteria for the 

DI program, the 1984 changes described above made it substantially more difficult for SSA to use CDRs to terminate benefits for 

DI recipients. Before the changes, the person conducting the CDR 

asked, Does this recipient meet the program’s medical eligibility 

criteria? After 1984, the person conducting the CDR also had to 

demonstrate that the condition that made the person eligible for 

DI had improved. If, for example, the initial decision was clearly 

incorrect such that the person could engage in substantial gainful 

activity, but the condition had not improved, then SSA could not 

use the CDR to terminate benefits. 

68 We focus on medical CDRs rather than on CDR mailings given 

that the former are much more likely to result in program exit. 

The mailings sent to DI recipients ask questions such as, Has your 

condition improved? Perhaps not surprisingly, a very small share 

leads to benefit termination.

Figure 42. Log (Age/Sex-adjusted Mortality Rate) for Male and Female DI Recipients, 1985–2085: Current 

Trustees Assumption versus Technical Panel Recommendation

Source: Office of the Chief Actuary, Social Security Administration, 2011; Panel calculations.

0.90 

1.00 

1.10 

1.20 

1.30 

1.40 

1.50 

1.60 

1.70 

1.80 

1985 1995 2005 2015 2025 2035 2045 2055 2065 2075 2085 

Historical Projected 

Log (age-sex adjusted mortality rate)

Men-Trustees assumption

Men-Recommended

Women-Trustees assumption

Women-Recommended
2011 Technical Panel on Assumptions and Methods 87

2010 through 2085.69 The recovery rate was particularly high in 1997, exceeding 2.1  percent, and 

resulted from a federal policy change (part of the 

1996 welfare reform law) that terminated benefits 

for tens of thousands of DI recipients who previously qualified for the program because of drug or 

alcohol addiction. Excluding the 1997 data, the average recovery rate from 1985 through 2009 is 9.9 

per 1,000 DI recipients. In a typical year, approximately 1 percent of DI recipients exit the program 

because they voluntarily return to the workforce or 

SSA determines that their condition has improved 

to a level that no longer meets DI’s medical eligibility criteria.

An examination of the data in Figure 43 reveals 

some striking trends in the recovery rate. For example, from 1993 to 2000, the rate steadily increased 

from 7.4 to 13.4 per 1,000 DI recipients. Given the 

69 The data for Figure 43 and the following section on recovery 

rates are based on the 2010 Trustees assumptions and were presented to the Panel on January 28, 2011, and transmitted to the 

Panel on May 27, 2011. Changes in the assumed recovery rate from 

2010 to 2011 assumptions were very small.

discussion above, the increase was likely linked 

somewhat to improving economic conditions, as 

the unemployment rate fell throughout the period. 

However, the trends in Figure  44 demonstrate 

that changes in the number of CDRs also played 

an important role. From 1993 to 2000, the share 

of DI recipients receiving a medical CDR increased 

from 0.1 to 6.2 percent. Interestingly, both trends 

reversed in the next several  years, with the share 

receiving a medical CDR falling to just 1.3 percent 

in 2009 and the fraction exiting due to recovery 

falling by 50 percent during the same period, from 

13.4 per 1,000 in 2000 to 6.7 per 1,000 in 2009. 

It therefore seems that the rate at which medical 

CDRs are performed is a significant determinant of 

the recovery rate.

The data in Figure  43 reveal that the Trustees 

project a substantial increase in the recovery rate in 

the next several years. For example, from 2009 to 

2015, the Trustees project an increase from 6.7 to 

11.4 per 1,000 DI recipients. The figures then fluctuate somewhat during the next several  years before settling into a long-run rate of 10.9 per 1,000 

Figure 43. DI Recovery Rate (per 1,000 DI recipients): 1985–2085

Source: Office of the Chief Actuary, Social Security Administration. Data presented to Technical Panel on January 28, 2011 and transmitted to the Technical 

Panel May 27, 2011.

Historical Projected 

0 

5 

10 

15 

20 

25 

1985 1995 2005 2015 2025 2035 2045 2055 2065 2075 2085 

Medical recoveries per 1000 recipients

Calendar Year
88 2011 Technical Panel on Assumptions and Methods

DI recipients, with the long-run low- and high-cost 

values at 13.2 and 8.7 per 1,000, respectively (In 

2011, the intermediate value is 10.7 with the lowand high-cost range at 12.9 and 8.5). 

The intermediate-cost projection for the long-run 

recovery rate is substantially greater than the average recovery rate in recent years and represents a 

sharp departure from the trends in Figure 43. The 

explanation is that SSA’s CDRs are currently at temporarily low levels (page 128 of the 2010 Trustees 

Report) and will soon return to higher levels. 

Given the recent trends in DI recipients’ recovery 

rates, the assumption of a sharp increase sustained 

over the long term seems highly optimistic and rests 

on a substantial increase in SSA’s ability to process 

more CDRs while garnering an increasing share 

of the federal government’s resources. But, given 

that unprecedented numbers of DI applications are 

straining SSA’s resources amid backlogged DI decisions and increasing Baby Boomer claims for retired 

worker benefits, the assumption may not come to 

pass. In addition, the likelihood of large spending 

cuts throughout most of the federal government 

puts this assumption in further jeopardy.70

Analysis of the data in Figures 43 and 44 forms 

the basis for the Technical Panel’s recommendation 

A-8, which is a lower assumed recovery rate over the 

short, medium, and long terms. The recommendation is for an almost 20  percent reduction in the 

intermediate-case assumption from the 2011 assumption of 10.7 to 8.7 per 1,000. Somewhat lower 

than the average from 1985 to 2009, the recommendation reflects the trend’s steady decline during 

the past decade, yet the rate is substantially greater 

than its recent level. The Technical Panel also recommends a significantly larger gap between the intermediate-cost projection and both the high- and lowcost projections given the uncertainty surrounding 

the resources allocated for CDRs; the Technical 

Panel calls for high- and low-cost recovery rates of 

6.0 and 11.4 (from 8.5 and 12.9 in the 2011assumptions) per 1,000 DI recipients, respectively.

70 It is worth noting that funds invested in CDRs yield a high “bang 

for the buck,” with estimates suggesting that $1 spent on CDRs 

yields more than $10 in reduced program outlays.

Figure 44. Percentage of DI Recipients Receiving Medical Continuing Disability Review : 1993–2009

Source: Annual Report of Continuing Disability Reviews, Fiscal Year 2009, Social Security Administration, 2010.

0% 

1% 

2% 

3% 

4% 

5% 

6% 

7% 

8% 

Calendar Year 

1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
2011 Technical Panel on Assumptions and Methods 89

Conclusion

The Technical Panel’s three assumption recommendations will increase the projected size of the 

DI program. Given the magnitude of the recommended changes, the cumulative effect on long-run 

DI enrollment is substantial. From 1989 to 2010, 

the fraction of adults age 25 to 64  years receiving 

DI benefits increased from 2.3 to 4.7  percent. The 

Trustees assume the share will increase to just 

4.9  percent by 2032. Consistent with that projection, a slowdown is likely given that the aging of the 

Baby Boom generation has to some extent “run its 

course” with respect to its effect on DI enrollment 

rates, especially as the fraction of women insured 

for DI will not increase as rapidly in the years ahead. 

However, recent research (Autor and Duggan 

2006; Duggan and Imberman 2009; von Wachter 

et al. 2011; Autor and Duggan 2010)  shows that 

many more forces have driven the rapid rise in DI 

enrollment during the past two decades and will 

likely affect it in the years ahead. For example, the 

rise in wage inequality along with the progressive 

benefit formula used by SSA to calculate monthly 

DI benefits has led to an increase in “replacement 

rates” (the ratio of potential benefits to potential 

earnings) for a large share of U.S. workers. Similarly, rising unemployment can induce large numbers 

of individuals, who would choose to work in better 

times, to withdraw from the labor force and apply 

for the DI program. Furthermore, the reduction in 

the generosity of retired worker benefits as a consequence of the 1983 Social Security Amendments 

has increased the relative attractiveness of applying 

for DI benefits.

The most important factor influencing growth of 

the DI program, however, is the change in its medical 

eligibility criteria. DI is now a realistic option for many 

individuals with subjective conditions such as mental 

disorders and back pain. Whether and to what extent 

the criteria (and those used for CDRs) will change in 

the years ahead represents the primary source of uncertainty about long-run program enrollment.

There are, however, many other important sources of uncertainty about the long-run size of the 

program. For example, whether and to what extent 

job opportunities will improve, especially for lowerskilled workers, will have a first-order impact on the 

number of individuals applying for DI. In addition, 

improvements in medical care will increase life expectancy for individuals with cancer, heart conditions, and other conditions common among DI recipients. While the health of non-elderly adults has 

improved substantially according to virtually every 

measure, the recent rise in obesity (and any further 

increases in obesity)  could increase the demand 

for DI benefits. The new health reform law may increase the number of individuals who “retire early,” 

perhaps leading to growth in the number applying 

for DI benefits. 

Finally, further reductions in the generosity of retired worker benefits resulting from the 1983 Social 

Security Amendments imply that, for anyone born 

in 1960 or later, DI benefits will be 43 percent more 

generous than retired worker benefits claimed at 

the early retirement age of 62 (the most common 

age for claiming retired worker benefits). It is reasonable to think that, with further increases in DI 

enrollment, the stigma of applying for the program 

will decline such that a much larger number of individuals will apply in the future.

Given all of these factors, the uncertainty about 

the long-run size of the DI program is substantial. 

In recommendation P-5, the Technical Panel suggests that OACT provide more discussion of the 

economic, programmatic, and demographic factors 

that influence DI enrollment. Trends in incidence 

rates, termination rates, and related variables 

strongly suggest the Trustees’ long-run assumptions significantly understate the DI program’s future size.

2011 Technical Panel on Assumptions and Methods 91

Chapter 3: Economic Assumptions and Methods

3.1 Labor Force Participation Rate

Method Recommendation M-11. Consistent with Recommendation P-1, the Technical Panel recommends 

characterizing labor force participation rates as a 

basic assumption with a meaningful range of uncertainty. Labor force participation rates should also 

be part of the formal sensitivity analyses currently 

presented in Appendix D.

Assumption Recommendation A-9. The Technical Panel recommends increasing the assumed labor force 

participation rates with intermediate values of 75.0 

for men and 61.9 percent for women in 2085; these 

rates are higher than the currently assumed values 

of 72.9 percent for men and 60.8 percent for women. Together, the recommended values would raise 

the age-sex-adjusted labor force participation rate 

from 66.6 to 68.2 percent. The Technical Panel also 

recommends a substantial increase in the range of 

uncertainty about labor force participation, with 

low- and high-cost age-sex-adjusted participation 

rates of, respectively, 70.3 and 64.8 percent in 2085. 

Method Recommendation M-12. The Technical Panel 

recommends moving toward a heuristic life-cycle 

approach for projecting labor force participation by 

age and sex. Ultimately, labor force participation 

should be driven by life-cycle–specific labor supply measures such as typical age of first entry, percentage of the working-age population in the labor 

force, age of primary job exit, and fraction of the retired population still working. The Technical Panel’s 

recommended intermediate-, low-, and high-cost 

values above are based on consideration of labor 

force participation across eight age/sex groups and 

thus represent a move in the desired direction.

The Current Labor Force Participation Model

The 2003 and 2007 Technical Panels recommended a review and restructuring of the model used to 

project the labor force participation assumptions 

used in the Trustees Report. We reiterate the need 

for fundamental change. Our suggestions might be 

considered a refinement of our earlier recommendations. We acknowledge that the philosophy behind 

the current approach has some merit, but believe 

that the fundamentally time-series based modeling 

strategy fails to generate meaningful projections of 

either future labor force participation rates of the 

uncertainty about these projections. 

In the ideal process of time-series model development, the process identifies all relevant causal 

(or independent)  variables affecting the variable 

of interest (the dependent variable) and then uses 

historical data to estimate the relationship between 

them. The estimated model then generates forecasts for the dependent variable by substituting expected future values for the independent variables. 

The current labor force participation model begins 

with this ideal framework, but its failure to properly distinguish causation from correlation leads to 

an inappropriate level of confidence about how well 

the model explains historical experience. 

Any discussion of the shortcomings of the current labor force participation model should be preceded by a description of the model’s strong points. 

In its first phase, the “model” is a collection of 153 

separate time-series equations, each for a particular demographic group characterized by some 

combination of age, sex, marital status, and pres-
92 2011 Technical Panel on Assumptions and Methods

ence/absence of children under age 6.71 This initial 

breakdown is important because the various demographic groups are the first-order determinants 

of labor force participation. Thus, disaggregation 

of the population into 153 groups introduces the 

most important independent variables and allows 

the key explanatory variables to have different effects on each of these different groups. 

In its second phase, the labor force participation 

model subjects each of the 153 groups to the following questions: Is there a trend in the labor force 

participation rate of that group? If so, does some 

other set of independent variables explain the 

trend? If the answer is “no trend” or “explainable 

trend,” then the model is deemed appropriate for 

the given group. More often than not, the conclusion is simply “no trend” and that the result is flat 

labor force participation rates. Yet, the conclusion 

often depends on the exact time period chosen and 

therefore may miss emerging trends. 

In addition, in the second phase of the modeling 

process, OACT introduces into the projections potentially serious errors and miscommunication. For 

example, the key explanatory variable in the equation for labor force participation of males age 62 

is the labor force participation rate of females age 

60. Why? Research has shown that couples tend to 

retire together. However, that does not mean that 

changes in female labor force participation cause

changes in male labor force participation; it means 

that the changes are correlated. In the current 

framework, causality leads to seriously flawed conclusions. Since the mid-1990s,the (cohort-driven) 

increase in labor force participation of females age 

60 has been used to “explain” the increase in labor 

force participation of males age 62 during the same 

period. Applying the “explained trend” criteria suggests that the problem has been solved, when it 

more accurately increases false confidence. 

In this case, the current approach leads to predictions that are probably biased and, at the very least, 

highly susceptible to great uncertainty. The labor 

71 The 153 groups are constructed as follows: age groups include 

16 to 17 years (i.e., 16–17), 18–19, 20–24, 25–29, 30–34, 35–39, 

40–44, 45–49, 50–54, 55, 56, ... 99, 100, and over. For age groups 

between 20 and 54, male and female labor force participation rates 

(LFPR) are further disaggregated by marital status, categories of 

which include never married, married with spouse present, and 

married with spouse absent (which includes separated, widowed, 

and divorced). Female LFPRs disaggregated by age (between 20 and 

44) and by marital status are further disaggregated by presence of 

own child. The groups for presence of own child are females with at 

least one child under age 6 and females without a child under age 6. 

Thus, there are 69 equations for males and 84 for females.

force participation rate of 60-year-old females has 

been rising for the last two decades. The cohort-level shifts in life-time participation that began with 

younger and middle-age women in the 1970s are 

now working their way through the age distribution. As those cohort effects are fully realized over 

the next few years, the current model projects that 

60-year-old female labor force participation rates 

will stabilize. When that occurs, the time-series 

equation for 62-year-old male labor force participation also predicts stabilized labor force participation rates (although, in this case, a few other effects 

continue the upward trend but at a greatly reduced 

pace; most important, the main driver has been 

neutralized in the projections). 

What are the real drivers of labor force participation of 62-year-old males? Why not build those into 

the model? The vast literature on determinants of 

retirement from life-time jobs indicates that many 

factors, such as the nature and generosity of public 

and private pensions, household wealth holdings, 

health of the worker and/or spouse, and availability of health insurance, all affect the retirement decision. It is not feasible to introduce these factors 

into a time-series econometric model estimated on 

a handful of data points. However, the factors can 

and should be an important part of the conversation about labor force participation projections, 

suggesting that a heuristic life-cycle analysis is indeed preferable.

A Heuristic Life-Cycle Approach

Labor force participation across age groups and 

over time may be portrayed visually by relying on 

at least two distinct approaches. The first approach 

looks at the life-cycle profile of labor force participation at various time points (Figures 45 and

46).72 The second approach looks at some measure 

of group-level participation rates over time (Figures  47 and 48).73 The two approaches require 

the simplification of decisions in order to limit the 

amount of information the reader must process, 

72 OACT provided the data used in this section, aggregated into 70 

age-sex groups (16–17, 18–19, 20–24, 25–29, 30–34, 35–39, 40–

44, 45–49, 50–54, and 55 to 80 and above by single years). Figures 

45 and 46 were generated by interpolating between midpoints of 

the groups under age 55. 

73 The measures in Figures 47 and 48 are age-adjusted; that 

is, the weights within each age group are fixed at their base year 

(2009) value both forward and backward in time. Age-adjusting (or 

age-sex-adjusting when aggregating over sex as well) is important 

because changes in the population distribution affect the group 

average even in the absence of any meaningful behavior changes.
2011 Technical Panel on Assumptions and Methods 93

but they also complement each other insofar as 

they suggest how best to simplify decisions. 

The life-cycle labor force participation profiles 

(Figures 45 and 46) clearly show the four phases 

of participation that are the focus of the heuristic analysis. The first phase encompasses schooling (age 16 to 24). The second phase covers prime 

working age (age 25 to 54). The third phase is early 

retirement (age 55 to 61), and the final phase is 

general retirement (age 62 and beyond). The two 

life-cycle profile figures show how participation differs dramatically across the four phases; the gaps 

between the two historical time points (1992 and 

2010)  demonstrate the changes across the four 

groups during the most recent two decades.

The age-adjusted labor force participation rates 

over time (Figures 47 and 48) provide significantly more information about trends, but at the cost 

of within-group detail. However, the complementarity between the two visual approaches is useful. 

The life-cycle profiles (Figures 45 and 46) indicate 

that any of the four age groups (schooling, primeage, early and general retirement) experienced the 

changes associated with each of the detailed groups 

(for example, participation rates fell for all ages 

in the schooling group and rose for all ages in the 

general retirement group). In addition, the trends 

in age-adjusted participation (Figures  47 and

48) show that the choice of 1992 as a base year for 

the heuristic analysis is appropriate because that is 

when significant changes in (especially) young and 

old participation rates began to emerge.

In an important connection between the heuristic approach suggested here and the current timeseries econometric model, the latter tries to explain 

the changes in labor force participation at detailed 

ages and then use the explanations as the basis for 

its projections. From the perspective of the life-cycle profiles (Figures 45 and 46), the current model 

explains the vertical distances at any given age. 

Clearly, dramatically different forces act on different groups; moreover, there are several ways to rationalize what amounts to a handful of data points 

for each group. Worse yet, some groups (for example, early-retiree males) registered little change 

between 1992 and 2010, but such an outcome does 

Figure 45. Male Labor Force Participation by Age: 1992, 2010, Trustees Projection and Technical Panel 

Recommendation for 2085

Source: Office of the Chief Actuary, Social Security Administration, 2011; Panel calculations.

0 

10 

20 

30 

40 

50 

60 

70 

80 

90 

100 

0 

10 

20 

30 

40 

50 

60 

70 

80 

90 

100 

16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60 62 64 66 68 70 72 74 76 78 80 

Percent of noninstitutional population

1992 (Actual)

2010 (Actual)

Trustees intermediate in 2085 

(projected)

Technical panel intermediate in 

2085 (projected)

Age
94 2011 Technical Panel on Assumptions and Methods

not mean that important economic factors have 

not affected labor force participation behavior. It 

simply means that those forces have canceled out 

one another in the recent past and that the absence 

of recent trends is an unacceptable  basis for predicting no change in the future. Current economic 

pressures and policy changes will likely produce 

significant impacts on the early retirement group 

in the coming years such that expected behavioral 

reactions must be built into the projections.

Alternative Scenarios

Based on the heuristic approach, the Technical 

Panel proposes labor force participation rates that 

are generally equal to or higher than those in the 

Trustees Report’s intermediate projections. The 

proposed values are based on consideration of recent trends and incorporate expectations about the 

economic and policy factors known to affect the decision to work. Obviously, those trends and factors 

differ across the four age groups, and some of the 

expectations about influences and/or behavioral reactions are uncertain. The expectations and uncertainty are quantified here in simple ways by extending/reversing trends and for various periods.

School-age males and females (age 24 and younger)  have experienced dramatic reductions in labor 

force participation in the past two decades. Some of 

the decrease is attributable to higher rates of school 

attendance, but participation has also fallen for 

those not attending school. Another factor at work 

is a significant cyclical component as the steady erosion in labor force participation between the early 

1990s and 2007 became a precipitous drop between 

2007 and 2010. The Trustees Report’s intermediate 

projection incorporates some recovery for young 

males and females (Figures  47 and 48), but not 

back to 2007 levels. The Technical Panel’s intermediate projection assumes more recovery  – back to 

about 2004 levels – based on the belief that significant economic pressures on young people and their 

parents will lead to increased work effort. The range 

of uncertainty extends from even more recovery 

(back to about 2001 levels, which is at the end of 

the second most recent recession) to absolutely no 

change from the new lows observed in 2010. 

Figure 46. Female Labor Force Participation by Age: 1992, 2010, Trustees Projection and Technical Panel 

Recommendation for 2085

Source: Office of the Chief Actuary, Social Security Administration, 2011; Panel calculations.

0 

10 

20 

30 

40 

50 

60 

70 

80 

90 

100 

0 

10 

20 

30 

40 

50 

60 

70 

80 

90 

100 

16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60 62 64 66 68 70 72 74 76 78 80 

Percent of noninstitutional population

1992 (Actual)

2010 (Actual)

Trustees intermediate in 2085 

(projected)

Technical panel intermediate in 

2085 (projected)

Age
2011 Technical Panel on Assumptions and Methods 95

Labor force participation rates among primeage males and females (age 25 to 54)  differ in recent  years but are nevertheless related because 

females have substituted for males as primary 

breadwinners in some households. The Technical 

Panel’s proposed intermediate levels are noticeably 

higher for males and slightly higher for females. 

The levels reflect more recovery from the recent recession as participation rates for males age 25 to 

54 plummeted between 2007 and 2010, whereas 

the current projections show only partial recovery. Although increased disability prevalence and 

health care reform may exert downward pressure 

on future participation, a return to and maintenance of the 2007 labor force participation rate is a 

reasonable intermediate trajectory given the effect 

of the business cycle, the economic pressures associated with lower income growth, and the collapse 

of housing prices. The range of uncertainty for 

prime-age workers is given by a plausible high cost 

(recent declines in participation continue for a few 

more years) and low cost (not only does participation return to 2007 levels, but some of the ground 

lost between 1992 and 2007 is regained) values.

Early retirees are a crucial group to consider when 

analyzing Social Security and other aging-related 

policy questions. Participation rates among 55- to 

61-year-old males have remained stable for the past 

20 years while participation rates among females in 

the same age group have increased dramatically. 

The Technical Panel believes that both trends will 

change. Economic forces and policy shifts are likely 

to cause more males and females to delay exit from 

the labor force at young ages, but the cohort effect that has raised female participation is likely to 

moderate.

Despite little in the way of discernible patterns in 

labor force participation among early-retiree males 

even as cohort effects continue to drive the upward 

trend for females, the Technical Panel believes that 

it is reasonable to raise the intermediate projections 

above current values. Not surprisingly, it is the intermediate projections for early retirees that spell 

the largest divergence between the Technical Panel’s and Trustees’ projections, which are based on 

how the current economic and policy environment 

has changed and the likely effects of those changes 

on future behavior. Factors such as the collapse of 

Figure 47. Age-Adjusted Male Labor Force Participation Rates: Historical (1970–2010) and Projected 

(2011–2085), Trustees versus Technical Panel

Source: Office of the Chief Actuary, Social Security Administration, 2011; Panel calculations.

0.0 

10.0 

20.0 

30.0 

40.0 

50.0 

60.0 

70.0 

80.0 

90.0 

100.0 

0 

10 

20 

30 

40 

50 

60 

70 

80 

90 

100 

1970 1980 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 

Ages 25-54 

Ages 55-61 

Ages 16-24 

Ages 62 and older 

Historical Projected 

Labor force participation rate

Solid black line 

represents Trustees 

intermediate 

assumptions
96 2011 Technical Panel on Assumptions and Methods

housing prices, changes in private sector pensions, 

cost pressures on state and local retirement plans, 

decreased generosity of Social Security because of 

the rising FRA, and increasing health care costs all 

point to longer work lives. It is also not surprising – 

for the same reasons – that the uncertainty ranges 

for early-retiree males are particularly wide.

The time-series approach to analyzing labor force 

participation obviously does not capture the effects 

on behavior that have not yet been realized. The 

ideal approach would be to look at retirement behavior in micro-level panel data and consider how 

the various factors above will likely affect future 

cohorts of retirees.74 Discerning and quantifying 

the factors is difficult, suggesting the advisability 

of another approach to tracking changes in retirement expectations over time. For example, data 

from the Health and Retirement Study show that 

the period from 1992 to 2004 witnessed a roughly 10 percentage point increase in the fraction of 

74 One recent study finds, for example, that the recent increase 

in the Social Security full retirement age has had a significant 

effect on both labor force participation and benefit claiming. See 

Giovanni Mastrobuoni (2009).

51- to 54-year-olds who expected to be working 

full-time at age 65 (National Institutes of Health 

2010). In addition, a 2010 Pew Research Center 

study found that the recent economic recession 

has led many near-retirees to delay their expected 

retirement; 60 percent of working people age 51 to 

60 said that they are likely to delay retirement in 

response to recent economic events (Pew Research 

Center 2010). The evidence points to the types of 

reductions in early retirement that underlie the 

Technical Panel’s alternative projections.

The Technical Panel generally agrees with the 

Trustees’ projections for the general retirement 

group (age 62 and older), but it expects slightly 

greater increases in labor force participation for 

younger members of the group. As with the early 

retirees, the chief factor is economic reality. People 

exit the labor force because they have to (for health 

reasons) or are able to do so. For two decades, economic reality has been affecting the participation 

of would-be retirees and is likely to continue to do 

so (or to intensify) in the coming years. Again, as 

with the early-retiree group, the Technical Panel 

acknowledges the tremendous uncertainty about 

Figure 48. Age-Adjusted Female Labor Force Participation Rates: Historical (1970–2010) and Projected 

(2011–2085), Trustees versus Technical Panel

Source: Office of the Chief Actuary, Social Security Administration, 2011; Panel calculations.

0.0 

10.0 

20.0 

30.0 

40.0 

50.0 

60.0 

70.0 

80.0 

90.0 

100.0 

0 

10 

20 

30 

40 

50 

60 

70 

80 

90 

100 

1970 1980 1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 

Ages 25-54 

Ages 55-61 

Ages 16-24 

Ages 62 and older 

Historical Projected 

Labor force participation rate

Solid black line 

represents Trustees 

intermediate 

assumptions
2011 Technical Panel on Assumptions and Methods 97

post-retirement labor force participation, underscoring the importance of constantly monitoring, 

reviewing, and evaluating participation from a heuristic perspective. If the Technical Panel is correct 

and labor force participation is higher than specified in the Trustees Report, a higher level of labor 

force participation will improve the trajectory of 

Social Security finances and alleviate some of the 

need for painful benefit cuts or tax increases. 

3.2 Real Wage Growth Rate

To project future income and cost rates, the Trustees must combine assumptions about the number 

of workers with assumptions about the wages those 

workers will earn and thus the benefits they will receive. The methodology used in the Trustees Report 

to project real wage growth begins with the productivity growth rate and sequentially considers steps 

that link productivity growth to real wage growth.

Productivity is defined as the ratio of real GDP to 

total hours worked in the economy as a whole. The 

growth rate of productivity is a major determinant 

of the economy’s ability to sustain a higher standard of living and, similarly, Social Security’s ability 

to generate revenue to support benefit payments. 

The rate of productivity growth is a chief determinant of the rate of growth of average real annual 

earnings per employed person. The relationship between productivity and the real wage is expressed 

as follows:

where Earnings are the wage, salary, and proprietors’ income as reported in the National Income 

and Product Accounts (NIPA); CPI is the Consumer Price Index for Urban Wage Earners and Clerical Workers (CPI-W) as reported by the Bureau of 

Labor Statistics (BLS); Employment refers to total 

employment in all sectors of the economy; PGDP is 

the implicit price deflator for gross domestic product; Compensation is total labor compensation as 

reported in NIPA; and Hours are total hours worked 

in the economy as tracked by BLS.

The left-hand side of the equation is average real 

earnings per employed person, or the real wage. The 

first term on the right-hand side is productivity. 

The four terms that post-multiply productivity are 

referred to as the “linkages” between productivity 

and the real wage. They are, in order, the compensation share of GDP, the earnings ratio to compensation, average hours worked, and the ratio of the 

GDP price deflator to the CPI.

As the equation is multiplicative in levels, the 

growth rate of the real wage  – the input to the 

OACT model  – is equal to the sum of the growth 

rates of the five terms on the right-hand side of the 

equation. OACT’s methodology is to make assumptions about each growth rate separately in order to 

derive the assumed growth rate of real wages. For 

example, the 2011 Trustees Report (Table V.B1) arrived at the growth rates depicted in Table 14.

This section  discusses each of the assumptions 

that links productivity and the real wage. The following sections discuss three other economic assumptions – the unemployment rate, the real interest rate, and the rate of inflation.

Earnings Hours PGDP

Compensation Employment CPI

* *

Earnings/CPI GDP/PGDP Compensation

Employment Hours GDP = * *

Table 14. Real Wage Assumptions in Trustees Report: 2011

Scenario Real Wage Productivity 

Growth

Compensation ShareEarnings 

Ratio

Average 

Hours

Price Differential

Low-Cost 1.8 2.0 0.0 0.0 0.1 -0.3

IntermediateCost 1.2 1.7 0.0 -0.1 0.0 -0.4

High-Cost 0.6 1.4 0.0 -0.2 -0.1 -0.5
98 2011 Technical Panel on Assumptions and Methods

3.2.1 Productivity

Assumption Recommendation A-10. The Technical Panel recommends retaining the productivity 

growth rate of 1.7 percent per year assumed in the 

2011 Trustees Report. The Technical Panel also recommends retaining the currently assumed low- and 

high-cost values of 2.0 and 1.4 percent, respectively.

This recommendation matches the recommendations of the past two Technical Panels (2003, 

2007)  and keeps the productivity growth rate assumptions at the same levels since the 2006 Trustees Report. The concept of productivity used by the 

Trustees pertains to the entire economy, whereas 

the measure of productivity most commonly discussed in the academic and business communities 

pertains only to the non-farm business sector. The 

latter excludes the agricultural sector, along with 

governments, households, and non-profits. The 

non-farm business sector is the largest sector of the 

economy, and its productivity growth is typically 

higher by a few tenths of a percentage point than 

productivity growth in the economy as a whole. The 

documentation of the differences across sectors 

provided by OACT is sound and contains a detailed 

explanation of the assumptions for each component (OACT 2010).

Figure 49 presents the time-series of productivity growth rates since 1960, with the dashed line 

showing annual values and the solid line showing 

a five-year moving average of annual values. The 

intermediate assumption of 1.7 percent is close to 

the annual average productivity growth of the last 

40 years as shown in the figure.

The five-year moving average reached its lowest 

point in 1980, during a period that extended from 

1973 to 1995 and that economists regarded as a 

productivity slowdown. The slowdown is bracketed 

by the first oil shock of the 1970s and the emergence of the technology boom in the mid-1990s. 

During the slowdown, productivity growth averaged 1.3 percent per year. The high-cost scenario is 

analogous to assuming that, in the future, productivity growth will only slightly exceed that achieved 

between 1973 and 1995.

Figure 49. Annual Productivity Growth and Five-Year Moving Average: 1960–2010

Source: Trustees Report, Table V.B1, 2011.

-2.0 

-1.0 

0.0 

1.0 

2.0 

3.0 

4.0 

5.0 

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 

Annual percent change

Year

Annual productivity growth

5 year moving average
2011 Technical Panel on Assumptions and Methods 99

The five-year moving average later peaked between 2000 and 2002 as the technology boom drew 

to a close. Productivity growth averaged 2.5  percent from 1996 to 2004 and 2.2 percent from 1996 

to 2010. The most important question facing productivity forecasters is whether the recent upturn 

in productivity will be sustained over the long term, 

boosting the rate assumed in long-range projections, such as those in the Trustees Report.

A standard explanation for the productivity 

slowdown between 1973 and 1995 is the employment shift from high-productivity manufacturing 

employment to lower-productivity service sector 

employment (Kozicki 1997). According to this explanation, the slowing of the employment shift has 

allowed the productivity growth rate to increase. 

Recent evidence on the links between demographics and productivity suggest that at least some of 

the time-series changes in productivity growth 

rates are attributable to the entry of the large cohort of young, unskilled Baby Boomers into the 

workforce during the 1970s and their subsequent 

evolution into a large, skilled cohort in the 1990s 

(Feyrer, 2007). It is likely that the secular increase 

in female labor force participation during the same 

period amplified these effects. Thus, productivity 

growth in the most recent period has been elevated 

temporarily by demographic factors and should not 

unduly influence the ultimate value assumed in the 

intermediate-cost projections.

3.2.2 Compensation Share of GDP

Assumption Recommendation A-11. The Technical 

Panel recommends retaining the intermediate assumption of a 0.0  percent annual growth rate for 

the compensation share of GDP. The Technical Panel 

further recommends introducing uncertainty about 

this parameter. Specifically, starting from a current 

value of 54.5  percent for the compensation ratio, 

the Technical Panel recommends low- and high-cost 

values of, respectively, 56 and 53 percent over the 

projection period. Growth rates of, respectively, 0.1 

and -0.1  percent per year for 25  years in the lowand high-cost scenarios would generate the suggested range in the compensation ratio.

The compensation share of GDP is the ratio of employee compensation (wage and salary accruals plus 

supplements to wages) to GDP. Table 15 shows the 

value of the ratio by decade since the 1950s.

The last four decades show a steady decline from 

the peak of 58.5 percent in the 1970s. Figure 50

shows the decline clearly, with both the series and 

its five-year moving average. Whether starting 

from the 1970s or 1980s, the rate of decline per decade through the most recent decade has been approximately 0.7 percentage point. The most recent 

value in 2010 is 54.5 percent.

Given the declines in the series, the assumption 

of a zero  percent projected growth rate should be 

justified not on the stability of the series historically, as in Trustees Reports and earlier Technical Panels, but rather on the basis of the presumption that 

the factors causing the decline will not continue. 

Compensation is just one component of personal 

income, which is itself a subset of gross domestic 

income (GDI). Figure  51 shows the components 

of GDI as a share of GDP. After compensation, the 

next largest component is the net operating surplus of private enterprises, which includes net interest to domestic industries, net business transfer 

payments, proprietors’ income, rental income, and 

corporate profits of domestic industries. The other 

three components are net taxes (defined here as 

taxes on production and imports plus the current 

surplus of government entities less subsidies), the 

consumption of fixed capital, and the statistical discrepancy between GDI and GDP. Figure 51 shows 

that, over the last four decades, the increase in the 

net operating surplus of private enterprises has 

more than offset the decrease in compensation. The 

shifts largely negate the jump in compensation relative to private enterprises that occurred between 

the 1960s and 1970s.

Table 15. Compensation Share of GDP, by Decade

1950–1959 1960–1969 1970–1979 1980–1989 1990–1999 2000–2010

54.9% 56.5% 58.5% 57.8% 56.8% 56.4%

Source: National Income and Product Accounts, Tables 1.1.5 and 2.1, June 24, 2011.
100 2011 Technical Panel on Assumptions and Methods

Table 16 shows the components of the net operating surplus of private enterprises by decade, presented as a percentage of GDP.

Every income component in the table  was the 

same or higher in the most recent decade than in 

the 1970s, when the compensation share peaked. 

That every component increased as the compensation ratio fell suggests that the shift in income was 

permanent. Net interest and business transfers 

have been on average higher since the 1970s than 

before the 1970s while proprietors’ income, rental 

income, and corporate profits are on average lower 

in the latest period versus the earlier period. It is 

conceivable that the overall downward trend will 

continue, with the compensation share continuing 

to fall toward its 1950s and 1960s values. It is also 

possible that the compensation share will stabilize 

at values seen in the more recent past.

To reflect those possibilities, the Technical Panel 

considers a range of 53 to 56 percent after 25 years 

as a reasonable projection, starting from a current 

value in 2010 of 54.5 percent. The range assumes 

growth rates of 0.1, 0.0, and -0.1 percent per year 

for 25  years in the low-, intermediate-, and highcost scenarios, respectively.

3.2.3 Earnings to Compensation Ratio

Assumption Recommendation A-12. The Technical 

Panel recommends setting the annual growth rate 

for the earnings to compensation ratio at 0.0 percent in the intermediate-cost scenario, an increase 

from the current assumption of -0.1  percent. The 

Technical Panel also recommends low- and highcost annual growth rates of, respectively, 0.1 and 

-0.1 percent per year, which yield an ultimate range 

for the earnings to compensation ratio of 77 to 

89 percent relative to a starting value of 83 percent. 

The adjustment for the effects of health care reform 

made in the 2010 Trustees Report (+0.1  percent 

per year) is reasonable and should be maintained, 

pending direct observation of the law’s impact 

in the coming  years. The Technical Panel’s recommendation of an intermediate-cost assumption of 

0.0 percent incorporates such adjustment.

Figure 50. Compensation Share of Gross Domestic Product: 1948–2010

Source: National Income and Product Accounts, Tables 1.1.5 and 2.1, June 24, 2011.

52% 

53% 

54% 

55% 

56% 

57% 

58% 

59% 

60% 

1948 1958 1968 1978 1988 1998 2008 

Percent of GDP

Compensation share of GDP

5-year moving average
2011 Technical Panel on Assumptions and Methods 101

Figure 51. Components of Gross Domestic Income as a Share of GDP: 1950s–2000s

Source: National Income and Product Accounts, Table 1.10, June 24, 2011.

54.9% 56.5% 58.5% 57.8% 56.9% 56.5% 

26.4% 24.9% 21.7% 22.1% 23.5% 24.4% 

7.7% 8.2% 7.8% 6.8% 7.1% 6.8% 

10.6% 10.2% 11.0% 12.3% 11.7% 12.4% 

0% 

10% 

20% 

30% 

40% 

50% 

60% 

70% 

80% 

90% 

100% 

1950s 1960s 1970s 1980s 1990s 2000s 

Percent of GDP

Statistical Discrepancy

Consumption of Fixed Capital

Net Taxes

Private Enterprises

Compensation

Table 16. Components of Net Operating Surplus of Private Enterprises, by Decade

Decade Net Interest Business

Transfers

Proprietors’ 

Income Rental Income Corporate Profits

2000–2010 6.1% 0.8% 8.1% 1.7% 7.7%

1990–1999 6.4% 0.7% 7.0% 1.8% 7.7%

1980–1989 8.1% 0.7% 6.0% 0.9% 6.5%

1970–1979 4.6% 0.5% 7.5% 1.5% 7.7%

1960–1969 2.6% 0.4% 8.9% 2.8% 10.2%

1950–1959 1.4% 0.3% 11.2% 3.2% 10.3%

Source: National Income and Product Accounts, Tables 1.10 and 1.1.5, June 24, 2011.
102 2011 Technical Panel on Assumptions and Methods

The earnings to compensation ratio is the ratio 

of total labor earnings, including wages and selfemployed income, to total labor compensation. 

Figure 52 shows the decline in the ratio over the 

last six decades.75 The decline was rapid in the three 

decades leading up to 1980, as employer contributions for pensions, government social insurance, 

and group health insurance increased. Figure  53

shows these components, as a share of total compensation, individually. Much of the initial growth 

and its subsequent persistence have been attributed to the tax advantages of fringe benefits relative 

to wages and salaries. Indeed, the sharp trend came 

to an end in the early 1980s, just as tax reform lowered marginal tax rates and reduced the incentive 

for firms and workers to shift compensation out of 

earnings.

As Figure  53 shows, employer contributions 

to pension plans stopped increasing in the early 

1980s, as many employers switched to defined 

contribution plans that may have required lower 

75 The earnings ratio as presented here includes proprietors’ 

income in both the numerator and denominator.

contributions. The generally positive growth of 

the stock market in the 1980s and 1990s, particularly as evidenced by the stock market bubble that 

emerged during the mid- to late 1990s, improved 

funding ratios in defined benefit pension plans, 

making it possible for employers sponsoring such 

plans to reduce their required contributions. In the 

wake of the bubble’s bursting and with stepped-up 

funding requirements under the Pension Protection 

Act of 2006, larger pension contributions will likely 

exert moderately downward pressure on the earnings ratio in the next few decades.

Employer contributions to government social 

insurance stabilized as a share of total compensation in the early 1980s as ad hoc increases in the 

Social Security maximum taxable earnings and the 

payroll tax rate gave way to the present configuration of tax rates and wage indexing under the 1983 

Social Security Amendments. In addition, much of 

the growth in total earnings over this period occurred above the Social Security maximum taxable 

earnings level, which tends to reduce the ratio of 

Figure 52. Earnings to Compensation Ratio: 1948–2010

Source: National Income and Product Accounts, Table 2.1, June 24, 2011.

80% 

82% 

84% 

86% 

88% 

90% 

92% 

94% 

96% 

98% 

100% 

1948 1958 1968 1978 1988 1998 2008 

Percent of total compensation
2011 Technical Panel on Assumptions and Methods 103

government contributions for social insurance as a 

share of total compensation.

With termination of the strongest tax incentives 

for shifting compensation out of earnings, the secular increase in health care costs relative to GDP 

has mechanically caused the tax-advantaged part 

of compensation to grow rapidly. At the same time, 

wage and salary growth has been tempered by the 

funding of health care through the employment 

contract. The only period that did not experience 

a decline in the earnings ratio was the boom years 

of the mid- to late 1990s. This temporary decline in 

the share of compensation contributed by employers to group health insurance is clear in Figure 53

as well. In addition to the weaker pension funding 

needs noted above, that period saw the initial diffusion of Health Maintenance Organizations (HMO), 

which succeeded briefly in arresting health care cost 

inflation. The sharp return to the upward trend in 

employer costs for group health insurance after the 

end of the technology boom indicates the temporary nature of the HMO as an innovation to control 

health care costs. However, as health expenditures 

continue to increase relative to GDP, there will be 

greater financial incentives to develop market innovations that reduce health care costs and thus 

the share of compensation paid as fringe benefits 

rather than as earnings.

Trustees Reports issued before 2010 set the decline in the earnings ratio to a value of -0.2 percent 

per year, corresponding roughly to its average over 

the entire period in Figure 52. Combining the assumption that higher health care costs will lead to 

a greater focus on cost containment with the observation that the annual rate of decline slowed markedly after 1980, both the 2003 and 2007 Technical Panels recommended that the Trustees modify 

the assumption to a rate of decline of 0.1 percent 

per year or less. Earlier Technical Panels were particularly concerned about assumptions that would 

push the earnings ratio below 75  percent of compensation relative to its recent values, which are 

now about 83 percent.

The 2010 Trustees Report lowered the rate of decline in the earnings ratio to 0.1 percent per year, 

justifying the decision on the passage of the Patient 

Figure 53: Employer Contributions for Earnings Supplements: 1950–2009

Source: National Income and Product Accounts, Tables 2.1 and 7.8, June 24, 2011.

0% 

1% 

2% 

3% 

4% 

5% 

6% 

7% 

1950 1960 1970 1980 1990 2000 2010 

Percent of total compensation

Pensions

Social Insurance

Group Health
104 2011 Technical Panel on Assumptions and Methods

Protection and Affordable Care Act of 2010 (ACA). 

The law’s major provision regarding the earnings 

ratio is an excise tax on employer-sponsored group 

health insurance, which is to be phased in later in 

the current decade. With the excise tax initially designed to apply only to extremely generous health 

plans, the threshold for premiums subject to the 

tax grows with the overall rate of inflation, which 

is expected to lag behind the growth per capita in 

health care costs. Over time, the excise tax will 

affect more health plans and pressure firms and 

workers to shift compensation out of health insurance and into earnings. As a specific change to account for the ACA, the Technical Panel finds this 

adjustment for the ACA to be reasonable, at least as 

an initial step until evidence on the law’s impacts 

can be examined.

However, the above adjustment does not address 

the underlying change in the earnings ratio evident 

in Figure  52 based on factors unrelated to the 

ACA. The Technical Panel recommends a reduction 

in the rate of decline in the earnings ratio. In the intermediate-cost scenario, the rate of decline should 

be zero. For the low-cost scenario, the Technical 

Panel recommends that the earnings ratio should 

increase by 0.1 percent per year. For the high-cost 

scenario, the Technical Panel recommends that the 

earnings ratio should decrease by 0.1  percent per 

year. These assumptions generate a range of 77 to 

89 percent at the end of 75 years.

3.2.4 Hours Worked

Assumption Recommendation A-13. The Technical 

Panel recommends retaining the intermediate-cost 

assumption of 0.0  percent for the annual change 

in hours worked. For the low-cost scenario, the 

Technical Panel recommends a slight increase of 

0.05 percent per year in hours worked over the 75-

year period. Recognizing a greater risk of a decline 

in hours worked, the Technical Panel recommends a 

reduction in annual hours of -0.15 percent per year 

for the 75-year period in the high-cost scenario.

Figure 54 shows the time-series of annual percentage changes in average hours worked per week 

Figure 54. Average Hours Worked: Annual Percent Change, 1960–2010

Source: Social Security Trustees Report, Table V.B1, 2011.

-2.5 

-2.0 

-1.5 

-1.0 

-0.5 

0.0 

0.5 

1.0 

1.5 

1960 1970 1980 1990 2000 2010 

Annual percent change

Change in average hours worked

5-year moving average
2011 Technical Panel on Assumptions and Methods 105

by using a series from BLS corresponding to the entire economy. While the annual changes fluctuate 

considerably, the five-year moving average shows 

only one period in the 1990s with sustained positive 

values. The trend in the last five decades has been 

negative at an average annual rate of -0.25 percent. 

Over the past two decades, the average decline has 

been somewhat smaller.

As with other labor market outcomes, OACT has 

considered how changes in the composition of the 

labor force might affect both historical trends and 

future projections of hours worked. For example, 

“Workers with higher education tend to work more 

hours than their less-educated counterparts, and 

males and prime-age workers tend to work more 

hours than females, the very young, and the very 

old” (OACT 2010). The Technical Panel agrees with 

the above observation but draws conclusions that 

differ from those of the Office of the Chief Actuary, 

which notes:

For the future, the OCACT [Office of the 

Chief Actuary] still believes that there are 

factors that, by themselves, suggest that 

the annual rate of change in average hours 

worked will be negative. As in the past, the 

assumed steady increases in productivity 

will allow workers to gradually increase leisure time while still maintaining increases 

in weekly and annual earnings. Furthermore, the average projected changes in the 

education and age-sex distributions of the 

workforce are not expected to significantly 

affect the average annual growth rate in the 

AHW [Average Hours Worked] in the future. 

However, the OCACT also believes that the 

assumed future increases in life expectancy 

will raise labor force participation rates for 

older workers and may also raise AHW, holding other factors constant (OACT 2010).

The Technical Panel agrees with the first statement and with the assertion that continued productivity growth will have a weak, negative impact 

on hours worked. The Technical Panel also agrees 

with the claim that possible changes in the labor 

force’s educational and sex composition may have 

no further impact on hours worked. These factors 

justify an assumption of 0.0  percent change in 

hours worked in the intermediate-cost scenario.

The Technical Panel does not agree with the 

claims about the impact of either the changing age 

composition or changes by age in labor force participation. The main impact of older workers as an 

increasing percentage of the labor force is that average hours worked will decrease, as older workers 

will be more likely to work part-time during a given 

week or fewer weeks per year. Consistent with the 

Technical Panel’s recommendations regarding the 

labor supply of older workers, the Technical Panel 

recommends a slight increase in the magnitude of 

decline in average hours worked in the high-cost 

scenario to an annual rate of -0.15  percent. Further, the Technical Panel recommends a reduction 

in the increase in average hours worked in the lowcost scenario to a rate of 0.05 percent per year.

3.2.5 Price Differential

Assumption Recommendation A-14. The Technical 

Panel recommends reducing the magnitude of the 

intermediate-cost assumed GDP-CPI price differential to -0.2 percent per year, relative to the currently 

assumed -0.4 percent price differential. The Technical Panel also recommends low- and high-cost price 

differentials of -0.1 and -0.3 percent, respectively.

The final link between the productivity growth 

rate and real wage growth is the differential 

in growth rates between the GDP price deflator (PGDP)  and the CPI-W. In the formula above, 

PGDP scales productivity, and CPI-W scales the real 

wage. If CPI-W increases more rapidly than PGDP, 

real wages grow less rapidly than productivity. The 

differences between the price indexes come from 

two sources. First, PGDP covers the entire economy, whereas CPI-W pertains only to the bundle of 

goods and services consumed by urban wage earners and clerical workers. Second, construction of 

the two indexes rests on different methodological 

approaches.

The consequences of differences in coverage between the entire economy and consumption may be 

measured by comparing the GDP price deflator to 

the price deflator for the Personal Consumption Expenditures (PCE) component of GDP. Both use the 

same methodology as part of the National Income 

and Product Accounts collected by the Bureau of 

Economic Analysis. The second and third columns 

of Table  17 show the geometric average inflation 

rates by decade for the two indexes.

Table  17 shows that, in the 1950s and 1960s, 

the GDP deflator grew faster than the PCE deflator 
106 2011 Technical Panel on Assumptions and Methods

by 0.25 to 0.28 percentage points per year. In the 

1970s, 1980s, and 1990s, the pattern was reversed, 

with the PCE deflator growing faster than the GDP 

deflator by 0.04, 0.24, and 0.14 percentage points 

per year, respectively. Since 2000, the comparison 

flipped again, with growth in the GDP deflator exceeding growth in the PCE deflator by 0.08 percentage points per year. The comparisons show that, by 

itself, the difference in inflation between consumption and the rest of the economy is not systematically positive or negative.

The Bureau of Labor Statistics publishes the 

Consumer Price Index series monthly. The most 

comprehensive measure is CPI-U, which is representative of all urban consumers. Social Security 

indexes benefits to CPI-W, which covers a subset of 

urban wage earners and clerical workers. The differences between the two indexes are reflected in 

the weights applied to each consumption category, 

consistent with their importance to the respective 

populations of consumers. CPI-W places relatively 

more weight on energy and commodities and less 

on services. Over the past six decades, CPI-W has 

averaged 0.04  percentage points less growth per 

year than CPI-U.

The fourth column of Table 17 shows the average annual  percentage changes in CPI-W in each 

decade. With the exception of the 1950s, CPI-W 

inflation exceeded the inflation rate of the PCE deflator by an average 0.24  percentage points since 

2000 and by as much as 0.80 percentage points in 

the 1970s. A long line of studies has documented 

the reasons for the differences between the CPI and 

PCE deflator. The principal reasons are differences 

in formulas, weights, and scope (Bosworth 2010).

Periodically, the methods used to estimate each 

price index undergo revision. For the PCE deflator, 

the revisions are incorporated into the published 

index as the National Income and Product Accounts 

are systematically revised. The published CPI indexes are never revised because they are frequently the 

basis for contracts. Any improvements made to the 

series occur only prospectively. Instead, BLS formulated a research series for CPI-U beginning in 1999 

and has provided updates since then (Stewart and 

Reed 1999). The series, CPI-U-RS, shows what the 

CPI-U would have been since 1977 if the current 

methodology had been in place over the entire period. To obtain values for CPI-U-RS before 1977, a 

reasonable approach takes the ratio of CPI-U-RS to 

CPI-U in 1977 and multiplies earlier values of CPIU by that ratio. Given the similarity of CPI-U and 

CPI-W, a hypothetical CPI-W-RS series, whose annual changes are summarized in the fifth column of 

Table 17, is generated by multiplying CPI-W by the 

ratio of CPI-U-RS to CPI-U in each year.

For the last decade, the published series CPIW and the hypothetical research series CPI-W-RS 

have been identical (the 0.01 disparity in Table 17

reflects a rounding error). In the 1990s, however, 

annual inflation in the research series averaged 

0.32 percentage points lower than that in the published series. In earlier decades, the annual inflation 

in the research series averaged between 0.01 and 

0.70 percentage points below that in the published 

series. The final column of Table 17 shows the differences by decade in the GDP deflator and the CPIW-RS series. The differences in the most recent four 

decades were -0.15, -0.34, -0.12, and -0.13 percentage points. The differences in earlier decades were 

positive. Based on these differences, the Technical 

Panel recommends incorporating a price differential 

of -0.2 percentage points into the intermediate-cost 

scenario and retaining the 0.1 percentage point difTable 17. Comparison of Inflation for Different Price Indexes, by Decade

Decade GDP Deflator PCE Deflator CPI-W CPI-W-RS PGDP Minus 

CPI-W-RS

2000–2010 2.24 2.16 2.40 2.39 -0.15

1990–2000 2.07 2.21 2.73 2.41 -0.34

1980–1990 4.22 4.46 4.53 4.34 -0.12

1970–1980 6.98 7.02 7.82 7.12 -0.13

1960–1970 2.72 2.44 2.75 2.56 0.16

1950–1960 2.44 2.19 2.09 2.08 0.36
2011 Technical Panel on Assumptions and Methods 107

ferentials in the low- and high-cost scenarios relative to the intermediate scenario.

3.2.6 Real Wage Differential

Assumption Recommendation A-15. Taken together, the Technical Panel’s recommendations A-10 

through A-14 for productivity growth and the four 

linkages generate an intermediate real wage growth 

rate of 1.5 percent per year in years 25 through 75, 

with low- and high-cost values of, respectively, 2.05 

and 0.85 percent. Over the first 25 years, our recommendations also generate an intermediate real 

wage growth rate of 1.5 percent, but with low- and 

high-cost values of, respectively, 2.15 and 0.75 percent per year.

The recommendations for the real wage and its 

various components are summarized in Table 18.

3.3 Unemployment Rate

Assumption Recommendation A-16. The Technical 

Panel recommends retaining the assumed ultimate 

long-run unemployment rate of 5.5  percent from 

the 2011 Trustees Report. The Technical Panel also 

recommends retaining the low- and high-cost assumed unemployment rates of, respectively, 4.5 

and 6.5 percent.

Figure 55 shows the civilian unemployment rate 

over the last five decades, when it averaged 5.9 percent. Before the sharp rise in the unemployment 

rate during the recent recession, unemployment 

had been trending down from its peak in the early 

1980s, which was the last time the Federal Reserve 

intervened with sharply higher interest rates to 

curb inflation and inflationary expectations. Such 

interventions come at the cost of a dramatic increase in unemployment.

As with other labor market outcomes, it is sensible to filter out predictable co-movements of the 

unemployment rate with demographic factors such 

as the age-sex composition of the potential labor 

force. OACT’s documentation of its economic assumptions discusses the filtering procedure and 

notes that “[t]he aggregate civilian unemployment 

rate, adjusted for changes in the age-sex distribution of the labor force, averaged about 5.6 percent 

over the last four complete economic cycles from 

1973 to 2007”(OACT 2010). OACT’s adjustment 

strengthens the case for an intermediate assumption of 5.5 percent, assuming that the age-sex adjustments are carried forward into the projections.

3.4 Interest Rates

Assumption Recommendation A-17. The Technical 

Panel recommends reducing the assumed long-run 

real interest rate to 2.7  percent. The rate is lower 

than the 2.9 percent long-run real interest rate assumed in the 2011 Trustees Report and more in 

line with market-based forecasts derived from current yields on inflation-protected Treasury securities. The Technical Panel recommends retaining the 

Table 18. Technical Panel Recommendations for Real Wage Assumptions

Scenario Real Wage Productivity 

Growth

Compensation ShareEarnings 

Ratio

Average 

Hours

Price 

Differential

Years 1–25

Low-Cost 2.15 2.0 0.1 0.1 0.05 -0.1

Intermediate 1.50 1.7 0.0 0.0 0.0 -0.2

High-Cost 0.75 1.4 -0.1 -0.1 -0.15 -0.3

Years 25–75

Low-Cost 2.05 2.0 0.0 0.1 0.05 -0.1

Intermediate 1.50 1.7 0.0 0.0 0.0 -0.2

High-Cost 0.85 1.4 0.0 -0.1 -0.15 -0.3
108 2011 Technical Panel on Assumptions and Methods

low- and high-cost values of, respectively, 3.6 and 

2.1 percent for the real interest rate.

The interest rate credited to the special public 

debt obligations is equal to the average market yield 

on all marketable  fixed-rate Treasury securities 

that are not callable and that do not mature within 

the next four years. Figure 56 shows the historical interest rates, net of inflation, since 1960. The 

peak in Figure 56 for the 1980s reflects a period of 

extremely tight monetary policy, when the Federal 

Reserve intervened in money markets to reduce inflation and inflationary expectations. Since that episode, inflation expectations have fallen and, with 

them, real interest rates have continued to decline. 

All three subsequent recessions have been induced 

by asset price deflations rather than by the Federal 

Reserve’s implementation of contractionary monetary policy. Over the past two decades, the real 

interest rate has averaged 3.2 percent and declined 

fairly steadily until the price deflation associated 

with the 2008–2009 financial crisis caused real interest rates to jump.

An examination of current rates indicates that 

the rise in real interest rates was temporary; market expectations for future rates continue to remain below the historical average. Figure 57 shows 

the eight-year history of weekly yields on portfolios 

of Treasury Inflation-Protected Securities that are 

adjusted to preserve a constant maturity of 5, 7, 10, 

20, or 30  years. The yields are consistently below 

2.5 percent, except for the very short period of extreme deflationary concerns during the 2008–2009 

financial crisis.76

Table 19 presents the values for each of the portfolio yields for the week ending July 2, 2011.

Table 19. TIPS Yield Curve Using Constant-Maturity 

Portfolios

5-Year 7-Year 10-Year 20-Year 30-Year

-0.28% 0.26% 0.73% 1.46% 1.75%

76 Given that the TIPS market is smaller than the market for 

nominal Treasuries, the yields may already factor in an illiquidity 

premium. As such, they likely overstate the real interest rate based on 

the difference between nominal yields and inflation expectations.

Figure 55. Civilian Unemployment Rate: 1960-2010

Source: Social Security Trustees Report, Table V.B2, 2011.

0 

1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

1960 1970 1980 1990 2000 2010 

Percent of unemployed

Unemployment rate

5-year moving average
2011 Technical Panel on Assumptions and Methods 109

Each yield is equal to the geometric average annual interest rate over the years from the present 

to the portfolio’s maturity. We calculate the average 

annual interest rate that is expected to prevail between any two time points, T1

 and T2, by applying 

the following formula for r1,2:

Based on the formula, Table 20 presents the expected average annual interest rates over the full 

30-year period.

Table 20. Expected Average Annual Interest Rates 

Implied by TIPS Yield Curve

Years 

0–5

Years 

5–7

Years 

7–10

Years 

10–20

Years 

20–30

-0.28% 1.62% 1.84% 2.20% 2.33%

Market participants expect that real interest 

rates will remain around or below zero for about 

five years before reverting to levels consistent with 

the trend of the past two decades. To form the basis 

of its recommendation, the Technical Panel considers the market forecasts of future interest rates to 

be informative and therefore recommends an ultimate assumption no higher than 2.7 percent. The 

Technical Panel’s considerations may be formalized 

as the following recommendation:

Method Recommendation M-13. The Technical Panel 

reiterates the recommendation of the 2007 Technical Panel that the approach to determining real and 

nominal interest rates should place greater weight 

on the forward-looking information in recent Treasury yield curves.

Figure 56. Annual Trust Fund Real Interest Rates: 1960–2010

Source: Social Security Trustees Report, Table V.B2, 2011.

-4 

-2 

0 

2 

4 

6 

8 

10 

12 

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 

Real interest rate

Annual Trust Fund real interest rate

5-year moving average

(1 + r1, 2) = T2

-T1

T2

T1

(1 + r2)

(1 + r1

)
110 2011 Technical Panel on Assumptions and Methods

3.5 Inflation

Assumption Recommendation A-18. The Technical 

Panel recommends retaining CPI-W inflation at 

2.8 percent in the intermediate-cost scenario. The 

Technical Panel also recommends retaining the 

low- and high-cost values of, respectively, 1.8 and 

3.6 percent.

The recommended values for inflation are consistent with the historical evidence from the earlier 

two decades shown in Table 17 and Figure 58. The 

five-year moving average of the inflation rate has 

spent the last 20 years in the narrow range of 2 to 

3  percentage points per year. After the monetary 

contraction of the early 1980s that occurred in response to the particularly high inflation of the late 

1970s, the annual rate of inflation has not exceeded 

5 percent in any year.

Assumption Recommendation A-19. The Technical 

Panel recommends setting the nominal interest 

rate to 5.5  percent in the intermediate-cost scenario, based on a 2.8  percent inflation rate and a 

2.7  percent real interest rate. The Technical Panel 

also recommends a low-cost nominal interest rate 

of 5.4  percent (1.8  percent inflation plus 3.6  percent real interest rate) and a high-cost nominal interest rate of 5.7 percent (3.6 percent inflation plus 

2.1 percent real interest rate). 

The recommended values for the nominal interest 

rate are consistent with the assumptions about real 

interest rates noted earlier and the inflation rates 

just specified. They imply slightly higher nominal 

interest rates than what may be inferred at present 

from the longest-maturity nominal Treasuries.

3.6 Taxable Share of Covered Wages

Assumption Recommendation A-20. The Technical 

Panel recommends the brief continuation of the 

downward trend in the taxable share of covered 

wages as the economy fully recovers from the 

recession and then reaches an ultimate level of 

Figure 57. Yields on Constant-Maturity Treasury Inflation-Protected Securities (TIPS) Portfolios: 2003–2011

Source: Federal Reserve data.

-0.5 

0.0 

0.5 

1.0 

1.5 

2.0 

2.5 

3.0 

3.5 

4.0 

4.5 

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 

30-year 20-year 10-year 7-year 5-year 

Percent yield
2011 Technical Panel on Assumptions and Methods 111

82.2  percent. The Technical Panel also recommends significantly expanding the range of uncertainty around the taxable share given that 

the taxable share could continue to shift rapidly 

in the coming years. The Technical Panel recommends a low-cost value of 84.3  percent and a 

high-cost value of 80.0  percent, a range that is 

modestly asymmetric around the recommended 

intermediate value.

Method Recommendation M-14. The Technical Panel 

recommends consideration of a formal linkage 

between the assumed earnings to compensation 

ratio and the taxable share.

Method Recommendation M-15. Consistent with 

Recommendation P-1, the Technical Panel recommends characterizing the taxable share as 

a basic assumption with a meaningful range of 

uncertainty. It should also be part of the formal 

sensitivity analyses currently presented in Appendix D.

Only earnings below the contribution and benefit base (also known as the taxable maximum), 

set at $106,800 per year in 2009–2011, are subject to OASDI payroll taxes and counted toward 

Social Security benefits.77 The taxable share refers 

to the fraction of total earnings in OASDI-covered 

jobs below this threshold (and therefore subject 

to payroll tax)  and thus encompasses one aspect 

of earnings dispersion that is important for Social 

Security costs.

Since 1983, the taxable share has steadily trended downward, as observed in Figure 59. The only 

exceptions have been periods of recession (and a 

recession’s immediate aftermath), when the taxable share briefly turned upward, only to continue 

its decline again shortly after the recession’s end. 

Data from 2010 (presented in the 2011 Trustees 

Report)  suggest that the pattern is repeating and 

that the taxable share has begun to turn downward.

77 The threshold is indexed to account for wage inflation but 

did not increase in years without a Cost of Living Adjustment. 

Section 1300 of the Social Security Handbook details the types of 

compensation subject to payroll taxation.

Figure 58. Annual CPI-W Inflation: 1960–2010

Source: Bureau of Labor Statistics. The data in the figure come from the CPI-W-RS series constructed above.

-1 

0 

1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 

Percent 

CPI-W inflation rate

5-year moving average
112 2011 Technical Panel on Assumptions and Methods

Detailed data on the U.S. earnings distribution 

suggest that the driving force behind the downward 

trend in taxable share has been rapid increases in 

the earnings of the very highest earners (e.g., Bakija, Cole, and Heim 2010; Kopczuk, Saez, and Song 

2007; Piketty and Saez 2003, 2010).78 We define 

highest earners as just a fraction of the top 1 percent of all earners; that is, a fairly small subset of 

the approximately 6  percent of the covered labor 

78 The underlying mechanisms discussed in the literature suggest 

that the rapid increases result from skill-biased technological 

change (Autor et al. 2006), technologies that permit “superstars” to 

increase their compensation (Rosen 1981), executive pay (Bebchuk 

and Fried 2003; Bebchuk and Grinstein 2005; Frydman and Jenter 

2010; Frydman and Saks 2010), and changing roles of key institutions (DiNardo, Fortin, and Lemieux 1996; Levy and Temin 2007). 

Some speculate that much of the trend may be attributable to the 

realization of salary gains associated with concurrent stock market 

and real estate bubbles. That this phenomenon is evident primarily 

in English-speaking countries leads some to conclude that norms 

about inequality play a significant role (Atkinson, Piketty, and Saez 

2011).

force that earns over the taxable maximum. While 

the downward trend is also attributable  to (1)  the 

aging of the Baby Boom generation into cohorts at 

which workers are more likely to earn above the taxable maximum and (2) other compositional changes 

(e.g., a growing foreign-born population with highly 

heterogeneous earnings), such effects appear to 

have been comparatively modest (Cheng 2011). At 

the same time, however, changing shares of compensation awarded as employee benefits rather than 

as wages at various points in the earnings distribution may help explain the trend (Pierce 2010).

The 2011 Trustees Report projected that the 

taxable share will level off at an ultimate rate of 

82.9 percent of covered payroll. The projection assumes that the taxable share’s decline reached a nadir at about its 2007 value and should remain relatively stable at just above that value. In the low- and 

high-cost alternatives of the 2011 Trustees Report, 

Figure 59. Historical and Projected Values of the Taxable Share of Covered Wages: 2011 Trustees Report and 

Technical Panel Recommendations 

Source: Table 4.B1, Annual Statistical Supplement to the Social Security Bulletin; OASDI Trustees Report, 2011, p. 115.

Notes: Vertical axis does not start at zero. Recessionary periods as defined by National Bureau of Economic Research are shaded. Interpolations between 

last observed historical value and ultimate values are simplified.

90.0% 

82.6% 

85.7% 

84.2%

82.9% 

83.6% 

82.1% 

84.3% 

82.2% 

80.0% 

78.0 

80.0 

82.0 

84.0 

86.0 

88.0 

90.0 

92.0 

1983 1986 1989 1992 1995 1998 2001 2004 2007 2010 2013 2016 2019 2022 2025 2028 2031 2034 2037 2040 

Taxable percent of covered wages

Historical values in black

Technical Panel recommendation in (red)

Trustees assumptions in blue

Historical values

Technical Panel recommendation

Trustees assumptions
2011 Technical Panel on Assumptions and Methods 113

the taxable share ultimately reaches, respectively, 

83.6 and 82.1 percent of covered payroll.

Because the literature and expert judgment are 

sharply divided on the question of whether the 

earnings of the very highest earners will continue 

to outpace earnings at lower points in the distribution, the Technical Panel recommends only modest change to the current Trustees’ assumption. 

Analysts who foresee a continuation of the trend 

toward a lower taxable share see few institutional mechanisms that would inhibit further rapid 

growth in earnings for the most highly compensated workers. Those who expect the trend to slow, 

flatten, or even reverse point to several explanatory 

factors. Such factors include the likelihood that 

marginal tax rates will increase, perhaps markedly, 

in coming  years, especially for very high earners 

and that health care reform could reduce the share 

of total compensation awarded as health benefits, 

with greater effects in the middle of the earnings 

distribution rather than at the top. Some posit that 

bubbles fueled much of the recent growth in compensation of the highest earners and are unlikely to 

occur again.

The Technical Panel believes that the argument 

that the downward trend is likely to continue is 

somewhat stronger, but it does recognize that the 

trend is unlikely to continue indefinitely. We therefore recommend only a slightly steeper downward 

slope until the taxable share reaches its ultimate 

value, proposed at 82.2  percent, just below the 

2007 value.

Given that the taxable share depends heavily on 

earnings for a just small fraction of the labor force, 

it could shift quickly and markedly with changes 

in the policy environment, including, for example, 

comprehensive reform of the personal income tax 

system, financial reform, change in the tax treatment of carried interest, or health reform. The 

Technical Panel therefore recommends that OACT 

continue to monitor earnings data closely to determine the extent to which the taxable share changes 

with the economy’s recovery from the recession 

and as various provisions of the Affordable Care Act

take effect.

While the evidence supporting a change to the 

intermediate value of the taxable share assumption 

is mixed, the Technical Panel reached a strong consensus that the future uncertainty of earnings variability is particularly high and that the currently assumed range between the low- and high-cost bands 

for the taxable share is too narrow given the possibility of continued change. This position echoes 

Recommendation O-2 from the 2007 Technical 

Panel (“High- and low-cost ratios should provide a 

realistic range of uncertainty”). The Technical Panel 

recommends a band of + 2.1 and -2.2  percentage 

points around the intermediate value assumed for 

the taxable share.

We recognize that the objective for the ultimate 

rate is a level that remains stable for a long period, 

yet many plausible scenarios imply levels that fall 

significantly outside the existing range for the lowand high-cost values in the 2011 Trustees Report 

(+ 0.7/- 0.8 percentage points around the intermediate value). If the linear trend from 1983 to 2007 

were to continue for even 7 years before leveling off, 

the taxable share would be more than a percentage 

point lower than under the high-cost alternative. 

Analogously, the taxable share over the past 10 

non-recession  years has averaged about 84.4  percent, 0.8 percentage point above the ultimate lowcost alternative. Neither alternative seems at all 

unreasonable for sensitivity analyses.

Changes to the taxable share could affect system 

financing in different ways depending on the types 

of changes introduced; in particular, the extent to 

which high earners’ wages change the average wage 

plays an important role (see, for example, Favreault 

2009; Gustman, Steinmeier, and Tabatabai 2010). 

The Technical Panel encourages the Trustees to 

raise the prominence of earnings dispersion in its 

discussion of the OASDI system’s financing, given that the recent downward trend in the taxable 

share has contributed to deterioration in OASDI’s 

long-run fiscal status.

Current OACT techniques for modeling the taxable share do not include information about the 

earnings to compensation ratio. The literature suggests that employers view employee compensation 

in total; accordingly, changes in any compensation 

type have implications for the earnings distribution 

and thus for the taxable share. Given that regulatory and market adjustments will likely change shares 

of non-earnings compensation of various types 

(health benefits, employer pension contributions), 

the Technical Panel encourages OACT to examine 

closely the resultant relationships. If appropriate, 

such outcomes could be formally linked.79

79 Disentangling correlation and causation in these relationships 

may require additional research and further refinement of other 

variables in the model of the taxable share.

2011 Technical Panel on Assumptions and Methods 115

References

■ CHAPTER 1: Methodology

1.1 Presentation of Uncertainty

Maestas, Nicole, and Julie Zissimopoulos (2010). 

“How Longer Work Lives Ease the Crunch of Population Aging.” Journal of Economic Perspectives

24(1): 139-160.

1.2 Actuarial Metrics

Actuarial Standards Board (1998). Actuarial 

Standards of Practice No. 32, Social Insurance. Adopted January  1998, updated for Deviation Language, effective May 1, 2011 (http://

www.actuarialstandardsboard.org/pdf/asops/

asop032_149.pdf).

Booth, Philip, Robert Chadburn, Steven Haberman, 

Dewi James, Zaki Khorasanee, Robert H. Plumb, 

and Ben Rickayzen (2005). Modern Actuarial 

Theory and Practice, Second Edition. Chapman & 

Hall/CRC, pp. 628-632.

Gokhale, Jagadeesh (2010). Social Security, A Fresh 

Look at Policy Alternatives. Chicago: University 

of Chicago Press, pp. 20-27, 124, 146.

Office of the Chief Actuary (2006). Actuarial Report (23th) on the Canada Pension Plan as of 31 

December 2006 (http://www.osfi-bsif.gc.ca).

Office of the Chief Actuary (2009). Actuarial Report (25th) on the Canada Pension Plan as of 31 

December 2009 (http://www.osfi-bsif.gc.ca).

U.S. Congressional Budget Office (2010). CBO’s 

2010 Long-Term Projections for Social Security, 

Additional Information, October  2010 (http://

www.cbo.gov/ftpdocs/119xx/doc11943/10-

22-SocialSecurity_chartbook.pdf).

U.S. Federal Accounting Standards Advisory Board 

(2010). Statements of Federal Accounting Concepts and Standards as of June 30, 2010, SFFAS 

17 and SFFAS 37 (http://www.fasab.gov/pdffiles/

codification_report2010.pdf).

1.3 Models and Methods

Anderson, Joseph M. (1997). Models for Retirement Policy Analysis. Report to the Society of 

Actuaries. Bethesda, MD: Capital Research Associates.

Burtless, Gary (1996). “A Framework for Analyzing 

Future Retirement Income Security.” In: Assessing Knowledge of Retirement Behavior, Eric A. 

Hanushek and Nancy L. Maritato, eds. Washington, DC: National Academy Press.

Citro, Constance  F., and Eric  A. Hanushek, eds. 

(1997). Assessing Policies for Retirement Income: 

Needs for Data, Research, and Models. Washington, DC: National Academy Press.

Citro, Constance F., and Eric A. Hanushek (1991). 

Improving Information for Social Policy Decisions: The Uses of Microsimulation Modeling. 

Panel to Evaluate Microsimulation Models for 

Social Welfare Programs, Committee on National 

Statistics, National Research Council. Washington, DC: National Academy Press.

Favreault, Melissa, John Rust, Frank Sammartino, 

and Eric Toder (2000). “Review of Social Security 

Microsimulation Alternatives.” Long-Term Model 

Development for Social Security Policy Analysis, E. Toder, M. Favreault, J. O’Hare, D. Rogers, 

F. Sammartino, K. Smith, and J. Rust, eds. Washington, DC: The Urban Institute.

Office of the Chief Actuary, U.S. Social Security Administration (2011). Long-Range OASDI Projection Methodology: Intermediate Assumptions of 
116 2011 Technical Panel on Assumptions and Methods

the 2011 Trustees Report. Baltimore, MD: Social 

Security Administration (http://www.ssa.gov/

OACT/TR/2011/documentation_2011.pdf).

U.S. Congressional Budget Office  (2011). CBO’s 

2011 Long-Term Projections for Social Security: 

Additional Information. Washington, DC: CBO.

U.S. National Commission on Fiscal Responsibility and Reform (2010). The Moment of Truth: 

Report of the National Commission on Fiscal 

Responsibility and Reform. Washington, DC: The 

White House (http://www.fiscalcommission.gov/

sites/fiscalcommission.gov/files/documents/

TheMomentofTruth12_1_2010.pdf).

U.S. Office of Management and Budget (2011). 

Analytical Perspectives: Budget of the U.S. Government, Fiscal Year 2012. Washington, DC: U.S. 

Government Printing Office.

U.S. Social Security Administration (2011). 

Disability Evaluation under Social Security

(Blue Book – June 2011). Baltimore, MD: Social 

Security Administration (http://www.ssa.gov/

disability/professionals/bluebook).

1.4 Implications of Health Care Reform

Buchmueller, Thomas C., John DiNardo, and Robert G. Valletta (2009). The Effect of an Employer 

Health Insurance Mandate on Health Insurance Coverage and the Demand for Labor: Evidence from Hawaii. Working Paper No.  2009-

08. San  Francisco: U.S. Federal Reserve Bank of 

San Francisco.

Colla, Carrie  H., William  H. Dow, and Arindrajit 

Dube (2011). The Labor Market Impact of Employer Health Benefit Mandates: Evidence from 

San Francisco’s Health Care Security Ordinance. 

NBER Working Paper No.  17198. Cambridge, 

MA: National Bureau of Economic Research.

Cutler, David, and Neeraj Sood (2010). New Jobs 

through Better Health Care. Washington, DC: 

Center for American Progress.

Fronstin, Paul (2010). “Sources of Health Insurance 

and Characteristics of the Uninsured: Analysis 

of the March  2010 Current Population Survey.” 

EBRI Issue Brief No. 347 (http://www.ebri.org/

pdf/briefspdf/EBRI_IB_09-2010_No347_Uninsured1.pdf, accessed June 1, 2011).

Gruber, Jonathan (2011). “Massachusetts Points 

the Way to Successful Health Care Reform.” Journal of Policy Analysis and Management 30(1): 

184-192.

Holtzblatt, Janet, and Benjamin Page (2009). “Effects of Changes to the Health Insurance System 

on Labor Markets.” Economic and Budget Issue 

Brief. Washington, DC: CBO.

Kaiser Family Foundation (2011). Summary of 

New Health Reform Law. (http://www.kff.

org/healthreform/upload/8061.pdf, accessed 

June 17, 2011).

Levy, Helen, and Katherine Baicker (2008). “Employer Health Insurance Mandates and the Risk 

of Unemployment.” Risk Management and Insurance Review 11(1): 109-132.

Levy, Helen, and David Meltzer (2004). “What Do 

We Really Know about Whether Health Insurance Affects Health?” Health Policy and the Uninsured, Catherine McLaughlin, ed. Washington, 

DC: The Urban Institute Press.

Madrian, Brigitte C. (2007). “The U.S. Health Care 

System and Labor Markets.” Wanting It All: The 

Challenge of Reforming the U.S. Health Care System, Jane Sneddon Little, ed. Boston: Federal Reserve Bank of Boston.

Madrian, Brigitte C., and Jonathan Gruber (2004). 

“Health Insurance, Labor Force Participation, 

and Job Choice: A Critical Review of the Literature.” Health Policy and the Uninsured, Catherine 

McLaughlin, ed. Washington, DC: The Urban Institute Press.

Singhal, Shubham, Jeris Steuland, and Drew Ungerman (2011). “How U.S. Health Care Reform Will 

Affect Employee Benefits,” McKinsey Quarterly 

(http://www.mckinseyquarterly.com/How_US_

health_care_reform_will_affect_employee_benefits_2813, accessed June 17, 2011).

Thurston, Norman (1997). “Labor Market Effects of 

Hawaii’s Mandatory Employer-Provided Health 

Insurance.” Industrial and Labor Relations Review 51(1): 117-135.

U.S. Congressional Budget Office (2010a). The Budget and Economic Outlook: An Update (http://

www.cbo.gov/ftpdocs/117xx/doc11705/08-

18-Update.pdf, accessed June 2, 2011).

U.S. Congressional Budget Office (2010b). CBO’s 

Analysis of the Major Health Care Legislation 

Enacted in March  2010, Testimony of Douglas 

Elmendorf before the Subcommittee on Health, 

Committee on Energy and Commerce, U.S. House 

of Representatives, March  30, 2011 (http://

www.cbo.gov/ftpdocs/121xx/doc12119/03-

30-HealthCareLegislation.pdf, accessed June  2, 

2011).
2011 Technical Panel on Assumptions and Methods 117

■ CHAPTER 2: Demographic 

Assumptions and Methods

2.1 Fertility

Bongaarts, J. (2002). “The End of Fertility Transition in the Developed World.” Population and Development Review 28(3): 419-444.

Bongaarts,  J. (2001). “Fertility and Reproductive 

Preferences in Post-Transitional Societies.” Population and Development Review 27(Supplement: 

Global Fertility Transition): 260-281.

Bongaarts, J., and G. Feeney (1998). “On the Quantum and Tempo of Fertility.” Population and Development Review 24(2): 271-291.

Bongaarts,  J., and S.C.  Watkins (1996). “Social Interactions and Contemporary Fertility 

Transitions.” Population and Development Review 22(4): 639-682.

Cherlin,  A.J. (1992). Marriage, Divorce, Remarriage, Revised Edition. Cambridge, MA: Harvard 

University Press.

Hayford,  S., and S.P.  Morgan (2008). “Religiosity 

and Fertility in the United States: The Role of Fertility Intentions.” Social Forces 86(3): 1163-1188.

Kohler, H.-P., and J.A. Ortega (2004). “Old Insights 

and New Approaches: Fertility Analysis and Tempo Adjustment in the Age-Parity Model.” Vienna 

Yearbook of Population Research 2: 57-89.

Morgan,  S.P. (2003). “Is Low Fertility a TwentyFirst-Century Demographic Crisis?” Demography 40(4): 589-603.

Morgan,  S.P., E.  Cumberworth, and C.  Wimer 

(2011). “The Great Recession’s Influence on Fertility, Marriage, Divorce, and Cohabitation.” The 

Consequences of the Great Recession, D. Grusky 

and C. Wimer, eds. New York: Russell Sage Foundation, forthcoming.

Morgan,  S.P., and R.B.  King (2001). “Why Have 

Children in the 21st Century? Biological Predisposition, Social Coercion, Rational Choice.” European Journal of Population 17(1): 3-20.

Morgan, S.P., and H. Rackin (2010a). “A Half Century of Fertility Change.” Journal of Comparative 

Family Studies 41(4): 515-535.

Morgan,  S.P., and H.  Rackin (2010b). “The Correspondence of Fertility Intentions and Behavior 

in the U.S.” Population and Development Review 36(1): 91-118.

Morgan,  S.P., G.  Zhigang, and S.  Hayford (2009). 

“China’s Below Replacement Fertility: Recent 

Trends and Future Prospects.” Population and 

Development Review 35(3): 605-630.

Myrskyla, M., H.-P. Kohler et al. (2009). “Advances 

in Development Reverse Fertility Decline.” Nature 460 (6 August): 741-743.

Parrado,E., and S.P.Morgan (2008). “Intergenerational Fertility among Hispanic Women: New 

Evidence of Immigrant Assimilation.” Demography 45(4): 651-671.

Zeng, Y., and K.C. Land (2002). “Adjusting Period 

Tempo Changes with an Extension of Ryder’s 

Basic Translation Equation.” Demography 39(2): 

269-286.

2.2 Mortality

Adams,  K.F., A.  Schatzkin, T.B.  Harris, V.  Kipnis, 

T. Mouw, R. Ballard-Barbash, A. Hollenbeck, and 

M.F.  Leitzmann (2006). “Overweight, Obesity, 

and Mortality in a Large Prospective Cohort of 

Persons 50 to 71 years Old.” New England Journal of Medicine 355(8): 763-778.

Alley, Dawn, Jennifer Lloyd, and Michelle Shardell 

(2010). “Can Obesity Account for Cross-National 

Differences in Life Expectancy Trends?” International Differences in Mortality at Older Ages: Dimensions and Source, Eileen M. Crimmins, Samuel H. Preston, and Barney Cohen, eds. Panel on 

Understanding Divergent Trends in Longevity in 

High-Income Countries; Divisions of Behavioral 

and Social Sciences and Education. Washington, 

DC: The National Academy Press.

Bell, William R. (1997). “Comparing and Assessing 

Time-Series Methods for Forecasting

Age-Specific Demographic Rates.” Journal of Official Statistics 13(3): 279-303.

Board of Trustees (2011). The 2011 Annual Report 

of the Board of Trustees of the Federal Old-Age 

and Survivors Insurance and Federal Disability 

Insurance Trust Funds, Washington, DC: Government Printing Office.

Bongaarts, John (2006). “How Long Will We Live?” 

Population and Development Review 32(4): 605-

628.

Carnes, Bruce  A., S.  Jay Olshansky, and Douglas 

Grahn (1996). “Continuing the Search for a Law 

of Mortality.” Population and Development Review 22(2): 231-264.
118 2011 Technical Panel on Assumptions and Methods

EUROSTAT (2011). Projections for France, Germany, Italy, Spain, and the United Kingdom (http://

epp.eurostat.ec.europa.eu/portal/page/portal/

statistics/search_database).

Glei, Dana, Samuel Preston, and John Wilmoth 

(2010). “Contribution of Smoking to International Differences in Life Expectancy.” International 

Differences in Mortality at Older Ages: Dimensions and Source, Eileen M. Crimmins, Samuel H. 

Preston, and Barney Cohen, eds. Panel on Understanding Divergent Trends in Longevity in HighIncome Countries; Divisions of Behavioral and 

Social Sciences and Education. Washington, DC: 

The National Academy Press.

Lee, R., and L. Carter (1992). “Modeling and Forecasting U.S. Mortality.” Journal of the 

American Statistical Association 87(419): 659-671.

Lee, R.D., and T. Miller (2001). “Evaluating the Performance of the Lee-Carter Method for Forecasting Mortality.” Demography 38(4): 537-549.

Li, Nan, and Ronald Lee (2005). “Coherent Mortality Forecasts for a Group of Populations: An 

Extension of the Lee-Carter Method.” Demography 42(3): 575-594.

McNown, Robert (1992). “Modeling and Forecasting U.S. Mortality: Comment.” Journal of the 

American Statistical Association  87(419): 671-

672.

Mehta,  N.K., and V.W.  Chang (2010). Secular Declines in the Association between Obesity and 

Mortality in the United States. Unpublished 

manuscript, University of Michigan.

National Research Council (2011). Explaining Divergent Levels of Longevity in High Income 

Countries. Eileen M. Crimmins, Samuel H. Preston, and Barney Cohen, eds. Panel on Understanding Divergent Trends in Longevity in HighIncome Countries; Divisions of Behavioral and 

Social Sciences and Education. Washington, DC: 

The National Academy Press, S-2, S-4, 5-4.

Oeppen, Jim, and James W. Vaupel (2002). “Broken 

Limits to Life Expectancy.” Science  296(5570): 

1029-1031.

Olshansky, S. Jay et al. (2005). “A Potential Decline 

in Life Expectancy in the United States in the 

21st Century.” New England Journal of Medicine 352(11): 1138-1145.

Olshansky,  S. Jay, Bruce  A. Carnes, and Christine 

Cassel (1990). “In Search of Methuselah: Estimating the Upper Limits to Human Longevity.” 

Science 250(4981): 634-640.

Preston,  S.H., and A.  Stokes (2010). Is the High 

Level of Obesity in the United States Related to 

Its Low Life Expectancy? Working Paper  2010-

08. Philadelphia: Population Studies Center, University of Pennsylvania.

Technical Panel on Assumptions and Methods 

(2003). Report to the Social Security Advisory 

Board. Washington, DC: Social Security Advisory 

Board, 38.

Technical Panel on Assumptions and Methods 

(2007). Report to the Social Security Advisory 

Board. Washington, DC: Social Security Advisory 

Board, 34-35.

U.S. Surgeon General (1964). Smoking and Health: 

Report of the Advisory Committee to the Surgeon General of the Public Health Service. U.S. 

Surgeon General’s Advisory Committee on Smoking and Health. Public Health Service. Office of 

the Surgeon General, Public Health Service Publication No. 1103. Washington, DC: U.S. Public 

Health Service.

Wilmoth, John R. (2001). “How Long Can We Live?” 

Population and Development Review 27(4): 791-

800.

Wilmoth, John R. (1997). “In Search of Limits.” Between Zeus and the Salmon: The Biodemography 

of Longevity, Kenneth  W. Wachter and Caleb  E. 

Finch, eds. Committee on Population, National 

Research Council. Washington, DC: The National 

Academy Press, 38-64.

Wilmoth, John R. (2005). Overview and Discussion 

of the Social Security Mortality Projections. Social Security Advisory Board Working Paper for 

the 2003 Technical Panel on Assumptions and 

Methods.

2.3 Immigration

Ahmed, Bashir, and J.  Gregory Robinson (1994). 

Estimates of Emigration of the Foreign-Born 

Population: 1980–1990. Technical Working Paper No. 9. Washington, DC: Population Division, 

U.S. Census Bureau.

Bean, Frank  D., Rodolfo Corona, Rodolfo Tuirán, Karen  A. Woodrow-Lafield, and Jennifer 

Van  Hook (2001). “Circular, Invisible, and Ambiguous Migrants: Components of Difference in 

Estimates of the Number of Unauthorized Mexican Migrants in the United States.” Demography 38(3): 411-422.
2011 Technical Panel on Assumptions and Methods 119

Clark, Ximena, Timothy  J. Hatton, and Jeffrey  G. 

Williamson (2007). “Explaining U.S. Immigration, 1971–1998.” The Review of Economics and 

Statistics 89(2): 359-373.

Cohen, Joel  E. (2011). International Migration 

Flows: Statistical Models for Use in Population 

Projections. United Nations, Population Division, Ninth Coordination Meeting on International Migration, UN/POP/MIG-9CM/2011/09. 

New York: United Nations.

Cohen, Joel E., Marta Roig, Daniel C. Reuman, and 

Cai GoGwilt (2008). “International Migration Beyond Gravity: A Statistical Model for Use in Population Projections.” Proceedings of the National 

Academy of Sciences 105(40): 15269-15274.

Costanza, Joe, Cynthia Davis, Caribert Irazi, Daniel 

Goodkind, and Roberto Ramirez (2001). Evaluating Components of International Migration: 

The Residual Foreign-Born. Population Division 

Working Paper No.  61. Washington, DC: U.S. 

Census Bureau.

Durand, Jorge, Douglas  S. Massey, and Emilio  A. 

Parrado (1999). “The New Era of Mexican Migration to the United States.” The Journal of American History 86(2): 518-536.

Edmonston, Barry, and Jeffrey  S. Passel (2004). 

“The Future Immigrant Population of the United 

States.” Immigration and Ethnicity: The Integration of America’s Newest Arrivals, B. Edmonston 

and J.S. Passel, eds. Washington, DC: The Urban 

Institute Press.

Gibson, Campbell. 1975. The Contribution of Immigration to United States Population Growth: 

1790-1970. International Migration Review 9 (2, 

Migration and Fertility, Summer): 157-177.

Greenwood, M. J., and J.M. McDowell (1999). Legal 

U.S. Immigration: Influences on Gender, Age, and 

Skill Composition. Kalamazoo, MI: W.E. Upjohn 

Institute for Employment Research.

Greenwood, Michael  J., John  M. McDowell, Donald M. Waldman, and Steven S. Zahniser (1999). 

“The Influence of Social Programs in Source 

Countries on Various Classes of U.S. Immigration.” Journal of the American Statistical Association 94(445): 64-75.

Grieco, Elizabeth M. (2008). Estimating Net International Migration for the United States. Presentation at the Joint ECE-EUROSTAT Work Session 

on Migration Statistics, Geneva, Switzerland.

Gryn, Thomas A., and Luke J. Larsen (2010). “Nativity Status and Citizenship in the United States: 

2009.” American Community Survey Briefs, ACSBR/09-16. Washington, DC: U.S. Census Bureau.

Hanson, Gordon  H., and Craig McIntosh (2009). 

“The Demography of Mexican Migration to the 

United States.” American Economic Review: Papers & Proceedings 99: 22-27.

Hanson, Gordon  H., and Craig McIntosh (2010). 

“The Great Mexican Emigration.” The Review of 

Economics and Statistics 92(4): 798-810.

Hatton, Timothy  J., and Jeffrey  G. Williamson 

(2002). What Fundamentals Drive World Migration? NBER Working Paper  9159. Cambridge, 

MA: National Bureau of Economic Research.

Hollmann, F.W., T.J. Mulder, and J.E. Kallan (2000). 

Methodology and Assumptions for the Population Projections of the United States: 1999 to 

2100. Population Division Working Paper No. 38, 

Washington, DC: U.S. Census Bureau.

Hollmann, Frederick W. (2005). Toward a Legal Immigrant Data Series for Population Projections. 

Presented at the Fourteenth Federal Forecasters 

Conference, Washington, DC.

Janoski,  T. (2010). The Ironies of Citizenship: 

Naturalization and Integration in Industrialized 

Countries. Cambridge, UK: Cambridge University 

Press.

Jasso, Guillermina, Douglas  S. Massey, Mark  R. 

Rosenzweig, and James  P. Smith (2008). “From 

Illegal to Legal: Estimating Previous Illegal Experience among New Legal Immigrants to the United States.” International Migration Review 42(4): 

803-843.

Jasso, Guillermina, and Mark  R. Rosenzweig 

(1990). The New Chosen People: Immigrants in 

the United States. New York: Russell Sage Foundation.

Jasso, Guillermina, Vivek Wadhwa, Gary Gereffi, 

Ben Rissing, and Richard Freeman (2010). “How 

Many Highly Skilled Foreign-Born Are Waiting in 

Line for U.S. Legal Permanent Residence?” International Migration Review 44(2): 477-498.

Kim, Keuntae, and Joel  E. Cohen (2010). “Determinants of International Migration Flows to and 

from Industrialized Countries: A Panel Data Approach beyond Gravity.” International Migration 

Review 44(4): 899-932.

Massey,  D.S., J.  Arango, G.  Hugo, A.  Kouaouci, 

A.  Pellegrino, and J.E.  Taylor (1998). Worlds in 

Motion: Understanding International Migration 

at the End of the Millennium. Oxford, UK: Clarendon Press.
120 2011 Technical Panel on Assumptions and Methods

Massey, Douglas S. (2010). “Immigration Statistics 

for the Twenty-First Century.” The Annals 631(1): 

124-140.

Massey, Douglas  S. (2009). Securing the Borders 

and America’s Points of Entry, What Remains to 

Be Done. Testimony before the Senate Committee on the Judiciary, Subcommittee on Immigration, Refugees and Border Security.

Massey, Douglas S. (2000). “To Study Migration Today, Look to a Parallel Era.” 

Chronicle of Higher Education Opinion, August 18, 

B4-B5.

Massey, Douglas S. (2007). “Toward a Comprehensive Model of International Migration.” Migration and Development: International Migration 

of Population–Russia and Contemporary World. 

Moscow: MAX Press.

Massey, Douglas  S. (1999). “Why Does Immigration Occur? A Theoretical Synthesis.” Handbook 

of International Migration: The American Experience, C. Hirschman, J. DeWind, and P. Kasinitz, 

eds. New York: Russell Sage Foundation.

Massey, Douglas S., and Katherine Bartley (2005). 

“The Changing Legal Status Distribution of Immigrants: A Caution.” International Migration 

Review 34(2): 469-484.

Massey, Douglas  S., and Nolan Malone (2002). 

“Pathways to Legal Immigration.” Population Research and Policy Review 21(6): 473-504.

Mulder, Tamany J., Betsy Guzman, and Angela M. 

Brittingham (2002). Evaluating Components 

of International Migration: Foreign-Born Emigrants. Technical Working Paper No.  62. Washington, DC: Population Division, U.S. Census Bureau.

Ortman, Jennifer M., Frederick W. Hollmann, and 

Renuka Bhaskar (2010). Alternative Bases for 

Projecting International Migration. Presented at 

the Annual Meeting of the American Society of 

Actuaries.

Passel, J.S. (2002). “New Estimates of the Undocumented Population in the United States.” Migration Information Source (www.migrationinformation.org).

Passel, Jeffrey  S., and D’Vera Cohn (2011). Unauthorized Immigrant Population: National and 

State Trends, 2010. Washington, DC: Pew Hispanic Center.

Passel, Jeffrey S., and D’Vera Cohn (2008). U.S. 

Population Projections: 2005 to 2050. Washington, DC: Pew Hispanic Center.

Passel, Jeffrey  S., and Karen  A. Woodrow (1987). 

“Change in the Undocumented Alien Population 

in the United States, 1979-1983.” International 

Migration Review 21(4): 1304-1334.

Passel, Jeffrey  S., and Karen  A. Woodrow (1984). 

“Geographic Distribution of Undocumented Immigrants: Estimates of Undocumented Aliens 

Counted in the 1980 Census by State.” International Migration Review 18(3): 642-671.

Pew Hispanic Center (2006). From 200  million to 

300  million: The Numbers behind Population 

Growth. Fact sheet (http://pewhispanic.org/

files/factsheets/25.pdf).

United Nations, Department of Economic and Social Affairs, Population Division (2004b). World 

Population to 2300. ST/ESA/SER.A/236. New 

York: UN DESA.

United Nations, Department of Economic and Social Affairs, Population Division  (2011). World 

Population Prospects: The 2011 Revision, CDROM edition. File 18: Net Migration Rate by Major Area, Region and Country, 1950–2100 (per 

1,000  population); Medium-fertility Variant, 

2010–2100, POP/DB/WPP/Rev.2010/01/F18. 

New York: UN DESA.

United Nations, Department of Economic and 

Social Affairs, Population Division.  (2009). 

World Population Prospects: The 2008 Revision, 

Highlights, Working Paper No.  ESA/P/WP.210. 

New York: UN DESA.

United Nations, Department of Economic and 

Social Affairs, Population Division. Long-range 

Population Projections (2004a). Proceedings of 

the United Nations Expert Working Meeting on 

World Population in 2300. New York: UN DESA.

United Nations, Department of Economic and 

Social Affairs, Population Division. Long-range 

Population Projections (2003). Proceedings of 

the United Nations Technical Working Group on 

Long-Range Population Projections. New  York: 

UN DESA. 

U.S. Census Bureau (2009b). Changes to the American Community Survey between 2007 and 2008 

and Their Potential Effect on the Estimates of Hispanic Origin Type, Nativity, Race, and Language 

(http://www.census.gov/population/www/

socdemo/hispanic/acs08researchnote.pdf).

U.S. Census Bureau (2010b). Characteristics of the 

Foreign Born by Generation, Table 4.1 Population 

by Sex, Age, and Generation: 2009. Washington, 

DC: Population Division, Immigration Statistics 

Staff, USCB.
2011 Technical Panel on Assumptions and Methods 121

U.S. Census Bureau (2010a). The Development and 

Sensitivity Analysis of the 2010 Demographic 

Analysis Estimates. Washington, DC: Population 

Division, USCB.

U.S. Census Bureau (2010c). National Population 

Estimates, July 1, 2009, Table 6. Estimates of the 

Components of Resident Population Change by 

Race and Hispanic Origin for the United States: 

July 1, 2008, to July 1, 2009 (NC-EST2009-06). 

Washington, DC: Population Division, USCB.

U.S. Census Bureau (2009a). Table  1. Projections 

of the Population and Components of Change by 

Net International Migration Series for the United 

States: 2010 to 2050 (NP2009-T1). Washington, 

DC: Population Division, USCB.

U.S. Congressional Budget Office (2011). CBO’s Labor Force Projections through 2021.

U.S. Department of Homeland Security (2010). Estimates of the Legal Permanent Resident Population in 2009. Rytina, Nancy. Washington, DC: 

DHS, Office of Immigration Statistics, Policy Directorate.

U.S. Department of Homeland Security (2011). Estimates of the Unauthorized Immigrant Population Residing in the United States: January 2010. 

Hoefer, Michael, Nancy Rytina, and Bryan  C. 

Baker. Washington, DC: DHS, Population Estimates, Office of Immigration Statistics, Policy 

Directorate.

U.S. Department of Homeland Security (2010). Estimates of the Unauthorized Immigrant Population Residing in the United States: January 2009. 

Hoefer, Michael, Nancy Rytina, and Bryan  C. 

Baker. Washington, DC: DHS, Population Estimates, Office of Immigration Statistics, Policy 

Directorate.

U.S. Department of Homeland Security (2006). Estimates of the Unauthorized Immigrant Population Residing in the United States: January 2005. 

Hoefer, Michael, Nancy Rytina, and Christopher 

Campbell. Washington, DC: DHS, Population Estimates, Office of Immigration Statistics, Policy 

Directorate.

U.S. Government Accountability Office (2011). 

H-1B Visa Program: Reforms Are Needed to Minimize the Risks and Costs of Current Program. 

GAO-11-23. Washington, DC: GAO.

U.S. Immigration and Naturalization Service, Office 

of Policy and Planning (2003). Estimates of the 

Unauthorized Immigrant Population Residing in 

the United States: 1990 to 2000.

Warren, R., and E.P. Kraly (1985). The Elusive Exodus: Emigration from the United States. Population Trends and Public Policy Occasional Paper 

No.  8. Washington, DC: Population Reference 

Bureau.

Warren, R., and J.S. Passel (1987). “A Count of the 

Uncountable: Undocumented Aliens Counted in 

the 1980 Census.” Demography 24(3): 375-394.

Woodrow,  K.A. (1991a). “Project D5: Preliminary 

Estimates of Emigration Component.” Research 

and Evaluation Memorandum No.  78. Washington, DC: U.S. Census Bureau.

Woodrow, Karen A. (1991b). “Project D2: Preliminary Estimates of Undocumented Residents in 

1990.” Research and Evaluation Memorandum 

No. 75. Washington, DC: U.S. Census Bureau.

Woodrow, Karen  A,. and Jeffrey  S. Passel (1990). 

“Post–IRCA Undocumented Immigration to 

the United States: Assessment Based on the 

June 1988 CPS.” Undocumented Migration to the 

United States: IRCA and the Experience of the 

1980s, F.D. Bean, B. Edmonston, and J.S. Passel, 

eds. Washington, DC: The Urban Institute Press.

Woodrow-Lafield,  K.A. (1996). “Emigration from 

the United States: Multiplicity Survey Evidence.” 

Population Research and Policy Review  15(2): 

171-199.

Woodrow-Lafield, Karen  A. (1992). “A Consideration of the Effect of Immigration Reform on 

the Number of Undocumented Residents in the 

United States.” Population Research and Policy 

Review 11(2): 117-144.

2.4 Disability

Autor, David, and Mark Duggan (2006). “The 

Growth in the Social Security Disability Insurance Rolls: A Fiscal Crisis Unfolding.” Journal of 

Economic Perspectives 20(3): 71-96.

Autor, David, and Mark Duggan. (2003). “The Rise 

in the Disability Rolls and the Decline in Unemployment.” Quarterly Journal of Economics 118(1): 157-206.

Autor, David, and Mark Duggan (2010). Supporting 

Work: A Proposal for Modernizing the U.S. Disability Insurance System. Center for American 

Progress and the Hamilton Project.

Black, Dan, Kermit Daniel, and Seth Sanders 

(2002). “The Impact of Economic Conditions on 

Participation in Disability Programs: Evidence 
122 2011 Technical Panel on Assumptions and Methods

from the Coal Boom and Bust.” American Economic Review 92(1): 27-50.

Bound, John (1989). “The Health and Earnings of 

Rejected Disability Insurance Applicants.” American Economic Review 79(3): 482-503.

Bound, John (1991). “The Health and Earnings of 

Rejected Disability Insurance Applicants: Reply.” 

American Economic Review 81(5): 1427-1434.

Bound, John, and Richard Burkhauser (1999). 

“Economic Analysis of Transfer Programs Targeted on People with Disabilities.” Handbook of 

Labor Economics, Volume  3, Orley Ashenfelter 

and David Card, eds. Amsterdam: North-Holland.

Bound, John, and Timothy Waidmann (1992). “Disability Transfers, Self-Reported Health, and the 

Labor Force Attachment of Older Men: Evidence 

from the Historical Record.” Quarterly Journal of 

Economics 107(4): 1393-1419.

Burkhauser, Richard, and Mary Daly (2002). “Policy Watch: U.S. Disability Policy in a Changing 

Environment.” Journal of Economic Perspectives 16(2): 213-224.

Chen, Susan, and Wilbert van der Klauuw (2008). 

“The Work Disincentive Effects of the Disability Insurance Program in the 1990s.” Journal of 

Econometrics 142(2): 757-784.

Duggan, Mark, and Scott Imberman (2009). “Why 

Are the Disability Rolls Skyrocketing?” Health in 

Older Ages: The Causes and Consequences of Declining Disability among the Elderly, David Cutler 

and David Wise, eds. Chicago: University of Chicago Press.

Duggan, Mark, Perry Singleton, and Jae Song 

(2007). “Aching to Retire? The Rise in the Full 

Retirement Age and Its Impact on the Disability 

Rolls.” Journal of Public Economics 91(7): 1327-

1350.

Gruber, Jonathan, and Jeffrey  D. Kubik (1997). 

“Disability Insurance Rejection Rates and the Labor Supply of Older Workers.” Journal of Public 

Economics 64(1): 1-23.

Hennessey, John, and Janice Dykacz (1993). “A 

Comparison of the Recovery Termination Rates 

of Disabled-Worker Beneficiaries Entitled in 

1972 and 1985.” Social Security Bulletin  56(2): 

58-69.

Parsons, Donald  O. (1980). “The Decline in Male 

Labor Force Participation.” Journal of Political 

Economy 88(1): 117-134.

Parsons, Donald O. (1991). “The Health and Earnings of Rejected Disability Insurance Applicants: 

Comment.” American Economic Review  81(5): 

1419-1426.

Rupp, Kalman, and Charles Scott (1996). “Trends 

in the Characteristics of DI and SSI Awardees and 

Duration of Program Participation.” Social Security Bulletin.

Stapleton, David  C., and Richard  V. Burkhauser 

(2003). The Decline in Employment of People 

with Disabilities: A Policy Puzzle. Kalamazoo, MI: 

Upjohn Institute for Employment Research.

U.S. Social Security Administration. Annual Statistical Supplement, various years.

U.S. Social Security Administration. DI Annual Statistical Report, various years.

Von Wachter, Till, Jae Song, and Joyce Manchester 

(2011). “Trends in Employment and Earnings of 

Allowed and Rejected Applicants to the Social Security Disability Insurance Program.” American 

Economic Review, forthcoming.

■ CHAPTER 3: ECONOMIC 

ASSUMPTIONS AND METHODS

3.1 Labor Force Participation Rate

Mastrobuoni, Giovanni (2009). “Labor Supply Effects of the Recent Social Security Benefit Cuts: 

Empirical Estimates Using Cohort Discontinuities.” Journal of Public Economics  93(11-12): 

1224-1233.

National Institutes of Health (2007). Growing 

Older in America: The Health and Retirement 

Study (http://hrsonline.isr.umich.edu/index.

php?p=dbook).

Pew Research Center (2010). A Balance Sheet at 30 

Months: How the Great Recession Has Changed 

Life in America (http://pewsocialtrends.org/

files/2010/11/759-recession.pdf).

3.2-3.5 Real Wage Growth Rate, Unemployment 

Rate, Interest Rates, and Inflation

Bosworth, Barry  P. (2010). Price Deflators, The 

Trust Fund Forecast, and Social Security Solvency. Working Paper No.  2010-12. Boston College 

Center for Retirement Research.

Feyrer, James  D. (2007). “Demographics and Productivity.” Review of Economics and Statistics 89(1): 100-109.
2011 Technical Panel on Assumptions and Methods 123

Kozicki, Sharon. (1997). “The Productivity Growth 

Slowdown: Diverging Trends in the Manufacturing and Service Sectors.” Federal Reserve Bank 

of Kansas City Economic Review (First Quarter): 

31-46.

Office of the Chief Actuary, U.S. Social Security Administration (2010). The Long-range Economic 

Assumptions for the 2010 Trustees Report.

Stewart, Kenneth J., and Stephen B. Reed (1999). 

“Consumer Price Index Research Series Using 

Current Methods, 1978-98.” Monthly Labor Review 122(6): 29-38. For updates, see http://www.

bls.gov/cpi/cpirsdc.htm.

3.6 Taxable Share of Covered Wages

Atkinson, Anthony  B., Thomas Piketty, and Emmanuel Saez (2011). “Top Incomes in the Long 

Run of History.” Journal of Economic Literature 49(1): 3-71.

Autor, David H., Lawrence F. Katz, and Melissa S. 

Kearney (2006). “The Polarization of the U.S. Labor Market.” American Economic Review Papers 

and Proceedings 96(2): 189-194.

Bakija, Jon, Adam Cole, and Bradley T. Heim (2010). 

Jobs and Income Growth of Top Earners and the 

Causes of Changing Income Inequality: Evidence 

from U.S. Tax Return Data. Williams College Economics Department Working Paper Series 2010-

24. Williamstown, MA: Williams College.

Bebchuk, Lucian, and Yaniv Grinstein (2005). “The 

Growth of Executive Pay.” Oxford Review of Economic Policy 21(2): 283-303.

Bebchuk, Lucian Arye, and Jesse M. Fried (2003). 

“Executive Compensation as an Agency Problem.” 

The Journal of Economic Perspectives 17(3): 71-

92.

Cheng, Anthony (2011). Chart  5. Ratio of OASDI 

Taxable to Covered Wages. Presentation to the 

Social Security Advisory Board’s Technical Panel 

on Assumptions and Methods. Washington, DC.

DiNardo, John, Nicole  M. Fortin, and Thomas 

Lemieux (1996). “Labor Market Institutions and 

the Distribution of Wages, 1973-1992: A Semiparametric Approach.” Econometrica  64(5): 1001-

1044.

Favreault, Melissa M. (2009). Rising Tides and Retirement: The Aggregate and Distributional Effects of Differential Wage Growth on Social Security. Working Paper No. 2009-07. Chestnut Hill, 

MA: Center for Retirement Research at Boston 

College.

Frydman, Carola, and Dirk Jenter (2010). “CEO 

Compensation.” Annual Review of Financial Economics 2(1): 75-102.

Frydman, Carola, and Raven  E. Saks (2010). “Executive Compensation: A New View from a LongTerm Perspective, 1936-2005.” Review of Financial Studies 23(5): 2099-2138.

Gustman, Alan L., Thomas Steinmeier, Nahid Tabatabai (2010). The Growth in Social Security Benefits among the Retirement Age Population from 

Increases in the Cap on Covered Earnings. NBER 

Working Paper No.  16501. Cambridge, MA: National Bureau of Economic Research.

Kopczuk, Wojciech, Emmanuel Saez, and Jae Song 

(2007). Uncovering the American Dream: Inequality and Mobility in Social Security Earnings 

Data since 1937. Working paper. Columbia University, National Bureau of Economic Research, 

and U.S. Social Security Administration.

Levy, Frank S., and Peter Temin (2007). Inequality 

and Institutions in 20th Century America. Working Paper 07-17. Cambridge, MA: Massachusetts 

Institute of Technology, Department of Economics.

National Bureau of Economic Research (2011). 

U.S. Business Cycle Expansions and Contractions 

(http://www.nber.org/cycles.html).

Pierce, Brooks (2010). “Recent Trends in Compensation Inequality.” Labor in the New Economy, 

Katharine  G. Abraham, James  R. Spletzer, and 

Michael Harper, eds. National Bureau of Economic Research. Studies in Income and Wealth  71. 

Chicago: University of Chicago Press.

Piketty, Thomas, and Emmanuel Saez (2003). “Income Inequality in the United States, 1913-

1998.” Quarterly Journal of Economics  118(1): 

1-39.

Piketty, Thomas, and Emmanuel Saez (2010). 

Tables from Piketty and Saez, 2003, updated 

through 2008 (http://elsa.berkeley.edu/~saez/).

Rosen, Sherwin (1981). “The Economics of Superstars.” American Economic Review 71(5): 845-858.

2011 Technical Panel on Assumptions and Methods 125

Compilation of 2011 Technical Panel Recommendations

■ Chapter 1. Methodology

Section 1.1 Presentation of Uncertainty

Presentation Recommendation P-1. The Technical 

Panel recommends expanding the list of key assumptions in summary Table  II.C1 to include 

missing drivers of long-run Social Security finances. In addition, as warranted, the Technical 

Panel recommends presenting the values for key 

assumptions in a way that is useful to readers. 

Improved communication will likely involve reporting values for “indicator” variables that are 

directly determined by the more precise (but not 

easily interpretable ) basic assumptions. 

Presentation Recommendation P-2. The Technical 

Panel recommends removing the current presentation of uncertainty from the Summary 

(Chapter  II)  and from the section on Long-Run 

Actuarial Estimates (Chapter  IV)  and recommends replacing the Summary chapter  presentation with sensitivity analysis for each of the 

key drivers of system finances. In addition, the 

Technical Panel recommends basing the selection 

of the low- and high-cost values for key assumptions on consistency – in a probabilistic sense – 

both across and within assumptions. In other 

words, it is essential to make certain that the 

low- and high-cost values for any given variable 

are equally likely alternatives with respect to the 

intermediate alternative, even if this implies an 

asymmetric range between the intermediate and 

the high- and low-cost assumptions. Further, 

the Technical Panel recommends ensuring that 

the likelihood of realizations within the range of 

outcomes is the same across all key assumptions. 

Presentation Recommendation P-3. The Technical 

Panel recommends adding a chapter  on uncertainty that explains, compares, and contrasts the 

high- and low-cost scenarios with integrated scenarios and stochastic simulation. The Technical 

Panel also recommends emphasizing that sensitivity analysis is the starting point for every measure of overall uncertainty and noting that any 

overall measure of uncertainty involves varying 

the combinations of key assumptions in particular ways. Each scenario and stochastic approach 

should be presented in a comparable way, specify 

how the key assumptions vary in each measure 

of overall uncertainty, and discuss the impact on 

various measures of system financial outcomes.

Section 1.2 Actuarial Metrics

Method Recommendation M-1. The Technical Panel 

recommends providing micro-level (individual) financial measures of the Social Security system in conjunction with macro-level (programwide) financial measures of the system.

Method Recommendation M-2. The Technical Panel 

recommends adding a subsection to Chapter IV, 

Section  B of the Trustees Report that provides 

more discussion and analysis of sustainable solvency.

Method Recommendation M-3. If the Trustees accept Recommendation M-2, then the Technical 

Panel recommends eliminating the Infinite Horizon metric.
126 2011 Technical Panel on Assumptions and Methods

Section 1.3 Models and Methods

Method Recommendation M-4. The Technical Panel 

commends OACT for its progress in increasing 

the transparency of its methods and in communicating detailed information to policymakers and 

the research community through its web site. The 

Technical Panel recommends maintaining and 

expanding these efforts in the coming years.

Method Recommendation M-5. The Technical Panel commends the Social Security Administration (SSA)  for investing in the development of 

matched data files that link survey information 

with administrative records on earnings and 

benefit receipt. The Technical Panel recommends 

making continued investments a high priority. 

Method Recommendation M-6. The Technical Panel 

recommends that SSA develop a strategic plan 

for expanding its dynamic microsimulation capacity and for integrating its segmented and 

microsimulation strategies. One objective of the 

strategic plan should be to increase coordination of dynamic microsimulation efforts within 

SSA in order to maximize existing resources. The 

Technical Panel recommends that the Social Security Advisory Board monitor progress on the 

development of these plans. The Board should 

consider convening or hosting a regular series 

of meetings of model developers within SSA and 

across various government agencies to review 

innovations, challenges, and prospects for collaboration. In deciding how to allocate scarce 

modeling resources, the Technical Panel recommends assigning a high priority to policies with 

potentially significant but uncertain effects on 

OASDI’s fiscal position.

Method Recommendation M-7. The Technical Panel 

recommends basing the intermediate projection 

of revenues from taxation of OASDI benefits 

more closely on the current income tax code rather than on historical shares of income subject to 

federal income taxation. The Technical Panel also 

recommends basing the projections of OASDI’s 

long-range actuarial status on two alternative 

sets of assumptions about future taxation that 

are analogous to “current law”/“extended baseline” and “current policy”/“alternative fiscal” 

scenarios, as is the practice of other government 

and private forecasting groups. At a minimum, 

the Technical Panel strongly recommends adding sensitivity analyses to the Trustees Report to 

demonstrate how projections of the long-range 

financial status of the OASDI program vary with 

alternative assumptions about laws governing 

personal income tax.

Section 1.4 Implications of Health Care Reform

Assumption Recommendation A-1. The Technical 

Panel recommends increasing the range of uncertainty around the major assumptions, including 

those regarding labor force participation and the 

earnings ratio, that are likely to be affected by 

health care reform. The expanded range reflects 

the uncertainty inherent in how health care reform will unfold. Over time, the extent of uncertainty is likely to narrow, at which point the recommended ranges for the affected assumptions 

will lend themselves to reduction.

Research Recommendation R-1. The Technical Panel 

recommends research into the impacts of health 

care reform on relevant outcomes as reform provisions start to take effect. Such outcomes include labor force participation, disability receipt, 

the earnings ratio, the taxable share, and mortality. The research findings should help determine 

the need for changes to the relevant assumptions 

and the need for adjustments to the range of uncertainty.

■ Chapter 2. Demographic 

Assumptions and Methods

Section 2.1 Fertility

Assumption Recommendation A-2. The Technical 

Panel recommends retaining the intermediate 

total fertility rate assumption of 2.0 from the 

2011 Trustees Report. The Technical Panel also 

recommends low- and high-cost total fertility 

rates of 2.2 and 1.6, respectively. We agree with 

previous Technical Panels that asymmetry in the 

range between the intermediate- and low- and 

high-cost values is appropriate, although our 

current estimate of such asymmetry is modest.
2011 Technical Panel on Assumptions and Methods 127

Section 2.2 Mortality

Presentation Recommendation P-4. The Technical 

Panel recommends summarizing the assumptions about future mortality in terms of life expectancy at birth at the end of the projection 

period rather than in terms of the average annual percentage reduction in total age- and sexadjusted death rates.

Method Recommendation M-8. The Technical Panel 

recommends simplifying the mortality projection model by eliminating separate projections 

by cause of death.

Assumption Recommendation A-3. The Technical 

Panel recommends increasing the intermediate life expectancy assumption to 88.7  years in 

2085, which is 3.7  years higher than the 2011 

Trustees Report’s assumption of 85.0  years. 

The Technical Panel also recommends low- and 

high-cost assumed life expectancies of 83.7 and 

93.7  years. The difference between these lowand high-cost assumptions is 10 years (93.7 minus 83.7  years)  compared with 7.7  years in the 

2011 Trustees Report; this range reflects the 

high degree of uncertainty about future mortality trends and the lack of agreement among experts about such trends.

Section 2.3 Immigration

Assumption Recommendation A-4. The Technical 

Panel recommends that immigration scenarios 

should tie the level of net immigration to historical evidence on net immigration and population 

size rather than decreasing or increasing constant numbers of immigrants. The Technical Panel recommends that the Trustees express their 

ultimate net migration assumptions as rates of 

the annual number of net migrants divided by 

population size.

Assumption Recommendation A-5. The Technical 

Panel recommends making the assumptions regarding future immigration more consistent with 

long-range historical averages for earlier periods. 

Specifically, the Technical Panel recommends that 

the intermediate assumption should ultimately 

be 3.2 net migrants per 1,000 persons. The Trustees’ current intermediate assumptions about 

net legal and net other immigrants in 2015 and 

assumptions about increases for 2015 through 

2025 may be appropriate based on current evidence, but the Technical Panel believes that net 

immigration levels beyond 2025 will not decline 

as reflected in the ultimate assumption for the 

remainder of the projection period. The Technical 

Panel also recommends that the low- and highcost assumptions should ultimately be 4.2 and 

2.2 net migrants, respectively, per 1,000 persons.

Section 2.4 Disability

Assumption Recommendation A-6. The Technical 

Panel recommends increasing the age-sex-adjusted disability incidence rate to 5.8 per 1,000 

insured workers, with somewhat larger increases 

for women and smaller increases for men; this is 

higher than the 5.2 per 1,000 rate assumed in the 

2011 Trustees Report. The Technical Panel also 

recommends low- and high-cost disability incidence rates of, respectively, 4.8 and 6.9. 

Assumption Recommendation A-7. The Technical 

Panel recommends a more rapid decline in DI 

mortality rates for both men and women from 

2020 through 2030 than is currently assumed. 

The effect of the recommended reduction on the 

age-adjusted mortality rate for men is a 15.7 percent lower mortality rate from 2030 through 

2085; for women, it is a 14.3 percent lower mortality rate during the same period. The recommended intermediate age-adjusted DI mortality 

rate for men in 2085 is 11.10 per 1,000 DI beneficiaries, which is lower than the currently assumed mortality rate of 13.20. The recommended intermediate age- adjusted DI mortality rate 

for women in 2085 is 8.20 per 1,000 DI beneficiaries, which is lower than the currently assumed 

mortality rate of 9.57. The recommended total 

age-sex-adjusted mortality rate in 2085 is 9.86, 

which is 13.7  percent lower than the currently 

assumed 11.42. The Technical Panel also recommends ultimate low- and high-cost total age-sexadjusted mortality rates of, respectively, 17.10 

and 6.30.

Assumption Recommendation A-8. The Technical 

Panel recommends reducing the assumed DI recovery rate from the currently assumed rate of 
128 2011 Technical Panel on Assumptions and Methods

10.7 per 1,000 DI beneficiaries to 8.7 per 1,000 

DI beneficiaries. The Technical Panel also recommends an increase in the range of uncertainty 

about the recovery rate, with low- and high-cost 

values of, respectively, 11.4 and 6.0 relative to 

the currently assumed low- and high-cost values 

of, respectively, 12.9 and 8.5.

Method Recommendation M-9. The Technical Panel 

recommends expanding the discussion of the factors leading to the projected decline in the share 

of DI-insured men and careful monitoring of the 

share to see if the recent declines among younger men carry forward to men at older ages. The 

Technical Panel notes that similar discussion and 

monitoring are warranted given the projection 

that the steady rise in the share of DI-insured 

women will level off in the short term.

Method Recommendation M-10. The Technical Panel 

recommends exploring in greater depth the effect of diagnoses of DI recipients on program exit 

rates because of recovery or death. The Technical Panel recommends similar exploration for the 

projected share exiting DI because of conversion 

to retired worker benefits.

Presentation Recommendation P-5. The Technical 

Panel recommends presenting more detail on the 

programmatic, economic, and health factors that 

drive DI applications and how the factors are assumed to change in the future.

■ Chapter 3. Economic Assumptions 

and Methods

Section 3.1 Labor Force Participation Rate

Method Recommendation M-11. Consistent with 

Recommendation P-1, the Technical Panel recommends characterizing labor force participation 

rates as a basic assumption with a meaningful 

range of uncertainty. Labor force participation 

rates should also be part of the formal sensitivity 

analyses currently presented in Appendix D.

Assumption Recommendation A-9. The Technical 

Panel recommends increasing the assumed labor force participation rates with intermediate values of 75.0 for men and 61.9 percent for 

women in 2085; these rates are higher than the 

currently assumed values of 72.9  percent for 

men and 60.8 percent for women. Together, the 

recommended values would raise the age-sexadjusted labor force participation rate from 66.6 

to 68.2 percent. The Technical Panel also recommends a substantial increase in the range of uncertainty about labor force participation, with 

low- and high-cost age-sex-adjusted participation rates of, respectively, 70.3 and 64.8 percent 

in 2085.

Method Recommendation M-12. The Technical Panel 

recommends moving toward a heuristic life-cycle 

approach for projecting labor force participation 

by age and sex. Ultimately, labor force participation should be driven by life-cycle–specific labor 

supply measures such as typical age of first entry, percentage of the working-age population in 

the labor force, age of primary job exit, and fraction of the retired population still working. The 

Technical Panel’s recommended intermediate-, 

low-, and high-cost values above are based on 

consideration of labor force participation across 

eight age/sex groups and thus represent a move 

in the desired direction.

Section 3.2 Real Wage Growth Rate

Assumption Recommendation A-10. The Technical 

Panel recommends retaining the productivity 

growth rate of 1.7  percent per year assumed in 

the 2011 Trustees Report. The Technical Panel 

also recommends retaining the currently assumed low- and high-cost values of 2.0 and 

1.4 percent, respectively.

Assumption Recommendation A-11. The Technical 

Panel recommends retaining the intermediate 

assumption of a 0.0 percent annual growth rate 

for the compensation share of GDP. The Technical 

Panel further recommends introducing uncertainty about this parameter. Specifically, starting 

from a current value of 54.5 percent for the compensation ratio, the Technical Panel recommends 

low- and high-cost values of, respectively, 56 and 

53  percent over the projection period. Growth 

rates of, respectively, 0.1 and -0.1  percent per 

year for 25  years in the low- and high-cost scenarios would generate the suggested range in the 

compensation ratio.
2011 Technical Panel on Assumptions and Methods 129

Assumption Recommendation A-12. The Technical 

Panel recommends setting the annual growth 

rate for the earnings to compensation ratio at 

0.0  percent in the intermediate-cost scenario, 

an increase from the current assumption of 

-0.1  percent. The Technical Panel also recommends low- and high-cost annual growth rates 

of, respectively, 0.1 and -0.1  percent per year, 

which yield an ultimate range for the earnings to 

compensation ratio of 77 to 89 percent relative 

to a starting value of 83 percent. The adjustment 

for the effects of health care reform made in the 

2010 Trustees Report (+0.1 percent per year) is 

reasonable and should be maintained, pending 

direct observation of the law’s impact in the coming years. The Technical Panel’s recommendation 

of an intermediate-cost assumption of 0.0  percent incorporates such adjustment.

Assumption Recommendation A-13. The Technical 

Panel recommends retaining the intermediatecost assumption of 0.0  percent for the annual 

change in hours worked. For the low-cost scenario, the Technical Panel recommends a slight 

increase of 0.05 percent per year in hours worked 

over the 75-year period. Recognizing a greater 

risk of a decline in hours worked, the Technical 

Panel recommends a reduction in annual hours 

of -0.15 percent per year for the 75-year period 

in the high-cost scenario.

Assumption Recommendation A-14. The Technical 

Panel recommends reducing the magnitude of 

the intermediate-cost assumed GDP-CPI price 

differential to -0.2  percent per year, relative to 

the currently assumed -0.4  percent price differential. The Technical Panel also recommends 

low- and high-cost price differentials of -0.1 and 

-0.3 percent, respectively.

Assumption Recommendation A-15. Taken together, the Technical Panel’s recommendations A-10 

through A-15 for productivity growth and the 

four linkages generate an intermediate real wage 

growth rate of 1.5  percent per year in  years 25 

through 75, with low- and high-cost values of, respectively, 2.05 and 0.85 percent. Over the first 

25 years, our recommendations also generate an 

intermediate real wage growth rate of 1.5  percent, but with low- and high-cost values of, respectively, 2.15 and 0.75 percent per year.

Section 3.3 Unemployment Rate

Assumption Recommendation A-16. The Technical 

Panel recommends retaining the assumed ultimate long-run unemployment rate of 5.5 percent 

from the 2011 Trustees Report. The Technical 

Panel also recommends retaining the low- and 

high-cost assumed unemployment rates of, respectively, 4.5 and 6.5 percent.

Section 3.4 Interest Rates

Assumption Recommendation A-17. The Technical 

Panel recommends reducing the assumed longrun real interest rate to 2.7 percent. The rate is 

lower than the 2.9 percent long-run real interest 

rate assumed in the 2011 Trustees Report and 

more in line with market-based forecasts derived 

from current yields on inflation-protected Treasury securities. The Technical Panel recommends 

retaining the low- and high-cost values of, respectively, 3.6 and 2.1 percent for the real interest rate.

Method Recommendation M-13. The Technical Panel 

reiterates the recommendation of the 2007 Technical Panel that the approach to determining real 

and nominal interest rates should place greater 

weight on the forward-looking information in recent Treasury yield curves.

Section 3.5 Inflation

Assumption Recommendation A-18. The Technical 

Panel recommends retaining CPI-W inflation at 

2.8  percent in the intermediate-cost scenario. 

The Technical Panel also recommends retaining 

the low- and high-cost values of, respectively, 1.8 

and 3.6 percent.

Assumption Recommendation A-19. The Technical 

Panel recommends setting the nominal interest 

rate to 5.5 percent in the intermediate-cost scenario, based on a 2.8 percent inflation rate and 

a 2.7  percent real interest rate. The Technical 

Panel also recommends a low-cost nominal interest rate of 5.4 percent (1.8 percent inflation plus 

3.6  percent real interest rate)  and a high-cost 
130 2011 Technical Panel on Assumptions and Methods

nominal interest rate of 5.7 percent (3.6 percent 

inflation plus 2.1 percent real interest rate).

Section 3.6 Taxable Share of Covered Wages

Assumption Recommendation A-20. The Technical 

Panel recommends the brief continuation of the 

downward trend in the taxable share of covered 

wages as the economy fully recovers from the 

recession and then reaches an ultimate level of 

82.2  percent. The Technical Panel also recommends significantly expanding the range of uncertainty around the taxable share given that 

the taxable share could continue to shift rapidly 

in the coming years. The Technical Panel recommends a low-cost value of 84.3  percent and a 

high-cost value of 80.0  percent, a range that is 

modestly asymmetric around the recommended 

intermediate value.

Method Recommendation M-14. The Technical Panel 

recommends consideration of a formal linkage 

between the assumed earnings to compensation 

ratio and the taxable share.

Method Recommendation M-15. Consistent with 

Recommendation P-1, the Technical Panel recommends characterizing the taxable share as 

a basic assumption with a meaningful range of 

uncertainty. It should also be part of the formal 

sensitivity analyses currently presented in Appendix D.


Social Security Advisory Board

400 Virginia Avenue, SW Suite 625

Washington, D.C. 20024

T (202) 475-7700

F (202) 475-7715

info@ssab.gov