report to the 

Social Security Advisory Board

2007 Technical Panel on

 Assumptions and Methods
Members of the Panel

Dan L. Crippen, Chair

Director, Congressional Budget Office, 1999-2003

Mary C. Daly 

Vice President, Applied Microeconomic Research and Regional Development, 

Director, Center for the Study of Innovation and Productivity

Federal Reserve Bank of San Francisco 

Robert J. Gordon 

Stanley G. Harris Professor of the Social Sciences 

Department of Economics, Northwestern University

William Hsiao

K.T. Li Professor of Economics 

Department of Health Policy and Management, 

Program in Health Care Financing Harvard School of Public Health

Steve Lieberman

Partner, The Moran Company

Deborah J. Lucas

Donald C. Clark/Household International Distinguished Professor of Finance

Kellogg School of Management, Northwestern University

Jeffrey S. Passel 

Senior Research Associate, Pew Hispanic Center

Beth Soldo

Director, Population Aging Research Center; Distinguished Senior Scholar, Sociology

Research Associate, Population Studies Center

University of Pennsylvania

P.J. Eric Stallard 

Research Professor and Associate Director for Management and Planning

Center for Demographic Studies, Duke University

Shripad Tuljapurkar 

Morrison Professor of Population Studies and Professor of Biological Sciences

Stanford University

This report may be cited as:

Technical Panel on Assumptions and Methods (2007).

Report to the Social Security Advisory Board. Washington, D.C.,

October 2007
2007

Technical Panel Report

on Assumptions and Methods

report to the Social Security Advisory Board

October 2007

Table of Contents 

Charter i

Introduction iii

Executive Summary 1

I. Methodology 13

A. Transparency 14

B. Uncertainty 15

C. Modeling 16

D. Presentation 19

II. Demographic Assumptions and Methods 23

A. Fertility 23

B. Mortality 29

C. Immigration 38

D. Disability Incidence and Termination 55

III. Economic Assumptions and Methods 59

A. Labor Force Participation Rate 59

B. Unemployment 62

C. Real Wage Growth 62

 1. Productivity Growth 63

 2. Compensation to GDP Ratio 66

 3. Earnings to Compensation Ratio 66

 4. Average Hours of Work 69

 5. GDP Deflator/CPI Growth Rate Differential 70

D. CPI Growth 73

E. Interest rates 75

F. Taxable Share of Covered Wages 81

References 85

Compilation of Technical Panel Recommendations 91

2007 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 funds. 

Specifically the Panel is asked to:

n Review the assumptions regarding key demographic factors, including mortality, fertility, 

immigration and disability incidence and termination.

n Review the assumptions regarding key economic factors including productivity, real wage 

growth, real net rates of return and variations 

in net rates of return (including equity returns), 

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

n Review and assess the projection methodology including other methodologies currently in 

use.

n Review in particular the trends in the earnings to total compensation ratio in light of the 

changing structure and cost of employee benefits including pensions, health and disability 

insurance.

n Review and assess the status of the recommendations of the 2003 and 1999 Technical 

Panel(s).

2007 Technical Panel on Assumptions and Methods iii

Introduction

For the third time since 1999, the Social Security Advisory Board has appointed a Technical 

Advisory Panel to examine the assumptions specified by the Board of Trustees and the methods 

used by the Office of the Chief Actuary each year 

to project the future financial status of the Social 

Security trust funds. 

The Advisory Board has invited some of the best 

actuaries, demographers, economists, and statisticians in the United States to provide an independent review of the very complex and important 

work that goes into the annual Social Security 

Trustees Reports. This report is the culmination 

of more than a year-long effort, begun in August 

2006, to offer critical yet constructive recommendations on how to improve policy makers’ and the 

public’s understanding of the long-range future of 

the Social Security programs. 

Our report makes some sweeping recommendations on many of the methodologies employed by 

the Office of the Chief Actuary, as well as suggestions for significant changes of several of the Trustees’ assumptions, particularly immigration and 

mortality. The Panel recommends that more emphasis be placed on explaining the inherent uncertainty of the long-range projections and suggests 

adopting the use of asymmetrical risk for several of 

the estimates. 

We believe the Trustees and actuaries must place 

a higher priority on more comprehensive estimation techniques, and greatly expand the use of 

methods that will help explain behavioral responses to policy changes as well as allow more thorough 

analysis of outcomes on particular populations.

We also recommend that the documentation of 

the methods presently used by the Office of the 

Chief Actuary, begun this year as part of a required 

audit, be continued and expanded. In addition, 

data employed in the estimation process needs to 

be made public (with appropriate safeguards for 

confidentiality). Ultimately, analysts outside the 

Social Security Administration should be able to 

nearly replicate the estimates produced in the annual Trustees Reports. Only then will the larger 

community of interest be able to contribute to the 

evolution of techniques to accomplish this very 

daunting task...producing economic and demographic projections for the next 75 years. 

This report reflects the dedicated work and 

well-considered recommendations of the entire 

Technical Panel. This report is truly the result of 

a group effort, and represents a consensus born 

of mutual respect and patience over the course of 

many months. Beth Soldo, Eric Stallard, and Shripad Tuljapurkar provided guidance and drafting 

for the sections on demography. Mary Daly and 

Deborah Lucas did much of the work on disability, 

labor force participation, and interest rates, as well 

as other economic issues, and provided assistance 

with drafting and editing. Robert Gordon contributed the sections on productivity, real wage growth 

and inflation. Jeff Passel guided us through the 

immigration thicket—and some of his work has already been adopted by the Trustees. William Hsiao 

and Steve Lieberman provided the insight and inspiration for much of our discussion of methodology, with substantial contributions from everyone 

on the Panel.

Our work would not have been possible without 

the patient tutoring of the Social Security Administration’s Chief Actuary, Stephen Goss, and the 

many capable people working with him including 

Deputy Chief Actuaries Alice Wade (long-term) and 

Eli Donkar (short term), as well as Al Winters and 

Pat Skirvin. All of the projections in this report 

were provided by the Office of the Chief Actuary.

We consulted several experts in the use of alternative long-range projection methodologies and 

would like to thank John Sabelhaus and Noah Meyerson of the Congressional Budget Office’s Longterm Modeling Unit; Martin Holmer of the Policy 

Simulation Group; Howard Iams, David Pattison 
iv 2007 Technical Panel on Assumptions and Methods

and Clark Burdick of the Social Security Administration’s Office of Research Evaluation and Statistics for their generous insight and assistance. Joyce 

Manchester, who was then the director of the Social Security Administration’s Division of Economic 

Research, was especially generous in lending assistance to the Panel on numerous issues including 

modeling methodology.

The Panel is also grateful for the assistance of 

Professors Ron Lesthaeghe, Hans-Peter Kohler, and 

S. Philip Morgan who took time from their busy 

schedules to conduct a one day symposium on the 

topic of the long-range future of fertility trends in 

the United States. Professor Mark Duggan helped 

the Panel gain a better understanding of trends in 

disability while Dixie Sommers, an Assistant Commissioner at the Bureau of Labor Statistics briefed 

the Panel on that agency’s methods for projecting 

labor force participation. 

The Panel benefited greatly from frank and spirited conversations with the two Public Trustees of 

the Social Security Board of Trustees John L. Palmer and Thomas R. Savings. Their liaison from the 

Social Security Administration, Mike Leonesio, was 

very helpful in setting up that meeting. The Panel 

also appreciates the opportunity to brief the numerous public servants who make up the Trustees’ 

working group chaired by Treasury Department 

Assistant Secretary for Economic Policy Phillip L. 

Swagel. Jim Duggan, senior economist at the Treasury Department greatly facilitated that meeting.

In an effort such as this, there are always a great 

many who contribute, but none more so than Joel 

Feinleib, the Panel’s Executive Director, and the 

Advisory Board’s staff economist. We would like to 

thank the entire staff of the Social Security Advisory Board for their excellent support.

Finally, the Panel acknowledges the work of the 

1999 and 2003 Technical Panels. We studied their 

reports, consulted some of their members, and examined the progress on the recommendations they 

had made. We have reiterated some of their previous 

suggestions that have not yet been implemented.

-Dan L. Crippen, Chair
2007 Technical Panel on Assumptions and Methods 1

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.

The operation of the Social Security system is determined by several key demographic and economic variables including: fertility, mortality, immigration, disability, labor force participation rates, 

unemployment rate, real wage growth, consumer 

price index (CPI) growth, and the real interest rate.

In order to project these variables into the future, 

the Office of the Chief Actuary (OCACT) must have 

models, implicit or explicit, for each variable, and 

one or more assumptions must be made to reach ultimate conclusions. As with any analytical exercise, 

the assumptions, the models, and the methodology 

to estimate the model parameters are all critical elements of the process. 

n Methodology

We chose to begin our report with observations 

on the methods and data used by OCACT and the 

Trustees, rather than on specific assumptions, for 

several reasons. The most obvious is that a change 

in method might have a more lasting impact on 

future projections than a change in any particular 

point estimate we could recommend. It is quite 

easy, in fact, to take narrow issue with any particular estimate, but more difficult to understand and 

examine the methods used to produce it. Because 

of the inherent uncertainty in long-range projections, the validity of the estimation process is arguably as important as any specific result.

The methodological challenge is to assess the financial soundness of the Social Security program. 

The future income and cost of Social Security must 

be estimated in such a way that allows the Trustees 

to: (1) examine the likely financial results of the system, including: year-by-year cash flows, the annual 

balance in the trust fund, and the actuarial balance 

at the end of the 75-year period; and, (2) describe 

the uncertainty of the forecasts. In addition, policy 

makers and the public may also wish to understand 

the distributional impact of any proposed change to 

the Social Security program. Technical experts may 

also wish to evaluate the reasonableness of the variables that are used to forecast the future financial 

changes, particularly the interaction and consistency between the different economic, social and 

demographic variables.

The state of actuarial science appears to be rapidly evolving beyond the cell-based models generally employed by the Social Security actuaries, to 

more explicitly incorporate interactions between 

economic and demographic variables and to better 

understand the uncertainty in the projections. The 

increase in computing power alone makes possible 

many analyses that were previously impractical, 

and allows additional data to be incorporated. 

New data sources are also emerging. Recent research using longitudinal data such as the Health 

and Retirement Survey (HRS) and the Survey of 

Income and Plan Participation (SIPP) linked to micro-level Social Security earnings data have yielded 

significant insights on disability, health and retirement dynamics. This potent combination—advanced computing, more and better data, and new 

methods—holds the prospect of significant advances in the analysis required for social programs 

and their associated trust funds.

Many of this Panel’s methodological recommendations—transparency, the use of micro-simulation 

and stochastic analyses, specifying and estimating 

interactions, employing additional data—are not 

new. Previous Technical Panels and other experts 

have made similar recommendations. What is new, 

perhaps, is that the actuaries have made some progExecutive Summary
2 2007 Technical Panel on Assumptions and Methods

ress on many of these fronts. There are reasons to 

be impatient, however. New computing power, new 

sources of data, and new estimating techniques 

should allow OCACT to make faster progress in 

advancing their models and methods. Indeed, others within government, ranging from the Office of 

Policy within the Social Security Administration 

(SSA) to non-executive branch agencies such as the 

Congressional Budget Office (CBO), are exploiting 

these developments and creating the means to analyze the system and its response to change. Only by 

aggressively deploying new data and techniques and 

by making the process more transparent can OCACT and the Trustees remain the definitive sourceof-record for this information.

There also appears to be an understandable reluctance by the Trustees to make significant changes to 

their projections in any given year. Rather, methodological changes that produce significant changes in 

point estimates are phased in, or offset with changes 

in other variables. Nonetheless, the Actuarial Standards of Practice, specifically Standard No.32: “Social 

Insurance”1

, suggests that new information should 

be incorporated when it is found, even if such information creates some discontinuities in the forecasts: 

“The actuarial assumptions, both individually and in 

combination, should reflect the actuary’s best judgment, taking into account anticipated future events 

affecting the related social insurance program.”

While OCACT is exploring new ways of augmenting their traditional methods, the adoption appears 

to us to be slow. Recommendations of previous advisory panels seem to have languished. As a result, 

important information in the estimating process 

may be lost. What follows is a series of comments 

that generally apply across the set of variables for 

which OCACT makes projections. 

A. Transparency

Throughout this report we call for more transparency in the models and data the actuaries use, 

as well as the assumptions that drive their results. 

This recommendation is perhaps the most important one we can make. Only with more transparency can other social scientists interested in retirement, Social Security, and the various related 

issues, bring their intellect to bear on the many 

complex questions the Trustees and actuaries face. 

Only by a clear articulation of their assumptions 

can the actuaries’ work be truly examined, and 

only by a clear understanding of the nature of trust 

fund accounting can the public be assured of the 

veracity of statements made about the program.

It is worth noting that all analytical agencies, 

whether the National Aeronautics and Space Administration (NASA), CBO, or OCACT, must make 

assumptions about behavior or phenomena that are 

unobservable or immeasurable. In the process, the assumptions become deeply embedded and the models 

closely guarded; and these agencies are understandably reluctant to revisit their assumptions or reveal 

methods. Nonetheless, it is essential to do so. First, 

accountability requires it—such is the nature of the 

nascent documentation external auditors recently 

required of OCACT. Second, and more important, 

ongoing comprehensive, external review can greatly 

assist the quality of the analytical exercise. 

Transparency of the OCACT models will require several developments: (1) providing more comprehensive 

documentation, (2) making data from SSA records 

more available, (3) creating explicit models where 

none exist, and (4) clearly explaining the processes 

employed. The ultimate test of transparency is whether the actuaries’ results can be essentially replicated. 

To this end, we recommend that the Social Security Advisory Board, to whom this Technical Panel 

reports, should hold semi-annual meetings with 

OCACT to discuss progress on the various recommendations contained in this report as well as 

those from previous panels. 

B. Uncertainty

The current approach to uncertainty of projections 

in the Trustees Report, using high-, medium- and lowcost “scenarios” or “variants” to indicate the range of 

plausible outcomes is a traditional one whose limitations are well-known. The current practice of assuming that all variables could simultaneously move in a 

low- or high-cost direction produces estimates that 

lack both an intuitive and a statistical interpretation. 

The temptation to assign probabilities to the scenarios or to suggest their degree of likelihood should be 

resisted. Previous Technical Panels have consistently 

drawn attention to the limitations of the variant approach. For example, the 1999 Technical Panel noted 

that using high and low alternatives: (1) assumes 

trajectories are always high or always low; (2) combines trajectories of various assumptions in rigid 

ways, for example, all are set at their high-cost value 

simultaneously; (3) ignores that different aspects of 1 Actuarial Standards Board, “Actuarial Standards of Practice No. 

32: Social Insurance,” January 1998.
2007 Technical Panel on Assumptions and Methods 3

the high and low scenarios have different levels of 

uncertainty, and (4) does not assign any probability 

to the forecast ranges.2

 We offer one additional observation: there is no requirement for symmetry of 

uncertainty—that the forecast be plus-or-minus an 

equal amount along the projection. Indeed, many key 

drivers have asymmetrical uncertainty as succeeding 

chapters will show, and the nature of the uncertainty 

may well change with the forecast horizon.

Stochastic analysis, on the other hand, produces 

uncertainty bands that are much easier to interpret. 

Critically, stochastic analysis can incorporate correlations between variables, and allows ranges to be 

given a probabilistic interpretation. Although, the 

actuaries have developed a stochastic model that is 

used to augment the use of scenarios to analyze uncertainty in the Trustees Report, those results appear more as an addendum than as an integral part 

of the analysis. The Panel therefore recommends 

using the results of the stochastic analysis to augment if not supplant the high- and low-cost scenarios, and to communicate the range of uncertainty 

around the intermediate projections. 

In addition to the increased use of stochastic analysis, there are other ways to use scenarios that can 

be more useful as a way to explore focal alternatives. 

For example, projecting internally consistent and 

plausible scenarios (although not necessarily the 

most likely ones) would make the range of possible 

outcomes easier to interpret and communicate. In 

this report we illustrate two new projection scenarios combining (1) relatively high cost demographic 

assumptions but intermediate cost economic assumptions, and (2) relatively low cost economic but 

intermediate cost demographic assumptions.

Uncertainty grows as the projection period 

lengthens. But we find that the practice of discounting summarized balances at a risk-free rate inherently over-weights the more uncertain periods 

of the projection. As a result, the analysis of the 

“long-run” may well cause critical medium-term 

policy implications to be overlooked.

C. Modeling—Use of Alternative Approaches 

to Modeling for Projections—the Case for 

Micro-Simulation

Models are developed for different purposes; and 

therefore, any particular model should be judged based 

on its validity, accuracy and reliability in accomplishing its stated purpose. Also, a model should be flexible 

enough for changes in assumptions and policies to be 

explored and evaluated. Since no single model is likely 

to achieve all of these objectives equally well, we believe it is imperative for OCACT to accelerate its development and incorporation of new models to augment 

its cell-based approach to projections. 

With the advent of increased computing power 

and better data, micro-simulation models have become important tools for analyzing policy changes 

and accounting for behavioral relationships. Several research and government agencies currently use 

such models to evaluate the effects of demographic, 

economic and policy changes related to the Social 

Security system. Although not a panacea, these 

models have proven helpful in examining a wide 

range of issues of interest to policy makers and 

analysts.3

 Moreover, by explicitly accounting for interactions across variables, micro-simulation models increase transparency around key assumptions 

underlying the cell-based projections, encouraging 

debate and discussion about these assumptions 

within the research and policy community.

The individual-based nature of these models 

makes them useful tools to: analyze the distribution 

of the effects of policy changes (e.g., across income); 

explicitly model and incorporate interactions between variables; make long-term projections; and, 

test alternative assumptions. Micro-simulation 

models are useful for tracing the behavior of individuals and families over time under varying and 

complex changes in economic and policy variables. 

Micro-simulation can improve forecast quality when 

changes in the cross-section over time affect macroeconomic outcomes and thereby system finances. 

Micro-simulation is most appropriately used 

when interactions are important and tractable. 

While it is relatively easy to gain agreement on the 

importance of interactions, the tractable test is 

somewhat more difficult to pass unanimously. Like 

all models, the behavior embedded in micro-simu2 Technical Panel on Assumptions and Methods (1999), Report to 

the Social Security Advisory Board, November, 1999, p. 7.

3 These include long-term financing (CBO, Updated Long-Term 

Projections for Social Security, June 2006); the impact of differential 

mortality improvement on Social Security’s progressivity (CBO, 

“Is Social Security Progressive?” Economic and Budget Issue Brief, 

December 12, 2006); the distributional effects of benefit changes 

(GAO-08-26, Social Security Reform: Issues for Disability and Dependent Benefits, October 26, 2007; Congressional Research Service, 

Options to Address Social Security Solvency and Their Impact on Beneficiaries: Results from the Dynasim Microsimulation Model, Report 

RL33840, January 29, 2007); and the costs of competing reform 

proposals (CBO, “Long-Term Analysis of the Liebman-MacGuineasSamwick Social Security Proposal”, February 8, 2006).
4 2007 Technical Panel on Assumptions and Methods

lation models requires a set of assumptions about 

how these interactions arise. Mathematical equations determine which individuals: become disabled 

in a given year; enter, remain in, or exit the work 

force; have earnings that rise or fall; immigrate (or 

emigrate); “marry” (assigning them spouses with 

certain characteristics); have children; divorce; 

claim Social Security benefits; and, ultimately, die. 

Although each of these decisions is typically based 

on the best available data, research and analysis, 

the complexity of modeling and the gaps in our understanding and practical limitations create some 

uncertainty about the reliability and accuracy of 

micro-simulation projections. Although the same 

types of decisions are also being made in the cellbased model, they are just not made explicit. 

The general advances over the past several decades in social science, computational capability, 

data, and modeling, coupled with an increased interest in Social Security and its long-range solvency, have created a rich environment for testing the 

plausibility of modeling decisions and techniques, 

collaboration with outside experts, and peer review. We favor approaches which rely on explicit, 

rather than implicit, relationships and assumptions. We believe that the advantages associated 

with micro-simulation, especially when taken in 

concert with our other recommendations, strongly argue for increased investment in and reliance 

on a single (integrated) micro-simulation model 

as a key tool in OCACT projections for the Trustees. We are not of the view that micro-simulation 

should be used to replace the cell-based approach, 

but rather to augment it by increasing the understanding of the interrelationships and impacts of 

the system on individuals, and to add transparency 

to the many implicit assumptions made in the cellbased models.

D. Presentation

At the nexus of transparency and clear exposition of uncertainty are a number of recommendations that have more to do with the presentation of 

the results, which apply regardless of the modeling 

techniques employed.

Near vs. Long-Term

While it is clearly reassuring to address the longterm (including the impulse to assure the public of 

“sustainability” for an infinite horizon), it is more 

important to be straightforward about what is reasonably “knowable” and what remains highly speculative. Although we know (relatively) a lot about 

beneficiaries and workers for the next 25 years, substantial uncertainty still remains, for example, the 

rate of immigration. In contrast, 75 years into the 

future is far more uncertain; the longer the projection period, the more likely uncertainty exists. The 

single point estimates associated with distant horizons may yield a false sense of precision; and the 

casual use of these estimates can be misleading.

Despite the fact that Trustees are required to report on system finances over a 75-year horizon, they 

have the discretion to focus greater attention on longer or shorter time periods. The Panel recognizes that 

there are pros and cons of emphasizing long-horizon 

forecasts. On balance we believe that for analysis of 

the trust funds the disadvantages of very long-range 

forecasts outweigh the advantages, and we recommend that for the annual Trustees Report emphasis 

be further shifted toward the intermediate term of 25 

years. In addition, more emphasis should be placed 

on the use of annual cost and income rates, and away 

from long-term measures including the 75-year summarized balance.

There are circumstances, however, when longer 

horizons are necessary to understand the dynamics of major policy changes—important effects may 

not appear until a generation or more in the future. 

For example, a change from pay-as-you-go funding to something akin to pre-funding would likely 

require a long transition period and the full effects 

would not be manifest until well beyond 75 years. 

For this purpose, a horizon of 150 years or more 

may be appropriate.

International Comparisons

As will be evident in succeeding chapters, we 

believe that comparisons with other countries, especially the developed and aging “industrialized” 

nations, provide valuable insights. Despite the fact 

that we do not fully understand the cause of many 

of the disparities, the fact that the consistent experience abroad is quite different from ours suggests 

the possibility of convergence; perhaps they will all 

gravitate toward us but the possibility of the opposite deserves consideration.

Forecasting Record

We believe that the accuracy of past projections 

should be the subject of routine reporting, either 

in the Trustees Report or in separate supplemen-
2007 Technical Panel on Assumptions and Methods 5

tal publications on methodological developments. 

There should be an analysis of the accuracy of past 

10-, 20-, and 30-year projections similar to those 

periodically done by the Census, Bureau of Labor 

Statistics (BLS), and the Congressional Budget Office. The report should include a comparison of historical values with projected high-cost and low-cost 

scenario variants, noting how often each variable 

exceeded past projected outer bounds.

Use of Graphs and Charts

Advances in computing make it easier to include 

more graphs and charts that incorporate large 

amounts of seemingly unrelated data. For example, graphical techniques such as fan charts convey 

more information than the high-cost and low-cost 

scenarios. Just as a predicted hurricane track is 

bounded by a cone of uncertainty, so too can the 

projections of trust fund components be shown 

with individual and collective bounds over time.

Nature of Trust Funds

Despite the use of a “trust fund,” almost from its 

inception, the Social Security program has been essentially pay-as-you-go, with payroll tax collections 

funding current benefits, and not accumulating 

“savings” for the future. The trust fund does not 

hold a store of value equal to future obligations. In 

that sense, it is not “fully-funded” as we think of 

private retirement plans.

Trust fund balances, and the dates of trust fund 

“exhaustion,” continue to receive prominence in 

the Trustees Report. Surprisingly little, however, 

is said in the introductory sections about what the 

trust funds represent, beyond saying that the securities held are a firm obligation of the U.S. Treasury. Although the broader significance of the trust 

funds is a difficult issue that the Trustees rightly 

sidestep, there are basic facts about trust fund accounting that are a prerequisite for understanding 

the report. It is important to convey, at the beginning of the report, that the trust fund functions as 

an accounting mechanism and to explain how that 

mechanism works. The trust fund limits the legal 

authority to pay benefits. Paying benefits from 

trust fund “assets” requires increasing taxes, borrowing, or cutting other federal spending, as would 

be the case if there were no trust fund. 

Furthermore, the trust fund is never completely 

“exhausted” as the usual connotation implies. Even 

when the balance reaches zero, there will be a flow of 

revenues that can be used to make payments—about 

70 percent of the payments under current projections. The trust fund is more like a checking account 

and will have “insufficient funds” by mid-century; 

today’s workers are making deposits to cover the 

checks currently being written to their parents. Our 

children will do the same for us, except there will be 

fewer of them to make deposits, and come 2042 or 

thereabouts, the account will not have enough deposits to cover full payment on all the checks.

Resources for Development

Implementing even some of our recommendations 

will require more resources for OCACT. However, 

it is not necessary for the actuaries to accomplish 

all model development in OCACT. With increased 

transparency, academic and other research centers 

can make meaningful contributions from outside 

government. Similarly, much of the work of the SSA 

Office of Policy could be incorporated more readily 

than is the current practice. Other governmental 

agencies, such as the CBO and the Government Accountability Office (GAO), could assist in evaluating 

the productivity and efficacy of specific analytical 

alternatives, even to the point of sharing computer 

code. The actuaries could use outside developers to 

replicate or augment their existing models.

E. Specific Assumptions

Table 1 lists our recommendations for the 15 demographic and economic assumptions made by the 

Trustees and used by OCACT in their projections. For 

many of the variables, we concluded that the Trustees’ 

current intermediate assumptions are reasonable, but 

believe that the risk of error is not symmetrical around 

this “best guess.” For several, we found ample evidence 

to suggest a change at least to the intermediate assumption, and often the high- and low-cost estimates 

as well. Where we do make suggestions for changes in 

assumptions in the key variables used to project trust 

fund finances, we must confess that, like OCACT, we 

did not have a complete structural model to provide an 

alternative estimate. However, evidence for a change 

in immigration, mortality, CPI, and interest rates is 

compelling. Ultimately, the evidence for the direction of change is more important than the absolute 

amount. As with the Trustees’ estimates, the apparent precision of these assumptions, down to 1/10 of 1 

percent of payroll, belies the large underlying numbers 

and great uncertainty inherent in each.
Table 1: Summary of Assumption Recommendations

Assumptions Source Low Cost Intermediate High Cost

Total Fertility Rate Recommended 2.1 no change 1.5

TR2007 2.3 2.0 1.7

Mortality (Avg. Annual decline)

(all ages, both sexes)

Recommended no change 1.00% 2.00%

TR2007 0.33% 0.70% 1.21%

Net Immigration Recommended Starting 1.35mil in 2007 1.35mil in 2007 1.35 mil in 2007 

1.1 mil in 2011*

Recommended Annual 

growth rate

2.1% 1st 25yrs 

0.5% next 50yrs

1.0% 1st 25yrs 

0.5% next 50 yrs

2012-2081: 

0.25% Legal 

0.5% “Other”

 Annual flow in 2081 2,820,000 2,189,000 1,437,000

 Ult. Net Migration Rate 4.6 4.2 3.0

 TR2007 (ultimate)** 1,300,000 900,000 672,500

 Ult. Net Migration Rate 2.5 2.1 1.9

Disability Incidence

(per 1000)

Recommended 4.6 no change 6.9

TR2007 4.4 5.5 6.6

Disability Termination no change no change no change

Labor Force Participation Rate age-adjusted percentage rates for ages 16 and over

Recommended ***M:77 W: 65 no change no change

TR2007 M:72.8 W:60.6 M:73.3 W:60.8 M:73.9 W:60.9

Unemployment Rate Recommended no change no change no change

TR2007 4.5 5.5 6.5

Components of Real Wage Growth:

 Productivity Growth Recommended no change no change 1.1%

TR2007 2.0% 1.7% 1.4%

 Compensation to GDP ratio Recommended no change no change no change

TR2007 0% 0% 0%

 Earnings to Compensation ratio (1st 25yrs, next 50yrs):

Recommended 0.0%, 0.1% -0.1%, 0.0% -0.2%, -0.1%

TR2007 -0.1%, -0.1% -0.2%, -0.2% -0.3%, -0.3%

 Hours worked (1st 25yrs, next 50yrs):

Recommended 0.0%, 0.1% -0.1%, 0.0% -0.2%, -0.1%

TR2007 0.1%, 0.1% 0.0%, 0.0% -0.1%, -0.1%

 GDP deflator-CPI Recommended -0.2% -0.2% -0.2%

TR2007 -0.4% -0.4% -0.4%

Net Real wage growth (1st 25yrs, next 50yrs):

Recommended 1.8%, 2.0% 1.3%, 1.5% 0.5%, 0.7%

TR2007 1.6%, 1.6% 1.1%, 1.1% 0.6%, 0.6%

CPI growth Recommended 1.5% 2.5% 3.5%

TR2007 1.8% 2.8% 3.8%

Real interest rate

(nominal less CPI)

Recommended 3.3% 2.6% 1.8%

TR2007 3.6% 2.9% 2.1%

* Decline from 1.35 million to 1.1 million over 6 years from fall of 50,000 per year in net “other” immigrants

** Trustees assume immigration levels, not growth rates; they decline in steps to reach ultimate level in 2027 for low and intermediate cost, and 2017 for high cost

*** Panel LOW COST recommends increasing LFPR for each 5-year age group over 55. LFPR of each 5-year age group will reach in 75 years (2081) the current rate 

(2007) of the next younger 5-year age group e.g. LFPR of 55-59 year old in 2081 will equal LFPR of 50-54 years old in 2007
2007 Technical Panel on Assumptions and Methods 7

n Demographic assumptions

A. Fertility

The total fertility rate for the United States is considerably higher than for other industrialized nations. 

We were unable to find in the literature, or from a 

panel of experts we convened specifically for the purpose, any clear and convincing explanation for the 

difference. We were not able to make a case for changing the intermediate assumption of 2.0, despite the 

large difference with most European countries. However, our recommendations for the ultimate high and 

low cost fertility levels reflect an asymmetry of likely 

variance. We believe there is greater risk that the U.S. 

will begin to move toward other countries and experience a reduction in fertility—even if not falling as 

low as some in the industrialized world—than there 

is that fertility in the U.S. will increase substantially 

above our already-high levels. 

B. Mortality

Mortality, or more accurately the reduction in mortality, will improve, we believe, more quickly than the 

Trustees assume. We also believe, based again on international experience, there is a real possibility that 

mortality will improve much more than even our intermediate assumption. While our suggested change 

to the intermediate assumption is a significant but 

modest 0.3 percent per year, we recommend raising 

the high-cost (i.e., most improvement in longevity) by 

0 .8 percent per year.

C. Immigration

Immigration has been greater in the recent past 

than the Trustees Reports portray and, we believe, will 

continue to be greater in the future than the Trustees 

project. We also believe it would be more appropriate 

to project the rate of change of immigration, rather 

than the level of immigration, as either are a function 

of both previous immigration and general population 

growth. For this report we have utilized the former.

The Trustees have felt constrained by limits contained 

in current law when making assumptions concerning 

the number of immigrants entering our country each 

year. As a result, total immigration is, in reality, considerably greater than the Trustees assume. While “current law” is a useful convention for the development of 

baselines against which to measure changes in policy, 

the projection of trust fund finances, especially over 

very long periods of time, is a fundamentally different 

exercise. Reality is a better foundation in this case.

We expect that future immigration will depend 

critically upon the growth in the U.S. economy, the 

fertility of native-born citizens, and the resultant 

demand for labor. While immigration from Mexico 

may eventually slow, there will be ample population 

in the rest of the world. The Panel strongly recommends that the Trustees pursue research to incorporate the demographic and economic differentials 

between native and foreign-born populations, by 

age and sex at a minimum, but also possibly by marital and labor status. 

D. Disability

The incidence of disability is particularly difficult 

to project—it depends more closely than other factors on the interpretation and application of the 

law to new beneficiaries. Disability incidence assumptions were lowered in the 2007 Report and the 

Panel believes this revision was reasonable given the 

data on health and benefit trends. These same data 

on health and benefit claiming lead the Panel to recommend changes to the low- and high-cost alternative scenarios. We found no compelling evidence to 

change the Trustees’ current intermediate assumptions, but do believe there is more risk of increasing 

incidence, and less chance of substantial reductions, 

as reflected in our recommendation.

n Economic assumptions

Economic factors are subject to more variation 

than demographics over short periods, but have exhibited relative stability over at least the medium 

term of 20-25 years. Some, such as the unemployment rate, do not by themselves materially change 

the trust fund outlook. Again, asymmetry of risks 

may apply, but with less regularity than with demographics.

A. Labor Force

With respect to labor force participation (LFPR), 

the Panel recommends putting more weight on the 

possibility that greater life expectancy, improved 

health, unmet demand for workers, low personal 

savings, changing workplace requirements, and 

the reduction in defined benefit private retirement 

plans may increase participation rates at older ages. 

The Panel believes that allowing for this possibility 

is important and could ultimately affect both the intermediate- and low-cost scenarios. 
8 2007 Technical Panel on Assumptions and Methods

B. Unemployment

The Panel recommends no change to the Trustees’ 

assumed rate of unemployment.

C. Real Wage Growth

Productivity Growth 

Our recommendation reflects the sharp slowdown 

in actual productivity growth between mid-2004 

and mid-2007 that has reduced the possibility that 

the American economy entered a new era of rapid 

high productivity growth after 1995. Instead, it appears that the marked acceleration of productivity 

growth between 1995 and 2004 can be attributed 

to special one-time factors that are unlikely to recur. 

In forecasting future productivity growth, substantial weight must be given to the poor performance 

of productivity growth in the period 1972-1995. We 

chose to recommend leaving the intermediate assumption unchanged, but do recommend lowering 

the high-cost estimate to reflect the greater risk of 

future substantial declines in productivity.

Earnings to Compensation Ratio

We believe that the decline of earnings relative to 

total compensation (i.e., the increase in fringe benefits, especially for healthcare) must slow over the 

next 25 years and abate thereafter. Recent experience 

suggests that there will be significant resistance to 

future increases in the health insurance costs borne 

by employers. The reasons for the growth of defined 

contribution pension plans are complex, but one important feature of such plans is the ability they give 

to employers to control the magnitude of their pension liabilities. Employers already have shifted a significant share of health insurance costs to their employees; even more dramatic shifts in this direction 

should be anticipated, with employers offering their 

workers a defined contribution to be applied toward 

health insurance coverage rather than a health insurance plan that offers a defined set of benefits.4

Average Hours of Work

We believe hours worked will decline slightly more 

than the actuaries do over the next 25 years. The Panel 

feels that the continuing decline in hours in Europe together with the sharp decline in the U. S. between 2000 

and 2006 make at least a modest further decline likely. 

We propose an annual rate of decline of hours per employee of 0.1 percent for the first 25 years of the projections and zero thereafter. After the baby boomers 

have retired, we assume, as the Trustees do, that hours 

worked will stabilize.

Inflation Differential

Based on recent evidence that monetary authorities in the industrialized world have developed the 

means and the will to control inflation, we conclude 

that the estimates for the CPI should be somewhat 

lower than the Trustees assume. Because the U.S. 

economy is driven largely by consumption spending, 

the difference between the gross domestic product 

(GDP) deflator and the CPI should diminish more 

quickly than the Trustees assume.

Summary of Real Wage Growth

As a result of these various adjustments, we conclude 

that real wage growth will exceed the Trustees’ estimates 

over the next 25 years and grow even faster thereafter.

D. Real Interest Rates

Historical data and current financial market results 

suggest that real interest rates will be lower than the 

Trustees assumed in their latest report. The Trustees set projected nominal rates to be consistent with 

their real interest rate and inflation assumptions. The 

result is an assumed nominal rate in the intermediate case that is inconsistent with the actual nominal 

Treasury yield curve. CPI inflation also exceeds the 

medium-term consensus view, and contributes to 

the discrepancy with market data. The Trustees put 

greater weight on the past than do financial markets. 

4 U.S. Department of Labor, “The Evolution of Compensation in a 

Changing Economy,” Report on the American Workforce, Washington DC, 2001, pp. 57-94.

2007 Technical Panel Growth Rate 

Recommendations

Real Wage Growth = (Yr. 0-25) 1.3 pct/yr

(Yr. 26-75) 1.5 pct/yr

+ Growth in 1.7 pct/yr

labor productivity 1.7 pct/yr

+ Growth in 0.0 pct/yr

[labor compensation/GDP] 0.0 pct/yr

+ Growth in -0.1 pct/yr

[earnings/labor compensation] 0.0 pct/yr

+ Growth in -0.1 pct/yr

[total hours/employment] 0.0 pct/yr

+ Growth in -0.2 pct/yr

[GDP deflator/CPI] -0.2 pct/yr
2007 Technical Panel on Assumptions and Methods 9

The historically low level of long-term yields on financial instruments in the U.S. and abroad suggests 

that investors expect inflation to remain moderate. 

Discounting

Several recent studies have drawn attention to the 

misrepresentations of liabilities that can occur by inappropriately discounting risky cash flows at a riskfree rate. The risk in Social Security liabilities arises 

from the indexing of benefits to aggregate wage 

growth: liabilities will be higher if the economy on average does well over the next 75 years than if it does 

poorly. This systematic risk implies that the theoretically correct rate is higher than the risk-free Treasury 

rate. Payroll tax revenues, which also are tied to aggregate economic performance, require similar risk 

adjustment. For calculations involving discounting 

such as the actuarial balance, the Panel recommends 

that the Trustees consider using risk-adjusted rates 

instead of a risk-free real interest rate.

Equity Risk Premium

The equity risk premium-the average return on 

stocks over the risk-free rate—has no effect on the 

analysis of system finances under current law. Periodically, however, the actuaries are asked to analyze the 

effect of legislative changes that include investments 

in the stock market. We generally agree with the level 

of risk premiums in recent analyses by the actuaries of 

proposals involving stock market investments. However, fairly presenting the implications of the equity 

premium can be a greater challenge than estimating it. 

The Panel recommends that the actuaries portray riskadjusted projections as a neutral risk-adjusted case, not 

as worst case for average returns.

E. Taxable Share of Covered Earnings

There is a growing and significant economic literature on the causes of increasing wage and income 

dispersion in the United States. The share of total 

wages has been growing most rapidly for those individuals at the top of the earnings distribution. This 

trend has been reflected in the falling share of Social Security covered wages that are taxable—from 

90 percent in 1983 to 83 percent in 2008. Despite 

the significance of this trend on the finances of the 

trust funds, the projections in Trustees Reports 

since 1983, however, have done a poor job anticipating it. Despite that poor record, those projections 

also continue to maintain low-cost and high-cost 

bounds that are unrealistically narrow. The Panel 

believes the Trustees should conduct additional research into the causes of wage dispersion and focus 

more attention on providing more reasonable projections of this important influence on overall system finances.

Figure 1: Projected Annnual Trust Fund Ratio under Intermediate Assumptions: 2007 Techncial Panel 

Recommendations vs Trustees Report 2007 

Trustees 2007

intermediate scenario

TPAM recommended

intermediate scenario

Percentage

0

50

100

150

200

250

300

350

400

450

2000 2010 2020 2030 2040 2050 2060 2070 2080 2090

Figure 1: Projected Annual Trust Fund Ratio under Intermediate Assumptions: 2007 Technical Panel vs. 

Trustees Report 2007
10 2007 Technical Panel on Assumptions and Methods

Figure 2: Projected Annual Balances under Intermediate Assumptions: 2007 Technical Panel vs

Trustees Report 2007 

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-3.00

-2.00

-1.00

0.00

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2.00

2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 2055 2060 2065 2070 2075 2080 2085

Trustees 2007 intermediate

scenario

TPAM recommended

intermediate scenario

Percent of taxable payroll

Figure 2: Projected Annual Balances under Intermediate Assumptions: 2007 Technical Panel vs. Trustees 

Report 2007

5 Porter, Eduardo, “Illegal Immigrants are Bolstering Social Security 

with Billions,” New York Times, April 5, 2005.

n Long-Term Financial Status of the 

OASDI Trust Funds

Taken together, our recommendations for changes in 

the Trustees’ assumptions yield a modest improvement 

in the finances of the system by all the usual measures. 

Generally, income is reduced by a small amount, which 

is more than offset by a reduction in system costs. The 

75-year actuarial deficit would be -1.74 percent of taxable payroll under the Panel’s recommended intermediate assumptions compared to -1.95 percent under 

the current Trustees’ assumptions. While the 75-year 

effect reflects a notable improvement, it is important 

to remember that while the direction of the change 

is reasonable, the exact magnitude is very uncertain. 

Some of the suggested changes, such as immigration, 

reduce the deficit, but by an uncertain amount. Others, such as the decline in mortality, increase costs by a 

similarly uncertain amount.

As depicted on Figure 1, the trust fund balance remains positive for only one additional year under the 

Panel’s recommended intermediate assumptions compared to those in the 2007 Trustees Report, with the 

balance reaching zero in 2042 rather than 2041.

Despite the improvement, annual costs exceed income (excluding interest) starting in 2017 (the same 

year as projected in the Trustees Report) and never 

turn around, growing to a deficit of 4 percent of payroll 

in the 75th year of the projection period. Even after the 

boomers are no longer a factor, the system’s finances 

continue to erode as far as the crystal ball can see, and 

well beyond. Put another way, we cannot “assume” our 

way out of the financial hole—see Figure 2.

Our assumption of a more rapid improvement in 

mortality, all else equal, raises system costs, especially in the longer forecasts, as retirees collect benefits for longer periods.

Increased immigration helps the outlook for the 

trust fund by lowering the cost rate over the entire 

period. Immigration adds to the gross payroll taxes and benefits paid, but the effect on rates arises 

mostly through costs due to immigrants entering the 

workforce very soon after arrival and adding to taxable payroll faster than collecting additional benefits. 

Undocumented immigrants who do not have proper 

Social Security numbers also contribute approximately $5 billion a year to the trust funds without 

ever claiming benefits for those contributions.5

Our recommendation to slow the decline in the 

earnings-to-compensation ratio improves the trust 
2007 Technical Panel on Assumptions and Methods 11

75 year 

summarized 

balance

Change 

from 

TR

25th year 

balance 

(2031)

Change 

from 

TR

50th year 

balance 

(2056)

Change 

from 

TR

75th year 

balance 

(2081)

Change 

from 

TR

Year cost 

exceeds 

income*

Year Trust 

Fund ratio 

<0

2007 Trustees 

Report

-1.95 -3.56 -4.20 -5.20 2017 2041

Mortality -2.20 -0.25 -3.64 -0.08 -4.64 -0.44 -6.02 -0.82 2017 2040

Immigration -1.50 0.45 -3.00 0.56 -3.24 0.96 -3.98 1.22 2018 2044

Real wage 

growth

-1.63 0.32 -3.46 0.10 -3.26 0.94 -4.06 1.14 2017 2042

CPI growth -2.02 -0.07 -3.64 -0.08 -4.31 -0.11 -5.31 -0.11 2017 2040

Interest rates -2.15 -0.20 -3.56 0.00 -4.20 0.00 -5.20 0.00 2017 2040

TPAM 

intermediate:

-1.74 0.21 -3.14 0.42 -2.98 1.22 -3.95 1.25 2017 2042

* excluding interest

Source: OCACT projections of Technical Panel asssumptions

Table 2: Summary of Effects of Individual Assumptions on System Finances

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Figure 3: Effect of Individual Techncial Panel Recommended Assumptions on OASDI Annual Balances: 2007-2085

Trustees Intermediate 2007

Mortality

Immigration

Net real wage growth

CPI

◆

◆

▲

Percent of taxable payroll

Figure 3: Incremental Effect of Individual Technical Panel Recommended Intermediate Assumptions on 2007 

Trustees Projection of Annual Balances

fund outlook slightly in the first years and a small 

amount over 75 years. The changes in hours worked 

and GDP-CPI differential also improves the long-term 

outlook by a small amount.

The recommended CPI change has a negligible effect 

in the short- and long-run. The change in the real interest rate adds very slightly to the trust fund deficit by 

reducing the interest income in the early years. Values 

summarized over 75 years in present value calculations 

would appear larger with a lower interest rate. These 

marginal effects are depicted graphically in Figure 3 

(interest rate effects are not shown) and numerically in 

Table 2.

2007 Technical Panel on Assumptions and Methods 13

We begin our report with observations on the 

methods and data used by the Office of the Chief 

Actuary (OCACT) and the Trustees, rather than 

on specific assumptions, since we would expect 

a more lasting impact from a change in method 

than a change in any particular point estimate we 

could suggest. It is quite easy, in fact, to take narrow issue with any particular estimate, but more 

difficult to understand and examine the methods 

used to produce it. Because of the inherent uncertainty in long-range projections, the validity of 

the estimation process is arguably as important 

as any specific result.

The methodological challenge is to assess the 

financial soundness of the Social Security program. The future income and cost of Social Security must be estimated in such a way that allows 

the Trustees to: (1) examine the likely financial 

results of the system, including year-by-year cash 

flows, the annual balance in the trust fund, and 

the actuarial balance at the end of the 75-year 

period; and, (2) describe the uncertainty of the 

forecasts. In addition, policy makers and the public may also wish to understand the distributional 

impact of any proposed change to the Social Security program. Technical experts may also wish to 

evaluate the reasonableness of the variables that 

are used to forecast the future financial changes, 

particularly the interaction and consistency between the different economic, social, and demographic variables.

The state of actuarial science appears to be rapidly evolving beyond the cell-based models generally employed by the actuaries, to more explicitly 

incorporate interactions between economic and 

demographic variables and to better understand 

the uncertainty in the projections. The increase 

in computing power alone makes possible many 

analyses heretofore impractical, and allows additional data to be incorporated. 

Chapter 1: Methodology

New data sources are also emerging. Recent research using longitudinal data such as the Health 

and Retirement Survey (HRS) and the Survey of 

Income and Plan Participation (SIPP) linked to micro-level Social Security earnings data have yielded 

significant insights on disability, health, and retirement dynamics. This potent combination—advanced computing, more and better data, and new 

methods—holds the prospect of significant advances in the analysis required for social programs 

and their associated trust funds.

Many of this Panel’s recommendations on methods—transparency, the use of micro-simulation 

and stochastic analyses, specifying and estimating interactions, employing additional data—are 

not new. Previous Technical Panels and other experts have made similar recommendations. What 

is new, perhaps, is that the actuaries have made 

some progress on many of these fronts. There are 

reasons to be impatient, however. New computing 

power, new sources of data, and new estimating 

techniques should allow OCACT to make faster 

progress in advancing their models and methods. 

Indeed, others within government, ranging from 

the Office of Policy within SSA to non-executive 

branch agencies such as the Congressional Budget Office, are exploiting these developments and 

creating the means to analyze the system and its 

response to change. Only by aggressively deploying new data and techniques and by making the 

process more transparent can OCACT and the 

Trustees remain the definitive source-of-record 

for this information.

There also appears to be an understandable reluctance by the Trustees to make significant changes 

to their projections in any given year. Rather, 

methodological changes that produce significant 

changes in point estimates are phased in, or offset with changes in other variables. Nonetheless, 

the Actuarial Standards of Practice, specifically 
14 2007 Technical Panel on Assumptions and Methods

Standard No.32: “Social Insurance,” suggests that 

new information should be incorporated when it 

is found, even if such information creates some 

discontinuities in the forecasts: “The actuarial assumptions, both individually and in combination, 

should reflect the actuary’s best judgment, taking 

into account anticipated future events affecting the 

related social insurance program.”6

While OCACT is exploring new ways of augmenting their traditional methods, the adoption appears 

to us to be slow and sometimes grudging. Recommendations of previous advisory panels seem to 

have languished. As a result, important information in the estimating process may be lost. What 

follows is a series of comments that generally apply 

across the set of variables for which OCACT creates 

projections. Their specific applicability and methodological comments unique to each variable appear in the appropriate chapters.

A. Transparency

Throughout this report, we call for more transparency in the models and data the actuaries use, as 

well as the assumptions that drive their results. This 

recommendation is perhaps the most important one 

we can make. Only with more transparency can other social scientists interested in retirement, Social 

Security, and the various related issues, bring their 

intellect to bear on the many complex questions the 

actuaries face. Only by a clear articulation of their 

assumptions can the actuaries’ work be truly examined. Only by a clear understanding of the nature 

of trust fund accounting can the public be assured 

of the outlook for the program and the veracity of 

statements made about it.

Method Recommendation M-1: Further document all 

models to the extent necessary for others to replicate 

forecasts. Make available sufficient data for non-government analysts to replicate forecasts, and conduct 

research to improve forecasting techniques. Include 

in the analysis an explicit discussion of the historical 

time periods, and the associated rationale, used for 

each variable.

Method Recommendation M-2: Explicitly model 

and document relevant interactions.

Method Recommendation M-3: The Social Security 

Advisory Board, to whom this Technical Panel reports, should hold semi-annual meetings with OCACT to discuss progress on the recommendations 

contained in this report as well as those from previous panels. 

All analytical agencies, whether NASA, CBO, or 

OCACT, must make assumptions about behavior 

or phenomenon that are unobservable or immeasurable. In the process, the assumptions become 

deeply embedded and the models closely guarded. 

These agencies are understandably reluctant to revisit assumptions or reveal methods. Nonetheless 

it is essential to do so. First, accountability requires 

it—such is the nature of the nascent documentation external auditors recently required of OCACT. 

Second and more important, ongoing comprehensive, external review can greatly assist the quality 

of the analytical exercise. 

Transparency of the OCACT models will require 

several developments:

n providing more comprehensive documentation 

n making data from SSA records more available 

n creating explicit models where none exist and 

n clearly explaining the processes employed

The ultimate test of transparency is whether the 

actuaries’ results can be replicated. For example, 

interactions between the variables that drive the 

projections are not made explicit in the cell-based 

models used by the actuaries, and it is not clear 

how these relationships are incorporated in the final projections. As a start, it would be helpful for 

OCACT to publish any calculations, spreadsheets, 

models or even rules-of-thumb that are currently 

used to assess interactions. The professionals of 

OCACT are aware of virtually every potential interaction we raised along the way, every additional 

technique that might be brought to bear, and almost every piece of relevant literature we cited. 

Although they “test” their assumptions and the 

resultant estimates it is often in ways that are not 

explicit, formal or replicable. 

Another area of necessary transparency is an explanation of the data used and the time-periods employed in the trend analysis, as well as the rationale 

for those choices. The heavy reliance on historical 

trends in long-term projections makes it particularly important to choose the “correct” reference 

period from which to draw inferences—a period 

that will vary depending upon the phenomenon being examined. Some retrospectives are limited by 6 Actuarial Standards Board, “Actuarial Standards of Practice No. 

32: Social Insurance,” January 1998.
2007 Technical Panel on Assumptions and Methods 15

the availability of data, or at least comparable data, 

and it is unwise to place too much weight on history when evidence is limited. Nor should we employ 

data from a longer but less relevant time period 

simply because we can. Current projections rightly 

use different time horizons as relevant reference 

points for different assumptions: to project mortality the focus is on the past 50 years; to project immigration the focus is the past 100 years; for fertility the focus is the past 20 years; and for disability 

incidence the emphasis is on more recent history. 

While these choices may be reasonable ones, the rationale behind them is not always transparent. 

Further, these data must be or become publicly 

available to allow replication and modification of the 

techniques. To the extent private data on individuals 

is used, minimal aggregation should be employed to 

protect identity, and the aggregated data made public.

B. Uncertainty

Method Recommendation M-4: Incorporate asymmetrical risk in the projections.

Method Recommendation M-5: Further develop 

stochastic modeling capabilities, and make much 

greater use of stochastic analysis to examine uncertainty, especially the effects interactions have on 

uncertainty.

Method Recommendation M-6: Consider risk-adjusting discount rates for summarized balances. Using the risk-free interest rate to discount uncertain 

future cash flows is inconsistent with valuation principles, and over-weights the outcomes that are most 

uncertain.

The exercise undertaken by OCACT and the Trustees is equivalent to asking someone in 1932, during 

the depths of the Great Depression when the Dow 

Jones Industrial Average reached an all-time low of 

41, to predict the size of the population and the state 

of the economy in the year 2007 and essentially everything in between—World War II, baby boom generation, nuclear power, Cold War, space travel, Vietnam 

War, improvements in healthcare, industrialization, 

computers, or the Dow Jones Industrial Average 

(DJIA) breaking 14,000. And looking forward from 

the perspective of 1932, it would have been virtually 

impossible to predict the economic and demographic 

changes for the succeeding ten years (which included 

the enactment of Social Security), let alone 75. Yet 

the actuaries and Trustees must have a sense of how 

uncertain the future may be to understand the validity of their work. The further the gaze into the future, 

the less certain the outlook. This is not a reason for 

futility, but it does require that explanations of uncertainty in the projections need to be expanded.

The current approach to uncertainty in the Trustees Report, using high-, medium-, and low- cost 

“scenarios” or “variants” to indicate the range of 

plausible outcomes is a traditional one whose limitations are well known; it produces estimates that 

lack both an intuitive and a statistical interpretation. In addition, the temptation to assign probabilities to the scenarios or to suggest their degree 

of likelihood should be resisted. 

Previous Technical Panels have consistently drawn 

attention to the limitations of the variant approach. 

For example, the 1999 Technical Panel noted that 

using high and low alternatives: (1) assumes trajectories are always high or always low; (2) combines 

trajectories of various assumptions in rigid ways, 

for example, all are set at their high-cost value simultaneously; (3) ignores that different aspects of 

the high and low scenarios have different levels of 

uncertainty; and (4) does not assign any probability 

to the forecast ranges.7

 We offer one additional observation: there is no requirement for symmetry of 

uncertainty—that the forecast be plus-or-minus an 

equal amount along the projection. Indeed, many 

key drivers have asymmetrical uncertainty as succeeding chapters will show, and the nature of the 

uncertainty may change with the forecast horizon.

Stochastic analysis, on the other hand, produces 

uncertainty bands that are much easier to interpret 

by incorporating correlations between variables and 

allowing ranges to be given a probabilistic interpretation. The Panel therefore recommends using the 

results of the stochastic analysis to augment if not 

supplant the high- and low-cost scenarios, and to 

communicate the range of uncertainty around the 

intermediate projections.

The actuaries have also developed a stochastic 

model to augment their use of scenarios to analyze 

uncertainty, but those results appear more as an 

addendum in the Trustees Report than as an integral part of the analysis. There are at least two 

aspects of uncertainty that the actuaries should 

analyze and integrate into the main analysis. First, 

the scenario presentation in the Trustees Report 

is focused on the intermediate projection—a point 

7 Technical Panel on Assumptions and Methods (1999), Report to 

the Social Security Advisory Board, November, 1999, p7.
16 2007 Technical Panel on Assumptions and Methods

forecast favored as the “best guess.” As the forecast 

horizon lengthens there is a substantively important decrease in the usefulness of any point forecast, whereas probabilistic statements about different outcomes remain useful to policy analysis.

To illustrate, suppose that over a 5-year horizon 

we make a point forecast, and that a small interval 

around that forecast covers a prediction interval 

with 90 percent probability. We can reasonably use 

the point forecast as a basis for decisions over the 

5 years. But the 90 percent probability interval will 

be more than twice as wide at a 25-year horizon, 

and nearly four times as wide at a 75-year horizon. 

(This scaling is robust for any class of models that 

uses multiplicative or additive random shocks.) 

Such a large increase in the uncertainty of, say, the 

dependency ratio or the summarized actuarial balance needs to be confronted realistically. For example, 

a statement that under the intermediate scenario a 

tax increase of 2 percent will balance the fund over 75 

years would be replaced by a statement that there is a 

probability of 50 percent that a tax increase of 2 percent will balance the fund, or there is a probability of 

75 percent that a tax increase of 4 percent will balance 

the fund. Policy makers can then decide on the level of 

insurance, if any, they want to buy with a tax increase. 

Second, while the Trustees Report focuses on the 

important question of the sensitivity of the intermediate forecast, it should spend some effort examining 

the sensitivity of the projection intervals in the corresponding stochastic forecasts. Research shows economic uncertainty is a major factor in the short-term 

(25 years) while demographic uncertainty dominates 

in the long-term (50 years).8

 The inclusion of behavioral responses may influence these patterns in ways 

that the present analyses do not capture.

In addition to the increased use of stochastic analysis, there are other ways to use scenarios that can 

be more useful as a way to explore focal alternatives. 

To illustrate how scenarios could be constructed to 

provide more useful and interpretable information, 

we asked the actuaries to calculate the implications 

of several “integrated” scenarios. The scenarios 

represent plausible, internally consistent alternatives, albeit not the most likely, outcomes. The first 

demonstrates what would happen if demographic 

forces (but not immigration) lead to the high-cost 

outcomes, holding economic assumptions to their 

intermediate assumed values. Specifically, the total 

fertility rate is assumed to fall from 2.0 to 1.5 over 

25 years, and mortality improvement is 2 percent per 

year, assumptions that are close to recent experience 

in some European countries. Immigration policy is 

assumed to ease in response to the lower fertility 

rate: starting at 1.35 million, growing at 2.1 percent 

for 25 years, and then at 0.5 percent thereafter—

what amounts to the Panel’s recommended low-cost 

immigration assumption. Other assumptions are as 

in the Panel’s recommended intermediate case. This 

results in a 75-year actuarial balance of -3.39 percent 

of payroll, an estimate that lies between the Trustees’ 

traditional intermediate- and high-cost scenarios.

We also looked at an alternative economic scenario 

reflecting more optimistic assumptions about future 

economic conditions, by assuming real wage growth 

and real interest rates would be at the Panel’s recommended low-cost values, while all other variables remain at the intermediate. Specifically, the real wage 

growth is assumed to be 1.8 percent for the first 25 

years, and 2 percent for the last 50 years of long-range 

period (see Table 1); the ultimate real interest rate is 

assumed to be 3.3 percent, and the share of covered 

earnings that are taxable is assumed to be 83.8 percent (equal to the Trustees’ low-cost assumption). 

This produces a 75-year actuarial balance of -.66 

percent of payroll, which lies between the Trustees’ 

traditional intermediate- and low-cost scenarios. The 

experiment indicates that even an improbably high 

rate of economic growth is not likely to be enough to 

bring the system into balance (see Figure 4).

Uncertainty grows as the projection period 

lengthens. But we find that the practice of discounting summarized balances at a risk-free rate 

inherently over-weights the more uncertain periods of the projection. In the process, the analysis 

of the “long-run” may well cause critical mediumterm policy implications to be overlooked.

C. Modeling: Use Of Alternative Approaches 

To Modeling For Projections—The Case For 

Micro-Simulation

Method Recommendation M-7: Increase the use of 

micro-simulation to analyze and display interaction 

effects and distributional outcomes of policy changes.

Models are developed for different purposes. A 

model should be judged based on its validity, accuracy, and reliability in accomplishing its stated 

8 Tuljapurkar, Shripad and Ronald Lee, “Stochastic Forecasts for 

Social Security,” in David Wise (ed.), Frontiers in the Economics of 

Aging, Chicago: University of Chicago Press, 1989, pp.393-420.
2007 Technical Panel on Assumptions and Methods 17

Figure 4: Comparison of Alternative Scenarios: Projected Annual 

-20.00

-17.50

-15.00

-12.50

-10.00

-7.50

-5.00

-2.50

0.00

2.50

5.00

2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 2055 2060 2065 2070 2075 2080 2085

Year

Percent of taxable payroll Technical Panel Intermediate

Technical Panel Low Cost

Technical Panel High Cost

Alternative I: High Cost Demographics

Alternative II: Low Cost Economics

Trustees Report 2007-Intermediate

Percent of taxable payroll

Figure 4: Comparison of Alternative Scenarios: Projected Annual Balances

purpose, and it should also be flexible enough for 

changes in assumptions and policies to be explored 

and evaluated. For example, for financial purposes, 

a model should be judged based on its accuracy and 

reliability in predicting future revenues, costs and 

financial balances. For distributional analysis, a 

model should be judged based on its ability to analyze impacts by socioeconomic classes and intergenerational groups. Since no single model is likely 

to achieve all of these objectives equally well, we 

believe it is imperative for OCACT to accelerate its 

development and incorporation of new models to 

augment its cell-based approach to projections. 

With the advent of increased computing power 

and better data, micro-simulation models have become important tools for analyzing policy changes 

and accounting for behavioral relationships. Several research and government agencies currently 

use such models to evaluate the effects of demographic, economic, and policy changes related to 

the Social Security system including the Congressional Budget Office (CBOLT), Social Security Administration’s Office of Policy (MINT), the Urban 

Institute (DYNASIM3), and the Policy Simulation 

Group (SSASIM/PENSIM/GEMINI). Although not 

a panacea, these models have proven helpful in examining a wide range of issues of interest to policy 

makers and analysts.9

 Moreover, by explicitly accounting for interactions across variables, microsimulation models increase transparency around 

key assumptions underlying the cell-based projections, encouraging debate and discussion about 

these assumptions within the research and policy 

community. For these reasons, the Panel believes it 

is imperative that OCACT increase its investment 

in and utilization of micro-simulation models as 

augmentations to cell-based projections. 

While advocating an increased reliance on micro-simulation, the Panel recognizes that there are also advantages of the cell-based methods employed by OCACT. 

Cell-based models can be more tractable, and the results 

more predictable than micro-simulation models. It can 

be easier to impose aggregate constraints on variables, 

such as the rate of real wage growth, which reflect de9 These include long-term financing (CBO, Updated Long-Term 

Projections for Social Security, June 2006); the impact of differential 

mortality improvement on Social Security’s progressivity (CBO, 

“Is Social Security Progressive?” Economic and Budget Issue Brief, 

December 12, 2006); the distributional effects of benefit changes 

(GAO-08-26, Social Security Reform: Issues for Disability and Dependent Benefits, October 26, 2007; Congressional Research Service, 

Options to Address Social Security Solvency and Their Impact on Beneficiaries: Results from the Dynasim Microsimulation Model, Report 

RL33840, January 29, 2007); and the costs of competing reform 

proposals (CBO, “Long-Term Analysis of the Liebman-MacGuineasSamwick Social Security Proposal”, February 8, 2006).
18 2007 Technical Panel on Assumptions and Methods

velopments in a broad range of underlying social and 

economic trends but are less dependent, in a tractable 

way, on the interactions captured in a micro-simulation. 

Also, the cell-based approach may avoid unintended 

consequences that can arise from explicit modeling of 

individual behavior. To avoid such problems, it is standard to constrain behavior in micro-simulation models so as to impose consistency with certain aggregate 

quantities. Similar aggregation restrictions also must 

be applied to cell-based models, but it is generally more 

straightforward to do so in that context.

The return to investing in a full blown micro-simulation model is that it can provide new insights and 

possibly improve accuracy when interactions among 

variables affect outcomes. This is especially true when 

the nature of these interactions is expected to change 

over time, or differentially across the population. Micro-simulation models use information on individuals from large-scale surveys to build a “virtual” population. This population is aged over time by applying 

demographic and economic processes (e.g., births, 

deaths, marriages, divorces, employment, and retirement) estimated from survey data. Individuals in the 

population “behave” in ways consistent with history. 

Policy changes can be applied to this virtual population 

and the results of these changes can be analyzed over 

time and compared to the outcomes under no policy 

changes. By starting with and maintaining a representative sample of the population, micro-simulation creates a potentially more flexible and detailed model, one 

that incorporates interactions as the base population 

evolves over time. Individual observations can be aggregated and analyzed in almost any grouping, or along 

any dimension that has been used within the data. Importantly, micro-simulations impose an “adding up” 

constraint, ensuring that economic aggregates and 

population counts remain internally consistent. 

The individual-based nature of these models makes 

them useful tools for a variety of inquiries: to analyze 

the distribution (e.g., across income) of the effects of 

policy changes; to explicitly model and incorporate interactions between variables; to make long-term projections; and, to test alternative assumptions. Microsimulation models are useful at tracing the behavior of 

individuals and families over time under varying and 

complex changes in economic and policy variables. 

Micro-simulation can improve forecast quality when 

changes in the cross-section over time affect macroeconomic outcomes and thereby system finances. 

Conditions where micro-simulation models are preferred to cell-based methods are best demonstrated by 

examples. A demographic example arises from mortality improvement differentials. Data show that improvements in mortality have been distributed unevenly 

across the population, with greater gains to higher income individuals. Such differentials are hard to overlay 

on a cell-based model since the effects on an age-sex 

group can change in a complicated way over time. In 

a micro-simulation, such differentials are straightforward to implement, since mortality rates can be assigned to individuals. In the case of mortality improvements, changes in the cross-section significantly affect 

system finances. To demonstrate this point, we asked 

the CBO to do a simple experiment where projected 

annual declines in overall death rates are distributed 

across the population according to the historical differential in mortality by earnings observed in the data. 

Relative to the baseline projection, where a reduction 

in mortality is distributed uniformly across earnings 

quintiles, the change increased life expectancy for the 

1940s to 2000 cohorts in the expected way. In the bottom quintile, the increase in life expectancy was about 

66 percent of the baseline, while at the top it was 138 

percent of the base case, or 3.5 versus 7 years, respectively. The changes in system finances are predictable. 

Incorporating differential mortality worsens the actuarial balance by 0.12. The change in 2080 is more dramatic, the cost-income gap as a share of taxable payroll 

worsens by 0.25 percentage points, which is roughly 5 

percent of the baseline projected imbalance. 

Micro-simulation can also be useful in capturing 

transitional changes in mortality patterns. For example, this same approach could incorporate and examine 

the effects of temporary changes in mortality patterns 

across men and women owing to sharp increases in female smoking rates in certain cohorts. To incorporate 

such temporary changes into a cell-based model would 

require altering the time period for evaluating trends 

or adjusting male-female differentials in an ad hoc way 

as the cohorts move through the age distribution. 

An economic example where micro-simulation 

provides macroeconomic insights is for the analysis of differential labor force participation rates. It 

seems likely that economic and demographic forces 

will change retirement behavior toward longer labor 

force participation. Life expectancy is increasing, 

defined benefit based incentives for fixed retirement dates are declining, and jobs are becoming less 

structured allowing for potentially better matches 

between older workers and employers. Data suggest 

that these factors are distributed differentially across 

the population, thus, as with mortality rates, differ-
2007 Technical Panel on Assumptions and Methods 19

entially affecting the forecast for increased participation at older ages across important variables such as 

wages, income, education, and gender. The complexity of these decisions, the interrelationships between 

the many variables both within and outside the Social 

Security system, and the fact that the retirement and 

work decisions change over time, would make it difficult to overlay these factors on a cell-based model.

A second economic example is analysis of the effect 

of income inequality. As wage inequality has steadily 

climbed, the size and composition of the population 

under the taxable maximum, and the distribution of 

replacement rates, has changed. It is difficult to predict 

the effect of a further widening of the income distribution with a cell-based model, but with a micro-simulation the implications can be examined by increasing 

the assumed volatility of shocks to wage income. Since, 

as we have seen, changes in the earnings distribution 

also affect variables such as labor force participation 

and mortality, being able to systematically incorporate 

these changes into a model is important.

Each of these examples highlights the fact that 

micro-simulation is most appropriately used when 

interactions are important and tractable. While it is 

relatively easy to gain agreement on the importance of 

interactions, the tractable test is somewhat more difficult to pass unanimously. Like all models, the behavior embedded in micro-simulation models requires a 

set of assumptions about how these interactions arise. 

Mathematical equations determine which individuals 

become disabled in a given year; enter, remain in or exit 

the work force and how much they earn; immigrate (or 

emigrate); “marry” (assigning them spouses with certain characteristics), have children, divorce, claim Social Security benefits, and, ultimately, die. Even though 

each of these decisions is typically based on the best 

available data, research and analysis, the complexity of 

the modeling and the gaps in our understanding and 

practical limitations create uncertainty about the reliability and accuracy of micro-simulation projections. 

That said, it is important to recognize that the same 

types of decisions are also being made in the cell-based 

model, they are just not made explicit. Bringing these 

best guesses into a micro-simulation model has the advantage that they are more exposed to scrutiny. 

As noted earlier, the general advances over the past 

several decades in social science, computational capability, data, and modeling, coupled with an increased 

interest in Social Security and its long-range solvency, 

have created a rich environment for testing the plausibility of modeling decisions and techniques, collaboration with outside experts, and peer review. We favor 

approaches that rely on explicit, rather than implicit, 

relationships and assumptions. We believe that the advantages associated with micro-simulation, especially 

when taken in concert with our other recommendations, strongly argue for increased investment in and 

reliance on a single (integrated) micro-simulation model as a key tool in OCACT projections for the Trustees.

D. Presentation 

At the nexus of transparency and clear exposition of uncertainty are a number of recommendations that have more to do with the presentation 

of the results, which apply regardless of the modeling techniques used. 

Presentation Recommendation P-1: Shift the emphasis toward the intermediate-term and away 

from very long-term measures such as the infinite 

horizon forecasts. Shift emphasis toward the use of 

annual cost and income rates, and away from summarized 75-year balances.

Presentation Recommendation P-2: Include in the 

analysis an explicit comparison of the U.S. experience with other countries.

Presentation Recommendation P-3: Report annually the accuracy of previous estimates and projections.

Presentation Recommendation P-4: Increase the 

use of graphical representations of uncertainty.

Presentation Recommendation P-5: Improve the 

explanation of trust fund accounting and its implications.

Near vs. Long-Term

While it is clearly reassuring to address the long-term 

(including the impulse to assure the public of “sustainability” for an infinite horizon), it is more important 

to be straightforward about what is reasonably “knowable” and what remains highly speculative. We know 

(relatively) a lot about beneficiaries and workers for the 

next 25 years—even then, substantial uncertainty still 

remains, such as the future rates of immigration. 

In contrast, 75 years into the future is far more uncertain. The longer the projection period, the more uncertainty exists. The single point estimates associated with 

distant horizons may yield a false sense of precision; and 

the casual use of these estimates is often misleading.

Despite the fact that the Trustees are required to 

report on system finances over a 75-year horizon, 

they have the discretion to focus greater attention 
20 2007 Technical Panel on Assumptions and Methods

on longer or shorter time periods. The Panel recognizes that there are pros and cons of emphasizing 

long-horizon forecasts. Advantages include that 

they allow the full effect of policy changes to be 

played out, and that they reveal long-term imbalances, perhaps thereby encouraging more comprehensive reform. Conversely, there are also serious 

disadvantages. The great uncertainty about economic, demographic, and other policy conditions at 

long horizons decreases the credibility of long-range 

estimates. Small errors in assumed growth rates can 

lead to big mistakes, and smaller but meaningful 

reforms can appear insignificant when compared 

to enormous but distant deficits. Emphasis on long 

horizons can invite policies that balance system finances but only by including deferred and unrealistically high tax increases or benefit cuts.

To illustrate the sensitivity of the infinite horizon 

actuarial balance to relatively small changes in assumptions, consider a reduction in the real interest rate from 

2.9 percent to 2.6 percent, consistent with our recommendation in this report. A back-of-the-envelope calculation shows that the actuarial balance increases by 

about 60 percent. In general, the calculation is enormously sensitive to small changes in the growth rate of 

the Gross Domestic Product (GDP) or interest rates.10

On balance we believe that for analysis of the 

trust funds the disadvantages of very long-range 

forecasts outweigh the advantages, and we recommend that for the annual Trustees Report emphasis be further shifted toward the intermediate term 

of 25 years and the use of annual cost and income 

rates, and away from long-term measures including 

the 75-year summarized balance.11

International Comparisons

As will be evident in succeeding chapters, we believe comparisons with other countries, especially 

the developed and aging “industrialized” nations 

provides valuable insights. Although we do not fully 

understand the cause of many of the disparities, the 

fact that the consistent experience abroad is quite 

different from ours suggests the possibility of convergence; perhaps they will all gravitate toward us 

or perhaps we will gravitate toward them. 

Forecasting Record

We believe that the accuracy of past projections 

should be the subject of routine reporting, either 

in the Trustees Report or in separate supplemental 

publications on methodological developments. There 

should be an analysis of the accuracy of past 10-, 20-, 

and 30-year projections similar to those periodically 

done by the Census, Bureau of Labor Statistics, and 

Congressional Budget Office. The report should include a comparison of the high-cost and low-cost scenario variants and how often past outer bounds have 

been exceeded for each variable.

Use of Graphs and Charts

Advances in computing make it much easier to include more graphs and charts that incorporate large 

amounts of seemingly unrelated data. For example, 

graphical techniques such as fan charts convey more 

information than the high-cost and low-cost scenarios. Just as a predicted hurricane track is bounded by a 

cone of uncertainty, so too can the projections of trust 

fund components be shown with individual and collective bounds over time.

Nature of Trust Funds

Among the developments likely not foreseeable 

in 1932 was the passage of the Social Security Act 

in 1935. Modeled in part on European retirement 

systems, this centerpiece of President Franklin D. 

Roosevelt’s signature New Deal program included 

an accounting device euphemistically called a “trust 

fund.” The program was described as “insurance” 

even though it was more “assurance” of a generational promise to provide a modicum of income to 

those who were disabled or retired. Initially, with 35 

workers for every beneficiary, it was relatively easy 

to fund the program. The projection of ample trust 

fund balances over long periods was used to justify 

periodic increases in benefits. However, almost from 

its inception, the Social Security program has been 

essentially pay-as-you-go, with payroll tax collections 

funding current benefits, and not accumulating “savings” for the future. The trust fund does not hold 

a store of value equal to future obligations. In that 

sense, it is not “fully-funded” as we think of private 

retirement plans.

10 The calculation assumes a cost rate in excess of the revenue rate 

of 2 percent of GDP starting in 2040, and a long-run GDP growth 

rate of 1.9 percent. The 2 percent gap is discounted to the present, 

using either 2.6 percent or 2.9 percent as the discount rate. 

11 There are circumstances, however, when longer horizons are 

necessary to understand the dynamics of major policy changes—

important effects may not appear until a generation or more in 

the future. For example, a change from pay-as-you-go funding to 

something akin to pre-funding would likely require a long transition period and the full effects would not be manifest until well 

beyond 75 years. For this purpose, a horizon of 150 years or more 

may be appropriate.
2007 Technical Panel on Assumptions and Methods 21

Trust fund balances, and the dates of trust fund 

“exhaustion,” continue to receive prominence in the 

Trustees Report. Surprisingly little, however, is said in 

the introductory sections about what the trust funds 

represent, beyond saying that the securities held are a 

firm obligation of the U.S. Treasury.

It is important to convey, at the beginning of the 

report, that the trust fund functions as an accounting 

mechanism and to explain how that mechanism works. 

The trust fund limits the legal authority to pay benefits. Paying benefits from trust fund “assets” requires 

increasing taxes, borrowing, or cutting other federal 

spending, as would be the case if there were no trust 

fund. These points are made in the body of the report, 

but that material should be drawn upon to provide 

guidance right at the beginning.

With regard to the date of trust fund exhaustion 

there are two issues. The first is that the date receives 

more prominence than seems warranted—it seems to 

suggest that we are simply spending down accumulated 

assets until that date and that no benefits could be paid 

after that date. Neither is accurate. A more minor issue 

is that what is assumed about cash flows following an 

exhaustion date is not always clear. This is particularly 

true of the Disability Insurance (DI) fund where the 

exhaustion date does not seem to affect benefit payments, even in presentations where Old Age and Survivors Insurance (OASI) fund exhaustion does.

As noted above, paying benefits from trust fund “assets” requires increasing taxes, borrowing, or cutting 

other federal spending, as would be the case if there 

were no trust fund. The fact that trust fund balances 

are positive should not be viewed with great comfort. 

Nor is the trust fund ever completely “exhausted” as 

the usual connotation implies. Even when the balance 

reaches zero, there will be a flow of revenues that can 

be used to make payments—about 70 percent of the 

payments under current projections. The trust fund is 

more like a checking account and will have “insufficient 

funds” by mid-century; today’s workers are making deposits to cover the checks being written to their parents. Our children will do the same for us, except there 

will be fewer of them to make deposits. Come 2042 or 

thereabouts, the account will not have enough deposits 

to cover full payment on all the checks.

Resources for Development

We have no doubt that implementing even some 

of our recommendations will require more resources for OCACT. However, it is not necessary for the 

actuaries to accomplish all model development in 

OCACT. With increased transparency, academic and 

other research centers can make meaningful contributions from outside government. Similarly, much 

of the work of Social Security Administration’s Office 

of Policy could be incorporated more readily than is 

apparently the current practice. Other governmental agencies, such as CBO and GAO, could assist in 

evaluating the productivity and efficacy of specific 

analytical alternatives, even to the point of sharing 

code. The actuaries could use outside developers to 

replicate or augment their existing code.

2007 Technical Panel on Assumptions and Methods 23

Demographic models and assumptions that provide estimates of the future population size and age 

structure are central to projecting future Social Security revenues and expenditures. The estimates of 

future population growth are generated from the 

initial population and assumptions concerning the 

total fertility rate, legal and other-than-legal immigration, and trends in mortality improvement. 

These estimates ultimately are used to determine 

the number of workers covered by Social Security 

and the number of beneficiaries in each year.

A. Fertility

Assumption Recommendation A-1: The Panel believes that there is greater risk (and cost) to the 

trust funds associated with overestimating the 

total fertility rate over the next 75 years than underestimating it. We therefore recommend retaining the intermediate assumption of 2.0 from the 

2007 Trustees Report, but we assume a high-cost 

total fertility rate of 1.5, 0.2 lower than that of the 

Trustees, and a low-cost rate of 2.1, rather than 

2.3. In Chapter 1, the Panel recommended that the 

Trustees adopt asymmetric high-cost and low-cost 

assumptions relative to their intermediate assumption. We made this recommendation because policy 

makers and future retirees should be able to understand the direction of our uncertainty in evaluating 

alternative assumptions for the deterministic projections prepared by Trustees. It should be noted 

here that the intermediate series is not the “average” or “most likely” assumption, nor are the lowand high-cost alternatives brackets with known 

sampling distributions, such as a 95 percent confidence interval about the mean.

Overview

The fertility assumption is expressed in terms of 

the total fertility rate (TFR), the average number 

of births per woman over her lifetime, assuming 

she survives to the end of her reproductive period 

and is exposed to the same age-specific schedule 

of fertility as observed in a given year. As a summary measure of fertility, the total fertility rate is 

a composite of the changes in the tempo, or timing, of childbearing and the level, or quantum. We 

address both components of the TFR in our discussion and recommendations. 

In order to inform short and longer term perspectives on fertility, it is useful to look at historical patterns. It was suggested to the Panel that the 

previous 10-25 years are the most relevant period 

for our analysis.12 And as a review of the empirical evidence from this recent period demonstrates, 

these findings are consistent with inferences supported by a much longer time series. When the 

data from the past 20 years is analyzed along with 

comparable date from the last 200 years, two conclusions emerge: (1) U.S. fertility is likely to continue to decline or plateau at current levels (i.e., 

not increase) and, (2) the baby boom of the 1950s 

is an aberration rather than a precursor of the immediate future. Although there have been numerous changes in women’s employment, age at marriage, wage rates, and family-friendly work place 

policies, the total fertility rate in the United States 

has remained relatively stable since the 1970s. 

The Trustees interpret their long-run scenarios 

of the fertility rate as a statement about the averChapter 2: Demographic Assumptions and Methods

12 The Panel convened a one-day meeting on “The future of U.S. 

fertility trends” on November 27, 2006. Outside experts who 

participated were Hans-Peter Kohler, Ph.D., Professor of Sociology, 

University of Pennsylvania; Ronald Lesthaeghe, Ph.D. Professor 

Emeritus of Demography and Social Sciences, Free University of 

Brussels (VSB); and S. Philip Morgan, Ph.D., Professor of Sociology, 

Duke University. Lowest-low fertility is largely a European Union 

phenomena not observed until after 1990 (see Kohler, H-P, F.C. 

Billari, and J.A. Ortega, “Low Fertility in Europe: Causes, Implications and Policy Options,” in F. R. Harris (Ed.), The Baby Bust: Who 

will do the Work? Who Will Pay the Taxes?, Lanham, MD, Rowman & 

Littlefield Publishers, 2006, pp.48-109.).
24 2007 Technical Panel on Assumptions and Methods

age level of fertility. This is reasonable; however, 

changes in fertility across much of the industrialized world strongly supports three key observations: (1) the traditional methods (historical 

analysis, expert opinion) are poor at predicting 

changes in fertility level; (2) the traditional view 

about replacement fertility as a natural floor is 

being proved incorrect; and, (3) feedback loops 

that link demographic processes are usually overlooked.13 Adding another 100 million people to the 

U.S. population in the next 50 years, for example, 

may have a depressing effect on fertility if growth 

is highly concentrated geographically. Several 

economists have suggested that increases in public 

pensions, and particularly PAYGO pension schema, suppress subsequent fertility.14 Current models relating fertility to public policy treat fertility 

as exogenous to the pension system, rather than as 

a lagged endogenous input into the solvency of the 

system. Such an effect on a public pension system 

could operate through increasing income and payroll taxes, or the consumer price index. 

Historical Background

The total fertility rate (TFR) for the U.S. has been 

marked by temporary downturns and upswings, 

but overall fertility has charted a remarkably steady 

downward trend over the last 200 years.15 Because 

whites are the largest racial/ethnic group in the 

population, the fertility rate for the population as 

a whole closely tracks that of white females. As can 

be seen in Figure 5, fertility rates for white women 

fell steadily in the 1800s and in the early part of 

the last century. Fertility increased during the early 

years of the Great Depression in the 1930s16 and 

nearly doubled at the end World War II, reaching its 

peak in 1956, before resuming its historic decline 

to the current level of 2.05.

A closer examination of fertility rates by race/ethnicity shows this same downward trend for blacks 

and Hispanics. (See Figure 6.) Since 1980 the total 

fertility rate, weighted by the relative size of its racial/

ethnic components, has hovered at or around the replacement level of 2.11, with a narrow 25-year range 

of 1.80 (1983) to 2.08 (1990). While the rate for Hispanic women is higher overall than for white or black 

women, it, too, has been declining. In 2005, there was 

eight-tenths of a child difference between the higher 

TFR of Hispanics and either the white or overall TFR. 

For Mexican-origin mothers, the comparable TFR was 

greater by slightly more than one child.17

In Figure 7, historical trend lines allow comparison of the total fertility rate, the weighted average 

of age-specific birth rates for women defined to be 

in their child-bearing years at a point in time,18 and 

cohort fertility (CFR), which is fertility of the same 

women at successive ages.19 The TFR is sensitive 

both to the level and stability of age-specific fertility, 

as well as the timing of child-bearing. Although the 

cohort fertility rate smoothes out temporal fluctuations in the period TFR and yields a more straightforward interpretation, it can only be estimated after cohort reproduction is complete. As a result, its 

usefulness as a projection tool is limited.20

Reflecting on the historical data presented here, 

the Panel anticipates a historically low total fertility rate over the course of the next 25 years, with a 

narrow range of 1.5 to 2.1, and an ultimate TFR that 

may well be below replacement levels. However, it 

is important to note that a negative growth rate for 

the U.S. is not inevitable, depending on the sheer 

number of immigrants and their level of fertility. 

Uncertainty

There are several reasons for asserting that there 

is more uncertainty on the low side rather than 

13 Note we do not discuss rates of childlessness in this section. 

While as much as 18-20 percent of cohorts who have completed 

their childbearing years never bore children, the effect on the 

actuarial balance is likely to be trivial because of longer work lives 

of childless women. For data on childlessness in the U.S., see Abma, 

J.C. and G.M. Martinez, “Childlessness among Older Women in the 

United States: Trends and Profiles,” Journal of Marriage and Family, 68: 1045-1056, 2006. 

14 Boldrin, M., M. De Nardi, and L.E. Jones, “Fertility and Social Security,” NBER Working Paper 11146, 2005; and Ehrlich, Isaac and 

Jinyoung Kim, “Has Social Security Influenced Family Formation 

and Fertility in OECD Countries? An Economic and Econometric 

Analysis,” Journal of Pharmaceuticals Policy and Law, Vol. 9, 2007 

pp. 99-120. 

15 Although Hacker, 2004, dates the long term decline in white 

fertility to the 1840s and the drop in white marital fertility to after 

the Civil War. 

16 Greenwood, J., A. Seshadri, and G. Vandenbroucke, “The Baby 

Boom and Baby Bust,” The American Economic Review 95(1), 2005, 

pp. 183-207.

17 Martin, J.A., B.E. Hamilton, P.D. Sutton, et al., “Births: Final Data 

for 2004”, National Vital Statistics Reports, 55(1), Hyattsville, MD, 

National Center for Health Statistics, 2006. 

18 Typically this is considered to be within the age range 15-44, but in 

light of increasing age at child-bearing the National Center for Health 

Statistics now reports the number of births to women aged 45-49 and 

50+. See Hamilton B.E., J.A. Martin, S.J. Ventura, Births: Preliminary 

Data for 2005. Health E-Stats, Released November 21, 2006.

19 Data is from the National Center for Health Statistics and published by Schoen, 2006, and Preston and Sten, 2007. 

20 Schoen, R., Dynamic Population Models, Dordrecht: Springer, 

2007.
2007 Technical Panel on Assumptions and Methods 25

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

1800 1820 1840 1860 1880 1900 1920 1940 1960 1980 2000

Figure 5: Total Fertility Rate: White Women, 1800-1998

Total fertility rate

Figure 5: Total Fertility Rate: White Women, 1800-1998

1.50

1.70

1.90

2.10

2.30

2.50

2.70

2.90

3.10

3.30

1980 1985 1990 1995 2000 2005

Total White Black Hispanic

Figure 6: Total Fertility Rate by Race/Ethnicity: 1980-2004

Total fertility rate

Year

Figure 6: Total Fertility Rate by Race/Ethnicity: 1980-2004

on the high side of fertility in preparing 25-year 

and 75-year projections. Among these are: timing 

of births by parity (the total number of live births 

ever had by a woman); tempo vs. quantum differences; international comparisons with other highly developed countries; and new insights into the 

relationship between migrant fertility, especially 

births to Mexican-born mothers, and the overall 

fertility rate in the United States. 

Timing of Births, Parity, and Levels of Fertility

Most demographers attribute the decline in fertility in the United States and in the European Union 

to delayed childbearing patterns and to changes in 
26 2007 Technical Panel on Assumptions and Methods

the distribution of parity.21 Research done on the 

1960-61 birth cohort by Shkolnikov et al.22 demonstrated that the decline in fertility is related to more 

women having two or fewer births. We recommend 

that the Trustees carefully monitor birth rates and 

the timing of childbearing for the population as a 

whole, by race, ethnicity and nativity.

For most of the last century, births to older women have been associated with high fertility and 

high parity but this is no longer the case. As shown 

in Figure 8, birth rates for women 30 years of age 

and younger have been declining while births to 

mothers aged 40-44, and especially to women aged 

45-49, have been rising. Traditionally, late fertility has been interpreted as the opportunity cost of 

highly educated women who postpone childbearing. Preston and Sten,23 however, suggest that the 

effect of education on the timing of childbearing is 

overstated. To an unknown extent, the increasing 

fertility of women in their 40s may reflect increased 

availability and use of assisted reproductive technologies that can extend childbearing years, as well 

as minimize the consequences of infertility and 

subfecundity.

Regardless of the age of the mother, nearly threequarters of all births have been first or second-born 

children. From 1990 to 2004, nearly one-half (49.8 

percent) of all births to women aged 45 and over 

were first or second live births; only 15.3 percent 

were to women with six or more births. Consistent 

with these trends, the overall mean age of childbearing has been steadily rising from 25.0 in 1980, 

to 26.4 in 1990, to 27.5 in 2004. These same trends, 

of lesser magnitude, are evident in other racial 

and ethnic groups. In 2004, for example, when the 

mean age-at-first-birth was 25.4 for whites, it was 

25.2 for all Hispanics. In contrast, the average age 

of first birth for Mexican-origin mothers was 22.5, 

only 0.2 of a year lower than the average age at first 

birth for black mothers. 

Table 3 presents estimates of the period total 

fertility rate (TFR) and the mean age at first birth 

(MAFB) for the U.S. and select countries whose 

current fertility rates are considered to be at the 

“lowest-low” level. In addition to the U.S., Greece, 

Italy, Spain, and Japan, all experienced fertility 

rates at 2.0 or less in the 1970s-1980s and reached 

lowest-low levels (TFR of 1.3 or less) in the 1990s.24

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

1950 1960 1970 1980 1990 2000 2010

Period TFR

Cohort TFR

Figure 7: Period Total Fertility Rate and Cohort Total Fertility Rate: 1959-2005

Total fertility rate

Figure 7: Period Total Fertility Rate and Cohort Total Fertility Rate: 1959-2005

24 The TFR in Japan did not fall below 1.3 until 2003.

21 Kohler, et al., 2006, pp. 48-109, op. cit. 

22 Shkolnikov, V.M., E.M. Andreev, R. Houle, and J.W. Vaupel, “The 

Concentration of Reproduction in Cohorts of Women in Europe 

and the United States,” Population and Development Review, 33(1), 

March 2007. 

23 Preston, S.H. and S.R. Sten, “The Future of American Fertility,” 

Paper presented at the 9th Annual Joint Conference of the Retirement Research Consortium, Washington, D.C., August 9-10, 2007.
2007 Technical Panel on Assumptions and Methods 27

In 1980 the MAFB in the U.S. was 22.7, while in 

Italy and Spain the mean age was in excess of 25.0 

and 26.4 years of age in Japan. The annual rate 

of increase in the mean age-at-first-birth in all of 

the countries, except Japan, was in the range of 

0.14-0.19 from 1980-1990. But during the period 

1990-2000, the annual rate of increase in the mean 

age accelerated in Greece, Italy and Spain by an average of 0.23, while the annual rate of increase fell 

to 0.10 in Japan and to 0.07 in the U.S., a drop of 

nearly 50 percent relative to the average annual rate 

for the preceding decade. An average annual rate of 

increase in the MAFB of 0.20 is considered rapid,25

signaling a change in the timing of fertility.

Quantum Change and Shifts in Composition

While the Panel believes that lower levels of fertility 

are likely, we recognize that it is important to understand the factors that have led to a fertility level in the 

U.S. that is substantially above the experience of most 

other high-income nations. One might argue that the 

U.S. simply trails behind Europe and Japan, and that 

fertility will fall to historically low levels in future years, 

Country 1980 1990 2000 2002 Annual rate of Increase in 

MAFB 1990-2002 MAFB TFR MAFB TFR MAFB TFR MAFB TFR

Greece 24.1 2.23 25.5 1.39 27.3a 1.29 -- 1.25 0.2

Italy 25 1.64 26.9 1.33 28.7b 1.24 -- 1.27 0.26

Spain 25 2.2 26.8 1.36 29.1 1.24 -- 1.25 0.23

Japan 26.4 -- 27 -- 28 -- 28.3 1.29 0.1

U.S. 22.7 1.81 24.2 2.08 24.9 2.06 25.2c 2.04c 0.07

a = 1997; b = 1999; c = 2004

SOURCE: Kohler, et al. 2006: Tables 1 and 2; and Martin, et al. 2006: Table 14

Table 3: U.S. vs. Select Lowest-low Fertility Countries: Mean Age at First Birth (MAFB), and Total Fertility 

Rate, 1980 – 2002, and Annual Rate of Increase in MAFB (1990-2000)

-50

-41

-21 -13

-4

18

43

62

150

-100

-50

0

50

100

150

200

10-14 15-17 18-19 20-24 25-29 30-34 35-39 40-44 45-49

Figure 8: Percentage Change in Birth Rates by Age of Mother, US:1990-2004

Percent change

Figure 8: Percentage Change in U.S. Birth Rates by Age of Mother: 1990-2004

25 Kohler, et al., 2006, op. cit.
28 2007 Technical Panel on Assumptions and Methods

as has occurred in other wealthy countries. The 2003 

Technical Panel observed that the high fertility rate 

of U.S. women may be the result of a greater ability to 

combine work and childbearing. Flexible work hours, 

access to a range of public and private child support 

services, and the relative ease of leaving and re-entering the work force make this a more viable lifestyle option. However, if the real or opportunity costs of childrearing increase, the fertility rate may well decline. 

This scenario is in part determined by wage growth, 

productivity, and employment rates. The Panel suggests that the Trustees commission a detailed study of 

macroeconomic effects on childbearing in the U.S. in a 

model that allows for recursive linkages. 

Rather than extend the work of the 2003 Technical 

Panel, this Panel focused on the compositional differences between our population and those of the lowestlow fertility countries. As pointed out in Figure 6 some 

of the largest immigrant and minority groups within 

the U.S. have fertility levels that are well above the national average. In 2005, the total fertility rate (2.045) 

rose slightly from the previous year but was still below 

replacement levels of fertility. In contrast, the TFR for 

Hispanics in 2005 was above replacement (2.877) and 

41 percent higher than the national average. The rate 

for Mexican mothers was 3.021 in 2004, the last year 

for which the TFR is available by country of origin. 

Whether or not the fertility of Mexican-origin women 

will continue to exceed that of non-Hispanic white 

women by an average of one child in the short-term, 

remains to be seen. It is further unknown whether or 

not the fertility of Mexican-born women will be sufficient to rejuvenate the size and age structure of the 

U.S. population over the next 25 or 50 years. 

Fertility Behaviors of Mexican-Born and MexicanAmerican Women

Conventional wisdom is that the fertility behavior 

of migrants and their immediate descendents quickly 

approaches similar levels as the fertility of non-migrant, native-born white women. There are numerous reasons why migrants might adjust their fertility 

downward over time and across several generations 

of descendents, including cultural assimilation of 

U.S. fertility norms, adaptation to new economic 

opportunities, and the higher relative cost of child 

bearing in the U.S.26 These theories lead us to expect 

a decline in migrant fertility.

Immigrants from Mexico have the potential to 

have a large effect on the fertility rates in the U.S. 

If we look closely at fertility trends in Mexico, we 

see that the total fertility rates in that country are 

falling and, as of 2000, were almost on a par with 

the U.S. In fact, over the next 30 years the TFR in 

Mexico is expected to fall to 1.86. Much of this has 

been attributed to a rapid decline in larger families, 

a rapid uptake in contraception, and increases in 

age at first birth.27 Even in the context of declining fertility trends in their country of origin, the 

fertility rate of Mexican immigrants has exceeded 

Mexican national levels since 1994.28 However, 

what may be even more surprising is that third or 

higher generation Mexican-Americans, overall, 

have more children than Mexican migrants or firstgeneration Mexican-American women.29 Research 

has shown that cohort differences in the timing of 

childbearing account for this anomaly and it is not 

anticipated that these generational differences will 

persist.30 Parrado and Morgan further show that 

when cohorts and migrant generations are arrayed 

on a more realistic generational time line, fertility 

differentials largely converge between whites and 

Mexican-born migrants, as well as with second and 

third generation Mexican-Americans. 31

While immigration will continue to impact the 

increase in the U.S. resident population in proportion to the size of migration streams, at this time 

neither the number of new additions, nor the fer26 Lindstrom, David P. and Silvia G. Saucedo, “The Short- and LongTerm Effects of U.S. Migration Experience on Mexican Women’s 

Fertility”, Social Forces, Vol. 80, No. 4, June 2002, pp. 1341-1368.

27 Tuiran, R., V. Partida, O. Morjarro, and E. Zuniga, “Fertility in 

Mexico: Trends and Forecast”, Completing the Fertility Transition, 

Department of Economic and Social Affairs, Population Division, 

United Nations, 2002, pp. 483-506. 

28 This cross-over was not observed in 1997, however. 

29 Using pooled data from the June Fertility Supplements to the 

1984-1986 Current Population Surveys (CPS), Bean et al., 1984, first 

noted the inverse correlation between fertility and generational status of Mexican-Americans in cross-section. Using the 1986-88 CPS 

Fertility Supplements, Bean et al., 2000, reached similar conclusions.

30 Frank, R. and P. Hauveline, “A Crossover in Mexican and MexicanAmerican Fertility Rates: Evidence and Explanations of an Emerging 

Paradox,” Demographic Research, Vol. 12:78-101, 2005.

31 Parrado, E. A. and S. P. Morgan, “Intergenerational Fertility among 

Hispanic Women: New Evidence of Immigrant Assimilation”, unpublished manuscript, 2007. Earlier studies based on cross-sectional 

data alone compare the fertility of same-aged women who differ by 

self-reported generational status, especially second- and third-generation Mexican-American women. This comparison involves descendents of different Mexican birth cohorts, born 25-30 years apart. 

Parrado and Morgan, on the other hand, index their comparisons to 

first generation migrant birth cohorts. The completed fertility estimates for the 2nd and 3rd generation Mexican-Americans are offset 

by a 25-year lag between adjacent generations. Their approach allows 

for pseudo inter-generational estimates that more realistically mimic 

migrant family progress in adapting to the U.S.
2007 Technical Panel on Assumptions and Methods 29

tility of their descendents three generations out, is 

of a magnitude to offset the momentum of nearreplacement fertility over the next 25-50 years.

B. Mortality

Assumption Recommendation A-2: For the intermediate-cost scenario, the Panel recommends that 

assumed ultimate rates of mortality decline by age 

and sex be increased to an average of 1.00 percent 

per year to be consistent with those observed during 1953–2003 for the total population. Assumed 

ultimate rates of mortality decline for the low-cost 

projections should be held at their current levels 

(averaging 0.33 percent per year). Assumed ultimate rates of mortality decline for the high-cost 

projections should be increased to an average of 

2.00 percent to reflect the potential for the U.S. to 

reach rates of mortality reduction seen in international data.

Method Recommendation M-8: The Panel recommends that the mortality projection model be simplified by dropping separate projections by cause 

of death and stating assumptions in terms of agespecific rates of decline for all-cause mortality.

Method Recommendation M-9: The Panel recommends that the infinite horizon mortality projection model be dropped.

Overview 

The Panel recommends that the Trustees increase 

the assumed rates of mortality decline for the intermediate-cost and high-cost projections, while also 

simplifying the projection model by eliminating 

the breakdown by causes of death. This recommendation can be justified by an analysis of historical 

trends for the U.S. alone, but it is also supported 

by the recent mortality experience of other highincome countries.32 The 1.00 percent per year ultimate rate of decline recommended by the Panel for 

the intermediate-cost projection is consistent with 

levels recommended by the 1999 and 2003 Technical Panels and represents a reaffirmation of the view 

of a substantial number of independent experts 

that the Trustees should increase this parameter. 

The last significant increase in this parameter was 

made in 2000, but to a level substantially below the 

level recommended by the 1999 Panel. 

The Trustees currently project rates of mortality 

decline separately for each of seven causes of death. 

These projections are based on cause-specific mortality data for 1983–2003 for five age groups, two 

sexes, and seven causes, for a total of 70 parameters. 

Consideration of the low-cost and high-cost projections increases the total number of parameters to 

210. Such detail should be dropped from the projection process; it is unlikely to produce more accurate 

results and there is little empirical basis for current 

assumptions. Moreover, the Panel believes that the 

use of the 21-year period 1983–2003 as the basis 

of a 75-year projection is too short; a better basis 

would be the 51-year period 1953–2003. 

The Panel believes that there is substantial uncertainty in the 75-year projection and that the 

uncertainty is asymmetric with greater risk on the 

high side. The Panel recommends that the ultimate 

rates of mortality decline for the low-cost projection be held at their current level of 0.33 percent 

per year. The ultimate rates of mortality decline 

for the high-cost projection, however, should be 

increased substantially to 2.00 percent to reflect 

intrinsic uncertainty inherent in projections based 

solely on experience data from the U.S., as well as 

additional uncertainty arising from the potential 

for the U.S. to reach rates of mortality decline seen 

in international data for 33 high-income countries 

with higher life expectancies. 

The uncertainty of the future mortality projection increases as the interval from the base year to 

the targeted future year of the projection increases. Given that existing projections of mortality 75 

years into the future are already highly uncertain, 

projections of mortality even further into the future (including over the “infinite horizon”) will be 

even more uncertain, making it impossible to select 

any one set of assumptions as a best estimate or to 

quantify the uncertainty in a meaningful way. The 

2003 Panel33 recommended “assuming a cessation 

of mortality decline at all ages beginning in 2200 

following a linear reduction in rates of decline (toward zero) beginning at the end of the ultimate period (i.e., 2077).” The stated basis for this assumption was that “one should not assume positive rates 

of mortality decline farther into the future than 

has been observed in the past.”34 The current Panel 

rejects this notion and believes there is no credible reason to expect that mortality declines will 

33 Technical Panel on Assumptions and Methods (2003), Report to 

the Social Security Advisory Board, October 2003, p. 40. 

34 Ibid 

32 U.S. Census Bureau, National Population Estimates, July 1, 2006, 

Population Division, Washington, D.C., 2007.
30 2007 Technical Panel on Assumptions and Methods

0

2,000

4,000

6,000

8,000

10,000

12,000

1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000

Total

Under 65

65 and Over

Figure 9: Age-Adjusted Central Death Rates by Age and Calendar Year, 1900-2003

Number of deaths per 100,000 population

Year

Figure 9: Age-Adjusted Central Death Rates by Age and Calendar Year, 1900-2003

cease in 2200. Given the range of scientific breakthroughs in our understanding of the fundamental 

mechanisms of disease and aging that may occur 

over the next 200 years, the Panel considered the 

possibility that mortality declines in 2200 may be 

substantially larger than the current declines, with 

life expectancy increasing one to two years or more 

per decade. Carnes and Olshansky35 argue that 

major breakthroughs will be essential if continued 

mortality reductions are to occur after life expectancy at birth reaches about 85 years. 

Historical Background 

Mortality risks across the age range fell dramatically during the 20th century (see Figure 9), leading 

to a large rise in life expectancy at birth (and at all 

ages) for both men and women in the U.S. 

For the total population, life expectancy at birth 

rose from 47.7 years in 1900 to 76.6 years in 2000, 

a 61 percent increase over the century. However, 

most of this increase (71 percent) occurred before 

1950. Life expectancy at older ages exhibited much 

smaller increases, with major differences in the 

timing. At age 65, for example, life expectancy rose 

from 11.7 years in 1900 to 17.6 years in 2000, a 

28 percent increase. However, most of this increase 

(66 percent) occurred after 1950. These timing differences are fundamental to our choice of the specific historical period 1953–2003 as the basis of the 

75-year projections.

Part of the slowdown in the rise of life expectancy at birth was due to the disproportionate influence of infant and child survival on this measure of 

average lifespan. Once childhood mortality became 

rare, there were few deaths left to eliminate in early 

life, making it more difficult to raise life expectancy 

at birth.36 In addition, there was a substantial reduction between the first and second halves of the 

20th century in rates of mortality decline among 

both children (ages 0–14) and adults of working 

age (15–64); see Figure 10. 

On the other hand, at ages 65 and above, the pace 

of mortality decline generally accelerated over the century, thanks to an unprecedented reduction in certain 

forms of old-age mortality (especially cardiovascular 

disease) beginning in the late 1960s; see Figure 11. 

Figures 9–11 demonstrate clearly that mortality declines varied considerably from decade to decade, and by sex. The 1940s and 1970s stand out as 

periods of very rapid improvement, while the last 

20 years have been less favorable, especially for fe-

 35 Carnes, Bruce A. and Jay S. Olshansky, “A Realist View of Aging, 

Mortality, and Future Longevity,”, Population and Development 

Review, 33(2):367–381, 2007. 

36 Keyfitz, Nathan, Applied Mathematical Demography, 2nd Edition, 

New York: Springer-Verlag, 1985; and Wilmoth, John R., “The Future of Human Longevity: A Demographer’s Perspective,” Science, 

280: 395-97, 1998.
2007 Technical Panel on Assumptions and Methods 31

0.0

200.0

400.0

600.0

800.0

1,000.0

1,200.0

1,400.0

1,600.0

1,800.0

1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000

Total

Male

Female

Figure 10: Age-Adjusted Central Death Rates at Age 0-64 by Sex and Calendar Year, 1900-2003

Number of deaths per 100,000 population

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000

Total

Male

Female

Figure 11: Age-Adjusted Central Death Rates at Age 65 and Over by Sex and Calendar Year

Number of deaths per 100,000 population

Figure 10: Age-Adjusted Central Death Rates at Age 0-64 by Sex and Calendar Year, 1900-2003

Figure 11: Age-Adjusted Central Death Rates at Age 65 and Over by Sex and Calendar Year, 1900-2003

males. The period 1982–1999 represented a period 

of stagnation for females, but not males, while the 

period 1954–1968 represented a period of stagnation for males, but not females. 

The Panel’s recommendation that the projections 

be based on the 51-year period 1953–2003 ensures 

that the calibration data include sub-intervals of 

rapid improvement as well as stagnation. This recom-
Alternative Low Cost Intermediate Cost High Cost Low Cost Intermediate Cost High Cost

Male Female

Under Age 15

Heart Disease 0.5 1.0 2.0 0.5 1.0 2.0

Cancer 0.8 2.0 5.2 0.8 2.0 5.2

Vascular Disease 0.3 0.6 0.7 0.3 0.6 0.7

Violence 0.6 0.9 1.2 0.6 0.9 1.2

Respiratory Disease 1.5 2.5 3.0 1.5 2.5 3.0

Diabetes Mellitus 1.1 1.8 2.3 1.1 1.8 2.3

Other 2.0 1.8 1.5 2.0 1.8 1.5

Resulting Total * 1.43 1.54 1.48 1.46 1.57 1.49

Ages 15 - 49

Heart Disease 1.1 2.3 3.1 1.1 2.2 3.0

Cancer 0.2 0.5 1.9 0.2 0.5 2.0

Vascular Disease 1.0 1.8 2.1 1.0 1.8 2.1

Violence 0.5 0.8 1.6 0.5 0.8 1.6

Respiratory Disease 0.3 0.5 0.8 0.3 0.5 0.8

Diabetes Mellitus 0.2 0.3 0.4 0.2 0.3 0.4

Other 0.5 0.8 1.2 0.3 0.6 1.0

Resulting Total * 0.52 0.86 1.54 0.41 0.73 1.45

Ages 50 - 64

Heart Disease 1.1 2.0 2.9 1.1 2.2 3.1

Cancer 0.1 0.4 1.2 0.1 0.4 1.3

Vascular Disease 1.0 1.5 2.1 1.0 1.6 2.3

Violence 0.5 0.8 1.6 0.5 0.8 1.6

Respiratory Disease 0.3 0.6 0.9 0.3 0.7 0.9

Diabetes Mellitus 0.2 0.3 0.6 0.2 0.3 0.6

Other 0.5 0.9 1.5 0.4 0.8 1.4

Resulting Total * 0.46 0.82 1.48 0.36 0.72 1.41

Ages 65 - 84

Heart Disease 0.7 1.7 2.3 0.8 1.8 2.4

Cancer 0.1 0.5 1.8 0.1 0.5 1.8

Vascular Disease 1.3 2.5 3.1 1.3 2.6 3.1

Violence 0.5 1.2 1.7 0.5 1.2 1.7

Respiratory Disease 0.0 0.2 0.4 0.0 0.2 0.4

Diabetes Mellitus 0.3 0.6 0.9 0.3 0.6 0.9

Other 0.1 0.3 0.6 0.1 0.3 0.6

Resulting Total * 0.31 0.72 1.30 0.30 0.68 1.23

Ages 85 and older

Heart Disease 0.6 1.2 1.7 0.6 1.2 1.7

Cancer 0.0 0.4 1.2 0.0 0.3 1.2

Vascular Disease 0.8 1.9 2.5 0.8 1.8 2.4

Violence 0.4 0.9 1.2 0.4 0.9 1.2

Respiratory Disease 0.0 0.2 0.4 0.0 0.2 0.4

Diabetes Mellitus 0.3 0.6 0.9 0.3 0.5 0.8

Other 0.0 0.2 0.5 0.0 0.2 0.5

Resulting Total * 0.25 0.62 1.03 0.26 0.61 1.01

* Resulting total represents average annual percent reduction in age-adjusted death rates for the last 50 years of the 75-year projection period.

Source: Social Security Administration, Office of the Chief Actuary, August 16, 2007.

Table 4: Assumed Ultimate Average Annual Percentage Reductions in Central Death Rates, 2007 Trustees Report
2007 Technical Panel on Assumptions and Methods 33

mendation gives appropriate weight to the arrested 

decline above age 80 beginning in the 1980s, as well 

as mortality reversals above age 85 during the 1990s. 

The 1999 and 2003 Panels suggested that unfavorable trends in old-age mortality during the 1980s and 

1990s may reflect the delayed effects of increased 

levels of smoking among women; recent articles offer 

empirical support for this explanation.37

Current Trustees’ Assumptions 

In recent years, the Trustees have specified their 

mortality assumptions in terms of ultimate rates 

of mortality decline by age, sex, and cause of death. 

For their 2007 Report, the complete set of assumptions consists of 70 numbers (5 age groups × 2 sexes 

× 7 cause categories). Consideration of the low-cost 

and high-cost projections increases the total number 

of parameters to 210; see Table 4 (unchanged since 

2002). Technically, these ultimate rates are the fundamental assumptions of the model, and all other summary statistics are results of the projection exercise. 

However, these values are not included in the Trustees Report, nor are they otherwise publicly available. 

The Panel included them here to make them publicly 

available and recommends that the Trustees make 

them available in future reports or in supplementary 

online tables (unless the Trustees adopt our Method 

Recommendation M-8 to drop the cause of death detail from the projection process). 

In lieu of the detailed tables, the Trustees summarize these assumptions by reporting the implied ultimate rates of decline (i.e., during the last 50 years 

of the 75-year projection horizon) for all-cause mortality and for a limited number of broad age groups 

(e.g., 0–14, 15–64, and over 65), adjusted to remove 

the effects of changes in the distribution of the 

population by age and sex. For example, the 2007 

Trustees Report contains the following description: 

“After adjustment for changes in the age-sex 

distribution of the population, the resulting total 

death rates are projected to decline at ultimate average annual rates of about 0.33 percent, 0.70 percent, and 1.21 percent between 2031 and 2081 for 

alternatives I, II, and III, respectively. In keeping 

with the patterns observed in the historical data, 

future rates of decline are assumed to be greater for 

younger ages than for older ages, but to a substantially lesser degree than in the past. Accordingly, 

age-sex-adjusted death rates for ages 65 and over 

are projected to decline at average annual rates of 

about 0.28 percent, 0.66 percent, and 1.15 percent 

between 2031 and 2081 for alternatives I, II, and 

III, respectively.”38

The Panel agrees that summarization of the assumptions in Table 4 over all ages or for broad 

age ranges is reasonable and provides appropriate 

transparency. Indeed, this is precisely the mode the 

Panel selected in formulating its recommendations 

to the Trustees with respect to their assumptions: 

Nonetheless, the Panel believes that it will not be 

apparent to the general reader that these assumptions imply a gradual deceleration in the pace of 

mortality decline throughout the projection interval. During the ultimate period and beyond, this 

deceleration is driven by the cause-of-death methodology: over time, categories that are assumed to 

decline the most slowly account for an increasing 

portion of deaths.39

In addition to this built-in deceleration, there is 

also an explicit assumption of a pronounced slowdown in mortality decline below age 65 during the 

first 25 years of the projection period. Below age 15 

this deceleration is roughly twice as large as the historical slowdown that occurred between the first and 

second halves of the 20th century; for ages 15-64 it is 

about 1.5 times as large. For ages 65 and above, the 

Trustees’ assumptions imply rates of mortality decline throughout the projection interval (0.66 percent 

per year) and for the sub-interval 2031–2081 (also 

0.66 percent per year, as noted above) that lie below 

the historical average both for the 20th century as a 

38 2007 Annual Report of the Board of Trustees of the Federal Old-Age 

and Survivors Insurance and Federal Disability Insurance Trust Funds, 

U.S. Government Printing Office: Washington, D.C., 2007, p. 74. 

39 Wilmoth, John R., “Are Mortality Projections Always More Pessimistic When Disaggregated by Cause of Death?” Mathematical 

Population Studies, 5(4), 1995, pp. 293–319.

37 Pampel, Fred C, “Cigarette Use and the Narrowing Sex Differential in Mortality,” Population and Development Review, 28(1), 2002, 

pp. 77–104; and Wang, Haidong, and Samuel H. Preston, “Forecasting U.S. Mortality Using Cohort Smoking Index,” Demography, 

43(4):631–646, 2006.

Assumption Set Low 

Cost

Intermediate 

Cost

High 

Cost

Trustees’ 

Assumptions

0.33 0.70 1.21

Panel’s 

Recommendations

0.33 1.00 2.00
34 2007 Technical Panel on Assumptions and Methods

whole (0.78 percent) and for the period 1950–2000 

(0.82 percent). The overall rates of decline for the 

overlapping periods 1950–2000 and 1953–2003 

were 0.98 percent and 0.97 percent, respectively, 

both of which were rounded to 1.00 percent in forming our recommendation for the intermediate-cost 

projection based on analysis of long-term historical 

trends for the United States. 

Explanation of Panel’s Recommendations 

Mortality projection involves a series of choices 

about how to extrapolate historical trends in death 

rates by age. Five of the most important choices 

concern the following: (1) method(s) for computing 

historical rates of change in age-specific death rates; 

(2) whether to consider various components of mortality separately (i.e., causes of death); (3) whether 

to perform separate projections for subpopulations 

(by sex, race, etc.); (4) historical period(s) from 

which assumed rates of future mortality decline are 

derived; and (5) whether to accelerate or decelerate 

rates of decline compared to the historical baseline. 

More detail about various aspects of these topics is 

contained in Wilmoth.40

Rates of Change

The first issue is methodological, concerning the formulas used to compute rates of mortality decline by age. 

The 2003 Panel considered two methods—the “slope” 

and “endpoint” methods. Briefly, the slope method 

consists of using a simple statistical technique to find 

the line that best fits the historical mortality trend for 

a given age group. On the other hand, the endpoint 

method considers only the decline between the beginning and the end of the time period, ignoring intermediate data. Differences between the two methods can 

be quite significant in certain cases, affecting assumed 

rates of mortality decline that are derived from historical experience. Nevertheless, each method possesses 

certain advantages from a methodological point of 

view.41 The 2003 Panel used an average value based on 

both methods for analyzing historical trends and setting assumptions. The current Panel used a modified 

form of the endpoint method that provided an alternative approach to dealing with the limitations of the 

simple form of the endpoint method (see below). 

Parsimony

The second and third issues exemplify the need for 

a balance between simplicity and complexity. In both 

cases, the current Panel agreed with the 2003 Panel 

that the projection methods should favor simplicity. 

This Panel noted, however, that the principle of parsimony should apply only to the projection methods 

and not to the analysis of historical trends used to 

support the projections. Thus, the Panel applauds the 

Trustees and the Office of the Chief Actuary for investigating past mortality trends separately by cause 

of death and for men and women. (Other breakdowns could be useful as well, for example, by race, 

ethnicity, income class or nativity.) However, making 

separate assumptions about future rates of mortality 

decline by cause of death or for sub-populations adds 

complexity to the projection model without evidence 

of improved accuracy in forecasting. 

A model based on separate projections by cause of 

death over a long time horizon is both implausible 

and inconsistent with historical experience. Historically, rates of decline for specific causes of death (or 

broad categories of causes) have tended to vary much 

more than for all-cause mortality, as populations often focus on combating those causes of death that 

dominate mortality patterns at a given moment. In 

the most successful cases, breakthroughs against specific diseases lead to rapid reductions in deaths from 

that cause. For example, antibiotic therapies sharply 

reduced infectious disease in the 1940s, and various 

factors decreased cardiovascular disease in the 1970s.

Methodologically, implementation of the cause 

of death assumptions implicitly assumes that the 

selected list of causes is the correct list and that 

the causes are functionally independent. Neither 

of these conditions holds. For example, in reviewing the list of diseases in Table 4, the Panel noted 

that diabetes is a risk factor for heart and vascular 

disease so that changes in any one of these “causes” 

cannot be independent of changes in any other. 

All three are related to diet and nutrition which 

may be treated as more fundamental in the causal 

chain.42 Similarly, cancer and respiratory disease 

are related to cigarette smoking which may also be 

treated as more fundamental in the causal chain. 

Violence is related to alcohol use (murder) and depression (suicide), both of which are components 

of the “other” cause category.

40 Wilmoth, John R., “Overview and Discussion of the Social Security 

Mortality Projections,” Social Security Advisory Board Working Paper, 

2005. 

41 Ibid.

42 Stallard, Eric, “Demographic Issues in Longevity Risk Analysis,”, 

Journal of Risk and Insurance, Vol. 73(4): ), 575–609, 2006, pp. 

575–609.
2007 Technical Panel on Assumptions and Methods 35

Furthermore, the empirical basis for the Trustees’ 

current cause-specific assumptions seems to be weak. 

In general, it is very difficult to construct consistent 

time series of mortality data by cause of death over 

long historical periods (for any country, not just the 

U.S.) due both to a lack of data for earlier periods and 

to changes in cause-of-death coding practices over 

time. The Trustees’ current projections are based on 

mortality data by cause for the U.S. beginning with 

1979. Cause-specific mortality data are available electronically for the period 1968–1978, but are coded 

using a prior version of the International Classification of Diseases and are not used by the Trustees.

Thus, on the basis of trends over little more than 

two decades, the Trustees derive rates of mortality 

decline for seven hypothetically independent causeof-death categories over a time horizon extending 

from 75 years to infinity. However, the connection 

between data and assumptions is not always clear. 

For example, the assumed ultimate rate of decline 

for cancer mortality in the 65–84 age range is 0.50 

percent per year for both sexes, although observed 

values were 0.23 percent for men and -0.69 percent 

for women during 1981–2001.43 There is little written explanation of how these assumptions were developed; the Panel recommends that this information 

be made more readily available if the current method 

is retained.

Bell and Miller44 explain the assumptions as 

follows:

“Ultimate annual percentage reductions in central death rates by sex, age 

group, and cause of death were postulated 

for years after 2029. The broad age groups 

for which specific rates of reduction were 

selected are: under age 15, ages 15–49, 

ages 50–64, ages 65–84, and age 85 and 

older.”

“Even though ultimate annual percentage reductions in central death rates 

are postulated for the seven causes ..., 

the resulting percentage reduction in ageadjusted central death rates for all causes 

combined are carefully reviewed, analyzed, 

and adjusted to assure consistency with 

the overall assumed rates of reduction. For 

each age and sex group, the decomposition 

of the percentage reduction by causes also 

provides a useful tool to test the reasonableness of the overall reduction.”

Material presented to the Panel by OCACT45 indicated that:

“Ultimate annual percentage reductions in central death rates are assumed 

to apply for years starting with 2030. The 

percentages were determined based on historical trends and consideration of many 

factors ... which affect mortality. Expected 

rates of improvement in mortality by cause 

of death have long played a role in selection of ultimate mortality improvement assumptions for the Trustees Reports. While 

these rates by cause of death have not effectively “controlled” the outcome for assumptions reflecting all causes combined, they 

serve as an important basis for analysis 

relative to past trends and for assessment 

of reasonableness of future assumptions.” 

“Because reductions in mortality have 

differed widely by age in the past, the ultimate reductions in death rates have been 

selected to vary by age group. Historically, 

reductions have been very rapid at the 

youngest ages. However reductions at the 

highest ages, 85 and over, have been very 

slow. [The Trustees’] assumptions have reflected for many years the belief that neither 

of these extremes will persist indefinitely 

into the future. The Trustees assumptions 

have reflected slower improvement at the 

youngest ages than evidenced over the past 

century and faster improvement at the highest ages (85 and over) than experienced historically. While this “compression” of rates 

of mortality improvement is in conflict with 

a literal interpretation of the Lee and Carter 

method, it was nevertheless endorsed explicitly by the 1999 Technical Panel, where 

Ron Lee was the principal demographer on 

the panel.” 

These descriptions indicate that a substantial 

amount of professional judgment is involved in 

setting the ultimate rates of mortality decline 

used by the Trustees. One critical component of 43 See Table 3 in Bell, Felicitie C., and Michael L. Miller, Life Tables 

for the United States Social Security Area 1900–2100, Actuarial 

Study No. 120, Social Security Administration, Publication No. 

11-11536, 2005. 

44 Ibid, p. 8.

45 Documents presented by the Office of the Chief Actuary to the 

Technical Panel, December 2, 2006.
36 2007 Technical Panel on Assumptions and Methods

this process appears to be an evaluation of the 

implications for all-cause mortality of the selected set of ultimate rates. 

The Panel’s recommendation takes this approach 

one step further and shifts the focus solely to allcause mortality without explicit consideration of 

the cause specific components. This is feasible given 

that there is no aspect of the actuarial calculations 

that depends on cause specific mortality projections. 

Moreover, once the cause-specific mortality projections are dropped, much longer historical periods 

can be used as the basis of the projections. Regarding sub-populations, separate mortality projections 

based on different historical rates of decline lead 

either to continual divergence between groups, or 

to convergence and eventual crossover (i.e., where 

groups change their relative positions). Both situations seem rather unlikely, at least for long-term 

projections. Although recent differential trends 

by sex could plausibly continue for another 10–20 

years, the Panel recommends that ultimate rates of 

mortality decline be equal for men and women, derived from trends for the total population. 

International comparisons can also be helpful as 

a guide to future mortality trends despite differences in levels. The U.S. differs from other wealthy 

countries in ways that affect the overall level of 

mortality (e.g., more inequality, a less extensive social safety net), and the current gap in levels could 

remain for many years. However, it seems much 

less likely that the pace of mortality decline will be 

vastly different over the long term amongst this 

close-knit group of nations. The post-1980 slowdown in mortality reduction for the U.S. was not 

typical; most high income countries have enjoyed 

an accelerated mortality decline at older ages during the last two decades, sometimes starting from 

lower levels than the U.S. in 1980.46 These experiences support the Panel’s recommendation for a 

projected recovery from the recent period of slow 

mortality decline in the U.S. 

Use of Historical Experience 

The fourth and fifth issues concern the subjective application of historical experience to choices 

about assumed rates of future mortality decline. A 

comparison of 20th century trends before and after 1950 is informative for these choices. Figure 10 

46 Wilmoth, 2005, op. cit.; and Bongaarts, John, “How Long Will 

We Live?” Population and Development Review, 32(4):605–628, 

2006.

shows that there was a pronounced deceleration in 

rates of mortality decline at younger ages between 

1900–1950 and 1950–2000, although the trend 

was quite variable from decade to decade. On the 

other hand, Figure 11 shows that the rate of mortality decline above age 65 increased from the first 

to the second half of the 20th century. This change 

might be taken as evidence that the historical peak 

rate of mortality decline at older ages has not yet 

arrived. Indeed, the possibility of major breakthroughs in our understanding of the fundamental 

mechanisms of disease and aging might be used to 

justify an assumption of a continued acceleration of 

mortality decline at older ages. However, the Panel 

believes that this argument would be too speculative to serve as a “best estimate”. 

Although it is generally accepted that long-term 

mortality projections should not be based on short 

historical intervals, the Panel believes that half 

a century is long enough to avoid giving undue 

weight to atypical, short-term trends. Figure 12 

displays the changes that would occur in the calculated annual rates of decline as one shifted the start 

year of the historical base period throughout the 

interval 1940–2002, using the “endpoint method” 

identified above. The calculations in Figure 12 are 

based on the data displayed in Figure 9 and clearly 

indicate that the estimated rate of decline depends 

on the selection of the base period. For example, 

the 0.97 percent decline for 1953–2003 would 

change to 1.19 percent if the base period were 

1968–2003 and to 0.65 percent if the base period 

were 1982–2003. The variability in the estimated 

rate of decline is smallest for base periods prior to 

1963 where the recommended value of 1.00 percent 

is reasonably representative for all-age mortality.

Further insight into the recommendations can be 

obtained by considering the sex-specific rates of decline displayed in Figure 13, based on stratification 

of the data displayed in Figure 9.

The differences between the sexes in Figure 13 reflect the different impacts of the respective stagnation periods, 1954–1968 for males and 1982–1999 

for females. Given the Panel’s recommendation that 

the ultimate rates of mortality decline be equal for 

men and women, as derived from trends for the total population, it is apparent from Figure 13 that this 

will be most reasonably accomplished if the selected 

base period starts in 1963 or earlier, in which case 

the rates of decline for both males and females would 

close to 1.00 percent, the Panel’s recommendation. 
2007 Technical Panel on Assumptions and Methods 37

The factors that may plausibly contribute to future mortality reductions may be best represented 

by a baseline that goes back 50–70 years. During 

this period, the medical treatment of sick persons 

became, for the first time in history, one of the 

major forces propelling mortality downward. This 

trend began in the 1930s with the introduction of 

an early generation of anti-bacterial drugs.47 Other 

factors, broadly characterized as improvements in 

living standards and public health, drove earlier 

mortality declines. All of these factors played a role 

in the mortality reductions observed since 1950 

in the U.S., and all of them are likely to influence 

47 McKeown, Thomas, The Role of Medicine: Dream, Mirage, or 

Nemesis, Oxford, U.K., Basil Blackwell, 1979.

All Ages Ages 0-64 Ages 65+

Figure 12: Alternative Calculations of the Average Annual Rate of Decline in Age-SexAdjusted Death Rates, Starting at Each Calendar Year in the Interval 1940-2002 and Ending in 

2003, All Ages and by Age Groups 0-64 and 65+

0.0%

0.2%

0.4%

0.6%

0.8%

1.0%

1.2%

1.4%

1.6%

1.8%

2.0%

1940 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005

Year

Average annual rate of decline

Figure 13: Alternative Calculations of the Average Annual Rate of Decline in Age-SexAdjusted Death Rates Starting at Each Calendar Year in the Interval 1940-2002 and Ending in 

2003, All Ages, by Sex

-0.2%

0.0%

0.2%

0.4%

0.6%

0.8%

1.0%

1.2%

1.4%

1.6%

1.8%

2.0%

1940 1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005

Year

Total Male Female

Average annual rate of decline

Figure 12: Alternative Calculations of the Average Annual Rate of Decline in Age-Sex-Adjusted Death Rates, 

Starting at Each Calendar Year in the Interval 1940-2002 and Ending in 2003, All Ages and by Age Groups 

0-64 and 65+

Figure 13: Alternative Calculations of the Average Annual Rate of Decline in Age-Sex-Adjusted Death Rates 

Starting at Each Calendar Year in the Interval 1940-2002 and Ending in 2003, All Ages, by Sex
38 2007 Technical Panel on Assumptions and Methods

future trends as well. These mortality reductions 

occurred despite the negative health effects of cigarette smoking and the more recent onset of the 

“obesity epidemic” and it is reasonable to expect 

that they will continue even in the face of these and 

other negative factors. 

Wang and Preston demonstrated that the sex differences in mortality over the period 1948–2003 

occurred on a cohort basis with increasing relative mortality for males born during or prior to 

1903–1907 and decreasing relative mortality for 

males born during or after 1908–1913 at least 

through the cohort born in 1948–1953.48 These differences were shown to be associated with sex differences in cigarette smoking by cohort with males 

attaining their peak smoking rates one generation 

earlier than females (i.e., about 25 years). An important outcome of their analysis was the prediction that “men’s mortality will benefit enormously 

from reductions in smoking that have already 

occurred.”49 These changes were predicted to lead 

to a substantial narrowing of the sex differences in 

mortality over the next several decades.

The Panel is skeptical about the quality of mortality 

data from the first half of the 20th century, especially 

the accuracy of age reporting at older ages, and is unwilling to recommend using such data. This position 

effectively limits the starting year of the recommended 

baseline periods to the range 1950–1963, with a preference for periods of 50 years. Thus, the Panel recommends that assumed ultimate rates of mortality decline at older ages be based directly on the experience 

of 1953–2003, with neither the slowdown implied in 

the Trustees’ current assumptions nor the uptick implied by models that assume major breakthroughs. 

Conclusion

The Panel recommends using 1953–2003 as the 

historical baseline. Using the full 20th century for 

this purpose would be another possibility, but then 

the assumed pace of mortality decline at older ages 

would be slightly slower (see Figures 9–11). In contrast, the mortality decline at younger ages was much 

slower on average during the second half of the 20th 

century; therefore, the assumed rates of decline 

would be much higher with a baseline of 1900–2003 

instead of 1953–2003. The most compelling reason 

to prefer the baseline of 1953–2003 over 1900-2003 

is that the second half of the century was character48 Wang and Preston, 2006, op. cit. 49 Ibid, p. 643

ized by a more even pace of mortality decline across 

the age range, and it is reasonable to assume that 

this pattern will prevail in the future as well.

The 1999 and 2003 Panels differed with respect 

to their opinions regarding the use of the 25-year 

phase-in period during which the baseline rates 

of decline were linearly blended with the ultimate 

rates of decline, with the 2003 Panel recommending 

a more rapid transition over a 10-year phase-in. The 

current Panel is satisfied with the 25-year phase-in 

period and believes that it represents a reasonable 

method of transitioning to the ultimate rates of decline in Assumption Recommendation A-2. 

C. Immigration

Assumption Recommendation A-3: The Panel recommends that immigration scenarios should tie 

the level of net immigration to the size and growth 

of the U.S. population rather than decreasing or increasing constant numbers of immigrants. The Panel recommends that the Trustees move toward expressing their ultimate net migration assumptions 

as rates (annual number of net migrants divided by 

population size).

Assumption Recommendation A-4: The Panel 

strongly recommends that the Trustees increase 

significantly their assumptions regarding future 

levels of net international migration; at a minimum, projections of future migration should be 

brought into line with current measured levels of 

net international migration. 

n	 In the intermediate scenario, net international migration should increase from 1,350,000 

in 2007 by 1.0 percent per year through 2030; 

thereafter, net international migration should 

increase at 0.5 percent per year. At this level, immigration as a percent of population (the “net 

migration rate” or NMR)50 remains within the 

range of both recent and historical experience. 

With the other demographic assumptions recommended by the Panel, this immigration scenario 

represents a net migration rate of 4.4 per 1,000 

population at the beginning of the projections, 

gradually rises to 4.6 and then declines to 4.2 after 75 years. With this assumption, the average 

50 Strictly speaking, the specified measure (immigration divided by 

population) is not a true demographic “rate” because the population in the denominator is not exposed to the risk of occurrences 

counted in the numerator. Nonetheless, the NMR measures the 

rate of growth of the population attributable to immigration and 

remains a useful term. 
2007 Technical Panel on Assumptions and Methods 39

NMR over 2005–2080 is equal to the average over 

the 1980–2005 period or 4.4 per 1,000. 

n	 Our high-cost (lower immigration) scenario 

recommendation is to assume that net “other” 

immigration drops by 50,000 per year from the 

initial value of 500,000 to 200,000 and that net 

legal immigration is held constant during this period. Then, beginning from 1.1 million in 2012, 

legal immigration would increase by 0.25 percent 

per year and net other immigration at 0.5 percent 

per year. With these assumptions, the NMR51 declines from approximately 4.3 per 1,000 at the 

beginning of the scenario, then drops quickly 

to 3.0 after 25 years where it remains constant 

throughout the rest of the 75-year projection. 

The Panel bases the high-cost scenario on assumptions that unauthorized migration might be 

brought under control and that the growth rate 

of legal immigration would be slower than population growth (i.e., a declining NMR).

n The low-cost (higher immigration) scenario assumes that annual immigration will have reached 

2.8 million by 2080, a value consistent with an annual immigration increase of 1.0 percent. For the 

period from 2030 to 2080, immigration is assumed 

to increase by 0.5 percent per year, implying an increase of 2.1 percent per year for the period leading 

up to 2030. This scenario assumes a relatively rapid 

rate of increase in the short term, but a slow down 

for the long run. The NMR in this scenario peaks at 

5.7 per 1,000 population for 2030–2035, equal to 

the 1995–2000 peak. The average NMR is 5.1, or 

slightly higher than the last 20 years, but less than 

the average over the long period of relatively high 

immigration to the U.S. in the second half of the 

19th century and the early 20th. The Panel’s recommendations for the low-cost and high-cost scenarios 

are designed to give a greater spread between high 

and low in the short-term than might be otherwise 

obtained from basic extrapolation models.

Method Recommendation M-10: The Panel recommends that the Trustees make fundamental changes in their approach for deriving net migration assumptions and for implementing the assumptions. 

Method Recommendation M-11: The Trustees’ net 

migration assumptions should not be based on the 

51 The NMRs reported for Panel scenarios other than the intermediate cost scenario are approximations based on projections 

carried out by the Panel with fertility and mortality assumptions 

approximating the Panel’s recommendations, but varying only the 

immigration assumption. The precise values would differ slightly 

when implemented with other demographic assumptions.

provisions of current immigration law, which are 

consistent with widely varying levels of net migration, and which can reasonably be expected to 

change in the future; but rather on an analysis of 

historical trends augmented by on-going and future 

research on behavioral, demographic and economic 

determinants of migration. 

Method Recommendation M-12: The Trustees 

should disaggregate the demographic projection 

model by nativity (i.e., into native and foreign-born 

populations). Such a model would facilitate incorporation of significant known differentials into the 

projections, including: emigration (largely limited 

to former immigrants), fertility (higher for immigrants than natives), and labor force participation (higher for foreign-born males and lower for 

foreign-born females than for the corresponding 

native groups). Such a disaggregation can be implemented with the current cell-based projection 

model or micro-simulation models that might be 

adopted in the future.

Method Recommendation M-13: The age-sex distributions of net international migration components 

should accurately reflect the demographic logic of 

the model. Specifically, the age distribution of net 

“other” immigration should encompass both positive and negative values rather than simply reflecting the age distribution of the migrant population.

In making these recommendations, this Panel 

strongly supports the concept of the principal immigration recommendation of the 2003 Panel while 

making some adjustments in level and method to 

reflect more recent measures of immigration. If the 

methodological changes recommended by the Panel 

are adopted, further adjustments are recommended to 

the assumptions. Specifically, rates of increase in net 

immigration recommended would be applied to the 

assumed levels of legal immigration and to assumptions regarding net “other.” Emigration rates would be 

applied to the foreign-born population each year. With 

this type of assumption, net international migration 

might grow more slowly as emigration numbers could 

increase in line with growth of the foreign-born population, not the total population.52

52 For applications of emigration rates see Passel, Jeffrey S. and 

D’Vera Cohn “U.S. Population Projections, 2005–2050,” Pew 

Hispanic Center, Washington, D.C., February 2008; and Hollmann, Frederick W., Tammany J. Mulder, and Jeffrey E. Kallan, 

Methodology and Assumptions for the Population Projections of the 

United States: 1999 to 2100, U.S. Census Bureau, Washington, D.C., 

January, 2000. 
40 2007 Technical Panel on Assumptions and Methods

Overview

International migration has proved to be the 

most difficult component to forecast of the three 

major demographic factors (fertility, mortality and 

international migration). In addition to social and 

economic determinants, the level of international 

migration is directly affected by specific national 

policies in ways that the other demographic components are not. Further, although many of the 

factors underlying migration trends are reasonably 

well-known, they have proved difficult to apply in a 

forecasting framework.

International migration is a particularly critical 

factor in the Trustees’ projections. In the near-term 

future (the first 25 years of the projections), virtually all of the variability in the projected labor force 

ages (roughly ages 18–64) can be traced to the immigration assumption. The fertility assumptions affect only ages up through 25 (i.e., those cohorts not 

yet born); the mortality assumptions are extremely 

relevant for Social Security, but they mainly affect 

the older ages during this time. Indeed, virtually 

all of the projected growth in labor force ages for at 

least the next 50 years can be traced to immigrants 

and their U.S.-born offspring (Passel 2007).

Historical data on international migration show 

a steady upward trend in immigration levels since 

the 1930s. This steady growth shows up regardless of whether the backward look covers 25, 50, or 

75 years. Annual immigration has grown at an average rate of around 4 percent since the early 1950s 

with net annual immigration averaging more than 

1.3 million since 1995. This recent high level of immigration has been maintained in spite of a significant drop during 2002–2004 due to an economic 

slowdown and security concerns.53 The growth rate 

in the number of immigrants is about the same 

when measured from the early 1930s and a bit less 

(just over 2 percent annually) when measured from 

the late 1970s. Legal immigration and net immigration show quite similar growth patterns.

During this most recent 75-year period, the volume of immigration, including both legal and unauthorized, grew faster than the overall rate of population growth (about 1.1–1.4 percent). As a result, the 

NMR increased steadily. For 1930–1945, the NMR 

was only 0.1 net immigrants per 1,000 population; 

by 1990–2005, it had reached 4.9.

53 For estimates see Passel and Cohn, 2008, op. cit.; and Passel, Jeffrey S. and Roberto Suro, “Rise, Peak, and Decline: Trends in U.S. 

Immigration 1992–2004,” Pew Hispanic Center, Washington, D.C. 

September, 2005.

The rapid growth of annual immigration reflects 

a steady increase in both legal and unauthorized 

immigration. The legal immigration changes are 

traceable to several major modifications in immigration law since 1952. Unauthorized or illegal 

immigration emerged on a large-scale basis only in 

the 1970s and was followed by significant expansion beginning in the late 1990s. The current legal 

immigration regime can be traced to major legislative changes in 1965, 1976, 1980, 1986, and 1990 

followed by adjustments in 1996 and 2001.54 These 

changes greatly increased the level of legal immigration and opened up the U.S. economy to larger 

numbers of legal temporary migrants (“legal nonimmigrants” in immigration lingo). 

In the 1970s, large and increasing numbers of 

unauthorized migrants began to settle permanently in the U.S with their families. Notwithstanding laws against the knowing hire of illegal 

immigrants, the growth of this population accelerated in the 1990s until the unauthorized migrant 

population reached about 12 million by 2006.55

With globalization of the U.S. economy, ever larger 

numbers of foreigners entered the U.S. as tourists, 

business persons, and as temporary workers. Even 

though only a small fraction of the visitors end up 

settling in the U.S. as unauthorized migrants (i.e., 

“overstayers”), the numbers eventually reached 

significant levels—about 4–5.5 million by 2005.56

In addition, relatively inexpensive international 

travel and easy, inexpensive communication facilitated the settlement of both legal and unauthorized migrants in the U.S. Most of these trends have 

their roots within the last 25 to 35 years and point 

to the study of this period as a basis for projecting 

immigration into the future.

In contrast to these observed trends over the 

last 25, 50 or 75 years, the immigration assumptions adopted by the Trustees for projecting the 

OASDI trust fund display a stark discontinuity. 

The Trustees’ projections start from a much lower 

54 Fix, Michael and Jeffrey S. Passel, Immigration and Immigrants: 

Setting the Record Straight, The Urban Institute Press, Washington, D.C., 1994; and U.S. Immigration and Naturalization Service, 

Statistical Yearbook of the Immigration and Naturalization Service, 

1998, Washington, D.C., U.S. Government Printing Office, 2000, 

Appendix 1.

55 Passel, Jeffrey S., “Size and Characteristics of the Unauthorized 

Migrant Population in the U.S.: Estimates Based on the March 

2005 Current Population Survey,” Pew Hispanic Center, Washington, D.C., March, 2006.

56 Passel, Jeffrey S., “Modes of Entry for the Unauthorized Migrant 

Population,” Pew Hispanic Center Fact Sheet, Washington, D.C., 

May 22, 2006.
2007 Technical Panel on Assumptions and Methods 41

level of immigration than the base year, project a 

near-term decrease in net immigration from this 

low level, and then reach a constant (and much 

lower) level after 20 years. In the intermediate 

scenario, the Trustees start with net immigration 

of 1,075,000 in 2007 or roughly 15 percent below 

the current level of net immigration. Net immigration is then assumed to decrease by about 0.9 percent per year to reach 900,000 by 2026 and then 

remain at that level for the remaining years of the 

projection. The Trustees’ intermediate assumption also represents a marked break with NMR 

trends. The assumed pattern of net immigration 

implies a steady decrease from its current level to 

approximately 2.1 net migrants per 1,000 population. The NMR trend has been steadily upward 

since the 1930s. Further, the NMR was last as low 

as 2.1 in the late 1960s, before the U.S. opening 

of immigration to the world had taken effect.

The Trustees’ high-cost scenario assumes lower ultimate levels of net immigration not seen since the 

1970s; even the higher levels of immigration assumed 

in the Trustees’ low-cost scenario just barely reach 

the levels attained in the last 10 years. The Panel finds 

these assumptions totally at odds with historical experience and highly implausible. Since a higher immigration assumption results in a larger and younger population, as well as a larger labor force in the near term, 

the impact of such an erroneous (and low) assumption 

on the system’s finances is a major concern.

Although measurement of current and historic 

levels of immigration remains somewhat problematic (especially with regard to unauthorized 

migration, emigration, and year-to-year changes 

in the level of immigration), there have been a 

number of advances in recent years to support 

the Panel’s recommendations. The bulk of legal 

immigration has been well-measured for more 

than a century, but estimates of the magnitude 

of illegal migration were very limited prior to the 

last two decades. Knowledge has improved thanks 

to demographic analysis of 2000 Census data, information about annual flows of migrants during the 1990s, historical analysis of the series of 

censuses during the 20th century, and improved 

measures from surveys such as the Current Population Survey (1994 and later) and the American 

Community Survey (2000–2004, with full annual 

implementation beginning with 2005).

The Panel recommends increasing the levels of 

immigration in the entire range of the assumptions 

used for projecting the OASDI trust funds. The 

Panel arrived at this conclusion only after agreeing on two fundamental changes in the way such 

assumptions are derived. First, current immigration law does not provide a sound basis for deriving plausible net migration assumptions, especially 

over the long- term horizon required for trust fund 

projections. Second, the most plausible, yet simple, 

manner of specifying an ultimate net migration assumption is in terms of the net migration rate (relative to the size of the U.S. population), rather than 

as a fixed number of migrants per year.

Historical Background

Legal immigration to the U.S. has undergone 

large swings in the history of the country. With 

the exception of a few periods marked by wars or 

economic difficulties, immigration flows to the 

U.S. moved steadily upward and peaked just prior 

to World War I during 1905–1915. Levels then declined largely as a result of decreased flows resulting from World War I and the first quantitative restrictions placed on immigration in the early 1920s. 

Immigration reached historic lows during the Great 

Depression and World War II. Since the end of the 

War, there has been a steady increase in the level of 

legal immigration (Figure 14). Immigration began 

to increase after World War II, but quantitative and 

geographic restrictions limited the level of legal immigration during the post-war period. After 1965, 

legislative changes throughout the second half of 

the 20th century gradually expanded the limits 

and led to larger numbers of legal admissions. By 

2001–2006, the annual number of legal admissions 

averaged more than 1 million per year—a level last 

attained in 1910–1914.57

Components of Immigration

In the Trustees’ projections, three categories of 

immigrants are taken into account. Each of these 

groups has a different history, different amounts of 

data available for analysis, and different characteristics that affect the OASDI trust funds. Accordingly, the assumptions and methods must be treated 

separately. The formal assumptions are formulated 

for somewhat different groups (defined below), but 

these three groups form the basis for the assumptions: (1) legal immigrants; (2) “other” immigrants, 

57 This comparison excludes the legalizations associated with the 

Immigration Reform and Control Act of 1986 (IRCA) that artificially inflated the annual admissions for 1989–1991.
42 2007 Technical Panel on Assumptions and Methods

consisting of illegal immigrants (i.e., unauthorized 

and undocumented migrants) and certain legal 

non-immigrants (i.e., temporary legal residents); 

and (3) emigration of legal immigrants.

Official government counts of legal immigrants are 

compiled by the Department of Homeland Security’s 

(DHS) Office of Immigration Statistics (OIS).58 These 

data form the basis for measuring legal immigrants, 

but they cannot be used without modification. The 

current data count the legal immigrants at the point 

when they formally become “legal permanent residents” (LPR). However, many of the LPRs have been 

in the country for a number of years—some had various permanent legal statuses such as refugee, asylee, 

or parolee; others had long-term temporary statuses 

such as foreign student or guest worker; some had 

short-term temporary statuses such as visitor for business or for pleasure (i.e., tourist); and others entered 

clandestinely or had expired legal statuses. To use the 

LPR data for demographic estimation, it is necessary 

to avoid double counting by subtracting those who 

had been counted upon entry in other statuses. Further, for some estimates, it is necessary to make adjustments for the various dates of entry of individuals 

58 Before 2003, these data were compiled by the Immigration and 

Naturalization Service (INS) in the Department of Justice and various other agencies before the creation of INS.

attaining LPR status in a given year.59 Notwithstanding the imprecision of LPR data, this is by far the best 

measured component of total net immigration. As of 

2006, there are roughly 25 million legal permanent 

residents in the U.S. with slightly more than half being 

U.S. citizens by naturalization.60

Legal non-immigrants are authorized to enter the 

U.S. for specific periods of time and specific purposes. Short-term temporary admissions include 

tourists and visitors for business who make up the 

vast majority of the more than 30 million entries 

on legal temporary visas each year. Although some 

may overstay their visas and become unauthorized 

migrants, these admissions do not become part of 

the resident population. On the other hand, other 

temporary migrants are entitled to live in the U.S. for 

extended periods of time and many are permitted to 

work legally in the country and are, thus, obligated 

to pay Social Security taxes on their earnings. Some 

examples of the latter include foreign students, diplomats, so-called “high-tech guest workers” or H1-B 

59 Note that the data in Figure 14 for 1960–2005 have been adjusted to take into account status upon entry and the timing differences between entry and date of admission. See Passel, 2004, and 

Passel et al., 2004, for more detail on this problem and methods of 

adjustment.

60 Passel, Jeffrey S., “Growing Share of Immigrants Choosing 

Naturalization,” Pew Hispanic Center Report, Washington, D.C., 

March 28, 2007a. 

0.000

0.500

1.000

1.500

2.000

2.500

3.000

Unauthorized Immigration

Legal Immigration

Technical Panel High Cost

Technical Panel Low Cost

Techncial Panel Intermediate

Trustees High Cost

Trustees Low Cost

Trustees Intermediate

Historical Net Immigration

2.7

2.1

1.4

1.3

0.9

0.7

1820-25

1830-351840-45

1850-551860-65

1870-751880-851890-951900-051910-151920-251930-351940-451950-551960-651970-751980-851990-952000-052010-152020-252030-352040-452050-552060-652070-75

Figure 14: Net Migration, Legal Immigration, and Unauthorized Migration to the U.S. 1820-2006 , with Projections of Net 

Migration to 2080 according to Trustees Report and Technical Panel Recommendations: Average Annual Migrants 

Average annual migrants in millions

Figure 14: Net Migration, Legal Immigration, and Unauthorized Migration to the U.S. 1820-2006 , with 

Projections of Net Migration to 2080 according to Trustees Report and Technical Panel Recommendations: 

Average Annual Migrants
2007 Technical Panel on Assumptions and Methods 43

visas, au pairs, visiting scholars, and NAFTA workers. 

Thus, only those legal non-immigrants who reside in 

the U.S. long enough to pay Social Security taxes and 

could eventually collect benefits are relevant to our 

discussion. In recent years, there has been a steady 

increase in the number of such persons residing in the 

U.S. at a given moment, reaching perhaps 1–1.5 million.61 Over the last 30 years, the net annual change 

in the legal non-immigrant population has increased, 

but there are fluctuations in net arrivals that reflect 

changing economic and political conditions as well as 

changing limits on various categories. 

The flow of unauthorized migrants into the country has proved difficult to measure (on either a net 

or gross basis). However, over the last 25 years, measurement of this component has improved substantially so that it is now possible with some degree of 

accuracy and precision to assess the size of the unauthorized population resident in the U.S., as well as 

net unauthorized migration over multi-year periods. 

The best measures of net unauthorized migration are 

derived as the change in the size of the population.62

Moreover, some new methods permit assessment of 

year-to-year changes in the flows, mainly by providing estimates for specific dates of arrival of the unauthorized population at a given point in time.63

Although this population is by definition unauthorized, many of the migrants eventually manage 

to gain LPR or some other legal status. If such persons are added to the population upon their illegal 

entry, care must be taken not to double-count them 

as part of the immigration flow when they attain 

LPR status. The clearest example of this phenomenon comes from the late 1980s and early 1990s 

when approximately 2.6 million formerly undocumented immigrants attained LPR status as a result 

of the 1986 Immigration Reform and Control Act 

(IRCA). LPR admissions reached 1.5 million in fiscal 1990 and an all-time high of 1.8 million in fis61 Passel, 2006, op. cit.

62 For example, Passel, 2006, op. cit.; and Hoefer, Michael, Nancy 

Rytina, and Christopher Campbell, Estimates of the Unauthorized 

Immigrant Population Residing in the United States: January 2006, 

Department of Homeland Security, Office of Immigration Statistics, Washington, D.C., September, 2007.

63 Passel and Suro, 2005, op. cit.; and Warren, Robert, “Illegal Alien 

Resident Population: Estimates of the Undocumented Immigrant 

Population Residing in the United States (October 1996),” U.S. 

Immigration and Naturalization Service, Office of Policy and 

Planning. Washington, D.C., December, 2001; and Warren, Robert, 

“Estimates of the Unauthorized Immigrant Population Residing in 

the United States: 1990 to 2000,” U.S. Immigration and Naturalization Service, Office of Policy and Planning, Washington, D.C., 

January, 2003.

cal 1991, yet only about 600,000 persons in each 

year were conventional LPR admissions. The rest 

were formerly unauthorized migrants adjusting to 

LPR status. Most of them had been in the U.S. for 

more than 5 years and many came in the 1970s or 

even earlier. Trends in immigration can be greatly 

distorted if these LPRs are not assigned to their actual periods of entry. In Figure 14 and Figure 15 

and throughout this discussion, such persons are 

not included in data concerning legal immigration, 

but rather are counted as illegal immigrants at their 

time of entry into the country.

A final component of net international migration is the movement of legal immigrants out of the 

country or “legal emigration.”64 This component has 

proved somewhat elusive, but a variety of techniques 

have lead to estimates of out-flows in the range of 

200,000–300,000 per year.65 The latter two applications use rates of emigration applied to foreign-born 

populations to project levels of emigration consistent with the existing data. The Panel recommends 

that the Trustees adapt a version of these methods 

to their population projections. Such methods require the development of separate projections of the 

foreign-born population as the vast majority of legal 

emigration is by former immigrants.

Trends in Net International Migration 

Notwithstanding the lack of complete, precise 

data on all components of net migration, it is still 

possible to construct historical series of estimates 

of immigration that are consistent with the periodic observations of the foreign-born population 

provided by decennial census data and more recent surveys. The estimates presented here draw 

64 Note that with the current methods used by the Trustees and 

those recommended by the Panel, the components of unauthorized migration and legal temporary migration are measures as 

net figures or the difference between in-flows and out-flows so 

that it is not necessary to measure emigration of either group. In 

contrast, legal immigration, well-measured by the LPR data, only 

accounts for in-flows, so it is necessary to include the component 

of out-migration in assessing net legal immigration. 65 For examples of estimates and methods see: Hollmann et al. 

2000, op. cit.; Passel, 2005, op. cit.; Warren, Robert and Ellen P. 

Kraly, “The Elusive Exodus: Emigration from the United States,” 

Population Trends and Public Policy Occasional Paper No. 8, Population Reference Bureau: Washington, D.C., 1985; Ahmed, B. and 

G. Robinson, 1994, “Estimates of Emigration of the Foreign-Born 

Population: 1980-1990,” Technical Working Paper No. 9, Population Division, U.S. Census Bureau, Washington, DC. December, 

1994; and Mulder, Tamany J., Betsy Guzman, and Angela M. 

Brittingham, “Evaluating Components of International Migration: 

Foreign-Born Emigrants,” Technical Working Paper No. 62, Population Division, U.S. Census Bureau, Washington, DC. June, 2002.
44 2007 Technical Panel on Assumptions and Methods

on the work of the 2003 Panel66, but rely principally on historical projections by Passel67 for the 

1960–2005 period and the work of Edmonston and 

Passel68 covering the 1900–1990 period. Figure 14 

shows levels of legal immigration and net international migration for 5-year periods beginning in 

1820. Figure 15 shows the same data since 1920 

presented as migration rates or the NMR that relate the migration figures to the population size at 

the beginning of each 5-year period. 

For most of U.S. history (i.e., through the early 

1970s), legal immigration exceeded net migration 

because emigration or return migration was larger 

than unauthorized migration (which was negligible 

until the 1970s except for a small amount of unauthorized Mexican migration in the early years of 

the 20th century). By the 1980s, however, growth 

66 Wilmoth, John R., “Theoretical and Technical Aspects of Projecting Net Migration as a Function of Population Size,” Social Security 

Advisory Board Working Paper: cited in 2003 Technical Panel on 

Assumptions and Methods, Report to the Social Security Advisory 

Board, October 2003.

67 Passel, 2004, op. cit.; and Passel and Cohn, 2008.

68 Edmonston, Barry and Jeffrey S. Passel, “The Future Immigrant 

Population of the United States,” in Edmonston and Passel (eds.), 

Immigration and Ethnicity: The Integration of America’s Newest Arrivals. The Urban Institute Press: Washington, D.C., 1994.

of the unauthorized population surpassed legal 

emigration so that net international migration 

was larger than legal immigration. When viewed in 

5-year periods, both the absolute level of immigration (either in-migration only or net) and the net 

migration rate show a wide range of variation. The 

net migration rate does show less variability, however. For the 75-year period from 1840 through 

1915, most of the annualized NMR values were in 

the range of 3 to 8 net immigrants per 1,000 population, per year. For the period, the average was 5.7 

net migrants per 1,000 population, per year with 

the rate for legal immigration averaging 8.7. For 

the historical peak period of 19th and early 20th 

century immigration (1880–1915), the average 

NMR was about 9.2 for legal immigration and 6.0 

per 1,000 for net international migration.

Restrictive immigration legislation of 1917, 

1921, and 1924 followed by the Great Depression 

and World War II led to major drops in immigration 

levels and rates. Gradually expanding legal immigration and new large-scale unauthorized immigration toward the end of the 20th century raised the 

levels and rates from the unprecedented low levels 

of the 1930s. The numbers of immigrants reached 

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

Unauthorized Immigration

Legal Immigration

Technical Panel High Cost

Technical Panel Low Cost

Techncial Panel Intermediate

Trustees High Cost

Trustees Low Cost

Trustees Intermediate

Historical Net Immigration

4.6

4.2

3.0

2.5

2.1

1.9

1920-25

1925-30

1930-35

1935-401940-45

1945-501950-551955-601960-65

1965-701970-751975-801980-851985-901990-951995-00

2000-052005-102010-152015-202020-252025-302030-352035-402040-452045-502050-552055-602060-652065-702070-752075-80

Figure 15: Net Migration, Legal Immigration, and Unauthorized Migration to the U.S. 1920-2006, with Projections of Net 

Migration to 2080 according to Trustees Report and Technical Panel Recommendations: Annual Migrants per 1,000 

initial Population

Annual migrants per 1000 initial population

Figure 15: Net Migration, Legal Immigration, and Unauthorized Migration to the U.S. 1920-2006, with 

Projections of Net Migration to 2080 according to Trustees Report and Technical Panel Recommendations: 

Annual Migrants per 1,000 initial Population
2007 Technical Panel on Assumptions and Methods 45

historic highs by the 1980s—net international migration in every period from 1980–85 onward exceeded the previous high of 700,000 net migrants 

per year last reached in 1910–15. However, in relation to population size, immigration—as measured 

by NMR—was well below the previous highs as it 

averaged about 5.4 immigrants per 1,000 population for this most recent 25-year period and 8.7 

for 1890–1915; and net migration averages about 

4.5 per 1,000 for 1980–2005 versus 5.7 for the earlier period.

Long-term averages of the NMR are below the current values. For the full 185-year history from 1820 

through 2005, the average NMR was 3.2. For the 

20th century, the average was just under 2.9. And, 

for the most recent 75-year period of 1930–2005, 

the NMR averages about 2.7 per 1,000.

Measuring the current level of annual legal immigration requires some assumptions about new 

arrivals and when persons adjusting to LPR status 

actually arrived in the U.S. After including refugee 

arrivals and discounting adjustments of previous 

unauthorized migrants, legal immigration levels for 

1990–2005 averaged about 860,000 per year. Note 

that LPR admissions exceeded 1.1 million for several years following 2001 as the Immigration and 

Naturalization Service (INS) and then DHS cleared 

some backlogs. Net unauthorized migration averaged over 600,000 per year during this period as 

the total number of unauthorized migrants living 

in the U.S. reached close to 12 million by the end of 

2005.69 Using Census Bureau emigration estimates 

and the underlying rates applied to the estimated 

foreign-born population, we estimate emigration at about 275,000 per year.70 Finally, the net 

in-flow of legal temporary migrants averaged about 

75,000–100,000 over this 15-year period. Combining these components yields average annual net 

immigration for this period at about 1.3–1.4 million with substantially higher levels in recent years 

and the several years around 2000. 

Beginning with the 2000 Census, data enhancements have led to changes in the method of generating official measures of net immigration for the 

Census Bureau’s population estimates. The new 

methods estimate net international migration from 

consecutive years of the American Community Survey (ACS) with adjustments for mortality.71 With 

69 Passel, 2006, op. cit.

70 Passel, 2004, op. cit.

71 U.S. Census Bureau, National Population Estimates, July 1, 2006, 

Population Division, Washington, D.C., 2007. 

this method, annual estimates of net migration 

averaged over 1.2 million for 2000–2006, reaching 

almost 1.4 million by the end of the period.72 Based 

on our own analyses and comparisons with the Census Bureau’s estimates, the Trustees’ assumption of 

net migration for 2006 of 1,075,000 seems considerably low, as do the projected values (which assume 

declines from this low level) when post-2000 trends 

show increasing levels of immigration.73

Current Trustees’ Assumptions

The Trustees Report uses logic similar to the above 

analysis (but with some outdated data) and considers three sets of flows: (1) legal immigration; (2) legal emigration; and (3) net “other” migration.74

As summarized in Table 5, the assumptions used 

since 1981 to define the level of net international migration have been straightforward. Prior to 

1988, the Trustees Reports did not include an allowance for illegal migration; there was little data 

on which to base an estimate and this assumption 

was consistent with population estimates and projections done by the Census Bureau. Since 1995, 

the Trustees’ intermediate scenario has included 

an ultimate annual inflow of 900,000 persons per 

year. For the most recent years, this assumption allowed for 800,000 legal immigrants per year, minus 

200,000 legal emigrants, plus 300,000 net other 

immigrants. Before 2003, the Trustees assumed 

that immigration levels would converge to these 

levels quickly, usually within three years. In the 

2007 Report, immigration converges more slowly 

than in the pre-2003 reports, falling from 1.2 million in 2005 to 900,000 in 2027, but with almost 

half of the drop occurring in the first year.

The ultimate assumption of 900,000 net migrants 

per year was derived, in part, based on the provisions 

of current immigration law. By the Immigration Act 

of 1990, the “worldwide cap” for legal admissions75

has been fixed at 416,000–675,000 persons per year 

since 1995. Adding an allowance of 80,000 for refugee and asylee admissions (which are not included 

72 New analyses of birth and death statistics for Hispanics, in 

conjunction with ACS and Census data suggest that even the 

Census Bureau’s measures understate the level of net immigration 

somewhat. 

73 U.S. Census Bureau, 2007, op. cit.

74 “Other-than-legal” includes both illegal aliens and aliens admitted 

lawfully under temporary work visas. It does not include tourists.

75 This cap covers family-sponsored preferences, employment preferences, and diversity immigrants. Immediate relatives are part of 

the calculation, but the cap is “pierceable” permitting admission of 

much larger numbers.
46 2007 Technical Panel on Assumptions and Methods

in the worldwide cap)76 plus approximately 10 percent in various other categories yields the assumption of 800,000 legal immigrants per year. During 

1992-2000, the average number of legal admissions 

was around 780,000, but levels were much higher for 

2001–2006 (averaging about 1.03 million in across 

the period). The Trustees’ assumption of 200,000 

emigrants annually is broadly consistent with current estimates but somewhat low compared with recent Census Bureau research. The Trustees’ ultimate 

assumption of 300,000 net other immigrants lies 

well below estimates of levels in recent years; even 

the higher assumption of 400,000 for 2008–2020 is 

far lower than figures implied by recent data.

Thus, the only component of the Trustees’ net 

migration assumption that can be justified by reference to current law is the largest one, consisting of all legal admissions other than refugees and 

asylees. Moreover, the “worldwide cap” of recent 

years is not a strict limit, but rather a target. Most 

significantly, the cap includes an annual allowance 

for immediate relatives of U.S. citizens, even though 

in reality there is no numerical restriction on this 

form of entry. Indeed, this category was the largest single category of legal immigration every year 

since 1986.77 The rapid growth in admissions of immediate relatives is a major part of the wide vari76 The cap allows for 70,000 refugees and 10,000 asylees; the asylee 

cap was lifted in 2005 to cut down on backlogs.

77 Table 5 in U.S. Department of Homeland Security, Office of 

Immigration Statistics, Yearbook of Immigration Statistics: 2006, 

Washington, D.C., January, 2007. 

ability in legal immigration levels during periods 

with a constant “numerical limit” (i.e., the number 

of legally permissible admissions within categories 

that are truly restricted by an annual quota). Since 

1995, this legally designated “numerical limit” has 

been 421,000,78 or less than half of the Trustees’ 

ultimate net migration assumption of 900,000, 

yet LPR admissions have continually exceeded the 

Trustees’ intermediate assumption since then.

There are also many indications that immigration 

levels were considerably higher in the latter half of 

the 1990s and in 2000–2001 than the average for 

the period or even the most recent year. All three 

components of international migration appear to 

have peaked at that time.79 The reasons for the increases and subsequent decreases differ for each of 

the components. Moreover, the 25–35 percent declines suffered by each in 2002–03 may be linked 

to idiosyncratic factors and thus considered transitory. The very strong economy of 1998–2000 drew 

large numbers of unauthorized migrants into the 

country and spurred other potential migrants to 

apply for green cards. The recession which began 

in 2000–01 was exacerbated by economic shocks 

associated with the aftermath of 9/11. These factors led to increases in the unemployment rates 

78 In fact, the value of 421,000 represents a lower bound for the 

numerical limit in a given year and can be supplemented by unused 

allocations from preceding years for immediate relatives and other 

(much smaller) categories of entry that have no numerical limitation.

79 Passel and Suro, 2005, op. cit.

Ultimate assumption for net migration

(1000s of persons per year; average across annual reports)

Years of 

Trustees 

Reports

Total Legal Immigration Other Immigration Ultimate

Low-Cost IntermediateHigh-cost Low-Cost IntermediateHigh-cost Low-Cost IntermediateHigh-cost

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 Year 1-8

1995-1999 1,150 900 750 710 610 560 440 290 190 Year 2-8

2000-2002 1,210 900 655 760 600 455 450 300 200 Year 2-3

2003-2007 1,300 900 673 850 600 473 450 300 200 Year 21

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.

Table 5: Assumed Ultimate Levels of Net Migration for 3 Scenarios, by Entry Status (Legal vs. Other), 

Trustees Reports, 1981-2007
2007 Technical Panel on Assumptions and Methods 47

and decreased demand for labor. Thus, it is not 

at all surprising that levels of illegal immigrant 

in-flows dropped substantially in 2002–03.80 Data 

from 2005–2007 show indications of a rebound in 

net unauthorized migration as unemployment has 

dropped, but the new arrivals do not appear to have 

reached the peaks attained in 1998–2001.

LPR admissions dropped by more than 30 percent between fiscal years 2002 and 2003; the survey-based estimates showed a similar decline.81 Unlike the case of unauthorized migration, the decline 

in LPR admissions appears to have been largely due 

to bureaucratic issues rather than a decrease in the 

desire on the part of potential migrants to move to 

the U.S. In reaction to the 9/11 attacks, the Department of State suspended all admissions of refugees. 

More stringent security checks and clearances were 

done for almost all LPR admissions. These enhanced 

security measures meant that each case took longer 

to process and the added delays led to a slowdown 

in admission and ultimately to the decreased numbers. The subsequent increases in 2004–2006 and 

the remaining large backlogs for admission point to 

a continued high level of demand to immigrate. 

All of these factors contributed to a decrease in 

levels of legal temporary admissions after 2001. The 

economic slowdown led to decreased demand on 

the part of employers for temporary labor. Security 

delays meant that some legal temporary applicants 

were not admitted; some (especially students) missed 

deadlines and so did not come; and, finally, others decided not to come. In addition, a temporary increase 

from 65,000 to 195,000 in the number of H1-B visas 

available annually that was passed in the late 1990s 

expired at this time. With the economic difficulties 

cause by the recession, employers did not need the 

additional workers and so the increased cap expired. 

More recent numbers on temporary migration appear 

to be increasing as the post-9/11 effects wear off.

Thus, even assuming that current immigration laws 

do not change, the levels assumed by the Trustees 

are far below current measures. Further, it does not 

follow necessarily that future net migration trends 

will be flat or decreasing as assumed by the Trustees. Furthermore, this Panel strongly endorses the 

recommendation made by the 2003 Panel that there 

is no need to freeze assumptions about immigration 

law. Social Security law must be held constant when 

projecting the financial status of the trust funds, 

80 Ibid.

81 Ibid.

but there is no such requirement for immigration 

law. This Panel also believes that the Trustees should 

present policy makers with the most likely picture of 

the future, and that it is unrealistic to assume that 

there will be no changes in immigration law over the 

next 75 years and beyond. Therefore, the Panel recommends assuming that legislative limits regarding 

legal immigration can be adjusted to fit economic and 

social circumstances; likewise, enforcement policies 

may be changed as needed.

Basis for Panel Recommendations

Rather than an approach based on current law, 

the Panel recommends that the Trustees derive 

their net migration assumption from an analysis 

of historical trends. Ideally, the analysis would 

employ a model-based framework and underlying 

theory for projecting immigration. Although there 

has been a considerable amount of research in this 

area in recent years, there is still no widely-accepted theory to address the problem. The Social 

Security Administration sponsored some work to 

survey existing national projections and available 

methods for projecting immigration and to make 

recommendations for future work.82 These authors 

argue for a complicated “driver-based” model to 

project immigration; the drivers include demographic factors, economic factors, other non-policy drivers (e.g., relative wealth, trade, technology, 

politics), policy drivers, as well as country-specific 

effects. The Panel feels that implementation of this 

approach would be premature, requiring a considerable degree of effort with little immediate pay-off 

in light of the current theoretical basis. However, 

the work does point to a number of factors that 

could affect future levels of immigration. 

Howe and Jackson identify six broad theoretical 

frameworks that could be used to develop projection models:

n Policy framework—national immigration 

policy determines levels of immigration;

n Neoclassical framework—in a global labor 

market, labor will migrate toward higher wages 

if the wage differential is larger than the moving 

cost;

82 Howe, Neil and Richard Jackson, Projecting Immigration: A 

Survey of the Current State of Theory and Practice, Center for Strategic and International Studies: Washington, DC. April, 2005; and 

Jackson, Richard, “Long-Term Immigration Projection Methods: 

Toward a Driver-based Model,” Presentation at ISIM Workshop, 

Center for Strategic and International Studies, September 26, 

2006. 
48 2007 Technical Panel on Assumptions and Methods

n World systems framework—immigration occurs when countries are incorporated in a capitalist world market; attitudinal shifts, remittances, 

and community effects lead to “cumulative causation” and increasing levels of immigration;

n New economics framework—extended family economic units participate in a series of decisions and moves to maximize income, diversify 

income sources, and insure against risk;

n Social network framework—networks of kin 

and other social contacts in both sending and receiving areas reduces costs and risks of migration, 

facilitating movement and settlement; momentum develops over time to increase migration;

n Dual labor market framework—segmentation 

of labor market in receiving countries sets up 

niches for immigrants and encourages migration.

Only the policy framework points to potential decreases in net immigration. Over the long-run the 

neoclassical framework could suggest lower levels 

of immigration, but there is no indication that an 

equilibrium state has been reached or that the equilibrium would be lower than current levels. Within 

broad limits, virtually all of the others point in the 

direction of a continuing demand for immigrants 

in large numbers in the U.S. economy.

The basic demography of the projections points to 

a continuing strong demand for immigrants. Comparing a basic set of projections with a hypothetical set assuming no future immigration, Passel and 

Cohn83 find that virtually all future growth in the 

working-age population is due to new immigrants 

and their offspring. With no future immigration, 

the 18–64 year old population would decline from 

186 million in 2005 to 179 million in 2050; this age 

group would never exceed 191 million and would 

continue its decline after 2050. With assumptions 

similar to the Panel’s recommendations, the labor 

force ages would grow by 37 percent to 255 million 

or by an average of 0.7 percent per year. While this 

rate of growth is not dramatic or excessive, even 

maintaining this level of growth would require increasing numbers of immigrants. 

Lowell et al.84 explicitly examine the impact of 

immigrants on past and future labor force trends. 

Although their projection horizon is far shorter 

than the Trustees’, they conclude that there will 

83 Passel and Cohn, 2008, op. cit.

84 Lowell, B. Lindsay, Julia Gellatt, and Jeanne Batalova, “Immigrants and Labor Force Trends: The Future, Past, and Present,” Task 

Force Insight No. 17, Migration Policy Institute: Washington, DC. 

July, 2006.

be a demand for growing numbers of immigrants 

to maintain labor force growth across a range 

of needs. To the extent there will be a need for 

“low-skilled” workers (i.e., in jobs with minimal 

requirements for formal education, such as service 

workers and health care and home care aids for the 

aging population), immigrants will be essential 

since the number of native high school dropouts in 

the labor force is projected to decrease. At the other 

end of the educational spectrum, the U.S. economy 

will continue to need growing numbers of highly 

educated workers; immigrants are projected to provide a growing share of the future workforce with 

at least a bachelor’s degree.

With the strong immigration trends of the past 

25 years and indications of continued need for immigrants in the U.S. economy, the Panel concluded 

that there is no strong reason to anticipate a sharp 

break with past trends in the near future. The annual net inflow since 1950 has grown around 4 percent per year on average with recent periods of even 

higher growth. The Trustees’ assumptions imply a 

sharp disruption in a trend that has endured for 

more than five decades. We consider such a large 

historical discontinuity to be highly unlikely. In the 

absence of strong arguments about why the pool 

of potential immigrants is going to shrink in the 

foreseeable future, or about how the government 

will successfully cap the inflow at a prescribed level, 

we find it more reasonable to anticipate that future 

migration trends will resemble past ones. Although 

this resemblance could take many forms, the Panel 

suggests that the most reasonable approach overall is to link assumed migratory flows over the long 

run to the size of the U.S. population.

The Trustees choice to begin the projection with 

a level of immigration that is considerably below 

the current measured level is particularly troubling. 

While the previous Panel could excuse such an error 

by noting the potential uncertainty surrounding 

immigration levels in the immediate post-census 

environment, that rationale is no longer tenable. 

There are now a number of consistent contemporaneous data sources together with material from 

Census 2000, as well as historical demographic 

analyses of trends in census counts by nativity 

(Passel 2004), that all point to current levels of net 

immigration that are considerably higher than the 

Trustees’ assumed starting point. Further, bringing 

the starting value in line with current trend information will enhance the evidence and arguments 
2007 Technical Panel on Assumptions and Methods 49

for higher immigration levels in the projections.

The Panel recommends that migration assumptions be based on historical analysis of the net migration rate (NMR). The previous panel recommended 

setting the ultimate migration assumption at the 

long-run historical average of NMR for the entire period for which we have data, i.e., 1820-2006, or an 

NMR at 3.2 per 1,000. This figure obviously averages 

periods of very high immigration with very low immigration. The current panel recommends a more 

limited historical analysis—the period from 1980 to 

the present. This period coincides with a modernization of the country’s immigration regime that puts 

it in the context of a global economic system. During this period, we have seen the establishment of 

large-scale settlement in the U.S. of unauthorized 

migrants, integration of the U.S. economy within 

a globalized system, and the development of inexpensive and quick means of communication across 

international boundaries. All of these factors serve 

to facilitate migration to the U.S. (if not settlement 

in the country). During the same period, a number 

of other potential migration-related developments 

have occurred including: the emergence of the U.S. as 

the sole super-power (in addition to its place as the 

preeminent economy); the development of the internet and e-mail; relatively inexpensive travel; and European countries becoming migrant-receiving rather 

than migrant-sending countries. The uniqueness of 

the current era suggests that earlier periods might be 

sufficiently different in terms of migration to restrict 

the historical analysis to the most recent 25 years.85

We have formulated our recommendation in 

terms that relate the trend in immigration to population trends. We have also provided alternative 

formulations in terms of the NMR that would yield 

approximately the same results, but the exact numerical values of future immigration would depend 

on fertility and mortality assumptions. With population growth at approximately 1 percent per year, 

setting the annual growth in net international migration at 1 percent should maintain the existing 

NMR. In practice, assuming that net international 

migration grows at 1 percent from the starting 

NMR value of 4.4 per 1,000 in combination with 

the Panel’s recommended fertility and mortality 

assumptions results in a very gradual increase in 

the NMR to a bit under 4.6 by 2025 followed by 

85 The passage of the 1965 immigration amendments also marks 

another turning point for U.S. immigration. While the panel 

prefers the post-1980 period as a basis for historical analysis, the 

post-1965 period represents a reasonable alternative.

a gradual decline to 4.4 in 2050 and 4.2 in 2080. 

The average NMR over the 2005–2080 period is 

4.4 per 1,000 population—equal to the average for 

1980–2005. The Panel felt that this assumption 

would be easier to implement than one stated in 

terms of NMR; however, we would not object to an 

intermediate assumption stated in terms of a constant NMR of 4.4. The Panel recommends applying 

the same growth factors to the three main types of 

immigration (legal immigration, legal emigration, 

and other immigration), but continuing to investigate alternative formulations.

The Panel recognizes that immigration levels are 

certain to fluctuate in the future. However, shortterm annual movements away from underlying 

trends are likely to be responses to economic fluctuations or short-term political considerations. Since 

the economic factors in the projections are assumed 

to move smoothly as trends of central tendencies, 

the Panel feels that similar assumptions would be 

appropriate for immigration as well. The Panel 

strongly encourages the Trustees to move away 

from an assumption of constant levels of immigration in the intermediate-cost scenario.

For the alternative scenarios, the Panel examined 

fluctuations in migration over the last 25–50 years. 

For the low-cost scenario (which implies higher net 

immigration), the Panel formulated a scenario in 

which the average NMR would almost reach the levels attained in the most recent period of very high 

net immigration—the 1990s when the average NMR 

was 5.2 per 1,000. The low-cost scenario starts with 

an assumption that net immigration will have grown 

by 1.0 percent per year for the entire 75-year projection horizon to reach 2.8 million in 2080; we further 

assumed that growth over the last 50 years would be 

only half as fast as the average. These assumptions 

imply an increase in the NMR from 4.4 for 2007 to 

5.7 for 2030–2035. This peak duplicates the NMR 

for 1995–2000, the highest value reached in the last 

75years. Following the peak, the NMR would decrease 

to an ultimate value of 4.6 for 2075–2080 and beyond. With these assumptions, the average NMR for 

2005–2080 would be 5.1 and the population in 2080 

would be about 80 million larger than in the intermediate scenario. An alternative, acceptable formulation 

would set the NMR at 5.1 for the entire period.

For the high-cost or low immigration scenario, the 

Panel devised a potentially plausible set of circumstances that could lead to lower levels of immigration and a 

lower NMR. The scenario assumes that unauthorized 
50 2007 Technical Panel on Assumptions and Methods

migration is gradually reduced so that net “other” immigration drops from the initial value of 500,000 for 

2007 to 200,000 in steps of 50,000 per year. This lower 

level is consistent with a much smaller net in-flow of 

unauthorized migrants but maintains a continuation 

of temporary legal migration. At the same time, some 

controls are placed on legal immigration so that the 

numbers are held constant for this initial period. Then, 

beginning in 2012 when net immigration will have declined to 1.1 million, immigration would increase, but 

much more slowly than in the intermediate scenario—

by 0.25 percent per year for legal immigration and 0.5 

percent for other. With these assumptions, the NMR 

declines gradually from the initial value of 4.4 to about 

3.0 after 25 years, and then remains roughly constant 

at that value for the rest of the 75-year projection horizon. This NMR is slightly lower than the 3.2 average 

for the entire U.S. immigration experience from 1820 

to 2005 and virtually identical to the average for the 

post-World War II period.

Figure 14 and Figure 15 illustrate the future 

trends of net international migration implied by the 

Panel’s recommendations, in terms of both numbers 

and rates.86 For each scenario, levels of net migration 

are substantially higher than what is implied by the 

Trustees’ assumptions (except for the initial 15 years 

in the Trustees’ high-immigration, low-cost scenario). The Trustees’ assumptions lead to 69 million 

net immigrants over 2007–2081 in their intermediate-cost scenario, 51 million in the high-cost and 

99 million in the low-cast. The Panel’s recommendations lead to substantially larger figures—135 million in the intermediate scenario, 122 million and 

150 million in the other scenarios.

Discussion

Over the next few decades, there are a number of 

trends that could affect the volume of immigration 

to the U.S. The 2003 Panel suggested that some of 

these could lead to stagnating growth or diminished 

levels of net international migration in future years 

and decades. However, in virtually every case, there 

are offsetting factors or theoretical arguments that 

are more likely to lead to increases. For example:

n “The recent economic slowdown could lower 

the demand for immigrant labor.” The economic 

86 The NMR for the Panel’s intermediate scenario uses a projection based on the Panel’s fertility and mortality assumptions. The 

NMR values for the other scenarios are approximations based on 

the Panel’s own calculations of projection scenarios. Full implementation with the Trustees’ projection model could yield slightly 

different results.

slowdown of 2002–2003 did lead to reduced immigration flows, but they have since increased to 

levels higher than 2001. Any impact of economic 

slowdowns is likely to be transitory as the overall 

demographic trends have a built-in bias toward 

continued high (and possibly increasing) levels 

of immigration. Further, neither the Trustees’ 

nor the Panel’s economic assumptions call for extended periods of slower economic growth.

n “Heightened security concerns may result 

in more limited refugee admissions and stricter 

border enforcement.” Again, this situation has 

occurred since 2001, but immigration levels 

have bounced back. If enforcement does result in 

lower levels of unauthorized migration, potential 

employers of immigrants are likely to demand alternative channels to access the workers needed 

in businesses. The result would likely be the same 

level of immigration but within different legal 

categories.

n “In the 1990s, many immigrants who were legalized under the Immigration Reform and Control Act (IRCA) legislation of 1986 brought their 

families to the U.S., but that source of inflow has 

nearly disappeared.” This statement is also true, 

but there are no indications of coming decreases 

and continuing immigration contains the seeds 

for future immigration through family connections to home countries. Indeed, several of the 

analytic frameworks (e.g., Social Networks and 

New Economics) posit family networks as a basis 

for increasing immigration flows.

n “Fertility rates began to fall in Mexico around 

1970, and this trend is expected to continue. The 

number of Mexicans at ages 15-19 is projected to 

start declining soon after 2010, which may reduce 

the supply of potential immigrants to the U.S.87

This shift could have important implications for 

legal immigration, since Mexico accounts for 

around 20 percent of such flows in recent years, 

but it is especially relevant for illegal immigration, which historically has come primarily from 

Mexico and Central America.” While the Mexican 

demographic factors are likely to lead to reductions in migration from Mexico, most projections 

of the Mexican population88 still project siz87 Centro Latinoamericano y Caribeño de Demografia (CELADE), 

“Estimaciones y Proyecciones de la Población, 1950–2050,” 2003.

88 Consejo Nacional de Población (CONAPO), “Proyecciones de la 

Población de México 2005-2050,” 2006; and U.S. Census Bureau, 

International Data Base, Population Projections for Mexico, Population Division: Washington, D.C., 2005. 
2007 Technical Panel on Assumptions and Methods 51

able migration through at least 2050, although 

perhaps at diminished levels. Further, there are 

many other potential sources of migration. [See 

also next comment.]

n “As Europe and Japan age rapidly, they may 

demand more foreign labor and compete with 

the U.S. for potential immigrants.” There is no 

projected shortage of potential migrants in the 

world. The United Nations projects that the less 

developed world will add about 1.8 billion persons 

of working age (defined as 15–64 by the UN) between 2005 and 2050 alone (a value which already 

assumes out-migration of more than 100 million 

people). There will be competition for potential 

migrants, especially those with advanced levels 

of education, but the political system and dynamic economy of the U.S. are likely to be continuing draws for new immigrants. It is also true 

that much of the growth will not be in traditional 

sending countries associated with current migration. All of these trends may simply mean that 

the U.S. will have to put into place more attractive policies and working conditions to attract the 

needed migrants, but they will be available.

n “The failure of Congress to pass immigration reform in 2007 will lead to a focus on security by the administration and a number of 

state and local governments, which will in turn 

lead to reduced migration. These actions will 

make life more difficult for unauthorized migrants by stopping more of them at the border, 

making it more difficult for them to get jobs, 

and ultimately detaining and deporting large 

numbers of them. As a result, fewer unauthorized migrants may come to the U.S. and more 

of them may depart (either by choice of forcibly). Then, net immigration in the short-term 

would fall well below the projected values recommended by the Panel.” While this scenario 

is certainly plausible, if there is a continuing 

strong demand for immigrant labor, Congress 

may be pressured into passing some sort of 

comprehensive reform or a guest worker program. In the Panel’s opinion, the economic pressures for higher levels of immigration are more 

likely to continue. However, if the restrictions 

and security measures prevail, revisions in the 

projection scenarios will be needed.

The Panel does not feel that any of these countervailing factors is strong enough to lead to recommending a different trend assumption for the 

U.S. On the other hand, there are a number of factors that point toward continued high levels or a 

sustained growth of net migration to the U.S. For 

example:

n The demand for immigrant labor seems likely 

to grow with the U.S. population and economy 

simply as a matter of scale. This demand will be 

reinforced by population aging that will place 

increased demands on health and service sectors, both of which are heavy users of immigrant 

workers.

n The increasing share of the U.S population 

that is foreign-born continues to enlarge the 

network of individuals who can assist new immigrants. Therefore, the mere momentum of past 

migration may help to sustain and reinforce future inflows. This phenomenon can be especially 

important in opening up new sources of immigrants over the 75-year horizon of the projections.

n Large untapped pools of potential immigrants 

exist in many parts of the world, especially Asia. 

With affordable transoceanic transport, immigration (authorized or not) from distant countries 

could increase, especially if foreign governments 

(e.g., China) relax their limits on emigration.

n Attempts to set legal caps on immigration 

seem likely to fail. In the past, such legislation 

has often produced unintended consequences, 

many involving sharp increases in net immigration levels (Briggs 1996). For example, more 

tightly guarded borders during the 1990s apparently led to reduced emigration, as foreign-born 

residents (especially unauthorized ones) anticipated greater difficulty returning to the U.S.89

n The projected changes in the U.S. age structure can generate even more demand for labor. 

There are several aspects of this. As noted above, 

an aging population requires more service and 

healthcare workers. Immigrants can provide this 

labor while at the same time providing needed 

workers in IT and other sectors that can enhance 

productivity, in part because immigrant workers 

tend to be younger and more productive.90

89 Massey, Douglas S., Jorge Durand, and Nolan J. Malone, Beyond 

Smoke and Mirrors: Mexican Immigration in an Era of Economic 

Integration, Russell Sage: New York, 2002; and Cornelius, Wayne A. 

and Jessa M. Lewis (eds.), Impacts of Border Enforcement on Mexican 

Migration: The View from Sending Communities, Center for Comparative Immigration Studies: UCSD, La Jolla, CA, 2007. 

90 Lowell et al., 2006, op. cit.
52 2007 Technical Panel on Assumptions and Methods

n While incomes and wages may rise in less developed countries, the wage differential with the 

U.S. is likely to persist. Thus, there will continue 

to be pressures toward migration. In the only 

framework that would predict decreases in migration, the “neoclassical”, wage differentials are 

the principal driver for migration. Yet, one of the 

difficulties encountered by neoclassical analyses 

is trying to explain why current levels of immigration are not higher in the face of very substantial wage differences. This conundrum is perhaps 

best summed up by Hanson, who says, “...given 

the large magnitude of U.S.-Mexico wage differences and the small apparent cost of crossing the 

border illegally, the volume of migration flows 

from Mexico to the United States is surprisingly 

low” (emphasis added).91

n The U.S. will be forced into competition for 

immigrants with current receiving countries as 

well as a number of new potential destinations. 

Nonetheless, the U.S. will remain attractive, both 

politically and economically.

Related Topics

Given any level of migration, OCACT must make 

assumptions about the age-sex pattern of migration. Currently, this distribution differs for the 

three broad categories of migrants. The projection 

model also includes assumptions about how immigrants interact with the labor force and the Social 

Security system. Currently, legal immigrants are 

assumed to have the same demographic and economic characteristics as the population as a whole, 

as are half of other immigrants. One-quarter of 

other immigrants are assumed to pay Social Security taxes but to receive no benefits, and one-quarter are assumed neither to pay taxes nor to receive 

benefits.

The Panel feels that overall, these assumptions 

are inadequate. Some changes, such as adjustments 

in the age-sex distributions of the components of 

immigration, can easily be made within the current projection framework. Others involving the 

differential demographic behavior of immigrants 

and natives and differences in interaction with the 

labor force require more fundamental changes in 

the projection models.

91 Hanson, Gordon H, “Illegal Immigration from Mexico to the 

United States,” National Bureau of Economic Research Working 

Paper #12141, March, 2006, p. 42

Age-Sex Distribution of Net Migration

Conceptually, the major types of immigration 

measured in the Trustees’ projection model are demographically different. Legal immigration is measured as an in-flow only. The corresponding outflow is measured in the emigration component. The 

demographic model treats unauthorized migration 

and legal temporary migration as net flows. 

Legal immigration and emigration have somewhat 

different age distributions in that the emigrants 

tend to be older than the immigrants (see Figure 16). 

Information on age and sex for the legal permanent resident (LPR) component (in-migration) can 

be readily obtained from OIS data on admissions. 

(Some minor adjustments may be required for refugees and other specialized immigrant arrivals.) The 

distribution of emigrants is available from a number 

of research studies.92 However, since the emigrants 

are drawn from the resident immigrant population, 

their distribution is a function of this population 

and rates of emigration. Since the composition of 

the resident legal immigrant population can change 

over time, this relationship argues for developing 

the age-sex distribution of emigrants from a set of 

emigration rates. If the projection model does not 

support this application (as is currently the case), a 

second-best approach is to use the age-sex distribution of emigrants available from current studies. Because emigration may exceed immigration in some 

age groups (especially older ones), it is important 

that the age-sex distribution of net legal immigration not be solely based on the age-sex distribution 

of arriving immigrants only.

Examination of the age distribution of temporary 

legal migrants and unauthorized migrants shows 

that they tend to stay relatively constant rather than 

aging. This pattern is perhaps clearest if we consider 

the population of foreign students living in the U.S. 

While the total numbers may move up or down, we 

would expect the age distribution to be relatively constant over time because the group is made up largely 

of college students. Put another way, we expect people to move out of this population as they graduate 

from college or leave the country, but there will be 

more new students than departures if the population is growing. To achieve the relatively constant age 

distribution, it is necessary that the age distribution 

of net legal temporary migration be negative at some 

ages indicating that more people leave the group 

92 For example, Hollmann et al. 2000, op. cit.; and Mulder et al. 

2002, op. cit.
2007 Technical Panel on Assumptions and Methods 53

than enter. To a very great degree, net unauthorized 

migration behaves the same way. Thus, it is essential 

that the Trustees use different assumptions for the 

age distribution of these immigration components 

than for legal immigration and emigration.

The conventional approach to the unauthorized 

and temporary components is to use an age-sex 

distribution of temporary migrants (or unauthorized migrants) taken from a survey or some other 

dataset. Such an age distribution is positive for 

every age group in which migrants are found; the 

distribution is never negative. However, the unauthorized migrant population has large concentrations in the ages 18–29 and relatively few persons 

at ages 40–45 and over. While the population ages 

somewhat with the passage of time, these age concentrations can still be found. To achieve such relative stability over time requires that a very high 

percentage of the in-flow goes into the early 20s 

and that after age 35 to 40 the net flow is negative 

(i.e., more unauthorized migrants depart than arrive). Figure 17 illustrates the difference in distribution between the unauthorized migrant population and unauthorized net immigration.

A consequence of using the wrong distribution 

is that the population ages “too quickly” by not 

allowing for out migration of persons at ages 40 

and over. Thus, over the medium- to long-term, 

the size of the labor force is slightly understated 

and the size of the older population not in the labor force is overstated. This problem can be fixed 

with the current methodology by using a corrected age distribution. Since the temporary and 

unauthorized components capture net migration, 

the simplest way to derive the correct distribution for this component is to take the difference 

between the age-sex distributions at two points 

in time and correct the difference for mortality 

that occurred in the interval.

Model Enhancements 

Elsewhere, the Panel lays out the case for the use 

of micro-simulation in the Trustees’ projections. 

The immigration assumptions illustrate the potential power of this approach. Specifically, the immigrants have very different patterns of educational 

attainment and income than natives. Further, the 

different types of migrants differ more from each 

other than from natives. Although legal immigrants 

are much more likely than natives to have failed to 

complete high school, they are also more likely than 

natives to have bachelor and graduate degrees. Unauthorized migrants are considerably less likely to 

be college graduates and much more likely to have 

less than a high school education. Legal temporary 

migrants are almost the mirror image of this pat285

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39 17 10

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Immigration

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25-29 years30-34 years

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40-44 years

45-49 years

50-54 years

55-59 years60-64 years

65-69 years

70-74 years75-79 years

80-84 years

85+ years

Population in Thousands

Figure 16: Sample Age Distributions for Legal Immigration and Legal Emigration for 2000-2005
54 2007 Technical Panel on Assumptions and Methods

tern with fewer high school “drop outs” and many, 

more with post-high school education. The current 

model assumes all immigrants have the same education distribution as natives. 

Other key differences between natives and immigrants are in labor force participation, fertility, emigration, and, as noted above, in payment of Social 

Security taxes and receipt of benefits. Male immigrants of working age are more likely than natives 

to participate in the labor force with unauthorized 

migrants being much more likely. Female immigrants are considerably less likely to participate in 

the labor force than native women. Unauthorized 

immigrant women are more likely to be married, 

more likely to have young children, and less likely 

to be in the labor force than either native women 

or LPR women. These behaviors are associated, in 

part, with higher fertility than native women. The 

current model assumes, however, that a new immigrant takes on the behavior of the average U.S. 

person in their age group (predominantly natives) 

immediately upon entering the U.S. population.

Finally, almost all emigration involves movement 

out of the country by foreign-born persons, i.e., 

former immigrants. As the size of the foreign-born 

population increases, the level of emigration would 

be expected to increase. This pattern can be easily 

captured by applying out migration rates to the 

foreign-born population. 

All of these differences, and many others, can be 

easily incorporated into a working micro-simulation model. The Panel strongly recommends that 

the Trustees pursue research to incorporate the differentials noted into the projection model. Ideally, 

the research would be in the direction of adopting 

micro-simulation models, but there are other possible approaches. 

An alternative approach to micro-simulation involves elaboration of the Trustees’ cell-based projection model. Essentially, the population would be 

subdivided into native- and foreign-born populations, by age and sex at a minimum, but also possibly by marital and labor status. This matrix of population values would be carried forward in time using 

the same models and procedures as with the current 

projections. New immigrants would be fed into the 

foreign-born matrix, but their native-born children 

would be fed into the native matrix. Where key parameters are known to differ—as in total fertility 

rates, educational distributions, or labor force participation—different sets of rates and proportions 

would be applied to the native and foreign-born 

matrices. Where the parameters are thought to be 

the same or at least not known to differ in critical 

ways, the current factors could be used. Methods 

similar to this have been used by the Census Bureau 

to develop separate projections of the foreign-born 

population and to model emigration levels as a 

4.2%

5.7%

12.8%

15.9% 15.6%

9.9%

6.3%

3.9%

2.2% 1.2% 0.5%

12.2%

7.0% 6.0%

11.3%

18.3%

6.5%

-1.5% -1.0% -0.7% -0.5% -0.3%

7.3%

1.9%

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-5.0%

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

35.0%

40.0%

45.0%

 0-4

years

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years

10-14

years

15-19

years

20-24

years

25-29

years

30-34

years

35-39

years

40-44

years

45-49

years

50-54

years

55-59

years

60-64

years

 65+

years

Unauthorized Population

Net Unauthorized

Migration

12.8%

7.8%

-3.5%

38.5%

Figure 17: Sample Age Distributions for Net Unauthorized Migration and Unauthorized Population: 

Distribution based on 2000-2005 Change and 2005 Population

Figure 17: Sample Age Distributions for Net Unauthorized Migration and Unauthorized Population: Distribution based on 2000-2005 Change and 2005 Population
2007 Technical Panel on Assumptions and Methods 55

function of rates.93 Even more elaborate models 

have been used to capture generational dynamics 

of the Hispanic population94, education and labor 

force projections95, and race-generational dynamics 

of the 20th century.96 Projections from this disaggregated model would more accurately capture the 

dynamics of the interaction of immigrants with the 

Social Security system. The Panel recommends that 

the Trustees pursue one of these two approaches 

to developing projections more appropriate to the 

dynamics of a population for which immigration 

is a principal driver of population and labor force 

change. 

D. Disability Incidence and Termination 

Assumption Recommendation A-5: Disability Incidence Rates: The Panel recommends that the assumptions of disability incidence for the intermediate projection remain the same as in the 2007 

Trustees Report. Disability incidence assumptions 

were lowered in the 2007 Report and the Panel believes this revision was reasonable given the data 

on health and benefit trends. These same data on 

health and benefit claiming lead the Panel to recommend changes to the low- and high-cost alternative scenarios. Specifically, the Panel recommends 

raising disability incidence in both the low- and 

high-cost scenario, from 4.4 to 4.6 and 6.6 to 6.9, 

respectively. These changes increase the uncertainty bands around the intermediate assumption and 

introduce asymmetry into the risk profile, allowing 

for larger cost overruns than cost savings in the alternative scenarios.

Assumption Recommendation A-6: Disability Termination Rates: The Panel recommends that the 

assumptions of disability termination remain the 

same as in the 2007 Trustees Report but calls for 

more research on these matters going forward. 

Changes in the mix of impairments and the age of 

benefit claiming suggest that life expectancies of 

the average future beneficiary could increase more 

quickly than those of the rest of the population. 

While termination rates are much less important 

to overall cost projections than incidence rates, 

greater understanding of the factors affecting future trends is warranted.

93 Hollmann et al. 2000, op. cit.

94 Passel 2004, op. cit.; and Passel and Cohn, 2008, op. cit.

95 Passel, 2005, op. cit.

96 Edmonston and Passel, 1994, op. cit., including a methodological 

explanation,

Method Recommendation M-14: Improvements in 

Current Models: The Panel recommends that consideration be given to augmenting the cell-based 

model of disability incidence and termination rates 

to include impairment specific data. The Panel also 

calls for additional examination of the evolution of 

male and female disability incidence rates and for 

more explicit discussion of the historical and forecast time path of these rates, including why they are 

not converging more over time. Overall, the Panel 

recommends that the judgmental adjustments to 

the cell-based model of disability incidence and disability termination be more formally documented.

Method Recommendation M-15: Behavioral Models and Risk Assessment: The Panel recommends 

that the models used to develop the short- and 

long-range projections for the DI program be better integrated and that the long-range projection 

methodology be better documented. More fundamentally, the Panel recommends that greater emphasis be placed on developing behavioral models of 

disability benefit claiming that could better inform 

the judgmental adjustments to historical extrapolations underlying the intermediate projections, 

improve the short- and long-run forecasts, and increase understanding of the risk factors associated 

with short- and long-run program growth. 

Method Recommendation M-16: Communications 

about the Disability Program: The Panel recommends more focus on communication about key 

components of the disability program followed by 

the research community. Specifically, the Panel recommends highlighting the distinction between eligibility for disability benefits—based on health—

and claiming behavior, which is based on eligibility 

and socio-economic conditions, age, and policy variables such as the normal retirement age. The Panel 

also recommends that published materials report 

disability prevalence rates, in addition to incidence 

and termination rates. Prevalence rates are the 

preferred metric in the research literature for summarizing the stock of workers receiving disability 

benefits and provide important information about 

the size of the program over time. Finally, the Panel 

recommends that the relationship between the DI 

and retirement programs be made explicit—DI is 

just a form of early retirement—especially in discussions about future influences on program size.
56 2007 Technical Panel on Assumptions and Methods

Overview

The Panel finds the Trustees’ forecasts of the size 

and cost of the Disability Insurance (DI) program as 

reported in the 2007 Trustees Report to be reasonable and generally consistent with views of other 

agencies and the broader research community. The 

Panel is less confident in the Trustees’ assessment 

of risks to these forecasts and recommends several 

modifications and additions, including: raising the 

assumptions on disability incidence in the high- and 

low-cost alternatives, allowing for asymmetry in the 

deviations from intermediate projections represented in the high- and low-cost scenarios, and devoting 

greater resources to examining components of risk to 

the disability incidence forecasts. Methodologically, 

the Panel echoes recommendations from previous 

Technical Panels and calls that greater attention be 

paid to the behavioral aspects of disability benefit 

claiming, especially in relation to socio-economic factors such as changing labor market conditions, wage 

dispersion, workplace accommodations, and increases in the normal retirement age. 

Explanations and Discussion97

SSA projects future costs of the Disability Insurance (DI) program based on projections of two key 

variables: (1) the disability incidence rate, and (2) 

the disability termination rate. The disability incidence rate (computed yearly) shows the number of 

newly entitled DI beneficiaries as a percentage of 

the number of DI insured workers. The disability 

termination rate shows the number of exits from 

disability beneficiary status due to death, recovery, 

and conversion (i.e., movement onto the retirement system at the normal retirement age). Prevalence rates are derived from separate projections of 

incidence, death, and recovery rates, and the total 

number of conversions. The main uncertainty in 

projections of DI costs comes from projections of 

the disability incidence rate, with termination rates 

affecting projections to a much lesser degree. 

Forecasting DI beneficiary incidence rates is inherently complex. Covered workers eligible for benefits apply for them based on a set of factors related 

97 The Panel evaluated the procedures used by the OCACT to project 

costs and revenues for the DI program based on published and 

unpublished documentation and conversations with OCACT staff. 

The assumptions and methods are documented in the 2007 Annual 

Report of the Trustees, Short-Range Actuarial Projections of the OASDI 

Program: Actuarial Study Number 119, 2005; and Social Security 

Disability Insurance Program Workers Experience: Actuarial Study

Number 118, 2005. 

to their health and their prospects in the labor market. Policy variables affecting eligibility and enforcement regimes also affect application behavior and 

their relationship to awards. Forecasts of DI incidence rates, then, must account for expected trends 

in health impairments and their effect on work, 

expected changes in socio-economic variables that 

affect claiming behavior for a given health impairment, and views about the future direction of policy 

variables influencing eligibility. Since many of these 

trends are difficult to predict, and the relationships 

between these factors and claiming behavior could 

change over time, the actuaries forecast disability 

benefit incidence using cell-based, judgmentallyadjusted extrapolations from historical trends, in 

place of structural behavior-based modeling. This 

approach has been accepted by this Panel and previous reviewers as producing reasonable projections 

of short-run rates of disability incidence. 98 There are 

a few areas where improvements could be made. 

Improvements to Current Models

First, at present the cell-based model includes 

simple age by sex stratification. The rapid rise in 

claims among individuals with mental impairments and muscular-skeletal impairments suggests 

some payoff to expanding the stratification to be 

impairment-specific. The age by gender by impairment disability incidence rates would also be useful in understanding whether total incidence rates 

for males and females are likely to converge to the 

same value over time.

More fundamentally, though, it is not clear that 

the current cell-based extrapolation accurately captures the uncertainty surrounding the intermediate 

projections. The magnitude of uncertainty about the 

DI program can be seen in the fluctuations in disability incidence rates that have occurred over the past 

30 years as illustrated in Figure 18. Very little of this 

variation can be explained by aggregate changes in 

health status. Research on other potential factors associated with these movements point to a large influence of increases in female labor force participation, 

and changes in socio-economic and policy variables 

(e.g., changes in labor market conditions, the easing 

of disability program standards, and changes in the 

normal or early retirement age).99

98 This Panel and the previous two Technical Panels accepted the 

intermediate assumptions of disability incidence, in the relevant 

Trustees Reports, based on this method.

99 Autor, David and Mark Duggan, “The Growth in the Social Security Disability Rolls: A Fiscal Crisis Unfolding,” Journal of Economic 
2007 Technical Panel on Assumptions and Methods 57

The influence of these variables suggests that 

risks to any projection based on extrapolations 

from simple age by sex cell-based trends could be 

substantial. The Panel believes that the historical 

fluctuations in disability incidence rates, and their 

apparent relationship to labor market conditions, 

wage dispersion, and changes in OASDI policy, create considerable uncertainty around the intermediate forecast. In the Panel’s view, this uncertainty 

points to the potential for larger cost overruns 

than cost savings and larger risk bands around the 

estimate than those presented in the 2007 Trustees Report.

Disability termination rates are much less important in the overall calculation of DI program costs. 

However, there is still relevant debate around their 

forecasts. The key issue in forecasting disability termination rates is in accurately forecasting death 

rates for those on benefits. Following rapid improvement in age-adjusted mortality rates for the DI population through the 1990s, DI mortality rates have 

slowed to rates closer to the overall population. The 

2007 Trustees Report sees this more recent trend 

continuing for the foreseeable future. Although the 

Panel recommended no change to the assumptions 

Perspectives, Summer, 2006, pp.71-94; Duggan, Mark and Scott 

Imberman, “Why are the DI Rolls Skyrocketing?”, Forthcoming 

in Health at Older Ages, edited by David Cutler and David Wise, 

University of Chicago Press; and Burkhauser, Richard V. and Mary 

C. Daly, “U.S. Disability Policy in a Changing Environment,” Journal 

of Economic Perspectives, Winter, 2002, pp.213-224.

about disability termination in the 2007 Trustees 

Report, we do recommend more formal analysis of 

the relationship between impairment mix and ageadjusted mortality rates in the DI population over 

time. It would be useful to see how these changes 

can be related to past changes in the age-sex adjusted mortality experience of beneficiaries, and if a 

reasonable relationship is found, how well it can be 

used to forecast out-of-sample values.

Behavioral Modeling

Ultimately, greater understanding of the potential influences on short- and long-run program 

growth comes from producing complementary 

behavioral models. This Panel echoes previous 

panels in recommending more resources be devoted to this effort. There are several benefits 

from improving behavioral modeling of disability 

benefit incidence. Information from behavioral 

models can inform the judgmental adjustments 

embedded in the current projections. They also 

can aid in prioritizing among the many variables 

that influence disability benefit application and 

award, and in understanding the potential risks 

to the short- and long-run forecasts. Ideally, assumptions made with respect to DI beneficiary 

incidence rates should be consistent with those 

made about age-based labor force participation 

rates and other key factors used to determine 

Old Age Insurance (OAI) incidence rates, costs 

Figure 18: Disability Incidence Rates by Gender, 1975-2006

0.000

1.000

2.000

3.000

4.000

5.000

6.000

7.000

8.000

9.000

1970 1975 1980 1985 1990 1995 2000 2005 2010

Year

Male

Female

Awards per 100 disability exposed

Figure 18: Disability Incidence Rates by Gender, 1975-2006
58 2007 Technical Panel on Assumptions and Methods

and revenues. Having a behavioral model that allows for these interactions would aid in creating 

a more unified structure.

Communications

As described above the projection process should 

consider both changes in underlying health factors 

and in the social environment that result in changes 

in DI beneficiary incidence rates. In projecting changes in the social environment, OCACT should especially recognize how ongoing policies and trends—such 

as the increase in the Normal Retirement Age (NRA) 

and the increasing incidence of awards on the basis 

of mental disorders—will affect workers with disability when they decide between continued efforts 

to remain in the work force and program application. 

These dual components of disability claiming status 

should be explained in the Trustees Report and other 

publications about the OASDI system. 

Another important aspect of communication regarding the DI program is to report prevalence rates. 

Prevalence rates show the number of individuals at 

any point in time receiving disability benefits. As 

Figure 19 highlights, apart from a short period in 

the early 1980s, the prevalence of disability benefit 

receipt has been flat or rising. Prevalence rates capture both the inflow to the program and the duration of time on the program. As such, they more 

accurately capture the consequences for system finances of the fluctuations in incidence rates shown 

in Figure 18. Therefore, they are a very useful gauge 

of costs associated with keeping the existing stock 

of beneficiaries funded. Reporting prevalence rates, 

in addition to incidence and termination rates, provides researchers and policy makers with important information about the future path of claims 

on resources. Although predicting the future path 

of policy is beyond the scope of the Trustees, understanding and documenting the factors likely to 

inform and affect policy decisions, (such as prevalence rates), is important and useful.

While the DI and Old-Age and Survivors Insurance (OASI) programs have separate funds, 

analysts and policymakers should understand 

that these separate calculations are nevertheless 

intertwined, and the assumptions for each fund 

must be consistent. In fact, after a DI beneficiary 

reaches the Normal Retirement Age, his or her 

benefits are paid from the OASI fund. In some 

sense, it is best to think of DI as nothing more 

than a case of “early-early” retirement. Changes 

in the Normal Retirement Age not only mechanically change the age at which people convert to 

the OASI fund, they also potentially influence the 

decision to apply for DI in the first place. 

Figure 19: Disability Prevalence Rate, by Gender, 1975-2006

0

5

10

15

20

25

30

35

40

45

50

1975 1980 1985 1990 1995 2000 2005

Year

Total

Male

Female

Disabled worker population per 1000 insured population

Figure 19: Disability Prevalence Rate, by Gender, 1975-2006
2007 Technical Panel on Assumptions and Methods 59

A. Labor Force Participation Rate

Assumption Recommendation A-7: Labor Force Participation Rate: The Panel recommends no change in 

the intermediate and high-cost projections of labor 

force growth reported in the 2007 Trustees Report, 

but calls for an increase in the labor force participation rate used in the low-cost alternative. The Panel 

believes there is considerable upside risk to the intermediate assumption on labor force participation 

related to the possibility that greater life expectancy, improved health, unmet demand for workers, 

changing workplace requirements, and the reduction in rule-based private retirement plans could 

increase participation rates at older ages. The Panel 

believes that allowing for this possibility is important and could ultimately affect both the intermediate and low-cost scenarios. As such, we recommend 

increasing total labor force participation in the lowcost scenario from 72.8 to 77.0 percent for males 

and from 60.6 to 65 percent for females.100

Method Recommendation M-17: The Labor Force 

Participation Model: The Panel recommends that 

the OCACT labor force participation model be reviewed and potentially restructured. Currently, 

the model is large and unwieldy, making modifications difficult and costly. Additions to the model 

required to incorporate emerging trends (e.g., participation rates by nativity) only add to the complexity. Thus, we recommend that the Trustees 

implement suggestions made in the 2003 Technical Panel and restructure the model, making it simpler, more transparent, and econometrically more 

rigorous.

100 The change in total participation rates comes from assuming 

that rates for each 5-year age group above 55 would attain, in 75 

years, the participation rates of the next younger 5-year age cohort 

at the beginning of the projection period. For example, those aged 

55-59 would in 2081 experience the participation rates of 50-54 

year olds in 2007, and so on for each successive 5-year cohort.

Method Recommendation M-18: Important Subgroups to Study: The Panel recommends more 

carefully following differences in labor force participation among various groups including natives 

and non-natives and older workers from different 

cohorts. Given the growing importance of both immigrants and older workers in the workforce, improved understanding of differences in their labor 

force behavior will be important to improving the 

accuracy of future projections.

Method Recommendation M-19: Integration of 

Labor Force with Other Projections: The Panel recommends that more consideration be given to how 

changes in the population and labor force might impact trends in hours of work, productivity and annual earnings and that these interrelationships be 

noted in the Trustees Report. This communication 

of the interconnectedness of the assumptions and 

projections is a useful component of policy discussions and decisions. The absence of such recognition 

hinders accurate characterizations of the tradeoffs 

and complementarities embedded in changes to 

particular variables, trends or policy alternatives.

Overview

The 2007 Trustees Report projects no net change 

in the labor force participation rate for males and 

only a slight increase for females over the next 75 

years. Although the Technical Panel recommends 

no change to this intermediate projection, we believe there is significant upside risk to this projected 

path. As such, we recommend putting more weight 

on the possibility that greater life expectancy, improved health, unmet demand for workers, changing workplace requirements, and the reduction in 

rule-based private retirement plans will increase 

participation rates at older ages and increase the total labor force participation rates in the low cost scenario from 72.8 to 77 for males and from 60.6 to 65 

percent for females. The Panel believes that allowing 

Chapter 3: Economic Assumptions and Methods
60 2007 Technical Panel on Assumptions and Methods

for this possibility is important and at a minimum 

should be reflected in the low cost scenario. 

In terms of methodology, the Panel reasserts recommendations made by the 2003 Technical Panel 

and calls for a thorough review and potential revision to the methods and models used by OCACT to 

project labor force participation rates. Specifically, 

we recommend that the models underlying projections of labor force participation be simplified, better documented, and more directly linked to other 

trends important to the finances of Social Security 

including trends in hours worked, productivity and 

annual earnings. Improvements in these areas will 

allow researchers to compare models and projections on these variables across agencies and against 

newly emerging research findings.

Explanations and Discussion 

The OCACT labor force model converts estimates 

of the population into estimates of Social Security 

taxpayers by age and sex. Together with assumptions defining the growth in real wages, the labor 

force model produces estimates of annual revenues 

to Social Security. The current labor force participation model is quite complex. The base methodology 

involves three steps: (1) estimate the historical link 

between the age-specific labor force participation 

rates (LFPR) and economic, demographic and policy 

variables (e.g., business cycle, disability rates) for 

various groups (classified by age, sex, marital status 

and child presence); (2) subjectively adjust some estimated coefficients based on economic theory, prior 

beliefs, and the “full mosaic” of all estimated coefficients; (3) estimate fitted values of the LFPRs of each 

group based on projections of explanatory variables 

and these estimated/imposed coefficients. The models for older ages are conceptually similar, but estimate retirement hazard rates (the percent of workers 

in the labor force who retire). These retirement rates 

are applied to the participation rates for younger 

workers to obtain the remaining participation rates. 

As detailed in the 2003 Technical Panel, the multistep process involved in this model as well as its sheer 

size make it unwieldy and difficult to follow. The subjective adjustments applied to the estimates further 

cloud the results, making it difficult for researchers or 

other outside parties to understand, replicate or improve upon the model. Implementing any one of the 

several suggestions described in the 2003 report would 

be an important step toward increasing transparency 

and improving discussion around the results. 

A simplified model structure would also improve 

OCACT ability to respond to changes in the population and the labor market likely to influence future 

participation rates. If there were fewer regressions 

or a pooled regression, adding new variables or altering the specification would be far easier, cheaper and 

faster. As such, this would improve OCACT’s ability 

to perform risk assessments and run alternative scenarios relevant to policy makers. Given the uncertain 

nature of the paths of many of the variables feeding 

into the labor force participation decision, the flexibility to perform simulations could greatly increase 

understanding. We recommend that more resources 

be devoted to reviewing and restructuring the labor 

force participation model used by OCACT. 

In addition to improving the overall methodology and models underlying projections of labor 

force growth, the Panel also calls for greater analytic focus on two important subgroups of potential workers: immigrants and older individuals. 

It is the Panel’s view that given projected unmet 

demand for workers going forward, trends in nonnative workers and older workers will be critical to 

forecast accurately a variety of variables including 

labor force growth, real wages, hours worked, and 

productivity. 

Immigrants 

At present the OCACT model does not account for 

nativity when projecting labor force participation. 

As Figure 20 shows, foreign-born men participate at 

greater rates than natives and their rates of participation have been rising while those of native-born men 

have been falling. Foreign-born women participate at 

lower rates than native-born women but this gap has 

closed in recent years, as labor force attachment of 

foreign-born women has increased. Given the growing share of potential workers who are immigrants, 

tracking differences in these rates and ongoing 

changes over time between natives and non-natives 

is likely to improve the forecast of labor force participation and thus growth, at least in the short-run.

Older workers

An even more critical area for additional tracking, research, and modeling is in the behavior of 

older workers. As reflected in the Panel’s recommendation for the low-cost alternative, we believe there are several reasons to think trends 

in work behavior among older workers will increase over time. First, the trend toward earlier 
2007 Technical Panel on Assumptions and Methods 61

retirement seems to have stopped or at least 

temporarily paused. The participation rates for 

older men have been relatively stable over the 

past 20 years and are now slightly higher than 

those of the mid-1980s (see Figure 21). Until 

about 1985, the trend toward earlier retirement 

was offset for women by the trend toward higher 

labor force participation in general, resulting in 

rather flat participation rates for older women. 

In recent years, the trend has shifted to increasing participation at older ages (see Figure 22). 

Although it is still too early to know exactly what 

is driving the changes in labor force participation at 

older ages, possible explanations include improvements in health, availability of less physically demanding jobs, changes in employer-sponsored benefits, and changes in Social Security benefit rules.101

101 Urban Institute, “Work and Retirement: Facts and Figures,” AuFigure 20: Labor Force Particpation Rate, by Nativity and Gender: 1994-2006

73% 73%

71%

76%

80% 81%

59%

61%

60%

50%

54% 55%

45%

50%

55%

60%

65%

70%

75%

80%

85%

1992 1994 1996 1998 2000 2002 2004 2006 2008

Male, Foreign-born

Male, Native-born

Female, Native-born

Female, Foreign-born

Figure 20: Labor Force Particpation Rate, by Nativity and Gender: 1994-2006

Figure 21: Male Labor Force Participation Rates: Ages 60-64 and 65-69

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Males 60-64 Actual

Males 60-64 Fitted

Males 65-69 Actual

Males 65-69 Fitted

Figure 21: Male Labor Force Participation Rates: Ages 60-64 and 65-69, Actual vs. 20-year Forecast 

Fitted to 1964-1986 Data 
62 2007 Technical Panel on Assumptions and Methods

Figure 22: Female Labor Force Participation Rates: Ages 60-64 and 65-69, Actual vs. 

20-year Forecast Fitted to 1964-1986 Data

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010

Females 60-64 Actual

Females 60-64 Fitted

Females 65-69 Actual

Females 65-69 Fitted

Figure 22: Female Labor Force Participation Rates: Ages 60-64 and 65-69, Actual vs. 20-year Forecast 

Fitted to 1964-1986 Data

Data from the National Center for Health Statistics show that the health of older Americans has 

improved steadily over the last 20 years. Although 

the rate of improvement appears to have slowed of 

late, ongoing improvements are anticipated. Better 

health combined with access to less physically demanding jobs means that fewer older workers cite 

health as a reason for not working. Institutional 

constraints to working at older ages also have been 

declining. Many employers have replaced traditional rule-based defined benefit pension plans (which 

penalized older workers for staying on the job) 

with defined contribution plans which increase in 

value with extra years of work. On the health side, 

a declining share of employers offer retiree health 

insurance, discouraging retirement until Medicare 

begins. Finally, Social Security reforms made for 

those born after 1938 are starting to kick in. These 

reforms gradually raise the normal retirement age 

from 65 to 67, increase the rate at which monthly 

payments rise with delayed benefits, and eliminate 

the benefit reduction for those working beyond the 

full retirement age. Combined these factors likely 

contributed to the rise in labor force participation 

at older ages observed over the past several years 

and are likely to affect it further going forward. 

gust, 2006. [http://www.urban.org/UploadedPDF/900985_work_

and_retirement.pdf]

B. Unemployment

Assumption Recommendation A-8: The Panel recommends that the assumptions on unemployment 

remain unchanged from the 2007 Trustees Report. 

The Panel finds a long-run unemployment rate of 

5.5 percent is a reasonable assumption for future 

unemployment rates.

C. Real Wage Growth

There are numerous concepts of the real wage corresponding to alternative measures of the nominal 

wage in the numerator and alternative price indexes 

in the denominator. The concept of the real wage 

relevant for the Trustees Report is earnings (excluding fringe benefits) per employee, divided by 

the CPI. Social Security benefits are indexed to wage 

growth, but the effect of wage growth on benefit expenditures is smaller than the effect on payroll tax 

revenues. First, there is a lag between the years a 

worker pays taxes and the year the worker becomes 

entitled to benefits. Second, following entitlement, 

benefits are indexed not to wages but to the slowergrowing CPI. Therefore, system finances are sensitive to changes in real wage growth.

The Trustees Report contains separate estimates of 

the growth in labor productivity, and the growth in 

each of several linkages between labor productivity 

and real wage growth. As shown in the following ex-
2007 Technical Panel on Assumptions and Methods 63

pression, real wages depend on output per hour (labor 

productivity); labor compensation as a share of GDP; 

wage, salary and self-employment earnings as a share 

of labor compensation; hours per worker; and the ratio 

of the GDP deflator to the consumer price index:

The term on the left-hand side of the expression is 

average real annual earnings per employed person, referred to as the real wage. The real wage equals wage, 

salary and proprietors’ earnings as reported in the National Income and Product Accounts, deflated by the 

CPI to convert it to a real figure and divided by employment to put it on a per-worker basis. The first term on 

the right hand side of the equation is real output per 

hour, or labor productivity. It is important to note 

that this measure of productivity applies to the whole 

economy, not the private or non-farm private business 

sectors that are described in the regular quarterly releases of the Bureau of Labor Statistics. The numerator of this productivity ratio is total real GDP and the 

denominator is economy-wide hours as tracked quarterly in an unpublished series by the Bureau of Labor 

Statistics (BLS). In the second term, the ratio of labor 

compensation to GDP, labor compensation includes 

employers’ benefit and social insurance costs in addition to amounts disbursed as wages, salaries and selfemployment income. The third term on the right-hand 

side shows earnings as a share of total labor compensation. The fourth term equals average annual hours 

per employed person. The last term captures the ratio 

of the price deflator relevant to the total output of the 

economy (as used to deflate real GDP, the numerator 

of the productivity ratio), relative to the CPI (which is 

used to index Social Security benefits). 

The above equation relates the level of the real wage 

to the levels of the various linkage ratios on the righthand side of the equation. However, in practice, the 

forecasts of the Trustees Report project not the levels 

but rather the growth rates of productivity, the real 

wage and each of the linkage variables just described. 

The relevant annual growth rates listed here are the 

Trustees’ “ultimate” growth rates, typically starting 

within 10 years of the beginning of the projection period and extending to the end of the 75-year horizon.

The 2003 Technical Panel recommended that the 

Trustees increase the projected rate of growth in 

the real wage (referred to as the real wage differential) from 1.1 percent per year as stated in the 2003 

Trustees Report to 1.3 percent per year. In terms 

of the above equation, they obtained this recommendation by raising the productivity growth rate 

from 1.6 to 1.7 percent per year and by reducing 

the negative growth rate of the earnings/compensation ratio from -0.2 to -0.1 percent per year. On 

balance there has been very little change from the 

recommendations of the 2003 Technical Panel and 

the assumptions of the 2007 Trustees Report. The 

productivity growth rate of 1.7 percent per year 

is the same. The only differences are: 1) the 2007 

Trustees Report includes a projected growth rate of 

the earnings/compensation ratio of -0.2 instead of 

the -0.1 recommended by the 2003 Technical Panel; 

and, 2) the Trustees choose a projected growth rate 

of the GDP Deflator to CPI ratio of -0.4 percent per 

year as compared to the -0.3 percent per year recommended by the 2003 Technical Panel.

Productivity Growth 

Assumption Recommendation A-9: The Panel recommends that the assumption on productivity 

growth be maintained at the same rate as in the 

2007 Trustees Report, that is, 1.7 percent per year. 

This recommendation reflects the sharp slowdown 

in actual productivity growth between mid-2004 

and mid-2007 that has reduced the possibility that 

2007 Trustees Report Ultimate Growth Rate 

Assumptions

Real Wage Growth = 1.1 pct/yr

+ Growth in 1.7 pct/yr

labor productivity

+ Growth in 0.0 pct/yr

[labor compensation/GDP]

+ Growth in -0.2 pct/yr

[earnings/labor compensation]

+ Growth in 0.0 pct/yr

[total hours/employment]

+ Growth in -0.4 pct/yr

[GDP deflator/CPI]

(Earnings/CPI)/ = (GDP/GDP Deflator)/ x (Labor Compensation)/

(Employment) (Total Hours) (GDP)

x (Earnings)/ x (Total Hours)/ x (GDP Deflator)/

(Labor (Employment) (CPI)

Compensation)

Real Wage Growth Linkages
64 2007 Technical Panel on Assumptions and Methods

the American economy entered a new era of rapid 

high productivity growth after 1995. Instead, it appears that the marked acceleration of productivity 

growth between 1995 and 2004 can be attributed to 

special one-time factors that are unlikely to recur. 

In forecasting future productivity growth, substantial weight must be given to the poor performance 

of productivity growth in the period 1972-1995. 

The 2007 Trustees Report projects ultimate labor 

productivity growth rates of 1.7 percent per year 

for the intermediate-cost case, 2.0 percent for the 

low-cost, and 1.4 percent for the high-cost case. 

These projections are for the total U.S. economy 

(real GDP per hour worked). 

Although productivity growth over the past decade 

has been notably faster than 1.7 percent per year, the 

Trustees, OCACT, and the Technical Panel must take 

a longer view when forecasting productivity growth 

over the next 75 years. To put the last decade in a 

broader historical context, Figure 23 contrasts facts 

on the actual behavior of total economy productivity 

growth with statistically estimated trends. The thin 

red zigzag line is the annualized growth rate of total 

economy productivity over the previous eight quarters. We see that this series exhibits highly volatile 

spikes of positive and negative growth. For the purposes of Social Security forecasts, short-run volatility is relatively unimportant. Rather, averages taken 

over a longer period of time must be utilized. 

The thick blue line in the figure displays the longrun trend in total economy productivity growth. 

These trends are developed as the average of trends 

computed by two different statistical procedures, 

the so-called Hodrick-Prescott filter and the Kalman 

filter.102 Compared to the current 2007 Trustees’ assumption of 1.7 percent per year for productivity 

growth in the long run, the estimated trend is both 

above and below 1.7 percent over substantial periods. The trend reached a peak of 2.7 percent per year 

in 1962 and remained well above the current Trustees’ long-run estimate, falling below 1.7 percent only 

in 1973. Between 1973 and 1998 the trend was well 

below 1.7 percent but then revived between 1998 

and 2006, reaching a peak of 2.3 percent in 2002.

Clearly, the average of the past 40 or so years 

reveals an average growth rate of total economy 

productivity that is quite close to the current 2007 

assumptions of the Trustees over the next 75 years. 

So the question is: Are there reasons why the Trustees’ estimates should give special weight to particular periods in the post-war era when total economy 

productivity growth has been so volatile? 

To address this question it is useful to consider 

the drivers of the volatility in productivity growth 

shown in Figure 23. First, why was productivity 

growth particularly rapid in 1950-65 and much slow102 See Gordon, 2003, pp. 221-3, for details about the methods of 

de-trending used in Figure 23. Over the past decade the HodrickPrescott and Kalman filter methods yield very similar estimates of 

the underlying productivity trend.

Figure 23: Actual 8-quarter Annual Rate of Change of Total Economy Output per 

Hour and Estimated Trend Growth

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005

Year

Trend in Total Economy LP

Actual 8-Quarter Change

Figure 23: Actual 8-quarter Annual Rate of Change of Total Economy Output per Hour and Estimated Trend Growth
2007 Technical Panel on Assumptions and Methods 65

er from 1965 to 1995? Although there is a considerable literature on this topic there is no consensus. A 

plausible hypothesis refers to impact of “Great Inventions” (electricity and the internal combustion 

engine) and their lagged influence on productivity 

growth. As the Great Inventions worked their way 

through the economy, productivity growth was particularly rapid during the period 1920-1965. Then 

after 1970 their impact petered out. 

Second, why did productivity growth revive after 1995, with the trend rising from 1.4 percent in 

1995 to a peak of 2.3 percent in 2002, before falling 

back to about 1.8 percent in 2007? Again, there is an 

enormous literature on this topic, especially for the 

period from 1995-2000. This research, ably summarized by Oliner-Sichel-Stiroh103, creates a prima 

facie case that the main reason for the productivity 

growth resurgence in the 1995-2000 period was an 

enormous upsurge of investment in information and 

communication technology (ICT).104 The standard 

methodology of growth accounting, which weights 

the contribution of labor and capital input by their 

shares of income compensation, attributes almost all 

of the 1995-2000 resurgence in productivity growth 

to ICT capital investment (see Figure 24). 

103 Oliner, Stephen D., Daniel E. Sichel, and Kevin J. Stiroh, “Explaining a Productive Decade,” Brookings Papers on Economic Activity, no. 1, 2007, pp. 81-152. 104 Other key contributions are Gordon, 2003, and Jorgenson-HoStiroh, 2005.

But what about the 2001-04 period when trend 

productivity growth increased further but investment in ICT capital collapsed? Several theories 

about this period have been offered. First, Brynjolfsson and his co-authors, and Susanto Basu and 

his co-authors argue that it took firms a long time 

to figure out how to productively use the hardware 

and software inventions of the late 1990s, the marriage of personal computers with communication 

technology embodied in internet connections, 

web browsers, and e-mail105. They argue persuasively that the big burst of ICT investment in the 

late 1990s had a delayed spillover effect to subsequent productivity. Much of the productivity benefit of the post-90s investment boom occurred not 

in 1997-2000 but in 2001-04. Others have argued 

that the trajectory of corporate profits, accounting scandals, and executive compensation created 

unprecedented pressure for corporations to cut 

costs, particularly payroll, during 2001-04 and the 

recovery of profits in 2004-07 helps to explain the 

slowdown in productivity growth during that period. Finally, the “early recovery productivity bubble” 

105 See Brynjolfsson, Erik, Lorin M. Hitt, and Shinkyu Yang, “Intangible Assets: Computers and Organizational Capital,” Brookings 

Papers on Economic Activity, no. 1, 2002, pp. 137-81; and Basu, 

Susanto, John G. Fernald, Nicholas Oulton, and Sylaja Srinivasan, 

“The Case of the Missing Productivity Growth, or Does Information 

Technology Explain Why Productivity Accelerated in the United 

States But Not in the United Kingdom?” in NBER Macroeconomics 

Annual 2003, MIT Press, 2004.

Figure 24: Share in Nominal GDP of Nominal Investment in Information Processing Equipment and Software

0.0

1.0

2.0

3.0

4.0

5.0

6.0

1965 1970 1975 1980 1985 1990 1995 2000 2005

Year

Figure 24: Share in Nominal GDP of Nominal Investment in Information Processing Equipment and Software
66 2007 Technical Panel on Assumptions and Methods

helped to push up productivity growth in 2001-04 

and also helps to explain why the decline in productivity growth in 2004-07 was so sharp and sudden. 

Based on available research this panel believes 

it is reasonable to treat the upsurge in trend productivity growth between 1995 and 2005, and 

2000-2005 as temporary phenomena, reflecting a 

combination of one-time events. Based on the above 

analysis, the Panel recommends that the long-run 

total economy productivity projection should remain at 1.7 percent per year, which is a bit above 

the historical growth rate from 1965 to 2007. The 

high- and low-cost scenarios should remain at 1.4 

percent and 2.0 percent, respectively.

One concern not so far discussed in this section is 

the “Baumol Disease” hypothesis that was recently 

reviewed by Blackstone.106 The Baumol disease hypothesis is that certain types of hands-on service 

activities are immune to productivity growth, as in 

the classic example of the string quartet that always 

needs four players. Rapid productivity growth in 

the late 1990s temporarily put the Baumol disease 

on hold, but it has now revived as reflected in slow 

productivity growth since 2004. Future projections 

of productivity growth should take account of the 

increased share of the future workforce that will be 

employed because of longer life expectancies projected in this report. With more employment in 

activities like home health care and nursing home 

care, a larger share of the labor force will be subject 

to Baumol’s disease which surely affects employment activities which involve one-on-one contact.

Compensation to GDP Ratio

Assumption Recommendation A-10: The share of 

labor compensation in GDP has historically been 

quite stable, and the Panel agrees with the current 

assumption of a constant ratio.

The ratio of employee compensation (defined to 

include wage and salary accruals and supplements 

106 Blackstone, Brian, “Is Productivity Growth Back in the Grips of 

Baumol’s Disease?” Wall Street Journal, August 13, 2007, p. A2.

to wages and salaries) to GDP has shown little variation over the last five decades. The average ratio 

over the period from 1950 through 2006 was 57.1 

percent, with a high of 59.4 percent and a low of 

53.5 percent. As shown in Table 6, the ratio edged 

up from the 1950s to the 1970s, but has stabilized 

over the past three decades at around 58 percent. 

The 2007 Trustees Report assumes the ratio will 

remain stable, and the Panel recommends that this 

assumption be retained.

Earnings to Compensation Ratio

Assumption Recommendation A-11: The Panel recommends that the change in the earnings to compensation ratio be reduced in the intermediate-cost 

assumption from a decline of 0.2 percent per year to 

a decline of 0.1 percent per year for the first 25 years 

of the projections, with a zero decline after that. In 

the low-cost assumption, the current ratio should be 

held constant, while in the high-cost assumption, the 

ratio should decline by 0.2 percent per year for the 

first 25 years and by 0.1 percent thereafter. 

Prior to World War II, non-cash compensation 

accounted for only a tiny fraction of workers’ total 

compensation. Restrictions on cash wage increases 

imposed by the War Labor Board during the war 

years encouraged employers to offer nonwage benefits such as pension plans and health insurance. 

These employer-provided benefits proved over time 

to be popular, in part because such non-cash compensation is not subject to personal income tax, and 

they grew in importance in subsequent decades. 

The costs of legally required benefits also became a 

larger share of total compensation.

As shown in Figure 25, these changes led to a 

steady decline in the share of total compensation accounted for by cash earnings that persisted through 

about 1980. The National Income and Product Accounts provide the most consistent source of data 

Table 6: U.S. Average Compensation Ratios

1950-59 1960-69 1970-79 1980-89 1990-99 2000-06 1950-2006

Compensation/GDP 0.549 0.565 0.585 0.580 0.570 0.576 0.571

Compensation is defined as wage and salary accruals plus supplements to wages and salaries. 

Source: National Income and Product Accounts (7/27/07)
2007 Technical Panel on Assumptions and Methods 67

on labor compensation and its composition. In 1929 

(not shown in the chart), cash earnings accounted 

for 98.9 percent of total compensation; by 1980, 

this share had fallen to 85.0 percent. Since 1980, 

however, there has been no consistent growth in 

benefit costs as a share of total compensation, and 

the ratio of earnings to total compensation has stabilized. The average annual growth rate between 

1980 and 2006 is exactly -0.10 percent.

One factor that has contributed to the leveling in 

the ratio of earnings to compensation has been the 

declining ratio of employer pension and profit sharing contributions to total compensation shown in 

Figure 26. The long-term shift from relatively generous defined benefit plans to less generous defined 

contribution plans helps to explain this decline.107

Another factor important to determining future 

trends in the earnings to compensation ratio is 

the future of employer-paid health insurance. Employer-paid health insurance costs rose steadily as 

a share of compensation through the early 1990s. 

This growth slowed dramatically in the mid-1990s, 

107 For an overview of recent trends, see: Poterba, James, Steven 

Venti, and David A. Wise, “The Changing Landscape of Pensions in 

the United States,” National Bureau of Economic Research Working 

Paper #13381, September 2007; and Rappaport, Anna M., “Retirement System at the Crossroads,” Employee Benefit Plan Review, 

February 2003, pp. 17-20.

reflecting the growth in HMOs and Preferred Provider Organizations (PPO), together with the shifting of some health insurance costs from employers 

to employees.108 Employers’ group health insurance 

costs as a proportion of compensation dropped by 

a full percentage point. More recently, however, 

employer-paid health insurance costs as a share of 

total compensation have again resumed its historic 

upward movement, as shown in Figure 27.

The Trustees currently assume that the ratio of 

earnings to compensation will fall by 0.2 percent 

per year for the indefinite future. The projected 

decline in the earnings to compensation ratio is 

based primarily on the Trustees’ belief that tax-exempt health benefits will make up an increasingly 

large portion of compensation. As already noted, 

earnings accounted for 82.8 percent of total compensation in 2006; a 0.2 percent annual decline in 

the earnings to compensation ratio would lead to 

earnings accounting for just 71.3 percent of compensation after 75 years.

Over much of the 20th century, the development of new treatments fueled steady growth 

in health care expenditures. Many observers 

believe that scientific advances will continue to 

108 Schwenk, Albert E., “Trends in Health Insurance Costs,” Compensation and Working Conditions, Spring, 1999, pp. 24- 27.

Figure 25: Trend in the Ratio of Total Earnings to Total Compensation, 1948-2006

0.75

0.80

0.85

0.90

0.95

1.00

1948 1952 1956 1960 1964 1968 1972 1976 1980 1984 1988 1992 1996 2000 2004

Year

Figure 25: Trend in the Ratio of Total Earnings to Total Compensation, 1948-2006

Source: Data from the National Income and Product Accounts, Bureau of Economic Analysis. The numerator of the ratio equals farm and nonfarm proprietors’ 

income plus wage and salary disbursements; the denominator equals farm and nonfarm proprietors’ income plus total employee compensation, including 

social insurance contributions and employer-provided benefit costs.
68 2007 Technical Panel on Assumptions and Methods

Figure 26: Employer Pension and Profit-Sharing Contributions as a Share of Total Compensation, 1948-2006 

0.00

0.01

0.02

0.03

0.04

0.05

0.06

1948 1952 1956 1960 1964 1968 1972 1976 1980 1984 1988 1992 1996 2000 2004

Year Source: Data from the National Income and Product Accounts, Bureau of Economic Analysis. The numerator of the ratio is employer pension and profit sharing plan contributions; the denominator equals farm and nonfarm proprietors’ income plus total employee compensation, including all social insurance 

contributions and employer-provided benefit costs.

Figure 26: Employer Pension and Profit-Sharing Contributions as a Share of Total Compensation, 1948-2006

Source: Data from the National Income and Product Accounts, Bureau of Economic Analysis. The numerator of the ratio is employer group health insurance 

contributions; the denominator equals farm and nonfarm proprietors’ income plus total employee compensation, including all social insurance contributions 

and employer-provided benefit costs.

Figure 27: Employer Group Health Insurance Contributions as a Share of Total Compensation, 1948-2006 

0.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

1948 1952 1956 1960 1964 1968 1972 1976 1980 1984 1988 1992 1996 2000 2004

Year

Figure 27: Employer Group Health Insurance Contributions as a Share of Total Compensation, 1948-2006

push health care costs upward for the foreseeable 

future.109 On the other hand, recent experience 

109 See, for example, Aaron, Henry, “The Unsurprising Surprise of 

Renewed Health Care Cost Inflation,” Health Affairs, January 23, 

2002.

suggests that there will be significant resistance 

to future increases in the health insurance costs 

borne by employers. Employers already have shifted a significant share of health insurance costs to 

their employees. Even more dramatic shifts in 
2007 Technical Panel on Assumptions and Methods 69

this direction should perhaps be anticipated, with 

employers offering their workers a defined contribution to be applied towards health insurance 

coverage—or even a defined contribution to be 

applied towards the benefit package of an employee’s choice—rather than a health insurance plan 

that offers a defined set of benefits.110 Another 

factor is that lower income tax rates could reduce 

the attractiveness of employer-provided benefits 

relative to wage and salary compensation.

Simply shifting health insurance costs from employers to employees need not raise the share of 

earnings that are subject to payroll taxes, which 

ultimately is what matters for the revenues flowing into the Social Security trust funds. A growing 

number of employers offer premium conversion or 

flexible benefit plans, under which employee-paid 

health insurance premiums are sheltered from both 

income and social insurance taxes.111 By making 

the tradeoff between health insurance benefits and 

cash compensation more explicit, shifting costs 

to employees may slow the growth in total health 

insurance expenditures.112 We also can expect continued efforts by insurers and policy makers to 

restrain costs through familiar measures such as 

co-payments and deductibles, requirements for 

second opinions, and even restrictions in coverage 

to treatments deemed cost-effective. Looking further into the future, continued upward pressure on 

medical care costs could lead to increased interest 

among medical researchers in the development of 

innovations that can reduce treatment costs without compromising the quality of care.

The Panel is uncomfortable with projecting that 

the share of earnings in total compensation will fall 

as much over this period as is currently assumed. 

The idea that this ratio will continue to decline over 

the indefinite future, and the resulting implication 

that the earnings share of compensation eventually will approach zero, is even more problematic.

On balance, these considerations, together with 

modest -0.1 percent annual rate of decline observed 

110 U.S. Department of Labor, “The Evolution of Compensation in a 

Changing Economy,” Report on the American Workforce, Washington 

DC, 2001, p. 82.

111 U.S. Bureau of Labor Statistics, “Employee Benefits in Medium 

and Large Private Establishments, 1997,” Bulletin 2517, Washington, D.C.: U.S. Government Printing Office, September 1999.

112 Recent evidence on individuals’ cost sensitivity with respect 

to health insurance purchases is reported in Goldman, Sood, and 

Leibowitz, 2003, which shows that increases in the relative price of 

health insurance faced by participants in a large company’s flexible 

spending plan reduced the amount of insurance they purchased.

since 1980, lead the Panel to conclude that, for the 

intermediate projections, it would be more realistic to adopt as an intermediate assumption a 0.1 

percent annual decline in the earnings to compensation ratio over the first 25 years and a zero rate 

of decrease after that. The implied ultimate level of 

the earnings-compensation ratio would be 80.8 percent. In the low-cost assumption the current ratio 

should be held constant, while in the high-cost assumption it should decline by 0.2 percent per year 

for the first 25 years and at 0.1 percent after that, 

implying an ultimate ratio of 75.0 percent. By comparison the 2003 Technical Panel recommended a 

decline of -0.1 percent with a cut-off when the ratio 

reached 75.0 percent.

Average Hours of Work

Assumption Recommendation A-12: The Panel recommends that the 2007 Trustees’ assumption of 

no change in average hours of work per week be 

changed to a decline of -0.1 percent per year for the 

first 25 years with a zero rate of decline thereafter. The high-cost assumption should be an annual 

decline of 0.2 percent for the first 25 years and a 

decline of 0.1 percent rate thereafter. The low-cost 

assumption would then be zero change, the same as 

the 2007 Trustees’ assumption. 

For much of the twentieth century, average weekly 

hours exhibited a declining trend. As shown in Figure 

28, average weekly paid hours fell from 39.7 hours in 

1948 to 34.0 hours in 1983, continuing a secular decline that had begun much earlier. Recent data suggest this process may have reached its limit. Since 

the mid-1980s, average weekly hours are essentially 

unchanged, exhibiting a cyclical rise in the late 1990s 

that was reversed in the first few years of this decade.

Until 2002, the Trustees had assumed that average 

weekly paid hours would decline at 0.1 percent per 

year over the projection period. The current Trustees’ 

assumption is that average weekly paid hours will remain constant. The reasoning underlying the prior 

assumption of continuing decline in average weekly 

hours seems to have been that, as workers’ real incomes rose, they would choose to consume increased 

leisure, leading to further reductions in the length of 

the work week. Beyond a certain point, however, the 

fixed costs of maintaining an employment relationship borne by both employers and employees argue 

against further declines in hours. 
70 2007 Technical Panel on Assumptions and Methods

One fact that might lead some observers to 

question the Trustees’ projection of stability in 

average weekly hours is the shortening of the 

work week that has been observed in some European countries. A useful comparison is to calculate the annual growth rate in hours per employee 

over two periods, 1960-86 and 1986-2006. The 

annual growth rate in the U.S. came to a halt, 

from -0.33 percent per year in the earlier period 

to -0.02 percent per year in the later period. The 

figures for Europe (the EU-15) fell by more than 

half from -0.86 to -0.33, but remain at a substantial rate of decline. As with the fertility rate, this 

is one among a number of areas in which it is the 

Panel’s judgment that future U.S. trends can be 

better predicted based on our own past experience than on European developments.

However, the Panel feels that the continuing 

decline in hours in Europe together with the 

sharp decline in the U.S. between 2000 and 2006 

make at least a modest further decline likely. As 

a compromise recommendation, we select an annual rate of decline of hours per employee of 0.1 

percent for the first 25 years of the projections 

and zero thereafter. This is consistent with the 

significant possibility for a substantial upward 

movement in the average retirement age (reflected in the Panel’s low-cost labor force participation assumption). We feel that some of the 

added employees in the labor force in the 65-75 

age groups will choose to work part-time rather 

than full-time.

The issue of how to think about hours of work 

is slightly complicated because while weekly 

hours worked is a common measure, the variable 

of interest for Social Security purposes is total 

annual earnings, and thus annual hours. If the 

ratio of average weekly employment (the average 

of the number of people working in each week) to 

average annual employment (number of people 

working at all during a year) is constant, weekly 

and annual hours will have the same trend. Over 

recent decades, however, there has been a decline 

in the prevalence of part-year work, as women 

have become more attached to the labor market. 

This shift presumably is picked up in the adjustment that the actuaries make when they project 

(annual) Social Security covered employment 

based on (weekly) CPS employment. More explicit attention to the factors that underlie the trend 

could perhaps improve the projections, though 

any effect is likely to be quite small.

Figure 28: Trend in Average Weekly Paid Hours, 1948-2006

30

31

32

33

34

35

36

37

38

39

40

1948 1952 1956 1960 1964 1968 1972 1976 1980 1984 1988 1992 1996 2000 2004

Source: Data from the Bureau of Labor Statistics. Average weekly hours equal total annual hours divided by 52 times average monthly employment. The Year

total annual hours estimates were provided by the BLS Office of Productivity and Technology. Average employment is a CPS figure, with an adjustment to 

account for armed forces employment.

Figure 28: Trend in Average Weekly Paid Hours, 1948-2006
2007 Technical Panel on Assumptions and Methods 71

GDP Deflator/CPI Growth Rate Differential

Assumption Recommendation A-13: The differential growth rate between the GDP deflator and 

the Consumer Price Index (CPI-W) should be reduced from the Trustees’ choice of -0.4 percentage points to -0.2 percentage points. We find no 

historical evidence to support the Trustees’ choice 

and indeed in the past six years the differential 

growth rate has been zero.

Of the 0.6 percentage point gap between projected productivity growth and real wage growth, 

the largest single component is the differential in 

growth between the GDP deflator and the CPI, projected in the 2007 Trustees Report to be -0.4 percentage points annually. This factor stems from the 

underlying definition of productivity as real GDP 

per hour in the entire economy. The GDP deflator is 

used to derive the productivity growth rate, which 

directly affects total growth in the economy and 

the taxable wage base. Yet ongoing Social Security 

benefits are adjusted annually by the CPI-W, the 

wage earners’ version of the Consumer Price Index, 

one of three versions released monthly by the BLS. 

Any tendency for the GDP deflator to grow more 

slowly than the CPI-W affects the future actuarial 

balance of the system by pushing up benefits relative to the gains in system income made possible by 

productivity gains.

Six price indexes are relevant to a consideration 

of the future evolution of the differential growth in 

the GDP deflator and the CPI-W. The first two are the 

deflators for total GDP and for Personal Consumption Expenditures (PCE), both published quarterly 

by the Bureau of Economic Analysis (BEA). These 

differ only in coverage; the GDP deflator covers 

all of current production, whereas the PCE deflator covers only the two-thirds of GDP consisting of 

personal consumption expenditures, thus excluding equipment and structures investment, as well 

as government spending and net exports.

The other four indexes are different versions of 

the CPI. The CPI-U reflects the price experience derived from the spending patterns experienced by 

all households in the U.S. except those households 

residing in rural areas, in the armed forces, or in institutions. The CPI-W applies to a subset of the CPIU population: those households with a full-time 

employee, the majority of whose income is derived 

from wage-earner or clerical-worker occupations. 

The same methodology is employed in the CPI-U 

and CPI-W, and the samples of areas, retail outlets, 

and prices are identical. The only difference in their 

construction is the expenditure weights used to aggregate the prices. Social Security benefit cost of 

living adjustments are indexed to the CPI-W, the 

only CPI definition available when benefits were 

indexed by legislation, in 1972. The GDP and PCE 

deflators are often revised back into history to reflect new data and methodological improvements. 

But because they are used in many legal contracts, 

the CPI-U and the CPI-W are never revised.

While the CPI-U and CPI-W are never changed 

after publication, the BLS also publishes two alternative versions of the CPI-U that reflect methodological changes over time. The CPI-U-RS (“research 

series”) is available back to 1978 and incorporates 

numerous methodological improvements made to 

the CPI during the last 30 years. The CPI-U-X1 is 

another version of the CPI-U. It is useful in assessing CPI inflation in years before 1978.

Table 7 displays growth rates for all six of these 

price indexes—the GDP and PCE deflators, the 

CPI-U and CPI-W, the CPI-U-RS linked at 1978 to 

Table 7: Major U.S. Price Indexes, Annualized Growth Rates, 1967-2006

GDP Deflator PCE Deflator CPI-U CPI-W CPI-U-RS/X1 Implied CPI-W-RS

2003-2006 3.04 2.75 3.04 3.06 3.06 3.08

2000-2003 2.07 1.82 2.21 2.08 2.19 2.07

1997-2000 1.56 1.67 2.35 2.31 2.25 2.21

1992-1997 1.99 2.06 2.69 2.63 2.34 2.28

1987-1992 3.31 3.81 4.22 4.11 3.74 3.64

1982-1987 3.09 3.40 3.26 2.99 3.34 3.06

1977-1982 7.67 7.86 9.30 9.29 8.24 8.23

1972-1977 6.97 6.96 7.43 7.38 7.06 7.02

1967-1972 4.66 4.10 4.49 4.51 4.03 4.05
72 2007 Technical Panel on Assumptions and Methods

the CPI-U-X1, and our calculation of the CPI-W-RS. 

The annualized growth rate of all six indexes is displayed for five year intervals spanning 1967-97 and 

over three year intervals between 1997 and 2006. 

To highlight the differences in the growth rates 

of the various price indexes, Table 8 displays key 

growth rate comparisons, allowing positive and 

negative differences among the price indexes to be 

easily identified. In most periods the GDP deflator 

grows more slowly than the PCE deflator, but in the 

two most recent periods (2000-2003 and 2003-06) 

and in the first two periods (1967-72 and 1972-77) 

the GDP deflator grew more rapidly than the PCE 

deflator. There is no “iron law” that the GDP deflator must grow more slowly than the PCE deflator.

In all periods shown (except for 1982-87) the 

rate of inflation in the PCE deflator is substantially 

slower than in the CPI-U. This is the major reason 

for the historical differential between the growth 

rate of the GDP deflator and the CPI-W. A small offsetting contribution is made by the fact that in all 

periods but the first and last, the growth rate of the 

CPI-W is modestly slower than the CPI-U.

The fourth column in Table 8 displays the differential growth rates between the CPI-W (used 

for Social Security indexation) and the implied 

constant-methodology CPI-W-RS. This difference 

is negligible in the two most recent periods, reflecting methodological improvements that have been 

applied equally to the CPI-U and CPI-W. The differential growth rate was particularly large in 1977- 

1982, when the pre-1983 CPI methodology for the 

measurement of housing prices had its greatest impact in overstating inflation.

The critical differential is in the fifth column of 

Table 8, namely the differential between the GDP 

deflator and the CPI-W-RS that incorporates current measurement methodology. Quite remarkably, this difference has been close to zero during 

2000-03 and 2003-06. In contrast, the difference 

over the pre-2000 period back to 1967 is an average 

annual growth rate of -0.15 percent per year. Even 

excluding the past six years, it is notable that the 

annual growth rate of -0.15 is much slower than the 

Trustees’ assumed rate of -0.4 percent per year.

The most important issue in projecting this differential forward is that methodological improvements in the CPI have not eliminated the differential growth rate of the PCE deflator and the CPI-U. 

The past provides some guidance for the Trustees. 

Historical perspective is provided by Table 9, which 

restates the differences in Table 8 over alternative 

historical horizons of 10, 20, 30, and 39 years.

Again, the fifth column is the most important. It 

displays the differential growth rate of the GDP deflator and constant-methodology CPI-W-RS. Over 

Table 8: Differences between Price Indexes, Annualized Growth rates, 1967-2006

GDPD-PCED PCED-CPIU CPIU-CPIW CPIW-CPIW/RS GDPD-CPIW/RS

2003-2006 0.29 -0.30 -0.02 -0.02 -0.04

2000-2003 0.25 -0.39 0.12 0.02 0.00

1997-2000 -0.10 -0.68 0.04 0.10 -0.65

1992-1997 -0.07 -0.63 0.06 0.35 -0.29

1987-1992 -0.49 -0.41 0.11 0.48 -0.32

1982-1987 -0.31 0.14 0.28 -0.07 0.03

1977-1982 -0.19 -1.45 0.02 1.06 -0.56

1972-1977 0.01 -0.46 0.04 0.37 -0.04

1967-1972 0.56 -0.38 -0.02 0.46 0.61

Table 9:Differences between Price Indexes over Alternative Horizons, 1967-2006

GDPD-PCED PCED-CPIU CPIU-CPIW CPIW-CPIW/RS GDPD-CPIW/RS

1996-2006 0.13 -0.47 0.05 0.04 -0.25

1986-2006 -0.11 -0.48 0.07 0.23 -0.28

1976-2006 -0.14 -0.53 0.09 0.32 -0.26

1967-2006 -0.03 -0.52 0.07 0.35 -0.13
2007 Technical Panel on Assumptions and Methods 73

the past ten years, this differential of -0.25 points 

has been well below the Trustees’ assumption of -0.4, 

and over longer horizons the differential has been 

equivalent or smaller. The most important source of 

the differential is the differential growth of the PCE 

deflator and the CPI-U, which in turn is mainly due to 

the difference between the fixed weights used in the 

CPI and the chain weights used for the PCE deflator.

Just looking at the history in Table 9, it is clear 

that there is no historical precedent for the 2007 

Trustees’ assumption of a -0.4 percent per annum 

growth rate in the GDP deflator vs. CPI-W differential. Detailed analysis of the data provides further reasoning that the differential growth rate 

should be smaller. 

Referring back to the first column of Table 8, 

concerning the GDP deflator vs. the PCE deflator, there is no reason to expect that any particular sub-period would be most relevant for the 75 

year forecast horizon. The average growth rate 

over 1967-2006 is -.03 percent per year, and we 

suggest that the best forecast for this differential 

growth rate is zero.

For the PCED vs. CPI-U differential, much of 

history is based on now outmoded CPI methodology. The average of 2003-06 is most relevant, 

-0.30 percent per year. For the CPI-U vs. CPI-W 

differential, the 1967-2006 average is +0.07, and 

there is no reason why this quite stable growth 

rate should change in the future. Methodology 

improvements in the CPI-W vs. CPI-W-RS growth 

rates are irrelevant for the future since the CPI 

has now adopted all the techniques used in the 

research series CPI-W-RS.

Summing up the components of the GDP deflator to CPI-W-RS differential relevant for the next 

75 years comes out to -0.23. Assuming that the 

BLS will adopt further methodological improvements in the CPI at various stages over the next 75 

years, the Panel’s recommendation of -0.2 may still 

overstate the differential.

Summary of Real Wage Growth

Assumption Recommendation A-14: Together, Assumptions A-8 through A-12 result in a rate of real 

wage growth in the intermediate assumptions of 

1.3 percent per year, slightly higher than the 1.1 

percent assumed in the 2007 Trustees Report.

The recommendations also result in recommended low-cost wage growth of 1.8 percent and highcost wage growth of 0.8 percent, in both cases 0.2 

percentage point higher than the 2007 Trustees’ 

assumptions.

Note that our projected -0.1 percent annual 

growth rate of the earnings/compensation ratio 

and hours/employee ratio persists only for the first 

25 years of the projections and are zero thereafter. 

Thus our real wage growth rate for 2032 to 2082 is 

1.5 percent a year, a substantially faster rate than 

the 1.1 percent rate in the 2007 Trustees Report.

D. CPI growth rate

Assumption Recommendation A-15: The Panel recommends that the assumed rate of increase in the 

Consumer Price Index be reduced by 0.3 percentage point in the intermediate assumption, from 2.8 

percent to 2.5 percent per year. The assumption of 

the future inflation rate in the GDP deflator should 

be reduced from the current 2.4 percent assumption to 2.3 percent, corresponding to our previous 

recommendation that the GDP deflator to CPI differential be reduced from -0.4 percent to -0.2 percent per year.

Social Security is indexed to inflation, so the effect of unexpected changes in future inflation on 

system finances is muted. However, due to timing 

effects, in that faster inflation will increase the 

growth in the taxable wage base prior to its effect 

on benefits, some sensitivity remains. 

As reviewed in the previous section, the concept 

of inflation used to index Social Security benefits 

tends to rise faster than the GDP deflator, which 

is relevant to the measurement of productivity. 

2007 Technical Panel Growth Rate 

Recommendations

Real Wage Growth = (Year 0-25) 1.3 pct/yr

(Year 26-75) 1.5 pct/yr

+ Growth in 1.7 pct/yr

labor productivity 1.7 pct/yr

+ Growth in 0.0 pct/yr

[labor compensation/GDP] 0.0 pct/yr

+ Growth in -0.1 pct/yr

[earnings/labor compensation] 0.0 pct/yr

+ Growth in -0.1 pct/yr

[total hours/employment] 0.0 pct/yr

+ Growth in -0.2 pct/yr

[GDP deflator/CPI] -0.2 pct/yr
74 2007 Technical Panel on Assumptions and Methods

Figure 29 displays the difference between the two 

inflation measures and points to particular periods 

when the difference was very large (notably the period 1978-82) and other periods when the difference was very small (2002-06).

 Our consideration of the future behavior of inflation profits from an enormous literature on the U. S. 

inflation process. For 25 years a consensus model has 

performed well in explaining the historical behavior 

of U. S. inflation—why inflation accelerated in the 

late 1960s and late 1980s, why inflation was so high 

in the 1970s and so low in the late 1990s, why inflation and unemployment moved in opposite directions in the late 1960s and late 1980s but in the same 

direction in the 1970s and late 1990s.

The consensus or mainstream model of the inflation process can be written as: 

Inflation today = Inherited Inflation + Demand Effect 

+ Supply Effect

Because this model of inflation has three driving forces—inertia, demand and supply, it has frequently been called the “triangle” model.113

The role of “inherited inflation” is fundamental. If 

there are no pressures pushing up or down on current inflation from demand or supply factors, then 

inflation will continue at the rate inherited from the 

113 Dew-Becker, Ian and Robert J. Gordon, “Where Did the Productivity Growth Go? Inflation Dynamics and the Distribution 

of Income,” Brookings Papers on Economic Activity, no. 2, 2005, pp. 

67-127.

past. However, inflation can be jarred away from this 

inherited rate by shocks to the demand or supply 

sides of the economy. The classic demand-induced 

inflation in the U.S. occurred during 1965-1970, 

when a combination of Vietnam War government 

spending, sharp cuts in income tax rates, and a generally ebullient atmosphere for spending on consumer durables and business investment pushed 

the unemployment rate down from 5.5 percent in 

1963 to roughly 3.5 percent during 1966-1969.

The demand effect can be represented as the “gap” 

between the actual unemployment rate and a hypothetical “natural unemployment rate” that is consistent with steady inflation.114 For instance, from 

the perspective of 45 years of data (1962-2007), we 

can estimate that in the late 1960s an unemployment rate of 5.5 percent would have been necessary 

to avoid an acceleration of inflation. The actual observed 1966-1969 unemployment rate of 3.5 percent 

implied an acceleration of inflation of roughly 1 percentage point per year; and inflation accelerated from 

1 percent in the early 1960s to 5 percent in 1970. The 

rule of thumb is that inflation accelerates by 0.5 percent for each percentage point gap between actual 

and natural unemployment. This rule of thumb was 

first noticed in the 1960s and is validated forty years 

114 The “natural unemployment rate” in the contemporary literature 

is more often labeled as the “NAIRU,” the Non-Accelerating Inflation Rate of Unemployment.

Figure 29: Eight Quarter Inflation Rate for GDP Deflator and CPI-W, 1955-2007

-2.0

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005

Year

Inflation rate

CPI-W inflation

GDP Deflator inflation

Ination rate

Figure 29: Eight Quarter Inflation Rate for GDP Deflator and CPI-W, 1955-2007
2007 Technical Panel on Assumptions and Methods 75

later in the latest academic estimates of the inflation 

process. Likewise, a positive gap—with unemployment above the natural rate—will cause inflation to 

decelerate. This is validated by the disinflationary periods of 1981-1986, 1990-1993, and 2000-2003.

Inflation remains at the rate of inherited inflation 

if the demand effect is zero, that is, if the unemployment gap is zero. When unemployment is low 

and the gap is negative, inflation accelerates, as in 

1966-1969 and 1987-1989. When unemployment 

is high and the gap is positive, inflation decelerates, 

as in 1981-1986, 1990-1993, and 2000-2003.

But inflation and unemployment have not always 

been negatively correlated. The U.S. experienced 

“twin peaks” of high unemployment and inflation 

in 1974-1976 and 1979-1981, and a “valley” of low 

unemployment and inflation in 1997-1999. Theories developed at the time of the first 1974-1975 oil 

shock, and subsequent empirical work, have validated the role of supply shocks (the “supply effect” 

in the above equation) as an additional factor that 

can cause inflation to accelerate or decelerate, sometimes quite rapidly.

These theories reflect two realistic aspects of any 

economy, which can usefully be imagined as divided into energy and non-energy sectors. The first aspect is that price and wage behavior in the non-energy sector is very “sticky,” or slow to adjust, which 

makes inflation adhere to inherited inflation when 

there are no demand or supply effects. Second, sudden quantum jumps to prices have occurred for crucial products, e.g., farm products and oil, for which 

the demand is highly price inelastic.

The combined effect of these two aspects is 

that when oil prices jump by a factor of four, as in 

1974-1975, the economy cannot cut back its spending on oil to any significant degree. It is stuck with 

its gas-guzzling automobiles, its aging fleet of jet 

planes, and its poorly-insulated houses and apartments. This decreases the income available to purchase non-energy goods and services, and real spending in the non-energy sector declines. In 1974-1975 

and 1979-1981 it declined by a lot. “Inflation Creates 

Recession,” in the words of a 1975 New York Times

article—and this mantra has been subsequently ratified by theory, econometric estimation, and is now 

incorporated in all macroeconomic textbooks. 

This model of inflation and unemployment behavior greatly simplifies the Trustees’ task of projecting 

the future inflation rate. Over long periods of time, 

the supply shocks are likely to average out to zero. 

Over long periods of time, the demand unemployment gap is likely to average out to zero. This means 

that future inflation will equal inherited inflation.

We can simulate the mainstream model, based on 

estimated parameters for the period 1962- 2006, assuming in the future no supply shocks and an actual 

unemployment rate equal to the natural rate of unemployment (perhaps 5.5 percent) by early 2005.115

This yields a future inflation rate in the GDP deflator of 2.3 percent. Since, in another section of our 

report, we project a differential between the GDP 

deflator and the CPI-W of -0.2 percent, this implies 

future growth in the CPI-W of 2.5 percent.

Some of the critical actuarial variables may be best 

modeled as an average over the past 20 or 30 years, 

but the inflation rate is decidedly not among that 

set of variables. Inflation earlier than six years ago 

is simply irrelevant for any projection of future inflation, including the 5 percent inflation rate registered 

in 1970 or the 10 percent registered in 1980. Unless 

a specific reason is suggested to support a positive 

demand or supply effect on average over the next 75 

years, then the best projection of CPI inflation for 

the future is not 2.8 percent, but rather that implied 

by the inflation inherited from a weighted average of 

the actual experience of the past six years, and this 

turns out to be roughly 2.5 percent.

Thus, the Panel recommends an intermediate projection of 2.5 percent per year. Although the Panel 

recommends low and high cost rates of 1.5 and 

3.5, respectively, we note there is a possibility that 

improved monetary policy will reduce the volatility of inflation in the future, which would indicate 

narrowing those bands over time. (Note that lower 

inflation results in a larger actuarial deficit, due to 

the time lag between the effects of CPI changes on 

taxable payroll and on benefit payments. Lower inflation has an immediate effect on nominal wages, 

and thus on revenues, while the reduction in benefits due to a smaller cost of living adjustment is 

experienced only after about a year. Thus, the lower 

taxable payrolls have a stronger effect than the lower benefits, thereby resulting in higher cost rates.)

E. Interest rates

Assumption Recommendation A-16: The Panel recommends using a long-term nominal rate of 5.17 

percent, based on a real rate of 2.6 percent and a 

115 The simulations are based on updated versions of the estimated 

equations in Dew-Becker and Gordon, 2005, op. cit.
76 2007 Technical Panel on Assumptions and Methods

CPI inflation rate of 2.5 percent. The corresponding 

real and nominal rates for the high cost scenario 

should be shifted down to 1.8 percent and 5.36 percent respectively. For the low cost scenario, we recommend lowering the real rate to 3.3 percent, and 

the nominal rate to 4.85 percent. These changes are 

based on a uniform reduction in the CPI inflation 

rate of .30 percent in all scenarios.

Method Recommendation M-20: The Panel recommends that the Trustees modify their approach 

to determining real and nominal interest rates to 

place more weight on the forward-looking information in recent Treasury yield curves. 

Method Recommendation M-21: For calculations 

involving discounting such as the actuarial balance, 

the Panel recommends that the Trustees consider 

using risk-adjusted rates instead of a risk-free real 

interest rate. 

Overview

Interest rates influence the time path of trust fund 

balances, and the overall actuarial balance, through 

their effect on expected returns on trust fund securities116 and on the discount rate. It is the real interest rate that has the greatest effect, but both real 

and nominal interest rates affect the projections.

As for other quantities, the Trustees tend to make 

relatively small changes in projected interest rates 

from year to year, a practice that sometimes causes 

assumed rates to deviate significantly from those 

suggested by either market yields or by professional forecasters. At present, the Trustees assumed interest rates, both real and nominal, are much above 

the consensus view, and the Panel recommends reducing the assumed rates to levels more in line with 

the consensus estimates. 

More fundamentally, the Panel recommends that 

the Trustees modify their approach to determining 

interest rates by placing more weight on the information in recent Treasury yield curves. It is notable that 

interest rates are the only variable where the Trustees can draw on information from a large, active, and 

forward-looking market where the stakes for participants are high. Suitably adjusted for the term premium and transitory market conditions, the yield curve 

generally provides the best available forecast of future 

116 Trust fund returns are based on special issue Treasury bonds. 

Since October 1960, the formula for the rate on new special issues 

has been the average market yield on all marketable government 

obligations that are not due or callable for at least 4 years from the 

date of determination. These securities can be redeemed at par at 

any time. 

interest rates.117 While this does not cover the entire 

75 years of the forecast, the information could at least 

be incorporated into the medium run out to 20 or 30 

years. At present, the “long-run” rate assumptions are 

completely phased in within 6 or 7 years.

The idea that long-run Treasury yields contain 

the best available information about expectations 

of future Treasury rates is known as the “expectations hypothesis.” It posits that investors seeking 

profit-making opportunities tend to push longrun rates to levels consistent with their expectation of future rates. Imagine, for instance, that 

the 2-year Treasury yield is 5 percent, and that 

the current 1-year Treasury yield is 4.5 percent. 

If investors expected 1-year rates to be less than 

5.5 percent next year, they would expect to profit 

from buying a 2-year bond financed by selling a 

1-year T- bond. If the rates were expected to be 

higher, they would be better off investing in the 

1-year bond financed by selling a 2-year bond of 

equal value. Thus the forces of supply and demand tend to move long-term interest rates in 

line with expected future rates. The fact that rate 

projections by professional forecasters tend to be 

consistent with the expectations hypothesis demonstrates the wide acceptance of this idea. 

Theoretically, the expectations hypothesis does 

not hold exactly if investors are risk averse, and 

the evidence suggests that in fact the relationship is systematically violated. Deviations, however, occur in a predictable direction that can be 

adjusted for. Specifically, long-term interest rates 

contain a “term premium” or “risk premium” that 

makes future short-term rates systematically 

lower than those implied by the expectations 

hypothesis. Thus, in using the term structure to 

forecast future rates, it is standard to rely on the 

“modified expectations hypothesis” that incorporates an adjustment for the term premium, as 

well as for any identifiably transitory market conditions.

An alternative approach to forecasting interest rates draws inferences from historical averages. Although it is useful to consider this data, 

a backward-looking approach to forecasting rates 

is confounded by several problems that are elaborated on below. Since historical data informs the 

forward-looking projections implied by the yield 

117 Buser, Stephen A., Karolyi, George Andrew and Sanders, Anthony B., “Adjusted Forward Rates as Predictors of Future Spot Rates,” 

Dice Center Working Paper Series 96-5, 1996. Available at SSRN: 

http://ssrn.com/abstract=40165 or DOI: 10.2139/ssrn.40165
2007 Technical Panel on Assumptions and Methods 77

curve, relying primarily on those measures is consistent with learning from the past.

Inferring Real Interest Rates

By definition, the nominal interest rate is the real 

rate compounded with expected CPI inflation. Before 

1997 the Treasury issued only nominal securities, 

hence historical real interest rates have to be inferred 

from observed nominal interest rates and inflation. 

Inflation complicates inferences about real rates for 

several reasons: Realized inflation can deviate widely 

from expected inflation; and past inflation may be a 

poor proxy for future inflation. More recent data from 

the Treasury Inflation-Protected Securities (TIPS) 

market avoids the complications associated with inflation, but also must be interpreted with caution due 

to other differences between the two markets. 

Episodes of high and variable inflation (or deflation) can cause real bond returns to differ significantly from what investors’ initially expect. Examples of such surprises include the spikes in inflation 

in the mid-1970’s and early 1980s that resulted in 

negative real bond returns, and the sharp deflation 

in the early 1920s that caused realized real rates to 

skyrocket. More subtly, the unexpectedly rapid return to low inflation in the late 1980s may have increased realized real returns during that period and 

into the 1990s. 

Inflation surprises make it difficult to infer historical expectations about real interest rates from 

historical nominal data. A simple averaging of ex 

post realized real rates from 1870 to 2004 implies 

an average rate just under 3 percent.118 However, 

because large inflation surprises are rare even over 

this long period, they may not average out to zero. 

We conclude that there is considerable uncertainty 

about whether the long-run average accurately reflects historical expectations of real returns. Inflation also complicates inferences about real rates because inflation over the next 75 years may behave 

quite differently than in the past. In recent years, 

inflation in the U.S. (see Figure 30) and other developed economies has been stabilized at low rates, 

and most economists believe that central banks 

have the knowledge and determination to maintain 

low inflation. This has several implications for longterm interest rate projections. Reduced inflation 

risk decreases the volatility of nominal rates going 

forward. It should also lower the inflation risk premium, and hence the level of required real returns. 

More recently, the introduction of TIPS has provided policymakers with a more direct measure of 

real Treasury interest rates. Drawing inferences 

from this market is complicated by its being relatively new, small, and far less liquid than the 

market for nominal Treasury obligations.119 Dur118 Girola, James, “The Long-Term Real Interest Rate for Social 

Security,” Research Paper No. 2005-02, U.S. Dept. of Treasury, 

March 30, 2005.

119 Since the returns on the special issue securities in the trust fund 

are linked to those on nominal Treasury’s, these discrepancies 

Figure 30: Historical Annual Inflation Rates, 1970-2007

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006

Year

Year over year percent change

CPI-U: All Items, 1982-84=100

CPI-U: All Items Less Food and Energy, 1982-84=100

Source: Federal Reserve Bank of Cleveland; Bureau of Labor Statistics

Year over year percent change

Figure 30: Historical Annual Inflation Rates, 1970-2007

Source: Federal Reserve Bank of Cleveland; Bureau of Labor Statistics
78 2007 Technical Panel on Assumptions and Methods

ing its first four years in operation, real returns 

on TIPS were in the 3.5 to 4 percent range, much 

higher than the real return reasonably expected 

on nominal Treasury securities of comparable 

maturity. Most observers attributed these high 

yields to the market’s newness and illiquidity, and 

did not rely on it to make inferences. In recent 

years, TIPS yields have been more consistent with 

nominal Treasury yields and other sources measuring inflation expectations. Indeed, the Fed 

now routinely uses TIPS data in their Monetary 

Report to the Congress. Nevertheless, differences 

between the TIPS and nominal Treasury market 

persist, and some caution is warranted in interpreting the rates.120

Rate Recommendations

Consistent with our methodological advice, we 

focus primarily on recent Treasury yield curve data 

and consensus inflation forecasts to evaluate the 

Trustees’ projections of real and nominal interest 

rates.121 Although rates in recent years were lower 

than in the past, as discussed earlier, we believe that 

the market correctly discounts the likelihood of a 

recurrence of high and variable inflation.

The first point of comparison is the direct evidence 

from the TIPS market. Table 10 reports statistics on 

daily TIPS yields from January 2003 to February 

2007. Over this period, the average 10-year real rate 

was 2.02 percent and the average 20-year rate was 

might matter.

120 Some have argued that the TIPS rate is likely below the real rate 

on nominal Treasury’s because rates do not include an inflation 

risk premium. An effect in the opposite direction, however, is that 

they may command a liquidity premium on TIPS. As neither effect 

is possible to quantify, it is not obvious in which direction a bias is 

more likely.

121 Because the yield curve is fairly flat in the 10- to 30-year range, 

we use the level of rates as a close proxy for implied forward rates 

of the relevant maturities.

2.15 percent. Although TIPS yields have increased 

somewhat since then, the 2.9 percent real rate assumed by the Trustees is well above the maximum 

rate of 2.68 percent realized over this period.122

The Trustees set projected nominal rates to be 

consistent with their real interest rate and inflation assumptions. The result is a nominal rate in 

the intermediate case that is inconsistent with 

the nominal Treasury yield curve. Since 2003, the 

long end of the nominal Treasury yield curve has 

on average hovered around 5 percent, whereas 

the Trustees assume a long-term nominal rate in 

the intermediate case of 5.7 percent.123 Part of 

the discrepancy is attributable to the assumption 

of high real rates. However, the Trustees’ assumption of 2.8 percent long-term CPI inflation also 

exceeds the medium term consensus view, and 

contributes to the discrepancy with market data. 

A recent survey of 49 professional forecasters reports a median inflation estimate of 2.35 percent 

over the next 10 years (longer forecasts do not 

seem to be available); the Trustees’ estimate over 

the next 10 years is 20 basis points above the upper quartile of those estimates.124

By taking a stand on real interest rates, inflation 

expectations can be inferred from long-term nominal 

Treasury yields. A long-term nominal rate of 5 percent 

combined with the Trustees’ assumption of a 2.9 percent real rate implies expected inflation of just over 2 

percent. This is clearly inconsistent with the 2.8 percent inflation rate assumed in the intermediate case, 

and also low compared to available forecasts. 

More broadly, the historically low level of longterm yields in the U.S. and abroad suggests that 

investors expect inflation to remain moderate. 

For instance, subtracting the current 30-year TIPS 

yield of 2.5 percent from the nominal 30-year bond 

rate of 5 percent implies expected inflation of 2.5 

percent, an estimate that is in line with other forecasts. Interest rates in Europe and Asia are also low 

by historical standards, reflecting a benign inflation outlook worldwide. The Trustees appear to put 

greater weight on the past than do markets. Their 

Report mentions that the CPI estimate reflects the 

possibility of the recurrence of the highly inflation122 Even with the recent concerns about credit risk and disruptions in the credit markets, recent TIPS yields remain around 2.5 

percent.

123 The divergence from market rates is even larger in the short-run 

with rates of 5.8 percent to 5.9 percent projected between 2009 

and 2013.

124 Federal Reserve Bank of Philadelphia, Survey of Professional 

Forecasters, February 2007.

Table 10: Implied Real Yield Curve

5 year 7 year 10 year 20 year

Average 1.56% 1.80% 2.02% 2.15%

Average since 

01/07 2.41% 2.43% 2.40% 2.40%

Std. Dev. 0.55% 0.40% 0.28% 0.22%

Min. 0.39% 0.87% 1.36% 1.69%

Max. 2.65% 2.64% 2.68% 2.68%

* 20-year data begins 7/2004
2007 Technical Panel on Assumptions and Methods 79

ary periods in the 1960s and 1970s, and discusses 

the forecast relative to a 40-year look-back period.

Based on these observations, the Panel’s recommendation in the intermediate case is to set the 

long-term nominal rate to 5.17 percent, based on 

a real rate of 2.6 percent, and a CPI inflation rate 

of 2.5 percent. The corresponding real and nominal 

rates for the high cost scenario should be shifted 

down by corresponding amounts: We recommend 

a real rate in the high cost scenario of 1.8 percent, 

and a nominal rate of 5.36 percent. For the low cost 

case these numbers are 3.3 percent and 4.85 percent respectively. The nominal rate recommendations are consistent with those for real rates, and 

with CPI inflation rates 0.3 percent lower than currently assumed.

Implications for Trust Fund Balances

By 2041 trust fund balance are projected to decline to zero. This means that interest rates beyond 

the 30 years spanned by the Treasury yield curve 

do not affect investment returns beyond that horizon. Balance estimates along the way, however, are 

quite sensitive to the assumed real rates of return 

between now and the early 2030s. Our calculations 

show that lowering the real interest rate by 0.3 percent as we recommend, and setting all other cash 

flows to match those in the 2007 Trustees Report 

intermediate scenario, lowers the projected trust 

fund balance in 2035 by almost $640 billion. 

Discounting and the Actuarial Balance

The actuarial balance is the present value of income plus current trust fund balances, minus the 

present value of benefits, expressed as a percentage of the present value of taxable payroll over the 

same period. It is sometimes interpreted as the 

amount payroll tax rates would have to be raised 

today, or the amount the benefit rate would have to 

be lowered, to bring the system into actuarial balance over a given period. Under the assumptions 

of the 2007 Trustees Report the 75-year balance 

stood at -1.95 percent of taxable payroll in 2007. 

The choice of real interest rates has a dramatic effect on the actuarial balance, with a lower rate leading to a higher present value cost or a more negative 

balance. For instance, the sensitivity analysis in the 

Trustees Report indicates that lowering the real interest rate from 2.9 percent to 2.1 percent worsens 

the actuarial balance by 0.52 percent. The effect of 

the real rate on the actuarial balance increases with 

the time horizon considered, since the growing divergence between projected income and cost rates is 

amplified by the use of a low discount rate. Periods of 

relatively low interest rates therefore have the unfortunate side effect of putting considerable weight on 

distant and therefore highly uncertain estimates.

Fortuitously then, there is theoretical justification for using a higher rate than that on special 

issue Treasury securities to calculate the actuarial 

balance. A general rule in computing present values 

(albeit one that is often ignored in federal financial 

calculations), is to use a discount rate that is “riskadjusted” to match the risk in the cash flows being 

discounted. For instance, a calculation of the present value of the expected returns on stocks is riskadjusted by discounting at a rate above the Treasury 

rate equal to the “equity risk premium.” The equity 

premium reflects the higher risk, and hence higher 

average return, required on stock market investments.125 The present value then has the interpretation of the dollar amount that would have to be 

invested today to buy financial claims to fully cover 

the projected cash flows. Social Security income and 

expenditures similarly have market risk. Payroll tax 

revenues, which are proportional to earnings, fluctuate with the aggregate economy. Social Security 

obligations also vary positively with aggregate earnings. The principal of discounting at a rate consistent with the aggregate risk in the underlying cash 

flows therefore implies adding a risk premium over 

Treasury rates in calculating the actuarial balance.

Recently several studies have begun to quantify the risk-adjustment appropriate for long-term 

wage-linked cash flows.126 Most directly relevant to 

the actuarial balance is the work of Geanakoplos 

and Zeldes, who estimate the value of Social Security liabilities taking into account their market 

risk. 127 The risk in Social Security liabilities arises 

125 A related use of the idea of risk-adjustment is used in projections 

of returns on private accounts. In that context, neutralizing the 

effect of the risk premium involves subtracting the risk premium 

from the expected return on Treasury securities when projecting 

future cash flows. In either case, risk adjustment has the effect of 

treating the higher expected return on stocks as compensation for 

risk rather than as a costless gain from risk-taking. 

126 Benzoni, Luca, Pierre Collin-Dufresne, and Robert Goldstein 

“Portfolio Choice over the Life Cycle when the Stock and Labor 

Markets are Cointegrated,” Journal of Finance (forthcoming); and 

Lucas, Deborah and Stephen Zeldes “Valuing and Hedging Defined 

Benefit Pension Obligations – The Role of Stocks Revisited,” manuscript Northwestern University, 2007.

127 Geanakoplos, John and Stephen P. Zeldes, “The Market Value of 

Accrued Social Security Benefits,” mimeo, Conference on Measuring and Managing Federal Financial Risk, Kellogg School of Management, Northwestern University, February 8-9, 2007.
80 2007 Technical Panel on Assumptions and Methods

from the indexing of benefits to aggregate wage 

growth: liabilities will be higher if the economy on 

average does well over the next 75 years than if it 

does poorly. This systematic risk implies that the 

theoretically correct rate is higher than the riskfree Treasury rate. Geanakoplos and Zeldes estimate that risk-adjusting the discount rate appropriately lowers the present value of liabilities to 73 

percent of the present value calculated at Treasury 

rates. Payroll tax revenues, which also are tied to 

aggregate economic performance, require similar 

risk adjustment.

The Panel recommends that the Trustees consider adopting risk-adjusted discount rates for computations that involve discounting. As well as making 

the measures more accurate theoretically, the use 

of higher discount weights has the salutary effect of 

reducing the sensitivity of the results to the more 

distant, and more uncertain, cash flows. 

Equity Risk Premium

Assumption Recommendation A-17: The Panel concurs with the choice of equity premium assumed in 

recent analyses by the Office of the Chief Actuary of 

proposals involving stock market investments.

Method Recommendation M-22: In such analyses, 

the Panel recommends that the Office of the Chief 

Actuary portray risk-adjusted projections as a neutral risk-adjusted case, not as worst case for average returns.

The equity risk premium—the average return on 

stocks over the risk-free rate—has no effect on the 

analysis of system finances under current law. Periodically, however, the actuaries are asked to analyze the effect of legislative changes that include 

investments in the stock market.

Although past realizations of the equity premium 

are readily observable, there is some disagreement 

about the expected premium going forward. It was 

once common practice to identify the equity premium with the long-run historical spread between the 

average realized return on common stocks and the 

short-term T-bill rate, and some economists continue to endorse this approach, which implies a premium in the range of 7 to 8 percent. More recently, 

an increasing number of financial economists and 

market participants believe that the premium has 

fallen, perhaps permanently. Evidence that supports this view includes the sustained run-up in 

stock prices that has led to historically low average 

earnings-price ratios; and the likelihood that risk 

tolerance has increased with the increased stability 

of the macro economy and better financial risk diversification. Reflecting this sentiment, the Federal 

Reserve Bank of Philadelphia’s most recent Survey 

of Professional Forecasters showed a median prediction of the equity premium of 3 percent over 

T-bills, and only 2.5 percent over bond returns. A 

2001 survey of 510 finance and economics professors reports a consensus 30-year equity premium 

forecast of 5 to 5.5 percent.128 In recent analyses 

the actuaries have assumed a premium that falls between those estimated using these two approaches. 

The Panel is comfortable with this choice, although 

it may be necessary to revisit it as more evidence 

becomes available to determine whether the premium is at a permanently lower level. Fairly presenting the implications of the equity premium can be a 

greater challenge than estimating it. Investments in 

equities on average earn more than do safe bonds, 

and clearly system finances on average would be improved by such investments. It is generally agreed, 

however, that the higher average return is compensation for greater systematic risk, and that there is 

no free lunch in exchanging $1 of bonds for $1 of 

stocks, either for individuals or for the government. 

The problem with emphasizing average outcomes 

is that policies with stock market investments look 

like an arbitrage opportunity; they appear to make 

the system better off at no cost. In fact, with the 

inclusion of equities the standard method for computing the actuarial balance produces a windfall for 

the system. Consider investing $100 billion of trust 

fund assets in equities, expected to earn 10 percent 

per year forever. At a Treasury rate of 5 percent, the 

present value of the expected cash flows of $10 billion per year is $200 billion, twice the true value of 

the investment.

A representation of equity investments that avoids 

the appearance of arbitrage is to lower projected returns on equity by the amount of the equity premium. Conceptually, this is like assessing a charge on 

equity for the market risk it imposes on the system. 

Equivalently, the returns on equity can be projected 

forward to Treasury rates. This approach has been 

taken by CBO in reporting on reform proposals, 

and SSA to some extent has followed suit. For in128 Welch, Ivo, “The Equity Premium Consensus Forecast Revisited,” 

September 2001, Cowles Foundation Discussion Paper No. 1325. 

This is an estimate of the arithmetic premium over short-term 

T-bills.
2007 Technical Panel on Assumptions and Methods 81

stance, in the analysis of the Liebman-MacGuineasSamwick proposal, the Office of the Chief Actuary 

(OCACT) projects system finances both using the 

expected return on stocks, and assuming stocks 

earn only the Treasury rate. In interpreting the riskadjusted projections the actuaries say: 

“This may be viewed as either illustrating the case where the average real yield on 

equities and corporate bonds is no higher 

than on government bonds, or illustrating 

the effect of assuming risk-adjusted returns 

on equities and corporate bonds. In either 

case, the “expected” yield on annuitized assets is assumed to match the actual yield, 

on average. It should be noted that while 

average real yields for equities have been at 

or below average bond yields for periods of 

a decade or so, the likelihood of having such 

a low average yield for a period of several decades is fairly low.”129 [emphasis added]

While this acknowledges the interpretation that 

projecting at Treasury rates gives a risk-adjusted 

forecast, it also invites using the numbers as a 

worst case. This diminishes the conceptual value of 

presenting a risk-adjusted estimate. It is also not 

a natural worst case—returns could turn out to be 

far worse than a steady 3 percent. The Panel recommends that the actuaries portray risk-adjusted projections as being neutral, not worst case, in future 

analyses of this type. 

F. Taxable share of covered wages

Other Recommendation O-1: The Panel recommends that additional research be undertaken to 

develop a greater understanding of the implications for trust fund finances of trends in the dispersion of covered wages. That research should aim 

to provide a stronger basis for projecting the share 

of covered wages that fall above and below the taxable maximum. In addition, that research should 

examine the implications of stagnating wages at 

the lower end of the earnings distribution on the 

incentives to apply for disability benefits.

Other Recommendation O-2: The Panel recommends that the rationale in the Trustees Report for 

129 Estimated Financial Effects of “A Nonpartisan Approach to 

Reforming Social Security – A Proposal Developed by Jeffrey Liebman, Maya MacGuineas and Andrew Samwick,” memorandum from 

Stephen Goss and Alice Wade to the authors of the proposal, Office 

of the Chief Actuary, Social Security Administration, November 17, 

2005.

the projection of the share of covered wages that is 

taxable be made more explicit and should account 

for the substantial deviation of current trends from 

previous projections. The Panel recommends that 

the high and low cost projections of the share of covered wages that is taxable reflect a realistic degree of 

uncertainty. The long-range sensitivity analyses in 

the report should include the effect on summarized 

cost balances of the range of assumptions about the 

share of covered wages that is taxable.

Overview

Trends in the dispersion of income and wages 

have garnered increasing attention from economists. Over the past quarter century, the share of 

wage earnings going to a relatively small percentage of the highest earners has grown faster than 

earnings as a whole and considerably faster than 

the earnings of those at lower levels on the earnings distribution.130

By law, there is a maximum amount of each individual’s earnings subject to the OASDI payroll tax 

each year, referred to formally as the “contribution 

and benefit base” and informally as the “taxable maximum”. That threshold is set by law and since 1981 

has been indexed to the growth of the national average wage index. [The historical and projected AWI series as well as the “contribution and benefit base” are 

published in the Trustees Report in table V.C.1]. 

The “benefit and contribution base” or taxable 

maximum has grown from $35,700 in 1983 to 

$102,000 in 2008. The share of total covered wages 

that is subject to the payroll tax is sometimes called 

the “taxable ratio”. The share of total covered wages 

subject to the payroll tax has fallen from 90 percent 

in 1983 to 83 percent in 2007, a result of the unequal growth of earnings. 

Each year’s Trustees Report discusses the projection of the taxable ratio. Although the underlying 

factors that influence the trends in the distribution of earnings growth are economic and demographic phenomena, the “contribution and benefits 

base” and the method of indexing are set by law 

130 Autor, David H., Lawrence F. Katz and Melissa S. Kearney, “The 

Polarization of the U.S. Labor Market,” American Economic Review 

Papers and Proceedings,Vol. 96, May, 2006, pp. 189-94; Piketty, 

Thomas and Emmanuel Saez , “Income Inequality In The United 

States, 1913–1998*,” Quarterly Journal of Economics, February 

2003, Vol. 143, issue 1; Piketty, Thomas and Emmanuel Saez. 2006. 

“The Evolution of Top Incomes: A Historical and International 

Perspective,” American Economic Review Papers and Proceedings, Vol. 

96, no. 2, 2005; Gordon, Robert and Ian Dew-Becker, “Unresolved 

Issues in the Rise of American Inequality,” manuscript, 2007.
82 2007 Technical Panel on Assumptions and Methods

and, thus, are treated as program assumptions. The 

share of payroll subject to taxation is projected over 

a ten year horizon with high, low and intermediate 

cost variants. For long-range calculations the taxable ratio in the tenth year is assumed to hold for 

the remainder of the 75 year projection period.

Discussion

The Trustees Reports recent history of projecting the share of covered earnings below the taxable 

maximum is a cause for significant concern. Figure 

31 shows that the taxable ratio has fallen rather 

steadily, with some gyrations, since 1983 at the 

time of the last major Social Security Amendments. 

In every year since, the assumption [blue dotted 

lines] has been that the taxable ratio would stay 

about level (1984, 2000, 2007), or that it would fall 

slightly and then stay level for the remainder of the 

75 year projection (1992, 1997). In virtually every 

case, the actual data departed significantly from 

the projected trend after only a few years.

We also note that the range of the projections 

from the high-cost to low-cost have been unusually narrow, and suggest that the possibility of the 

taxable ratio falling more quickly than anticipated 

has consistently been underestimated. In 1984, the 

10-year low-cost projection was 91.9 percent and 

the high-cost was 91.4 percent. The 1996 projection 

was somewhat less certain with a range between 

87.9 percent for the low-cost and 85.6 percent in 

the high-cost variant. It should be noted that 10 

years after the projection, the high-cost scenario 

was exceeded in both cases. The 2007 Trustees Report contains a long-run taxable ratio assumption 

of 83 percent (roughly the 2007 actual level) with 

a low cost assumption of 83.8 percent, and a high 

cost projection of 82.2 percent. Given the inaccuracy of previous 10-year projections, this seems unrealistically narrow.

Accurate projection of the taxable ratio is important to accurate projections of the trust fund 

balances. If the taxable ratio continues to decline 

along the linear trend experienced from 1983 

through 2007, [dotted red line in Figure 31] for 30 

years and then stays level, with all other assumptions remaining at the Trustees’ 2007 intermediate 

values, the 75-year actuarial deficit would fall from 

the currently projected 1.95 percent of payroll to 

2.59 percent of payroll. This is as large an effect as 

assuming the total fertility rate falls to 1.5. 

Given that the historical projections over the past 

25 years have tended to underestimate the extent 

of the decline in the share of total earnings that 

are subject the payroll tax, the Panel believes the 

Trustees and actuaries should examine the basis 

for these projections. They need to understand better the forces that underlie the trends in wage dispersion, particularly the disproportionate growth 

at the very top of the distribution (approximately 

6 percent of those with covered earnings, have annual earnings that exceed the taxable maximum). 

In addition, subsequent Trustees Reports should 

include a more complete explanation of why the 

current projections truncate the historical pattern 

of decline. The 2007 Trustees Report provides two 

sentences of rationale for their current projection. 

The first is largely tautological: “This [1983-2005] 

decline was mainly due to a relative increase in 

wages for high wage earners.” The second suggests 

that some of the decline is due to changes in the 

age distribution as the baby boom has moved into 

ages of higher relative earnings. There is no reference to the growing literature of the causes of wage 

inequality, and no suggestion as to whether those 

causes are expected to continue or abate. To the 

extent that the forces underlying these trends are 

not well understood, this should be reflected in a 

wider range between the high and low cost scenarios. Further, the Panel believes such an important 

source of projection uncertainty should be dealt 

with explicitly in stochastic models as well as in the 

sensitivity analysis in the current reports.
2007 Technical Panel on Assumptions and Methods 83

Figure 31: Percent of covered earnings below taxable maximum: 10-year (ultimate value) projections 1984-2007 vs. historical 

values and 25-year projected trendline 

0.75

0.77

0.79

0.81

0.83

0.85

0.87

0.89

0.91

0.93

0.95

1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035

Percent of covered earnings

Historical values

Linear trend based on 1984-2007 data

1984 projection

1987 projection

1992 projection

1997 projection

2000 projection

2007 projection

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Percent of covered earnings

Figure 31: Percent of covered earnings below taxable maximum: 10-year (ultimate value) projections 

1984-2007 vs. historical values and 25-year projected trendline

2007 Technical Panel on Assumptions and Methods 85

Aaron, Henry, “The Unsurprising Surprise of Renewed Health Care Cost Inflation,” Health Affairs, 

January 23, 2002.

Abma, J.C. and G.M. Martinez, “Childlessness 

among Older Women in the United States: Trends 

and Profiles,” Journal of Marriage and Family, Vol. 

68, 2006, pp. 1045-1056.

Actuarial Standards Board, “Actuarial Standards of 

Practice No. 32: Social Insurance,” January 1998. 

(http://www.actuarialstandardsboard.org/pdf/

asops/asop032_062.pdf)

Ahmed, B. and G. Robinson, 1994, “Estimates of 

Emigration of the Foreign-Born Population: 

1980-1990,” Technical Working Paper No. 9, 

Population Division, U.S. Census Bureau, Washington, DC. December, 1994. (http://www.

census.gov/population/www/documentation/

twps0009/twps0009.html)

Autor, David and Mark Duggan, “The Growth in 

the Social Security Disability Rolls: A Fiscal Crisis Unfolding,” Journal of Economic Perspectives, 

Summer, 2006, pp.71-94. (http://www.econ.

umd.edu/~duggan/JEP-Disability.pdf)

Autor, David H., Lawrence F. Katz and Melissa S. 

Kearney, “The Polarization of the U.S. Labor Market,” American Economic Review Papers and Proceedings 96, May, 2006, pp. 189-94.

Basu, Susanto, John G. Fernald, Nicholas Oulton, 

and Sylaja Srinivasan, “The Case of the Missing 

Productivity Growth, or Does Information Technology Explain Why Productivity Accelerated in 

the United States But Not in the United Kingdom?” in NBER Macroeconomics Annual 2003, 

MIT Press, 2004. 

Bean, F.D., R.M. Cullen, E.H. Stephen, C. G. Swicegood, “Generational Differences in Fertility 

among Mexican Americans: Implications for Assessing the Effects of Immigration,” Social Science 

Quarterly, 65:573-82, 1984.

Bean F.D., C.G. Swicegood, and R. Berg, “Mexican-Origin Fertility: New Patterns and Interpretations,”

Social Science Quarterly, 81(1): 404-420, 2000.

Bell, Felicitie C., and Michael L. Miller, Life Tables for 

the United States Social Security Area 1900–2100, 

Actuarial Study No. 120, Social Security Administration, Publication No. 11-11536, 2005. 

Benzoni, Luca, Pierre Collin-Dufresne, and Robert 

Goldstein, “Portfolio Choice over the Life Cycle 

when the Stock and Labor Markets are Cointegrated,” Journal of Finance, (forthcoming).

Blackstone, Brian, “Is Productivity Growth Back in 

the Grips of Baumol’s Disease?” Wall Street Journal, August 13, 2007, p. A2.

Boldrin, M., M. De Nardi, and L.E. Jones, “Fertility and Social Security,” NBER Working Paper 

#11146, 2005. 

Bongaarts, John, “How Long Will We Live?” Population and Development Review, Vol. 32(4), 2006, pp. 

605–628.

Briggs Jr., Vernon M., Mass Immigration and the National Interest (2nd edition), Armonk, NY: M.E. 

Sharpe, 1996.

Brynjolfsson, Erik, Lorin M. Hitt, and Shinkyu 

Yang, “Intangible Assets: Computers and Organizational Capital,” Brookings Papers on Economic 

Activity, No. 1, 2002, pp. 137-81.

References 
86 2007 Technical Panel on Assumptions and Methods

Burkhauser, Richard V. and Mary C. Daly, “U.S. 

Disability Policy in a Changing Environment,” 

Journal of Economic Perspectives, Winter, 2002, 

pp.213-224.

Buser, Stephen A., George Andrew Karolyi, and Anthony B. Sanders, “Adjusted Forward Rates as Predictors of Future Spot Rates,” Dice Center Working Paper Series 96-5, 1996. (http://ssrn.com/

abstract=40165 or DOI: 10.2139/ssrn.40165)

Carnes, Bruce A. and Jay S. Olshansky, “A Realist View of Aging, Mortality, and Future Longevity,” Population and Development Review,

33(2):367–381, 2007. 

Cigno, A, and F.C. Rosati, “Jointly Determined Saving and Fertility Behavior: Theory and Estimates 

for Germany, Italy, and the U.S.,” European Economic Review, 40:1561-1589, 1996.

Centro Latinoamericano y Caribeño de Demografia 

(CELADE), “Estimaciones y Proyecciones de la 

Población, 1950–2050,” 2003. (http://www.eclac.

cl/celade/proyecciones/basedatos_BD.htm)

Congressional Budget Office, “Is Social Security 

Progressive?” Economic and Budget Issue Brief, 

December 12, 2006.

Congressional Budget Office, “Long-Term Analysis 

of the Liebman-MacGuineas-Samwick Social Security Proposal,” February 8, 2006.

Congressional Budget Office, Updated Long-Term 

Projections for Social Security, June 2006.

Congressional Research Service, Options to Address 

Social Security Solvency and Their Impact on Beneficiaries: Results from the Dynasim Microsimulation 

Model, Report RL33840, January 29, 2007.

Consejo Nacional de Población (CONAPO), “Proyecciones de la Población de México 2005-2050,” 2006. 

(http://www.conapo.gob.mx/00cifras/5.htm)

Cornelius, Wayne A. and Jessa M. Lewis (eds.), 

Impacts of Border Enforcement on Mexican Migration: The View from Sending Communities, Center 

for Comparative Immigration Studies, UCSD, 

La Jolla, CA, 2007. 

Dew-Becker, Ian and Robert J. Gordon, “Where Did 

the Productivity Growth Go? Inflation Dynamics 

and the Distribution of Income,” Brookings Papers 

on Economic Activity, no. 2, 2005, pp. 67-127.

Duggan, Mark and Scott Imberman, “Why are the 

DI Rolls Skyrocketing?” forthcoming in Health 

at Older Ages, edited by David Cutler and David Wise, University of Chicago Press, 2007. 

(http://www.nber.org/books_in_progress/disability/duggan-imberman7-18-07.pdf)

Edmonston, Barry and Jeffrey S. Passel, “The 

Future Immigrant Population of the United 

States,” in Edmonston and Passel (eds.), Immigration and Ethnicity: The Integration of America’s Newest Arrivals. The Urban Institute Press: 

Washington, D.C., 1994. 

Ehrlich, I and J. Kim, “Has Social Security Influenced Family Formation and Fertility in OECD 

Countries? An Economic and Econometric Analysis,” Journal of Pharmaceuticals Policy and Law, 

9:99-120, 2007. 

Federal Reserve Bank of Philadelphia, Survey of 

Professional Forecasters, February, 2007.

Fix, Michael and Jeffrey S. Passel, Immigration and 

Immigrants: Setting the Record Straight, The Urban 

Institute Press, Washington, D.C., 1994. (http://

www.urban.org/publications/305184.html)

Frank, R. and P. Hauveline, “A Crossover in Mexican 

and Mexican-American Fertility Rates: Evidence 

and Explanation s of an Emerging Paradox,” Demographic Research, Vol. 12, 2005, pp. 78-101.

Geanakoplos, John and Stephen P. Zeldes, “The 

Market Value of Accrued Social Security Benefits,” mimeo, Conference on Measuring and 

Managing Federal Financial Risk, Kellogg 

School of Management, Northwestern University, February 8-9, 2007.

Girola, James A., “The Long-Term Real Interest 

Rate for Social Security,” Research Paper No. 

2005-02, U.S. Department of Treasury, March 

30, 2005.
2007 Technical Panel on Assumptions and Methods 87

Goldman, Dana, Neeraj Sood, and Arleen Leibowitz, 

“The Reallocation of Compensation in Response 

to Health Insurance Premium Increases,” NBER 

Working Paper No. 9540, March 2003.

Gordon, Robert J., “Exploding Productivity Growth: 

Context, Causes, and Implications,” Brookings Papers on Economic Activity, 2003, no. 2, pp. 207-79.

Gordon, Robert and Ian Dew-Becker, “Unresolved 

Issues in the Rise of American Inequality,” manuscript, 2007.

Goss, Stephen and Alice Wade, “Estimated Financial Effects of A Nonpartisan Approach to Reforming Social Security – A Proposal Developed 

by Jeffrey Liebman, Maya MacGuineas and Andrew Samwick,” memorandum to the authors of 

the proposal, Office of the Chief Actuary, Social 

Security Administration, November 17, 2005. 

(http://www.ssa.gov/OACT/solvency/Liebman_20051117.pdf)

Government Accountability Office, Social Security 

Reform: Issues for Disability and Dependent Benefits, GAO-08-26, October 26, 2007.

Greenwood, J., A. Seshadri, and G. Vandenbroucke, 

“The Baby Boom and Baby Bust,” The American 

Economic Review 95(1): 183-207, 2005. 

Hacker, J. David, “Rethinking the ‘Early’ Decline of 

Marital Fertility in the United States,” Demography 40(4):605-620, 2004.

Haines, M. R, “Total Fertility Rate and Birth Rate, 

by Race and Age: 1800–1998”, in S. B. Carter, S.S. 

Gartner, M.R. Haines, A.L. Olmstead, R. S., and 

G. Wright, (eds.), Historical Statistics of the United States, Earliest Times to the Present: Millennial 

Edition, New York, Cambridge University Press, 

2006, Table Ab52-117.

Hanson, Gordon H., “Illegal Immigration from Mexico to the United States,” National Bureau of Economic Research Working Paper #12141, March, 

2006. (http://www.nber.org/papers/w12141)

Hamilton B.E., J.A. Martin, S.J. Ventura, Births: 

Preliminary Data for 2005. Health E-Stats, Released November 21, 2006.

Heyman, J., A. Earle, and J. Hayes, “The Work, Family, and Equity Index: How Does the U.S. Measure 

Up?” The Project on Global Working Families, Institute for Health and Social Policy, McGill University, Montreal CA.

Hoefer, Michael, Nancy Rytina, and Christopher 

Campbell, Estimates of the Unauthorized Immigrant 

Population Residing in the United States: January 

2006, Department of Homeland Security, Office 

of Immigration Statistics, Washington, D.C., September, 2007. (http://www.dhs.gov/xlibrary/assets/statistics/publications/ill_pe_2006.pdf)

Hollmann, Frederick W., Tammany J. Mulder, and 

Jeffrey E. Kallan, Methodology and Assumptions 

for the Population Projections of the United States: 

1999 to 2100. U.S. Census Bureau, Washington, 

D.C., January, 2000. (http://www.census.gov/

population/www/projections/natproj.html)

Howe, Neil and Richard Jackson, Projecting Immigration: A Survey of the Current State of Theory and 

Practice, Center for Strategic and International 

Studies: Washington, DC. April, 2005. (http://

www.csis.org/component/option,com_csis_

pubs/task,view/id,2528/)

Jackson, Richard, “Long-Term Immigration Projection Methods: Toward a Driver-based Model,” Presentation at ISIM Workshop, Center for Strategic 

and International Studies, September 26, 2006. 

Johnson, David. “Comparison of Movements in 

the CPI and PCE Price Indexes,” presented to the 

Federal Economic Statistics Advisory Committee, March 21, 2003.

Jorgenson, Dale W., Mun S. Ho, and Kevin J. Stiroh, 

Productivity: vol. 3: Information Technology and the 

American Growth Resurgence, MIT Press, 2005.

Keyfitz, Nathan, Applied Mathematical Demography, 

2nd Edition, New York: Springer-Verlag, 1985. 

Kohler, H-P, F.C. Billari, and J.A. Ortega, “Low Fertility in Europe: Causes, Implications and Policy 

Options,” in F. R. Harris (Ed.), The Baby Bust: 

Who will do the Work? Who Will Pay the Taxes?,

Lanham, MD, Rowman & Littlefield Publishers, 

2006, pp.48-109. 
88 2007 Technical Panel on Assumptions and Methods

Lindstrom, David P. and Silvia G. Saucedo, “The 

Short- and Long-Term Effects of U.S. Migration 

Experience on Mexican Women’s Fertility,” Social 

Forces, Vol. 80, No. 4, June 2002, pp. 1341-1368.

Lowell, B. Lindsay, Julia Gellatt, and Jeanne Batalova, “Immigrants and Labor Force Trends: The 

Future, Past, and Present,” Task Force Insight No. 

17, Migration Policy Institute: Washington, DC. 

July, 2006. (http://www.migrationpolicy.org/ITFIAF/TF17_Lowell.pdf)

Lucas, Deborah and Stephen Zeldes, “Valuing and 

Hedging Defined Benefit Pension Obligations–

The Role of Stocks Revisited,” manuscript, Northwestern University, 2007.

Martin, J.A., B.E. Hamilton, P.D. Sutton, et al., 

“Births: Final Data for 2004,” National Vital Statistics Reports, 55(1), Hyattsville, MD, National 

Center for Health Statistics. 2006. 

Massey, Douglas S., Jorge Durand, and Nolan J. 

Malone, Beyond Smoke and Mirrors: Mexican Immigration in an Era of Economic Integration, Russell Sage, New York, 2002. 

McKeown, Thomas, The Role of Medicine: Dream, 

Mirage, or Nemesis, Oxford, U.K., Basil Blackwell, 

1979. 

Morgan, S.P, “Is Low Fertility a Twenty-FirstCentury Demographic Crisis?” Demography, Vol. 

40(4), 2003, pp. 598-603

Motsiopoulos, Chris and Richard B. Tucker, ShortRange Actuarial Projections of the Old-Age, Survivors, and Disability Insurance Program, Actuarial 

Study No. 119, Social Security Administration, 

Office of the Chief Actuary, August, 2005. (http://

www.socialsecurity.gov/OACT/NOTES/pdf_

studies/study119.pdf)

Mulder, Tamany J., Betsy Guzman, and Angela M. 

Brittingham, “Evaluating Components of International Migration: Foreign-Born Emigrants,” 

Technical Working Paper No. 62, Population Division, U.S. Census Bureau, Washington, DC. June, 

2002. (http://www.census.gov/population/www/

documentation/twps0062.html)

Oliner, Stephen D., Daniel E. Sichel, and Kevin J. 

Stiroh, “Explaining a Productive Decade,” Brookings Papers on Economic Activity, No. 1, 2007, pp. 

81-152.

Pampel, Fred C, “Cigarette Use and the Narrowing 

Sex Differential in Mortality,” Population and Development Review, 28(1), 2002, pp. 77–104. 

Parrado, E. A. and S. P. Morgan, “Intergenerational 

Fertility among Hispanic Women: New Evidence 

of Immigrant Assimilation,” unpublished manuscript, 2007.

Passel, Jeffrey, “Projections of Population, Educational Attainment, and Labor Force Participation: 

By Generation, Age, Sex, and Race/Ethnicity: 

2000–2050,” Urban Institute Technical Report, 

Washington, D.C., February, 2004a.

Passel, Jeffrey S., “Methodology and Assumptions 

for Population Estimates and Projections by Race 

and Generation, 1960–2030,” Technical memorandum for National Academy of Sciences’ Panel 

on the Hispanic Population, Urban Institute, 

Washington, D.C., August, 2004b.

Passel, Jeffrey S., Size and Characteristics of the 

Unauthorized Migrant Population in the U.S.: Estimates Based on the March 2005 Current Population 

Survey. Pew Hispanic Center, Washington, D.C., 

March, 2006. (http://pewhispanic.org/reports/

report.php?ReportID=61)

Passel, Jeffrey S., “Modes of Entry for the Unauthorized Migrant Population,” Pew Hispanic Center Fact Sheet, Washington, D.C., May 22, 2006a. 

(http://pewhispanic.org/factsheets/factsheet.

php?FactsheetID=19)

Passel, Jeffrey S., “Growing Share of Immigrants 

Choosing Naturalization,” Pew Hispanic Center Report, Washington, D.C., March 28, 2007a. 

(http://pewhispanic.org/reports/report.

php?ReportID=74)

Passel, Jeffrey S. and D’Vera Cohn, “U.S. Population 

Projections, 2005–2050,” Pew Hispanic Center 

Report, Washington, D.C., February 2008.
2007 Technical Panel on Assumptions and Methods 89

Passel, Jeffrey S. and Roberto Suro, Rise, Peak, and

Decline: Trends in U.S. Immigration 1992–2004, 

Pew Hispanic Center, Washington, D.C. September, 2005. (http://pewhispanic.org/reports/report.php?ReportID=53)

Piketty, Thomas and Emmanuel Saez, “Income 

Inequality in The United States, 1913–1998*,” 

Quarterly Journal of Economics, February 2003, 

Vol. 143, issue 1.

Piketty, Thomas and Emmanuel Saez, “The Evolution of Top Incomes: A Historical and International Perspective,” American Economic Review 

Papers and Proceedings 96, no. 2, May, 2006.

Porter, Eduardo “Illegal Immigrants are Bolstering 

Social Security with Billions,” New York Times, 

April 5, 2005.

Poterba, James, Steven Venti, and David A. Wise, 

“The Changing Landscape of Pensions in the 

United States,” National Bureau of Economic Research Working Paper #13381, September 2007.

Preston, S.H. and S.R. Sten, “The Future of American Fertility,” Paper presented at the 9th Annual 

Joint Conference of the Retirement Research 

Consortium, Washington, D.C., August 9-10, 

2007. 

Rappaport, Anna M., “Retirement System at the 

Crossroads,” Employee Benefit Plan Review, February 2003, pp. 17-20.

Rindfuss, R., K.B. Gruzzo and S.P. Morgan, “The 

Changing Institutional Context of Low Fertility,” 

Population Research and Policy Review, Vol. 22, 

2003, pp. 411-438.

Schoen, R., “Timing effects and the Interpretation 

of Period Fertility,” Demography, 41(4): 801-819, 

2004. 

Schoen, R., “Insights from Parity Status Life Tables 

for the 20th Century U.S.,” Social Science Research

35(1), 2006, pp. 29-39.

Schoen, R., Dynamic Population Models, Dordrecht: 

Springer, 2007.

Schwenk, Albert E., “Trends in Health Insurance 

Costs,” Compensation and Working Conditions, 

Spring, 1999, pp. 24- 27.

Shkolnikov, V.M., E.M. Andreev, R. Houle, and J.W. 

Vaupel, “The Concentration of Reproduction in 

Cohorts of Women in Europe and the United 

States,” Population and Development Review, 

33(1), March 2007.

Stallard, Eric, “Demographic Issues in Longevity Risk Analysis,” Journal of Risk and Insurance,

73(4), 2006, pp. 575–609. 

Technical Panel on Assumptions and Methods 

(1999), Report to the Social Security Advisory 

Board, November, 1999. (http://www.ssab.gov/

Publications/Financing/tech99.pdf)

Technical Panel on Assumptions and Methods 

(2003), Report to the Social Security Advisory 

Board, October 2003. (http://www.ssab.gov/doc

uments/2003TechnicalPanelRept_000.pdf)

Tuiran, R., V. Partida, O. Morjarro, and E. Zuniga, 

“Fertility in Mexico: Trends and Forecast,” in 

Completing the Fertility Transition, Department 

of Economic and Social Affairs, Population Division, United Nations, 2002, pp. 483-506.

Tuljapurkar, Shripad, and Ronald Lee, “Stochastic 

Forecasts for Social Security,” in, David Wise, ed. 

Frontiers in the Economics of Aging, Chicago: University of Chicago Press, 1998, pp.393-420.

United Nations Population Division, World Population 

Prospects: The 2006 Revision. United Nations, New 

York, 2006. (Database at http://esa.un.org/unpp/)

Urban Institute, “Work and Retirement: Facts and 

Figures,” August, 2006. (http://www.urban.org/

UploadedPDF/900985_work_and_retirement.pdf)

U.S. Bureau of Labor Statistics, “Employee Benefits 

in Medium and Large Private Establishments, 

1997,” Bulletin 2517, Washington, D.C.: U.S. Government Printing Office, September 1999.

U.S. Census Bureau, International Data Base (IDB), 

Website visited August 15, 2007: (www.census.

gov/ipc/www/idb/)
90 2007 Technical Panel on Assumptions and Methods

U.S. Census Bureau, International Data Base, Population Projections for Mexico, Population Division: Washington, D.C., 2005. (http://www.census.gov/ipc/www/idb/tables.html)

U.S. Census Bureau, National Population Estimates, 

July 1, 2006, Population Division, Washington, 

D.C., 2007. (http://www.census.gov/popest/national/)

U.S. Department of Homeland Security, Office 

of Immigration Statistics, Yearbook of Immigration Statistics: 2006, Washington, D.C., January, 

2007. (http://www.dhs.gov/ximgtn/statistics/

publications/yearbook.shtm)

U.S. Department of Labor, “The Evolution of Compensation in a Changing Economy,” Report on the American Workforce, Washington DC, 2001, pp. 57-94.

U.S. Immigration and Naturalization Service, Statistical Yearbook of the Immigration and Naturalization Service, 1998, Washington, D.C., U.S. Government Printing Office, 2000. 

Wang, Haidong and Samuel H. Preston, “Forecasting U.S. Mortality Using Cohort Smoking Index,” 

Demography, 43(4), 2006, pp. 631–646.

Warren, Robert, “Illegal Alien Resident Population: 

Estimates of the Undocumented Immigrant Population Residing in the United States (October 

1996),” U.S. Immigration and Naturalization Service, Office of Policy and Planning. Washington, 

D.C., December, 2001. (Updated) (http://uscis.

gov/graphics/shared/statistics/archives/illegal.

pdf)

Warren, Robert, “Estimates of the Unauthorized 

Immigrant Population Residing in the United 

States: 1990 to 2000,” U.S. Immigration and Naturalization Service, Office of Policy and Planning, 

Washington, D.C., January, 2003. (http://uscis.

gov/graphics/shared/statistics/publications/Ill_

Report_1211.pdf)

Warren, Robert and Ellen P. Kraly, “The Elusive Exodus: Emigration from the United States,” Population Trends and Public Policy Occasional Paper No. 

8, Population Reference Bureau: Washington, 

D.C., 1985.

Welch, Ivo, “The Equity Premium Consensus Forecast Revisited,” Cowles Foundation Discussion 

Paper No. 1325, September 2001. 

Wilmoth, John R., “Are Mortality Projections Always More Pessimistic When Disaggregated by 

Cause of Death?” Mathematical Population Studies, 5(4), 1995, pp. 293–319. 

Wilmoth, John R., “The Future of Human Longevity: A Demographer’s Perspective,” Science, Vol. 

280, 1998, pp. 395-97.

Wilmoth, John R., “Theoretical and Technical Aspects of Projecting Net Migration as a Function 

of Population Size,” Social Security Advisory 

Board Working Paper: cited in Technical Panel on 

Assumptions and Methods (2003), Report to the 

Social Security Advisory Board, October 2003.

Wilmoth, John R., “Overview and Discussion of the 

Social Security Mortality Projections,” Social Security Advisory Board Working Paper, 2005. 

Zayatz, Tim, Social Security Disability Insurance Program Worker Experience, Actuarial Study No. 118, 

Social Security Administration, Office of the Chief 

Actuary, June, 2005. (http://www.socialsecurity.

gov/OACT/NOTES/pdf_studies/study118.pdf)
2007 Technical Panel on Assumptions and Methods 91

n Methodology

Method Recommendation M-1: Further document 

all models to the extent necessary for others to replicate forecasts. Make available sufficient data for 

non-government analysts to replicate forecasts, 

and conduct research to improve forecasting techniques. Include in the analysis an explicit discussion of the historical time periods, and the associated rationale, used for each variable.

Method Recommendation M-2: Explicitly model 

and document relevant interactions.

Method Recommendation M-3: The Social Security 

Advisory Board, to whom this Technical Panel reports, should hold semi-annual meetings with OCACT to discuss progress on the recommendations 

contained in this report as well as those from previous panels. 

Method Recommendation M-4: Incorporate asymmetrical risk in the projections.

Method Recommendation M-5: Further develop 

stochastic modeling capabilities, and make much 

greater use of stochastic analysis to examine uncertainty, especially the effects interactions have on 

uncertainty.

Method Recommendation M-6: Consider risk-adjusting discount rates for summarized balances. 

Using the risk-free interest rate to discount uncertain future cash flows is inconsistent with valuation 

principles, and over-weights the outcomes that are 

most uncertain. 

Method Recommendation M-7: Increase the use of 

micro-simulation to analyze and display interaction 

effects and distributional outcomes of policy changes.

Presentation Recommendation P-1: Shift the emphasis toward the intermediate-term and away 

from very long-term measures such as the infinite 

horizon forecasts. Shift emphasis toward the use of 

annual cost and income rates, and away from summarized 75-year balances.

Presentation Recommendation P-2: Include in the 

analysis an explicit comparison of the U.S. experience with other countries.

Presentation Recommendation P-3: Report annually the accuracy of previous estimates and projections.

Presentation Recommendation P-4: Increase the 

use of graphical representations of uncertainty.

Presentation Recommendation P-5: Improve the explanation of trust fund accounting and its implications.

n Demographic assumptions and 

methods

Assumption Recommendation A-1: The Panel believes that there is greater risk (and cost) to the 

trust funds associated with overestimating the 

total fertility rate over the next 75 years than underestimating it. We therefore recommend retaining the intermediate assumption of 2.0 from the 

2007 Trustees Report, but we assume a high-cost 

total fertility rate of 1.5, 0.2 lower than that of the 

Trustees, and a low-cost rate of 2.1, rather than 

2.3. In Chapter 1, the Panel recommended that the 

Trustees adopt asymmetric high-cost and low-cost 

assumptions relative to their intermediate assumption. We made this recommendation because policy 

makers and future retirees should be able to understand the direction of our uncertainty in evaluating 

alternative assumptions for the deterministic projections prepared by Trustees. It should be noted 

here that the intermediate series is not the “average” or “most likely” assumption, nor are the lowand high-cost alternatives brackets with known 

sampling distributions, such as a 95 percent confidence interval about the mean. 

Assumption Recommendation A-2: Mortality: For the 

intermediate-cost scenario, the Panel recommends 

that assumed ultimate rates of mortality decline by 

Compilation of Technical Panel Recommendations
92 2007 Technical Panel on Assumptions and Methods

age and sex be increased to an average of 1.00 percent 

per year to be consistent with those observed during 

1953–2003 for the total population. Assumed ultimate rates of mortality decline for the low-cost projections should be held at their current levels (averaging 0.33 percent per year). Assumed ultimate rates of 

mortality decline for the high-cost projections should 

be increased to an average of 2.00 percent to reflect 

the potential for the U.S. to reach rates of mortality 

reduction seen in international data. 

Method Recommendation M-8: Mortality: The Panel recommends that the mortality projection model 

be simplified by dropping separate projections by 

cause of death and stating assumptions in terms of 

age-specific rates of decline for all-cause mortality.

Method Recommendation M-9: Mortality: The Panel recommends that the infinite horizon mortality 

projection model be dropped. 

Assumption Recommendation A-3: Immigration: 

The Panel recommends that immigration scenarios 

should tie the level of net immigration to the size 

and growth of the U.S. population rather than decreasing or increasing constant numbers of immigrants. The Panel recommends that the Trustees 

move toward expressing their ultimate net migration assumptions as rates (annual number of net 

migrants divided by population size). 

Assumption Recommendation A-4: Immigration: 

The Panel strongly recommends that the Trustees 

increase significantly their assumptions regarding 

future levels of net international migration; at a 

minimum, projections of future migration should 

be brought into line with current measured levels 

of net international migration. 

n In the intermediate scenario, net international 

migration should increase from 1,350,000 in 2007 

by 1.0 percent per year through 2030; thereafter, 

net international migration should increase at 0.5 

percent per year. At this level, immigration as a 

percent of population (the “net migration rate” or 

NMR) remains within the range of both recent and 

historical experience. With the other demographic 

assumptions recommended by the Panel, this immigration scenario represents a net migration rate 

of 4.4 per 1,000 population at the beginning of the 

projections, gradually rises to 4.6 and then declines 

to 4.2 after 75 years. With this assumption, the average NMR over 2005–2080 is equal to the average 

over the 1980–2005 period or 4.4 per 1,000. 

n Our high-cost (lower immigration) scenario 

recommendation is to assume that net “other” 

immigration drops by 50,000 per year from the 

initial value of 500,000 to 200,000 and that net 

legal immigration is held constant during this period. Then, beginning from 1.1 million in 2012, 

legal immigration would increase by 0.25 percent 

per year and net other immigration at 0.5 percent per year. With these assumptions, the NMR 

declines from approximately 4.3 per 1,000 at the 

beginning of the scenario, then drops quickly 

to 3.0 after 25 years where it remains constant 

throughout the rest of the 75-year projection. 

The Panel bases the high-cost scenario on assumptions that unauthorized migration might 

be brought under control and that the growth 

rate of legal immigration would be slower than 

population growth (i.e., a declining NMR).

n The low-cost (higher immigration) scenario assumes that annual immigration will have reached 

2.8 million by 2080, a value consistent with an 

annual immigration increase of 1.0 percent. For 

the period from 2030 to 2080, immigration is assumed to increase by 0.5 percent per year, implying an increase of 2.1 percent per year for the period leading up to 2030. This scenario assumes a 

relatively rapid rate of increase in the short term, 

but a slow down for the long run. The NMR in 

this scenario peaks at 5.7 per 1,000 population 

for 2030–2035, equal to the 1995–2000 peak. 

The average NMR is 5.1, or slightly higher than 

the last 20 years, but less than the average over 

the long period of relatively high immigration to 

the U.S. in the second half of the 19th century 

and the early 20th. The Panel’s recommendations 

for the low-cost and high-cost scenarios are designed to give a greater spread between high and 

low in the short-term than might be otherwise 

obtained from basic extrapolation models. 

Method Recommendation M-10: Immigration: The 

Panel recommends that the Trustees make fundamental changes in their approach for deriving net 

migration assumptions and for implementing the 

assumptions. 

Method Recommendation M-11: Immigration: The 

Trustees’ net migration assumptions should not 

be based on the provisions of current immigration 

law, which are consistent with widely varying levels of net migration, and which can reasonably be 

expected to change in the future; but rather on an 

analysis of historical trends augmented by on-going and future research on behavioral, demographic 

and economic determinants of migration. 
2007 Technical Panel on Assumptions and Methods 93

Method Recommendation M-12: Immigration: The 

Trustees should disaggregate the demographic 

projection model by nativity (i.e., into native and 

foreign-born populations). Such a model would 

facilitate incorporation of significant known differentials into the projections, including: emigration (largely limited to former immigrants), fertility (higher for immigrants than natives), and labor 

force participation (higher for foreign-born males 

and lower for foreign-born females than for the corresponding native groups). Such a disaggregation 

can be implemented with the current cell-based 

projection model or micro-simulation models that 

might be adopted in the future.

Method Recommendation M-13: Immigration: The 

age-sex distributions of net international migration components should accurately reflect the demographic logic of the model. Specifically, the age 

distribution of net “other” immigration should encompass both positive and negative values rather 

than simply reflecting the age distribution of the 

migrant population.

Assumption Recommendation A-5: Disability Incidence Rates: The Panel recommends that the assumptions of disability incidence for the intermediate projection remain the same as in the 2007 

Trustees Report. Disability incidence assumptions 

were lowered in the 2007 Report and the Panel believes this revision was reasonable given the data 

on health and benefit trends. These same data on 

health and benefit claiming lead the Panel to recommend changes to the low- and high-cost alternative scenarios. Specifically, the Panel recommends 

raising disability incidence in both the low- and 

high-cost scenario, from 4.4 to 4.6 and 6.6 to 6.9, 

respectively. These changes increase the uncertainty bands around the intermediate assumption and 

introduce asymmetry into the risk profile, allowing 

for larger cost overruns than cost savings in the alternative scenarios.

Assumption Recommendation A-6: Disability Termination Rates: The Panel recommends that the 

assumptions of disability termination remain the 

same as in the 2007 Trustees Report but calls for 

more research on these matters going forward. 

Changes in the mix of impairments and the age of 

benefit claiming suggest that life expectancies of 

the average future beneficiary could increase more 

quickly than those of the rest of the population. 

While termination rates are much less important 

to overall cost projections than incidence rates, 

greater understanding of the factors affecting future trends is warranted.

Method Recommendation M-14: Disability: The 

Panel recommends that consideration be given to 

augmenting the cell-based model of disability incidence and termination rates to include impairment 

specific data. The Panel also calls for additional 

examination of the evolution of male and female 

disability incidence rates and for more explicit discussion of the historical and forecast time path of 

these rates, including why they are not converging 

more over time. Overall, the Panel recommends 

that the judgmental adjustments to the cell-based 

model of disability incidence and disability termination be more formally documented. 

Method Recommendation M-15: Disability: The 

Panel recommends that the models used to develop 

the short- and long-range projections for the DI 

program be better integrated and that the longrange projection methodology be better documented. More fundamentally, the Panel recommends 

that greater emphasis be placed on developing behavioral models of disability benefit claiming that 

could better inform the judgmental adjustments to 

historical extrapolations underlying the intermediate projections, improve the short- and long-run 

forecasts, and increase understanding of the risk 

factors associated with short- and long-run program growth. 

Method Recommendation M-16: Disability: The Panel recommends more focus on communication about 

key components of the disability program followed 

by the research community. Specifically, the Panel 

recommends highlighting the distinction between 

eligibility for disability benefits—based on health—

and claiming behavior, which is based on eligibility 

and socio-economic conditions, age, and policy variables such as the normal retirement age. The Panel 

also recommends that published materials report disability prevalence rates, in addition to incidence and 

termination rates. Prevalence rates are the preferred 

metric in the research literature for summarizing 

the stock of workers receiving disability benefits and 

provide important information about the size of the 

program over time. Finally, the Panel recommends 

that the relationship between the DI and retirement 

programs be made explicit—DI is just a form of early 

retirement—especially in discussions about future 

influences on program size. 
94 2007 Technical Panel on Assumptions and Methods

n Economic assumptions and methods

Assumption Recommendation A-7: Labor Force Participation Rate: The Panel recommends no change in 

the intermediate-and high-cost projections of labor 

force growth reported in the 2007 Trustees Report, 

but calls for an increase in the labor force participation rate used in the low-cost alternative. The Panel 

believes there is considerable upside risk to the intermediate assumption on labor force participation 

related to the possibility that greater life expectancy, improved health, unmet demand for workers, 

changing workplace requirements, and the reduction in rule-based private retirement plans could 

increase participation rates at older ages. The Panel 

believes that allowing for this possibility is important and could ultimately affect both the intermediate and low-cost scenarios. As such, we recommend 

increasing total labor force participation in the lowcost scenario from 72.8 to 77.0 percent for males 

and from 60.6 to 65 percent for females.131

Method Recommendation M-17: Labor Force Participation Rate: The Panel recommends that the 

OCACT labor force participation model be reviewed 

and potentially restructured. Currently, the model 

is large and unwieldy, making modifications difficult and costly. Additions to the model required 

to incorporate emerging trends (e.g., participation 

rates by nativity) only add to the complexity. Thus, 

we recommend that the Trustees implement suggestions made in the 2003 Technical Panel and restructure the model, making it simpler, more transparent, and econometrically more rigorous. 

Method Recommendation M-18: Labor Force Participation Rate: The Panel recommends more carefully following differences in labor force participation among various groups including natives and 

non-natives and older workers from different cohorts. Given the growing importance of both immigrants and older workers in the workforce, improved understanding of differences in their labor 

force behavior will be important to improving the 

accuracy of future projections. 

Method Recommendation M-19: Labor Force Participation Rate: The Panel recommends that more 

consideration be given to how changes in the popu131 The change in total participation rates comes from assuming 

that rates for each 5-year age group above 55 would attain, in 75 

years, the participation rates of the next younger 5-year age cohort 

at the beginning of the projection period. For example, those aged 

55-59 would in 2081 experience the participation rates of 50-54 

year olds in 2007, and so on for each successive 5-year cohort.

lation and labor force might impact trends in hours 

of work, productivity and annual earnings and that 

these interrelationships be noted in the Trustees 

Report. This communication of the interconnectedness of the assumptions and projections is a useful 

component of policy discussions and decisions. The 

absence of such recognition hinders accurate characterizations of the tradeoffs and complementarities embedded in changes to particular variables, 

trends or policy alternatives. 

Assumption Recommendation A-8: Unemployment 

Rate: The Panel recommends that the assumptions 

on unemployment remain unchanged from the 

2007 Trustees Report. The Panel finds a long-run 

unemployment rate of 5.5 percent is a reasonable 

assumption for future unemployment rates.

Assumption Recommendation A-9: Productivity: The 

Panel recommends that the assumption on productivity growth be maintained at the same rate as in the 

2007 Trustees Report, that is, 1.7 percent per year. 

This recommendation reflects the sharp slowdown 

in actual productivity growth between mid-2004 

and mid-2007 that has reduced the possibility that 

the American economy entered a new era of rapid 

high productivity growth after 1995. Instead, it appears that the marked acceleration of productivity 

growth between 1995 and 2004 can be attributed to 

special one-time factors that are unlikely to recur. In 

forecasting future productivity growth, substantial 

weight must be given to the poor performance of 

productivity growth in the period 1972-1995. 

Assumption Recommendation A-10: Compensation to GDP ratio: The share of labor compensation 

in GDP has historically been quite stable, and the 

Panel agrees with the current assumption of a constant ratio.

Assumption Recommendation A-11: Earnings to 

Compensation Ratio: The Panel recommends that 

the change in the earnings to compensation ratio 

be reduced in the intermediate-cost assumption 

from a decline of 0.2 percent per year to a decline 

of 0.1 percent per year for the first 25 years of the 

projections, with a zero decline after that. In the 

low-cost assumption, the current ratio should be 

held constant, while in the high-cost assumption, 

the ratio should decline by 0.2 percent per year for 

the first 25 years and by 0.1 percent thereafter. 

Assumption Recommendation A-12: Average Hours 

of Work: The Panel recommends that the 2007 

Trustees’ assumption of no change in average hours 

of work per week be changed to a decline of -0.1 
2007 Technical Panel on Assumptions and Methods 95

percent per year for the first 25 years with a zero 

rate of decline thereafter. The high-cost assumption should be of an annual decline of 0.2 percent 

for the first 25 years and a decline of 0.1 percent 

rate thereafter. The low-cost assumption would 

then be of zero change, the same as the 2007 Trustees’ assumption.

Assumption Recommendation A-13: GDP DeflatorCPI Growth Differential: The differential growth 

rate between the GDP deflator and the Consumer 

Price Index (CPI-W) should be reduced from the 

Trustees’ choice of -0.4 percentage points to -0.2 

percentage points. We find no historical evidence 

to support the Trustees’ choice and indeed in the 

past six years the differential growth rate has been 

zero. 

Assumption Recommendation A-14: Real Wage 

Growth: Together, assumptions A-8 through A-12 

result in a rate of real wage growth in the intermediate assumptions of 1.3 percent per year, slightly 

higher than the 1.1 percent assumed in the 2003 

Trustees Report.

Assumption Recommendation A-15: CPI Growth: 

The Panel recommends that the assumed rate of increase in the Consumer Price Index be reduced by 

0.3 percentage point in the intermediate assumption, from 2.8 percent to 2.5 percent per year. The 

assumption of the future inflation rate in the GDP 

deflator should be reduced from the current 2.4 

percent assumption to 2.3 percent, corresponding 

to our previous recommendation that the GDP deflator to CPI differential be reduced from -0.4 percent to -0.2 percent per year.

Assumption Recommendation A-16: Interest Rate: 

The Panel recommends using a long-term nominal 

rate of 5.17 percent, based on a real rate of 2.6 percent and a CPI inflation rate of 2.5 percent. The corresponding real and nominal rates for the high cost 

scenario should be shifted down to 1.8 percent and 

5.36 percent respectively. For the low cost scenario, 

we recommend lowering the real rate to 3.3 percent, and the nominal rate to 4.85 percent. These 

changes are based on a uniform reduction in the 

CPI inflation rate of .30 percent in all scenarios. 

Method Recommendation M-20: Interest Rate: The 

Panel recommends that the Trustees modify their 

approach to determining real and nominal interest 

rates to place more weight on the forward-looking 

information in recent Treasury yield curves. 

Method Recommendation M-21: Interest Rate: 

For calculations involving discounting such as the 

actuarial balance, the Panel recommends that the 

Trustees consider using risk-adjusted rates instead 

of a risk-free real interest rate. 

Assumption Recommendation A-17: Equity Premium: The Panel concurs with the choice of equty 

premium assumed in recent analyses by the Office 

of the Chief Actuary of proposals involving stock 

market investments.

Method Recommendation M-22: Equity Premium: 

In such analyses, the Panel recommends that the 

Office of the Chief Actuary portray risk-adjusted 

projections as a neutral risk-adjusted case, not as 

worst case for average returns.

Other Recommendation O-1: Taxable ratio: The 

Panel recommends that additional research be undertaken to develop a greater understanding of the 

implications for trust fund finances of trends in the 

dispersion of covered wages. That research should 

aim to provide a stronger basis for projecting the 

share of covered wages that fall above and below 

the taxable maximum. In addition, that research 

should examine the implications of stagnating 

wages at the lower end of the earnings distribution 

on the incentives to apply for disability benefits.

Other Recommendation O-2: Taxable ratio: The 

Panel recommends that the rationale in the Trustees Report for the projection of the share of covered wages that is taxable be made more explicit 

and should account for the substantial deviation 

of current trends from previous projections. The 

Panel recommends that the high and low cost projections of the share of covered wages that is taxable reflect a realistic degree of uncertainty. The 

long-range sensitivity analyses in the report should 

include the effect on summarized cost balances of 

the range of assumptions about the share of covered wages that is taxable.


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