# Presentation: 394040

## Estimating Pensions in MINT

- Prepared for the
- Conference on Methodologies for Measuring Pension Wealth
- Federal Interagency Forum on Aging-Related Statistics
- August 8, 2007
- By Karen Smith and Eric Toder
- The Urban Institute

## Model of Income in the Near Term (MINT)

- Microsimulation data system projects income, assets, federal and state income taxes, and demographic characteristics of the 1926 to 1972 birth cohorts to 2020.
- The MINT5 extension augments the MINT4 projections to include the 1926 to 2018 birth cohorts to 2099.
- MINT5 provides a fairly comprehensive set of characteristics for evaluating the income sources and measures of well-being for recent and future retirees.

## Data Sources (SIPP)

- MINT begins with the 1990 to 1996 SIPP panels matched to Social Security Administration longitudinal data
- SIPP data includes
- Demographic characteristics (age, sex, race, Hispanicity, birth place, State)
- Marriage and fertility history
- Pension data
- Housing and financial assets
- SIPP has characteristics of individual recipients, but is not matched to employer data on pension plans

## Data Sources (SSA data)

- Social Security Administration data includes
- SER (Social Security covered earnings 1950-2004).
- DER (IRS earnings, including employee deferred contributions and earnings above the Social Security taxable maximum 1982-2004).
- MBR (Social Security benefit history file through 2004).
- SSR (SSI benefit history file through 2004).
- Numident (Social Security mortality file through 2004).

## Data Sources (pension data)

- Pension Benefit Guaranty Corporation’s (PBGC) Pension Insurance Modeling System (PIMS).
- Form 5500 data 1990-2003 (information on cash balance plans).
- EBRI/ICI database for assumptions regarding employer DC contributions and asset allocation behavior.
- Policy Simulation Group’s PENSIM to project job changes.

**Notes:**
PENSIM has over 264.000 job histories.

PIMS has 607 individual pension plans.

## Data Sources (tax data)

- 2003 Statistics of Income data statistically matched to the 1996 SIPP panel
- Match on taxable earnings, DB pension income, Social Security benefit, money asset income, calculated tax filing status, home ownership, state.
- SOI provides itemized deductions, non-projected income sources (alimony, capital gains, etc.).

**Notes:**
PENSIM has over 264.000 job histories.

PIMS has 607 individual pension plans.

## Projections

- From this richly detailed starting file, including actual historic earnings, education, fertility, family composition, wealth and pension characteristics, MINT projects for sample individuals:
- Marriage, remarriage, and divorce.
- Mortality and widowhood
- Immigration and emigration
- Fertility
- Disability
- Earnings and job changes
- Housing and financial asset accumulation and spend down
- Pension wealth (DB, DC, CB)
- Retirement and benefit take-up
- Social Security benefits, SSI
- Federal and State income taxes
- Co-resident income
- MINT projections are calibrated to hit OCACT targets for earnings growth, disability, mortality, and immigration.

## Types of analysis

- Characteristics of recent and future retirees.
- Distribution of retirement income sources for recent and future retirees.
- Sources and amounts of income by characteristic.
- Distributional impact of Social Security reform options.
- Distributional impact of changes in pension characteristics.
- Distributional impact of tax changes on income and retirement assets.

## Steps in Pension Projection

- 1) We obtain self-reported information on pension coverage for past and current jobs from the SIPP.
- 2) We use data from the PENSIM model to impute job changes and pension coverage on future jobs.
- 3) We calculate pension benefits from past, current, and future jobs.
- 		a) PBGC data for DB plans
- 		b) EBRI/ICI assumptions to grow wealth 	in DC Plans

**Notes:**
About 30 percent of individuals in the MINT data file do not have a pension topical module.  We impute topical module information using a statistical matching to link a person with a topical module to a person without a topical module by sex, earnings quintile, cohort, and DER deferred contribution status,

## Job Changes 

- Policy Simulation Group’s PENSIM model was developed for the Department of Labor.
- Simulates job histories using job tenure models estimated from the SIPP and applied to a synthetic dataset of workers.
- PENSIM simulates pension coverage using estimates from the National Compensation Survey, CPS, and Form 5500 data.
- For each job, a worker can have
- No pension, DB pension, DC pension, or both DB and DC.

**Notes:**

For job changes prior to age 50, MINT incorporates data on synthetic work histories from
the Policy Simulation Group’s PENSIM model, developed for the Department of Labor, Pension
and Welfare Benefits Administration (PWBA).

PENSIM simulates job histories using job tenure models estimated from the SIPP and applied to a synthetic dataset. 
PENSIM pension characteristics were estimated from 1996-98 National Compensation Survey establishment data.

 For each worker in the PENSIM dataset, information is available on the start and stop
age for each job, characteristics of each job (industry and firm size), and individual
characteristics (gender and education). Pension coverage information is also available for each
job. For each job, individuals have either no pension plan, DB coverage only, DC coverage
only, or both DB and DC coverage.

## Model Job Changes

- MINT links workers to PENSIM job histories by
- gender, education, employment history, job tenure, age, industry, firm size, pension coverage (at SIPP interview).
- Find the best PENSIM match. PENSIM imputes pension coverage on future jobs.
- Assumes no changes in pension job after age 50.

## Workers with DB Pensions

- We assign a DB plan from the PIMS data for workers reporting having a DB plan.
- Assignment by firm size, industry, union status, and whether the worker also has a DC plan.
- The PIMS data includes plan specific parameters for determining pension benefits (plan type, early and normal retirement age, reduction factors, accrual rates, service thresholds).
- PIMS data gives us enough information to calculate pension income for workers at retirement, given job tenure and earnings.

**Notes:**
Firmsize
<1000 employees
1000-4999 employees
5000-9999 employees
10000+ employees
Industry
Manufacturing
Nonmanufacturing

Plan types:
Final salary plans
Average salary plan
Flat benefit plan

## DB Plan Dynamics 

- To account for the shift from DB to CB, and DB plan freezes
- We add a time dimension to the PIMS data.
- We assume that worker behavior has not changed, but a worker in a firm that switched to a CB plan would convert to a CB plan in the year of the conversion.
- Similarly, a worker in a firm that froze its DB plan would convert to a substitute DC plan.

## Cash Balance Plans

- Use Form 5500 data from 1990 to 2003 to find plans that converted from DB to CB.
- Collect summary plan information for converted plans that are in the PIMS sample (51 plans).
- Model relevant CB plan parameters (year of conversion, interest rate, age and tenure structure, adjustments for earnings above Social Security tax max, transition provisions).

## DB Plan Freezes

- Identify 23 DB plans on the PIMS data that have announced they have or will freeze their DB plan.
- Collect information on plan
- Freeze date, type of freeze, replacement plan characteristics.
- Employer contributions and match rates before and after the conversion.

## Typical MINT projection

**Notes:**
Example of 5 workers as they progress over time.

Green represents worker covered by a  DB plan, 
Blue represents worker covered by a  CB plan
Purple represents worker covered by a  DC plan
Gray represents worker covered by a  NO plan,

Worker 1 has one job (since the pension interview).  It provides a DB plan through 1993 and converts to a cash balance plans in 1994.  The worker retires in 1996.  He will get a the cash balance plan as his DB plan converted to CB.  Transition rules, specific to the plan, will adjust his CB assets for his age and tenure at the conversion.

Worker 2 has two jobs.  Job 1 and 2 offer a DC plans. Worker participation is base on the DER through 2004.  Worker 2 makes no contributions in 1998.  The employer match rates can change between employer.

Worker 3 has a DB plan between 1993 and 2002.  His DB plan freezes in 2003 and the worker converts to having a DC plan.  The worker will get a DB plan based on 10 years of earnings through 2002.

Worker 4 has no pension coverage from his employer.

Worker 5 has two jobs.  He gets a DB pension from job one.  He  changes jobs at age 49 and is offered a DC plan.  At retirement, he will have a DB pension base on job 1 and DC assets based on accumulated assets in job 2.

## DC pensions

- SIPP reports DC, IRA, and Keogh balances as of the SIPP survey (wealth topical module)
- Allocate starting balance into stocks and bonds that varies by age.
- Stock and bond balances earn a varying annual rate of return less a 1% administration fee.
- 			real	standard
- 			return 	deviation
- 		stock	6.5%	.17
- 		bond	3.3%	.02
- Rebalance portfolio every 5 years.
- Assets accumulate until retirement.

**Notes:**
No spenddown until the later of age 50 or retirement age 

## Asset Allocation by Age

**Notes:**
Plan types:
Final salary plans
Average salary plan
Flat benefit plan

## DC Pension Participationgiven offer

- Two participation models based on last year’s contribution status (yes,no) estimated from 1996 SIPP/DER.
- Corrections to Census imputed pension type to be consistent with DER contributions.
- Includes actual worker contributions for 1990 to 2004 from the DER.

**Notes:**
DER is from employer W2 forms.  It includes value of deferred earnings (worker 401k contributions)

## Determinants of DC Participation

- Participation much higher if contributed previous year
- For prior year contributors, varies with
- Earnings (+)
- Whether 1st year on new job (-)
- For prior year non-contributors, varies with
- Earnings (+)
- Whether 1st year on new job (+)
- For both groups, no effect of age, after controlling for earnings

## DC Contributions

- Among participants we estimate employer contributions using a random-effects Tobit model
- Tobit controls the censored contribution amounts due to statutory contribution limits.
- Individual-specific error term is the average error term (DER contribution amounts – predicted contribution: 1990-2004).

**Notes:**
Non-participants get a random error term drawn from the distribution of non-missing errors.

Random-effects model includes both an individual-specific and transitory error term.

## Determinants of Worker Contribution Level

- Earnings (+)
- Job tenure (+)
- Contributed before (+)
- Employer contributes to plan (+)
- No. of dependent children (-)
- Whether spouse works (-)
- Earnings of spouse if working (+)
- Demographic characteristics
- Blacks and Hispanics < Whites
- Married Couples > Singles

## DB Pension Benefit Calculation

- Use pension benefit formula and model projected retirement age to calculate pension income (federal, military, state and local government, private, union).
- Update pension income by colas:
- Self-report for retirees reporting having a cola on the SIPP.  Imputed for future jobs.
- Update federal and military pensions based on plan values.
- Different treatment for federal and military workers who started before and after 1986.
- Provide a 50% survivor annuity to surviving spouse for retirees that reporting having a joint and survivor option.
- Impute joint and survivor take-up based on logistic model estimated on the HRS.  Model includes pension wealth, financial assets, earnings, race, education, marriage duration.

## Model Three Pension Scenarios

- High: Current pension status with know pension freezes through 12/2006.
- Medium: All private sector pensions freeze over the next ten years.
- Low: All private sector pensions and 1/3 of State and Local Government pensions freeze over the next five years.

## Pension Coverage: High Option

## Valuing Pension Well-Being for DB and DC

- Need a way to compare well-being (income) for retirees with a DB and DC.
- DB pensions pay a stream of benefits from retirement until death.  Income includes both yield (interest rate) and return of principal.
- DC pensions accumulate a lump sum of assets.
- For comparability, need to measure income from DC plans to include both yield and return of principal
- We measure DC income as the “fair” market annuity on 80% of DC wealth.
- Estimate life expectancy based on race, gender, education, and life earnings to compute “fair annuity”
- Apply 20% discount for risk of outliving assets
- To compute path of DC income over time, we decay DC assets using an estimated asset spend down model.  Two effects of aging on income:
- Lower wealth reduces income
- Reduced life expectancy raises income.

## Average Per-Capita Income at Age 67 by Birth Year and Income Source

**Notes:**
Average DB income declines for later cohorts.
Asset Income rises from the 1931 to 1960 cohort and then declines slightly.  Increased DC pension assets do not offset decline in asset income.

Eric, I will separate out DC from non-pension assets.  This chart includes only 1996 panel

## Compare Pension SimulationsCoverage

- Note: Charts showing effects of alternative pension freeze scenarios on pension coverage and retirement income of different cohorts will be added.