Model “Hones”
After a winter filled with predictions of winter weather that never quite measured up to the forecasts, the nation’s capital (and the Southeast) finally got a taste of what those in the Midwest and Northeast have been contending with for weeks. Not that there haven’t been close calls here, but up until this week, the multitude of factors that have to come together to produce a significant snowfall here—hadn’t. Much to the discomfiture of those who ply their trade making such predictions, it should be noted.
While Mother Nature can be notoriously fickle, technologies like Doppler radar are able to discern with greater precision real-time activity which can be fed into sophisticated computer models that draw on the experience of the past to extrapolate a series of potential outcomes—some deemed more likely than others. Projected outcomes that, despite the recent experience here, do an increasingly accurate job of helping each of us plan our daily commute or that vacation a couple of weeks hence.
Arguably, predictions about retirement readiness are even more complicated than weather forecasting, though there are certain similarities. Done properly, they require a foundation in knowing the actual resources available to individuals—and an ability, through the use of sophisticated computer models, to forecast the impact of current behaviors on future outcomes. Those models must also consider the likelihood and timing of certain external factors, and their impact on resources, and to project if (or when) those resources will run short against lifespans and circumstances as unique and variable as the American population.
Of course, those computer models require updating on a regular basis to properly account for changes in assumptions (and realities). A recent EBRI Issue Brief[1] noted that, due to the increase in financial market and housing values during 2013, the probability that Baby Boomers and Generation Xers would NOT run short of money in retirement increased between 0.5 and 1.6 percentage points (when aggregated by age cohort), based on the Employee Benefit Research Institute (EBRI) Retirement Readiness Ratings (RRRs).[2]
EBRI’s analysis, which analyzes the major factors that cause retirement outcomes to differ, and their impact, found that, among other things, eligibility for participation in an employer-sponsored 401(k)-type plan remains one of the most important factors for retirement income adequacy. In fact, Gen Xers in the lowest-income quartile with 20 or more years of future eligibility in a defined contribution plan are half as likely to run short of money as those with no years of future eligibility.
Not surprisingly, the report also noted that the risks of a long life and high long term-care costs drive huge variations in retirement income adequacy—and suggested that annuities and long-term care insurance could mitigate much of the variability in retirement income adequacy at or near retirement age.
Of course, while a broad-based forecast is sufficient for the local weather, and a broad-based sense of the nation’s retirement readiness is powerful fodder for purposes of setting public policy goals, individual forecasts—in order to be accurate—require more customized inputs.[3]
Nevin E. Adams, JD
[3] Fortunately, individuals who want a sense of their retirement readiness can check out EBRI’s BallparkE$timate,® along with the other materials available at www.choosetosave.org
While Mother Nature can be notoriously fickle, technologies like Doppler radar are able to discern with greater precision real-time activity which can be fed into sophisticated computer models that draw on the experience of the past to extrapolate a series of potential outcomes—some deemed more likely than others. Projected outcomes that, despite the recent experience here, do an increasingly accurate job of helping each of us plan our daily commute or that vacation a couple of weeks hence.
Of course, those computer models require updating on a regular basis to properly account for changes in assumptions (and realities). A recent EBRI Issue Brief[1] noted that, due to the increase in financial market and housing values during 2013, the probability that Baby Boomers and Generation Xers would NOT run short of money in retirement increased between 0.5 and 1.6 percentage points (when aggregated by age cohort), based on the Employee Benefit Research Institute (EBRI) Retirement Readiness Ratings (RRRs).[2]
EBRI’s analysis, which analyzes the major factors that cause retirement outcomes to differ, and their impact, found that, among other things, eligibility for participation in an employer-sponsored 401(k)-type plan remains one of the most important factors for retirement income adequacy. In fact, Gen Xers in the lowest-income quartile with 20 or more years of future eligibility in a defined contribution plan are half as likely to run short of money as those with no years of future eligibility.
Not surprisingly, the report also noted that the risks of a long life and high long term-care costs drive huge variations in retirement income adequacy—and suggested that annuities and long-term care insurance could mitigate much of the variability in retirement income adequacy at or near retirement age.
Of course, while a broad-based forecast is sufficient for the local weather, and a broad-based sense of the nation’s retirement readiness is powerful fodder for purposes of setting public policy goals, individual forecasts—in order to be accurate—require more customized inputs.[3]
Nevin E. Adams, JD
[1] “What Causes EBRI Retirement Readiness Ratings™ to Vary: Results from the 2014 Retirement Security Projection Model®” is available online here.
[2] EBRI’s proprietary Retirement Security Projection Model® (RSPM), unlike many other models, takes into account a combination of deterministic expenses from the Consumer Expenditure Survey (as a function of age and income) as well as health insurance and out-of-pocket, health-related expenses, plus stochastic expenses from nursing home and home-health care (at least until the point such expenses are covered by Medicaid). A chronology of the EBRI Retirement Security Projection Model® is available online here.
[2] EBRI’s proprietary Retirement Security Projection Model® (RSPM), unlike many other models, takes into account a combination of deterministic expenses from the Consumer Expenditure Survey (as a function of age and income) as well as health insurance and out-of-pocket, health-related expenses, plus stochastic expenses from nursing home and home-health care (at least until the point such expenses are covered by Medicaid). A chronology of the EBRI Retirement Security Projection Model® is available online here.
[3] Fortunately, individuals who want a sense of their retirement readiness can check out EBRI’s BallparkE$timate,® along with the other materials available at www.choosetosave.org
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