Previous research has concluded that prespecified asset allocations used by many Section 529 college savings plans are suboptimal. We extend this research to show that though it may be true, it is true for reasons other than those asserted in previous research. In addition, it tends to deflect attention from other investment options and strategies.Investments ; Saving and investment

Ramon P. DeGennaro

English

Research Papers in Economics

 
Working Paper Series 
 
 
Asset Allocation and Section 529 Plans 
 
Ramon P. DeGennaro 
 
Working Paper 2003-1 
January 2003 
 
  
 
The author thanks Dale Domian and Deborah Murphy for helpful comments and Ernie Evangelista, T. Shawn Strother, and 
Annie Tilden for excellent research assistance. He also gratefully acknowledges the support of a University of Tennessee 
Finance Department Summer Faculty Research Award and a College of Business Scholarly Research Grant. The views 
expressed here are the author’s and not necessarily those of the Federal Reserve Bank of Atlanta or the Federal Reserve 
System. Any remaining errors are the author’s responsibility. 
 
Please address questions regarding content to Ramon P. DeGennaro, Visiting Scholar, Federal Reserve Bank of Atlanta, 
1000 Peachtree Street, NE, Atlanta, Georgia 30309-4470, 865-974-1726, rdegenna@utk.edu. 
 
The full text of Federal Reserve Bank of Atlanta working papers, including revised versions, is available on the Atlanta Fed’s 
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Federal Reserve Bank of Atlanta 
Working Paper 2003-1 
January 2003 
 
 
Asset Allocation and Section 529 Plans 
 
 
Ramon P. DeGennaro, Visiting Scholar, Federal Reserve Bank of Atlanta 
 
 
 
 
Abstract: Previous research has concluded that prespecified asset allocations used by many Section 529 
college savings plans are suboptimal. We extend this research to show that though it may be true, it is true for 
reasons other than those asserted in previous research. In addition, it tends to deflect attention from other 
investment options and strategies. 
 
JEL classification: G11, G20, G29 
 
Key words: asset, allocation, college, savings, taxes Asset Allocation and Section 529 Plans
1. Introduction
Recent changes in the United States’ tax code have raised Section 529 plans to the forefront
of investment vehicles for college savings.  Legislation has increased both the investment limits
and tax benefits of these plans.  Not surprisingly, the number of investors using Section 529 plans
and the amounts invested in them have grown rapidly.  Block and Waggoner (2002) report that
about $25 billion flowed to such plans in 2002, and the figure is expected to balloon to $200
billion by 2007.
Spitzer and Singh (2001, hereafter, SS) compare Section 529 plans with predetermined
asset allocations with comparable investments held outside a tax-preferred vehicle.  They provide
a concise review of the theory of asset allocation and a brief introduction to the essentials of
Section 529 plans.  Their concern is that the tax advantages of a 529 plan might be negated by the
reduced return resulting from mandated asset allocations.  They conduct simulations based on
historical returns and interpret the results as demonstrating that this may well be the case,
especially for investors in low marginal tax brackets and for those who delay investing until the
child is nearly ready for college.
My paper extends SS’s work by distinguishing between two issues.  The first is
prespecifying asset allocations.  The second is the tax advantages of 529 plans (though the
essential points of SS and this article also apply to most other tax-advantaged investment
vehicles).  SS correctly question the wisdom of prespecifying asset allocations, then proceed by
considering a small number of specific preallocations.  They compare New York's College
Savings Program (NYCSP) with an unrestricted, fully taxable investment.  While this approach
may have some merit, I contend that the conclusions drawn from that study are potentially
3misleading.  Separating the analysis of the general class of predetermined asset allocations from
the specific allocation of the NYCSP resolves these issues.  Put somewhat differently, the decision
to allocate funds to a 529 plan is essentially independent of the allocation within the plan.  For
example, SS state all of the following:
“...  adherence to prespecified asset allocation for low tax bracket investors
often results in return loss that overshadows the tax benefit.”  (p. 101).
“This evidence strongly suggests that for families in the ‘low’ income category,
which have a long term college savings goal, the [529 plan] is likely to be an
inferior alternative to a plan which aggressively contributes to a 100% equity
plan.”  (p. 111).
“Buying into the [529 plan] when the child is near college is shown to be a poor
strategy.” (p. 114).
“Investors in lower income groups who are considering these plans would be
well advised to consider ... exercising investment options that are equity
aggressive, ...”  (p. 115).
Though all of these representative statements are potentially true, I argue that they risk
misleading investors.  First, conclusions drawn by analyzing a specific predetermined asset
allocation may not extend to the general class of predetermined asset allocations.  Second,
4allocating funds to a 529 plan is a prior decision that is essentially unrelated to the portfolio
choice within the plan.  Third, investors can invest in 529 plans outside of their states of
residence, providing a much wider range of investment options.  Finally, investors base their
investment decisions considering risk as well as expected or average return.  Although SS surely
realize this, their interpretations of their simulation results tend to deflect attention from it.
Section 2 explains what SS call the fallacy of cookie cutter asset allocation and clarifies
my paper’s primary contribution, which is how the important distinction between asset allocation
to an investment and within the investment changes the analysis.  Section 3 discusses the
implications of risk on the investment decision, and Section 4 describes the impact of Section 529
plans in a portfolio context.  Section 5 contains the summary and investment implications.
2. The Fallacy
Other researchers are surely correct in noting that Section 529 plans such as New York's
have flaws.  One investment option within New York's plan (as well as many others) has a fixed
asset allocation (among stocks and bonds) depending on the age of the child.  The younger the
child, the higher the proportion of stocks.  The idea behind such a strategy is that if the child is
young, he should hold predominantly stocks because stocks tend to return more.  But as the child
ages, the story goes, he should shift to bonds so that he reduces the risk of losing his nest egg.
Proponents apparently believe that the market may not have time to rally if it crashes near his
withdrawal date.  SS correctly identify the weakness of this reasoning.  But even setting aside
individual risk preferences, an age-dependent allocation has little or no economic support.  It
relies on mean reversion in stock prices and ignores path dependence: if an investor in a plan with
a prespecified portfolio mix loses a good portion of his investment early and is far short of his
needs with just a few years remaining, he must still switch to bonds, again presumably because the
5market may not have time to recover.  In fact, though, if the investor is well short of his target with
little time remaining, he might very well want to gamble.  A prespecified asset allocation
precludes this.
Prespecifying asset allocations also precludes adjusting to changes in the tax code,
expected tuition, scholarships, external support such as gifts from relatives, etc.  It is also a poor
choice for those who delay college -- at a minimum, the time until the funds are needed is a better
measure than age.  Indeed, Gunthorpe and Levy (1994) find that the optimal portfolio composition
changes drastically and systematically with changes in the holding period.  Given the increasing
numbers of nontraditional students, this design oversight becomes even more critical.  Investors
themselves are in a much better position to decide what proportion of their funds should be
allocated to equities.
In fact, nothing prevents an investor from matching the allocation of the predetermined plan
initially, while retaining the option to deviate from that allocation if he later desires.  It is well
known that an option is worth more alive than dead.  Absent a compelling reason to do so,
(perhaps large transactions costs), why would an investor destroy his option to reallocate his
portfolio?  The short answer is, he would not.
Thus, specifying the allocation based on age is an obvious fallacy.  SS take a different tack.
They essentially ask this question: Is it possible for the ex post return on one risky asset to exceed
the ex post return on a different risky asset?  Put that way, the answer is obviously yes.  SS go
further, exploring the likelihood that an ex post return from a risky asset exceeds the ex post return
from another less-risky, but tax-preferred asset.  One way to do this would be to derive or assume
a distribution of returns and calculate the result analytically.  Another approach, adopted by SS, is
to conduct a Monte Carlo simulation.  SS use historical returns and return variances for stocks and
6bonds, run simulations for various holding periods, then compute the average returns for various
portfolio allocations.  Given the historical returns used, a portfolio allocated totally to stocks has
the highest average return.  This is no surprise because, on average, the historical return on stocks
really was higher during the sample period.  Thus, for a wide range of tax rates, a fully taxable
all-equity portfolio may well return more than a tax-advantaged 529 plan with substantially less
than 100% equities, on average, even though the 529 plan has a tax advantage.
Perhaps the complexity of the simulation blurs the issue, for SS conclude that the
prespecified allocation is the problem.  In fact, though, preallocation is not at all the cause of the
result.  An investor could prespecify 100% equities in the 529 plan and always beat the same
portfolio held outside the plan, so long as total realized returns are positive.  This is a
mathematical certainty for positive tax rates and positive nominal returns.  Being predetermined
within a Section 529 plan is a matter entirely separate from allocating between a 529 plan and a
fully taxable investment.
Some readers might see this better algebraically.  Equation (1) gives the terminal value
(per dollar) of a fully taxable portfolio returning an average of Rt before taxes, taxed at an annual
rate t, over a period of N years.  Equation (2) gives the terminal value (also per dollar) of a
portfolio held within a 529 plan, exempt from taxes, and returning an average of R529 over that
same period.
TV = [(1+(Rt   (1-t))]N,     (1) %
TV529 = (1 + R529)N.     (2)
In principle, can the portfolio returning Rt provide a greater return than one returning R529?
Certainly.  Can that return be high enough to outweigh the tax penalty of t ?  Again, the answer is
yes.  SS’s simulation using historical returns demonstrates that for reasonable tax rates t and
7holding periods N, this would have happened often if the taxable portfolio were invested fully in
stocks while the 529 portfolio were invested according to the NYCSP’s prespecified allocation.
Clearly, though, investors can learn another lesson.  For any positive portfolio return and
for any positive tax rate, TV529 > TV for any positive holding period, if the portfolio returns are
equal; that is, if Rt = R529.  The only question is whether obtaining comparable portfolio returns is
reasonable.  And not only is it reasonable, but it is also available for the asking.  Many states,
including Michigan, Minnesota and Missouri, offer 100% equity funds.  This portfolio,
predetermined to be completely invested in stocks, is virtually indistinguishable from the one SS
recommend.  Although choosing a plan outside of one’s state of residence foregoes any state tax
advantage, it dominates a similar portfolio held outside the plan for any positive federal tax rate,
so long as the nominal ex post return is positive.  Even New York residents who wish to preserve
their 529 plan’s state tax advantage can choose what New York calls its High Equity Option.  This
investment choice invests between 75% and 100% in a domestic stock index mutual fund.  As of
December 2002, the allocation was 100% stocks (see
htttp://www.nysaves.org/piecharts_guar_highequity.html).
Some might call the distinction between allocation to a 529 plan from allocation within a
529 plan to be merely semantics, or needlessly precise.  In fact, though, the portfolio that SS’s
simulation identifies as having the highest average return is also prespecified.  The difference is
not that the portfolio is prespecified, but rather that the portfolio is riskier.  The riskier portfolio is
prespecified to be 100% equities, while NY’s prespecified portfolio comprises stocks, bonds and
money funds.  This is more than just semantics, because it deflects attention from investment
strategies that many investors would find attractive.
83. Risk
Drawing investment advice based on realized mean returns from a Monte Carlo simulation
is potentially misleading because it essentially ignores the risk of the portfolio.  With risky assets,
investors are unable to earn a guaranteed average return for any given holding period.  That is
because they only obtain a single realization from the return distribution.  To see this, consider the
choice between a sure 1% profit on a $10,000 investment and the opportunity to bet $10,000 on a
single coin toss that pays $21,000 if the coin lands heads and nothing if it lands tails.  A simulation
would recommend the coin toss because with multiple tosses, the bet returns an average of 5% per
toss.  Many investors, though, would rationally decline the single toss and choose the safer
investment.
A Cautionary Note
SS use data from 1980 - 1999 in their simulation.  They replicate their simulation using
1970-1999 and report that the results are “substantially similar.”  Although they conclude that their
results are independent of the sample period, investors would still do well to consider the risk of a
100% equity portfolio.  Shiller (2000) reports that it took years for stocks to recover from the
Great Depression.  He writes that, “The real S&P Composite Index did not return to its September
1929 value until December 1958” (page 9).  This does neglect dividends, but Shiller adds that,
“The average real return in the stock market (including dividends) was -13.1% a year for the five
years following September 1929, -1.4% a year for the next ten years, -0.5% a year for the next
fifteen years, and 0.4% a year for the next twenty years” (page 9).  Investors in the Japanese stock
markets are currently experiencing a similarly trying period.  Recent Nikkei averages hover at
about the levels of 20 years ago, though dividends would at least make the 20-year nominal return
9positive.  Simulation results, by converging to the average realized return over that particular
sample period, obscure these unpleasant possibilities.
4. Portfolio Considerations
My analysis matches SS in that it ignores the rest of a Section 529 plan participant’s
portfolio.  Portfolio considerations, though, probably weigh against the argument for allocating the
investment in a Section 529 plan to 100% equities.  Several authors, notably Miller (1977), argue
that a tax premium is probably embedded in the prices of assets; assets that are subject to higher
taxes probably have higher before-tax returns.  Tepper (1981) gives the implications of this for
tax-sheltered investments: all else equal, investors should hold high-yield stocks or bonds in
tax-preferred vehicles such as 529 plans, and hold low-yield stocks in other accounts.  Intuitively,
this strategy eliminates the largest tax liability.  
This fits well with Reichenstein (1998).  He illustrates the importance of considering the
investor’s entire balance sheet, including not only his financial assets but also, for example, his
pension assets, life insurance and mortgage liabilities.  Reichenstein’s analysis would conclude
that allocating Section 529 plan assets to 100% stocks would require offsetting investments in
other assets held outside of the 529 plan.  Even an extremely risk-tolerant investor, who prefers
100% equity investments, would do better to follow Domian and Racine (2002) and gain the
additional equity exposure by leveraging his investments held outside the tax shelter.  SS probably
make the best recommendation of all when they cite Elton and Gruber (2000), who conclude that it
might be impossible to judge the rationality of asset allocation recommendations.
5. Summary and Conclusions
Section 529 plans are not for everyone.  Some investors may have no discretionary funds to
save at all, or they may have no college-bound children.  Other children may have their educations
10already funded, perhaps via a relative’s estate.  The effects of 529 plans on financial aid might
deter some investors, and some others might prefer that their children learn the lessons of working
their own way through college.  
Recent tax law changes, though, have magnified the importance of Section 529 plans.  The
appeal of these plans is now much greater.  For most investors, they are fully tax-exempt at the
federal level, and investment limits are typically an order of magnitude larger.  Portfolio
allocation -- both to and within Section 529 plans -- is sure to remain the focus of extensive
research.
  
11References
Block, Sandra and John Waggoner (2002).  529 college plan choices are all over the map,  
http://www.usatoday.com/money/covers/2002-07-08-529-college-plans.htm.
Domian, Dale L. and Marie D. Racine.  Wealth and risk from leveraged stock portfolios,
Financial Services Review 11, (1), 2002, 33-46.
Elton, E. J., and Gruber, M. J. (2000).  The rationality of asset allocation recommendations,
Journal of Financial and Quantitative Analysis. 35(1), 27-42.
Gunthorpe, Deborah, and Haim Levy, (1994).  "Portfolio Composition and the Investment
Horizon," Financial Analysts Journal, January/February, 51-56.
Miller, Merton H.  (1977). Debt and Taxes,  Journal of Finance 32, 261-275.
Reichenstein, William.  (1998).  Calculating a family’s asset mix, Financial Services Review 7,
195-206.
Shiller, Robert J.  (2000).  Irrational Exuberance.  Princeton University Press, Princeton, New
Jersey.
Spitzer, John J. and Sandeep Singh.  (2001).  The fallacy of cookie cutter asset allocation: some
evidence from New York's college savings program, Financial Services Review 10,
101-116.
Tepper, Irwin.  (1981).  Taxation and corporate pension policy,  Journal of Finance 36, 1-13. 
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