Investing for retirement: The moderating effect of fund assortment size on the 1/n heuristic (Morrin et al. 2012)
Morrin, M., Inman, J. J., Broniarczyk, S. M., Nenkov, G., & Reuter, J. (2012). Investing for retirement: The moderating effect of fund assortment size on the 1/n heuristic. Fox School of Business Research Paper No. 14-009, 1–38.
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Experiments using U.S. households
- The study’s objective was to examine whether increases in the number of funds offered in a retirement plan caused investors to allocate their contributions more evenly across all available investment options.
- The authors administered one survey to a nationally representative sample of U.S. households and two surveys to people from consumer panels. The surveys contained information on hypothetical savings plans that were manipulated to include either a small or large fund assortment size. Participants were instructed to choose the plans in which they would invest and indicate the percentage they would invest in each of the chosen funds.
- The study found that participants were more likely to allocate hypothetical investments across all available funds when offered a small versus large assortment size.
- The quality of the causal evidence presented in this portion of the study is moderate because, although the authors controlled for observable characteristics of samples members and there was no evidence that survey versions were systematically assigned to sample members, the Clearinghouse for Labor Evaluation and Research (CLEAR) could not confirm that survey versions were randomly assigned.
Analysis of employees’ data
- The study’s objective was to determine whether the number of fund options offered by a 401(k) plan influenced the investment behavior of plan members.
- The authors compared investment behaviors among employees offered 10 or 19 fund options for investment, controlling for employees’ characteristics. The analysis used administrative data on contributions to the defined contribution plan of the Oregon University System. The study used an interrupted time series (ITS) design that analyzed changes in outcomes before and after an increase in the number of available investment options.
- The analysis demonstrated that offering a larger fund assortment size was associated with a statistically insignificant decrease in the tendency of employees to invest in all available funds and spread invested dollars evenly among chosen alternatives.
- The quality of causal evidence presented in this study is low. This means that we are not confident that the estimated effects are solely attributable to fund assortment size; other factors are likely to have contributed.
Evaluation of Informational Interventions for Households and Workers
The researchers conducted three surveys and one analysis of administrative data to examine the effects that 401(k) plan assortment size have on investment decision making. Specifically, the authors examined whether larger fund assortments overwhelmed investors and led them to use more simplified diversification strategies. The authors explored the tendency for decision makers to use a heuristic approach, or the 1/n rule, to allocate their savings equally among all investment funds when offered different numbers of investment options. They also looked at two underlying behavioral dimensions of the heuristic: the tendency to invest in all available funds offered and the tendency to spread the contributions evenly across chosen funds. The researchers first tested their hypothesis by manipulating 401(k) plan fund assortment size in three separate surveys asking people to make hypothetical investment decisions. The studies were conducted through mailed or online questionnaires and each experiment included one treatment condition in which sampled members were assigned to the large plan assortment size.
In study 1a, 5,000 households were mailed a booklet with information on a hypothetical 401(k) plan, including a description of each of the fund options within the plan. Participants were asked to imagine that they worked at a firm that presented these options to its employees. In the treatment condition, participants were presented with the hypothetical opportunity to invest in 15 mutual funds (5 stock, 5 bond, and 5 money market funds). Participants in the comparison group selected from among three possible funds (one each of stock, bond, and money market funds). In both conditions, participants indicated how much money they would invest and to which funds they would allocate their investment. Investments across the selected funds had to sum to 100 percent of the total amount indicated. The response rate for this survey was 7 percent with a final sample size of 344 households.
In study 1b, a market research firm sampled 363 adults from a nationally representative online panel who completed a survey similar to that in study 1a. However, this study administered the survey online; the treatment group was offered 25 mutual funds for investment (15 stock, 5 bond, and 5 money market funds), and the comparison group was offered 5 mutual funds (3 stock, 1 bond, and 1 money market fund).
In study 2, 300 adults sampled from a nationwide consumer panel completed an online survey similar to that in first two experiments. Those in the treatment group were offered 18 mutual funds for investment (9 stock, 6 bond, and 3 money market funds) and those in the comparison group were assigned 6 mutual funds for investment (3 stock, 2 bond, and 1 money market fund). Unlike the first two studies, this experiment included a cognitive exercise task. In this task, participants memorized a two- or five-digit number before being shown the plan information and then recalling the number after the investment information was provided. The task was designed to reduce the amount of attention available to making the hypothetical investment decision. The two-digit number is considered to have a low cognitive load, whereas the five-digit number is considered to have a high cognitive load.
CLEAR was unable to determine if survey forms were assigned at random in these studies.
In a final study, the authors analyzed the savings behaviors of 1,721 employees of the Oregon University System before and after the implementation of a new fund structure for the university’s defined contribution plan, known as the Optional Retirement Plan (ORP). This new structure, implemented in July 2007, increased the number of investment options from 10 to 19.
The final study used data from the TIAA-CREF (Teachers Insurance and Annuity Association – College Retirement Equities Fund) on participants’ demographics and income, the return on the Standard and Poor’s 500 index over the prior 12 months (a proxy for possible changes in investor sentiment or market conditions), and fund assortment size. Study participants were newly eligible to participate in ORP and made active contributions. This included 1,451 participants who became eligible from February 1998 to June 2007 and were offered 10 investment options (the comparison condition) and 270 participants who became eligible from July 2007 to March 2010 and were offered 19 investment options (the treatment condition).
The study focused on comparing fund allocation patterns before and after the implementation of the new fund structure. The study therefore had an ITS structure that measured and compared outcomes before and after the policy change.
Experiments using U.S. households
- Participants were significantly more likely to invest in all available funds when offered a small fund assortment size compared with a large assortment size.
- Increases in fund assortment size were associated with significant increases in the propensity to allocate investments evenly across chosen funds only when participants faced a high cognitive load.
Analysis of employees’ data
- Participants offered 19 funds invested in a significantly larger number of funds than those offered 10 options (5.30 compared with 3.74 funds, on average). However, increasing the number of available funds for investment did not significantly change the probability that participants would invest in all available funds or that the allocation of money would be evenly spread across funds.
Considerations for Interpreting the Findings
In the studies using survey data, the authors used ordinary least squares regression and controlled adequately for observable characteristics that might be associated with the outcomes of interest, such as age, gender, income, and 401(k) enrollment. There is no reason to believe that the treatment and comparison groups differed systematically; however, CLEAR could not determine how participants were allocated to different versions of the survey. Thus, these studies cannot be considered randomized controlled trials.
Low response rates in study 1a also suggest that survey respondents might differ somewhat from the population as a whole. Additionally, participants in studies 1b and 2 were members of consumer panels, which might not represent the entire population and could lead to less generalizable results. It should also be noted that the studies of survey data asked participants to make hypothetical decisions; these decisions might not represent actual behavior.
In the final study, the comparison and treatment groups fall along a chronological continuum; thus, effects are estimated in an interrupted time series framework. The authors conducted only a single demonstration of the intervention and did not provide any evidence to suggest that its timing was not confounded with prior trends, so it is possible that the intervention coincided with other events that mask its true effect.
Causal Evidence Rating
The quality of the causal evidence presented in each of the household survey-based studies detailed in this study is moderate. This means we have some confidence that the estimated effects are attributable to the interventions studied, although other factors also could have contributed.
The quality of the causal evidence presented in the study using employees is low. This means we are not confident that the estimated effects are attributable to the number of funds offered by the defined contribution plan. Other factors are likely to have contributed. To provide more convincing evidence of the intervention’s effects that satisfies CLEAR criteria, the authors should consider implementing the program at other firms and using more pre- and post-intervention observations in their analyses. If other implementations demonstrated similar effects and more data were used to show such effects, we could be more confident that changes in outcomes were driven by the intervention, and not some other concurrent change.