Modeling Expert Opinions on Food Healthiness: A Nutrition Metric

Background Research over the last several decades indicates the failure of existing nutritional labels to substantially improve the healthiness of consumers' food and beverage choices. The difficulty for policy-makers is to encapsulate a wide body of scientific knowledge in a labeling scheme that is comprehensible to the average shopper. Here, we describe our method of developing a nutrition metric to fill this void. Methods We asked leading nutrition experts to rate the healthiness of 205 sample foods and beverages, and after verifying the similarity of their responses, we generated a model that calculates the expected average healthiness rating that experts would give to any other product based on its nutrient content. Results The form of the model is a linear regression that places weights on 12 nutritional components (total fat, saturated fat, cholesterol, sodium, total carbohydrate, dietary fiber, sugars, protein, vitamin A, vitamin C, calcium, and iron) to predict the average healthiness rating that experts would give to any food or beverage. We provide sample predictions for other items in our database. Conclusions Major benefits of the model include its basis in expert judgment, its straightforward application, the flexibility of transforming its output ratings to any linear scale, and its ease of interpretation. This metric serves the purpose of distilling expert knowledge into a form usable by consumers so that they are empowered to make healthier decisions.

Behavioral Economics Perspective on Public Sector Pension Plans

We describe the pension plan features of the states and the largest cities and counties in the U.S. Unlike in the private sector, defined benefit (DB) pensions are still the norm in the public sector. However, a few jurisdictions have shifted toward defined contribution (DC) plans as their primary savings plan, and fiscal pressures are likely to generate more movement in this direction. Holding fixed a public employee's work and salary history, we show that DB retirement income replacement ratios vary greatly across jurisdictions. This creates large variation in workers’ need to save for retirement in other accounts. There is also substantial heterogeneity across jurisdictions in the savings generated in primary DC plans because of differences in the level of mandatory employer and employee contributions. One notable difference between public and private sector DC plans is that public sector primary DC plans are characterized by required employee or employer contributions (or both), whereas private sector plans largely feature voluntary employee contributions that are supplemented by an employer match. We conclude by applying lessons from savings behavior in private sector savings plans to the design of public sector plans

Behavioral Economics Perspectives on Public Sector Pension Plans

We describe the pension plan features of the states and the largest cities and counties in the U.S. Unlike in the private sector, defined benefit (DB) pensions are still the norm in the public sector. However, a few jurisdictions have shifted towards defined contribution (DC) plans as their primary savings plan, and fiscal pressures are likely to generate more movement in this direction. Holding fixed a public employee‘s work and salary history, we show that DB retirement income replacement ratios vary greatly across jurisdictions. This creates large variation in workers‘ need to save for retirement in other accounts. There is also substantial heterogeneity across jurisdictions in the savings generated in primary DC plans because of differences in the level of mandatory employer and employee contributions. One notable difference between public and private sector DC plans is that public sector primary DC plans are characterized by required employee or employer contributions (or both), whereas private sector plans largely feature voluntary employee contributions that are supplemented by an employer match. We conclude by applying lessons from savings behavior in private sector savings plans to the design of public sector plans

The Availability and Utilization of 401(k) Loans

We document the loan provisions in 401(k) savings plans and how participants use 401(k) loans. Although only about 22% of savings plan participants who are allowed to borrow from their 401(k) have such a loan at any given point in time, almost half had used a 401(k) loan over a longer, seven-year horizon. The probability of having a loan follows a hump-shaped pattern with respect to age, job tenure, account balance, and salary, but conditional on having a loan, loan size as a fraction of 401(k) balances declines with respect to these variables. Participants are less likely to use loans in plans that charge a higher interest rate, and loans are smaller when plans allow fewer simultaneously outstanding loans, impose a shorter maximum possible loan duration, or charge a lower interest rate

How Are Preferences Revealed?

Revealed preferences are tastes that rationalize an economic agent's observed actions. Normative preferences represent the agent's actual interests. It sometimes makes sense to assume that revealed preferences are identical to normative preferences. But there are many cases where this assumption is violated. We identify five factors that increase the likelihood of a disparity between revealed preferences and normative preferences: passive choice, complexity, limited personal experience, third-party marketing, and intertemporal choice. We then discuss six approaches that jointly contribute to the identification of normative preferences: structural estimation, active decisions, asymptotic choice, aggregated revealed preferences, reported preferences, and informed preferences. Each of these approaches uses consumer behavior to infer some property of normative preferences without equating revealed and normative preferences. We illustrate these issues with evidence from savings and investment outcomes.Economic

How Does Simplified Disclosure Affect Individuals' Mutual Fund Choices?

We use an experiment to estimate the effect of the SEC’s Summary Prospectus, which simplifies mutual fund disclosure. Our subjects chose an equity portfolio and a bond portfolio. Subjects received either statutory prospectuses or Summary Prospectuses. We find no evidence that the Summary Prospectus affects portfolio choices. Our experiment sheds new light on the scope of investor confusion about sales loads. Even with a one-month investment horizon, subjects do not avoid loads. Subjects are either confused about loads, overlook them, or believe their chosen portfolio has an annualized log return that is 24 percentage points higher than the load-minimizing portfolio.Economic

Simplification and Saving

The daunting complexity of important financial decisions can lead to procrastination. We evaluate a low-cost intervention that substantially simplifies the retirement savings plan participation decision. Individuals received an opportunity to enroll in a retirement savings plan at a pre-selected contribution rate and asset allocation, allowing them to collapse a multidimensional problem into a binary choice between the status quo and the pre-selected alternative. The intervention increases plan enrollment rates by 10–20 percentage points. We find that a similar intervention can be used to increase contribution rates among employees who are already participating in a savings plan.EconomicsGovernmen

What Goes Up Must Come Down? Experimental Evidence on Intuitive Forecasting

Do laboratory subjects correctly perceive the dynamics of a mean-reverting time series? In our experiment, subjects receive historical data and make forecasts at different horizons. The time series process that we use features short-run momentum and long-run partial mean reversion. Half of the subjects see a version of this process in which the momentum and partial mean reversion unfold over ten periods ("fast"), while the other subjects see a version with dynamics that unfold over 50 periods ("slow"). Typical subjects recognize most of the mean reversion of the fast process and none of the mean reversion of the slow process.Economic

Following through on Good Intentions: The Power of Planning Prompts

We study whether prompts to form and recall a plan can increase individuals’ responsiveness to reminders to make and attend beneficial appointments. At four companies, all employees due for a colonoscopy were randomly assigned to receive either a control mailing or a treatment mailing. The mailings were identical except that the control mailing included a blank sticky note while the treatment mailing included a sticky note that prompted the recipient to write down the appointment date for a colonoscopy and the name of the doctor who would conduct the procedure. During the seven-month follow-up period, 7.2% of treatment employees received a colonoscopy compared to 6.2% of control employees, a statistically significant difference that is roughly equal to the variation in compliance associated with a 10 percent increase in the fraction of the procedure’s cost covered by insurance. The treatment effect was largest for demographic groups judged to be at the highest risk of failing to receive a colonoscopy due to forgetfulness

Testimonials Do Not Convert Patients from Brand to Generic Medication

Objectives: To assess whether the addition of a peer testimonial to an informational mailing increases conversion rates from brand-name prescription medications to lower-cost therapeutic equivalents, and whether the testimonial’s efficacy increases when information is added about an affiliation the quoted individual shares with the recipient. Research Design and Methods: 5,498 union members were randomly assigned to receive one of three different informational letters: one without a testimonial (No Testimonial Group), one with a testimonial from a person whose shared union affiliation with the recipient was not disclosed (Unaffiliated Testimonial Group), and one with a testimonial from a person whose shared union affiliation with the recipient was disclosed (Affiliated Testimonial Group). Results: The conversion rate for the No Testimonial Group was 12.2%, which is higher than the Unaffiliated Testimonial Group rate of 11.3% and the Affiliated Testimonial Group rate of 11.7%. The differences between the groups are not statistically significant. Conclusions: Short peer testimonials do not increase the impact of a mailed communication on conversion rates to lower-cost, therapeutically equivalent medications, even when the testimonial is presented as coming from a more socially proximate peer.Economic