University of VirginiaDarden School of Businessresearch shows new, more effective ways to plan for retirement, professors from the school contend.

Every day, financial planners help future retirees determine how much they'll spend or "consume" each year of their lifetime. The answer lets individuals know how much they'll need to save to live comfortably.

However, making plans without knowing how long you will live is a financial challenge. As the saying goes, "You can't take it with you when you die." At the same time, people don't want to outlive their retirement savings.

Darden professorSamuel E. Bodily and assistant professorCasey Lichtendahldiscuss what they believe to be a more effective model for the financial-planning problem in their research paper titled, "Preferences for Consumption Streams: Scale Invariance, Correlation Aversion and Delay Aversion Under Mortality Risk."

The professors demonstrate that people should put their money where their health is.

"People tend to under plan," says Bodily. "They plan to spend less at 65 years of age and spend more money when they are in their 80s. With this type of spending delay, individuals risk not getting to spend as much as they might like during their lifetimes."

To better determine consumption habits, a small but growing number of financial planners offers computer-based forecasting tools. The tools ask individuals to enter information about financial obligations, savings, and assets. These financial planning calculators generate reports that guide individuals and their planners as they choose the best approach for growing retirement savings based on consumption during each phase of a retiree's life.

Bodily and Lichtendahl favor this approach, but identify one pitfall: The common financial model, which takes additive preferences into account, fails to address uncertainties. It doesn't distinguish between situations in which consumption is all bad or all good versus situations in which there are some bad and some good years. Instead, the researchers developed what they call the multiplicative-expo power utility (MEP), which accounts for risks and uncertainties. Using MEP can help financial planners better forecast their clients' retirement spending needs.

Past experiments that studied consumption preferences showed that most people are correlation averse, meaning they prefer to have a mixture of bad and good years rather than all bad or all good years. One positive effect of using MEP is that it suggests that retirees spend more in their early retirement years when they are more likely to be healthy and able to consume more rather than later.

"We're taking raw preferences of individuals and using the information to make decisions about spending," says Lichtendahl. "This model has important implications for how planners and analysts advise individuals planning for retirement."

"With MEP, you can solve dynamic problems because you can take them apart in time," Bodily added. "The MEP form is general and can also help with decisions such as career choices, investment choices, and insurance planning."

Last month, Bodily and Lichtendahl won a"Best Paper" special recognition awardfor their paper in Decision Analysis on "Multiplicative Utilities for Health and Consumption." This paper, they say, builds upon the use of multiplicative utilities such as MEP to connect consumption habits with health status and future health considerations.

In addition to advancing knowledge in the area of decision analysis and modeling, Bodily and Lichtendahl say they hope to modernize the way financial planners and wealth managers help individuals shape the quality of their older adult lives through more effective planning for retirement.

Bodily researches decision-and-risk analysis, strategy modeling and analysis, forecasting and lifetime consumption, and investment planning. He has written several books and a wide variety of journal articles.

Lichtendahl teaches quantitative analysis courses in Darden'sMBAprogram. His research focuses on eliciting, evaluating, and combining probability forecasts for use in corporate and governmental decision-making situations.