Stages of the Financial Life Cycle

In my last blog I introduced the economic theory and field of study of life cycle finance, a principal goal of which is to construct a useable framework to help individuals improve their financial decision making to produce better monetary outcomes and maintain the smoothest and highest possible standard of living throughout their lives.

A central construct upon which life cycle finance is based is that most individuals experience important lifetransitions each with different social, family, career and financial characteristics. The quality of the financial decisions they make during these periods will have significant and long-lasting implications for their finances.

The life cycle concept has been widely accepted by sociologists and marketers for decades and adopted as a useful framework to study and predict human development and consumption behavior. In contrast the adoption of financial life cycle theory has until recently remained in the realm of academic research and is only now becoming an accepted tool of personal finance practitioners.

Economists generally agree that a person’s financial life consists of six sequential stages, three of which occur during their working years and three more during retirement. Let’s look at each one briefly.

Early career – This is the start of a person’s financial life. Typically the priorities include paying down student loans, establishing an emergency fund, borrowing for the purchase of a car and perhaps a first home and launching a retirement savings and investment plan.

Career development and raising a family – The focus may be on upgrading career skills, improving earnings prospects, moving to a larger home, building a college fund for children, increasing insurance protection for the family’s breadwinners and accelerating retirement savings.

Pre-retirement and peak earning years – During this phase the financial needs of the family typically decline, career prospects level off and the emphasis shifts decisively toward retirement planning and preparation.

Active retirement –This period is often characterized by a desire to enjoy a busy lifestyle filled with travel, entertainment and other leisure activities. While individual spending patterns vary widely, many new retirees experience an increase in discretionary spending in order to pay for these activities.

Passive retirement- This is the stage when energy levels may begin to decline and health issues surface. Devoting more time to family and friends and staying closer to home becomes the preferred way to enjoy leisure time. Discretionary expenditures will likely decline only to be replaced by rising health care costs.

Elderly care – This phase is often marked by a significant decline in physical and mental capacity, a further reduction in vigorous activity and increased health and age-related expenditures.

To better understand human development and spending behavior researchers and practitioners in the fields of psychology, sociology and marketing have studied changes that individuals, couples and families exhibit over their lives. Not surprisingly patterns emerge at various ages and stages in life as people experience major life cycle transitions such as launching a career, starting a family, preparing for a departure from the workforce and then retirement and old age. Personal finance researchers and more recently financial practitioners have begun to make extensive use of these same approaches in studying how people do and perhaps more importantly should make the kinds of financial decisions that have far-reaching consequences for themselves and their families.

What is Life Cycle Finance?

Life cycle theory is one of the more exciting and useful areas of research in personal finance. In broad terms, it represents the body of economic theory and knowledge that examines how individuals can make wiser and more beneficial decisions about spending, saving, investing and insuring over their lifetimes. There are several concepts underlying life cycle theory. We’ll discuss two of them in this article.

First is the premise that individuals will be making decisions about how to manage their wealth across a planning horizon that can span 60 years or more. This period begins at the start of a career at age 25 until the end of retirement at 85 or older and includes different life phases. The second assumption, derived from the field of classical economics, presumes that people are rational, have a firm grasp on self-control. Therefore, they will deploy their income and assets in a way that will enable them to maintain the smoothest and highest possible standard of living throughout their lives. This concept is known as “consumption smoothing”.

For example, following the consumption smoothing framework, a person might make a series of spending, saving, investing and insuring choices that allow them to maintain inflation-adjusted spending of $75,000 per year over their entire life. This is presumed to be preferable to a series of financial decisions that result in a $95,000 per year standard of living during their working years but only $55,000 during retirement or vice versa. The rationale behind this concept is intuitive. Given the option, most people would not choose to live an opulent lifestyle while they are working and then because they have failed to save enough, be forced to live frugally in retirement when they have more time to enjoy themselves. Conversely, they also wouldn’t want to live an unnecessarily frugal life throughout their careers in order to enjoy a lavish lifestyle that they may be unable to enjoy in retirement. In short, the main goal of life cycle finance is effectively to distribute a person’s income from the working and earning years over their entire life.

In theory, in order to accomplish this goal, individuals would borrow early in life when income and assets are low and needs are high. This would include paying for college, buying a car and purchasing a first home. Later in life when income is rising and basic individual and family needs have been satisfied, saving becomes important in order to fund the later years when they leave the workforce and rely on those assets to supplement Social Security, employer pensions and other income. That’s the theory. But as 20th-century philosopher and Yankee Hall of Famer, Yogi Berra has been attributed as saying, “In theory, there is no difference between theory and practice, but in practice there is.” In a computer model, applying consumption smoothing is relatively straightforward. In real life, however, many of the important financial choices we face are shrouded in uncertainty and fraught with risk. For instance, we can’t predict with accuracy the length or trajectory of our career earnings, the financial needs of our families, the returns we will earn on our investments or how long we will live in retirement.

In future posts, we’ll look at ways the average investor can use the life cycle model to make better financial decisions and improve the economic outcomes for themselves and their families.

The big business of prediction – Part One

Predicting where the stock market is heading has been the holy grail of financial professionals for over a century. Every year investment companies and forecasting firms dedicate enormous sums pitching their prognostications to investors, and it’s easy to understand why: the payoff can be huge. For brokerage houses and their sales representatives, it is a proven strategy for attracting uninformed investors looking to earn superior returns with minimal risk.

Unsurprisingly, the most ardent defenders of forecasting stock prices are those who make their living from it, including investment firms and financial news outlets. Most academic economists, on the other hand, are skeptical that any forecasting model—even the most sophisticated—can predict turning points in the markets. An overwhelming amount of evidence gathered over the last 80 years supports their position. A groundbreaking report titled Can Stock Market Forecasters Forecast? published in 1933 by Alfred Cowles III, an economist and founder of the Cowles Commission at Yale University, concluded, after thorough analysis, that it was “doubtful.” Since its publication, I am not aware of one credible report contradicting Cowles’ findings. Rather, several provide corroboration.

A 2012 study conducted by the Vanguard Group applied over a dozen different metrics (e.g. price to earnings ratios, dividend yield, etc.) to past stock returns for the period between 1935 and 2012. The goal was to identify reliable signals that might provide guidance for future performance. The researchers concluded that forecasting stock returns is essentially impossible in the short term. In other words, we simply have no way of predicting which way or by how much stocks will move over the next few days, weeks or months.  Furthermore, the researchers determined that even over longer time horizons of 10 years or more, many metrics assumed to have predictive value, in fact, had little to none.

In a 2015 article, Robert Shiller, Yale professor, and 2013 Nobel Laureate, wrote that after searching the news archives about the country’s major recessions beginning in 1920, he “found virtually no warning from economists of a severe crisis. Instead, the newspapers emphasized the views of business executives or politicians, who tended to be optimistic.” The almost-universally-unanticipated 2008 collapse of our country’s financial system offers a prime example. No model, including those developed at the world’s most elite institutions including the United States Federal Reserve Bank, foresaw a collapse until it occurred. Most were projecting continued GDP growth and rising asset values into 2009.

If we can guide rockets into outer space and back to earth with precision, why can’t some of the world’s smartest people using the most sophisticated technology develop reliable market forecasts? An explanation that has gained widespread acceptance is that current models are doomed to fail because they are vast simplifications of reality and cannot capture the interaction of forces that drive the markets. Instead, they rely on the conventional economic theory that assumes that the financial markets are made up of players who make decisions to buy and sell in a logical and predictable fashion. In 2000 and then again in 2008, investors worldwide witnessed firsthand the gap between theory and reality: in the real world, things get chaotic. When this happens, investors—swept up in the euphoria or panic of the moment—abandon logic and behave unpredictably.

In my next post, we’ll talk about a fundamentally new way of thinking about the financial markets.