Margin of Error -- What Talking Heads Don't Know

This could apply in the benefits or compensation world. Why? Because we look at lots of data. And, when we look at data, we often do sampling, whether we realize it or not.

But, this is my turn to rant. Why? Because it's been a while since I last ranted.

It is mind-boggling to me that most of the talking heads (newscasters if you prefer) on TV have college degrees, or for that matter, high school diplomas. They don't understand basic math.

From one of them today: "Scott Walker is ahead in all the polls we are seeing, but they are all within the margin of error, so the race is too close to call."

Think about it. If you take one poll and the margin of error is, say, plus or minus 5% and Walker leads by 51.8 to 48.2, then that poll is within the margin of error.

Note that the margin of error is based on the sample size not the whim of the pollster. 

Now, suppose that you have 20 polls and Walker leads in each one and in each one, his lead is near the outer limits of the margin of error. What does that tell you?

Well, the sample size has grown. If the sample size in poll #1 is n1 and the sample size in poll 2 is n2, etc, then the total sample size assuming that no single person was surveyed twice among the twenty polls is n1 + n2 + n3 + ... + n20. Ostensibly the margin of error is inversely proportional to the square root of the sample size. Or, in lay terms, every time the sample size gets multiplied by 4, the margin of error gets cut in half.

So, for simplicity, if each of n1 through n20 is 192, then the margin of error is roughly 7%. But, if there are no duplicates in the 20 populations, then the total sample size of the 20 is 3840 leading to a margin of error in the vicinity of 1.5%. 

So, if Walker is ahead by 3% in each of the 20 small polls, then each poll shows that the race is within the margin of error. However, taken together, the race is well outside the margin of error and they are predicting that Walker will win.

Duh!

Multiple Employer Plans are for Related Multiple Employers

Last Friday, the Department of Labor (DOL) released Advisory Opinion 2012-04A. I found it interesting because it related to some conversations that I had several months ago. It seems that for the last number of months, one of the very hot topics among retirement plan advisers for smaller plans has been multiple employer plans.

Someone had found a gimmick. You see, a multiple employer retirement plan is a single plan for employees of multiple employers. As a single plan, it needs one Form 5500, one plan audit, one plan document, etc. Each of those elements costs money. Split among lots of employers, that's a lot of savings.

Several of those advisers asked me about this approach. I didn't have statute or regulations in front of me, but remarked that I didn't think it passed the smell test and that government agencies would find a way to kill this idea. The downside of being a part of it if it was found to be non-compliant far exceeded the upside of the cost savings.

Guess what? The DOL Advisory Opinion found more than just failure to pass the smell test. ERISA tells us that a plan must be maintained by an employer or employee organization or both. Employer further includes a group or association of employers acting for an employer.

To break this down into lay terms, organizations in one multiple employer plan need to bear some relation to each other. The DOL found that in the instant plan, many employers bore no relationship to each other.

Bottom line, while the Advisory Opinion only carries limited weight and does not specifically affect qualification under Sections 401 and 501 of the Internal Revenue Code, be assured that Labor and Treasury read each other's pronouncements related to retirement plans.

The downside may have exceeded the upside.

Dodd-Frank Section 953(b): A Legislated Disaster

I recently wrote this article for BNA.

It is © 2012 Bloomberg Finance, LP. Originally published by Bloomberg Finance LP.  Reprinted with Permission. The opinions expressed are those of the author.

You may view the article by clicking on the link below, but you are not authorized to edit, reproduce or distribute copies of the article without the express written consent of Bloomberg Finance LP and the author.

Here is an excerpt:


In my experience, what I would describe as reactionary laws are bad laws. In other words, when Congress
runs across a particularly unforeseen problem, it has a habit of over-legislating in an effort to solve that
problem. I’m not saying that every bill that is written this way is bad, or that even among the bad bills that
the entirety of every bill is bad, but reactionary bills tend to have some horrible provisions. Perhaps this is
why we are burdened with Section 953(b) of the Dodd-Frank Wall Street Reform and Consumer Protection
Act.

The requirements of this provision seem simple enough. Each issuer [of a proxy] is to provide three
items:


You can read the full article here.

Don't Overestimate the Value of Survey Data

I saw some interesting data this morning. According to their quarterly Retirement Pulse Survey, Charles Schwab found that 35% of investors consider protecting their retirement assets more important than increasing them. Conversely, 8% believe that increasing them is more important than protecting them. What about the other 57%?

Unfortunately, the write-up that I saw has only sparse data (not a Schwab write-up, so I am specifically not placing blame on Schwab).

In any event, the headline from the Plan Sponsor News Dash was "Americans Most Want to Protect Retirement Assets From Risk." While that may be true, the data is not conclusive to this. 57% gave some other answer and I don't know what those answers are.

One can easily rationalize. Older plan participants probably fall into 3 categories:

• Those who feel their assets are or will be sufficient to retire
• Those who think they are close to where they will have sufficient assets to retire
• Those who either think or know that their assets will not be sufficient to retire

That final group needs to increase their assets. There are exactly two ways to do this: save more and get better returns. Being risk-averse just won't cut it. This is not me advising them, this is common sense. 

The News Dash write-up suggests to me that younger plan participants are more risk-averse. Could this be because they have not seen the big market booms in their investing lifetimes. As an investor, even in good times, the 2000s have not been pleasant. While there have been lots of good months, there have been lots of bad months. At this point in my life, volatility is not my friend.

So, going back to the data, taken in chunks, it could be misleading. I would hope that without closer review that plan sponsors don't put too much credence in the headline.

However, would it not be worth it for a large plan sponsor to learn the attitudes of its own plan participants? Are they risk-averse? Or, are they risk-takers? Shouldn't the fund lineup be commensurate with the goals of plan participants? If it's stability they want, shouldn't the plan's Committee have a lineup with a higher propensity of lower volatility options? Conversely, if the company has a bunch of natural risk takers, is it not appropriate that the find lineup be reflective of that?

Perhaps? What is the role of the Committee? Ultimately, they are to act in the best interests of plan participants. Nobody knows exactly what that means. But, it seems to me that meeting the needs or perceived needs of plan participants is not contrary to that role.

So, don't overestimate the value of broadly available data. I suggest you collect your own.

Asymmetric Risk Situations

These days, a good bit of my consulting practice is dedicated to defined benefit pensions and executive benefits and compensation. Over the last several days, in reading the news, it occurred to me the significant asymmetries in the two practice areas.

For those who have been living under a rock, certainly, at least in my opinion, the biggest business news has been the trading debacle at JPMorgan. Ina Drew, a long-time employee of JPMorgan who oversaw the trading unit is being held responsible. According to JPMorgan's proxy issued this spring, Ms. Drew earned approximately $14 million last year (frequent readers may know that the total annual compensation disclosed in a proxy may not be an excellent representation of the actual amount earned) making her, according to the proxy, the 4th highest compensated employee of the bank.

By all publicly available information that I could find, Ms. Drew has a reputation as being one of the best at her field. This from a Reuters article, "Until the loss was disclosed on Thursday, Drew was considered by some market participants as one of the best managers of balance sheet risks."

For full disclosure, I was once an employee of JPMorgan. I became one when my employer at the time was acquired by a JPMorgan unit. My employment there ended when the division of which I was a part was sold by the company. As a result of JPMorgan's incentive compensation plan which requires certain employees to defer parts of their incentive compensation ( the plan has previously been disclosed publicly), I have control of a relatively small number of shares of JPMorgan stock. This post is neither intended as approval nor condemnation of the company or its employees. JPMorgan happens to be in the news, currently, but on a different date, I could have chosen a different company.

So, where am I headed with this? Pension plans and individual (executive or commissioned) compensation represent entirely different risks. Each is asymmetric, but in opposite directions. So, this post is about behavioral risk management. It could easily be extended elsewhere, but I have no expertise in social psychology, for example (you may argue that I have none in the fields that I am writing about either, but I am going to defend that I have some, at the least).

Under current US pension law (see for example, Internal Revenue Code Sections 430 and 436), if we leave out transition rules and there are many, non-governmental qualified defined benefit plans typically get treated differently at funding levels of 60%, 80%, and 100%. Speaking in significant generalities, if your plan is less than 60% funded, there is not much that you can do with it. Participants generally cannot accrue new benefits, the plan sponsor can't improve the plan; essentially, all you can do is fund it, and the funding rules for plans less than 60% funded are pretty onerous (not judging the appropriateness of this part of the law here). Once a plan gets over 60% funded, but less than 80%, things get somewhat better. Restrictions are less. Between 80% and 100%, things are generally pretty uniform and a plan sponsor can operate on a normal ongoing basis, so to speak (this is not intended to be a course in pension funding law; it's illustrative). If your plan is better than 100% funded, it may be unusual these days, but funding gets easy. Note that there is no nice threshold in excess of 100%.

What does this tell us? If your plan is less than 60% funded, there are no more downside thresholds. The sponsor, oversimplifying significantly, has little downside risk. Between 60% and 100%, there is both upside reward and downside risk, and while they are not identical, there is certainly a degree of symmetry. Once your plan is better than 100% funded, there is almost no upside reward, but there is downside risk.

These risks and rewards should inform the asset allocation decisions. They should inform the fiduciary decisions and, in my experience, they often do.

Let's turn our discussion to compensation, specifically that of two types of individuals: 1) top executives whose incentive reward potential often dwarfs their base pay, and 2) commissioned salespeople whose commissions have the potential to exceed their base pay or are their entire compensation.

Here are some facts about the compensation of many of the people in both of those groups:

• There is little, if anything, that applies in practice that limits the upside of their incentive compensation. Even to the extent that it is limited, those limits are very rarely reached. (Some plans are not designed this way, but many are.)
• Unless a plan has clawbacks (a means for recovery of compensation for various reasons, often related to fraud or other criminal activity), employees don't receive a negative bonus. At least, I have never seen it.

In the context that we used for pensions, there is plenty of upside reward potential, but there is little downside risk. Suppose I am a commissioned salesman. Further suppose that my compensation is entirely based on a percentage, 3% for example, of my sales. The smallest that my compensation can be is $0. I cannot sell less than nothing. The most that my compensation can be is 3% of infinity. That's a big number. I have an incentive to take risks. 

In their best-selling book, Freakonomics, authors Levitt and Dubner discuss this in the context of real estate agents (excerpts can be found here). Oversimplifying, a real estate agent can sell two types of homes: someone else's or their own. When selling someone their own home, an agent has an incentive to sell for the highest price. For each additional dollar of sales price, the agent receives nearly 100 cents (their broker and the agent on the other side each receive something). When selling a client's home, out of every additional dollar of sales price, the agent gets about 3 cents. According to Levitt and Dubner (and I agree), the agent selling your home has an incentive to get sell your home quickly. If they can get an additional $300 for getting you an extra $10,000 in sales price, the system motivates them not to do it because $300 doesn't mean anywhere near as much to them as $10,000 does to you. Speed is more important. But, if they are selling their own home, that $10,000 represents more than $300,000 in sales of other people's homes. If they can afford to, that system motivates them to hold out for more.

Executive compensation is not quite the same. But, often, it's closer to the real estate agent model. Incentive payouts for many CEOs and their direct reports is discretionary. It may have theoretical limits, but according to dozens of proxies that I have examined (you can get proxies at the SEC website),an executive who has a fantastic year may have their compensation exceed even the upper limits specified in a plan. Upper limits are often more than twice a target. The incentive is there to take risk. 

Why do people play the lottery? It's a losing proposition ... for all except the winners. The upside is huge, however. But, it's a game of chance. You know that going in. And, if you play, you are willing to risk some amount for a huge potential upside. 

Should you treat your pension plan as a game of chance? I don't think so. The system has been set up against it. The system has rules and those rules should, in my opinion, inform your behavior. Whether the current system is the correct one is irrelevant. It is the current system.

Should your executive compensation program be a game of chance? Should it contain asymmetric incentives? When I am a shareholder with an opportunity to vote my shares, my bias is against it. I prefer the companies of which I am an owner to not take inappropriate risks. It's human nature. Even for an incredibly ethical person, incentives matter. If you give me an asymmetric bet, and that bet is in my favor, if I use the logical part of my brain only, I should take it. We would like executives to use logic.

When we give them an asymmetric risk opportunity, are we not asking them to take perhaps inappropriate risks? Are they risks that you wouldn't take in your pension plan?

Hiatus

I am having to take a short hiatus from blogging while someone tasked with this chore determines whether or not it constitutes impermissible internet guidance under FINRA guidelines. I hope to return to blogging soon.

Statistics ... Disraeli was Correct

Many Americans attribute the quote to Mark Twain. Twain, on the other hand, attributed it to former British Prime Minister, Benjamin Disraeli. Disraeli was purported to have written (or spoken): "There are three kinds of lies: lies, damned lies, and statistics."

Let's not worry about who actually coined the phrase. Even so, what does it have to do with our usual subject matter here? In the benefits and compensation arena (and many others), people love statistical data. They seem to love to create it, to cite it, to reference it, and to make decisions from it.

I beg them not to. Consider such data, but consider it as a point of reference. Use it intelligently.

I saw a survey last week or the week before that asked three questions of its respondents. Roughly recalling the questions, respondents were asked whether they were going to have enough money in retirement to make it to ages 75, 85, and 95 respectively. Less than half said they would have enough to live happily until age 85. The article reporting on the survey then told its readers that most Americans won't have enough money for their life expectancies.

Excuse me! Where did that come from? What made age 85 the life expectancy of any, let alone all, of the survey respondents. Were the respondents all the same age? Were they all the same gender? How many of them even know how much money they will need?

Just this morning, this summary of an article appeared in my inbox:

Fidelity Investments reported the average 401(k) balance in 401(k) plans it administers rose to $74,600 at the end of the first quarter, an increase of 8% from the end of the fourth quarter 2011. The first quarter balance also represents a 62% increase since the end of the first quarter 2009, often considered the low of the 2008-2009 market downturn, when the average balance was $46,200.

This is not to be construed as a condemnation of Fidelity. In fact, I feel quite certain that what they have said is correct. What concerns me is how others will use the data. Who will cite this information and how will they use it?

Let's consider what has happened between the end of the first quarter of 2009 and the end of the first quarter in 2012. I'm not looking for just investment performance and deferral behaviors, but how about external factors.

• After the severe market losses from 4th quarter 2007 through 1st quarter 2009, many people who had been considering retirement were forced to defer it. These would be almost exclusively in the older group of workers. As a group, we would suspect that these would be people with higher account balances who were not withdrawing their 401(k) money from Fidelity. Does this not skew the data point upward?
• As more companies freeze defined benefit plans, many of them have increased their 401(k) match. The way I see it, this makes it more likely that participants will take full advantage of the match. So, their deferrals will increase and the matching money will increase. Does this not move the data point upward?
• Does Fidelity administer the same plans that it did three years ago? I'm sure that many are the same, but not all of them. Vendors gain new clients and lose existing ones. They don't all have the same participant profiles. I don't know which way this moved Fidelity's data, but it certainly moved it.

Let's go back to life expectancy. Let me ask you some questions. What is your life expectancy? Do you know? If you think you do, on what do you base it? Life expectancy from birth? From now? Is it based on IRS tables? Is it based on some other mortality tables? Newspaper articles? A guess? Does it consider your health? Does it consider the life spans of your ancestors? Does it consider your gender?

I am going to tell you something. Your life expectancy is a nice number, whatever it is. It may be the best estimate (at a point in time) of the age you will be when you die. That said, unless we are using a lot of rounding, you will not die at your life expectancy. That's right, if we are precise, you will not die at your life expectancy. 

If we were to choose a mortality table and calculate your life expectancy (or mine), it might tell you that your life expectancy is another 20 years (rounded). Or, if you are more precise, it might tell you that your life expectancy is another 20.3 years. Or 20.27 years. Or, 20.26637185943 years. 

Another table might generally increase those numbers by several months, or even years. Another one might shorten your life expectancy. In any event, given a table, your life expectancy would have your life ending on a particular day at a particular time. 

It's not going to happen.

But, people using statistical date cite life expectancy as if it were the most relevant point in time. 

Statistics are very useful. They are especially useful when they are not misused.