Policy & Politics

My last blog looked at how U.S. federal government outlays were distributed in 2015 – one of the few situations I’ve found where a pie chart actually works! But taking a deeper look at the issue, and especially considering federal spending trends over time, we’ll see that pie charts are severely limited. We need a better presentation approach, and in the process we’ll come face-to-face with the limitations of data visualization.

You know how much I hate pie charts – in my book, "Painting with Numbers," using a pie chart is Deadly Sin #10. But occasionally – very occasionally – a pie chart tells an important story. Current federal government spending is such an example – let’s learn something about federal spending AND get some insight into the ugly, the bad, and the good of data visualization.

I don’t usually make policy statements in this blog, but sometimes a simple and clear presentation of data says everything that needs to be said. The trend in U.S. manufacturing jobs over the last 70+ years is a great example.

For New Year’s reading I commend “What Kind of ‘Jobs President’ Has Obama Been – In 8 Charts,” from the NPR website. The eight graphs referred to are straightforward and easy to understand. They show critical data in a journalistically ethical way – a characteristic in very short supply these days. With one exception that’s all too common in data visualization today…

A couple of years ago, I wrote a series of blogs about using data visualization to appreciate the fickleness of the U.S. electorate. A group of tables and graphs examined the ups & downs in the numbers of Republicans and Democrats in the House of Representatives since 1952, compared to the political party of the incumbent president. Well, I’ve updated the graph for the 2016 election, and extended the analysis back to 1920. Read on and enjoy!

In the current presidential cycle, there’s been much blather about “wasted votes” and “strategic voting.” Is there really such a thing as a “wasted vote”? Well, maybe, but it’s not what you think – at least if you consider the example of Norman Thomas.

To a successful businessman, words must mean what they mean, especially when they are describing complex financial and numerical matters. That’s why Mr. Trump’s endlessly-repeated assertion, “… and Mexico will pay for the wall,” deserves examination.

This second post in a short series on TV news innumeracy looks at an even more ludicrous example – the notion of “bellwether” counties. The pundits seem to have an obsession with counties – or towns, or even precincts – that have voted for the winning side in several consecutive elections, as if that information actually meant anything. Well, it doesn’t, and the reason it doesn’t has implications for financial analysis.

In last night’s TV coverage of the Iowa caucuses, two words kept coming up – “winner” and “bellwether” – showing that when it comes to the real meanings of numbers as well as words, even the "experts" don’t get it.

The Powerball payout has reached the jaw-dropping, mind-numbing (insert your favorite hyper-adjective here) level of $1.4 billion. I must speak: state lotteries are one of the most sinister and unfair ideas our elected officials have ever had. And simple, straightforward numerical thinking would have clarified everything. Let us count the reasons why I feel this way:

In an interview today National Public Radio reported on home construction data that the U.S. Commerce Department had been reporting erroneously for ten years. Not a sexy topic, but read on, since it addresses the whole subject of why we bother to collect data, and whether we need to spend more of our tax dollars in that effort.

Dishonesty can take many forms. Many are easy to spot, or at least will get caught out by a little research – or by the increasingly large number of journalists and organizations focused on fact-checking. Other forms are subtler. My “favorite” with respect to numerical information is cherry-picking – using a few carefully selected facts to support or refute an argument. The facts cited are usually correct, and the presenter might be well-intentioned, but the approach is intellectually dishonest. Let's consider some examples...

In an “Investment Writing” post, Susan Weiner observes that the frontrunner presidential candidates in both parties are the ones that speak the simplest English. We can assess the complexity of writing or speaking with metrics like the Flesch-Kincaid Grade Level score. Should we have similar metrics for our quantation?

In a Washington Post op-ed piece, Catherine Rampell takes on presidential candidates pledging to “run government like a business,” as they advocate inane policies like 10% across-the-board cutbacks. She identifies several federal government situations where they should be spending more money, not less. She’s right, but it’s not just about spending money to make money. Well-run businesses use metrics intelligently.

I love metrics. I love keeping score. And as a lover of metrics, I was delighted by the Bipartisan Policy Center’s announcement yesterday of a new metric: the Healthy Congress Index (HCI)! But as enthusiastic as I am about this new metric to assess the productivity of the U.S. Congress, there’s a fundamental problem that the BPC really needs to address.

The efforts by both the Obama administration and the Republican-controlled Congress to tinker with the employer mandate won’t work. The problem is that the efforts are merely symptoms of what is not only a fundamental flaw in the ACA, but a flaw in many incentive compensation plans: excessively binary schemes.

Let’s try an unusual, but sometimes effective technique: recasting the data. Rather than looking at individual presidents and individual elections, let’s look at – for want of a better term – “dynasties,” that is, continuous periods where a single party controlled the presidency, and see how that party fared in the U.S. House during that dynasty:

Pres. Obama’s has just threatened a “proportionate response” to North Korea’s cyber-attack on Sony Pictures’ computer systems. I’m at a loss to understand what he really meant by that, or why he chose the words he did. In quantation, getting the words right is critically important – the numbers mean nothing without them. So today’s word is “proportionate,” a word with obvious quantation implications.

Since my last post was so negative, and so critical of the stuff given to us to read, it’s a pleasure to encounter a good example of quantation, even on an unpleasant subject. I’m referring to a Washington Post-ABC News poll of public opinion related to the recent Senate report on torture and the CIA. Here’s what I liked about the survey design:

In my last post we looked at using a table, instead of a graph, to present a more complete, precise, and arguably understandable picture of how the composition of the U.S. House and the president’s party interrelate. And we were still able to take advantage of data visualization! This time, let’s take a look at using one of the most powerful tools in the quantation arsenal – the humble ratio – to really get a message across.

We’re back, and I’m hoping you all enjoyed the holiday. As I suggested in the last post, let’s try using a table instead of a graph to see how House of Representatives election results correlate with the incumbent president’s party!

The composition of the U.S. House of Representatives provides great material for data visualization. We’ve already produced a graph (click here for the original post, here for the improved version) that, like the Minard graphic of Napoleon’s march to Moscow popularized by Edward Tufte, presents seven types of data in a single two-dimensional space. It paints a rather complete picture. But does it really feed the bulldog?

I’m including this post in the series because of the extremely insightful suggestions offered by my new friend, Hicham Bou Habib, on LinkedIn’s Certified Corporate FP&A Professionals group discussion thread.

At last week’s terrific Association for Financial Professionals (AFP) national conference, there was much discussion of “data visualization,” a major information-presentation buzzword these days. Last week’s U.S. elections seem to provoke the same urges to barrage us with graphics. But do all these beautiful pictures really get us anywhere?

A fascinating piece in a recent Washington Post draws a striking comparison between income inequality and political polarization. It suggests a high correlation between greater inequality and more polarization. That’s all well and good, but it’s all meaningless if you don’t hypothesize a causal relationship between the two.

During a week in which the most hotly debated news topic has been the quality of decision-making by senior federal government officials, my nominee for the worst decision is VA Secretary Eric Shinseki’s parting gesture not only to cancel performance bonuses for senior VA executives, but to ban patient wait time as a measure used in performance evaluations.

What are metrics for? When properly used, most are nothing more than a relative tool for comparing one time period – or company, or country, or person – to another, or actual results to planned or expected results. They are not an absolute score, meaningful on its own.

“How Useful a Measure Is GDP?” is a thoughtful and thought-provoking article by Diane Coyle. She observes that the concept of GDP has come under fire recently by those who argue that it doesn’t really measure well-being – that it doesn’t measure, for example, happiness, or income distribution, or sustainability.

Does raising the minimum wage have any bad side effects? George Will, in his op-ed piece in yesterday’s Washington Post, gives about fifteen reasons why raising it is the wrong thing to do. There are valid policy reasons on both sides of the issue, but Will highlights some issues that have to be faced. The numbers, and the process generating those numbers, can’t be ignored.

In clear, effective quantation, the words we put around the numbers are often as important for audience comprehension as the numbers themselves. In this morning’s Washington Post is an excellent op-ed piece, “What to call this economy?” by Robert Samuelson, where he observes that we lack the economic vocabulary to describe the current state of the U.S. economy.

Sometimes, the numbers are not the numbers: they may be correct, and they may be understandable, but they don’t really address the question being asked. A good example of this dissonance is Obamacare and the frequent assertion that it is absolutely budget-neutral.

When done properly, numbers provide a profound glimpse into the future. Here are two graphs from a Washington Post story about the possible implications of China’s recent changes to their “one-child” policy.

The Washington Post recently ran a front-page story headlined “106,000 have signed up for health coverage,” with a sub-heading of “Enrollment less than predicted.”

Much has been said about how tight-lipped the Obama administration has been about the enrollment numbers since October 1 for the private exchanges mandated by Obamacare. There is a lesson here about communicating, that applies just as powerfully to quantation (the act of presenting numbers) as it applies to all other types of communication.

I recently downloaded a Wall Street Journal article about the congressional food fight over spending and the debt ceiling. I learned that “on Oct. 17 [the Treasury] would be left with only about $30 billion.” I went on to learn that this amount was approximately equal to the Harvard University endowment in 2011, and the cost of Hurricane Ike in 2008.

The words we wrap our numbers in can play a key role in how well those numbers are understood. A great example of this is the question of “payroll taxes” – the payments employees and employers make toward Social Security and Medicare. They are a major topic in the raging debate about the “fiscal cliff,” but I have to ask: Are “payroll taxes” really taxes? The answer to this question has important public policy implications; it’s not just a question of semantics.

Last post, we talked about the miracle of compound interest, and how that “miracle” gives you such a strong incentive to start contributing early to 401Ks, IRAs, or any other pension or savings plan. In this post, we’ll talk about another powerful incentive driven by the “miracle” – the fact that in a pension plan your money compounds at pre-tax rather than after-tax rates. For most of you, this will make an even bigger difference.

In last week’s post, we discussed using metrics to help understand past and forecast spending on Social Security (SS). These metrics are important because it’s hard for anyone to grasp raw numbers this large — annual SS benefits are expected to top $1 trillion (yes, trillion!) around 2018, for example. So metrics like spending as a percentage of GDP help to put raw numbers in some context.

In recent weeks, I’ve promised that some future posts will discuss both Social Security and general U.S. government spending. In this post we’ll do both, as we take a look at trends in Social Security payments. First, let’s look at total dollars of Social Security payments historically from 1970 and projected through the year 2022.

This post will not have a single number in it. Yesterday morning’s edition of The Washington Post ran a story headlined, “Social Security’s financial forecast gets a bit darker.” The sub-headline adds that Medicare is not looking much better. The story reviewed the annual forecast of the trustees overseeing the Social Security and Medicare trust funds, a forecast that looks ahead to the funds’ solvency as far out as the end of this century.

As I said I would do last week, I now offer the first of a few posts that I hope will provide insight into the U.S. federal government’s fiscal situation, from the perspective of clear quantation. Consider the following graph (in which I break my own rule and use a pie chart) showing the distribution of federal government outlays projected for fiscal 2012 (the 12 months ending 9/30/12).

Sometimes a clear presentation of numbers can really put things in perspective, and the absence of such a clear presentation can cause us to lose sight of what’s important. Put another way, good quantation can not only enlighten us, but first it simply makes us more aware.

Few public policy issues have generated as much verbal hysteria, irrational claims, and downright incorrect information as Social Security. And that’s saying a lot. This is a great topic for “Painting with Numbers,” because it’s just not that complicated to understand, provided the numbers are presented clearly and coherently, and that is what this site is most interested in.

In today’s broadcast of Marketplace on NPR, David Brancaccio led a great discussion about using statistical indicators to predict presidential elections. Which works best? GDP? Disposable income? American war casualties? Unemployment? Gas prices? Durable goods spending?

I just saw a 7/1/11 CNN interview with Scott Hodge, the President of the Tax Foundation, on the subject of “Who Pays Income Taxes in America.” I won’t elaborate on Hodge’s position here – you can see the video for yourself – but in the course of the interview CNN put the following slide up on the screen, using data provided by the Tax Foundation...

In the current debate about the U.S. federal government’s fiscal predicament, there is much rhetoric, from both sides of the aisle, about the need to “rationalize” and “simplify” the federal income tax code, and lower tax rates in the process. The real issue, of course, is the deficit, and the only way to reduce a deficit is to either spend less or tax more. So how can “lowering tax rates” help solve the problem?

The word for today is context. Yesterday’s New York Times ran a story about a bill in the New Jersey state legislature about to become law, which will reduce the state’s cost of benefits for government employees and retirees. The fiscal condition of the states is a burning issue nationwide, and deserves a clear and concise airing for interested citizens.

A headline in today’s Los Angeles Times reads, “Boehner demands trillions in cuts in exchange for debt vote.” Wow! But wait! It gets even more specific! Since the cuts the Times cites Boehner as demanding cuts greater than the increase in the debt ceiling being negotiated, that somehow means he’s demanding cuts of “$2 trillion or more.” Double wow!! (Have I used too many exclamation points?)

On this morning’s “Meet the Press,” the usually oracular Alan Greenspan was unusually plain-spoken. He suggested that while tax increases rarely achieve their intended deficit-reduction purpose, given the U.S. government’s current deficit troubles, it might be best to allow the Bush era tax cuts (“BETCs”) to expire for all taxpayers, not just those in the upper income brackets.

If you can understand the federal budget from what you see and hear from newscasters and soundbites from our legislators, you’re more astute than I. So take matters into your own hands: go straight to the source, and you’ll be amazed by what you can learn.

In the mid-1980s, I joined Oracle as Corporate Controller. Not only was I hopelessly under-qualified for that job, but the entire finance and administration function was held in generally low repute and didn’t add much value to Oracle’s operations. The principal problem, truth be told, was simply understaffing in an area not appreciated in a newly public company where engineering and sales were kings of the hill.

In one of my posts last week we met two amazing yet confusing numbers from the Website, “The Debt to the Penny and Who Holds It.”

First, the good news: there is a group of U.S. Senators called the “Gang of Six” – three Democrats and three Republicans who are addressing the federal deficit issue in a constructive, bipartisan, and I hope sensible way. They are filling a leadership void that has existed in every branch of the federal government. Uh, am I being too subtle here?

If you are looking for a frighteningly fascinating Website to visit, I recommend “The Debt to the Penny and Who Holds It.” The site is operated by your and my U.S. Treasury Department, and if you’ve ever wanted to see what at an actual fourteen-digit number looks like (plus two decimal places), look no further.

I am a resident of, and a taxpayer in the State of California, the 50th least likely state to declare bankruptcy, and in the last 24 hours I have learned something wonderful. The governor and the legislature just announced a budget deal to address the $26 billion deficit staring the state in the face.

“Can’t anybody here play this game” is one of Casey Stengel’s best-known profound observations – and he made many of them – when he found himself having to watch the team he managed, the brand-new New York Mets of 1962, attempt to play baseball.

There’s a folksy old musing that goes something like this: “Why do dogs chase cars? I mean, what would a dog do if it actually caught one?” Excellent question. What would happen? Best case, the dog gets some exercise, and motorists get a little entertainment value from watching a 30-pound spaniel try to hunt down and kill a two-ton metal beast.

A while ago, I wrote a deliberately uninformed post, suggesting that the whole Bernie Madoff fiasco wouldn’t have happened if Madoff’s fund had had an audit conducted by a reputable firm, and that this should be a requirement for all investment funds (see “Madoff and the ‘Idiot Plot’” 12/17/08).

Recently, I took a bank CEO to task for asserting that you could actually identify which dollars in your bank account were used to pay which bills, thereby insulting the intelligence of many (see “All Dollars Are Green,” posted 2/15/09). But corporations aren’t the worst offenders here. That award goes to state and federal legislatures.

Just the other day a senior corporate executive reminded us why much of the public thinks of corporate executives as not only greedy, but also contemptuous of the public’s intelligence.

Today’s post by Michael Arrington of “TechCrunch,” is on Newt Gingrich’s call for the repeal of the Sarbanes-Oxley Act. Often referred to as “SOx,” this law was enacted in 2002 in the wake of some sensational accounting scandals, to ensure stricter compliance with accounting standards by U.S. public companies. Very eloquently, Gingrich asserts that SOx has accomplished very little at very great expense.

This morning on Meet the Press, Colin Powell announced his support for Barack Obama. His comments about both Sens. McCain and Obama were balanced and largely positive, but two factors seemed key: the negative tone of the McCain campaign, and the choice of Sarah Palin as running mate – a choice you could argue was motivated in the first place by the tone of the campaign.

Phred Dvorak recently wrote an excellent article on executive compensation disclosures in public company proxy statements (WSJ, 3/21/08). Her main theme was that in the face of SEC requirements for fuller disclosure of executive compensation, companies have provided so much additional verbiage that normal humans can no longer make any sense of the disclosures. Amen.

First of all, if you think I’m actually going to offer an opinion on this subject, you’re crazy. Oh, no, no, no. We’re here to help you form your own opinion. You can do this in Four Easy Steps, by finding out...

In yesterday’s presidential debate, Barack Obama attributed the current financial crisis to eight years of Republican misrule and shoddy regulatory practices.

Since this is my first posting on “Painting with Numbers,” it seems completely appropriate to talk about words instead of numbers. And just one word, at that. And that word is. . . “BAILOUT”! OK, there’s another word, too: “SPEND.” What does this have to do with “numbers”, and how we “paint” with them? A lot.