Making Arguments with Made-Up Data

Economic inequality around the world has been increasing in recent decades. It’s tricky to find the right balance between sharing the wealth and reducing the incentive to work and innovate. This is an important debate, but it is filled with nonsense arguments using made-up data. For some reason, people are impressed by arguments that include some sort of numerical evidence, even if the numbers make no sense.

In a discussion of government spending and public debt, I once heard someone say that every dollar the government spends gets re-spent seven more times in the economy. The implication is that government spending provides a free multiplier effect, but just a little thought shatters this dream. If the government were to borrow and spent a few trillion dollars, it wouldn’t somehow grow and make us all rich. But this made up statistic seemed to win the argument at the time.

A widely-cited web site is the Global Rich List (that has disappeared from the internet since this article was written). It purports to tell you where you stand in the world based on either your net income or wealth. For amusement, I punched in that I was American (didn’t feel like scrolling to find Canada) and earned a net income of US$50k. The site told me that only 18,653,583 people in the word have at least this net income. Let’s round this up to 19 million.

I understand that big numbers make most people’s heads spin, but this struck me as a suspiciously low number. I wandered off to Wikipedia’s page on U.S. personal income. We have to be careful because it gives gross income figures rather than net income. The chart says that more than 35 million Americans make more than $75k. Presumably, these people net more than US$50k. And this is just the U.S. What about Canada, Australia, Europe, and the wealthiest in Russia, China, and India? The world-wide number has to be far greater than the 19 million reported by the Global Rich List.

Now the purpose of this web site is marketing. They want to drive donations to a charity. Maybe getting the numbers wrong actually helps with this goal. I’d like to think that they’ve simply made a mistake and would fix it if they knew. It’s possible that few people have noticed the problem and none have pointed it out before now. What troubles me most is that there is little incentive to fix the problem. Few people will notice the error, and charitable donations are flowing in.

Some say we’re in a post-factual world. The fact that the Global Rich list site just sits there pumping out bad data with no negative consequences seems to support this idea. I try to do my part in promoting rational discussion by rejecting arguments based on bad data whether they support my point of view or not. More of us need to think critically about the statistics we hear and reject them if they make no sense.