Today’s read uses a specific example to highlight a broader problem that concerns me: the misleading use of statistics. Ezra Klein’s article from Vox discusses a recent statistic from Oxfam which states that the combined wealth of the richest 1% will be greater than the combined wealth of the remaining 99% within the next year. Taken by itself, this is indeed an alarming statistic, but as Klein illustrates, you have to drill down into Oxfam’s methodology to really see what this statistic is telling us. The article spells it out in detail, but the upshot is that the criteria used by Oxfam to calculate wealth takes into account debt as well as assets. What this means is that a poor rural resident of an underdeveloped part of the world who has no debt is considered “wealthier” than a resident of a developed nation whose debt exceeds her income. In other words, by Oxfam’s calculations, you could be making $150,000 a year – but if you owe $500,000 on a mortgage, you have a negative net wealth, which means you are “poor.”
It’s well worth reading this article to see what calculations went into the statistic, and for Klein’s analysis of what we can learn from the overall Oxfam report. I have no doubt that inequality is an enormous global problem – but even when a statistic seems to support my position I want to make sure I am understanding that stat correctly. Sure, stats can make great soundbites, but I wish more people would make sure they knew what the stats they quote really mean.