Is this good or bad?
Mark Twain is often associated with the quote:, “There are three kinds of lies: lies, damn lies and statistics.” Twain attributed the quote to nineteenth century British conservative politician and former prime minister, Benjamin Disraeli. There are variations of the quote stated by a number of people and it is not exactly clear who first uttered these words/came up with the thought.
It really doesn’t matter who originated it, there is a large element of truth in the quote.
Recently I have seen memes on Facebook that seem to indicate that one politician or another is directly responsible for a particular set of economic numbers. These numbers can be either good or bad.
One Facebook meme that caught my eye was posted by a friend who agreed with the sentiment that President Biden was responsible for the current high rate of inflation. The meme used statistics and a chart showing that the inflation rate was 1.4% when Biden became President and then it was 8.3% in August of 1922. The accuracy of the numbers (statistics) is not my point here. Even if they were correct, the numbers only show part of the story.
I am not sure why my friend posted this meme in September, 2023, over a year after the numbers cited. Perhaps the August 2023, inflation rate of 3.7% did not sound bad enough?
There is no mention of the fact that the low inflation rate at the beginning of Biden’s term was probably driven more by the covid pandemic (and related shutdowns) than the wise economic policies of the previous administration.
Additionally, the meme avoided other figures that showed progress during the Biden years. These include: Unemployment (Down from 6.3% in January 2021 to 3.8% in August 2023; and growth of gross domestic product which increased from -2.8% in 2020 to a current estimate of + 2.2% annual growth for 2023. According to the Bureau of Labor Statistics. wages and salaries increased 4.6 percent for the 12-month period ending in June 2023 and increased 5.3 percent for the 12-month period ending in June 2022.
So, is the economy good or bad?
The economy is often a mixed bag. It is also driven by a number of variables, only some of which can be impacted by government action.
Gasoline prices are currently at an all-time high. While it is easy to blame the government, what impact do private interests play? Why are energy companies recording record profits? Why is OPEC restricting oil production?
One of my favorite quotes that is certainly relevant to the economy and associated statistics is, “For every complex problem there is a simple answer….and it is wrong.”
Some people don’t even go as far as endorsing memes. They rely on bumper stickers to address complex issues. As aways, the important issues of the day (any day) are very complex and require much thought and analysis by people in the know.
Are statistics at all useful? Yes, they are very important. So important in fact that without quantification and recording of details there can be no facts applicable at a macro level, only beliefs. Beliefs do have a place in our personal lives. However, void of the facts that only accurate statistics can provide, personal beliefs are very little help in addressing macro subjects such as climate, the economy, or societal trends.
So, what is the problem here Jim? Part of the problem is that people often start out with a belief and then find the “facts” that support said belief. Statistics being one of the strongest kinds of proof.
The other commonly used method is ancedotal first or second-hand experience. Anecdotal evidence can be useful on a personal level, but the application of this “wisdom” derived from antidotes is only useful more broadly if it is substantiated by statistics. In short, we need to know if an example is a real trend or circumstance or just a one-off occurrence.
Another problem is that statistics are by their very nature complex. Take unemployment for instance. The U.S. Federal Government (Bureau of Labor Statistics) has several different definitions of “unemployment.” The most commonly used is called U-3 which includes only those people who are actively looking for work. Retirees like me are not included as being “unemployed” using this definition. Another BLS metric is U-6 which includes people on the “margins” which includes those discouraged, underemployed, working part time and disabled. Some economists say this rate (which is always higher than U-3) is a more accurate measurement.
Unless the reader fully understands the data being presented to them, they are easily misled. In most cases we need “Experts” to help us maneuver through numbers to get to the “truth.”
One number often tossed around is the number of undocumented aliens living in the U.S. The U.S. Department of Homeland Security reports that in January 2021 this number was 10,220,000. I’m not sure how DHS counts these people. But even if we accept their number as being accurate, this still begs the question: “Is this good or bad?”
10,200,00 is a lot of people. Only 9 states have populations greater than this. On the other hand, it is only about 3.1% of the total population.
The number taken alone is not particularly insightful. For instance, this number can be used to show that even after 4 years of effort to get rid of undocumented aliens, the last outgoing administration left a huge number of undocumented aliens in the US when they left office. Conversely, the number is less than what it was four years prior thus showing some “progress.” Not considered in this number were the important factors like age, sex, home country, and most importantly, the reason why these people were willing to risk arrest and/or deportation.
Like all important issues, undocumented aliens, and the larger issues of legal immigration and refugees, is extremely complicated. Statistics can play an important role in finding solutions, but only if used by “experts” who have extensive knowledge of the myriad of numbers related to the issue.
Sadly, virtually all politicians lie to some degree or other. In a democracy it is almost impossible to get elected if one really, “Tells it like it is.” Liberal politicians are not likely to admit that they cannot pay for all of the social programs that they support. Conversely, conservatives like to believe that people really don’t need to pay as much as they do for taxes and that giving more money to the wealthy will “trickle down” to the rest of us.
Dictators of course, are not bound by any tie to the people they rule. Often people who live under dictators just assume that what they are being told by their “leaders” is not the truth. They may not like it, but, short of a revolution, they really have no say in the matter. Statistics produced by regimes headed by a dictator are not reliable, there are no checks and balances.
Mark Twain differentiated between “lies” and “damn lies”. The difference between “Lies” and “Damn Lies” is one of those areas where you have to concede that you know it when you see it. The difference is subjective.
“Liars” selectively choose the numbers that further their cause or which benefit them personally. Quarterbacks with losing win/loss records can focus on total passing yards gained. CEOs can focus on increased sales when profits are low. Politicians can pick the financial numbers that best support their personal goals.
“Damned liars” just make up their own numbers. For example, former president Trump said repeatedly when first running for office and during his term of office that the trade deficit with China was $500 billion when he took over. The real number was $367 Billion. Damned liars just don’t care. They tell people what they want to hear.
Statistics, on the other hand, do offer the facade of being impartial and in a way, they are. But only if the numbers are “real” and, also, only if they are used properly. Most of the time this requires analysis by someone who is an expert in whatever field is being covered.
In researching for this post, I came across a concept called, “Simpson’s Paradox” (No relation). Simpson’s Paradox is only one of many ways that statistics can be misused to make a point. Simpson’s paradox involves leaving out a key variable so that, although the numbers may be accurate, they don’t really give a correct picture of the larger issue. Sometimes the picture given is exactly the opposite of reality.
An example of this paradox is hospital death rates. Unless the condition of the patient when admitted is taken into account, we easily could get a false view of the “success” of certain hospitals and “failure” of others. A given hospital may have an overall lower death rate but in vital life-saving trauma situations they may not be the best, they could even be the worst.
The display of the data itself can be very misleading and cause the reader to misinterpret what they are looking at. Here below is a chart produced by the Florida Department of Law Enforcement intended to show the impact of the “Stand Your Ground Law” on murders committed using firearms. At first glance it appears that there was a reduction after the law was passed. A closer look reveals that the chart has been turned upside down (The y axis usually has 0 at the bottom) from what we normally expect.
The chart at the beginning of this post has incomplete descriptions of both the X and Y axis. At first glance it may appear positive with things trending upward. But is it? We really don’t know.
Many of the graphs and representations of statistics we are exposed to regularly tell only half-truths and require extensive research or expertise to really tell what is going on. This applies across the board: Both liberal and conservative politicians and pundits are equal opportunity offenders when it comes to using statistics and related charts.
Mark Twain (or whoever it was originally) hit upon a “truth” when he questioned the use of statistics and lumped them with “lies and damn lies.” What he did not tell us was how to deal with them.
My recommendation is to pick reliable sources for information and to rely on “experts” you trust in any given area/field. My previous post “Truth” (Accessible through links in the Menu above or by entering jimsim.com/truth in your browser) attempts to address this fundamental question: “Who are you going to believe?”
