Measures of central tendency aren't enough...

 

Here's another example of why "averages" are not enough.

This article claims that U.S. car shoppers want "too much car" because they want a 300-mile range for EVs.

"Yet there is a glaring disconnect between what American drivers want and what they actually need: Some 95% of U.S. car trips are 30 miles or less."

That statement doesn't address the issue at all because it doesn't address the length of the other 5% of trips. It's focused on averages instead of variability.

I might fit this pattern. Most of my trips, probably close to 95%, are less than 40 or 50 miles. However, about every two months, I head out of town to visit relatives who are between 450 and 700 miles away.

If EVs are only short-range, then my options are:

1. Stop frequently to recharge on my long trips.
2. Rent a gas vehicle every time I leave town.
3. Own two vehicles: an EV for around town and a gas vehicle for out of town.
4. Don't buy an EV

So far, I've selected option #4. For most one-car households, that's a reasonable choice that has nothing to do with wanting "too much car". 

However, my wife and I have considered #3 because we already are a two-car family. If we could find an EV that wasn't too expensive and had sufficient legroom (I'm over 6' tall), then we might buy one. 

Sex! Drugs! (or just another correlation/causality example)

How did I not hear about this sooner? Maybe I just wasn't paying attention, but one would think that this would have been headline news.

Five months ago, research came out showing an association between Viagra (sildenafil) and Alzheimer's: "sildenafil users were 69% less likely to develop Alzheimer’s over a six-year period than non-users". 

The full paper is behind a paywall, but you can read the abstract. The most important line is this: 

"The association between sildenafil use and decreased incidence of AD does not establish causality, which will require a randomized controlled trial."

As much as some want to giggle about Viagra, this is an interesting statistical problem. Think about how one would structure a controlled trial.

Remember - sildenafil is prescribed for two reasons:

• Sex (erectile dysfunction)
• High blood pressure (pulmonary arterial hypertension)

Could we even do a randomized controlled trial with men in these groups? That's tricky. Even with informed consent, is it ethical to randomly withhold medical treatment known to help with either of these conditions? 

A ethical trial would require a group of men old enough to be at risk for Alzheimer's and with neither medical condition. They would volunteer to be randomly assigned to sildenafil or a placebo. In a double-blind study, neither they nor their direct researchers would know who was receiving the real drug. 

It's Viagra. How long do you think it would take before the men figured out which group they were in?

This leaves us with problems.

1. It would be unethical to do a trial with men who have a medical need for sildenafil.
2. It would be nearly impossible to maintain double-blind status for any length of time.

I don't have a solution but I have a suggestion for where research could start. Since sildenafil is prescribed for two different conditions, the existing data should be separated by medical condition. Then the Alzheimer's incidence could be compared between those two conditions.**

Suppose that those treated for erectile dysfunction had lower incidence of Alzheimer's than those treated for hypertension. That could imply that it's not the sildenafil itself, but the increased frequency of sex that helps prevent Alzheimer's. Many men would cheer for that.

Then suppose the opposite. What if the data showed that those treated for hypertension had lower incidence than those treated for erectile dysfunction. Would that imply that too much sex could increase the risk of Alzheimer's? Now most men wouldn't cheer as much.

What if there's no difference in Alzheimer's incidence? That's evidence in favor of sildenafil causing decreased Alzheimer's, but it's still far from proof. Maybe sildenafil allows both groups to exercise more. Maybe it's ... just about anything. 

This is why medical research is hard. There are usually ethical issues and it's difficult to maintain double-blind status for any treatment that has well-known side effects.

-------

**It's possible that this separation was done in the study. Since it's behind a paywall, I can't check but the abstract doesn't mention it.

Looking at Minimum Wage

With both the "great resignation" and inflation in the news, I decided that it was time to look at the US minimum wage. I've put my findings in a single chart.

Since the minimum wage was last raised in 2009, I converted all values to 2009 dollars. To my eye, a couple of things stand out.

• After stabilizing around 1950, there appears to be a floor near $6.00 (2009 value) for the minimum wage. The current wage is $6.01 in 2009 dollars.
• The highest minimum wage was in 1968 with the second highest in 1978. There was significant inflation during this time period.

Since we are approaching the historical floor, I think that one can make a fairly strong argument in favor of increasing the federal minimum wage. 

The bigger question is how far it should be raised. The data gives us three points to consider.

• If we wish to match the highest historical value, then 1968's wage translates to $12.62 today.
• If the highest historical value seems too high, then we could aim for the second highest. The 1978 wage would give us $11.30 today.
• If we simply wanted to match the last increase, then 2009's $7.25 would be $9.39 today.

Combining those, one could reasonably argue for a new minimum wage anywhere between $9.40 and $12.65.

Disclaimers: I am well aware that many historical "minimum wage" jobs now pay more than minimum wage. I will let others argue about whether that is due to labor supply/demand or political pressure. My analysis is based on nothing more than the data. It is not an analysis of human value.  

However, I'll make one political statement. It would be a great bipartisan move to increase the minimum wage. Sure, the argument about the exact figure could get ugly, but our political leaders could also decide to act like grown-ups, look at the data, find a compromise number, and show the country that they can work together. It could be done quickly. 

Sources:

https://www.dol.gov/agencies/whd/minimum-wage/history/chart
https://en.wikipedia.org/wiki/Minimum_wage_in_the_United_States
https://www.usinflationcalculator.com/

"Great Resignation" or "Great Retirement"?

Over 10 years ago, I wrote Will the Baby Boomers Ever Retire? in response to an article predicting tremendous retirements among financial professionals in "three to five years".

Here is a quote from early in post:

"Today is March 17th, 2011. The funny thing is, I've been hearing about mass retirements in the next "three to five years" since the 1990s."

My overall conclusion/prediction was: 

"So what's going to happen? Will there be a "tremendous number" of retirements in "three to five years"? I don't know for sure, but I don't think so. Of course the Boomers will all eventually retire or die but I think they'll go by attrition rather than en masse. Most of the Boomers I know simply do not have the resources to retire any time soon. Some will be forced to retire when their health fails. Others might get a nice inheritance along the way and decide that they finally have the resources to retire. Others will work well into their 60's and even their 70's either because they have to or they just plain want to."

For several years, I think that my prediction held up well. 

Then Covid-19 came.

We're hearing a lot about the "Great Resignation" and the depleting labor force. However, this article makes the argument that it's not a general abandonment of the labor force. Instead, it's driven by retirement. 

"Last month, there were 3.6 million more Americans who had left the labor force ... compared with November 2019. ... Older Americans, age 55 and up, accounted for whopping 90% of that increase."

There is disagreement on exactly where the line is between the Boomers and GenX, but most demographers put it somewhere between 1964 and 1966. In other words, "age 55 and up" pretty much catches the tail end of the Boomers.

After 25 years of "three to five year" predictions, it looks like the Boomer are finally retiring.