History

Historical Price to Earnings Ratios By Industry

James Bailey4 Comments

Getting long-run historical PE ratios of US stocks by industry seems like the kind of thing that should be easy, but is not. At least, I searched for an hour on Google, ChatGPT, and Bing AI to no avail.

I eventually got monthly median PEs for the Fama French 49 industries back to 1970 from a proprietary database. I share two key stats here: the average of median monthly industry PE 1970-2022, and the most recent data point from late 2022.

IndustryLong Run MeanEnd 2022
AERO12.1419.49
AGRIC10.759.64
AUTOS9.6517.52
BANKS10.3810.46
BEER15.2335.70
BLDMT12.0015.41
BOOKS12.9517.60
BOXES12.1810.69
BUSSV12.0713.03
CHEMS12.4019.26
CHIPS10.4817.47
CLTHS11.4510.94
CNSTR8.984.58
COAL8.042.92
DRUGS1.148.01
ELCEQ10.7817.85
FABPR10.2819.40
FIN11.1612.97
FOOD14.3025.03
FUN9.1021.06
GOLD3.18-5.95
GUNS11.505.05
HARDW7.9619.16
HLTH11.916.09
HSHLD12.6020.15
INSUR10.9516.33
LABEQ13.4625.18
MACH12.5120.27
MEALS13.8319.19
MEDEQ6.8127.64
MINES8.0616.27
OIL6.969.00
OTHER12.2027.68
PAPER12.5016.69
PERSV12.86-0.65
RLEST8.13-0.30
RTAIL12.268.58
RUBBR12.1112.81
SHIPS9.7917.42
SMOKE11.7417.79
SODA12.3832.09
SOFTW8.21-2.85
STEEL8.184.30
TELCM6.759.58
TOYS9.18-1.32
TRANS11.2513.11
TXTLS9.43-49.00
UTIL12.3417.41
WHLSL11.0813.13
Mean Industry Median10.5212.73

One obvious idea for what to do with this is to invest in industries that are well below their historical price, and avoid industries that are above it (not investment advice). Looking just at current PEs is ok, but a stock with a PE of 8 isn’t necessarily a good value if its in an industry that typically has PEs of 6.

By this metric, what looks overvalued? Money-losing industries (negative current earnings): Gold, Personal Services, Real Estate, Software, Toys, and Textiles. Making money but valuations 19+ above historical average: Medical Equipment, Beer, Soda. Most undervalued relative to history: Guns, Health, Coal, Construction, Steel, Retail (all 3+ below the historical average).

Of course, I don’t recommend blindly investing in these “undervalued” industries- not just for legal reasons, but because sometimes the market prices them low for a reason- that earnings are expected to fall. The industry may be in secular decline due to new types of competition (coal, steel, retail). Or investors may expect it to get hit with a big cyclical decline in an upcoming recession or rotation from the Covid goods/manufacturing economy back to services (guns, construction, steel, retail). Health services (as opposed to drugs and medical equipment) stands out here as the sector where I don’t see what is driving it to trade at barely half of its usual PE.

I’d still like to get data on long run market-cap weighted mean PE by industry, as opposed to the medians I show here. The best public page I found is Aswath Damodaran’s data page, which has a wide variety of statistics back to about 1999. Some of the current PEs he calculates are quite different from those in my source, another reason to tread carefully here. I’m not sure how much of this is mean vs median and how much is driven by different classification of which stocks fit in which industry category.

This gets at a big question for anyone trying to actually trade on this- do you buy single stocks, or industry ETFs? Industry ETFs make sense in principle (since we’re talking about industry level PEs overall) and also add built-in diversification. But the PE for the ETF’s basket of stocks likely differs from that of the industry as a whole. It would make more sense to compare the ETF’s current PE to its own historical PE, but most industry ETFs have very short track records (nothing close to the 53 years I show here). PE is also far from the only valuation metric worth considering.

All this gets complex fast but I hope the historical PE ratio by industry makes for a helpful start.

Pins to Patterns at AdamSmithWorks

Joy BuchananLeave a comment

I’m at AdamSmithWorks this week with “FROM PINS TO PATTERNS: FOLLOWING THE THREADS OF PRODUCTIVITY”

In the tapestry of human progress studies, two authors, Adam Smith and Virginia Postrel, have left their mark on the story of productivity and innovation. Their books, written centuries apart, both explore the power of specialization and the division of labor.

Part of the reason this came out this week is that I’m reading The Fabric of Civilization. So good! It had come highly recommended before, but I finally have an excuse to read it because I’m working on an article about fashion.

Fashion is not just for teen girls

Joy BuchananLeave a comment

It’s teen girls who care about what they wear, and rough military men do not even think about it. Right? Wrong.

Up Front is a book depicting WWII soldiers by cartoonist Bill Mauldin. Around page 135, Mauldin describes how men dressed who were close to the front lines but not actually in combat. Mauldin coined the term garritrooper (a portmanteau of garrison and paratrooper). I thank Prof. Mike Munger for the pointer.

The garritroopers are able to look like combat men or like the rear soldiers, depending on the current fashion trend. When the infantry was unpublicized and the Air Forces were receiving much attention, the emphasis was on beauty… [The garritroopers] would not wear ordinary GI trousers and shoes, but went in for sun glasses, civilian oxfords, and officers’ forest-green clothing. This burned up many decidedly unglamorous airplane mechanics who worked for a living and didn’t look at all like the Air Force men the garritrooper saw in the magazines.

We are all trying to look like the celebrities in magazines, even if we don’t all agree on who is a celebrity and which magazine to read.

Look at that smirk, found on the Wikipedia page. Bill Mauldin is temporarily my new favorite writer.

Minor Investment

Zachary Bartsch8 Comments

Gary Becker, the Nobel laureate in economics, applied economic reasoning to social circumstances and particularly to families. He argued that children are a normal consumption good, and people consume more children with higher incomes. However, he also emphasized a quantity-quality trade-off. More children in a family means fewer resources and attention for each child. Higher-income couples may opt to invest in classes, training, and spend more time with a unitary child rather than increasing the number of children.

However, goods have multiple attributes and children do not merely provide a stream of consumption value while in the household. They offer access to future resources when they become employed themselves. Having more children or higher-quality children increases the economic benefits that older parents can enjoy, such as more help with household activities and the ability to travel with their adult children. Old-age benefits such as social security now serve the function of insulating people from their prior investments in future consumption.

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The Leading Causes of Death Among Elementary-Age Children

Jeremy Horpedahl7 Comments

You might have seen this chart recently. It comes from a letter published in the New England Journal of Medicine in April 2022. The data comes directly from the CDC. It shows the leading causes of death for children in the US. You will notice that firearm-related deaths have been rising for much of the past decade, and in 2020 eclipsed car accidents as the leading cause.

Many are sharing this chart in response to the recent elementary school shooting in Nashville. It’s natural to want to study these problems more in the wake of tragedies. After the Uvalde shooting last year, I tried to read as much as I could about the history of homicide and gun violence in the US, and to look at the research on what might work to reduce gun violence, which is summarized in a post I wrote last June.

That being said, I don’t think the chart above accurately characterizes the problem of elementary school shootings. It might accurately describe some broader problem, but it’s misleading with respect to the shooting we all just witnessed. The most important reason is that the definition of “children” here extends to 18- and 19-year-olds. Much of the gun-related homicides for “children” shown here are gang-related violence, not random school shootings at elementary schools. It’s not that we shouldn’t care about these deaths too — we very much should care — but the causes and solutions are entirely different from elementary school mass shootings.

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Deaf Census Speculations

Zachary Bartsch1 Comment

Between 1850 and 1910, most US censuses asked whether an individual was deaf. There were four alternative descriptions among the combinations of deafness and dumbness. Seems straightforward enough. The problem is that these aren’t discrete categories, they’re continuous. That is, one’s ability to hear can be zero, very good, bad, or just middling. What constitutes the threshold for deafness? In practice, it was the discretion of the enumerator. Understandably, there was a lot of variation in judgement from one enumerator to another. A lot of older people were categorized as deaf, even if they had some hearing loss.

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What is $100 from the Late Nineteenth Century Worth Today?

Jeremy Horpedahl1 Comment

Recently I was watching a lecture by historian Marcus Witcher which addressed the treatment of African Americans in the Jim Crow era. Witcher mentioned the “pig laws,” which were severe legal punishments given to Blacks in the South for what used to be petty crimes. Such as stealing a pig. He mentioned that the fines could be anywhere from $100 to $500, and then he asked me directly: how much is $100 adjusted for inflation today?

My initial, immediate answer was about $3,000. That turns out to be almost exactly correct for around 1880. But the more I thought about it, the more I realized that this wasn’t a satisfactory answer. We were trying to put $100 from a distant past year in context to understand how much of a burden this was for African Americans at the time. Does knowing that adjusted for inflation it’s about $3,000 give us much context?

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Life Expectancy By State 1990-2019

James Bailey3 Comments

I’m making a panel of historical life expectancy data by state available here:

Life Expectancy By State 1990-2019

It covers the years 1990 to 2019 for every US state, and has life expectancy at birth, age 25, and age 65. It includes breakdowns by sex and by race and ethnicity, though the race and ethnicity breakdowns aren’t available for every state and year.

This is one of those things that you’d think would be easy to find elsewhere, but isn’t. The CDC’s National Center for Health Statistics publishes state life expectancy data, but only makes it easily available back to 2018. The United States Mortality DataBase has state life expectancy data back to 1959, but makes it quite hard to use: it requires creating an account, uses opaque variable names, and puts the data for each state into a different spreadsheet, requiring users who want a state panel to merge 50 sheets. It also bans re-sharing the data, which is why the dataset I present here is based on IHME’s data instead.

The IHME data is much more user-friendly than the CDC or USMDB, but still has major issues. By including lots of extraneous information and arranging the data in an odd way, it has over 600,000 rows of data; covering 50 states over 30 years should only take about 1,500 rows, which is what I’ve cleaned and rearranged it to. IHME also never actually gives the most basic variable: life expectancy at birth by state. They only ever give separate life expectancies for men and women. I created overall life expectancy by state by averaging life expectancy for men and women. This gives people any easy number to use, but a simple average is not the ideal way to do this, since state populations aren’t exactly 50/50, particularly for 65 year olds. If you’re doing serious work on 65yo life expectancy you probably want to find a better way to do this, or just use the separate male/female variables. You might also consider sticking with the original IHME data (if its important to have population and all cause mortality by age, which I deleted as extraneous) or the United States Mortality DataBase (if you want pre-1990 data).

Overall though, my state life expectancy panel should provide a quick and easy option that works well for most people.

Here’s an example of what can be done with the data:

If states are on the red line, their life expectancy didn’t change from 1990 to 2019. If a state were below the red line, it would mean their life expectancy fell, which done did (some state names spill over the line, but the true data point is at the start of the name). The higher above the line a state is, the more the life expectancy increased from 1990 to 2019. So Oklahoma, Mississippi, West Virginia, Kentucky and North Dakota barely improved, gaining less than 1.5 years. On the other extreme Alaska, California, New York improved by more than 5 years; the biggest improvement was in DC, which gained a whopping 9.1 years of life expectancy over 30 years. My initial thought was that this was mainly driven by the changing racial composition of DC, but in fact it appears that the gains were broad based: black life expectancy rose from 65 to 72, while white life expectancy rose from 77 to 87.

You can find other improved datasets on my data page, and once again this life expectancy data is here: Life Expectancy By State 1990-2019

It’s Never Good News When Deposit Insurance is in the News

Jeremy Horpedahl3 Comments

As you may have heard, there have been a few bank failures in the US in the past week. This has led ordinary people to start refreshing their memory about exactly what “deposit insurance” is and what it means for them. It has also led regulators, politicians, and economists to start refreshing their memory about the social purpose of deposit insurance, which is to stabilize the banking system. There are lots of aspects of the bank failures and deposit insurance to consider, but I think we can all agree that when ordinary people are thinking about this topic, bad things are going on.

While I can’t find a systematic survey of economists on this topic, my guess is that most economists would agree with the statement “on balance, deposit insurance promotes stability in the financial system.”

But there is a minority view, and one with (in my opinion) considerable historical support. Deposit insurance could potentially be destabilizing, since it has the potential (like any form of insurance) to create moral hazard. By lowering the cost of making mistakes, we would expect more mistakes. The cost need not be lowered all the way to zero for moral hazard to be a problem (bank owners still have some skin in the game), but the cost is certainly lower. These problems may be even more of a threat to the financial system than other areas of life covered by insurance.

That’s the theory. What’s the evidence?

My favorite paper on this topic is a 1990 article by Charles Calomiris called “Is Deposit Insurance Necessary? A Historical Perspective.” Not only does it conclude that deposit insurance isn’t necessary, but even more: it may be destabilizing. (You can also read a version of the article intended for a more general audience that Calomiris wrote for the Chicago Fed.)

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Complacency and American Girl Dolls 2

Joy Buchanan2 Comments

It’s time to revisit American Girl Dolls and the Saturn V rocket. The trending topic among millennials is the new “historical” American Girl doll who lives in the year 1999.

Previously, I blogged about the historical Courtney doll from 1986 in “Complacency and American Girl Dolls.” I used Courtney’s accessories to illustrate stagnation in the physical environment (within rich countries) of recent decades. Courtney has a Walkman for playing cassette tapes and she has an arcade-style Pac-Man game to entertain herself. I pointed out that ’80’s Courtney had to be given the World War II doll Molly just to keep life interesting.

What do Isabel and Nicki have a decade later in 1999?  

They have a personal CD player and floppy disks. It’s cute and the toys will sell. However, it does not seem like innovation has introduced many new capabilities. Isabel can listen to music through her headphones and be entertained on screens, just like Courtney could.

Isabel eats Pizza Hut and has dial-up internet access. There is no sense of sacrifice or expanding the frontier. The world was settled, and history had ended.  

What counts for adventure in 1999? Shopping vintage clothing. Just like Courtney, Isabel revisits the past to get a sense of purpose or excitement.

This is Isabel’s diary. Having nothing to do besides look at clothes from past decades, she obsesses over status. Presumably “Kat” complimented her hat in person. Facebook didn’t start until 2004, so Isabel is not worried about “Likes” in social media.

So, what did I do with my kids for their school break on Presidents’ Day?  We went to the U.S. Space and Rocket Center to see the Saturn V rocket.

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