Author: Jeremy Horpedahl

The Value of Life, Again

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Bryan Caplan argues that the life of a 10-year-old is worth 100-1,000 times that of an 80-year-old. But he suggests the modal answer people would give is that the two lives are equally valued.

I’m not sure if he is right about what the modal answer would be that they are exactly equal (though see below for an attempt to answer this question). Surprisingly, though, roughly equally valuing all lives is actually the answer that a normal economic calculation, willingness-to-pay for risk reduction, would give you! Or at least roughly. I haven’t seen an estimate for a 10-year-old, but estimates of the Value of a Statistical Life for 20-year-old is roughly equal to an 80-year-old. I’ve written about this before, and here’s a summary of a working paper by Aldy and Smyth that I am drawing on. Middle age lives are worth more, using this method, though perhaps just 2-3 times more.

Caplan doesn’t directly connect his hypothetical to the COVID pandemic, but in the comments Don Boudreaux does make that connection and says that “surely the correct level of precaution to take against a disease that kills X number of old people is lower [than a disease that kills the same number of young people].” I find this a very interesting statement because Don Boudreaux, and many others, have been against just about any precaution (other than asking the elderly to isolate) in the current pandemic. Would he and others support more caution if they believed the VSL estimate to be true?

So who is right? Caplan’s intuition? Or the modeled VSL calculations? For surely these are miles apart, and they can not both be correct.

As an economist, I have a strong preference in favor of willingness-to-pay over our intuitions. Indeed, Caplan himself as defended the VSL approach quite forcefully!

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Teaching Economics with COVID

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In many of my blog posts I address either issues related to COVID or teaching economics. In this post, I want to combine the two. One thing economists of a certain age struggle to do is find examples to illustrate economic concepts which will actually connect with 18-22 year olds. The silver lining of the pandemic is that we now have an example that everyone is familiar with, and can be used to illustrate a host of economic concepts.

A great new book by Ryan Bourne, Economics in One Virus, really pushes this idea to the limit. He uses examples related to COVID to explain almost every single concept you would cover in a typical introductory economics course: cost-benefit analysis, thinking on the margin, the role of prices, market incentives, political incentives, externalities, moral hazard, public choice issues, and more.

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The Impact of the Pandemic on US States: GDP and Deaths

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Following up on my recent post on country GDP growth rates and mortality in 2020, we now have the first look at state GDP growth rates for 2020 from the BEA.

As with the national data, I would look to caution against over-interpreting this data. I’m presenting it here to give a picture of how 2020 went for states (including a few months of 2021 for morality data). One thing you will notice is that there appears to be little correlation with the raw data between GDP declines and mortality. Lots of important factors (policy, behavior, demographics, weather, luck) aren’t controlled for here. Still, I think it’s useful to see all the data in one picture, given how much many of us have been following the daily, weekly, and monthly releases.

Here is the data. Below I’ll explain more how I created this chart, especially the excess mortality data.

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Working Hard for the Money

Jeremy Horpedahl4 Comments

40 hours. That’s what we think of as a typical workweek. 8 hours per day. 5 days per week. Perhaps the widespread practice of working from home during the pandemic (as well as the abnormal schedule changes for those unable to work from home), has led some to rethink the nature of the workweek. But the truth is that the workweek has always been evolving.

Take this chart, for example. It comes from Our World in Data (be sure to read their excellent related essay as well), and the historical data comes from a paper by Huberman and Minns. I’ve singled out 4 countries, but you can add others at the OWiD link.

The historical declines are dramatic. This is especially true in Sweden. The average Swedish worker labored for over 3,400 hours per year in 1870. Today, that’s down to 1,600 hours. In other words, the typical Swede works less than half as many hours as her historical counterpart. Wow! The decline for the US is not quite as dramatic, but still astonishing: a US worker today labors for only about 57% of the hours of his 1870 predecessor.

It’s tempting to focus on the differences across countries today: the average worker in the US works about 250 hours more than the average French worker. That’s 6 weeks of vacation! And as recently as 1980, the US and France were roughly equal on this measure. We might also wonder why these historical changes happened. For a very brief introduction to the research, I recommend the last section of this essay by Robert Whaples.

But still, the historical declines are dramatic, even if we in the US haven’t seen much improvement in the past generation (and those poor Swedes, working 100 hours per year more than 40 years ago).

I think another natural question to ask is whether GDP data is distorted, at least as a measure of well being, given these differences in working hours. The answer is partially. Let’s look at the data!

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The Luck (?) of the Irish

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Poor Ireland. Long oppressed by the Brits. Losing 25% of their population in the Great Famine due to both deaths and emigration. Today, there are possibly 10 times as many Irish Americans as there are residents of Ireland. There are as many Irish Canadians as there are residents of Ireland.

Poor Ireland.

And indeed, Ireland used to be literally very poor, at least in an economic sense. In 1960, their GDP per capita was about half of the United Kingdom. As recently as 1990, they were still only at about 70% of the United Kingdom and the rest of Western Europe. That’s all according to the latest Maddison database figures, which are probably as close to accurate as we can find. But after 1990, we probably shouldn’t use those figures, for reasons peculiar to Ireland.

Today? Ireland is much wealthier. But how much wealthier? It’s tricky. Ireland’s GDP is inflated significantly due to a lot of foreign investment. And possibly some tax evasion/avoidance. You see, Ireland is a tax haven. It has one of the lowest corporate tax rates in the world. That means we have to interpret the data with care, but only because it is such a great place to invest.

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Dow 1,000,000?

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While the Dow Jones Industrial Average is one of the most widely quoted stock market indexes, it is well known to have many shortcomings. Specifically, it is price weighted (most indexes are value weighted), and that the 30 companies included are arbitrarily chosen.

But there’s an even bigger problem: it excludes dividends. This doesn’t matter much day-to-day, but it does matter a lot in the long run.

A new working paper, “Replicating the Dow Jones Industrial Average,” looks at both of these problems. First, they find that while price-weighting is weird, it doesn’t matter much. Also, if you just used the 30 largest companies in the US, rather than the 30 that are somewhat arbitrarily included, the return doesn’t change much. Either way, you get an average annual return of between 6.5% and 7.0% over the period 1929-2019. The DJIA is indeed a weird index, but that doesn’t seem to matter.

But the exclusion of dividends (and their reinvestment) is a massive problem over the long run. The authors find that the DJIA would have finished 2019 at a value over 1 million (specifically: 1,113,047) if dividend reinvestments were included (referred to as the “total return” index) rather than the 28,538 that it actually closed at. In other words, the average annual return of the DJIA from 1929-2019 was 11% rather than 7% (these are nominal returns, not inflation-adjusted).

If you know anything about compound growth, this is huge! At 11%, an investment will double roughly every 6 years rather than roughly every 10 years at 7% (using the rule of 70, or more precisely the rule of the natural log of 2). Over a 90 year period, that means the investment will be worth 40 times as much. Even using a log scale, as the chart here does, the dramatic difference is clear when you include dividends.

Economists can’t offer too much in the way of investment advice, other than: get your money into an index fund! Now!

GDP Growth in 2020

Jeremy Horpedahl5 Comments

Last year was a historically bad year for many reasons, but to economists that badness is most visible in our widest measure of the economy: Gross Domestic Product. All issues with GDP aside, especially as a perfect measure of relative living standards, the annual real (inflation-adjusted) growth rate of GDP gives us a good picture of how much national economies were harmed by the pandemic, private behavior changes, and government restrictions (disentangling these three effects is hard — I will leave that to the academic journals rather than a blog post).

While GDP is reported with a lag of several months and is subject to revision, many countries have now reported full GDP data for 2020. For those that don’t follow GDP very closely, for a developed country an annual rate of growth of about 2% is pretty normal and respectable. For further context, in the US recent recessions had declines of -2.5% in 2009, -0.1% 1991, and -1.8% in 1982 (the 2001 recession never had an annual decline, only a few quarterly declines). While it is unusual for countries to go more than 10 years without a decline, it does happen. For example, Australia’s last annual decline was in 1991, when it declined -1.3%. But that’s unusual.

This chart shows the 2020 GDP growth rates (mostly negative, with one exception — Taiwan) for 2020 for most countries were I could find data. What this number shows us is the total amount of economic activity in 2020 compared with the total amount of economic activity in 2019 (adjusted for inflation, of course). I believe this is a better measure than others you might see, such as data that compares the level in the 4th quarters of 2020 and 2019 (a country could have had a terrible 2nd quarter but still gotten back close to the prior year level, and a simple Q-over-Q measure would miss that decline). As I did for the 3rd quarter data, this chart also plots the cumulative COVID-19 death rates on the vertical axis.

GDP data comes from government statistical agencies and media reports. COVID-19 death data is from Our World in Data.

What can we learn from this data?

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Economic Research on COVID-19

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The past 12 months has been dominated by COVID-19, the related recession, the government response, and other matters. But it has not just dominated our lives, it has also dominated new research, including research by economists!

Working papers from the National Bureau of Economic Research are one place to track on-going research by economists. While not all economic research is released as an NBER working paper (there are other series, and some economists just post them on their own website or department page), the volume of NBER papers should tell us something about the trends.

Here’s a chart showing the weekly NBER working papers that are in some way related to COVID-19. The first batch of three papers was released in late February, one long year ago. The second batch of nine papers came one month later. Since then, there have been papers released every single week, with the exception of the week of Christmas.

In total, there have 373 papers released that relate to COVID-19. The peak comes in late May and early June, with 61 papers released in a 4-week period and 21 of those papers coming out on May 25 alone. Since the May-June peak, we’ve seen a slow decline in papers on COVID-19, and we are now at our lowest level, with just 14 papers released in the past 4 weeks.

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The Role of Prices in an Emergency, Winter Storm Edition

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When natural disasters and other emergencies strike, two things are certain. First, many essential goods will run out of stock at stores. Second, economists will complain that if only prices would rise in response to the increase in demand, shortages could be avoided.

Let’s take the current winter storm passing through much of the center of the nation, importantly including the southern US where both individuals and governments are unprepared for major winter storms. Here is a sign up at Home Depot in Arkansas:

I can verify that many people in Arkansas don’t have snow shovels. I’ve seen folks using dust pans and leaf rakes to try and clear their driveway. This video is a few years old, but I have no doubt that someone in Arkansas right now is strapping a widescreen TV box to their lawn tractor to clear snow.

So why no snow shovels in Arkansas at Home Depot? The common answer: it doesn’t snow much here, so the stores don’t stock many, and then when it does snow everyone rushes out to buy them.

Simple enough, but the economist says: WRONG! The reason Home Depot doesn’t have any snow shovels in Arkansas is because they didn’t raise the price. Why do economists insist on this?

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Broad Base, Low Rates: Every US State Fails on Good Sales Tax Principles

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In a previous post, I contrasted the income and property taxes, but I left out the other important tax: the retail sales tax. So let’s rectify that omission.

The retail sales tax is like the “Little Engine that Could,” delivering a steady stream of revenue to governments, while mostly staying out of the passionate debates surrounding the income and sales taxes. About 23% of state and local tax revenue comes from general sales taxes in the US, roughly equal to income taxes, and if you include selective sales taxes it’s slightly larger than the property tax share.

But there’s a problem with sales tax. The sales tax “base,” basically the extent of economic activity that the base covers, has been shrinking. A lot. As Jared Walczak has recently written, in just the past 20 years the “breadth” of the sales tax (how much of the potential base it covers) has fallen from about 50% to 30%.

As Walczak also notes, there are seven or so broadly agreed on principles of sales taxes, but I would say there are two primary ones (the first two on his list):

  1. An ideal sales tax is imposed on all final consumption, both goods and services.
  2. An ideal sales tax exempts all intermediate transactions (business inputs) to avoid tax pyramiding.

But US states violate these two principles in various ways, leading to (oddly enough) a tax base that is simultaneously too narrow and too wide. Why is this?

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