Bad Jobs Exist

I’m James Bailey, an economist at Providence College who studies how government policies affect health care and the labor market. Thanks to Joy for the chance to join the blog for a few months!

For my first post, I have to share the brand new book I wrote a chapter of, “Regulation and Economic Opportunity: Blueprints for Reform“. Normally academic volumes like this are sold for hundreds of dollars, so only a few people with access to academic libraries end up reading them. But the publisher of this volume, the Center for Growth and Opportunity, released it as a free Ebook– so I hope you’ll check it out. It covers everything from housing and health care to energy and education to beer and cigarettes.

I wrote chapter 5, on how various regulations affect wages and employment. Here’s an excerpt:

Continue reading

The Pappy Pricing Puzzle

If you drink bourbon whiskey (or even if you don’t) you’ve probably heard of Pappy Van Winkle. Bourbon has experienced something of a revival in the past two decades, after being in decline for much of the 20th century. As part of this revival, some bourbons have become very highly sought after by the nouveau bourbon enthusiasts. And the various offerings of Pappy Van Winkle are arguably the most highly sought after. Finding Pappy is almost impossible these days, though this was also true a decade ago so it’s not really a “new” phenomena.

So here’s the “puzzle” for economists: why aren’t Pappy and other rare whiskies sold at market prices? No one in the “legal” market seems willing to do so. I put “legal” in quotation marks because there is a robust secondary market for these bottles, and the legal status of these sales is entirely unclear to me as an economist (alcohol markets are, to say the least, highly regulated).

In these secondary markets, it is not unusual for a 20-year bottle of Pappy Van Winkle to sell for $2,000. The “manufacturer’s suggested retail price” is $199.99. But you will never find this bottle on the shelf for that price. The bottles are held by retailers, either to sell to friends, auction off for charity, or conduct a lottery for the right to purchase the bottle at well below market prices.

So why doesn’t the distillery raise the MSRP? Clearly, they do this from time to time. Ten years ago, if you were lucky enough to find this bottle it was around $100 (I was lucky enough, on occasion). Clearly, they recognize that prices can increase. And that’s not just “keeping up with inflation”: $100 in 2011 is about $120 in current dollars. By 2016, they had raised the MSRP to $169.99. But why doesn’t the distillery raise the price more, perhaps all the way up to the market clearing price? By doing so, they would, perhaps, be able to ramp up production so that in 2041 there might be a lot more Pappy on the shelf. At the very least, they could dramatically increase their profit.

Receipt for 1 bottle of 20-year Pappy and 2 bottles of 12-year Van Winkle “Special Reserve” from 2011.

Also, why don’t retailers just put bottles on the shelf at $2,000? Stores occasionally do this, but mostly because they are fed up with all of the customers calling about rare bottles. Sometimes they will price it even higher than secondary markets. But usually, they allocate the bottles by something other than the price mechanism. Why? Businesses don’t usually leave dollar bills, especially $1,000 dollar bills, on the table.

Continue reading

Are Poor Americans Really as Rich as Average Canadians?

Have you seen this chart? I certainly have. It floats around on social media a lot. The chart seems to indicate that poor Americans are better off than the average person in most other rich countries. Roughly equal to Canada and France, and better off than Denmark or New Zealand.

When I’ve asked for sources in the past, people usually aren’t sure. They remember downloading it from somewhere, but they can’t recall where.

But I think I found the source: it’s this article from JustFacts. After seeing how they calculated it, I’m skeptical that it provides a good comparison of poor Americans to other countries.

Here’s what the chart does. For most countries, it uses a World Bank measure of consumption per capita. They then convert that to US dollars using PPP adjustments. For the poor in the US, they use a consumption estimate for the bottom 20% of households (Table 6), and then divide by the average number of people per household. For the poor in the US, the average consumption for 2010 was an amazing $57,049, more than double the poverty line! That’s about $21,000 per poor person.

How is this possible?

Continue reading

Current Research on the Gig Economy – Palagashvili

Online platforms are allowing us to trade used goods more easily than before. Similarly, sites like UpWork and Uber are making it easier to trade small blocks of human labor. Since the gig economy is growing (as documented by Dimitri Koustas), it’s important to understand how it is affecting workers.

Liya Palagashvili of Mercatus has a working paper with Paoula Suarez “Women as Independent Workers in the Gig Economy” examining particularly how the growing opportunities to work on a gig basis has affected women in different ways than men. They note, for example, that (in 2014–2015) 87 percent of independent workers on the Etsy platform were female, while 14 percent of workers on Uber’s platform were female.

Abstract: New technologies and digital platforms have ushered in a rise of gig, freelance, contract, and other types of independent work. Although independent workers and the gig economy as a whole have received plenty of attention, little research has examined the heterogeneity of work characteristics among different independent work opportunities, specifically as it relates to the participation of women in this workforce. Existing data indicate that some digital platforms are more male dominated, whereas others are more female dominated. What accounts for these differences? In this paper, we empirically examine the heterogeneity of work within independent work opportunities in relation to female participation by analyzing work characteristics in the United States from the Occupational Information Network (O*Net) database that reflect greater temporal flexibility, which has been shown to vary across occupations and to attract more female workers. Our findings suggest that women in the independent work context do self-select into the types of independent work jobs that reflect greater temporal flexibility, as is the case for women working in traditional employment. However, our findings also reveal that the way in which the existing literature measures temporal flexibility in traditional work settings may not be the same as the way it is measured in the context of independent work. We discuss the implications of our findings for public policy and labor laws. (emphasis mine)

Current Research on the Gig Economy – Koustas

Dmitri Koustas of U. Chicago has a forthcoming paper “Is New Platform Work Different than Other Freelancing?”

Abstract: The rise of freelance work in the online platform economy (OPE) has received considerable media and policy attention in recent years, but freelance work is by no means a new phenomenon. In this paper, we draw on I.R.S. tax records to identify instances when workers begin doing online platform work versus other freelance/independent contractor “gig” work for firms. We find gig work occurs around major reductions in outside income, and document usage over the lifecycle. Our results provide suggestive evidence on motivations for entering into each type of work. (emphasis mine)

His work was cited in the LA Times last year

people take on this work primarily because they’ve lost a job or some of their income — and particularly for younger workers, app-based services have been significantly more lucrative than more traditional side hustles.

I got to (virtually) talk to Dmitri Koustas, who is now a leading expert on gig work, this week. He became interested in the gig economy when he was thinking through a more traditional econ. question of generally how people modulate their labor supply in response to income shocks.

He also has a working paper “Is Gig Work Replacing Traditional Employment? Evidence from Two Decades of Tax Returns”

First half of the Abstract: We examine the universe of tax returns in order to reconcile seemingly contradictory facts about the rise of alternative work arrangements in the United States. Focusing on workers in the “1099 workforce,” we document the share of the workforce with income from alternative, non-employee work arrangements has grown by 1.9 percentage points of the workforce from 2000 to 2016. More than half of this increase occurred over 2013 to 2016 and can be attributed almost entirely to dramatic growth among gigs mediated through online labor platforms. We find that the rise in online platform work for labor is driven by earnings that are secondary and supplemental sources of income. Many of these jobs do not show up in self-employment tax records… (emphasis mine)

Old Lives Matter

Bryan Caplan has kindly responded to my latest blog post, which was in turn a response to his blog post on the relative value of human lives by age. Caplan has always been kind in his responses, even when responding to pesky graduate students — kind in both his approach and the time he dedicates to responding thoughtfully. So I appreciate his taking the time to respond to me, and I will offer a few more thoughts on the matter.

To briefly summarize: Caplan believes that young lives (10 year olds) are worth 100-1,000 as much as old lives (80 year olds). I contend that they are closer to roughly equally valued. My disagreement with Caplan can be broken down into two categories:

  • A. Caplan’s three reasons why young lives are worth more (a lot more!) than old lives. I didn’t respond to that directly, but I will do so here. I think Caplan is narrowing the goalposts.
  • B. A disagreement over the shape of the VSL curve over the lifetime, specifically whether an inverted-U-shaped curve makes sense. I’ll say more about this too, but Caplan doesn’t just have a beef with me, but with almost everyone in the VSL literature!

Let’s start with Caplan’s three reasons, which he calls “iron-clad”: young people have more years to live, those years are generally healthier, and young people will be missed more when they are gone. The first in undeniably true on average, the second is probably true almost all the time, and I’m not sure on the third, but I’m willing to admit it’s not a slam dunk either way.

So how can I disagree? These are only three things. There are many other considerations, and we can imagine other reasons that old lives are valued as much or more than younger lives! I’ll call mine 4-6 to go with Caplan’s 1-3:

  1. Old age spending is the largest component of public budgets in developed countries (and this is unlikely mostly due to rent seeking or the self interest of younger generations).
  2. The elderly possess wisdom which is highly valuable and that the young benefit from.
  3. The last years of your life are, on average, worth a lot more — you are usually very wealthy, have no employment obligations, you have grandchildren you love (without the responsibilities of parenting), and are (until the very end) generally healthy too.

Taken as a whole, I think these three reasons present a strong counterargument to Caplan’s three reasons. And I think we could certainly come up with more! My point being that Caplan has picked three areas where clearly young lives have the advantage, but ignored all the good reasons why old lives are more valuable. These is what I mean by we shouldn’t rely on our intuitions. Neither of our lists are exhaustive, but let me elaborate on a few of these.

Continue reading

The Value of Life, Again

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!

Continue reading

Teaching Economics with COVID

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.

Continue reading

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

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.

Continue reading

On Cylindrical Revolutions

The three technological innovations new to my life in the last year with the greatest impact are:

  1. Pfizer mRNA vaccines (price = $19.50, input costs: no less than $2 Billion, probably more)
  2. Amazon Basics Foam Roller (price $18.99, input costs: $4.44 per ounce of styrofoam)
  3. Zoom teleconferencing (price: $no idea what my school pays for it, input costs: $146 Million in venture funding)

The vaccine, of which I am scheduled to receive my first dose of tomorrow, will allow me to (sort-of) return to my pre-pandemic life. The introduction and regular use of a cylinder of high-density styrofoam has given me a better functioning left leg than I’ve enjoyed in 5 years. Zoom has arguably done more to maintain my the short-term integrity of my income (i.e. it’s allowed me to teach online effectively).

That is a very oddly shaped distribution of investments in high-utility yield innovations.

Biotechnology and medicine as a high investment, high risk, big payoff innovation game is well understood. Less known was whether or not a rapid “innovation on demand” vaccine project was an achievable outcome, no matter how much money was thrown at it. Turns out it was, and we’re left with what might be the most impressive feat of willed innovation since the moon landing. High-resolution teleconferencing technology, on the other hand, is exactly the kind of product we’ve grown accustomed to modern tech firms producing– the supply of such innovative products via the private capital-entrepreneurship pipeline is almost always less in question than the eventual demand it may or may not find in the marketplace.

But what of treating your muscles like sugar cookie dough? This is neither a sophisticated new composition of materials nor, at face value, a particularly complex theory of musculature. But, to my knowledge, this is not something even professional athletes were doing 7 years ago, yet now is both the bleeding edge of physical maintenance and such common knowledge that everyone who’s strained a muscle in the last 6 months currently has one of these cylinders leaning against a wall in their home. And, while I don’t mean to oversell it, the introduction of foam rolling has massively improved the quality of my life, not just when I try to play any sort of sport, but when I walk down a flight of stairs. It’s not crazy to suggest it may buy me an extra decade of easy use of my preferred mode of transportation, and while using my natural knees at that.

Investment in innovation is an interesting thing – there appears to be significant returns to scale at the micro, meso, and macro levels. Firms flush with capital can focus teams on single problems, fill them with talent, and grant them the keys to every piece of equipment deemed to hold even the slightest possibility of aid en route to an end product. There are simply innovative outcomes on the horizon for the Pfizers of the world that will never be available to scrappy new start-ups. At the same time, we can see the network-driven returns to scale in markets, a la Silicon Valley or Hollywood, that only begin to appear when a critical mass of agents all find themselves drawn to the bubbling creative soups that appears in the diners, salons, and coffee shops of whatever place has become the place.

But there are scale returns at the most macro of macro levels as well, and that is where we get miraculous cylinders of foam, as well as wheels on suitcases and the polymerase chain reaction. People are many things. Occupiers of space. Emitters of carbon dioxide. Consumers of fried dough. Sometimes while doing all three they also come up with ideas.

Humans as idea machines lies at the core of Michael Kremer’s theory of economic growth, and it is perhaps my favorite idea within economics in the last 40 years. Simply put, more people leads to more ideas. Population growth is not just a product of innovation, it is a source of it. Every individual is a lottery ticket that we hope pays off with a world changing eureka moment that the rest of us can benefit from and build on for all time going forward. More people, more lottery tickets.

Those organic globules of cognitive betting slips coalesce into the long tail of innovation return on investment. We take the brightest minds, throwing them and piles of cash at our biggest problems, hoping that for the closest thing to a assured payoff. But it’s within the billions of people, and their billions of bad ideas that sometimes aren’t, within which we get countless miracles that change our lives for the better bit by bit, one smoothened middle-aged stride at a time.