Data

Self-Conception, Relative Prices, & Confabulation

Zachary Bartsch7 Comments

We all like to think that we are individuals. We like to think that we grow and that our tastes develop and mature. We begin to appreciate different things in life, and among other behaviors, our spending habits change.

But what would you say if I told you that your maturing tastes didn’t cause your maturing consumption patterns? Indeed, what if it’s the other way around? Maybe, you’re just a bumbling ball bearing bouncing about and pinging off of various stimuli in a very predictable fashion. What if the prices that you face changed over the course of the past two decades, adjusting your optimal bundle of consumption, and then you contrived reasons for your new behavior in an elegant post-hoc fashion.

Have you *really* taken a liking to whole wheat bread and pasta over the past decade because your tastes have developed? Or maybe it’s because you found that scrumptious New York Times recipe that turned you away from potatoes and toward rice. Whether it’s a personal experience, a personal influence, or a personal development, we like to think about ourselves as complex organisms with a narrative that makes sense of the way in which we interact with the world.

On the other hand, we have price theory. Price theory still accepts that you are special and that you have preferences. Then, it asserts that your preferences remain fixed and that your changes in behavior are merely responses to changing costs and benefits that you perceive in the world. Maybe you’re not any more inclined to eat healthily than you were previously, but the price ratio of whole wheat bread to white bread is 10% less than it use to be. Maybe your east-Asian inspired recipe didn’t cause you to spurn potatoes, but instead the price ratio of rice to potatoes fell by 20%.   

Continue reading →

The Economics of Brushing Teeth and the Tooth Fairy

Jeremy Horpedahl2 Comments

There are many papers with titles in the style of “The Economics of X” with X covering a wide variety of topics, some deadly serious (“Economics of Suicide“) and others more trivial or unintentionally hilarious (“The Economics of Sleep and Boredom” comes to mind). There is a related genre of papers on “The Political Economy of Y,” once again with papers that are both serious and occasionally silly (or sometimes deadly serious papers with silly-sounding titles, such as “The Political Economy of Coffee, Dictatorship, and Genocide“).

But perhaps the best paper of this sort is a 1974 article on the Journal of Political Economy by Alan Blinder, titled “The Economics of Brushing Teeth.” It is, as you might guess, a paper that is somewhat tongue-in-cheek (tongue-in-teeth?), but the paper carefully follows the formal style you would expect from a JPE paper in 1974. I recommend reading the paper in full, and I can assure you that it is not at all like pulling teeth. But if you prefer not to look a gift horse in the mouth, here are a few favorite parts.

The paper is, of course, full of tooth-related puns, even in the footnotes, such as this acknowledgment: “I wish to thank my dentist for filling in some important gaps in the analysis.”

There are also plenty of jokes about human capital theory, jokes that only an economist could love, such as: “The basic assumption is common to all human capital theory: that individuals seek to maximize their incomes. It follows immediately that each individual does whatever amount of toothbrushing will maximize his income.”

Another section manages to poke fun at both sociologists and economists. In reference to a fake paper (no, there is no Journal of Dental Sociology), Blinder chastises the fake sociologist for misattributing a change in brushing patterns (assistant professors brush more) to advancing hygiene standards over time. No! It must be about maximizing income: “To a human capital theorist, of course, this pattern is exactly what would be expected from the higher wages received in the higher professorial ranks, and from the fact that younger professors, looking for promotions, cannot afford to have bad breath.”

And what good is a paper without a formal model of teeth brushing? This is the kind of model that many young economists cut their teeth on in graduate school.

Continue reading →

Twenty Years of Animal Protein Affordability

Zachary Bartsch2 Comments

Have you heard the hubbub about eggs? People say that they’re expensive. My wife told me that if she’s going to pay an arm and a leg, then she may as well get the organic, pasture raised eggs. Absolutely. That’s what the substitution effect predicts. As the price ratio of low-quality to high-quality eggs rises, we’re incentivized to consume more of the high-quality version. It has to do with opportunity costs.

Consider a world in which the low-quality eggs cost $2 and the high-quality eggs cost $6 per dozen. Every high-quality egg costs 3 low-quality eggs. You might still choose the high-quality option, but you know that you’re giving up a lot by doing so. Consider the current world where low-quality eggs are priced on par with high-quality eggs. Now, the opportunity cost of consuming the fancy, pasture-raised eggs has fallen. When consuming one high-quality egg costs you one low-quality egg, it’s much easier to opt for the high-quality version. You’re not giving up as much when you purchase it.

For vegetarians, the recent price swing has probably been rough. Not eating meat, they’re facing the price squeeze more so than their omnivorous counterparts. Through the magic of math, median wages, and average retail prices, the figure below charts the affordability of eggs and dairy products.* The median person has been facing falling egg affordability for two decades. Indeed, it’s only been the past few years, punctuated by the Covid crisis, that consumers experienced more affordable eggs.

Dairy products, however, have become much more affordable. The median American can now afford 50% more of their namesake cheese. Further, we can afford 20-25% more whole milk and cheddar cheese. So, the vegetarians are not so poorly off after all.

But how do meatier sources of protein compare?

Continue reading →

Behavioral Risk Factor Surveillance System Survey: Now in Stata and CSV formats

James Bailey1 Comment

The BRFSS Annual Survey is now available in Stata DTA and Excel-friendly CSV formats at my Open Science Foundation page.

The US government is great at collecting data, but not so good at sharing it in easy-to-use ways. When people try to access these datasets they either get discouraged and give up, or spend hours getting the data into a usable form. One of the crazy things about this is all the duplicated effort- hundreds of people might end up spending hours cleaning the data in mostly the same way. Ideally the government would just post a better version of the data on their official page. But barring that, researchers and other “data heroes” can provide a huge public service by publicly posting datasets that they have already cleaned up- and some have done so.

That’s what I said in December when I added a data page to my website that highlights some of these “most improved datasets”. Now I’m adding the Behavioral Risk Factor Surveillance Survey. The BRFSS has been collected by the Centers for Disease Control since the 1980s. It now surveys 400,000 Americans each year on health-related topics including alcohol and drug use, health status, chronic disease, health care use, height and weight, diet, and exercise, along with demographics and geography. It’s a great survey that is underused because the CDC only offers it in XPT and ASC formats. So I offer it in Stata DTA and Excel CSV formats here.

Let me know what dataset you’d like to see improved next.

The Minimum Wage and Crime

Jeremy Horpedahl2 Comments

The minimum wage is one of the most studied topics in economics, and also something that is frequently discussed on this blog from many different angles. For someone that isn’t an expert in this area, it can be hard to keep track of all the most recent, cutting-edge research on the topic.

Here’s a brand-new paper in the literature with an important finding: raising the minimum wage increases crime. Specifically, in “The Unintended Effects of Minimum Wage Increases on Crime” the authors find that 16-to-24-year-olds commit more property crimes after a minimum wage increase. For every 1% increase in the minimum wage, there is a 0.2% increase in property crime. That implies a doubling the minimum wage would increase property crimes for this age group by 20%. Here’s a figure from the paper showing this increase in crime:

What is the mechanism by which the rising minimum wage increases crime? Here the authors move into examining one of the central questions of the empirical minimum wage debate: the labor market. The authors do find evidence that employment decreases for this same age group following an increase in the minimum wage. Again, a figure from the paper:

The results in this paper add one more element to the cost-benefit calculus of the minimum wage. But I think the results are also interesting because they seem to point in the opposite direction of a paper co-authored by fellow EWED blogger Mike Makowsky. His paper “The Minimum Wage, EITC, and Criminal Recidivism” found that increasing the minimum wage made it less likely that former prisoners would commit another crime. I would be interested to hear Mike’s thoughts on this paper!

The Murky Macro Picture

James Bailey2 Comments

Last June I wondered if we were seeing the peak of inflation, and by at least one major measure I called the peak exactly:

At the moment, though, I’m feeling more confused than prophetic. The big question a year ago was how long it would take the Fed to get inflation down to reasonable levels, and how much collateral damage they would do to the real economy in that effort. Today most current indicators make it look like they pulled off the miraculous “soft landing”. Inflation over the last 12 months is still high, but over the last 6 months we’re nailing the Fed’s 2% annualized target. This has hit a few sectors of the real economy hard, with housing slowing dramatically and tech doing mass layoffs, but the overall picture is great: GDP growth was around 3% the last 2 quarters, and the 3.4% unemployment is the lowest since 1969.

What’s confusing about this is that we have a hard time believing we really got this lucky. Its like your plane lost power, you diverted course for an emergency crash landing, and once you touch down and find yourself seemingly unharmed you look around and wonder if the plane is about to explode. Consumer sentiment is worse than it was in the depths of Covid; business sentiment has been falling for over a year and is almost down to March 2020 levels. Betting markets forecast a 50% chance of a recession in 2023, and the yield curve is strongly inverted (one of the best predictors of a recession, though the guy who first noticed this says it might not work this time):

Finally, M2 money supply is shrinking for the first time since at least 1960, and I believe the first time since the Great Depression. This bodes well for inflation continuing to moderate, but its also one more indicator of a potential recession.

To sum up, most of the indicators of the current state of the economy look great, while most indicators of its near-term future look awful. So which do we trust?

My guess is that we avoid recession in 2023, but honestly this is mostly the gut feeling of an optimist. There’s no one knock-down piece of data I’d point to in support; its more that things are currently going well, and usually the best prediction is that tomorrow will be like today unless you have a good reason to think otherwise. The main reason people expect a slowdown is because of the Fed’s actions to fight inflation. The Fed itself predicts that they will cause a slowdown, but not a recession. Their most recent summary of economic projections from December predicts GDP growth slowing to 0.5% in 2023 and unemployment rising to 4.6%.

I think the “so what” outlook is also murky. Stocks have already fallen a lot from their highs and a recession already seems somewhat ‘priced in’, so even if I thought one was coming I wouldn’t necessarily sell stocks. On the flip side US stocks are still quite expensive by historical standards, so I don’t want to buy more on the assumption that they’ll rise more on good economic news this year. You might want to lock in decent rates on long-term bonds if you think the Fed will cut rates in response to a recession, but the inverted yield curve shows this is already somewhat priced in. 1-year bonds yielding almost 5% seems decent in either scenario, I have some and I’ll probably buy more, but 5% returns are nothing to get excited about. I’d like to hear suggestions but to me the small direct betting market on a potential recession is the clearest “so what” for anyone who does have a confident view about this year’s macro picture.

The Growth of Black Families Income

Jeremy Horpedahl4 Comments

Black families are the poorest major racial or ethnic group in the US. With a median income of $59,541, a Black family only has about 59 percent of the income of a White, Non-Hispanic family. That’s the same proportion, 59 percent, as was true in 1972, the earliest date that we have comparable data. (For most of the data in this post, I will be using Table F-23 from the Census Bureau’s Historical Income Tables.) That’s almost 50 years with no closing of the racial gap in total money income for families.

Of course, what this also means is that family incomes of both Black and Whites grew at the same rate from 1972 to 2021. They both are about 50 percent larger than in 1972, and that’s after accounting for inflation (using the CPI-U-RS). As a first point of optimism, this very much goes against the typical narrative of income stagnation since the early 1970s.

To be sure, some of this growth is because families have more earners today, but even so: they have a lot more income. Having two earners does mean that you must spend more on some consumption categories, such as daycare when kids are young, possibly more on dining out or prepared meals. But even with those additional expenses, these families will have significantly more disposable income than their 1970s counterparts.

There is an ever more optimistic fact that we need to point out for Black families today: there are many, many more rich Black families today than in 1972. There are more rich families in absolute terms and as a proportion of the total. Here is the basic data from the Census Bureau (it goes back to 1967, the earliest date available for Blacks).

Continue reading →

The Social Drug of Prohibition

Zachary Bartsch1 Comment

Why does the average drinker consume alcohol? There are plenty of reasons, one of which is social. Alcohol, while inhibiting clarity, precision, and discretion, is a social lubricant. If you’re one of those drinking, then it’s enjoyable to be around other drinkers. Also, people build the habit of drinking *something* while socializing. We all know that prohibition resulted in bootlegging and tainted cocktails. But what were the legal alternatives? One was that you could purchase grape juice and make your own wine (that’s a story for another time). Another is to switch to another drug.

Alcohol is a depressant and arguably the most popular one in the US. It’s not a clear substitute for alcohol in terms of its direct effects on the body. However, it’s a liquid, safe, and tasty. That make is a good candidate for satisfying the physical urge to imbibe. But, importantly, it is also a social drug. People would get so hopped up on coffee and feed off of one another’s high that Charles the II of England banned coffee houses in order to prevent seditious fomentation. This brings us to an important characteristic of coffee. It’s a stimulant. You’d think that a stimulant would not be a substitute for alcohol. If anything, one might think that they are complements. Coffee helps to provide that kick in the pants after having an enjoyable night. But, the social feature makes coffee a good candidate to substitute alcohol, should the times be dire.

Illegal activity aside, people wanted an outlet for their physical and social proclivities. They wanted intoxication. Coffee provided exactly that. Conveniently, the continental US didn’t grow any of its own coffee. That means that imports and domestic consumption have a tight relationship.

Continue reading →

Economic Recovery from the Pandemic

Jeremy Horpedahl3 Comments

How well have countries recovered from the declines in the pandemic? It’s actually a bit difficult to answer that question, because it depends on how you measure it. Even if we agree that GDP is the best measure, how do we measure recovery? One possibility is to simply ask whether the country has exceeded its pre-pandemic GDP level. Exactly which quarter to use as the baseline is debatable, but here is a chart that Joseph Politano made for G7 countries using the 3rd quarter of 2019 as the baseline.

But we know that absent the pandemic, most countries would have continued growing (absent a recession for some other reason), so just getting back to pre-pandemic levels isn’t necessarily a full recovery. But how much growth should we have expected? It’s a hard question, but here’s a chart along those lines from the Washington Post, using the CBO’s measure of “potential GDP” as what growth might have looked like.

Using either of these approaches, it appears that the US has recovered pretty well, although it would be nice to have a comparison across countries using the same approach as the Washington Post chart does. While there is no consistent measure similar to CBO’s potential GDP figure for all countries, a simple approach is to project growth forward using the average pre-pandemic growth rate. I have done so for a number of countries, using the average growth rate from 2017-2019. In the following charts, the blue line is actual GDP levels, and the orange line is projecting the 2017-2019 growth rate forward. Sorry that I can’t easily fit all these into one chart, so here come the charts!

Continue reading →

Counting Jobs

Jeremy Horpedahl2 Comments

Last week I wrote about the challenges of counting deaths. But surely in economics, we can count better, especially when it comes to something concrete like the number of people working. Right?

Maybe not. If you follow the economic data regularly, you’ll know that once per month, the Bureau of Labor Statistics releases data on the employment situation of the nation’s economy. And if you are familiar with this report, you will probably know that it is based on two separate surveys, one of businesses and one of households. And furthermore, it gives us two separate measures of employment, the number of people working for pay.

Joseph Politano has been tracking the employment situation reports, and he writes that the two measures of employment have “completely diverged since March of [2022], with the establishment survey showing payroll growth of nearly 2.7 million and the household survey showing employment growth of 12,000.” The surveys are tracking the labor market differently, so it’s not surprising that they won’t be exactly the same (they rarely are), but this sort of discrepancy is huge. Even accounting for most of the differences between the surveys, there is still a gap of about 2 million jobs.

Today, the BLS released yet another measure of employment, this one comes from the Business Employment Dynamics series. The BED is not released as quickly as the data in the employment situation report — the BED data released today is for the 2nd quarter of last year. But that’s because this data is much more comprehensive, and it’s actually the same data underlying the employment measure from businesses in the monthly employment report (it comes from unemployment insurance records, which covers most of the workforce).

What did the BED find for the 2nd quarter of 2022? A net loss of 287,000 jobs. The BED is only looking at private-sector jobs, and it is also seasonally adjusted to smooth out normal quarterly fluctuations. If we look back at the monthly data on employment, what did it look like in the 2nd quarter of 2022? Using the seasonally adjusted, private-sector jobs number to match the BED, it showed a gain of 1,045,000 jobs. In other words, we have a discrepancy of 1.3 million jobs in a single quarter. This is huge.

Perhaps some of this could be attributed to different seasonal adjustment factors, but even using the unadjusted data there is still a gap: 3,089,000 jobs added in the monthly payroll survey (private sector only), but only a net gain of 2,432,000 private-sector jobs in the BED data. That discrepancy is smaller, but it is still a difference of over 600,000 jobs. Note here that there was job growth in the second quarter in the BED measure, just not enough job growth that on a seasonally adjusted basis that it showed net growth. Another way to think of this: there is almost always growth in the 2nd quarter, but we expected it to be a bit stronger than this data shows.

If you aren’t confused enough yet, BLS produces yet another measure of employment, called the Quarterly Census of Employment and Wages. Really this is the broadest measure of jobs and is using the same underlying data as the BED and monthly nonfarm jobs in the business survey. But like the BED, it is also released with a significant lag. What does it show? A gain of 2,338,000 jobs in the 2nd quarter of last year (this includes public sector employment too). That number isn’t seasonally adjusted and compares with the CES (monthly nonfarm employment) number of 2,702,000, a discrepancy of 364,000 jobs (note: the CES will later be revised and benchmarked with the QCEW data).

What can we learn from all these different estimates of jobs? And which is right? The short answer to the second question is: they are all right, but measuring different things. The big takeaway is that there was indeed job growth in the 2nd quarter of 2022 (even the household survey shows job growth), but based on more complete data the monthly business survey probably overstated job growth, and it may have actually been pretty weak job growth compared to what we would normally expect in that quarter in the private sector (but of course, we aren’t in normal times).