Economics of the Russia-Ukraine Conflict

Russia launched a full invasion of Ukraine last night. Most of the discussion I’ve seen has naturally focused on the fighting itself- what is happening, what is likely to happen, how did it come to this.

Since there are plenty of better sources to follow about that, I’ll simply offer a few observations on the economics of the conflict:

  1. Russia is not only more than 3 times as populous as Ukraine, it also more than twice as well off on a per-capita basis. This means its overall economy is more than 6 times the size of Ukraine’s. This gap has been growing since the fall of the Soviet Union, as Russia’s per-capita GDP growth has been much stronger, while its population has shrunk much less than Ukraine’s. Putting this together, Ukraine’s measured real GDP is actually smaller than it was in 1990, while Russia’s is larger.

2. Russia’s much larger economy allows it to spend much more on its military. Russia spends $60 billion per year, the 4th most of any country (after the US, China and India). Ukraine spends only $6 billion per year on its military. So Russia is starting with a big economic advantage here, though Ukraine has some of its own advantages, like fighting on their own ground and receiving more foreign support.

3. War is bad for business. Russian stocks are down 33% in a day, their biggest-ever loss; Ukraine shut down trading entirely, and their bonds are being hit even worse than Russia’s. Regardless of which side “wins” the fight for territory, both countries will be economically worse off for years as a result of the war.

4. Russia, though, expected that the war would lead to sanctions from the West that would harm their economy, and prepared for this by building up hundreds of billions of dollars worth of foreign reserves over many years.

5. US markets are down only slightly, much less than they would be if traders thought the US would get involved directly in the fighting. But this slight overall decline conceals huge swings. Companies that do business in Ukraine or Russia are big losers. But those that compete with Russian exports see their value rising given the expected sanctions. Because Russia’s biggest exports are oil and natural gas, the value of US-based oil & gas companies is rising, while alternatives like solar are also up substantially.

6. There is still some hope for Ukraine to expel Russian troops, but its not looking good, and even a victory would involve huge costs. This leaves people all over the world wondering, how did it come to this? How might future conflicts like this be avoided? There is of course a lot to say about military preparedness, nuclear umbrellas, and ways the West can impose costs on Russia as a deterrent. But what stands out to me is that a stagnant economy and shrinking population make a country weak and vulnerable. Ukraine has a worse economic freedom score than Russia; this combined with its relative lack of natural resources explains much of the stagnation. Political elites often focus on grabbing a large share of the pie, rather than growing the pie and risk empowering domestic opponents. But we’re now seeing how stagnation carries its own risks. A growing economy, and especially growing energy sources that don’t depend on hostile nations, is the path to independence and survival.

Home(r) Economics

Is it harder to buy a home today than in the past? Many seem to think so. Lately, some people have used the example of the fictional Simpsons family to make this claim. A recent Tweet with around 100,000 likes expressed the sentiment:

The unspoken implication is that today a “single salary from a husband who didn’t go to college” couldn’t buy a typical home in the US. Or at least, it would stretch your budget so thin that you would have to give up something else or need two incomes to support that lifestyle (famously dubbed “the two-income trap” by Elizabeth Warren).

And it’s not just a Tweet that caught fire. A December 2020 article in the Atlantic claimed “The Life in The Simpsons Is No Longer Attainable” and used housing as a prime example. And while a 2016 Vox article on Homer’s many jobs doesn’t mention the cost of housing, they draw a similar conclusion and implication: “Homer Simpson has gone nowhere in the past 27 years — and the same could be said of actual middle-class Americans.”

But is this an accurate picture of the Simpsons family over time? And does that picture accurately represent a typical family in the US? Let’s investigate. And let’s start by pointing out that as measured by the availability of consumption goods, the Simpsons do see rising prosperity over time. They have flat screen TVs now, instead of consoles with rabbit ears, as the late Steve Horwitz and Stewart Dompe point out in their contribution to the edited volume Homer Economicus. But with all due respect to my friends Steve and Stewart, I don’t think many would deny that TVs, cell phones, and computers are cheaper today than in the 1990s. The familiar refrain is “but what about housing, education, and health care?”

In this post I want to take on the question of housing, partially by using the Simpsons as an example. My main result is this chart, which I will present first and then explain.

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Health Insurance Benefit Mandates and Health Care Affordability

My article on benefit mandates was published today at the Journal of Risk and Financial Management. It begins:

Every US state requires private health insurers to cover certain conditions, treatments, and providers. These benefit mandates were rare as recently as the 1960s, but the average state now has more than forty. These mandates are intended to promote the affordability of necessary health care. This study aims to determine the extent to which benefit mandates succeed at this goal

I began my research career by writing about these mandates, and my goal with this article was to tie up that whole chapter. I realized that all my articles on benefit mandates, as well as most of what other economists write about them, simply try to measure their costs- how much they raise health insurance premiums, raise employee contributions to premiums, lower wages, lower employment, or harm smaller businesses. Its good to know their costs, but to really evaluate a policy we should learn about its benefits too so that we can compare costs and benefits.

One key benefit that had yet to be measured was how much a typical mandate lowers out-of-pocket health care costs. In this article, I estimate that the average benefit mandate lowers costs by 0.8%-1%. I argue that combining this with a measure of how mandates affect total health spending by households could provide a sufficient statistic for the net benefits of mandates for households. I’m not totally confident this works in theory though, and it has a big challenge in practice- one of my empirical strategies finds that mandates reduce total spending, but the other finds they don’t. So I think the main contribution of the article ends up being the first estimate of how the average state health insurance benefit mandate affects out-of-pocket costs.

I’m currently planning to move on from writing about mandates- other topics are catching my eye, state policymakers don’t seem to particularly care what the research says about mandates, and changes in how economists use difference-in-difference methods are making it harder to publish articles like this that study continuous treatments. But I think there are still big opportunities here for anyone who wants to take up the torch. First, the ACA Essential Health Benefits provision changed the game for state mandates in a way that I have yet to see the empirical literature grapple with. Second, there are more than a hundred separate types of state benefit mandates; in most of my articles I aggregate them but they should really be studied separately. A handful have been, such as mandates for autism treatments, infertility treatments, and telemedicine. But the vast majority appear to be completely unstudied.

P.S. Writing this article gave me two wildly varying opinions of our federal bureaucracy. I tried to get both data and funding from the Agency for Healthcare Research and Quality for this article. The data side worked well- they were surprisingly fast, efficient and reasonable about the process of accessing restricted data. On the other hand, I applied for funding from AHRQ in March 2019 and still have yet to officially hear back about it (it is “pending council review” in NIH Commons). This sort of thing is why nimble organizations like Fast Grants can do so much good despite having much smaller budgets.

P.P.S. This article is part of a special issue on Health Economics and Insurance that is still accepting submissions. I’m the guest editor and would handle your submission, though my own got handled by other editors and put though multiple rounds of revisions.

Is Global Capitalism Increasing Poverty?

A few days ago on Twitter, Nathan Robinson made the claim that global capitalism wasn’t reducing poverty. In fact, it appears that poverty, using the threshold of $10/day (rather than the usual lower numbers) has increased from 1981 to 2017:

While there were a lot of critical responses to him on Twitter, he’s not wrong about the data: in 2017, there were 1.3 billion more people living on less than $10 per day (we’re going to assume in this post that the underlying data is basically correct, and correctly adjusted for inflation and purchasing power). It’s also true that at lower thresholds, such as $1.90 and $3.20, the absolute number of poor people has declined. And as a proportion of the world population, fewer people are under $10 per day. But in absolute terms there are more people under $10 per day. And not just a few: over a billion! There are also a lot more people above $10/day in the world than in 1981 (1.7 billion more!), but I agree that we should be concerned if there are more poor people too.

So how should we think about these numbers? Here’s what I think is the fundamental problem with Robinson’s claim: he asserts that the entire world has experienced something called “global capitalism” during this time period. But there has been considerable variation in the extent to which countries have experienced something we would call “capitalism,” and the degree to which it has increased in the past 40 years (I wrote a series of Tweets on this too).

The easiest way to see this is to break down that 1.3 billion people into different countries. Where were the biggest increases? Also, did any countries experience decreases in poverty? (Spoiler alert: YES!)

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What Proportion of Journalists Live in NYC?

Michael’s post this week on the dangers of high-status, low wage jobs opened by citing this tweet:

Michael presents a fascinating model that applies well beyond journalism. But when his post went viral, some commenters asked how accurate Josh Barro’s claim about half of young journalists living in Brooklyn was. Clearly Michael’s post doesn’t depend on it being true, and I’m not even sure Barro meant it literally, but it got me wondering- just what proportion of all young journalists do live in NYC?

For a first pass, we can look at the BLS Occupational Employment and Wage Statistics for the category “News Analysts, Reporters, and Journalists“. Their latest data (May 2020) shows 41,580 workers employed in those occupations nationwide. It also shows that the NYC metro has by far the most journalists with 5,940, more than twice as many as the second place metro (DC). This implies that 14.2% of all journalists in America live in the NYC metro. Since only 6% of all Americans live in the NYC metro, journalists are clearly clustering there, though clearly well over half of journalists still live elsewhere.

But, this doesn’t quite get at Barro’s claim, which is about journalists under 40 concentrating in Brooklyn. I don’t know of any data source that would let me really test the Brooklyn part, but I can get at the under-40 claim using Microdata from the American Community Survey, which also zooms us in a bit closer to Brooklyn since it tells us who is in NYC proper (not just the metro area).

The 2019 ACS shows that 10% of all “news analysts, reporters, and journalists” are in NYC proper, rising to 14% if I only consider journalists under 40 years old. This is quite concentrated (only 2.5% of all Americans live in NYC proper), but still a lot less that half of all journalists.

As Michael suggested, the vast majority of young NYC journalists are white (77%) with a college degree (91%), though English was only their second most common major after Communications.

The data confirm the last part of Michael’s post quite well- as journalists get older they are likely to move out of NYC and switch to more lucrative fields like PR. Only 5% of all “public relations specialists” are in NYC.

What’s a Sewer Worth?

Have access to clean water and a functioning sewer system is something that many Americans take for granted. Not all Americans, of course, especially those in rural areas not connected to an urban water system. But most Americans do. But how much is it worth?

It’s a hard question to answer. We know clean water and sewers probably have large effects on disease transmission. For example, Ferrie and Troesken (2008) looked at several major improvements in Chicago’s water system, and found that there were large declines in mortality from diseases like typhoid fever after the improvements (here’s an ungated working paper, with the much better title “Death and the City“). But the limits of earlier studies like this are that they primarily looking at a time series of mortality rate and relating this to some change in public infrastructure. A good attempt, but perhaps not convincing to everyone.

A better method would be to look at not mortality rates but property values. People are, surely, willing to pay more for a home with piped water and a sewer system. But how much more? Knowing this could give us better information on the value of the water systems. And that’s exactly what the authors of a new working paper do, once again visiting Chicago in the nineteenth century to look at how much property values increased after the installation of water and sewer systems. The paper is “The Value of Piped Water and Sewers” by Coury, Kitagewa, Shertzer, and Turner (ungated version).

The effects are huge. There most conservative estimate is that sewer and water systems doubled property values (a 110% increase), but the effect could be much larger (almost 4 times as much, if I am reading it correctly, under other reasonable assumptions).

People are willing to pay a lot for sanitation, it turns out.

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Are Special Elections Special?

While the United States does have its problems with democracy, one area where we shine is direct democracy. Rare at the federal level, at the state and local level direct democracy is quite common in the US, much more so than most other democracies (Switzerland also stands out). Almost half the states have some form of citizen initiative or referendum process, and it is used frequently in most of those states. But even more direct democracy takes place at the local level.

And much of that direct democracy at the local level takes place through what are called special elections. I’m not talking about elections to fill unexpected vacancies in office — though of course those do happen. I’m talking about actual voting on issues. Many of these issues revolve around questions of public finance: whether to raise a local sales tax, to approve a property tax millage, or to issue bonds for a capital project.

One very relevant example for me is an upcoming special election in my city of Conway, Arkansas. Citizens are being asked to approve the issuing of bonds to construct a community center, pool, soccer fields, and some other amenities. The bonds would be secured by a tax on restaurants. The tax already exists — city councils can put these in place without a public vote. But to issue bonds, the citizens must be asked. I wrote an op-ed about it in my local paper (if that is gated, try this blog post).

The key is that this is a special election. There are no other issues on the ballot. It takes place on February 8th, not a date that probably stands out in voters minds as an election date. What will this special election mean for voter turnout? A lot of academic research, including a paper that I wrote (currently under review, but summarized here), finds clear evidence that voter turnout will be much lower. Will the result be different? Again, a lot of evidence suggests yes. For example, property tax elections in Louisiana were less likely to pass with higher turnout, and less likely to pass in a general election (my research finds a similar result for sales tax elections in Arkansas).

But why are tax increases less likely to pass in special elections? On this question there are many theories, but they are hard to test. Is it because different kinds of voters show up at special elections, representing a different sample of the population? Possibly, but evidence is hard to find.

A new paper just published in the American Political Science Review sheds some light on these questions.

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Is the Labor Market Back?

Last month I asked if travel was back. Air travel has recovered a lot from the depths of the pandemic, but it was still only about 80-85% of pre-pandemic levels.

Labor markets also plummeted during the worst of the pandemic, and have slowly (and sometimes quickly) clawing their way back. But are we back to pre-pandemic levels?

The national unemployment rate is now under 4%, a level which is rarely reached even in the best of times. But there is considerable variation across states.

The latest BLS release of state unemployment data shows that some states are at their historic lows, with one state standing out: Nebraska currently has the lowest unemployment rate a state has ever recorded at 1.7% in December 2021 (the data go back to 1976). Utah is also just below 2% in December — at 1.9% it’s the 2nd lowest in history (after Nebraska, of course).

Of course, all is not well everywhere. California and Nevada have the highest unemployment rates, at around 6.5%. This is well above their pre-pandemic levels of about 4%, and also well above what you would expect during normal times, other than during and immediately following at recession.

So is the labor market back in Nebraska, Utah, and other similar states? Not so fast.

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Housing & The Fed’s Reputation

I am not worried about inflation and I’m not worried about the total spending in the economy. As I’ve said previously, total spending is on track with the pre-pandemic trend and, I think, that helped us experience the briefest recession in US history. When output growth declines below trend, we face higher prices or lower incomes. The former causes inflation, the latter causes large-scale defaults. Looking at the historical record, I’m for more concerned about the latter.

I do, however, want to call special attention to the composition of the Fed’s balance sheets. Specifically, its Mortgage Backed Security (MBS) assets. Having learned from the 2008 recession, the Fed was very intent on maintaining a stable and liquid housing market. Purchasing MBS is one way that it maintained that stability. Its total MBS holdings almost doubled from March of 2020 to December of 2021 to $2.6 trillion. Should we be concerned?

At first, a doubling sounds scary. And, anything with the word ‘trillion’ is also scary. Even the graph below looks a little scary. MBS holdings by the Fed jumped and have continued to increase at about a constant rate. Is the housing market just being supported by government financing? What happens when the Fed decides to exit the market?

Luckily for us, there is precedent for Fed MBS tapering. The graph below is in log units and reflects that a similar acceleration in MBS purchases occurred in 2013. Fed net purchases were practically zero by 2015 and total MBS assets owned by the Fed were even falling by 2018. Do you remember the recession that we had in 2013 when the Fed stopped buying more MBS’s? Wasn’t 2018-2019 a rough time for the economy when the Fed started reducing its MBS holdings? No. We experienced a recession in neither 2013 nor 2018. Financial stress was low and RGDP growth was unexceptional.

Although there was no macroeconomic disruption, what about the residential sector performance during those times? Here is a worrisome proposed chain of causation:

  1. Relative to a heavier MBS balance sheet, the Fed reducing its holdings increases supply on the MBS market.
  2. This means that the return on creating new MBS’s falls (the price rises).
  3. A lower return on MBS’s means that there is less demand from the financial sector for new loans from loan originators.
  4. A tighter secondary market for mortgages decreases the eagerness with which banks lend to individuals.
  5. Fewer loans to individuals puts downward pressure on the demand for houses and on the price of the associated construction materials.

The data fits this story, but without major disruption.

Less eager lenders went hand-in-hand with higher mortgage rates and less residential construction spending. The substitution effect pushed more real-estate lending and spending to the commercial side. Whereas residential spending was almost the same in late 2019 as it was in early 2018, commercial real-estate spending rose 13% over the same time period.

But, importantly in the story, the income effect of a Fed disruption should have been negative, resulting in less total spending and lower construction material prices. And that’s not what happened. Total Construction spending rose and so did construction material prices. Both of these are the opposite of what we would expect if the Fed had caused disruption in the housing construction sector due to its MBS holding changes.   Spending on residential construction fell understandably. But spending on commercial construction and the price of construction materials rose.

My point is that you should not listen to the hysteria.

The Fed has a variety of assets on its balance sheet and it pays special attention to the residential construction sector. Do you think that there is a residential asset bubble? Ok. Now you have to address whether the high prices are due to demand or supply. Do you suspect that the Fed unloading its MBS’s will result a popped bubble and maybe even contagion? It’s ok – you’re allowed to think that. But the most recent example of the Fed doing that didn’t result in either a macroeconomic crisis or substantial disruption in the construction markets.

The Fed has a track record and it has a reputation that serves as valuable information concerning its current and prospective activities. The next time that someone gets hysterical about Fed involvement in the housing sector, ask them what happened last time? Odds are that they don’t know. Maybe that information doesn’t matter for their opinion. You should value their opinion accordingly.

Are Car Accidents Getting Labeled as “COVID Deaths”?

Of all the increases in mortality in 2020, one that is notable is motor vehicle accidents. There were 43,045 deaths from motor vehicle accidents, according to the final CDC data. This means motor vehicle accident was listed on the death certificate, even if it was not determined to be the “underlying cause,” though for 98% of these deaths the accident was listed as the underlying cause.

The increase from past years was large. Compared with 2019, there were over 3,000 more motor vehicle deaths, though such as increase is not unheard of: 2015 and 2016 each saw increases of around 2,500. Even so, the crude death rate from motor vehicle accidents in 2020 was the highest it has been since 2008.

If that weren’t bad enough, another theory emerged in 2020 and continues to be suggested today: that car crashes are being labeled as “COVID deaths,” artificially inflating the COVID death count. While one can find this claim made almost daily by anonymous Twitter users, one of the most prominent statements was on Fox News in December 2020. Host Raymond Arroyo said that car accidents were being counted as COVID deaths, and that due to errors like this COVID deaths could be inflated by as much as 40 percent. Senator Marco Rubio made a similar claim on Twitter in December 2021, though he was talking about hospitalizations, not deaths.

Back in 2020, many doctors and medical professionals tried to debunk the “car accidents being labeled as COVID deaths” claim, but the problem was we didn’t have complete data. Anonymous anecdotes were cited, but medical professionals tried to reassure the public this wasn’t the case or at least wasn’t widespread.

But now, we have the data! That is, the complete CDC mortality data for 2020 available through the CDC WONDER database.

What does this data show us? Short answer: there aren’t that many car accidents being labeled as COVID deaths. At most, it’s about 0.03% of COVID deaths.

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