Economics

Inflation Empirics

Zachary Bartsch2 Comments

Way back in the late 1970s and early 80s, Kydland and Prescott proposed rational expectations theory. This line of research arose, in part, because the Phillips curve ceased to describe reality well. Amid increasing inflation, people began to anticipate higher prices to a relatively correct degree when making labor, supply chain, and pricing decisions. Kydland and Prescott argued that individuals understand the rules of the game or how the world works – at least on average.

An increase in the money supply would increase total national spending, and increase demand for goods. However, firms also experienced increasing revenues and demanded more inputs such as commodities, capital, and intermediate goods. Because there were no greater productivity earlier in the supply chain, price roses. Firms began to understand that greater demand would eventually find its way to causing greater costs. Therefore, firms began raising prices before the cost of resources rose, increasing their willingness to pay for inputs and, ironically, hastening the increase in input prices. As a result, increases in the money supply began having substantial short-run price effects and negligible output effects.

However, assuming that people understand the rules of our economic system and ‘how the world works’ is hard to swallow. It is not at all clear that the typical economist understands monetary theory, much less clear that the typical person has a good understanding. Fortunately, another theory of expectations can help carry some of the load and achieve similar results.

Adaptive Expectations

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Economics of the Russia-Ukraine Conflict

James Bailey4 Comments

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

Jeremy Horpedahl5 Comments

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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Asymmetric Liability, Common Law, & Urbanization

Zachary Bartsch1 Comment

Tort law is interesting. You can argue that someone harmed you, and you can cite almost no legislation in the process. Torte law in the US uses case law – the precedent set by previous rulings in the context of social norms. But, what cases did the early cases cite? They also cited earlier cases and social norms, though we may no longer have a record. The beauty of tort law it allows for changing relative costs in prudence and negligence.

Can you imagine a legislature attempting to codify the appropriate amount of neglect by, say, a painter? The standards would quickly go out of date. The relative cost of resources including labor, communications, materials, and the price differences among competitors of differing quality all change over time. Multiply these factors by 20 and then again by the number of occupations and regions in a country. You will quickly see that legislating the appropriate degree of prudence and neglect through congress is a fool’s errand. The challenge is too complicated and the world changes too quickly. In fact, attempting to legislate definitions for neglect and prudence could even backfire and result in regulatory arbitrage, which occurs when firms comply with de jur rules while avoiding them de facto.*

Externalizing Costs

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Health Insurance Benefit Mandates and Health Care Affordability

James BaileyLeave a comment

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?

Jeremy HorpedahlLeave a comment

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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Mises’s Bureaucracy, a Recap

Zachary Bartsch3 Comments

My favorite two economists are Ludwig Von Mises and Milton Friedman. They might consider one another from very different schools of thought, though there is reason to think that they are not so different. As an undergraduate student, I liked them both, but I became more empirics-minded in graduate school and as a young assistant professor.

As I progressed through graduate school and conducted empirical research, my opinions and policy prescriptions changed and were refined from what they once were. In graduate school, I didn’t study Austrian Economics, though it was certainly in the water at George Mason University. Recently, as an assistant professor with a few years under my belt, I picked up Bureaucracy (1944) and read it as a matter of leisure.

One word:

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What’s a Sewer Worth?

Jeremy HorpedahlLeave a comment

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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Controversial Study Finds Lockdowns Don’t Reduce COVID Mortality; Some Less Controversial Takeaways

Scott Buchanan2 Comments

A recent working paper, A LITERATURE REVIEW AND META-ANALYSIS OF THE EFFECTS OF LOCKDOWNS ON COVID-19 MORTALITY,  released by Steve Hanke (professor of Applied Economics at Johns Hopkins) and other applied economists (Jonas Herby of Denmark and Lars Jonung of Sweden) has been understandably controversial. I will survey some of its methods and conclusions, and (very briefly) some of the reactions to it.

I will not take a position on how valid its conclusions are, for the simple reason that I am totally unqualified to make such a judgement. What I would like to contribute are a couple of takeaways that are worth considering for the next pandemic or even the remainder of this one.

Methodology of the Paper

Where and how you start largely determines where you will end up. The authors included studies which were (as much as possible) straight apples-to-apples ex post empirical observations (e.g., between otherwise similar countries or U.S. states, at similar times), while avoiding ex ante studies which relied primarily on models of what-would-have-happened-without-lockdowns:

They write (I omit some details, marked with ellipses):

We distinguish between two methods used to establish a relationship (or lack thereof) between mortality rates and lockdown policies. The first uses registered cross-sectional mortality data. These are ex post studies. The second method uses simulated data on mortality and infection rates. These are ex ante studies.

We include all studies using a counterfactual difference-in-difference approach from the former group but disregard all ex ante studies, as the results from these studies are determined by model assumptions and calibrations.

Our limitation to studies using a “counterfactual difference-in-difference approach” means that we exclude all studies where the counterfactual is based on forecasting (such as a SIR-model) rather than derived from a difference-in-difference approach. This excludes studies like…We also exclude all studies based on interrupted time series designs that simply compare the situation before and after lockdown, as the effect of lockdowns in these studies might contain time-dependent shifts, such as seasonality. This excludes studies like….

The authors in particular address a study by Seth Flaxman, which had claimed great effectiveness for lockdowns. They note Flaxman’s modeling approach likely overstated the effects of lockdowns, as noted by other critics of Flaxman:

Given our criteria, we exclude the much-cited paper by Flaxman et al. (2020), which claimed that lockdowns saved three million lives in Europe. Flaxman et al. assume that the pandemic would follow an epidemiological curve unless countries locked down. However, this assumption means that the only interpretation possible for the empirical results is that lockdowns are the only thing that matters, even if other factors like season, behavior etc. caused the observed change in the reproduction rate, Rt. Flaxman et al. are aware of this and state that “our parametric form of Rt assumes that changes in Rt are an immediate response to interventions rather than gradual changes in behavior.” Flaxman et al. illustrate how problematic it is to force data to fit a certain model if you want to infer the effect of lockdowns on COVID-19 mortality.

Conclusions and Controversy

In the interests of time/space, I will give just a few snapshots here. A key conclusion is:

Overall, our meta-analysis fails to confirm that lockdowns have had a large, significant effect on mortality rates. Studies examining the relationship between lockdown strictness (based on the OxCGRT stringency index) find that the average lockdown in Europe and the United States only reduced COVID-19 mortality by 0.2% compared to a COVID-19 policy based solely on recommendations. Shelter-in-place orders (SIPOs) were also ineffective. They only reduced COVID-19 mortality by 2.9%.

The authors are well aware that this is highly controversial, so they cite other studies that have reached similar conclusions. They offer further defenses against a number of other objections, which again I will not elucidate here.

As might be expected, U.S. mainstream media outlets (which have long accused red-state governors of reckless endangerment for not locking down as hard as blue states) have either ignored this paper, or tried to discredit it. An article in the Sacramento Bee, for instance, devoted nearly a whole paragraph to statements by Seth Flaxman (yes, that Seth Flaxman, see above) attacking the paper, while not reaching out to the paper’s authors for a response. And as might be expected, right-leaning media outlets are citing the study as vindicating the freedom-loving red states’ policies over against the heavy-handed Establishment.

Some Maybe Useful Takeaways

Pushing past this predictable partisan unpleasantness, I’ll share a couple of items from the paper that seem worth pondering. One was a strong statement of the harms done by lockdowns, with a plea for considering these in future policy-making. This sort of balancing of wide-ranging consequences is normally considered enlightened economics; in general, we as a society do not say, “The only thing that matters is saving/prolonging every life, no matter the other costs” :

The use of lockdowns is a unique feature of the COVID-19 pandemic. Lockdowns have not been used to such a large extent during any of the pandemics of the past century. However, lockdowns during the initial phase of the COVID-19 pandemic have had devastating effects. They have contributed to reducing economic activity, raising unemployment, reducing schooling, causing political unrest, contributing to domestic violence, and undermining liberal democracy. These costs to society must be compared to the benefits of lockdowns.

The other general issue that was touched on at several points in the paper was the importance of voluntary (as opposed to mandated) social distancing. Nothing in this paper disputed that social distancing, especially in pandemic peak periods, will slow the spread of a disease. The issue here is the effectiveness of state-imposed measures versus voluntary actions. These voluntary actions could be (on the positive side) conscious adoption of distancing and masking with or without legal requirement, or (on the other side) flouting of the laws or careless interpersonal contacts which were unsafe even if they were not illegal. These more risky actions may simply reflect local cultural attitudes (which are hard to change), or they may reflect less urgent government messaging (which is something that can be addressed by policy). A couple of relevant paragraphs are:

What explains the differences between countries, if not differences in lockdown policies? Differences in population age and health, quality of the health sector, and the like are obvious factors. But several studies point at less obvious factors, such as culture, communication, and coincidences. For example, Frey et al. (2020) show that for the same policy stringency, countries with more obedient and collectivist cultural traits experienced larger declines in geographic mobility relative to their more individualistic counterpart. Data from Germany Laliotis and Minos (2020) shows that the spread of COVID-19 and the resulting deaths in predominantly Catholic regions with stronger social and family ties were much higher compared to nonCatholic ones…

Government communication may also have played a large role. Compared to its Scandinavian neighbors, the communication from Swedish health authorities was far more subdued and embraced the idea of public health vs. economic trade-offs. This may explain why Helsingen etal. (2020), found, based on questionnaire data collected from mid-March to mid-April, 2020, that even though the daily COVID-19 mortality rate was more than four times higher in Sweden than in Norway, Swedes were less likely than Norwegians to not meet with friends (55% vs. 87%), avoid public transportation (72% vs. 82%), and stay home during spare time (71% vs. 87%). That is, despite a more severe pandemic, Swedes were less affected in their daily activities (legal in both countries) than Norwegians.

And:

We believe that Allen (2021) is right, when he concludes, “The ineffectiveness [of lockdowns] stemmed from individual changes in behavior: either non-compliance or behavior that mimicked lockdowns.” In economic terms, you can say that the demand for costly disease prevention efforts like social distancing and increased focus on hygiene is high when infection rates are high. Contrary, when infection rates are low, the demand is low and it may even be morally and economically rational not to comply with mandates like SIPOs, which are difficult to enforce. Herby (2021) reviews studies which distinguish between mandatory and voluntary behavioral changes. He finds that – on average – voluntary behavioral changes are 10 times as important as mandatory behavioral changes in combating COVID-19. If people voluntarily adjust their behavior to the risk of the pandemic, closing down non-essential businesses may simply reallocate consumer visits away from “nonessential” to “essential” businesses, as shown by Goolsbee and Syverson (2021), with limited impact on the total number of contacts.

Looking at the vastly different death tolls per capita between, say, Australia (with a more rigorous lockdown and quarantining policy) and the U.S. or U.K, I find it difficult to believe that policy mandates have as little effect as found in this study. That point aside, I think the study is helpful in reminding us that it is what people actually do that matters. Foot-dragging compliance with imposed regulations is a different thing than fully-bought-in compliance, which speaks to motivation and values.

Regarding messaging by governments and other organizations, I suspect that there is not a one-size-fits-all motivational message here. It could be worth reflecting on what sort of message would resonate with a particular population subgroup. (This is just basic Marketing 101: Identify your various segments and tailor the messages to them). Berating some subgroup for their poor choices to date may make the berators feel warmly superior, but that does not move things forward.

I’ll close with some anecdotal observations regarding behaviors, independent of mandates. I have personally continued to generally avoid gatherings where large numbers of people are talking or singing, and wear an effective mask*  when in such a meeting, regardless of what the current rules are.

Also, I have shuttled back and forth between northern Virginia (very blue) and Alabama (very red) in the past two years. Whether or not formal lockdowns or mask mandates were in force, I saw much more mask-wearing in northern Virginia, compared to Alabama. I suspect this reflected overall attitudes and behaviors regarding social distancing. Not saying one is right and one is wrong, but the total COVID deaths per 100,000 in Virginia (196) to date are roughly half of deaths in Alabama (356).

*See Suggestions for Comfortable and Effective Face Masks, e.g., Korean KF94’s on effective, comfortable face masks

Teaching Price Controls (Poorly)

Zachary Bartsch3 Comments

Economics textbooks differ in their treatment of price controls. None of them does a great job, in my opinion. The reason is mostly due to the purpose of textbooks. Despite what you might suspect, most undergraduate textbooks are not used primarily to give students an understanding of the world. They are often used as a bound list of things to know and to create easy test questions. If a textbook has to change the assumptions of a model too much from what the balance of the chapter assumes, then the book fails to make clear what students are supposed to know for the test.

I think that this is the most charitable reason for books’ poor treatment of price controls – even graduate level books. The less charitable reasons include sloppy exposition due to author ignorance or an over-reliance on math. I honestly would have trouble believing these less charitable reasons.

I picked up 5 microeconomics text books and the below graph is typical of how they treat a price ceiling.

The books say that the price ceiling is perfectly enforced. They identify producer surplus (PS) as area C and consumer surplus (CS) as areas A & B. There are very good reasons to differ with these welfare conclusions.

Problem #1

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