I don’t think there are many people who would say that 2020 was their favorite year. Even if everything else had gone right, the 1.7 million deaths from the COVID pandemic would already make this a very bad year.
And this Christmas season certainly felt quite different, with most of us unable to safely travel and forced to interact with our families only via video calls. New Year’s this year won’t feel like a celebration of a successful year so much as relief that we finally made it through.
Many of us have lost loved ones. Fortunately none of my immediate friends and family have died of COVID, but I can now count half a dozen acquaintances, friends-of-friends or distant relatives who are no longer with us. And I’ve been relatively lucky overall; both I and my partner work in jobs that are easy to do remotely, so our lives haven’t had to change all that much.
Yet 2020 is nearly over, and already there are signs that things really will get better in 2021. There are many good reasons for hope.
Over the last 20 years, real per-capita GDP has risen from $46,000 to $56,000 (in 2012 dollars):
It’s not just increasing inequality (though it is partly that); real median household income has increased over the same period from $62,500 to $68,700 (in 2019 dollars):
The American Enterprise Institute has utterly the wrong interpretation of what’s going on here, but their graph is actually quite informative if you can read it without their ideological blinders:
Over the past 20 years, some industries have seen dramatic drops in prices, such as televisions, cellphones, toys, and computer software. Other industries have seen roughly constant prices, such as cars, clothing, and furniture. Still other industries have seen modest increases in prices that tracked overall inflation, such as housing and food. And then there are some industries where prices have exploded to staggering heights, such as childcare, college education, and hospital services.
Since wages basically kept up with inflation, this is the relevant comparison: A product or service is more expensive in real terms if its price grew faster than inflation.
It’s not inherently surprising that some prices would rise faster than inflation and some would rise slower; indeed, it would be shocking if that were not the case, since inflation essentially just is an average of all price changes over time. But if you look closely at the kinds of things that got cheaper versus more expensive, you can begin to see why the statistics keep saying we are getting richer but we don’t feel any richer.
The things that increased the most in price are things you basically can’t do without: Education, childcare, and healthcare. Yes, okay, theoretically you could do without these things, but the effects on your life would be catastrophic—indeed, going without healthcare could literally kill you. They are necessities.
The things that decreased the most in price are things that people have done without for most of human history: Cellphones, software, and computer software. They are newfangled high-tech goods that are now ubiquitous, but not at all long ago didn’t even exist. Going without these goods would be inconvenient, but hardly catastrophic. Indeed, they largely only feel as necessary as they are because everyone else already has them. They are luxuries.
This even explains why older generations can be convinced that we are richer than the statistics say: We have all these fancy new high-tech toys that they never had. But what good does that do us when we can’t afford our health insurance?
Housing is also an obvious necessity, and while it has not on average increased in price faster than inflation, this average washes out important geographic variation.
Over the same period, Detroit’s housing prices plummeted, then returned to normal, and are now only 30% higher than they were 20 years ago (comparable to inflation):
It’s hardly surprising that the cities where the most people are moving to are the most expensive to live in; that’s basic supply and demand. But the magnitude of the difference is so large that most of us are experiencing rising housing prices, even though on average housing prices aren’t really rising.
Put this all together, and we can see that while by the usual measures our “standard of living” is increasing, our financial situation feels ever more precarious, because more and more of our spending is immediately captured by things we can’t do without. I suggest we call this effect necessitization; our consumption has been necessitized.
Healthcare is the most extreme example: In 1960, healthcare spending was only 5% of US GDP. As recently as 2000, it was 13%. Today, it is 18%. Medical technology has greatly improved over that time period, increasing our life expectancy from 70 years in 1960 to 76 years in 2000 to 78 years today, so perhaps this additional spending is worth it? But if we compare 2000 to 2020, we can see that an additional 5% of GDP in the last 20 years has only bought us two years of life. So we have spent an additional 5% of our income to gain 2.6% more life—that doesn’t sound like such a great deal to me. (Also, if you look closely at the data, most of the gains in life expectancy seem to be from things like antibiotics and vaccines that aren’t a large part of our healthcare spending, while most of the increased spending seems to be on specialists, testing, high-tech equipment, and administrative costs that don’t seem to contribute much to life expectancy.)
Moreover, even if we decide that all this healthcare spending is worth it, it doesn’t make us richer in the usual sense. We have better health, but we don’t have greater wealth or financial security.
AEI sees that the industries with the largest price increases have the most government intervention, and blames the government; this is clearly confusing cause with effect. The reason the government intervenes so much in education and healthcare is because these are necessities and they are getting so expensive. Removing those interventions wouldn’t stop prices from rising; they’d just remove the programs like Medicaid and federal student loans that currently allow most people to (barely) afford them.
But they are right about one thing: Prices have risen much faster in some industries than others, and the services that have gotten the most expensive are generally the services that are most important.
Why have these services gotten so expensive? A major reason seems to be that they are difficult to automate. Manufacturing electronics is very easy to automate—indeed, there’s even a positive feedback loop there: the better you get at automating making electronics, the better you get at automating everything, including making electronics. But automating healthcare and education is considerably more difficult. Yes, there are MOOCs, and automated therapy software, and algorithms will soon be outperforming the average radiologist; but there are a lot of functions that doctors, nurses, and teachers provide that are very difficult to replace with machines or software.
Suppose we do figure out how to automate more functions of education and healthcare; would that solve the problem? Maybe—but only if we really do manage to automate the important parts.
Right now, MOOCs are honestly terrible. The sales pitch is that you can get taught by a world-class professor from anywhere in the world, but the truth is that the things that make someone a world-class professor don’t translate over when you are watching recorded video lectures and doing multiple-choice quizzes. Really good teaching requires direct interaction between teacher and student. Of course, a big lecture hall full of hundreds of students often lacks such interaction—but so much the worse for big lecture halls. If indeed that’s the only way colleges know how to teach, then they deserve to be replaced by MOOCs. But there are better ways of teaching that online courses currently cannot provide, and if college administrators were wise, they would be focusing on pressing that advantage. If this doesn’t happen, and education does become heavily automated, it will be cheaper—but it will also be worse.
Similarly, some aspects of healthcare provision can be automated, but there are clearly major benefits to having actual doctors and nurses physically there to interact with patients. If we want to make healthcare more affordable, we will probably have to find other ways (a single-payer health system comes to mind).
For now, it is at least worth recognizing that there are serious limitations in our usual methods of measuring standard of living; due to effects like necessitization, the statistics can say that we are much richer even as we hardly feel richer at all.
The race to the bottomis a common result of competition, between firms, between states, or even between countries. One firm finds a way to cut corners and reduce costs, then lowers their price to undercut others; then soon every firm is cutting those same corners. Or one country decides to weaken their regulations in order to attraction more business; then soon every other country has to weaken their regulations as well.
Let’s first consider individual firms. Suppose that you run a business, and you are an upstanding, ethical person. You want to treat your employees, your customers, and your community well. You have high labor standards, you exceed the requirements of environmental regulations, and you make a high-quality product at a reasonable price for a moderate profit.
Then, a competitor appears. The owner of this company is not so ethical. They exploit their workers, perhaps even stealing their wages. They flaunt environmental regulations. They make shoddy products. All of this allows them to make their products for a lower price than yours.
Suppose that most customers can’t tell the difference between your product and theirs. What will happen? They will stop buying yours, because it’s more expensive. What do you do then?
You could simply go out of business. But that doesn’t really solve anything. Probably you’ll be forced to lower your standards. You’ll treat your workers worse, pollute more, reduce product quality. You may not do so as much as the other company, but you’ll have to do it some in order to get the price down low enough to still compete. And your profits will be lower than theirs as a result.
Far better would be for the government to step in and punish that other business for breaking the rules—or if what they’re doing is technically legal, change the rules so that it’s not anymore. Then you could continue to produce high-quality products with fair labor standards and good environmental sustainability.
But there are some problems with this. First, consider this from the point of view of a regulator, who is being lobbied by both companies. Your company asks for higher standards to improve product quality while protecting workers and the environment. But theirs claims that these higher standards will push them out of business. Who will they believe?
In fact, it may be worse than that: Suppose we’ve already settled into an equilibrium where all the firms have low standards. In that case, all the lobbyists will be saying that regulations need to be kept weak, lest the whole industry fail.
But in fact there’s no reason to think that stricter regulations would actually destroy the whole industry. Firm owners are used to thinking in terms of fixed competitors: They act in response to what competitors do. And in many cases it’s actually true that if just one firm tried to raise their standards, they would be outcompeted and go out of business. This does not mean that if all firms were forced to raise their standards, the industry would collapse. In fact, it’s much more likely that stricter regulations would only moderately reduce output and profits, if imposed consistently across the whole industry.
To see why, let’s consider a very simple model, a Bertrand competition game. There are two firms, A and B. Each can either use process H, producing a product of high quality with high labor standards and good sustainability, or use process L, producing a product of low quality with low labor standards and poor sustainability. Process H costs $100 per unit, process L costs $50 per unit. Customers can’t tell the difference, so they will buy whichever product is offered at the lowest price. Let’s say you are in charge of firm A. You choose which process to use, and set your price. At the same time, firm B chooses a process and sets their price.
Suppose choose to use process H. The lowest possible price you could charge to still make a profit would be a price of $101 (ignoring cents; let’s say customers also ignore them, which might be true!).
But firm B could choose process L, and then set a price of $100. They can charge just one dollar less than you charge for their product, but their cost is only $50, so now they are making a large profit—and you get nothing.
So you are forced to lower your standards, in order to match their price. You could try to undercut them at a price of $100, but in the long run that’s a bad idea, since eventually you’ll both be driven to charging a price of 51 and making only a very small profit. And there’s a way to stop them from undercutting you, which is to offer a price-matching guarantee; you can tell your customers that if they see a lower price from firm B than what you’re offering, you’ll match it for them. Then firm B has no incentive to try to undercut you, and you can maintain a stable equilibrium at a price of $100. You have been forced to used process L even though you know it is worse, because any attempt to unilaterally deviate from that industry norm would result in your company going bankrupt.
But now suppose the government comes in and mandates that all firms use process H, and they really enforce this rule so that no firm wants to try to break it. Then you’d want to raise the price, but you wouldn’t necessarily have to raise it all that much. Even $101 would be enough to ensure some profit, and you could even maintain your current profits by raising the price up to $150. In reality the result would probably be somewhere in between those two, depending on the elasticity of demand; so perhaps you end up charging $125 and make half the profit you did before.
Even though the new regulation raised costs all the way up to the current price, they did not result in collapsing the industry; because the rule was enforced uniformly, all firms were able to raise their standards and also raise their prices. This is what we should typically expect to happen; so any time someone claims that a new regulation will “destroy the industry” we should be very skeptical of that claim. (It’s not impossible; for instance, a regulation mandating that all fast food workers be paid $200 per hour would surely collapse the fast food industry. But it’s very unlikely that anyone would seriously propose a regulation like that.)
So as long as you have a strong government in place, you can escape the race to the bottom. But then we must consider international competition: What if other countries have weaker regulations, and so firms want to move their production to those other countries?
Well, a small country may actually be forced to lower their standards in order to compete. I’m not sure there’s much that Taiwan or Singapore could do to enforce higher labor standards. If Taiwan decided to tighten all their labor regulations, firms might just move their production to Indonesia or Vietnam. Then again, monthly incomes in Taiwan, once adjusted for currency exchange rates, are considerably higher than those in Vietnam. Indeed, wages in Taiwan aren’t much lower than wages in the US. So apparently Taiwan has some power to control their own labor standards—perhaps due to their highly educated population and strong industrial infrastructure.
Perhaps these rules go too far; while I agree with the concern about protectionism, I definitely think we should be doing more to enforce penalties for forced labor, for instance. But this is not the result of too little international governance—if anything it is the result of too much. Our free trade agreements are astonishingly binding, even on the most powerful countries (China has successfully sued the United States under WTO rules!). I wish only that our human rights charters were anywhere near as well enforced.
This means that the race to the bottom is not the inevitable result of competition between firms or even between countries. When it occurs, it is the result of particular policy regimes nationally or internationally. We can make better rules.
The first step may be to stop listening to the people who say that any change will “destroy the industry” because they are unable (or unwilling?) to understand how uniformly-imposed rules differ from unilateral deviations from industry norms.
But in fact, unemployment does not kill. The evidence on this is quite clear. Even in the Great Depression, with massive unemployment, terrible monetary policy, and only the most minimal social welfare measures in place, death rates did not increase. In fact, for all causes except suicide, death rates decrease during recessions—probably because pollution, traffic accidents, and work-related injury and illness go down. And the suicide rate increase isn’t enough to increase the overall death rate.
Of course, dying by suicide is not the same thing as dying from cancer—and indeed, they are most likely different people being affected in each case. So in that sense unemployment can kill people; but it typically saves more people than it kills. Almost any policy choice will cause some deaths and prevent others, so really the best we can do is look at the overall aggregate and see whether our QALY have gone up or down.
This doesn’t mean that we should go out of our way to have recessions in order to save lives; the number of lives saved is small and the loss in quality of life is probably large enough to compensate for it. (That’s why we use quality-adjusted life years after all.) But this recession isn’t arbitrary; it’s the result of trying to stop a global pandemic, so that we don’t have a repeat of what influenza did in 1918.
Many of the common critiques of economics are actually somewhat misguided, or at least outdated: While there are still some neoclassical economists who think that markets are perfect and humans are completely rational, most economists these days would admit that there are at least some exceptions to this. But there’s at least one common critique that I think still has a good deal of merit: “Good for the economy” isn’t the same thing as good.
I’ve read literally dozens, if not hundreds, of articles on economics, in both popular press and peer-reviewed journals, that all defend their conclusions in the following way: “Intervention X would statistically be expected to increase GDP/raise total surplus/reduce unemployment. Therefore, policymakers should implement intervention X.” The fact that a policy would be “good for the economy” (in a very narrow sense) is taken as a completely compelling reason that this policy must be overall good.
The clearest examples of this always turn up during a recession, when inevitably people will start saying that cutting unemployment benefits will reduce unemployment. Sometimes it’s just right-wing pundits, but often it’s actually quite serious economists.
The usual left-wing response is to deny the claim, explain all the structural causes of unemployment in a recession and point out that unemployment benefits are not what caused the surge in unemployment. This is true; it is also utterly irrelevant. It can be simultaneously true that the unemployment was caused by bad monetary policy or a financial shock, and also true that cutting unemployment benefits would in fact reduce unemployment.
Indeed, I’m fairly certain that both of those propositions are true, to greater or lesser extent. Most people who are unemployed will remain unemployed regardless of how high or low unemployment benefits are; and likewise most people who are employed will remain so. But at the margin, I’m sure there’s someone who is on the fence about searching for a job, or who is trying to find a job but could try a little harder with some extra pressure, or who has a few lousy job offers they’re not taking because they hope to find a better offer later. That is, I have little doubt that the claim “Cutting unemployment benefits would reduce unemployment” is true.
The problem is that this is in no way a sufficient argument for cutting unemployment benefits. For while it might reduce unemployment per se, more importantly it would actually increase the harm of unemployment. Indeed, those two effects are in direct proportion: Cutting unemployment benefits only reduces unemployment insofar as it makes being unemployed a more painful and miserable experience for the unemployed.
Indeed, the very same (oversimplified) economic models that predict that cutting benefits would reduce unemployment use that precise mechanism, and thereby predict, necessarily, that cutting unemployment benefits will harm those who are unemployed. It has to. In some sense, it’s supposed to; otherwise it wouldn’t have any effect at all.
That is, if your goal is actually to help the people harmed by a recession, cutting unemployment benefits is absolutely not going to accomplish that. But if your goal is actually to reduce unemployment at any cost, I suppose it would in fact do that. (Also highly effective against unemployment: Mass military conscription. If everyone’s drafted, no one is unemployed!)
Similarly, I’ve read more than a few policy briefs written to the governments of poor countries telling them how some radical intervention into their society would (probably) increase their GDP, and then either subtly implying or outright stating that this means they are obliged to enact this intervention immediately.
Don’t get me wrong: Poor countries need to increase their GDP. Indeed, it’s probably the single most important thing they need to do. Providing better security, education, healthcare, and sanitation are all things that will increase GDP—but they’re also things that will be easier if you have more GDP.
(Rich countries, on the other hand? Maybe we don’t actually need to increase GDP. We may actually be better off focusing on things like reducing inequality and improving environmental sustainability, while keeping our level of GDP roughly the same—or maybe even reducing it somewhat. Stay inside the wedge.)
But the mere fact that a policy will increase GDP is not a sufficient reason to implement that policy. You also need to consider all sorts of other effects the policy will have: Poverty, inequality, social unrest, labor standards, pollution, and so on.
To be fair, sometimes these articles only say that the policy will increase GDP, and don’t actually assert that this is a sufficient reason to implement it, theoretically leaving open the possibility that other considerations will be overriding.
But that’s really not all that comforting. If the only thing you say about a policy is a major upside, like it or not, you are implicitly endorsing that policy. Framing is vital. Everything you say could be completely, objectively, factually true; but if you only tell one side of the story, you are presenting a biased view. There’s a reason the oath is “The truth, the whole truth, and nothing but the truth.” A partial view of the facts can be as bad as an outright lie.
Of course, it’s unreasonable to expect you to present every possible consideration that could become relevant. Rather, I expect you to do two things: First, if you include some positive aspects, also include some negative ones, and vice-versa; never let your argument sound completely one-sided. Second, clearly and explicitly acknowledge that there are other considerations you haven’t mentioned.
Moreover, if you are talking about something like increasing GDP or decreasing unemployment—something that has been, many times, by many sources, treated as though it were a completely compelling reason unto itself—you must be especially careful. In such a context, an article that would be otherwise quite balanced can still come off as an unqualified endorsement.
The beauty and clearness of the dynamical theory, which asserts heat and light to be modes of motion, is at present obscured by two clouds. The first came into existence with the undulatory theory of light, and was dealt with by Fresnel and Dr. Thomas Young; it involved the question, how could the earth move through an elastic solid, such as essentially is the luminiferous ether? The second is the Maxwell-Boltzmann doctrine regarding the partition of energy.
The above quote is part of a speech where Kelvin basically says that physics is a completed field, with just these two little problems to clear up, “two clouds” in a vast clear horizon. Those “two clouds” Kelvin talked about, regarding the ‘luminiferous ether’ and the ‘partition of energy’? They are, respectively, relativity and quantum mechanics. Almost 120 years later we still haven’t managed to really solve them, at least not in a way that works consistently as part of one broader theory.
But I’ll give Kelvin this: He knew where the problems were. He vastly underestimated how complex and difficult those problems would be, but he knew where they were.
I’m not sure I can say the same about economists. We don’t seem to have even reached the point where we agree where the problems are. Consider another quotation:
For a long while after the explosion of macroeconomics in the 1970s, the field looked like a battlefield. Over time however, largely because facts do not go away, a largely shared vision both of fluctuations and of methodology has emerged. Not everything is fine. Like all revolutions, this one has come with the destruction of some knowledge, and suffers from extremism and herding. None of this deadly however. The state of macro is good.
But the content is also important: Blanchard didn’t say that microeconomics is in good shape (which I think one could make a better case for). He didn’t even say that economics, in general, is in good shape. He specifically said, right before the greatest economic collapse since the Great Depression, that macroeconomics was in good shape. He didn’t merely underestimate the difficulty of the problem; he didn’t even see where the problem was.
Wikipedia’s list is full of esoteric problems that require deeply faulty assumptions to even exist, like the ‘American option problem’ which assumes that the Black-Scholes model is even remotely an accurate description of how option prices work, or the ‘tatonnement problem’ which ignores the fact that there may be many equilibria and we might never reach one at all, or the problem they list under ‘revealed preferences’ which doesn’t address any of the fundamental reasons why the entire concept of revealed preferences may fail once we apply a realistic account of cognitive science. (I could go pretty far afield with that last one—and perhaps I will in a later post—but for now, suffice it to say that human beings often freely choose to do things that we later go on to regret.) I think the only one that Wikipedia’s list really gets right is ‘Unified models of human biases’. The ‘home bias in trade’ and ‘Feldstein-Horioka Puzzle’ problems are sort of edging toward genuine problems, but they’re bound up in too many false assumptions to really get at the right question, which is actually something like “How do we deal with nationalism?” Referring to the ‘Feldstein-Horioka Puzzle’ misses the forest for the trees. Likewise, the ‘PPP Puzzle’ and the ‘Exchange rate disconnect puzzle’ (and to some extent the ‘equity premium puzzle’ as well) are really side effects of a much deeper problem, which is that financial markets in general are ludicrously volatile and inefficient and we have no idea why.
And Wikipedia’s list doesn’t have some of the largest, most important problems in economics. Moffatt’s list does better, including good choices like “What Caused the Industrial Revolution?”, “What Is the Proper Size and Scope of Government?”, and “What Truly Caused the Great Depression?”, but it also includes some of the more esoteric problems like the ‘equity premium puzzle’ and the ‘endogeneity of money’. The way he states the problem “What Causes the Variation of Income Among Ethnic Groups?” suggests that he doesn’t quite understand what’s going on there either. More importantly, Moffatt still leaves out very obviously important questions like “How do we achieve economic development in poor countries?” (Or as I sometimes put it, “What did South Korea do from 1950 to 2000, and how can we do it again?”), “How do we fix shortages of housing and other necessities?”, “What is causing the global rise of income and wealth inequality?”, “How altruistic are human beings, to whom, and under what conditions?” and “What makes financial markets so unstable?” Ironically, ‘Unified models of human biases’, the one problem that Wikipedia got right, is missing from Moffatt’s list.
And I’m also humble enough to realize that some of the deepest problems in economics may be ones that we don’t even quite know how to formulate yet. We like to pretend that economics is a mature science, almost on the coattails of physics; but it’s really a very young science, more like psychology. We go through these ‘cargo cult science‘ rituals of p-values and econometric hypothesis tests, but there are deep, basic forces we don’t understand.We have precisely prepared all the apparatus for the detection of the phlogiston, and by God, we’ll get that 0.05 however we have to. (Think I’m being too harsh? “Real Business Cycle” theory essentially posits that the Great Depression was caused by everyone deciding that they weren’t going to work for a few years, and as whole countries fell into the abyss from failing financial markets, most economists still clung to the Efficient Market Hypothesis.) Our whole discipline requires major injections of intellectual humility: We not only don’t have all the answers; we’re not even sure we have all the questions.
I think the esoteric nature of questions like ‘the equity premium puzzle’ and the ‘tatonnement problem‘ is precisely the source of their appeal: It’s the sort of thing you can say you’re working on and sound very smart, because the person you’re talking to likely has no idea what you’re talking about. (Or else they are a fellow economist, and thus in on the con.) If you said that you’re trying to explain why poor countries are poor and why rich countries are rich—and if economics isn’t doing that, then what in the world are we doing?—you’d have to admit that we honestly have only the faintest idea, and that millions of people have suffered from bad advice economists gave their governments based on ideas that turned out to be wrong.
It’s really quite problematic how closely economists are tied to policymaking (except when we do really know what we’re talking about?). We’re trying to do engineering without even knowing physics. Maybe there’s no way around it: We have to make some sort of economic policy, and it makes more sense to do it based on half-proven ideas than on completely unfounded ideas. (Engineering without physics worked pretty well for the Romans, after all.) But it seems to me that we could be relying more, at least for the time being, on the experiences and intuitions of the people who have worked on the ground, rather than on sophisticated theoretical models that often turn out to be utterly false. We could eschew ‘shock therapy‘ approaches that try to make large interventions in an economy all at once, in favor of smaller, subtler adjustments whose consequences are more predictable. We could endeavor to focus on the cases where we do have relatively clear knowledge (like rent control) and avoid those where the uncertainty is greatest (like economic development).
At the very least, we could admit what we don’t know, and admit that there is probably a great deal we don’t know that we don’t know.
The states and cities that create the most jobs aren’t the ones that offer the most generous handouts to corporations. They are the ones that have the cleanest air, the best infrastructure, and above all the most educated population. This is why there have been months when the majority of US jobs were created in California. California is the largest state, but it’s not that large—it’s only about 12% of the US population. If as many as 70% of the new jobs are being created there, it’s because California is doing something right that most other states are doing very, very wrong.
And then there is the rent-seeking competition that megacorporations like Amazon engage in, getting cities to bid higher and higher subsidies, then locating where they probably would have anyway but with billions of dollars in free money. This is a trick we need to stop falling for: The federal government should outright ban any attempt to use subsidies to get an existing corporation to locate in a specific state or city. That’s not contributing to American society; it’s just moving things around.
There are a few kinds of industries it makes sense to subsidize, because they have high up-front costs and large public benefits. Examples include research and development and renewable energy. But here the goal is not to create jobs. It’s to create wealth, typically in the form of scientific knowledge. We aren’t trying to get them to hire people; we’re trying to get them to accomplish something that’s difficult and important.
Why don’t subsidies create jobs? It’s really quite simple: You need to pay for those subsidies.
The federal government doesn’t face a hard budget constraint like businesses do; they can print money. But state and municipal governments don’t have that power, and so their subsidies need to be made up in either taxes or debt—which means either taxes now, or taxes later. Or they could cut spending elsewhere, which means losing whatever benefits they were getting from that spending. This means that any jobs you created with the subsidies are just going to be destroyed somewhere else, by higher taxes or lower government spending.
People don’t seem to understand that a capitalist economy basically just creates as many jobs as it needs. In a financial crisis, that mechanism falters; that’s when the federal government should step in and print money to get it running again. But when the economy is running smoothly, trying to “create jobs” is just not a useful thing to do. Jobs will be created and destroyed by the market. Policy should be trying to increase welfare. Educate your population. Improve your healthcare system. Build more public transit. Invest in fighting poverty and homelessness. And if you don’t think you can afford those things, then you definitely can’t afford handouts to megacorporations that won’t even make back what you paid.
One thing that endlessly frustrates me (and probably most economists) about the public conversation on economics is the fact that people seem to think “destroying jobs” is bad. Indeed, not simply a downside to be weighed, but a knock-down argument: If something “destroys jobs”, that’s a sufficient reason to opposite it, whether it be a new technology, an environmental regulation, or a trade agreement. So then we tie ourselves up in knots trying to argue that the policy won’t really destroy jobs, or it will create more than it destroys—but it will destroy jobs, and we don’t actually know how many it will create.
Destroying jobs is good.Destroying jobs is the only way that economic growth ever happens.
I realize I’m probably fighting an uphill battle here, so let me start at the beginning: What do I mean when I say “destroying jobs”? What exactly is a “job”, anyway?
At its most basic level, a job is something that needs done. It’s a task that someone wants to perform, but is unwilling or unable to perform on their own, and is therefore willing to give up some of what they have in order to get someone else to do it for them.
Capitalism has blinded us to this basic reality. We have become so accustomed to getting the vast majority of our goods via jobs that we come to think of having a job as something intrinsically valuable. It is not. Working at a job is a downside. It is something to be minimized.
There is a kind of work that is valuable: Creative, fulfilling work that you do for the joy of it. This is what we are talking about when we refer to something as a “vocation” or even a “hobby”. Whether it’s building ships in bottles, molding things from polymer clay, or coding video games for your friends, there is a lot of work in the world that has intrinsic value. But these things aren’t jobs. No one will pay them to do these things—or need to; you’ll do them anyway.
The value we get from jobs is actually obtained from goods: Everything from houses to underwear to televisions to antibiotics. The reason you want to have a job is that you want the money from that job to give you access to markets for all the goods that are actually valuable to you.
Jobs are the input—the cost—of producing all of those goods. The more jobs it takes to make a good, the more expensive that good is. This is not a rule-of-thumb statement of what usually or typically occurs. This is the most fundamental definition of cost. The more people you have to pay to do something, the harder it was to do that thing. If you can do it with fewer people (or the same people working with less effort), you should. Money is the approximation; money is the rule-of-thumb. We use money as an accounting mechanism to keep track of how much effort was put into accomplishing something. But what really matters is the “sweat of our laborers, the genius of our scientists, the hopes of our children”.
Economic growth means that we produce more goods at less cost.
That is, we produce more goods with fewer jobs.
All new technologies destroy jobs—if they are worth anything at all. The entire purpose of a new technology is to let us do things faster, better, easier—to let us have more things with less work.
This has been true since at least the dawn of the Industrial Revolution.
The Luddites weren’t wrong that automated looms would destroy weaver jobs. They were wrong to think that this was a bad thing. Of course, they weren’t crazy. Their livelihoods were genuinely in jeopardy. And this brings me to what the conversation should be about when we instead waste time talking about “destroying jobs”.
Here’s a slogan for you: Kill the jobs. Save the workers.
We shouldn’t be disappointed to lose a job; we should think of that as an opportunity to give a worker a better life. For however many years, you’ve been toiling to do this thing; well, now it’s done. As a civilization, we have finally accomplished the task that you and so many others set out to do. We have not “replaced you with a machine”; we have built a machine that now frees you from your toil and allows you to do something better with your life. Your purpose in life wasn’t to be a weaver or a coal miner or a steelworker; it was to be a friend and a lover and a parent. You can now get more chance to do the things that reallymatter because you won’t have to spend all your time working some job.
When we replaced weavers with looms, plows with combine harvesters, computers-the-people with computers-the-machines (a transformation now so complete most people don’t even seem to know that the word used to refer to a person—the award-winning film Hidden Figures is about computers-the-people), tollbooth operators with automated transponders—all these things meant that the job was now done. For the first time in the history of human civilization, nobody had to do that job anymore. Think of how miserable life is for someone pushing a plow or sitting in a tollbooth for 10 hours a day; aren’t you glad we don’t have to do that anymore (in this country, anyway)?
But we shouldn’t simply throw away the people who were working on that noble task as if they were garbage. Their job is done—they did it well, and they should be rewarded. Yes, of course, the people responsible for performing the automation should be rewarded: The engineers, programmers, technicians. But also the people who were doing the task in the meantime, making sure that the work got done while those other people were spending all that time getting the machine to work: They should be rewarded too.
Losing your job to a machine should be the best thing that ever happened to you. You should still get to receive most of your income, andalso get the chance to find a new job or retire.
How can such a thing be economically feasible? That’s the whole point: The machines are more efficient. We have more stuff now. That’s what economic growth is. So there’s literally no reason we can’t give every single person in the world at least as much wealth as we did before—there is now more wealth.
There’s a subtler argument against this, which is that diverting some of the surplus of automation to the workers who get displaced would reduce the incentives to create automation. This is true, so far as it goes. But you know what else reduces the incentives to create automation? Political opposition. Luddism. Naive populism. Trade protectionism.
Moreover, these forces are clearly more powerful, because they attack the opportunity to innovate: Trade protection can make it illegal to share knowledge with other countries. Luddist policies can make it impossible to automate a factory.
Whereas, sharing the wealth would only reduce the incentive to create automation; it would still be possible, simply less lucrative. Instead of making $40 billion, you’d only make $10 billion—you poor thing. I sincerely doubt there is a single human being on Earth with a meaningful contribution to make to humanity who would make that contribution if they were paid $40 billion but not if they were only paid $10 billion.
This is something that could be required by regulation, or negotiated into labor contracts. If your job is eliminated by automation, for the next year you get laid off but still paid your full salary. Then, your salary is converted into shares in the company that are projected to provide at least 50% of your previous salary in dividends—forever. By that time, you should be able to find another job, and as long as it pays at least half of what your old job did, you will be better off. Or, you can retire, and live off that 50% plus whatever else you were getting as a pension.
From the perspective of the employer, this does make automation a bit less attractive: The up-front cost in the first year has been increased by everyone’s salary, and the long-term cost has been increased by all those dividends. Would this reduce the number of jobs that get automated, relative to some imaginary ideal? Sure. But we don’t live in that ideal world anyway; plenty of other obstacles to innovation were in the way, and by solving the political conflict, this will remove as many as it adds. We might actually end up with more automation this way; and even if we don’t, we will certainly end up with less political conflict as well as less wealth and income inequality.
The most important change we need to make is to abandon the assumption of dynamic optimization. This will be a very hard sell, as most macroeconomists have become convinced that the Lucas Critique means we need to always base everything on the dynamic optimization of a single representative agent. I don’t think this was actually what Lucas meant (though maybe we should ask him; he’s still at Chicago), and I certainly don’t think it is what he should have meant. He had a legitimate point about the way macroeconomics was operating at that time: It was ignoring the feedback loops that occur when we start trying to change policies.
Goodhart’s Lawis probably a better formulation: Once you make an indicator into a target, you make it less effective as an indicator. So while inflation does seem to be negatively correlated with unemployment, that doesn’t mean we should try to increase inflation to extreme levels in order to get rid of unemployment; sooner or later the economy is going to adapt and we’ll just have both inflation and unemployment at the same time. (Campbell’s Lawprovides a specific example that I wish more people in the US understood: Test scores would be a good measure of education if we didn’t use them to target educational resources.)
The reason we must get rid of dynamic optimization is quite simple: No one behaves that way.
It’s often computationally intractable even in our wildly oversimplified models that experts spend years working on—now you’re imagining that everyonedoes this constantly?
The most fundamental part of almost every DSGE model is the Euler equation; this equation comes directly from the dynamic optimization. It’s supposed to predict how people will choose to spend and save based upon their plans for an infinite sequence of future income and spending—and if this sounds utterly impossible, that’s because it is. Euler equations don’t fit the data at all, and even extreme attempts to save them by adding a proliferation of additional terms have failed. (It reminds me very much of the epicyclesthat astronomers used to add to the geocentric model of the universe to try to squeeze in weird results like Mars, before they had the heliocentric model.)
We should instead start over: How do people actually choose their spending? Well, first of all, it’s not completely rational. But it’s also not totally random. People spend on necessities before luxuries; they try to live within their means; they shop for bargains. There is a great deal of data from behavioral economics that could be brought to bear on understanding the actual heuristics people use in deciding how to spend and save. There have already been successful policy interventions using this knowledge, like Save More Tomorrow.
The best thing about this is that it should make our models simpler. We’re no longer asking each agent in the model to solve an impossible problem. However people actually make these decisions, we know it can be done, because it is being done. Most people don’t really think that hard, even when they probably should; so the heuristics really can’t be that complicated. My guess is that you can get a good fit—certainly better than an Euler equation—just by assuming that people set a target for how much they’re going to save (which is also probably pretty small for most people), and then spend the rest.
The second most important thing we need to add is inequality. Some people are much richer than others; this is a very important fact about economics that we need to understand. Yet it has taken the economics profession decades to figure this out, and even now I’m only aware of one class of macroeconomic models that seriously involves inequality, the Heterogeneous Agent New Keynesian (HANK) models which didn’t emerge until the last few years (the earliest publication I can find is 2016!). And these models are monsters; they are almost always computationally intractable and have a huge number of parameters to estimate.
Understanding inequality will require more parameters, that much is true. But if we abandon dynamic optimization, we won’t need as many as the HANK models have, and most of the new parameters are actually things we can observe, like the distribution of wages and years of schooling.
Observability of parameters is a big deal. Another problem with the way the Lucas Critique has been used is that we’ve been told we need to be using “deep structural parameters” like the temporal elasticity of substitution and the coefficient of relative risk aversion—but we have no idea what those actually are. We can’t observe them, and all of our attempts to measure them indirectly have yielded inconclusive or even inconsistent results. This is probably because these parameters are based on assumptions about human rationality that are simply not realistic. Most people probably don’t have a well-defined temporal elasticity of substitution, because their day-to-day decisions simply aren’t consistent enough over time for that to make sense. Sometimes they eat salad and exercise; sometimes they loaf on the couch and drink milkshakes. Likewise with risk aversion: many moons ago I wrote about how people will buy both insurance and lottery tickets, which no one with a consistent coefficient of relative risk aversion would ever do.
So if we are interested in deep structural parameters, we need to base those parameters on behavioral experiments so that we can understand actual human behavior. And frankly I don’t think we need deep structural parameters; I think this is a form of greedy reductionism, where we assume that the way to understand something is always to look at smaller pieces. Sometimes the whole is more than the sum of its parts. Economists obviously feel a lot of envy for physics; but they don’t seem to understand that aerodynamics would never have (ahem) gotten off the ground if we had first waited for an exact quantum mechanical solution of the oxygen atom (which we still don’t have, by the way). Macroeconomics may not actually need “microfoundations” in the strong sense that most economists intend; it needs to be consistent with small-scale behavior, but it doesn’t need to be derived from small-scale behavior.
This means that the new paradigm in macroeconomics does not need to be computationally intractable. Using heuristics instead of dynamic optimization and worrying less about microfoundations will make the models simpler; adding inequality need not make them so much more complicated.
Though central banks are a cornerstone of the modern financial system, I don’t think most people have a clear understanding of how they actually function. (I think this may be by design; there are many ways we could make central banking more transparent, but policymakers seem reluctant to show their hand.)
Central banks “print money” and “set interest rates”. But how exactly do they do these things, and what on Earth do they have to do with each other?
The first thing to understand is that most central banks don’t actually print money. In the US, cash is actually printed by the Department of the Treasury. But cash is only a small part of the money in circulation. The monetary base consists of cash in vaults and in circulation; the US monetary base is about $3.6 trillion. The money supplycan be measured a few different ways, but the standard way is to include checking accounts, traveler’s checks, savings accounts, money market accounts, short-term certified deposits, and basically anything that can be easily withdrawn and spent as money. This is called the M2 money supply, and in the US it is currently over $14.1 trillion. That means that only 25% of our money supply is in actual, physical cash—the rest is all digital. This is actually a relatively high proportion for actual cash, as the monetary base was greatly increased in response to the Great Recession. When we say that the Fed “prints money”, what we really mean is that they are increasing the money supply—but typically they do so in a way that involves little if any actual printing of cash.
The second thing to understand is that central banks don’t exactly set interest rates either. They target interest rates. What’s the difference, you ask?
Well, setting interest rates would mean that they made a law or something saying you have to charge exactly 2.7%, and you get fined or something if you don’t do that.
Targeting interest rates is a subtler art. The Federal Reserve decides what interest rates they want banks to charge, and then they engage in what are called open-market operationsto try to make that happen. Banks hold reserves—money that they are required to keep as collateral for their loans. Since we are in a fractional-reservesystem, they are allowed to keep only a certain proportion (usually about 10%). In open-market operations, the Fed buys and sells assets (usually US Treasury bonds) in order to either increase or decrease the amount of reserves available to banks, to try to get them to lend to each other at the targeted interest rates.
Why not simply set the interest rate by law? Because then it wouldn’t be the market-clearing interest rate. There would be shortages or gluts of assets.
It might be easier to grasp this if we step away from money for a moment and just think about the market for some other good, like televisions.
Suppose that the government wants to set the price of a television in the market to a particular value, say $500. (Why? Who knows. Let’s just run with it for a minute.)
If they simply declared by law that the price of a television must be $500, here’s what would happen: Either that would be too low, in which case there would be a shortage of televisions as demand exceeded supply; or that would be too high, in which case there would be a glut of televisions as supply exceeded demand. Only if they got spectacularly lucky and the market price already was $500 per television would they not have to worry about such things (and then, why bother?).
But suppose the government had the power to create and destroy televisions virtually at will with minimal cost.
Now, they have a better way; they can target the price of a television, and buy and sell televisions as needed to bring the market price to that target. If the price is too low, the government can buy and destroy a lot of televisions, to bring the price up. If the price is too high, the government can make and sell a lot of televisions, to bring the price down.
Now, let’s go back to money. This power to create and destroy at will is hard to believe for televisions, but absolutely true for money. The government can create and destroy almost any amount of money at will—they are limited only by the very inflation and deflation the central bank is trying to affect.
This allows central banks to intervene in the market without creating shortages or gluts; even though they are effectively controlling the interest rate, they are doing so in a way that avoids having a lot of banks wanting to take loans they can’t get or wanting to give loans they can’t find anyone to take.
The goal of all this manipulation is ultimately to reduce inflation and unemployment. Unfortunately it’s basically impossible to eliminate both simultaneously; the Phillips curvedescribes the relationship generally found that decreased inflation usually comes with increased unemployment and vice-versa. But the basic idea is that we set reasonable targets for each (usually about 2% inflation and 5% unemployment; frankly I’d prefer we swap the two, which was more or less what we did in the 1950s), and then if inflation is too high we raise interest rate targets, while if unemployment is too high we lower interest rate targets.
What if they’re both too high? Then we’re in trouble. This has happened; it is called stagflation. The money supply isn’t the other thing affecting inflation and unemployment, and sometimes we get hit with a bad shock that makes both of them high at once. In that situation, there isn’t much that monetary policy can do; we need to find other solutions.
But how does targeting interest rates lead to inflation? To be quite honest, we don’t actually know.
The basic idea is that lower interest rates should lead to more borrowing, which leads to more spending, which leads to more inflation. But beyond that, we don’t actually understand how interest rates translate into prices—this is the so-called transmission mechanism, which remains an unsolved problem in macroeconomics. Based on the empirical data, I lean toward the view that the mechanism is primarily via housing prices; lower interest rates lead to more mortgages, which raises the price of real estate, which raises the price of everything else. This also makes sense theoretically, as real estate consists of large, illiquid assets for which the long-term interest rate is very important. Your decision to buy an apple or even a television is probably not greatly affected by interest rates—but your decision to buy a house surely is.
If that is indeed the case, it’s worth thinking about whether this is really the right way to intervene on inflation and unemployment. High housing prices are an international crisis; maybe we need to be looking at ways to decrease unemployment without affecting housing prices. But that is a tale for another time.