Monopsony is all around us

Mar 15 JDN 2458924

Perhaps because of the board game (the popularity of which honestly baffles me; it’s really not a very good game!), the concept of monopoly is familiar to most people: A market with one seller and many buyers can command high prices and high profits for the seller.

But the opposite situation, a market with many sellers and one buyer, is equally problematic, yet far less well-known. This is called monopsony. Whereas in a monopoly prices are too high, in a monopsony prices are too low.

I have long suspected, but the data now confirms, that the most widespread form of monopsony occurs in labor markets. This is a particularly bad place for monopsony, because it means that instead of consumer prices being lower, wages will be lower. Monopsonistic labor markets are bad in two ways: They lower wages and they increase unemployment.


Monopsonistic labor markets are one of the reasons why raising minimum wage seems to have very little effect on employment.
In the presence of monopsony, forcing employers to increase wages won’t cause them to fire workers; it will just eat into their profits. In some cases it can actually cause them to hire more workers.

Take a look at this map, from the Roosevelt Institute:

widespread-labor-monopsony1

This map is color-coded by commuting zone, based on whether the average labor market (different labor markets weighted by their number of employees) is monopsonistic. Commuting zones with only a few major employers are colored red, while those with many employers are colored green. In between are shaded orange and yellow. (Not a very colorblind-friendly coding scheme, I’m afraid.)

Basically you can see that the only places where labor markets are not monopsonistic are in major metro areas. Suburban areas are typically yellow, and rural areas are almost all orange or red.


It seems then that we have two choices for where we want to live: We can
live in rural areas and have monopsonistic labor markets with low wages and competitive real estate markets with low housing prices, or we can live in urban areas and have competitive labor markets with high wages and monopolistic real estate markets with high housing prices. There’s hardly anywhere we can live where both wages and housing prices are fair.

Actually the best seems to be Detroit! Median housing price in the Detroit area is an affordable $179,000, while median household income is a low but not terrible $31,000. This means you can pay off a house spending 30% of your income in about 10 years. That’s the American Dream, right there.

Compare this to the San Francisco area, where median housing price is $1.1 million and median income is an impressive $104,000. This means it would take over 35 years to pay off your house spending 30% of your income. (And that’s not accounting for interest!) You can make six figures in San Francisco and still be considered “low income”, because housing prices there are so absurd.

Of course, student loans are denominated in nominal terms, so you might actually be able to pay off your student loans faster living in San Francisco than you could in Detroit. Say taxes are 20%, so these become after-tax incomes of $25,000 and $83,000. Even if you spend only a third of your income on housing in Detroit and spend two-thirds in San Francisco, that leaves you with $16,600 in Detroit but $27,600 in San Francisco. Of course other prices are different too, but it seems quite likely that being able to pay $5,000 per year on your student loans is easier living in San Francisco than it is in Detroit.

What can be done about monopsony in labor markets? First, we could try to split up employers—the FTC already doesn’t do enough to break up monopolies, but it basically does nothing to break up monopsonies. But that may not always be feasible, particularly in rural areas. And there are genuine economies of scale that can make larger firms more efficient in certain ways; we don’t want to lose those.

Perhaps the best solution is the one we used to use, and most of the First World continues to use: Labor unions. Union membership in the US declined by half in the last 30 years. Europe is heavily unionized, and the most unionized of all are Scandinavian countries—probably not a coincidence that these are the most prosperous places in the world.


At first glance, labor unions seem anti-competitive: They act like a monopoly. But when you currently have a
monopsony, adding a monopoly can actually be a good thing. Instead of one seller and many buyers, resulting in prices that are too low, you can have one seller and one buyer, resulting in prices that are negotiated and can, at least potentially, be much fairer. This market structure is called a bilateral monopoly, and while it’s not as good as perfect competition, it’s considerably more efficient than either monopsony or monopoly alone.

The real cost of high rent

Jan 26 JDN 2458875

The average daily commute time in the United States is about 26 minutes each way—for a total of 52 minutes every weekday. Public transit commute times are substantially longer in most states than driving commute times: In California, the average driving commute is 28 minutes each way, while the average public transit commute is 51 minutes each way. Adding this up over 5 workdays per week, working 50 weeks per year, means that on average Americans spend over 216 hours each year commuting.

Median annual income in the US is about $33,000. Assuming about 2000 hours of work per year for a full-time job, that’s a wage of $16.50 per hour. This makes the total cost of commute time in the United States over $3500 per worker per year. Multiplied by a labor force of 205 million, this makes the total cost of commute time over $730 billion per year. That’s not even counting the additional carbon emissions and road fatalities. This is all pure waste. The optimal commute time is zero minutes; the closer we can get to that, the better. Telecommuting might finally make this a reality, at least for a large swath of workers. Already over 40% of US workers telecommute at least some of the time.

Let me remind you that it would cost about $200 billion per year to end world hunger. We could end world hunger three times over with the effort we currently waste in commute time.

Where is this cost coming from? Why are commutes so long? The answer is obvious: The rent is too damn high. People have long commutes because they can’t afford to live closer to where they work.

Almost half of all renter households in the US pay more than 30% of their income in rent—and 25% pay more than half of their income. The average household rent in the US is over $1400 per month, almost $17,000 per year—more than the per-capita GDP of China.

Not that buying a home solves the problem: In many US cities the price-to-rent ratio of homes is over 20 to 1, and in Manhattan and San Francisco it’s as high as 50 to 1. If you already bought your home years ago, this is great for you; for the rest of us, not so much. Interestingly, high rents seem to correlate with higher price-to-rent ratios, so it seems like purchase prices are responding even more to whatever economic pressure is driving up rents.

Overall about a third of all US consumer spending is on housing; out of our total consumption spending of $13 trillion, this means we are spending over $4 trillion per year on housing, about the GDP of Germany. Of course, some of this is actually worth spending: Housing costs a lot to build, and provides many valuable benefits.

What should we be spending on housing, if the housing market were competitive and efficient?

I think Chicago’s housing market looks fairly healthy. Homes there go for about $250,000, with prices that are relatively stable; and the price-to-rent ratio is about 20 to 1. Chicago is a large city with a population density of about 6,000 people per square kilometer, so it’s not as if I’m using a tiny rural town as my comparison. If the entire population of the United States were concentrated at the same density as the city of Chicago, we’d all fit in only 55,000 square kilometers—less than the area of West Virginia.
Compare this to the median housing price in California ($550,000), New York ($330,000), or Washington, D.C. ($630,000). There are metro areas with housing prices far above even this: In San Jose the median home price is $1.1 million. I find it very hard to believe that it is literally four times as hard to build homes in San Jose as it is in Chicago. Something is distorting that price—maybe it’s over-regulation, maybe it’s monopoly power, maybe it’s speculation—I’m not sure what exactly, but there’s definitely something out of whack here.

This suggests that a more efficient housing market would probably cut prices in California by 50% and prices in New York by 25%. Since about 40% of all spending in California is on housing, this price change would effectively free up 20% of California’s GDP—and 20% of $3 trillion is $600 billion per year. The additional 8% of New York’s GDP gets us another $130 billion, and we’re already at that $730 billion I calculated for the total cost of commuting, only considering New York and California alone.

This means that the total amount of waste—including both time and money—due to housing being too expensive probably exceeds $1.5 trillion per year. This is an enormous sum of money: We’re spending an Australia here. We could just about pay for a single-payer healthcare system with this.

Why will no one listen to economists on rent control?

Sep 22 JDN 2458750

I am on the verge of planting my face into my desk, because California just implemented a statewide program of rent control. I understand the good intentions here; it is absolutely the case that housing in California is too expensive. There are castles in Spain cheaper than condos in California. But this is not the right solution. Indeed, it will almost certainly make the problem worse. Maybe housing prices won’t be too high; instead there simply won’t be enough homes and more people will live on the street. (It’s not a coincidence that the Bay Area has both some of the world’s tightest housing regulations and one of the highest rates of homelessness.)

There is some evidence that rent control can help keep tenants in their homes—but at the cost of reducing the overall housing supply. Most of the benefits of rent control actually fall upon the upper-middle-class, not the poor.

Price controls are in general a terrible way of intervening in the economy. Price controls are basically what destroyed Venezuela. In this case the ECON 101 argument is right: Put a cap on the price of something, and you will create a shortage of that thing. Always.

California makes this worse by including all sorts of additional regulations on housing construction. Some regulations are necessary—homes need to be safe to live in—but did we really need a “right to sunlight”? How important is “the feel of the city” compared to homelessness? Not every building needs its own parking! (That, at least, the state government seems to be beginning to understand.) And yes, we should be investing heavily in solar power, and rooftops are a decent place to put those solar panels; but you should be subsidizing solar panels, not mandating them and thereby adding the cost of solar panels to the price of every new building.

Of course, we can’t simply do nothing; we need to fix this housing crisis. But there are much better ways of doing so. Again the answer is to subsidize rather than regulate.

Here are some policy options for making housing more affordable:

  1. Give every person below a certain income threshold a one-time cash payment to help them pay for a down payment or first month’s rent. Gradually phase out the payment as their income increases in the same way as the Earned Income Tax Credit.
  2. Provide a subsidy for new housing construction, with larger subsidies for buildings with smaller, more affordable apartments.
  3. Directly pay for the construction of new public housing.
  4. Relax zoning regulations to make construction less expensive.
  5. Redistribute income from the rich to the poor using progressive taxes and transfer payments. Housing crises are always and everywhere a problem of inequality.

Some of these would cost money, yes; we would probably need to raise taxes to pay for them. But rent control has costs too. We are already paying these costs, but instead of paying them in the form of taxes that can be concentrated on the rich, we pay them in the form of a housing crisis that hurts the poor most of all.

The weirdest thing about all this is that any economist would agree.

Economists can be a contentious bunch: It has been said that if you ask five economists a question, you’ll get five answers—six if one is from Harvard. Yet the consensus among economists against rent control is absolutely overwhelming. Analyses of journal articles and polls of eminent economists suggest that over 90% of economists, regardless of their other views or their political leanings, agree that rent control is a bad idea.

This is a staggering result: There are economists who think that almost all taxes and regulations are fundamentally evil and should all be removed, and economists who think that we need radical, immediate government intervention to prevent a global climate catastrophe. But they all agree that rent control is a bad idea.

Economists differ in their views about legacy college admissions, corporate antitrust, wealth taxes, corporate social responsibility, equal pay for women, income taxes, ranked-choice voting, the distributional effects of monetary policy, the relation between health and economic growth, minimum wage, and healthcare spending. They disagree about whether Christmas is a good thing! But they all agree that rent control is a bad idea.

We’re not likely to ever get a consensus much better than this in any social science. The economic case against rent control is absolutely overwhelming. Why aren’t policymakers listening to us?

I really would like to know. It’s not that economists have ignored the problem of housing affordability. We have suggested a variety of other solutions that would obviously be better than rent control—in fact, I just did, earlier in this post. Many of them would require tax money, yes—do you want to fix this problem, or not?

Maybe that’s it: Maybe policymakers don’t really care about making housing affordable. If they did, they’d be willing to bear the cost of raising taxes on millionaires in order to build more apartments and keep people from being homeless. But they want to seem like they care about making housing affordable, because they know their constituents care. So they use a policy that seems to make housing more affordable, even though it doesn’t actually work, because that policy also doesn’t affect the government budget (at least not obviously or directly—of course it still does indirectly). They want the political support of the poor, who think this will help them; and they also want the political support of the rich, who refuse to pay a cent more in taxes.

But it really makes me wonder what we as economists are even really doing: If the evidence is this clear and the consensus is this overwhelming, and policymakers still ignore us—then why even bother?

The Amazon is burning.

Sep 1 JDN 2458729

As you probably already know, the Amazon rainforest is currently on fire. You can get more details about the fires from The Washington Post, or CNN, or New York magazine, or even The Economist; but I think the best coverage I’ve seen has been these two articles from Al-Jazeera.

I have good news and bad news. Let’s start with the bad news: If we lose the Amazon, we lose everything. The ecological importance of the Amazon is basically impossible to overstate. The Amazon produces 20% of the oxygen on Earth. 25% of the carbon absorbed on land is absorbed by the Amazon. We must protect the Amazon, at almost any cost: Given how vital preserving the rainforest will be to resisting climate change, millions of lives are at stake.

The good news is there is still a lot of Amazon left.

This graph shows the total cumulative deforestation of the Amazon, compared against its current area and its original area. The units are square kilometers; the Amazon rainforest has been reduced from 4.1 million square kilometers (1.6 million square miles) to 3.3 million hectares (1.3 million square miles), a decline of about 20% (21 log points). We still have four-fifths of the rainforest remaining—less than we should, but a lot more than we might.

Amazon_cumulative

This graph shows the annual deforestation of the Amazon, with results that are even more encouraging. While the last few years have had faster deforestation than previously, we are still nowhere near the peak deforestation rates of the early 2000s. At peak deforestation, the Amazon was projected to last no more than 150 years; but at current rates of deforestation, the Amazon would not be completely destroyed in more than 400 years.

Amazon_annual

Of course, any loss of the Amazon is bad. We should actually be trying to restore the Amazon—that extra 800,000 square kilometers of high-density forest would sequester a lot of carbon. We probably can’t actually add the 9 million square kilometers (3.4 million square miles) of forest it would take to stop climate change; but any reforestation we do manage will help.

And a number of ecologists have been sounding the alarm that the Amazon is approaching some sort of tipping point where it will stop being a rainforest and become a savannah. If this happens, it may be irreversible. It sounds crazy to me—80% of the forest is still there!—but that’s what ecologists are saying, and I’ll defer to their expertise.

On the other hand, ecologists have been panicking about “irreversible tipping points” on almost everything for the past century. We really can’t be blamed for not taking their word as gospel: They’ve cried wolf about “population bombs” and shortages of food and water for a very long time now. So far their projections on the rates of temperature rise, species extinction, and deforestation have been quite accurate; but their predictions of dire human consequences have always suspiciously failed to materialize. Humans are quite creative and resilient, as it turns out. This is part of why I’m not actually afraid climate change will cause the collapse of human civilization (much less the utterly laughable claim of human extinction); but tens of millions of deaths is still plenty of reason to take drastic action.

Indeed, I think panicking is precisely what we need to avoid. If we exaggerate the problem to the point where it sounds hopeless, that won’t encourage people to take action; it may actually cause them to throw in the towel.

What do we actually need to do here? We need to restore as many forests as possible, and we need to cut carbon emissions as rapidly as possible.

This doesn’t require a revolution to overthrow capitalism. It doesn’t require exotic new technologies (though fusion power and improved electricity storage would certainly help). It simply requires a real commitment to bear real economic costs today in order to prevent much higher costs in the future.

Bernie Sanders has a climate change plan that is estimated to cost $16 trillion over the next ten years. Make no mistake: This is an enormous amount of money. US GDP is about $20 trillion, growing at about 3% per year, so we’re looking at about 6% of GDP over that interval. This is about twice our current military budget, or about our military budget in the 1980s. Notably, it is nowhere near the levels of military spending we reached in the Second World War, which exceeded 40% of GDP. That’s what happens when America really commits to something.

Would this be enough? The UN seems to think so. They estimate that it would cost about 1% of global GDP to keep global warming below 2 C. Even if that’s an underestimate, 6% of the GDP of the US and EU would by itself account for twice that amount—and I have no doubt that if America committed to climate change mitigation, Europe would gladly follow.

And it’s not as if this money would be set on fire. (Military spending, on the other hand, almost literally is that.) We would spending this money mainly on infrastructure and technology; we would be paying wages and creating millions of jobs.

So far as I know Sanders’s plan doesn’t include paying Brazil to restore the Amazon, but it probably should. Part of why Brazil is currently burning the Amazon is the externalities: The ecological benefit of the Amazon affects us all, but the economic benefit of clear-cutting and cattle ranching directly benefits Brazil. We should set up some sort of payment mechanism to ensure that it is more profitable for Brazil to keep the rainforest where it is than to burn it down. How can we afford such a thing, you ask? No: How can we afford not to?

How much should we value statistical lives?

June 9 JDN 2458644

The very concept of putting a dollar value on a human life offends most people. I understand why: It suggests that human lives are fungible, and also seems to imply that killing people is just fine as long as it produces sufficient profit.

In next week’s post I’ll try to assuage some of those fears: Saying that a life is worth say $5 million doesn’t actually mean that it’s justifiable to kill someone as long as it pays you $5 million.

But for now let me say that we really have no choice but to do this. There are a huge number of interventions we could make in the world that all have the same basic form: They could save lives, but they cost money. We need to be able to say when we are justified in spending more money to save more lives, and when we are not.

No, it simply won’t do to say that “money is no object”. Because money isn’t just money—money is human happiness. A willingness to spend unlimited amounts to save even a single life, if it could be coherently implemented at all, would result in, if not complete chaos or deadlock, a joyless, empty world where we all live to be 100 by being contained in protective foam and fed by machines. It may be uncomfortable to ask a question like “How many people should we be willing to let die to let ourselves have Disneyland?”; but if that answer were zero, we should not have Disneyland. The same is true for almost everything in our lives: From automobiles to chocolate, almost any product you buy, any service you consume, has resulted in some person’s death at some point.

And there is an even more urgent reason, in fact: There are many things we are currently not doing that could save many lives for very little money. Targeted foreign aid or donations to top charities could save lives for as little as $1000 each. Foreign aid is so cost-effective that even if the only thing foreign aid had ever accomplished was curing smallpox, it would be twice as cost-effective as the UK National Health Service (which is one of the best healthcare systems in the world). Tighter environmental regulations save an additional life for about $200,000 in compliance cost, which is less than we would have spent in health care costs; the Clean Air Act added about $12 trillion to the US economy over the last 30 years.

Reduced military spending could literally pay us money to save people’s lives—based on the cost of the Afghanistan War, we are currently paying as much as $1 million per person to kill people that we really have very little reason to kill.

Most of the lives we could save are statistical lives: We can’t point to a particular individual who will or will not die because of the decision, but we can do the math and say approximately how many people will or will not die. We know that approximately 11,000 people will die each year if we loosen regulations on mercury pollution; we can’t say who they are, but they’re out there. Human beings have a lot of trouble thinking this way; it’s just not how our brains evolved to work. But when we’re talking about policy on a national or global scale, it’s quite simply the only way to do things. Anything else is talking nonsense.

Standard estimates of the value of a statistical life range from about $4 million to $9 million. These estimates are based on how much people are willing to pay for reductions in risk. So for instance if people would pay $100 to reduce their chances of dying by 0.01%, we divide the former by the latter to say that a life is worth about $1 million.

It’s a weird question: You clearly can’t just multiply like that. How much would you be willing to accept for a 100% chance of death? Presumably there isn’t really such an amount, because you would be dead. So your willingness-to-accept is undefined. And there’s no particular reason for it to be linear below that: Since marginal utility of wealth is decreasing, the amount you would demand for a 50% chance of death is a lot more than 50 times as much as what you would demand for a 1% chance of death.
Say for instance that utility of wealth is logarithmic. Say your currently lifetime wealth is $1 million, and your current utility is about 70 QALY. Then if we measure wealth in thousands of dollars, we have W = 1000 and U = 10 ln W.

How much would you be willing to accept for a 1% chance of death? Your utility when dead is presumably zero, so we are asking for an amount m such that 0.99 U(W+m) = U(W). 0.99 (10 ln (W+m)) = 10 ln (W) means (W+m)^0.99 = W, so m = W^(1/0.99) – W. We started with W = 1000, so m = 72. You would be willing to accept $72,000 for a 1% chance of death. So we would estimate the value of a statistical life at $7.2 million.

How much for a 0.0001% chance of death? W^(1/0.999999)-W = 0.0069. So you would demand $6.90 for such a risk, and we’d estimate your value of a statistical life at $6.9 million. Pretty close, though not the same.

But how much would you be willing to accept for a 50% chance of death? W^(1/0.5) – W = 999,000. That is, $999 million. So if we multiplied that out, we’d say that your value of a statistical life has now risen to a staggering (and ridiculous) $2 billion.

Mathematically, the estimates are more consistent if we use small probabilities—but all this assumes that people actually know their own utility of wealth and calculate it correctly, which is a very unreasonable assumption.

The much bigger problem with this method is that human beings are terrible at dealing with small probabilities. When asked how much they’d be willing to pay to reduce their chances of dying by 0.01%, most people probably have absolutely no idea and may literally just say a random number.

We need to rethink our entire approach for judging such numbers. Honestly we shouldn’t be trying to put a dollar value on a human life; we should be asking about the dollar cost of saving a human life. We should be asking what else we could do with that money. Indeed, for the time being, I think the best thing to do is actually to compare lives to lives: How many lives could we save for this amount of money?

Thus, if we’re considering starting a war that will cost $1 trillion, we need to ask ourselves: How many innocent people would die if we don’t do that? How many will die if we do? And what else could we do with a trillion dollars? If the war is against Nazi Germany, okay, sure; we’re talking about killing millions to save tens of millions. But if it’s against ISIS, or Iran, those numbers don’t come out so great.

If we have a choice between two policies, each of which will cost $10 billion, and one of them will save 1,000 lives while the other will save 100,000, the obvious answer is to pick the second one. Yet this is exactly the world we live in, and we’re not doing that. We are throwing money at military spending and tax cuts (things that many not save any lives at all) and denying it from climate change adaptation, foreign aid, and poverty relief.

Instead of asking whether a given intervention is cost-effective based upon some notion of a dollar value of a human life, we should be asking what the current cost of saving a human life is, and we should devote all available resources into whatever means saves the most lives for the least money. Most likely that means some sort of foreign aid, public health intervention, or poverty relief in Third World countries. It clearly does not mean cutting taxes on billionaires or starting another war in the Middle East.

MSRP is tacit collusion

Oct 7 JDN 2458399

It’s been a little while since I’ve done a really straightforward economic post. It feels good to get back to that.

You are no doubt familiar with the “Manufacturer’s Suggested Retail Price” or MSRP. It can be found on everything from books to dishwashers to video games.

The MSRP is a very simple concept: The manufacturer suggests that all retailers sell it (at least the initial run) at precisely this price.

Why would they want to do that? There is basically only one possible reason: They are trying to sustain tacit collusion.

The game theory of this is rather subtle: It requires that both manufacturers and retailers engage in long-term relationships with one another, and can pick and choose who to work with based on the history of past behavior. Both of these conditions hold in most real-world situations—indeed, the fact that they don’t hold very well in the agriculture industry is probably why we don’t see MSRP on produce.

If pricing were decided by random matching with no long-term relationships or past history, MSRP would be useless. Each firm would have little choice but to set their own optimal price, probably just slightly over their own marginal cost. Even if the manufacturer suggested an MSRP, retailers would promptly and thoroughly ignore it.

This is because the one-shot Bertrand pricing game has a unique Nash equilibrium, at pricing just above marginal cost. The basic argument is as follows: If I price cheaper than you, I can claim the whole market. As long as it’s profitable for me to do that, I will. The only time it’s not profitable for me to undercut you in this way is if we are both charging just slightly above marginal cost—so that is what we shall do, in Nash equilibrium. Human beings don’t always play according to the Nash equilibrium, but for-profit corporations do so quite consistently. Humans have limited attention and moral values; corporations have accounting departments and a fanatical devotion to the One True Profit.

But the iterated Bertrand pricing game is quite different. If instead of making only one pricing decision, we make many pricing decisions over time, always with a high probability of encountering the same buyers and sellers again in the future, then I may not want to undercut your price, for fear of triggering a price war that will hurt both of our firms.

Much like how the Iterated Prisoner’s Dilemma can sustain cooperation in Nash equilibrium while the one-shot Prisoner’s Dilemma cannot, the iterated Bertrand game can sustain collusion as a Nash equilibrium.

There is in fact a vast number of possible equilibria in the iterated Bertrand game. If prices were infinitely divisible, there would be an infinite number of equilibria. In reality, there are hundreds or thousands of equilibria, depending on how finely divisible the price may be.

This makes the iterated Bertrand game a coordination gamethere are many possible equilibria, and our task is to figure out which one to coordinate on.

If we had perfect information, we could deduce what the monopoly price would be, and then all choose the monopoly price; this would be what we call “payoff dominant”, and it’s often what people actually try to choose in real-world coordination games.

But in reality, the monopoly price is a subtle and complicated thing, and might not even be the same between different retailers. So if we each try to compute a monopoly price, we may end up with different results, and then we could trigger a price war and end up driving all of our profits down. If only there were some way to communicate with one another, and say what price we all want to set?

Ah, but there is: The MSRP. Most other forms of price communication are illegal: We certainly couldn’t send each other emails and say “Let’s all charge $59.99, okay?” (When banks tried to do that with the LIBOR, it was the largest white-collar crime in history.) But for some reason economists (particularly, I note, the supposed “free market” believers of the University of Chicago) have convinced antitrust courts that MSRP is somehow different. Yet it’s obviously hardly different at all: You’ve just made the communication one-way from manufacturers to retailers, which makes it a little less reliable, but otherwise exactly the same thing.

There are all sorts of subtler arguments about how MSRP is justifiable, but as far as I can tell they all fall flat. If you’re worried about retailers not promoting your product enough, enter into a contract requiring them to promote. Proposing a suggested price is clearly nothing but an attempt to coordinate tacit—frankly not even that tacit—collusion.

MSRP also probably serves another, equally suspect, function, which is to manipulate consumers using the anchoring heuristic: If the MSRP is $59.99, then when it does go on sale for $49.99 you feel like you are getting a good deal; whereas, if it had just been priced at $49.99 to begin with, you might still have felt that it was too expensive. I see no reason why this sort of crass manipulation of consumers should be protected under the law either, especially when it would be so easy to avoid.

There are all sorts of ways for firms to tacitly collude with one another, and we may not be able to regulate them all. But the MSRP is literally printed on the box. It’s so utterly blatant that we could very easily make it illegal with hardly any effort at all. The fact that we allow such overt price communication makes a mockery of our antitrust law.

How we can actually solve the housing shortage

Sep 16 JDN 2458378

In previous posts I’ve talked about the housing crisis facing most of the world’s major cities. (Even many cities in Africa are now facing a housing crisis!) In this post, I’m going to look at the empirical data to see if we can find a way to solve this crisis.

Most of the answer, it turns out, is really not that complicated: Build more housing.

There is a little bit more to it than that, but only a little bit. The basic problem is simply that there are more households than there are houses to hold them.

One of the biggest hurdles to fixing the housing crisis comes ironically from the left, in resistance to so-called “gentrification”. Local resistance to new construction is one of the greatest obstacles to keeping housing affordable. State and federal regulations are generally quite sensible: No industrial waste near the playgrounds. It’s the local regulations that make new housing so difficult.

I can understand why people fight “gentrification”: They see new housing going in as housing prices increase, and naturally assume that new houses cause higher prices. But it’s really the other way around: High prices cause new construction, which brings prices down. By its nature, new housing is almost always more expensive than existing housing. Building new housing still brings down the overall price of housing, even when the new housing is expensive. Building luxury condos does make existing apartments more affordable—and not building anything most certainly does not.

California’s housing crisis is particularly severe: California has been building less than half the units needed to sustain its current population trend since the crash in 2008. It’s worst of all in the Bay Area, where 500,000 jobs were added since 2009—and only 50,000 homes. California also has a big problem with delays in the permit process: Typically it takes as long as three or four years between approval and actual breaking ground.

We are seeing this in Oakland currently: The government has approved an actually reasonable amount of housing for once (vastly more than what they usually do), and as a result they may have a chance at keeping Oakland affordable even as it grows its population and economy. And yet we still get serious journalists saying utter nonsense like The building boom and resulting gentrification are squeezing the city’s most vulnerable.” Building booms don’t cause gentrification. Building booms are the best response to gentrification. When you say things like that, you sound to an economist like you’re saying “Pizza is so expensive; we need to stop people from making pizza!”

Homeowners who want to increase their property values may actually be rational—if incredibly selfish and monopolistic—in trying to block new construction. But activists who oppose “gentrification” need to stop shooting themselves in the foot by fighting the very same development that would have made housing cheaper.

The simplest thing we can do is make it easier to build housing. Streamline the permit process, provide subsidies, remove unnecessary regulations. Housing is one of the few markets where I can actually see a lot of unnecessary regulations. We don’t need to require parking; we should provide better public transit instead. And while requiring solar panels (as the whole state is now doing) sounds nice, it makes everything a lot more expensive—and by only requiring it on new housing, you are effectively saying you don’t want any new housing. I love solar panels, but what you should be doing is subsidizing solar panels, not requiring them. Does that cost the state budget more? Yes. Raise taxes on something else (a particularly good idea: electricity consumption) if you have to. But by mandating solar panels without any subsidies to support them, you are effectively putting a tax on new housing—which is exactly what California does not need.

It’s still a good idea to create incentives to build not simply housing, but affordable housing. There are ways to do this as well. Denver did an excellent job in creating an Affordable Housing Fund that they immediately spent in converting vacant apartments into affordable housing units.

There are also good reasons to try to fight foreign ownership of housing (and really, speculative ownership of housing in general). There is a strong correlation between current account deficits and housing appreciation, which makes sense if foreign investors are buying up our housing and making it more expensive. If Trump could actually reduce our trade deficit, that would drive down our current account deficit and quite likely make our housing more affordable. Of course, he has absolutely no idea how to do that.

Victor Duggan has a pretty good plan for lowering housing prices in Ireland which includes a land tax (as I’ve discussed previously) and a tax on foreign ownership of real estate. I disagree with him about the “Help-to-Buy” program, however; I actually think that was a fine idea, since the goal is not simply to keep housing cheap but to get people into houses. That wealth transfer is going to raise prices at the producer side—increasing production—but not at the consumer side—because people get compensated by the tax rebate. The net result should be more housing without more cost for buyers. You could have done the same thing by subsidizing construction, but I actually like the idea of putting the money directly in the pockets of homeowners. The tax incidence shouldn’t be much different in the long run, but it makes for a much more appealing and popular program.