How Political Prediction Markets Cut Through Partisan Spin

One of the most interesting developments in political analysis over the past decade has been the rise of online political prediction markets. What are prediction markets? The idea is pretty simple.

Participants will put money on their prediction of how an event (for example an election) will turn out. Sports prediction markets where you can bet on the winners of games or point spreads have been popular throughout history. Now these markets have made their way into our political environment.

If you predict the outcome correctly, you get paid out some amount based on when you made your prediction and what other participants predicted. The market provides a win-win for predictors and onlookers. Predictors who have developed more accurate prediction techniques or knowledge stand to gain money by beating their competitors. Furthermore, onlookers will have access to the information of those willing to put their money on the line.

For example, if someone were to develop a new statistical model which more accurately predicts voter turnout, and he is confident in his model, he will be willing to put a lot of money on the line. When he does this, the odds in the prediction market shift, so onlookers can see the impact of this new statistical model without knowing anything about it.

You don’t have to look far to find websites that either offer political betting or keep track of the odds. But while the money-making and information-sharing features of prediction markets are kind of neat, what really makes these markets fascinating is how they can be used as a tool for political analysis.

Put simply, political prediction markets are a powerful way to gauge who is winning the election. They are imperfect tools—but no tool is perfect. Let’s talk about why they are likely the best among second-best options. I’ve compiled some data from ElectionBettingOdds.com from this year’s cycle which I’ll discuss throughout the piece. Here it is:

Image Credit: Custom image by FEE

1) Talk Is Cheap

The major reason I trust prediction markets over polls is simple—talk is cheap. Imagine you go to a grocery store and there is only one bag of apples available, but you and four other customers want it. Imagine the owner of the store says he’ll give the bag to the person who wants it most. He tells you to rank your desire on a scale from one to ten.

What do you say? Likely, you, and everyone else, would rate your desire a ten. Why? Talk is cheap! Saying ten is no harder than saying nine, and saying ten makes you more likely to get the apples.

Now imagine the store owner has you bid for the apples. In this case, it’s clear the person willing to pay the most will come out on top.

Money eliminates cheap talk. You may say you urgently want apples, but if you’re only willing to pay $5 for a bag, it must not be that urgent.

The same thing operates in politics. After a bad debate performance, people affiliated with the losing candidate will often try to spin the performance as “not that bad.” However, when people put money on the line, they don’t worry about optics for their candidate. They just want to win the bet, so they report accurately about how they think the debate performance will affect things.

For example, Harris’s longest sustained margin over Trump in the prediction market began after she debated with him. On September 9, the day before the debate, Trump was up 50.5% to 46.8%. The next week he fell to 47.1%, and Harris rose to 51.6%.

On the flip side, the VP debate seemed to pull Trump back into the race—Harris’s margin fell from 4 points to 1. Partisans on both sides were no doubt spinning these debates in their favor. But wouldn’t it make far more sense to trust the combined judgment of people who are putting their hard-earned money on the line?

2) Lagging Polls

Another reason to favor prediction markets is that they move in real time, whereas polls lag. When poll results are released, they are potentially already outdated in volatile election seasons like this one. Poll aggregators make this even worse, aggregating poll results that are several weeks old.

3) Using All the Information Available

It’s also important to remember that prediction markets include and discount poll results appropriately. Bettors also look at polls, so all that information is included in the prediction market results. Not only that, but bettors have an incentive to discover reasons for poll failure and discount partisan polls insofar as they are unreliable.

4) Insider Information

A final reason to trust prediction markets over polls is that prediction markets have the advantage of giving people access to insider information. Insider trading is illegal, but that doesn’t mean that insiders abide by the rules or that secondhand rumors don’t make an impact.

While it would be hard to know for sure that insider information makes its way into prediction markets, we may have an example from this very election cycle.

Joe Biden dropped out of the election on July 21, but if you look at the above graph, you’ll notice markets had Harris overtake Biden the week of July 8. Just the week before, Harris only had a 4.3% chance. What happened?

Some might say that it was Biden’s abysmal presidential debate on June 27, but this doesn’t quite explain it. Even on July 1, three days after the debate, Harris was still below Biden. It wasn’t until July 3 that Harris catapulted over Biden. Why then?

Well, one possible answer is that prediction markets just took a few days to decide the debate was bad enough to oust Biden. We can’t rule out this possibility, but the change is very sharp for there to be no inciting incident. On July 2, Harris was at 5.2%. The next day, she was up over 20%.

Here’s my guess as to what happened. Some of the big names of the Democratic Party got together on the 2nd or 3rd and made the decision to transition to Kamala. This decision was made before Joe was on board himself, and bettors took advantage of the political rumors.

We can’t say for sure whether insider information was the cause, but we can say that bettors decided Joe was out before he did. In other words, the prediction market accurately predicted a major event before it happened.

We’ll see if that level of accuracy holds for the election itself.

Article by: Peter Jacobsen

Peter Jacobsen teaches economics and holds the position of Gwartney Professor of Economics. He received his graduate education George Mason University. His research interest is at the intersection of political economy, development economics, and population economics.

This article was originally published on FEE.org. Read the original article.

High Interest Rates Are an Opportunity for Education

For most of my adolescence, interest rates were near zero. In fact, even certificates of deposit (CDs), which boast higher interest rates than typical savings accounts, were generating returns below 1%. This was an anomaly. For most of recent history (especially the end of the 20th century), interest rates were much higher.

Investors in the 1960s could reasonably expect at least 5% annual returns from their banks. From the mid-’70s to the mid-’80s, many savers were getting a 10% return. But for those of us who came along after that, such rewards for saving have been impossible.

This was no market accident. When the real estate market collapsed in 2008–09, the US Federal Reserve (the institution responsible for determining US monetary policy) made a series of policy decisions intended to lower the interest rate. Although the Federal Reserve does not directly determine the interest rates, it has a variety of tools to push interest rates up or down.

The leadership of the Federal Reserve saw low interest rates as desirable because lower interest rates mean that it is less costly to borrow money. If businesses want to begin long building projects, for example, lower interest rates would make the projects more financially feasible—all else held constant.

Whether using monetary policy to drive down interest rates is a good idea is its own question. The fact of the matter remains: the Federal Reserve kept interest rates down near zero for a decade. Now that they’ve risen, there is a good opportunity to teach the next generation an important lesson about saving.

One of the major downsides of the decision to keep interest rates near zero is that a generation of Americans never got a chance to learn about the value of savings.

Saving is an integral part of human development. In order to take on big projects, someone must be saving. For example, when you start a business, it often can take months or years before your business makes a profit. How can you pay for workers or materials if you aren’t making a profit? Well, you have to draw from your own savings or someone else’s (the latter would be a loan).

This same logic underlies the decision to go to college. College costs money, and the benefits come later. How can you pay for something that doesn’t deliver a return until much later? Again, you have to leverage savings. Students either have a college fund or they borrow (from the savings of others).

Saving is necessary for the development of a modern economy.

When interest rates are normal, the value of savings is easy to teach because it literally pays to save. If you put $1,000 in a savings account when interest rates are 4% (annual), you end up earning $40 over a year.

This might not sound like a lot, but it can be a great teaching tool for kids for two reasons. First, it’s hard to earn any money as a kid, so any opportunity to earn feels like a big opportunity. Second, the miracle of compound interest can start to produce some truly tangible rewards.

Interest builds on itself, so a $40 gain this year doesn’t mean a $40 gain next year. The interest you earn each year also accumulates interest. This can be hard to visualize without a spreadsheet. To overcome this, the Rule of 72 can help you understand how important interest compounding is.

I’ve discussed this rule writing for FEE before in the context of inflation. The main idea is straightforward. If you divide the number 72 by the annual interest rate, that tells you how many years it will take for your money to double.

For example, let’s say you have $1,000 in your bank account, and the annual interest rate is 6%. Divide 72 by 6, the answer is 12. In 12 years, your balance will grow from $1,000 to $2,000.

Now we can see the importance of our changed interest rates. If savings account interest rates are 0.1% (as they were most of my adolescence), it would take 720 years for your bank account balance to double. Today with interest rates closer to 4%, it would still take about 18 years for an account balance to double. This number, 18, will have clear significance for any parent. This is the perfect amount of time to show your kids the benefit of savings.

Article by: Peter Jacobsen

Peter Jacobsen teaches economics and holds the position of Gwartney Professor of Economics. He received his graduate education George Mason University. His research interest is at the intersection of political economy, development economics, and population economics.

This article was originally published on FEE.org. Read the original article.

New Study Shows Why ‘Taxing the Rich’ Isn’t So Straightforward

 A common rallying cry on the left is that we can fund our social programs if we just “tax the rich.” While popular, this slogan is far from a real solution for the country. As has been pointed out elsewhere, if you confiscated all the wealth of every billionaire in the US, you wouldn’t even have enough money to run the government for a year. Our fiscal problem is a spending issue, not a revenue issue.

However, this isn’t the only problem with the proposal. It turns out that “tax the rich” is easier said than done.

A new working paper put out by the National Bureau of Economic Research (NBER) examines the impact of a tax system targeted at the rich. Researchers Nicolas Ajzenman, Guillermo Cruces, Ricardo Perez-Truglia, Darío Tortarolo, and Gonzalo Vazquez-Bare examine a new progressive property tax in Tres de Febrero (a city in Argentina), a system that effectively increased taxes on the rich while decreasing taxes on the poor.

How does this study show an issue with tax-the-rich sloganeering? To understand, we’ll have to consider the work of economist Art Laffer.

The Real Political Economy of Taxes

It’s simple to say, “I want to increase taxes on the rich.” Art Laffer’s work highlights how that desire may be easy to hold but hard to implement.

Laffer was famous for plotting a curve (famously called the Laffer curve) that showed the relationship between tax rates and tax revenues. Laffer’s insight was simple: as tax rates increase, tax revenues increase—at first. However, once tax rates go high enough, people are increasingly incentivized to avoid paying them, with the result being that tax revenues might actually start going down as rates go up. In other words, a tax rate of, say, 40 percent, might bring in more money to the government than a rate of 60 percent.

The Laffer Curve | Image Credit: Bastianowa via Wikimedia | CC BY SA 2.5

Avoiding taxes comes in many forms. One way is simply to earn less income. If you get taxed at an extremely high rate, such as losing 80 cents of every dollar you earn, you’re unlikely to work as much as if you only lose 20 cents for every dollar. If tax rates are pushed high enough, tax revenues will fall because people will engage in less income-generating activity.

Economic laws are simple. If you tax something, you get less of it. If you tax work, people will work less.

Another way to avoid taxes is to minimize your taxable income. This can happen legitimately or illegitimately. A legitimate way to lower your taxable income is to take advantage of accounting maneuvers like deductions. An illegitimate way to lower your taxable income is by not reporting income to the government. We can think of this as “non-compliance” with tax laws.

As tax rates increase, people will invest more resources into avoiding their taxes both legally and via non-compliance. Thus, when tax rates go high enough, this leads to lower tax revenue. This is the fundamental insight of the Laffer curve.

Non-compliance and Fairness

With this in mind, we can understand the results of the study of the Argentinian city. The authors report, “We find that reducing taxes for poorer households increases their compliance while increasing taxes for richer households decreases their compliance.” The logic behind the Laffer curve holds up. Higher taxes means lower compliance.

Specifically, they find that “a 1% reduction in the tax rate for the poor increases their compliance by 0.17% … Conversely, a 1% increase in the tax rate for the rich reduces their compliance by 0.36%.”

Interestingly, in the conclusion of the paper, the authors refer to this as an asymmetric response between the rich and the poor:

Our analysis reveals asymmetric responses to tax rate changes across income groups: tax reductions for lower-income households significantly increase their compliance rates, while tax increases for high-income households lead to decreased compliance.

However, there is nothing asymmetric about this from the perspective of economic theory. Both the rich and the poor households’ behaviors are perfectly consistent with the economic logic that underlies the Laffer curve. As you increase the tax burden on people, they have a larger incentive to avoid taxes. As you decrease tax burdens, the risk of non-compliance becomes larger relative to the benefits.

The authors go beyond examining compliance alone. Another part of the working paper is what people do when they are informed about the effect of the tax change.

As you’d expect, not all taxpayers in the study are politically informed enough to know that there has been a change. So the researchers examine the effect of informing voters that the new tax system is progressive. The results are interesting.

First, both rich and poor households claim to recognize the change as one that improves the fairness of the tax system. Furthermore, being informed of this change in and of itself appears to improve the tax compliance rates of poor households. However, the same is not true of rich households.

According to the paper, the authors found no significant increase or decrease in rich-household tax compliance upon receiving information about the progressive nature of the new tax system.

Taxing the Rich Is Harder than It Looks

The study’s findings are interesting for a few reasons. First, they highlight that talk is cheap when it comes to taxes, and this highlights one major issue with progressive tax policies. Many supporters of taxing the rich in theory will increase their non-compliance when the bill comes due. In fact, it may be the very richest of the group who are most able to do so.

This last point highlights a major issue with the plan to bring prosperity to the masses by taxing the most well-off. Ultimately, the government can decide the rate at which they want to tax rich households, but they can’t determine the revenue they collect from them.

Presented with these facts, it’s likely that the tax-the-rich crowd will just argue that we need to crack down on the rich to ensure compliance. But this is no silver bullet. Cracking down is expensive, so any attempt to increase revenues by increasing compliance is going to be offset (at least to some degree) by the associated expenses.

Furthermore, even if you eliminate some forms of non-compliance, others will arise. When you impose costs on people, there is a profit opportunity for those who find a way around the costs.

Finally, even if you could close off all avenues at low cost, the last method of tax avoidance is unstoppable. People can always stop working—and rigorous enforcement will push more people to take that option. As such, there will always be a tax rate beyond which you lose tax revenue. The Laffer curve lives.

Article by: Peter Jacobsen

Peter Jacobsen teaches economics and holds the position of Gwartney Professor of Economics. He received his graduate education George Mason University. His research interest is at the intersection of political economy, development economics, and population economics.

This article was originally published on FEE.org. Read the original article.

How Hobbies Can Save Us from Over-Specialization

 As we roll through the middle of February, we’re getting to the point of the year where most people start to abandon their New Year’s resolutions. According to research by Dr. Michelle Rozen, 94% of people fail their resolutions within two months. However, this doesn’t mean resolutions are a bad thing.

New Year’s resolutions make good economic sense. People want to improve, but monitoring whether you’ve actually improved in something is costly. As such, using the beginning (and end) of a year as a benchmark provides a low-cost way of ensuring self-monitoring. Maybe many fail, but New Year’s provides a good place to start either way.

For many, New Year’s resolutions involve reading more or losing weight. However, I’m noticing an increasing number of people centering their resolutions around hobbies.

New Year’s resolutions and hobbies often go hand in hand. Among my friend group, people are pursuing resolutions of improving woodworking skills, learning how to work with glass, and honing jiu-jitsu skills. Recent Pew Research data suggests that, of the people who make resolutions, 55% make resolutions about hobbies.

I see hobby-culture as an important part of our increasingly specialized society. While specialization has obvious upsides, we can also find clear downsides to the tendency. Hobbies act as a perfect hedge against the downsides of specialization.

The Benefits of Specialization and Why It Matters

Specialization as an idea comes at the very beginning of economics as a science. In Adam Smith’s book An Inquiry into the Nature and Causes of the Wealth of Nations, he introduces the idea of a factory that manufactures pins. He argues that if each person learns to make a small part (1/10th) of a pin, they will be much more productive:

Each person, therefore, making a tenth part of forty-eight thousand pins, might be considered as making four thousand eight hundred pins in a day. But if they had all wrought separately and independently, and without any of them having been educated to this peculiar business, they certainly could not each of them have made twenty, perhaps not one pin in a day.

Economists have recognized two reasons why specialization improves productivity. Armen Alchian and William Allen present these two arguments in their textbook Universal Economics. The first reason specialization improves productivity is that some producers naturally have a lower production cost. As such, specialization allows individuals to produce that which is the lowest cost for them.

For example, a farmer in the US does not have an adequate climate to produce coffee for as low of a cost as a farmer in Honduras. Likewise, the Honduran farmers would have to sacrifice acres perfect for coffee growth in order to grow corn. To remedy these issues, the US farmer can specialize in corn while the Honduran farmer can specialize in coffee, and then the two can trade.

The second source of the gains from specialization comes from learning by doing. People improve at just about any action via repetition. The same is true of production. If a tailor is responsible for producing all kinds of clothes, he will have relatively limited time to learn how to produce suit jackets well. If, instead, he only produces suit jackets, it seems reasonable to think this specialization will improve his skills.

These benefits of specialization have made it commonplace in the modern world. Whereas historically everyone needed to know how to grow crops, mend clothes, chop down trees, and hunt for food, nowadays most people outsource these roles to experts who specialize in them. It’s unlikely that our society could have risen to its current heights of wealth without specialization.

Hobbies: The Antidote to Over-Specialization

Libertarian author Robert Heinlein provides a different perspective on specialization in his book Time Enough for Love:

A human being should be able to change a diaper, plan an invasion, butcher a hog, conn a ship, design a building, write a sonnet, balance accounts, build a wall, set a bone, comfort the dying, take orders, give orders, cooperate, act alone, solve equations, analyze a new problem, pitch manure, program a computer, cook a tasty meal, fight efficiently, die gallantly. Specialization is for insects.

What are we to make of Heinlein’s quote here—does this undermine the importance of specialization in society? I don’t think so.

Nowhere does this quote imply that specialized jobs are without benefits. Rather, Heinlein appears to be arguing that people should be well-rounded regardless of their careers. Heinlein is saying that every man should be a Renaissance Man.

So how can someone whose job it is to program computers learn how to design a building, write a sonnet, or build a wall? Put simply, many of the activities Heinlein lists above are hobbies. Admittedly, some of the things on the above list extend beyond the realm of hobbies (I don’t know any amateur bone-setters), but many people learn these things today through their own interests.

One of the benefits of hobbies, then, is that they insure us against the biggest downside of specialization: fragility. If everyone only knows how to do the work associated with his or her own station, what happens if someone doesn’t show up to his station? The whole production process gets stalled.

Imagine, for example, if delivery trucks stopped coming to your local grocery store. How would you get food? Likely, many people don’t have a good answer to this question. Those who have taken up hunting or forestry as a hobby likely do have a good answer because they’ve achieved diversification through hobbies.

This is an extreme example, to be sure, but it is representative of the downside of specialization and the attendant upside of hobbies.

We can imagine a milder example (one that is personally relatable). Let’s say a winter storm strikes and all your local auto repair shops are backed up. The snow causes something on the bottom of your car to become dislodged, and it occasionally scrapes on the pavement.

Maybe, once upon a time in history, car owners would know the necessary information to diagnose the problem themselves. However, in the era of specialization, you are used to taking your car to a specialist. What’s the remedy here? Well, you could wait several weeks for an auto repair shop, or you could call on a friend who is a car hobbyist.

Your friend might not be a professional, but his experience might be enough to make up for your ignorance. At least that’s how it worked out for me, and this example shows exactly how hobbies build resilience.

So if you’re not sure what to do for a resolution this year, get yourself a hobby. Heinlein’s list provides a pretty good idea of where to start.

Article by: Peter Jacobsen

Peter Jacobsen teaches economics and holds the position of Gwartney Professor of Economics. He received his graduate education George Mason University. His research interest is at the intersection of political economy, development economics, and population economics.

This article was originally published on FEE.org. Read the original article.

Game Over for Ownership?

A movement is growing in Europe about consumer protection in the video games industry. A citizen’s petition in the EU recently reached 1 million signatures, meaning that EU regulators will consider the issue. That petition has a simple message: stop killing games.

The issue at hand is that game studios have been selling games as “licenses” and then revoking those licenses without warning. While online multiplayer games have always had a problem with server shutdowns due to maintenance costs, developers are now tying even single-player games to online functionality.

For example, Ubisoft shut down the servers for The Crew (which at one point logged 12 million players), leaving all forms of the game (including the solo campaign mode) unplayable. This problem reflects a larger trend of games shifting from physical discs owned by consumers to online-only software licensed to users.

The petitioners argue that studios should provide some sort of “offramp” for buyers to enjoy their games individually, even when online support ends. The petition and problems in the industry deal with both single-player and multiplayer games.

Are these demands a call for fair consumer protection or deleterious regulations?

Games and Intellectual Property

To unpack this issue, we need to consider the economics of property rights. Economist Armen Alchian argued that there were three core attributes of ownership:

1. The ability to use property.

2. The ability to sell property.

3. The ability to derive income from property.

When I was a kid, game owners had all three of these. If you bought a game, it came in a physical format. You could play it, sell it, or even rent it out (like Blockbuster or GameStop did). As games have transitioned away from physical discs, attributes 2 and 3 have disappeared.

What’s unique about the licensing model is that studios are now even limiting on attribute 1. Gamers were already upset by the slow death of the used-game market, but they’re even more unhappy with companies destroying their ability to play games they’ve paid for.

This is the fundamental difference between a product and a license. When you buy a product, you maintain a permanent ability to use the product. A license gives you limited or contingent access. The rallying cry of license opponents was recently echoed by Minecraft creator Markus Persson (also known as “Notch”):

Minecraft creator Notch responded to Pirate Software’s disapproval of the Stop Killing Games campaign

"If buying a game is not a purchase, then pirating them is not theft" pic.twitter.com/iVzAWSsFPK

— Dexerto (@Dexerto) July 9, 2025

Notch’s sentiment is not legally accurate. That is, you can still be charged for a crime for pirating games. But the deeper sentiment speaks to the fundamental issue. Game studios can treat products as mere licenses because governments have decided that the code belongs to the company, not the consumers.

Even though this movement is about games, the implications extend to the software industry in general. Increasingly, all kinds of programs are adopting license models. Products like Adobe’s Photoshop are no longer available for purchase, only through subscription. Stop paying, the software stops working. While Microsoft Office does still allow one-time purchases, they include license options, and one wonders how long before they make the transition to license-only.

Books are another example. When you buy a physical copy, you can generally do what you want with it, for as long as you like. You can read it hundreds of times, lend or give it to a friend, mark it up, fold the corners, copy down quotes, or even rip the pages out and use it for kindling. The book belongs to you, and you have use rights. But when you buy an ebook, you’re getting a license, and access may be revoked.

Likewise with games, where intellectual property law means the code to the game is not yours. You can’t just copy the code of a licensed game and modify it to play offline. Doing so, in general, violates the license agreement.

Intellectual property law gives software companies a greater ability to influence the entire lifecycle of their products than any company has ever had. If the government didn’t enforce these laws, companies would be unable to force consumers to lose games because consumers could copy and modify the code.

It’s not my intention in this article to argue whether intellectual property is illegitimate. FEE has published several articles on this over the years. I’m making a very modest point. Some might argue that the “Stop Killing Games” movement is about imposing unfair regulations. I disagree. Intellectual property law is inherently a regulation on consumers. Modifying it to impose responsibilities on companies is not adding new rules. Rather, this movement simply seeks to adjust current regulations such that they are less one-sided in protecting companies.

If you, like me, are a supporter of free markets, then it may be tempting to think this movement is just another EU regulatory overreach. But current intellectual property law already attenuates consumers’ ability to use the products they purchase, so modifying the law to restore some of their ownership rights could be a fair correction

Article by: Peter Jacobsen

Peter Jacobsen teaches economics and holds the position of Gwartney Professor of Economics. He received his graduate education George Mason University. His research interest is at the intersection of political economy, development economics, and population economics.

This article was originally published on FEE.org. Read the original article.

As I predicted, Biden’s latest policy announcement spelled the end of the student loan payment pause which began during Covid-19 lockdowns. However, ending the pause alone would be too unpopular so, along with that news, Biden announced student loan forgiveness.

Individuals making less than $125,000 a year will have $10,000 of their federal student loan balance removed if the order proves successful.

Many side-effects of the policy have been targeted for criticism. Rising college costs, increasing inflation, regressive effects, and moral hazards for future borrowers have been considered.

However, as an economist I noticed that one incentive has been ignored. If people expect future loan forgiveness to happen in this way, they will choose lower quality colleges, everything else constant.

Why would loan forgiveness make people choose lower quality colleges?

Let’s explain with some intermediate economics.

Relative Costs

To see why students will be more likely to choose low-quality education, let’s consider a simplified example.

Imagine there are two universities: High Quality University (HQU) and Low Quality University (LQU).

HQU offers students better classes, amenities, and connections. It is “high quality” in every sense. Let’s say HQU costs $40,000 a year. (In reality, expensive universities are more than this, but using a larger number wouldn’t change the results.)

On the other hand, LQU is a budget university. Class selections are limited, living spaces are in disrepair, and there is no promise of an expansive alumni network to offer new grads jobs. Due to this lower quality, LQU is less expensive, with a price tag of, say, $20,000.

Notice the relative cost of these two universities. HQU is double the price of LQU. Or, put differently, with the resources used to go to HQU one time, students could attend LQU two times. If these are the two options, the opportunity cost of attending HQU is two trips to LQU. Likewise, we could also say the cost of attending LQU is forgoing half a trip to HQU.

Enter loan forgiveness.

What’s important about Biden’s forgiveness plan for our example is that it offers a fixed payout for every student regardless of university quality. So let’s see what forgiveness does to the relative cost of these universities.

With $10,000 in forgiveness, the price of HQU (faced by students) falls from $40,000 to $30,000. The price of LQU falls from $20,000 to $10,000. It’s possible colleges could raise tuition in response, but we’ll hold that consideration unchanged for now (or in economist speak: ceteris paribus—“all else equal”).

Before the loan forgiveness, remember that HQU was double the price of LQU. Things have changed now. After the forgiveness, HQU is triple the price of LQU ($30,000 compared to $10,000).

In other words, going to HQU once would cost you three trips to LQU. Before forgiveness the cost was two trips. Thus, while the relative “price” of HQU has gone down, the “cost” of HQU in terms of lost opportunities has gone up. The following table summarizes the change:

	HQU	LQU	Relative Cost
Before Loan Forgiveness	$40,000	$20,000	HQU is 2x more expensive than LQU
After Loan Forgiveness	$40,000-$10,000 =$30,000	$20,000-$10,000 =$10,000	HQU is 3x more expensive than LQU

The result is that high-quality education is relatively more expensive compared to low-quality education than before the loan forgiveness. If people expect future forgiveness that takes this form, they’ll be making their education decisions with this fact in mind.

How will this impact education decisions? Well, if the cost of apples increases relative to oranges, we’d expect people would buy fewer apples and more oranges. Likewise, if the cost of high-quality college increases relative to low-quality college, we’d expect people to buy less high-quality education and more low-quality education.

The Third Law of Demand

Student loan forgiveness isn’t the only policy where a fixed price change has caused problems. In the market for illegal drugs, a similar principle operates. Laws that add fixed fines to drugs based on weight rather than quality lead to people consuming more potent drugs. Why?

Imagine two drugs: a low-quality version of a drug with low potency that you can buy for $1 per ounce and a high-quality version of the same drug with high potency that you can buy for $3 per ounce. Now imagine a cost of $1 per ounce is added to each drug to avoid law enforcement.

Since the low- and high-potency versions of the drug are equally enforced and punished, the cost of avoiding law enforcement will be the same. Consider what that does to the relative cost.

Now the low quality version is $2 per ounce and the high quality version is $4 per ounce.

Before the cost to avoid law enforcement, the high-quality drug was three times as expensive as the low-quality drug ($3/oz compared to $1/oz). After the cost to avoid law enforcement, the high-quality drug is now only two times as expensive ($4/oz compared to $2/oz). The relative cost of high-potency drugs has fallen. Thus, people buy more high-potency drugs than they otherwise would in a free market.

My former economics professor Walter Williams applied this same example in class to explain why married couples tend to go on fancier dates.

If you have to hire a babysitter at $20, it doesn’t really make sense to get a $20 meal at a fast food restaurant. A couple who chooses to do this is doubling the price of a cheap date. However, what’s $20 on top of fancy dinner and a Broadway show, for example? It’s a drop in the bucket.

This logic is called the Third Law of Demand or, sometimes, the Alchian-Allen Effect (it’s also the reasoning behind the iron law of prohibition). In summary the law goes something like this.

When you add a fixed cost to a good of varying quality, the cost of the lower-quality version will increase by a larger proportion than the cost of the higher-quality good, and this will cause people to substitute toward the higher-quality good.

Our education example is this logic in reverse. When you add a fixed subsidy (student loan forgiveness) you’ll get the opposite effect. It decreases the cost of the higher-quality good by a lower proportion than it does the lower-quality good, which means people will substitute into the lower-quality good, all else equal.

My suspicion is that Biden and advocates of student loan forgiveness would hope that the program would lead to more students having the chance to go to their dream college. However, the incentives created by the policy mean more will go to cheaper universities.

From my perspective, this effect of the policy isn’t such a bad thing. I’m a firm believer that, for many people, a cheaper university is a better option than a more expensive one. In fact, I also suspect many low-price universities provide better education than many of the top ranked colleges.

But, insofar as you believe you get what you pay for with universities, this policy will lead to students opting for lower-quality colleges.

Peter Jacobsen

Peter Jacobsen teaches economics and holds the position of Gwartney Professor of Economics. He received his graduate education George Mason University. His research interest is at the intersection of political economy, development economics, and population economics.

This article was originally published on FEE.org. Read the original article.

The Afghanistan War Was a 20-Year Failure in Central Planning

The Afghanistan War/nation-building project is now confirmed as a complete failure—and a costly one, in both lives and resources.

Brown University’s Watson Institute estimates the US spent $2.2 trillion over the 19 years, increasing the tax burden of every American by $6,000. Further, the Watson Institute estimates “241,000 people have died as a direct result of this war. These figures do not include deaths caused by disease, loss of access to food, water, infrastructure, and/or other indirect consequences of the war.”

Yet, in the end, it was all for nought. The US-sponsored Afghan government collapsed shortly after the lethally botched US military withdrawal, and the Taliban are once again in power. Only now, they are armed with billions of dollars worth of US military gear.

Who’s to blame?

In a recent speech, President Biden laid much of the responsibility for the failure of the regime on the Afghani forces for being unable to hold off the Taliban. The administration has also been quick to place blame on the peace agreement the Trump administration made with the Taliban before he left office.

However, the failure of liberal democracy in Afghanistan isn’t the fault of the Afghani military, the Biden Administration, or the Trump Administration. In reality, the failure of US nation building is a failure of central planning which was doomed to be a disaster from the very beginning.

Nation Building: Futile and Fatal

In 2007, Professor Chris Coyne of George Mason University published a book titled After War: The Political Economy of Exporting Democracy. The subject of the book surrounded the inherent problems of trying to export liberal democracy. Dr. Coyne broke these problems into two categories: knowledge problems and incentive problems.

The knowledge problem of centrally planning the establishment of other governments is that, despite the fact that politicians know what democracies look like superficially, they don’t know what underlying conditions are necessary to foster a healthy liberal democracy. For example, differing belief systems and cultures may be incompatible with any familiar form of liberal democracy. The US Constitution, for example, rose up within a specific context. Merely “airdropping” a constitution into a country doesn’t mean the underlying context will match with the constitution. It turns out airdropping political institutions is more difficult than airdropping supplies.

Gen. Stanley McChrystal, a former top commander in Afghanistan, once boasted, "We’ve got a government in a box, ready to roll in.” By now it should be obvious to everybody how much hubris was wrapped up in that claim.

Similarly, Dan Sanchez pointed out in 2016 that US central planners miss out on important local knowledge which cannot be codified. This decentralized knowledge is referred to by Nobel Prize-winning economist F.A. Hayek as the knowledge of, “the particular circumstances of time and place.” While central planners may like to believe they can access this knowledge, there is simply no way for them to centralize all this disparate, uncodified knowledge to serve the central plan.

Coyne continues by explaining the incentive problem associated with nation building. Even if central planners were able to solve the knowledge problem in theory, it’s unlikely they’d be able to implement their solution. Why? The implementation of the plan is controlled by US politicians who face incentives incompatible with successful nation building.

Consider the incentives of the bureaucracies associated with reconstruction efforts. Bureaucrats improve their position by taking on more roles and by increasing their bureau’s budget. Since there is a limited amount of funding available, this means bureaucrats have to compete with one another for funding.

So, despite the fact that successful nation building may call for different bureaus to work together, there is no guarantee that doing so will be to the benefit of bureaucrats.

It’s also important to note that US politicians are subject to the incentives provided by special interest groups. Through campaign contributions and lobbying funds, special interest groups influence policy.

Perhaps, for example, the path to liberal democracy in Afghanistan involves the US troops gaining citizens’ trust by not using indiscriminate drone bombing. In this case, drone bombing would be bad for the prospect of liberal democracy, but it would still be good for the bottom line of military weapon manufacturers. In that case, that special interest group may exert pressure on politicians to use these unhelpful tactics.

Ultimately, the assumption that America can spread liberal democracy via military action was wrong. It relied on conceptualizing state central planners as both being able to collect the requisite knowledge and being immune to conflicting interests in implementing plans. However, in the real world, this assumption does not bear out. Knowledge and incentive problems abound.

The Real Culprits

So there’s no need to play the blame game with Trump or Biden. The blame for the disaster in Afghanistan falls squarely on the experts in Washington, DC, who began this crusade nearly 20 years ago.

The question is now, how should we hold these experts accountable for this disaster?

Peter Jacobsen

Peter Jacobsen is an Assistant Professor of Economics at Ottawa University and the Gwartney Professor of Economic Education and Research at the Gwartney Institute. He received his PhD in economics from George Mason University, and obtained his BS from Southeast Missouri State University. His research interest is at the intersection of political economy, development economics, and population economics. 

This article was originally published on FEE.org. Read the original article.