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.