Episode 20: What is Economics Useful For?

What is economics good for? I think there’s a lot of confusion as to what it can do and what its limitations are.

The problem us economists face is that we must always have answers, and they must always be accurate. Anything short of that means that the entire science is bogus.

But economics is only as good as the data it relies on, and data is always imperfect in some way.

The way I like to talk about economics to the general public is that it helps tell you where to look, and also if you’ve found what you’re searching for.

The first part is like advanced geology mapping equipment. Let’s pretend that you’re looking for gold in your back yard. Now you can stumble around blindly and just dig here or there, and depending on how much gold you have you might find some. But economics can point you to where the best spot to dig would be.

Economics achieves this by figuring out which way data are facing. That is to say, to maximize profit, should we decrease prices? Well if you do that you calculate  that you’ll sell more products, but make less money per sale. Is it worth it? Economics can give you your answer.

But it’s not perfect because your data isn’t perfect.  Maybe your sales estimation model is off. Maybe reducing your prices doesn’t lead to as many new sales as you thought. Just like how you can miss the gold vein, sometimes you can end up with the wrong result. But it helps you get close. And with more refinement you can often strike something.

The second way it can help is to verify what you’ve found. So you pull a strange rock out of the ground. Does it have gold in it?  Economics can help you test if the strategy you’ve discovered is indeed a winning one.

The way economics can tell you with certainty what it is that you have is with the magic of the p values. You’ll see this in most econ literature. The p stands for probability, and it’s the probability that the effect you are seeing is because of random chance. The lower the p-value, the more confident you can be that an effect is “real”. The higher the p-value, the more likely the result is just the randomness of data.

A quick example is the fastest way to illustrate the point. You’re flipping a coin, heads or tails. My hypothesis is that the coin is rigged to always land on heads.

You flip the coin and it lands on heads twice in a row. Well that’s data in the direction of my hypothesis, but you could get the same result with a normal coin easily. So the p-value would be maybe .5 or a 50% chance that the coin is rigged (yes economists, I know this isn’t how p-value is directly calculated but I’m trying to keep things simple to illustrate the point), but also a 50% chance that the flips of a coin are random.

The next two flips are tails. Wow. The chance that a rigged coin would “misfire” twice in a row is pretty unlikely. Our p-value jumps to maybe .99, or 99%. We’re almost certain it’s not a rigged coin based on the data that we have.

Then the next 10 flips are heads. Every single one; right in a row. That is statistically fairly unlikely, but not impossible (probability of about .01%). So our p-value jumps down to maybe .07. Then the next 10 are heads. 20 head flips in a row? That’s really very unlikely to be a “localized streak” (probability of about .0001%). There’s almost certainly some connection between the coin and these flips; it almost certainly can’t be random chance!

For our example let’s assume our p-value falls to .04, or 4%. It is generally accepted in the scientific community that a p-value under 5% is “statistically significant”. That is to say, we’ve crossed a magical threshold. I can tell you with reasonable certainty that the something with these flips is indeed rigged. It’s still possible that I’m wrong, but so unlikely, that I can say with reasonable certainty that the rigging of the toss is real.

Then we flip heads another 10 times in a row. Well now we’ve flipped 2 heads, 2 tails, and 30 heads in a row. The chances of a coin being flipped 30 times heads in a row are astronomically small. I mean like .0000001%. Another way to think about it is you can expect to have a run like this if you did a series of 10000000000 coin flips (I may have missed a zero or two it’s hard to keep track). We’re talking rare.

So our p-value now jumps below .01, maybe to .009, or .9% that the effect is due to chance (in reality it might be much lower with 30 flips but stay with my analogy). We can be almost positive that our results are in fact real. There is something rigged about the tosses. The chance that they are not connected is practically, but not entirely, zero. There is truth to the famous Mac (from IASIP) quote that “with God, all things are possible”. And that’s certainly true. But really our data suggests we have a fact. Under 1%, or <.01 p-value is the next generally accepted threshold for scientists. Usually when 5% gets a * (to mark it’s significant), 1% gets ** (two stars)!

Okay so let’s flip the coins some more, and let’s in fact say that you flip heads another 70 times.

That’s a run of 100 head flips in a row. The odds become… impossible on a near universal scale. Like. A .00000000000000000000000000007% chance. I mean it’s such a small number it’s insane. In the scientific community we’d just say your p-value is now <.001. This is generally regarded as the last stop and is given *** (3 stars) to denote its statistical significance. There’s generally no point in going smaller because at just a .1% chance of being due to a random streak of data we can say with confidence that this effect is real.

Certain applications of statistics will push for an even lower p-value, but it’s really just to make a point. At <.001 whatever you are trying to prove is a fact.

Here’s another way to think about it. Lavar Ball says his son Lonzo Ball is going to play for the Lakers at Lonzo’s birth.  The chances of someone playing in the NBA are amazingly tiny, and to play for a specific team are tinier still. If Lavar Ball’s statement had a p-value of <.001 however, then even if Lonzo’s birth existed in 1001 different universes, he would play for the Lakers in 1000 of them.

At that point you can just say it’s destiny that Lonzo is in fact going to play for the Los Angeles Lakers. There is a cosmic connection, or a rigged system. It’s not up to chance.

And the same can be said for our coin.

Economics and p-values are powerful tools. And I’m only scratching the surface. There’s R-values and T-values and regression analysis to tell you all sorts of fun stuff.

But for the general layperson out there, this is the basis of the power of economics. To give you a general map of what is really going on, and then to test to prove that the gold you found is really gold, and not fools gold.

Episode 6: Using the idea of “utility” to calculate “value”

Economics gets a bad reputation for being wrong about things, or only measuring things in terms of dollars or GDP (gross domestic product).

But most of these “bad raps” are simply because people don’t understand what economics is, and what it is actually capable of.

When I talk about “economics”, I’m not talking about Adam Smith (Wealth of Nations), or Marx, or anything before the 1950’s really. Those guys were philosophers. They looked at the world, thought about things, and then made sweeping guesses about how the world worked.

They get credit for sometimes being right, but just because Aristotle philosophized that there must be some small finite particle because you couldn’t cut things in half forever, it doesn’t mean he discovered the quark!

We wouldn’t call Aristotle a nuclear physicist and we shouldn’t call Adam Smith an economist. Hard science research and philosophy are fundamentally different fields. The biggest difference? A lot of math. Statistics. Econometrics. Linear Algebra. Adam Smith drew some lines on a chart; it’s philosophy.

Modern Economics only really came into its own in the late 1940’s or 1950’s, with the Milton Friedman generation. That makes the science maybe 70 years old at most! And that’s nothing. Modern physics got started in maybe the very late 1800’s, so imagine the difference between what we knew about physics in 1970 (which was a lot, we had nuclear power, etc…), compared to today. It’s a whole different level of sophistication and understanding.

Economics has come a long way, but it is a much newer field and simply hasn’t had time to fully blossom. It also helps your field if the largest nations on earth is pouring billions into research to make weapons to blow other nations up (ahem physics, computing, chemistry, etc…). So you have to forgive the field of economics for being a little bit behind.

With that lengthy precursor; how then does economics calculate value?

When economists try and figure out which decisions people will take, they have to compare apples to apples. There are a few ways to do this. The oldest trick is money, or money equivalents. Would you prefer a massage or a hamburger? Idk. So I instead ask how much would you pay for one or the other.

Just give each a “value” in dollars and compare, poof. Now we’re cooking.

The evolution of this method of comparing values is the idea of “utility”. Instead of money, you figure out how much something is “worth” to a human, or the utility the human gets.

For example, when your spouse cooks you breakfast that has an inherent value. But because it is not a financial transaction there is no financial transaction where money changes hands; so you must turn to the level of “utility” (happiness essentially) the breakfast provides you.

The main way to measure this is still in dollars (money) instead of “units of utility”; which has little meaning. The best way to measure what a spouse cooked breakfast is worth is usually to illicit how much you would pay for someone else to make that same meal for you. But there are lots of different ways to calculate utility.

The main point is that utility more accurately represents human decision-making because humans make decisions in abstract ways.

We don’t boil everything down into dollars (money) and compare the two values every time we make a decision. And once you get into behavioral economics utility amounts become even more important.

This is because the traditional economic assumption was that humans try to maximize their utility. The axiom, or assumption we take to be true is that we are rational, we want what’s best, so we maximize our utility. If there is a simple way to make $5 we’ll do it because that’s more than $0.

But, of course, there are many many times when that doesn’t happen! Just read the rest of these blog posts. That’s behavioral economics.

The answer is of course that we’re just measuring utility wrong. Traditional economics MISSES critical variables. Mind journey time! Think of a paperclip on a beach.

You are walking down the street with 3 of your closest friends in high school. It’s the suburbs so not a lot is going on.

It’s a tree-lined street, and farther down the street there are kids learning how to bike on a training bike. The sun is out, and birds are singing. It’s a very nice day.

On the ground off to the side of the sidewalk, you spot a crinkled $5 bill. Dirty, but totally spendable. You note “Oh! Look it’s $5!”, the friend walking on your left turns to you and says “Ew, that’s covered in dirt, you weren’t really going to pick that up, were you? It could be poop!”

You glance at your other friend to your left, and then to the friend to your right. All of them are staring at you with one eye raised and a grimace of slight disgust on their face.

Classical economics says you pick up the $5 because your utility of $5 is greater than $0, but of course you don’t pick up the free money. There is a hidden cost that traditional economic theories miss, which is the “social utility”. There is a social cost to your friends thinking you’re weird. Or poor. Or dirty. And that can be insanely powerful, more than a free $5 powerful.

It’s not that economics is broken or doesn’t work; it’s just that often it isn’t advanced enough to correctly calculate all the variables appropriately.

The first MAJOR behavioral economic papers in the 1970’s and 1980’s were all about different ways to calculate utility. There’s transactional utility, social utility, discounted utility, etc… etc… etc… It’s all just trying to reframe what humans are weighing when making their decisions. Some of it is because of fear of loss, or laziness, or social pressures.

I’ll probably devote an entire other blog post just to Kahneman and Tversky’s seminal, groundbreaking, famous-making paper “Prospect Theory: An Analysis of Decision under Risk” from 1979. There’s a reason those two are really considered the grandfathers of the behavioral sciences, especially behavioral economics. This is one of a few famous papers that really defined the genre.

In sum, their whole point was that economists were doing it wrong! It’s not about linear choices or straight classic rational decision making. And I quote from that paper: “people normally perceive outcomes as gains and losses, rather than as final states of wealth or welfare.”

So sure, your final state after you pick up the $5 is +$5 but that’s not the calculation you go through. You feel the loss of your social status, you weigh that decision not as finite, but in the moment. It’s complicated and messy, and human.

And that’s hard to measure; but discovering the Higgs Boson was hard too. It just takes time and refinement. Maybe a few Nobel Prizes, and a few billions of dollars for a huge research facility (CERN Particle Accelerator but for Behavioral Econ) would go a long way.

So I’m positive about the future of the field. And the concept of utility is an important one, and one you should understand. So that’s a brief primer on it.

Btw, I have attached a picture of what real full-fledged economics looks from the original Prospect Theory paper from 1979. The good news is that later papers are… more concise and have more fun field work, although the economic models are more complicated.

This segment is not from some crazy appendix by the way, but from the heart of the paper, perhaps outlining one of the more important points, which is the concavity of u (utility). So just in case you were worried about what you were missing…

Also… this is a formula for the value of different prospects. Economics is so fun!

Don’t worry, they clarify this nicely later in plain English. I’d go through it, but I’ll save it for the post about Prospect Theory.