So before we get into economic science and experimental, what is the most important thing that people my age or in my generation should know that we don't?

Well, I kind of have two things that are kind of equally important. One is kind of specific and one is please, the first is about saving and investing. So now I'm 58 years old and I realize now based on how much the S & P 500 has gone up, how fast stocks have gone up. The average return of the S and P 500 has been 11.3% over the last 50 years. If I do a calculation, I realize that if I had saved $16,000, if I could have put away $16,000 when I was 22 years old, I'd have a million now. And I think that's something I never appreciated when I was a young person that I could have if I'd been able to sock away some money, not look at it, that I would have so much money now.

So it's very hard to, I can't tell you how you can get rich in the short run, how you can get rich next year in five years, but it's pretty easy to tell you how you're going to get rich in 30, 40 years. And that's just by socking away some money, putting in the stock market, not looking at it. So that's one thing that I never appreciated when I was a young person, and I think it's useful to impart on young people now that I never really appreciated how fast, how much investments grow, not how fast, how much they grow over a long period of time.

The other thing I thought I'd mention in this vein was a lot of people tell you the secret to success is hard work and keeping your nose to the grindstone, and there is truth in that. I don't want to deny that it's important to work hard, but the other thing I never appreciated when I was a young person is the value of being in the right place at the right time around the right people. So just being around a place where something big is happening or dynamic people are around that could make something big happen that really increases your chance of being involved in the next big thing, sort of catching a big wave. So I think to my own career, when I was a young researcher, there were a lot of people around with a better background and more ability that I had. But I was very lucky because I found myself in one of the places I was studying at Caltech.

That was one of the places that was pioneering experimental economics. And the experimental economics just took off when I was in graduate school. So I was lucky that I was able to catch the wave and contribute to the field before a crowd of brilliant young people appeared on the scene. So I was just very lucky to be in the right place at the right time. So my advice to young people is try to be around interesting people in dynamic places. If you have job offers, don't necessarily take the one that offers you the best deal, just try to be in the right place at the right time around the right people, go places, be associated with places where neat, interesting things are happening. So those are the two things. If I could sort of tell young people, give them some advice, those are the two things I would recommend.

And those are great pieces of advice. I see a common thread throughout them, and I might be making this up out of thin air because wishful thinking, I like the fact that I can tie them together and tie them to economics. Both of those are kind of dependent on institutions in a way. So being around dynamic people and having a place where dynamic people can congregate and innovate and have ideas together and actually act on them, that's an institution, right? To have a culture like that. And in order to keep having that and to have more places like that, we want to cultivate those institutions. And similarly with investment, in order for the stock market to [grow?], we have to ensure that we have growth and that's dependent on institutions, which is exactly part of what we're going to be talking about today. So maybe I made that up, but I think it sounds legit.

I think it's taking place in an institutional context. So when I say you should invest for 30, 40 years in the future, you need to have a system of secure property rights that ensures that you'll be able to realize your earnings, take your money out in 30, 40 years, and you have to have some kind of stability. And as you say, you have to have the economic growth that can sustain asset price growth, being around people who are going to do the capacity to exciting things and to innovate, depends on the institutions in place that allow people to benefit from their great ideas and make them workable. So you've really kind of hit the nail on the head with what's needed to realize your plans.

I think it's important to lay out the place where you're actually doing all this cool work in economics, which is the economic science laboratory. So can you tell us a bit about what it is, what sort of work you guys do, what sort of questions you answer and how?

Sure. The Economic science laboratory was originally founded by Vernon Smith, a Nobel laureate in economics and one of the founders of the field. It was founded in 1985. So what are experiments in economics? Well, in economic data, any all economic data and classified into two types, one type is observational. So this is going out in the world and recording what's happening. So when we get price data of some commodities, if we GDP data, interest rate data, we are recording what's happening in the world. That's observational data. The other type of data is experimental data. This is data that's generated in settings that are deliberately created by the researcher in order to answer a search question. That's what experimental data is, and that's what the economic science laboratory was founded to promote and engage in. So typically what we do is what's called laboratory experiments, which means the setting is we bring volunteer, we bring volunteers into the lab and we put them in an economic situation, which is say a situation, a game if you will, which has the same structure of an economic model or an economic setting of interest.

We incentivize them, which means we pay them more the higher their profits are in the economic model that we're building. So for example, if it's a model, if it's an experiment about firm behavior, we incentivize the people in the role of firms by giving them more money. The higher the profits they make in their role as firms, you can think of it as they accumulate a point score and the point score is based on how well they're doing in the experiment, in the economic model being considered and that point score converts to dollars or whatever currency you're using at the end of the session. And so the big advantage of laboratory experiments is you have really control over the environment so you understand fully the underlying structure of the economy in a way you don't out in the world. Occasionally we do field experiments, which means we conduct an experiment which is outside the laboratory setting.

The typical participants in the laboratory are undergraduate students in a classical experiment. And the two reasons we typically use students are that one, there's students available, so there are many, many participants available. The other is it facilitates replication. So if I do an experiment at the University of Arizona and somebody at another university say, University of Virginia doesn't believe my results, they can replicate with a similar population. And so focusing on students on university students facilitates replication of your studies. And so we study all kinds of topics. So we study individual decision making, we study strategic interaction, we study market behavior and we study macro economies. We study economic growth and we do a lot of work like this. We typically focus on behavioral data as economics typically does. We study the decisions people make, but we also study non-choice data. For example, we study people's emotional state while they're making certain decisions. We study their biometrics while they're making their decisions. So a lot of different things. It's a very active lab and it's exciting to be involved with a lab that does a lot of activities like that.

Yeah, a few questions stemming from that. I'm just going to shoot 'em off because they're a little shorter. They're maybe not as involved, but how do we know that students are a valid sample for maybe the whole population if we're trying to gain economic insight into human behavior, how do we know that students are okay? It's good for replication, but do adults act like that? And then…

I'm sorry.

Oh, just one more question. How do you measure emotional states? We've talked about this a lot, but I think it's super interesting and I want the listeners to hear about it a bit.

Okay. So there's studies focused on how much you can generalize behavior of students to other populations. So you can do an experiment, you compare students of the laboratory to other people coming into the laboratory and participating, or you can take your task outside the laboratory and run it with other populations. And when you do that, you always see that qualitatively you get similar results. Sometimes the magnitudes are a little different. For example, you might get, if you're trying to measure say, risk aversion, you'll get different risk aversion estimates and a sample of students than in a sample of 50-year-old adults. But if your tests of economic models, I can't think of any exception, this to the principal that if you're testing an economic model that if it's supported among students, it's supported among other populations as well. And an experiment with multiple treatments where you're looking for a treatment effect finds the treatment effect going in the same direction, whether it's with students or with any other population. So the results qualitatively generalize very well.

The one point where a result in the lab may not generalize to a setting out in the world out in the field is if you've changed the game too much from what exists in the field, then you can get slight differences. So there are cases where if you change a game enough that you change the results, but the student population itself is typically no different or minimally different from other subsets of the population. So that's very encouraging. Emotional states we measure, there's an old fashioned technique which is you stop the experiment and you give people a survey with might be 30 to 50, 60 questions about how strong they feel a particular emotion at a certain time. That's an old fashioned, that's a classic technique. It's valid, it's interesting. But what we do is in our lab is we use software to track people's facial expressions as they engage in the experiment.

So we videotape people while they're doing the experiment and then we analyze the recordings later on with specialized software we have and we merge that with the behavioral data. So we can ask questions like what emotional states predict that you're going to donate more to charity or sell in a stock market? And then we can also look at the emotional reaction to getting information. So suppose you get a lousy offer in a bargaining game, what emotions appear when you get a bad offer or a good offer? So you were able to, with facial expressions, we're able to measure emotional states for emotions that appear in the facial expressions.

That's awesome. Can you think off the top of your head, I know this might be a little difficult, but of an example of an experiment where it differs too much from the real world. Is there anything you can think of that has actually done that and how did we know it was?

Yes. For example, I have a paper that had several different treatments. So it was a social dilemma experiment. You could cooperate or you could be non-cooperative. So we set up this abstract game in the lab with students and people exhibited a moderate level of cooperation. We then took this game and we ran it with a group of recreational fishermen out at a recreational fishing pond. The abstract game people cooperated to a similar level as the students. Then we kept we the general structure similar, but we changed the game so that now you cooperate. We put the people around the fishing pond where their fishing rods and we said, the way you cooperate in this game, you can make more money if you don't fish, if you restrain yourself from fishing and taking out too many fish from the pond. And nobody did that As soon as we had them actually in the fishing game, people acted much more non cooperatively and they weren't prepared to forego fishing, which they really enjoy to increase the payoff of other people in the group.

So it mattered whether they were playing an abstract game on paper, even though there was real money involved, they were much more cooperative than what cooperation actually involved not doing the thing they really liked, which was fishing. So that's an example of when you change that showed if I changed the population, if I went from the students to the fishermen with average age 55 and I had them play the same game, they play the same game the same way, but if I change the game, then they behave differently even though it's in its abstract structure, the game is similar but they don't think of it as similar.

And it's not even necessarily the age difference. If you had had a recreational fishermen student in the student population, they'd probably behave more like the actual fishermen.

I think you're exactly right. So it's not an age effect, it's an effect of what of the context you might say. I think you're absolutely right.

How did you come to inherit this lab? It's such a cool resource and way to answer questions. How did you come into that?

Well, I was lucky again, I guess being in the right place at the right time. So the director position was vacant because the previous director had left. And at the same time, my family was itching to move somewhere, wanted a change of scenery. And so I let it be known that I was available if they were interested and they happened to be interested and that's how I was able to get the job. So again, I was in the right place at the right time. I was in the right state of mind ready to move when they were looking for a director.

Do you think that this theme, the almost accidental but blissfully, so like a great serendipitous coincidence, have you seen that in a lab? I don't know how to necessarily phrase this, but I would think this is a fundamental part of human beings to get this sort of piece of advice. Advice usually is true and applicable to more people than the person giving it, at least we would hope. But has the lab taught you that or anything about humanity, human nature that you don't think other strains of economics can get at? Or is this just something you've learned experientially and then it also just applies to humans that way? Yeah,

Well I have to say it's the latter. So that's something I've learned through my lifetime of experience. Not directly studied it in the lab, but like I said, lab data isn't the only source of knowledge. There's observation of the world, and that's where I came to that conclusion. But it would be nice to study to try to study that phenomenon in the lab. Now it is the case that you can't use the lab for everything. So the lab is one methodology among many. And I love to do laboratory research, but I don't mean that as to slight other methodologies in economics, economic theory is very important, empirical work, non-experimental empirical work is also very important for understanding the economy. All these methods are complimentary

And

Some things you learn by looking at the world around you rather than in the lab.

Do you think that the fact that you're so drawn to the lab and that this is where you seem to excel, does that have to do with just your research interests or maybe your nature as a person? What draws you to it?

I really think it's so some people go into economics because they love the mathematical elegance of it. Some people go into economics because they really want to learn something about how people behave. They're really guided by I want to know why people do this strange thing. And that always guided me. So that naturally led me to doing behavioral research in the lab. So it really depends on, there are different types of people in this field and I think it has to do with what aspect of economics they find compelling. Like I said, I think a lot of people go into theory find the mathematical elegance of economics, which I do appreciate, but they find that really, really attractive and they're drawn to that. A lot of people find working with data find econometrics which is elegant in its own way. And you learn a lot about the economy by doing econometrics. Some people are really passionate and attracted to that idea of working with big data sets. So I think my personality and interests are conducive to experimental economics. When I was in college, I majored in psychology and economics. I was equally interested in both. And that sort of naturally led me to psychology has been at least in part in experimental science for a very long time. And so that kind of attracted me to experimental economics, the interest in psychology as well as economics.

Yeah. So speaking of how different types of economics are complimentary to one another, A funny complement might be experimental economics to macro. Not only is it kind of difficult, right? Because every time in the lab you simulate an entire economy. Is it a very small economy relative to really any economy we observe out in the real world. But also every single time you run an experiment, even though there are maybe up to 20 people, maybe even more, if you can handle that, our lab at UVA can't handle really more than 20, you lose 19 observations because all of those count as one, which I guess is interesting. You can observe different things, but it doesn't necessarily seem like a super intuitive tool to use to study macro. So can you kind of walk us through what it looks like to run a macro experiment and how experimental can actually give us an insight that may be looking at the real world?

Okay, so the overriding question is the overriding topic of interest is why are some countries rich and some countries poor, some countries have a high amount of social capital, some countries have a low amount of social capital. And in the world it's tricky. So say we want to know why is the United States different than Brazil? And there's so many factors that come into play. There's so many differences between the United States and Brazil. And so to try to start understanding how each individual institutional detail, cultural detail matters, you have to be able to isolate individual aspects, individual aspects that differ between the two countries and the lab is a way to try to do that. So in the lab what we can do is we can create countries, we can create small economies with production, consumption, government, and we can create these economies that differ from each other in only one aspect.

So we can calculate, we can create economies that differ only in the system of government. So we have two economies identical in structure. In the lab, each might have 20 people. Let's say one of them is a dictatorship, one of them has political competition as two parties, another one a third treatment might have policy determined by referendum like in Switzerland or in many localities in the US direct democracy. So we can isolate the effect of just purely those institutions in the lab, all else being equal. Furthermore, if we are comparing United States and Brazil, we have one United States to compare to one Brazil in the lab, we can create any number of economies identical in structure and compare those to any number of other economies. They're identical in their structure. So we can compare 50 democracies with 50 dictatorships. All of them are otherwise equal. So we can run significance tests and we can see with any level of precision whether outcomes differ in under one treatment than another.

The other issues that arise in the world, you might say we want to compare institutions in the world. We might do something like let's compare institutions before and after a revolution. But that's not a clean comparison because if a revolution occurs, it must be that the previous institutions weren't functioning that well. So I mean that's referred to as endogeneity. The revolution just doesn't come about randomly. It comes about because of previous conditions. And so when we compare the conditions before and after the revolution, we're not really comparing the institutional structure before and after the revolution in a clean way. But in the lab we can, in the lab, the experimenter can just say, okay, we're going to, all of a sudden this is a dictatorship and it had nothing to do with the failure of previous institution. And all of a sudden we can say free speech is outlawed. The experimenter says that it's not a function of whatever the speech was before it was outlawed. So the lab allows a very clean way to establish causality between institutional structure and economic outcomes. So the causal relationship is clean. So because the institutions exogenously imposed by the experimenter.

And how do you measure that? What do you use to measure the effects of an institution?

Okay, well the best measure you can measure things like average prices in the economy, the output of the economy, how much is being produced, but the best measure of performance is overall welfare. This is something that's actually really difficult in the world to measure. We can measure the GDP of the United States pretty well, but the overall level of welfare in the US depends on consumer surplus and the economy damage being done to the environment, et cetera. Things that are hard to quantify. In the lab, we have a natural measure of welfare and that is how much people earn in the experiment. There's a very clean measure of how well objectively the economies are doing in the lab. 

And how is that different from GDP?

For example? Think about the concept of, so welfare for example would include consumer surplus, whereas GDP wouldn't. So GDP is the sum of the market value of goods and services being produced. Okay. Now suppose you're a consumer in the market and you value something at $10. The $10 would be the most you'd ever pay for it if you had to, but you only pay because the market price is $6. So you're able to buy it for $6. You've added $6 to GDP. But actually the benefit is there's also additional benefit, which is that $10 minus $6 surplus or welfare you got in excess of what you paid in the experiment. We can measure that very clearly and add that to the welfare calculations, whereas that doesn't get added into a GDP computation because the GDP company is just the market value goods and services produced. The actual value to consumers is different than that.

So we have these things called rotunda principles. When we teach macro at UVA, one of our professors came up with this clever term for it. One of them is trade creates value. The other one, there are a few of them, but one of the other notable ones that's really relevant is the three sources of economic growth are resources, technology and institutions. And I know them verbatim because if you spell a word wrong, well no, we actually give points back for spelling a word wrong. But if you mix the order of the resources, technology institutions, you get the question wrong because it actually in that order tells solo one, solo two modern growth theory. It tells a story about how macro developed and how we came to understand the economy a whole thing. And obviously we've been talking a lot about institutions, but it sounds like what this is actually being able to measure the value that trade creates in a way that is so hard to teach students because you can't see it just looking at market prices.

Yes, correct. So experiments are a great way to teach the gains from trade because there are clear measures of gains from trade. So for example, if we do an experiment, say a purposes to teach, kind of gain some trade that can be generated in the market, say you're a seller and I'm a buyer. And what we do is the experimenter can tell me as a buyer the there's this good called X that we can create a market for. If you buy it, you get $10 in payoff, we'll give you $10. As a buyer, you're a seller. We say you have the capacity to sell this unit, this good called X. If you sell X, you can sell it for whatever price you can get for it, but you have to pay the experimenter $2 that represents your cost of production. So if we don't trade, neither of us makes any money.

If we can trade at some price between $2 and $10 between us, we've made $8. And so you can really see how the market, that trade, that gain of $8 wouldn't have existed without the market bringing us together. Doing an experiment is such a clean way to teach an abstract concept like this. Experiments have become very big in instruction in teaching economics, just like it shouldn't be surprising. Experiments are how we teach sciences. We teach chemistry to high school students with experiments. We teach physics with experiments, we teach psychology with experiments. So it's only natural that economics education can benefit in the same way.

Yeah, that's a really good comparison. Let's talk some results. So what does economic theory and just generally economic thought, tell us about what institutions are good for growth and welfare and people and is that seen in the lab?

It is widely believed and the researchers, Acemoglu and Robinson are associated with this particular view that, and they've come up with this terminology that I like to borrow from them, which is that inclusive institutions are conducive to growth and extractive institutions are harmful to growth. So Acemoglu and Robinson, their category of inclusive institutions. Inclusive institutions are those that allow participation from a broad segment of society, ideally all of society. These are things like a democratic voting process. Everybody can vote free speech, anybody can say whatever they want. Freedom of assembly, anybody can get together with anybody else. Those are inclusive institutions. Extractive institutions are institutions that allow an elite to exploit everybody else. So for example, dictatorship is like that. So if there's a dictatorship, then the dictator and people associate the dictator can exploit everybody else a prohibition on from expressing those are extractive institutions in the laboratory.

So I've been involved with research to study the effect of different institutions on economic growth. So I can create an experimental environment in which a well performing economy can grow, but a poorly performing economy won't. So there's scope to observe different levels of economic growth, and sure enough, it's typically the case that inclusive institutions do lead to higher growth in the lab and extractive institutions lead to lower growth. One thing we've also discovered in the lab is that a functioning price system is really important. So a price system in the economy, the system of prices in the economy tell the economy what to produce, how much of it to produce, and how much to save and invest for the future without a price system to put up prices on consumption goods and capital. It's really difficult to, even if you're well-intentioned and say you're a dictator and want to maximize the discounted value of economic growth, which is the overall payoffs over time to everybody, it's impossible for somebody to allocate the resources. Well, it's too difficult a problem unless you have prices to guide you to reflect the scarcity of different goods in the economy. So one thing we've discovered with our experiments is a functioning price system is really crucial in allowing resources to be allocated in a way that's conducive to growth.

Something I struggle with, I see the beauty in and the usefulness of lab experiments, but part of me wonders if you can actually divorce people from the culture that they grew up in and live in. So obviously you're running these in Arizona, in America, and we have certain ideas and cultural norms around some of these things that you test. And so I can imagine, even though I believe it, maybe because I want to, that this stuff holds someone criticizing these findings and saying that you can't remove people from their institutions that must influence the economy that the lab is creating even if you don't intend to. So what sort of a response would you give to that sort of comment?

I would say that that point is well taken and we can check it. So for example, if somebody says, well, these results in the United States don't apply in Brazil, we can go to a lab in Brazil and run exactly the same experiment and see if we observe the same thing. So those cultural differences are an important dimension that has to be taken into account. And so fortunately, the experimental methodology allows us to check for these, does check if cultural differences might affect the relative performance of different institutions. So that's something that can be checked. Now in general, if you survey the landscape of experiments of experimental economics, most studies exhibit very small differences when conducted in different cultures. Studies that involve market behavior involve individual decision making in the absence of any other people interacting and experiments where there's no scope for cooperation or social aspects to enter, behave similarly all over the world.

As a broad general statement, where you do get cultural differences are in a class of experiments studying what we call social preferences. This is how the outcomes of other people, how your decisions affect the outcomes of other people. So things like social dilemmas where there's scope for cooperation games where altruism can make a big difference, games in which how much you trust other people make a big difference. Those do exhibit cultural differences because there appear to be really different norms in different parts of the world. And so if your experiment, if those aspects social preferences are very prominent in your environment, you particularly would have to check whether the results hold in different parts of the world to make a statement that they're general. Typically for market experiments, I'm unaware of any market experiment of the kind of described where results are different in different parts of the world. They tend to behave the same everywhere, but the issue, the skeptic raises that the same results might not occur in another country. That's fair to go to that country and check it,

Which is awesome because I think a lot of the time we embark on experiments, I say experiments, but I don't mean necessarily experimental economics. I mean academic research that is not easy to replicate, either it's super expensive or the methodology is complex or you just can't package it. Whereas a lot of experiments are done online or even on paper, it's kind of easy to just print the sheet out and hand it to someone or just log into that web browser, which is super cool. It's funny, I want to say it's funny, but it's also, it floors me how beautiful it is that now we can ask and answer all these sorts of questions just because of technological innovation.

I agree. So suppose we want to say, well supposedly have an economy where there are people in the US and Brazil interacting at the same time, and how does that behave? Does that behave differently than an economy populated by Americans? Until recently, we could in the US could both log in together, but now we can. And so technology makes more and more things feasible all the time.

Yeah. So along this idea of inclusive and inclusive, what is it? Inclusive and?

Extractive and extractive institutions?

Yeah. Yes, that's what it is. I just want to say exclusive because it's the opposite of inclusive, but that's not necessarily right. I thought one thing that you mentioned when you came down and presented this work at UVA, one of the things that you were talking about was actually voting and electing representatives and kind of structures. Obviously a dictatorship ends up, maybe not obviously, but I think it's kind of obvious it ends up with lower overall welfare. It's very extractive. But can you talk about the different results depending on what type of electoral system and other institutions are at play together on welfare?

Sure. So as you mentioned, on average, we find that a dictatorship will do worse than an inclusive institution of political competition. You can be lucky with your dictator. So what happens in the dictatorship is crucially sensitive to who the dictator is. And you could be lucky and your dictator could be benevolent and your economy could do pretty well, but on average it won't. On average, a dictatorship won't do as well as political competition. Now, one thing you could do is, so most of the time in economic economic models, we assume benevolent motives on the part of the people in power. But suppose we allow to be corrupt. A dictator gets both. A dictator will steal a lot of resources if they can without fear of being caught or any fear of any punishment. The political competition will also lead to a lot of stealing unless it's policed.

And it's because under political competition, the horizon of the people in power is actually more short term than that of a dictator. So sometimes there'll be even more theft under political competition than under dictatorship. So it is very important to be able to have other institutions in place that police, the people in power, that provide checks on them from appropriating too many resources to the uses that they favor. So it's a complex problem. On average, the research does show that the political competition is better than a dictatorship on average, but it's very important to have other institutions in place to incentivize whoever's in power to behave benevolently if possible. So that's what we're working on now.

So not all of us have access to an awesome experimental lab that can watch emotions and stuff, but we do have access to obviously these results and these ideas. And not all of us have access to maybe being the president, a role model or hopefully a role model or a congressman. Not all of us are meant to do that time and place hard work, all that stuff. Preferences also. But what can we learn from this, even if we're not going into economics as just people operating in a society, what should we expect to have a prosperous society where everyone is better off and how can we enact that either politically or in our own lives, all of the above?

Well, that's a difficult in general question. So from experiments in general, if you really read the results in detail, you can really learn a lot to help you in your daily life. So learning, so the macro experiments we've been discussing are kind of on a big scale. So it teaches you kind of big lessons about the economy overall, very hard for an individual to kind affect the behavior of overall economy. But there are other experiments that really tell you a lot about things that are useful in your life. So experiments where people lose money show the hazards of certain types of situations you find yourself in.

For example, there's experiments generally speaking, any experiment that puts you in competition with somebody else reports the result that people compete too hard, they just compete too hard. So they'll typically dissipate all the benefits available in a prize. You can compete to win in an auction. People tend to bid too high in a contest. People compete too hard, exert too much effort. And so a lesson to be learned is that if you're in a competitive situation, your instinct is to compete more than is optimal, and maybe you should kind of be aware of that and kind of restrain yourself. Another thing we learned from the literature on social preferences is that the basic classical assumption in economics that people only care about their own consequences themselves is just way too simplistic that people have your utility is based on what happens to you without regard to what happens to other people.

And that's just way, way too simplistic. So people have a strong altruistic streak. They have a strong envious streak. They resent people doing much better than they do. They feel bad when they have much more than somebody else and have an instinct to help that person. People have a strong instinct to pay back kind actions with kindness. They have a strong instinct to try to punish nasty actions with nastiness. People have two sides when it comes to being cooperative. People have a cooperative side and a selfish side. So if there's a situation in which can cooperate, they don't find themselves being completely cooperative or completely selfish. They're kind of somewhere in the middle. And so once you learn about getting those insights about how the human beings you run into in your life are likely to behave, I think helps you a lot. So there are lots of lessons to be drawn from experimental economics, so it really guides me in how I live my life quite a bit. It is one of the kind of sources of intuition I have about how the people I interact with are likely to behave or what I should do in a given situation.

Yeah, that's awesome. Thank you so much for taking the time to be on the podcast and to share all of your knowledge and your wisdom and your passion for economics, especially experimental. I really love it and I think it's super interesting, and I think my listeners we'll learn and do agree as well. So I have one last question for you if that's good. What is one thing that you believed at one time in your life that you later changed your position on and why?

Well, I used to believe many years ago that human advancement was exponential necessarily. So I thought progress would follow the smooth exponential path of continuous progress and a lot of faith in technology, in new technology showing up on a consistent basis. So I used to think when I was growing up, I thought that by 2024, we'd have colonies on the moon, we'd have cities on Mars, life expectancy would be at least a hundred. But now I realize that actually progress comes, but it comes in fits and starts, and innovation is expensive and risky and there are obstacles and sometimes you break through the obstacles and progress is not this smooth path. It's more looks like a time series of stock prices or something goes up and down. The trend is upward, but it can even go in reverse brief for a while. The overall trend is towards progress, but it really comes in bursts and fits and starts. Technological progress is fickle. It's an unpredictable thing. And so I've really kind of changed the way I think about kind of human advancement over the years.

Once again, I'd like to thank my guests for their time and insight. I'd also like to thank you for listening to The Great Antidote Podcast means a lot. The Great Antidote is sound engineered by Rich Goyette. If you have any questions, any guests or topic recommendations, please feel free to reach out to me at great antidote@libertyfund.org. Thank you.