H@H: Ep 23 – On this episode of Here@Haas, Ray talks with Shachar Kariv, Tel Aviv-native and former Department Chair of Economics at UC Berkeley. We delve into Shachar’s research on social preferences, including the 3 fundamental tradeoffs of decision-making and why Yale law students have such a disproportionate impact on society. Shachar then talks about how his virtual teaching experience and his expectations for the fall. Finally, we wrap with Shachar’s contributions towards X-Lab, a Berkeley social science laboratory, and Capital Enterprises, his own financial services startup.
I would actually argue that all decisions in life large and small, financial or not financial, are basically governed by three trade-offs: “Risk vs. return, today vs. tomorrow, self vs. others”
“There is more heterogeneity in altruism within socio-demographics than across socio-demographics.”
“We live in a democracy but eventually a lot of the decisions are made by elite groups.”
“Kale is just completely overrated. Basically I’d rather eat grass than kale.”
[00:00:00] Welcome to hear@haas, a student-run podcast, connecting you to students and faculty within the Berkeley Haas community.
[00:00:08] Today, we’re joined by a Shachar Kariv, a visiting professor and the former department chair of economics. He currently teaches game theory and microeconomics for EMBA and evening weekend students.
[00:00:24 ] Ray: Welcome to the podcast Shachar.
[00:00:26] Kariv: Thank you. Thanks for having me. Great pronunciation of my name!
[00:00:31] Ray: Alright. So first, just tell us about your background and how you came about teaching here at Haas.
[00:00:40] Kariv: I was born in Israel and I started when I went to undergrad, I wanted to study math and physics. But for reasons that it will be too long to get into, I ended up basically in my first semester of undergraduate, I ended up that I was only able to audit one class and the only class that fits with my schedule was a higher division elective on game theory in the math department in Tel Aviv University. And this was a life-changing experience. Uh, I said to myself, Oh my goodness, you can actually describe human beings in terms of mathematical modeling. And this caught me immediately. So, I did my undergrad in economics and then I liked it so much that I also did my Ph.D. in economics at NYU in fields that we call decision theory and game theory. We can discuss them later. And when I graduated, when I got my Ph.D., my first job was Berkeley and, uh, that’s it.
[00:01:52] Ray: So why were you interested in doing a Ph.D. in the United States of all places?
[00:01:59] Kariv: Asking the question like this from an academic I think, you know, with all modesty is like asking a basketball player. Why do you want to play in the NBA and not anywhere else? You know, US academia became the center of gravity for academia.
[00:02:15] And actually what we consider the field research university in the United States is Berkeley. Then the history is actually that the rise of UA academia happened between world war one and world war two. Many people from Europe actually left and came to the United States. And you know, now it’s the center of gravity.
[00:02:38] So even though when I went to Ph.D., I honestly thought that I will return to Israel and Israel have great universities, was clear to me that if I want to do a Ph.D., I need to do it outside. And you know, I enjoyed every episode of my life, but if I could turn back time and go to one of them, I would come back a Ph.D. student.
[00:03:01] It was a wonderful experience. People from all over the world and we all came here to the United States and then some of us stayed.
[00:03:12] Ray: I want to shift gears and talk about some of the research that you’ve done. Since you’ve come over to the US you have done a good amount of this research in the realm of social science.
[00:03:24] Can you tell us about some of the topics that you generally study and research about?
[00:03:30] Kariv: So, you know, I would say that I am a theorist. I’m what is called the decision theorist, but I also care not only about writing models that will describe human behavior but also confronting these models with data. So, we can actually test these models and improve these models. Now, all models in economics are wrong; let’s start with this. Because it’s just, it’s a model. It’s a simplification of the world. And, you know, uh, many times, actually a good model in economics is actually what I call strong and wrong, meaning you make a strong prediction and because you make a strong prediction, it is easy to falsify these predictions within a valuable set of data.
[00:04:23] Kariv: You know, you need to make many decisions in life. Life is just an infinite sequence of decisions. But I would actually argue that all decisions in life large and small, financial or not financial, are basically governed by three trade-offs.
[00:04:41] I call these trade-offs the fundamental trade-offs in life. The first trade-off is the trade-off that I call risk versus return. Think for yourself, for example, if we’ll talk about the financial domain, should I put my money in stocks or in bonds? Bonds, there is less risk, but the lower expected return. Stocks is riskier, but have a higher expected return.
[00:05:08] So this is the first fundamental trade-offs in life. It is risk versus return.
[00:05:13] Kariv: The second trade-off is the trade-off that I would call the trade-offs between today and tomorrow. You can think about it like consumption today versus consumption tomorrow.
[00:05:24] Should I buy this car? Or, should I put the money aside and be able to basically consume more in the future. So, this is the trade-offs between today and tomorrow. By the way, this trade-off doesn’t only govern financial decisions. For example, should I eat this cookie? This is what I want to do today.
[00:05:49] Ray: Yeah. Short term pleasure versus long-term weight gain.
[00:05:52] Kariv: Exactly or, you know, take, for example, any health behavior. Also, exercising. Very few people like to believe that they actually find it fun to go to the gym. You know, maybe if you go to the gym just to look around, to socialize, and then you leave. That may be fun. But actually, you know, working at the gym is sweaty. I think it’s fun when it’s over.
[00:06:17] Kariv: So, this is the second trade-off, today versus tomorrow. The third trade-off is the trade-off that I call self versus others. And this is the trade-off between your own wellbeing and the wellbeing of other people.
[00:06:35] For example, when you save for your retirement, you need to make a decision on how much money you are going to live for your kids and how you’re going to allocate the money among your kids. So, any decision that altruistic in nature is basically about self versus others. Now I know that people think that the economist thinks that everyone is on pay off, maximize it.
[00:07:05] Basically you are perfectly selfish, but you know, even hardcore economists don’t actually believe this. Of course, we have altruistic preferences, but different people have different altruistic references. So, a lot of my research has been about basically understanding, modeling the preferences with which people are solving these: risk vs. return trade-off, today vs. tomorrow, and self vs others. And also, using laboratory experiments especially trying to see how accurate these models are. And, you know, because in many decisions we are basically doing via agents. For example, when you decide how to invest, you go to a financial advisor, but if the financial advisor doesn’t know your….
[00:08:02] So this how you are basically trading off risk versus return. This financial advisor might put you in a portfolio that is actually too aggressive for you, too risky. Then when it is a downturn because it doesn’t fit your preferences, you’re actually going to sell exactly at the wrong time.
[00:08:24] Ray: Right. I think we’re potentially seeing that early this year with starting with the academic or with the pandemic.
[00:08:32] Ray: I read in some of your research that you define social preference as the trade-off between what we had just talked about, right, being selfish versus fair-minded. Can you elaborate on some of the insights that you found in terms of, you know, is there any correlation of selfish versus fair-mindedness across cultures, across different genders, and across even different professions?
[00:09:00] Kariv: That’s a good question. You’ve done your homework. So, we actually tested or solicited the social preferences of a very large sample of Americans and also particular samples that I can talk later about that they are of very particular interest.
[00:09:26] There are a couple of important messages from this research. The first research is, you know, Americans are actually very altruistic but they are very heterogeneous on how altruistic they are, you know, and towards who they are altruistic. You know, some people think that success is because of luck. Some people think that success is because of work.
[00:09:53] And of course, given your belief that you have about who is successful, who is wealthy, this will determine your social preferences. You know, people that actually believe that if you are poor, you probably either been unlucky or you actually had a bad starting point. Of course, more likely to be altruistic than people that think that if you are poor, well, you didn’t work hard enough. We know this sounds human but we were able to actually document them in details and you know, I would say now following your question, I always say to students, maybe it’s the most important thing I’ll tell you in my career. So, you know, you kind of ask me the question. Let’s say, are there differences in socio-demographics in how well altruistic you are? For example, are females more altruistic than males? Because, you know, we always try to organize the world in our heads in terms of sorts of demographics. Is one’s ethnicity more altruistic than another ethnicity? Are people at some point in the income distribution are more or less altruistic than people above or below in the income distribution? Are people on the East coast more altruistic than people on the West coast, et cetera, et cetera?
[00:11:14] So here’s the important sentence. There is more heterogeneity in altruism within socio-demographics than across social demographics. So, people vary a lot in their levels of altruism. And these variations cannot be explained simply by socio-demographics. Now, of course, if you do simple differencing means you might actually find that one socio-demographic is more altruistic than others, but this is missing the point because even though you might actually have a difference in means, the distributions are actually so wide. Exactly. Exactly. So, you know, one thing that I learned from my research that actually, you know, I always find comforting, you know, we need comfort these days.
[00:12:11] Kariv: We debate. We debate about taxation and redistribution. But given my research, I understood why we are debating. We are debating because our preferences did govern our views about taxation and redistributions are so heterogeneous. So, you know, the debates are healthy. We can actually of course have the debates in a more civilized manner that will always be good, but you know, there are real issues and we have different preferences, so we should, uh, you know, respect the heterogeneity in preferences that we have.
[00:12:50] Ray: So, when you say there’s more heterogeneity within social groups, for example, for people who are lower-income, right?
[00:12:58] There’s actually a lot of variety in terms of their preference or in terms of their altruism within this group than for example across like income groups.
[00:13:09] Kariv: Exactly. However, but there is a big, however, you want to, you want to hear the however on one hand or the other hand, and as I told you, the research was done with the general population. It really, it was thousands of Americans. But there are specific groups that, you know, we inspect very carefully. One group that we actually studied very carefully over more than a decade are students at Yale law school.
[00:13:43] Ray: Wow. That’s a pretty niche group.
[00:13:46] Kariv: But this niche goal is actually unbelievably important. Let me give you, let me tell you why. You know, we all, for example, talk about the people that are sitting in the Supreme court, whether they are liberals, whether they are conservatives, many issues, which of course just look at the decision that happened last week.
[00:14:11] Ray: Many of them recently in the last two or three weeks, we’ve had a few major Supreme court decisions.
[00:14:18] Ray: And we saw some of the justices flipped so that, you know, there were typically more of a conservative background but they voted with the liberals. Okay. So, what does your research tell us about that?
[00:14:28] Kariv: What is, what is our point? These decisions have a lot to do with social preferences. Basically the welfare of one group on one hand versus the welfare of another group on the other hand. So, these nine judges that are very important in the US, actually, their social preferences are extremely important. Of course, they are interpreting the law, but they are interpreting the law in the lenses of their social preferences. Okay. Now, you know how many of the nine Supreme court justices are graduate of Yale law school and Harvard law school?
[00:15:14] All of them except Ruth Bader Ginsburg who basically she started at Harvard, but she graduated from Columbia because her husband found a job in New York as a tax lawyer.
[00:15:27] Kariv: So, we have to understand, you know, we live in a democracy but eventually a lot of the decisions are made by groups that I would call elite.
[00:15:38] Ray: Right. There’s not too much diversity.
[00:15:41] Kariv: Yes. And it’s, by the way, it’s not only in this country, but it’s also in other countries which can bring us to this paper about Tanzania that, that we can speak about. So, you can actually think that you know, the people that are actually, I’m going to make decisions, have preferences that are different than their constituencies. So, we did it with two important groups.
[00:16:02] One is Yale law school. The other people that are actually their altruistic preferences are extremely important, providers of medical care, physicians. Because physicians, you know, this is the only profession that actually there is an oath that you need to make that you are altruistic.
[00:16:24] Ray: Wow, really?
[00:16:25] Kariv: Yes. So, the social preferences of physicians is a, you know, especially during this time of the coronavirus. Um, you know, whether you wake up in the morning and you actually go to this hospital, you know, it’s your job, but there is more than this. You actually have to be altruistic.
[00:16:44] We did this experiment and actually we published the paper already years ago showing that actually the students that, uh, the medical students are actually not more altruistic, let me put it this way than the law students.
[00:17:01] Ray: That’s unfortunate to hear.
[00:17:03] Kariv: Yes, I thought so too. However, uh, this is not in a paper yet. We are just now finishing the experiments with actual physicians that actually have been on the job for, you know, a decade, two decades. And actually, they are much more altruistic than the general population. So, it might be that when you go to medical school, you know, your altruistic preferences are not shaped yet but after the years on the job, you learn something, you know, preferences change.
[00:17:40] I did not like sushi and now I cannot live without sushi. So, my preference changed, you know, maybe one day I will start liking classical music, who knows.
[00:17:51] Ray: Right. Well, I wonder how much of that do you think is generational, you know, did you control for like the ages of the participants as well?
[00:18:00] Kariv: You’re asking good questions. So, yeah, so we control for it. I don’t think it’s generational. We have people that really kind of fall, their rate is in the nineties, did the experiment and people were, you know, towards the end of their life, I would say they lose their altruism.
[00:18:21] They become, they become a bit grumpy. Let’s put it this way. It’s understandable.
[00:18:28] Ray: Yeah. Cause it’s understandable because you know, you probably, at that point you might be lonely. You might not have a spouse, a living spouse, and even for the younger generation, I feel like, I don’t know, maybe if you’re, when you’re a medic school, when you’re completing the survey or the study, you might be very stressed because you’re a med school student.
[00:18:49] And then you realize you don’t have to work 80 hours per week. You might have to work 60 hours sometimes if the hospital is short-staffed, but those 80-hour residency weeks are behind you. You know, I guess there are a few different ways you can interpret that, but the end result is if we do get sick at least in our minds, we can think that the people that are taking care of us are altruistic compared to the general population. Awesome.
[00:19:19] So the most recent paper that you wrote that came out, I believe it was last month, uh, was about a study that you did comparing UC Berkeley students to students at the top university in Tanzania.
[00:19:34] We talked earlier about how maximizing utility can affect decision making as a whole, but in your study, I think you’re looking at how that affected the economic decision making. And so, can you just elaborate on this experiment, what you did, and what the results were?
[00:19:58] Kariv: Yes. So, we talked about kind of what I would call elite groups. And, you know, here you basically see that the leadership is coming from schools like Harvard, Princeton, Yale, and Berkeley. In Tanzania, you know, they all come from the University of Dar es Salaam. So, you know, the president, the prime minister, they’re all graduates of the University of Dar es Salaam.
[00:20:24] So even though the Berkeley students and the University of Dar es Salaam students, they are very different. They are coming from different backgrounds. You know, they represent the same slice in their respective societies. This is the slice that we know from research in development economics, this is the slice that actually should get the economy going.
[00:20:49] These are the first decision-makers, second engineer. So, we wanted to compare these two groups of students that again, they are very, very different. However, they are the same basically parts of their society. And we did it in two ways. First, we did it in the standard psychology way by basically just giving them a standard IQ test.
[00:21:16] And secondly, we also, using the experimental economics we measured what we’ll call the economic rationality. Basically, whether they are maximizing utility function. And what we found is that there were huge differences in IQ scores between these two groups. Actually, the difference is so big that the top 10 percentile in Tanzania was the bottom 10 percentile in Berkeley.
[00:21:46] So if you actually think that
[00:22:17] What I found using our economic tests is still Berkeley students are more economically rational. However, the differences are actually very small. And there is a very large fraction of Tanzanian students that are actually as rational as the Berkeley students. So, it gives you a completely different picture of these two populations.
[00:22:45] And, you know, I think that this picture is extremely, extremely important.
[00:22:50] Ray: So, then what can we take away from this experiment that you did comparing the economic decision making of US leaders versus Tanzania? Do you think that a potential difference in maybe the GDP between some countries and others is because that the top students or the top kind of layer in their society maybe have a lower ability to capitalize on their utility?
[00:23:24] Kariv: Yeah. So, you know, this is a big debate in the social sciences, why some countries are rich and some countries are poor and, you know, there are competing explanations. So, you know, what is the first explanation, it’s kind of obvious, is that some countries have resources and other countries don’t have resources. So, it’s about resources.
[00:23:47] By the way, the case of Africa actually goes against it, will the countries that actually have the most natural resources are the most dysfunctional because actually there is fighting over these resources. Okay. So, but the first issue is resources. If the country has resources. Okay. The second is about institutions. And, you know, you need to develop institutions in order to have economic growth. In order to do business, you need institutions.
[00:24:15] So like, you know, for example, you need a code system, you need a tax system, you need institutions.
[00:24:21] So the first was resources. The second was institutions. And the third one, which is, I must say the most controversial is basically saying that in some countries, you know, people are smarter, I dunno, even alums will say they’re just making bigger decisions. And, our research will basically dispute this.
[00:24:42] Now, what are the important implications of this research? Let’s suppose that you are sitting in the world bank. And, uh, if you’re sitting in, if you are an economist in the world bank, you probably graduated from Harvard, the mighty Princeton, et cetera. And you’ll have a large pot of money that you need to basically invest in Tanzania.
[00:25:03] So, you know, one decision that you need to make is whether I’m going to make the decisions what to do with this money myself or I’m actually going to hand this money to the local government. And actually, the people in the local government will make decisions. I totally believe that the world bank doesn’t want to actually have a paternalistic view of Tanzania.
[00:25:25] Of course cooption is always a problem when you talk about these things, but you know, I’m sure that the people in the world bank, they want Tanzania to make the decisions for themselves.
[00:25:36] I research basically show is that they can. Maybe they aren’t graduates of Berkeley, MIT, and Harvard, but in terms of their ability and economic rationality, they certainly can. If you look at IQ, you will get a different message.
[00:25:51] Ray: I think IQ tests while they’re fun to complete, I don’t know how much they actually reflect upon our intelligence, to be honest.
[00:26:03] Kariv: I was actually in Tanzania and I saw this IQ test given. This IQ test is a multiple choice. And what I found very funny is that you know, people in Tanzania asked me, why are you giving us the answer? Are you trying to help us or confuse us? They’re not used to take a multiple-choice test.
[00:26:24] Ray: Okay. So, there might be an advantage if you’ve been exposed to this method of testing that’s not controlled for.
[00:26:31] Kariv: Exactly.
[00:26:33] Ray: Fair enough. Thank you for sharing some of your research with us professor. I think what I want to talk about next is just your career teaching at Haas.
[00:26:44] We talked about the pandemic, we’re recording here on the 1st of July and still somewhat under a quarantine. Obviously, your classes have moved remotely as with almost everyone at Haas and probably a lot of teachers, professors worldwide.
[00:27:02] What do you find to be most challenging about teaching remotely?
[00:27:07] Kariv: Yeah, I rather teach in the classroom but I wouldn’t say that I had any challenge. The only challenges that I bought myself, what I had to buy. This was the only challenge. I bought myself a whiteboard, you know, home, but this is a very small whiteboard, so I have to erase all the time. So, it’s like exercising. So, I’m more tired.
[00:27:32] Ray: Right. Instead of doing bicep curls, you’re moving the eraser.
[00:27:35] Kariv: Exactly. So, the second thing that I had to buy, I actually, because I wanted people to actually see my whiteboard and now it’s radio. So, you cannot see my whiteboard, but I can send you a picture.
[00:27:47] Ray: We can play it on the show notes. No worry.
[00:27:49] Kariv: Okay. Yes. Okay. That will do. I’ll send you a picture of my whiteboard. My whiteboard it’s, you know, it’s like these small boards that you give to kids that they can draw.
[00:28:00] Ray: I got it, right. I’m sure you have all the colors, right? The different markers.
[00:28:04] Kariv: Oh yes, absolutely. I’ll also show you these. And so, the biggest challenge I had to buy a camera, which is better than the kind of, you know, laptop camera. So, I had to buy it when the quarantine started and this was very difficult to find because everyone needed this camera.
[00:28:25] So, but after I found my camera and my whiteboard, I must say, you know, I miss, I miss the face to face interaction. What we are doing now, I’m teaching now, basically, we are taking a break, we are continuing the discussion, but it’s not the same because, you know, a lot of the fun of teaching adults, MBA students, is the interaction, but you know, we do what we can.
[00:28:50] And I think this was just fine.
[00:28:53] Ray: What have you found to be some of the better ways to engage students remotely? Because I get you, right. Like when you have, when you’re in person and the breaks, you can talk to students individually in small groups, but online, you know, usually during, even if you create breakout rooms during breaks, people want to use the restroom.
[00:29:15] They want to go walk their dog. You know, they want to get a drink. I’m talking nonalcoholic of course, but okay. We’ll have to leave that part in. What are some ways that you’ve found to best engage with students?
[00:29:35] Kariv: Okay. So, I actually think that the best way is doing it low tech and not high tech. I’m not breaking into homes and there is no hand waving. There is basically, let’s try to do what we do in class, just with a camera. Take the kind of old-fashioned whiteboard and basically take a pen and write on the whiteboard.
[00:29:59] And, you know, we pass the half of the game fuel because of them teaching over the summer and based at least on the mid-course evaluations. People love it. And I like it as well because I’m not sitting on my butt. I’m actually, you know, I’m standing in front of a whiteboard talking to the window and there are streets. I pretend to myself that there are people on the street.
[00:30:23] Ray: Yeah, you can meditate, exercise, and learn economics all at once.
[00:30:30] Kariv: Absolutely
[00:30:31] Ray: So, I think we have some listeners that are going to be in the class of 2023 incoming students. And I want to switch and talk about microeconomics, just the class. What are some key concepts covered in microeconomics?
[00:30:49] Kariv: The course is actually, I would basically think about the course less as my core economics. I would actually think about the course is actually using economic tools to provide you guidance into decision making. And this is, I think is what the course is all about.
[00:31:09] Let’s think about engineering. Suppose that I was an engineer and I told you I designed this bridge and I guarantee to you that I never wrote even one mathematical equation when designing this bridge. Would you drive on this bridge?
[00:31:28] Ray: Probably not.
[00:31:28] Why, because you will say you can only design a bridge using mathematics otherwise, who knows whether the bridge is actually strong enough. Now in managerial decision-making, I actually think that the more we use mathematics, meaning economic tools, we are going to build better bridges. So, this is the entire thing that the course is about.
[00:31:53] The purpose of this course is to give you the tools to actually make better decisions.
[00:31:58] Ray: One of the things I learned in the class that I took with, I think Jim Saley, one of your colleagues is the sunk cost. And so, you know, sometimes especially during this pandemic. Sometimes, if you pay for a monthly benefit at the beginning of the month and then we go into quarantine or shelter in place, you don’t get that money back but it doesn’t mean that you should make a decision based off of that.
[00:32:24] Kariv: Absolutely. Jim did well. If you’ll remember this, Jim did well. Absolutely. Absolutely.
[00:32:31] Ray: So, this year, this fall, we’re going to have this class remote for the first time in a while. How will the curriculum be different than years past?
[00:32:43] Kariv: Nothing will be different. You know, let me first say that every year is a bit different. What do I say is a bit different? I would actually say that you know, about 20% of the class is what I call optional topics. It’s the last 20% of the class. And during the semester, we kind of understand each other because, you know, we can do an infinite amount of microeconomics.
[00:33:10] But, you know, we have 20% that we are actually doing, you know, based on, I would say general interest.
[00:33:17] And, um, for us, business, as usual, is just that, uh, yeah, no, no changes whatsoever.
[00:33:27] Ray: All right. So, I know you also do some extracurricular work.
[00:33:31] I think one of the things that you do is work with their Berkeley research venture on X mobile. Can you share a little bit about your work?
[00:33:42] Kariv: Sure. So, you know, XLAB is the Berkeley social science laboratory. It basically uses the cost campus, but it’s located at Haas, it’s in the business school. And you know, before I became a department chair, I was also the director of XLAB . I was the faculty director of XLAB.
[00:34:03] We basically, instead of people going into an experimental laboratory, which is like a room with computers, we actually wanted to move the laboratory to the mobile. And now we are talking about the early days of mobile. Why? Because let’s suppose that I’m doing an experiment with you about your food preferences. It is one thing to do it with you when you’re all sitting in the laboratory after breakfast, but it’s another thing to do it with you. while basically I know from yourself that now you are going into a restaurant to eat lunch. The experiment will be that I’m going to give you a coupon for healthy food.
[00:34:45] So I want to see whether it change what you are actually doing. So basically, what XLAB mobile did, they brought experimental research into the field, into the real world, out of the computer lab, and into the point of decision. So, I know exactly when to actually interact with you. And, you know, this was a joint project of people that this was a lot of fun to build and I’m very happy that other people are now using it including students.
[00:35:16] Ray: Hmm. That’s so funny that you mentioned measuring these decisions at the point of impact versus asking someone. Because a lot of times people, you know, even if they know that they’re taking part in a survey or an experiment they’re not willing to admit they went to the store to buy cannabis.
[00:35:35] Right. Or, you know, maybe they might be underage. I don’t know, but, or they’re not willing to, you know, admit that they had three burgers and fries and a big shake, right.
[00:35:45] Kariv: Exactly. No, but by the way, if you ask me at 10:00 AM in the morning, Shachar, what are you going to eat at night? I will tell you a salad. When night comes…
[00:35:58] Ray: Right, right.
[00:35:58] Kariv: So this is what we have done. And, you know, with Xlab mobile, they were wonderful research done, including, you know, research on the Berkeley campus. Let me give you an example, Berkeley has a parking problem. Some parking lots are getting full, others are not. So basically, we did an experiment. People signed up.
[00:36:19] They have an extra mobile on the phone. Now I see you in the morning driving through a parking lot that I know that it will get full, I’m basically sending you, Oh, do you want to basically take $2 off your monthly parking permit and park somewhere else?
[00:36:34] Ray: What were the results? I mean, did we see a group that took the coupon and they have similar characteristics.
[00:36:41] Kariv: Absolutely. Absolutely. So, it’s all about incentives. So, the purpose of this experiment was to find the right incentives. For such data, we can actually get some people to go. Now, of course, who took a lot of these incentives, people that are poorer, students.
[00:37:00] Ray: Sure.
[00:37:00] Kariv: All of that, you have list value for their time. But yes, it works very nicely. And, we continue, you can think about parking in the city. That basically different places will have different prices. So, you basically know where there is high demand, there will be a different price.
[00:37:20] How can you know? You can know by basically…
[00:37:25] Ray: That is, that’s really interesting. You also mentioned that you are a co-founder of a startup.
[00:37:31] Kariv: Yeah, I can talk very quickly about the start-up and that’s fine. It’s also, no, I would not have done the start-up if I didn’t teach for Haas because it actually kind of exposed me to questions in the real world.
[00:37:44] Kariv: The startup is a FinTech startup, in the domain of financial advice. So, if you go to a financial advisor, they have a fiduciary responsibility to do what is called risk for filing. They basically need to know how risk-averse you are.
[00:38:01] What is the list? Yes. What is your risk tolerance? So, what is your risk appetite? The way that they will do things today is something like, you know, you’ll go to a financial advisor and they will ask you, how would you feel losing 20% of your portfolio? Terrible. Very terrible. Extremely terrible.
[00:38:20] Okay. This doesn’t mean anything, of course, these multiple-choice questions. So, we basically developed some games, graphical games that by the way that you are actually playing this game and the game involving trading off risk versus retail, we can actually measure your risk precision and given the model portfolios that the financial advisor has, we can actually match you what I would say scientifically mathematically to the best portfolio to you. And this startup, you know, it’s not what is called B2C; it’s B2B. And, you know, the largest financial institutions in the world that are actually using it under the hood.
[00:39:08] And, I must say that the only way that I actually thought about it was having coffees with MBAs. Otherwise, I would not actually, you know, I would stay in the golden cage of academia. The interactions with MBA students over the years gave me, I would say the courage to put one foot in the real world.
[00:39:33] So I’m really grateful.
[00:39:36] Ray: No, that sounds like a great story. Lastly, we want to wrap up with some lightning round questions. I can already tell this is going to be great. Lightening questions, lightening answers. You can elaborate a little bit, but, uh, so the first question, what are some new hobbies, if any, you’ve picked up while sheltering in place.
[00:40:01] Kariv: Okay, let me tell you something that I’m very proud of. So, um, you know, I grew up in Israel. And I was like all Israelis. I was in the military. So, you can imagine to yourself that I wasn’t very good shape, you know, something that’s happened to me, the vision that I heard of myself is me in my twenties.
[00:40:22] So I’m still in good shape, but that’s not to be the case. So, but, uh, the quarantine thing was actually very good for my health. So I improved a lot, so, I always say that in my years in the military, I actually did more exercising for a lifetime so I don’t need any more, but, you know, exercising is a flow, not a stock.
[00:40:52] The quarantine actually got me back to it.
[00:40:54] Ray: Well, you already told me that you write stuff on the board and have to erase it. So, I think your arms are fine, you know, that’s one less thing you have to worry about. Okay. What is the favored book that you’ve read for pleasure only?
[00:41:10] Kariv: It’s actually a book written by a Berkeley resident. The book is called The Undoing Project: A Friendship That Changed Our Minds by Michael Lewis. And it’s actually about the friendship between Daniel Kahneman and Amos Tversky. Danny won the Nobel prize in economics but it’s about the friendship and in some sense the academic journey that they took and you can see how no great research contributions you need to have the right minds, but you also need to have the right chemistry.
[00:41:40] I highly recommend this book.
[00:41:43] Ray: I think that’s the same author that wrote Moneyball. We had a guest on for who actually works for the Oakland A’s and so we were talking about Moneyball, so that’s a that’s really cool.
[00:41:57] Ray: And lastly, I want to ask you, what is your favorite vegetable?
[00:42:01] And the reason I say that is I actually read that in Tel Aviv there’s like the highest per capita of vegans than anywhere in the world, but you may or may not be vegan. Yeah.
[00:42:13] Kariv: I’m not vegan. Actually, grateful than great vegetables. I will tell you about my least favorite vegetable. It’s kale.
[00:42:24] Kale is just completely overrated. Basically, I’d rather eat grass than eat kale.
[00:42:31] Ray: Well, Professor Kariv, you’re throwing some hot opinions over here. No filter. I love it.
[00:42:40] Kariv: I hope I’m not offending Kale.
[00:42:44] Ray: I would say if this was five years ago, kale is super popular. Somehow. I think it’s lost its popularity to maybe avocados.
[00:42:53] Kariv: Oh. I love avocados.
[00:42:54] Ray: And other vegetables. Yeah, exactly. All right. Well, the last question for you is for listeners of the 2023 class, what would you say to them if they’re listening to this in preparation for your class?
[00:43:11] Kariv: I always say that classes at MBA must be useful but in order for things to be useful, they must be fun. And if you don’t, if you don’t have fun in the class, come and tell me. It won’t hurt my feelings. Don’t worry. You know, my self-esteem is so high so it’s impossible to insult so you can tell it to me.
[00:43:31] But if you don’t have fun, then there is no learning. There is no learning without fun.
[00:43:36] Ray: Right. One of our core pillars is confidence without attitude. So, it seems like you definitely have the confidence down and maybe they’ll find out about the attitude later.
[00:43:51] Kariv: They’ll find out, yeah. Hey, thank you very much. This was great.
[00:43:53] Thanks for tuning in to another episode of here at Haas. If you enjoyed our show, please subscribe to us on your favorite podcast player and give us a rating and review. If you want to hear more about alumni perspectives, check out our sister podcast OneHaas or you can subscribe to our monthly newsletter at onehoss.org, spelled O N E H A A S dot O R G.
[00:44:21] I’m Ray Guan and we’ll see you next time here at Haas.