Vish Hindocha: Hello, and welcome to another episode of the All Angles podcast. I'm delighted to be joined today by Professor Roberto Rigobon. Professor, welcome to the show.

Roberto Rigobon: Oh, thank you so much for inviting me, Vish. Thank you.

Vish Hindocha: Before we dive in too much, I'd love for you to give a little potted history of you. What are some of the things that have interested you through time, and how have you got to be focused on the areas that you're focused on today?

Roberto Rigobon: I am a macroeconomist. So my path is not a very usual one to end up working on ESG by being a theoretical macroeconomist. But actually, what happened is that, for a long time, I was concerned with measurement, which is a very important macro issue. I started thinking about financial contagion when the word financial contagion did not exist. That was the first set of papers that we were thinking about, how to develop methodologies to measure that. Then I moved to inflation rate, and I moved to inflation rate mostly because I thought that the inflation rate of the poor versus inflation rate of the rich were incorrectly computed. And many countries that had very low inflation rate that were actually very successful from the inflation rate point of view, those comments were losing elections. And so there had to be an explanation, and it was a bad measurement — is that they think that they're doing a good job, but actually a humongous proportion of the population was mismeasured and therefore they were suffering.

Interestingly, I developed a project together with Alberto Cavallo. In this emphasis for a measurement, we developed a project that was called The Billion Prices Project, where we used web scraping from the web to compute inflation rate, and at that time, actually, web scraping was very rare. This is the year. . .

Vish Hindocha: Noble.

Roberto Rigobon: Yeah, yeah. It was 2004, 2006. Not even computer scientists knew exactly how to do web scraping. We were teaching them how to do web scraping. That project turned out to be very successful, and I was actually teaching the students how to measure daily GDP in Brazil, which I was able to actually measure. And one student asked me if I have been measuring human trafficking, and I was completely shocked. I said like, "This is totally orthogonal, no?" So I had nothing to say, and I asked her, "I don't know what you have in mind, but I know nothing about human trafficking. So why don't we chat after the class?"

And we chatted, and actually we chatted for eight hours, and she brought her partner, and both of them were on law enforcement, and they both have been working on human trafficking. And when they explain me the horrors that existed there and the problems of measurement that existed there, I started working almost like nonstop on measuring unethical behavior. This is the way I call it today. But actually I started working on human trafficking, on child pornography, and what I did was to try to measure how these markets work. And by the way, the first thing I had to explain was that these were markets, and law enforcement has a very moral view about the issue. So they said they should not be a market. And I said, "Yeah, I agree," but that's not the point. There should not be a market, but there is one, and therefore you need to understand how the market works. . .

Vish Hindocha: Understand it, yeah.

Roberto Rigobon: . . . to understand your influence. And I started working then, and still today, every Wednesday, I devote a huge proportion of my Wednesday just to think about the problems. I work in a way that protects me from the horrors. So what they do is they describe the problem and I try to think about a methodology, so that's the way we work. And I tend to have one student every three or four years, a PhD student that is interested in working on this area. So last year, a PhD student from Harvard, we found a way how to detect child prostitution in massage parlors in the United States, and now I think that law enforcement in every state is using that methodology that we devised.

It is so interesting because once you start thinking about how to measure ethical behavior or unethical behavior of firms and societies, it's so incredibly important that it is hard to think about anything else. And in fact, for the last seven years, I have become someone that just measure CO2 emissions and things about labor treatment, a lot about labor treatment, about the impact of AI, education systems. So I'm thinking about how to measure these social interactions that we do. And what I mean we do is everyone, truly social policies done by every single human being. So of course, it's done by politicians and that create institutions. But NGOs and firms do. I mean, MFS, you do social policy with your actions, your management is doing social policy all over the place. And in fact, I think that management, for example, is the most impactful profession after politicians. With your values and the way you behave, you will affect hundreds of individuals, literally hundreds.

Vish Hindocha: You are right. Actually, I've described this before as the finance has a role to play, not the only role to play, but has a sort of Archimedean lever on which small actions can actually create huge impacts on what we call the real economy or the real world, which is a responsibility that we should take extremely seriously, and something that you've been very focused on. When the way that MFS first crossed your path, certainly I became more aware of you, and many of our listeners will be aware of your name is in attachment to the aggregate confusion project, and aggregate confusion — I'm going to call it 1.0 — of your original paper and thesis that was looking at ESG ratings and ESG ratings agencies. And so what are some of the things that you discovered as you began to really unpack what these rating agencies were doing, what their methodologies were, how they were being used, and what some of the shortcomings that you found in some of those methodologies?

Roberto Rigobon: The way I entered the ESG world was through the human trafficking. I said, "Well, somebody had to be measuring this." So I discovered by accident that yes, MSCI, Sustainalytics at the time, Vigeo, they were asking questions, and they were asking the question about human trafficking in the supply chain. I said, "Oh, that's so interesting." So I started talking to all of them and I said, "Can you tell me how you do this?" And then I realized that they were all measuring different aspects of human trafficking. And I said, "But wait a second. You should be sharing the data. You're all measuring different things. How you can call this human trafficking?"

So I am not going to be very precise about human trafficking, but let me give you an example that I did uncover on water, which is kind of the same spirit. So they were calling this water management, and I said, "Okay, so what are you measuring on water management?" They said, "Well, we are measuring whether or not you follow the law." I said, "Oh, that's an important aspect." Then the second one is, "Well, I am just measuring how much water you are wasting." I said, "Well, that might be related or not to the law. It's just completely different." And the other one was actually mentioning about pollution, and all three of these items had the same name, water management. I said, "You have to be crazy. These are truly not the same thing."

But the same happened with human trafficking. I don't want to be precise about a subject that is so sensitive, but then I realized, "Oh, I can actually work on the four days of my week on the other 64 possible attributes." So the first thing that the project did was to try to understand the sources of discrepancy. This is something that actually most people in finance knew before we wrote the paper. The main message of the paper is not that there is discrepancy. Correct me if I'm wrong, Vish, but I think it was known before our paper. Is that correct or not?

Vish Hindocha: I think it was known before the paper, I think, and since, it's sort of become common knowledge that there is discrepancy. Something that is inherently so intangible, subjective and hard to measure is unlikely to get there. But I think what you are driving to is actually there were other underlying implications of your work that I think have had really profound implications on how practitioners think about it. Because to be honest, there are still large sums of money that are managed in accordance with ESG ratings. And I want to be really careful here too. We are not saying that ESG ratings are evil or bad. We have lots of clients who use ESG ratings as a means to check that there's no controversy or that their reputation isn't likely to be impaired by the investments that they make. And I guess we're not necessarily arguing good or bad, moral right or wrong, but just effective, ineffective.

I think one of the underlying things of your paper was, okay, we shouldn't throw the baby out with the bath water, but we should be more discerning and more careful about how we're using these ratings to help guide what could be really, to your earlier point, really meaningful and impactful asset allocation decisions that start to move prices, markets, returns, risk for individuals and companies. So I think you're right. People had an inclination that clearly these ratings are just kind of a point estimate at a moment in time that's inherently subjective. But I think there was an undercurrent that was maybe driving the industry towards an overreliance on ratings, and I think the work was incredibly important because it came at a really important moment to force the industry to pause. But again, was that your experience too?

Roberto Rigobon: The issue is that I am surrounded by people that tend to think very deeply about ESG by selection. So people like MFS, you had a whole team to think about how to measure impact. I think that when I spoke to your team the first time, and when I spoke to your president, Carol I mean she thought that my paper was totally trivial. My intention was just to, again, measure why the discrepancy existed, and I think that that's kind of give an avenue about how to improve. In fact, your statement that many, many investors still today are automatically using an index to guide their investments, I think actually this is not going to change. I don't think that every investment shop will have the ability to invest in understanding all the underlying features. ESG is incredibly broad. It goes from electromagnetic field pollution to CO2 emissions to water pollution to biodiversity, and that's only pollution. And then you have marketing practices, product safety, you have governance.

So, truly, I don't think that one person can become an expert on everything. So we will need to rely on someone to aggregate that, to tell us, roughly, am I doing a good job or not? But what our paper, at least my intention was, on that paper was to highlight what were the sources. And I was hoping, as the name says, aggregate confusion, I thought that the biggest problem was how people were putting the indicators and then aggregating into one score. I thought that the biggest problem was the aggregation part, and I was wrong, not even close to being right, okay?

So the important result of the paper is that about 50, more than 50, so 50% of the errors and the discrepancy comes from the fact that two rating agencies, two data providers are measuring the same thing — or they think they're measuring the same thing — but they're measuring this differently. And then about 40% comes from the fact that some rating agencies disregard some indicators. I mean, electromagnetic field pollution is my preferred one because very few measure that. In Northern Europe, this is an issue. And by the way, this is also an issue in the United States. If I sell you a home that is under the power cables, you would pay less. So aggregation was only 5%.

So talking about missing the point . . . but all of our research that started from that paper and the paper has been very widely cited. That was to my surprise, because I thought that the only point that we were making was the decomposition. And it is almost trying to give an advice saying if the problem is measurement, then we have to work on . . .

Vish Hindocha: We have to improve the measurement. Yeah, and . . .

Roberto Rigobon: The other problems should be easier to solve. The next research is about how to fix in both dimensions. We need to fix it, by the way. Criticizing the fact that the measurement is wrong . . .

Vish Hindocha: Exactly. Yeah.

Roberto Rigobon: . . . is almost saying like, well, GDP is incorrectly measured. I am telling you, GDP is horribly measured, but we still need to learn to live with a measurement that is not perfect, that is kind of correlated with our standards of living, and we have to make decisions based on the imperfect measure that we have. This is not measuring the height of a person. We know how to measure that perfectly. Measuring the economic outcomes is much, much harder. And a lot of these are economic outcomes that are hidden. Discrimination happens every microsecond, but we measure only the extreme of that outcome. So when discrimination has been bad enough that someone complains or that . . .

Vish Hindocha: Or that it's manifest in some measurable way. I think that being comfortable in the things that we don't understand is a recurring theme of this podcast. This idea of whether it's embracing complexity or understanding the nuance or just . . . Unfortunately you have to scratch beneath the surface on a lot of these topics in order to really understand what is happening, but also understand the limitations of measurement. And obviously, as a fully active fundamental investment manager, we believe a lot in the power of judgment, as well as the power of data and analytics and tools. But that judgment and skill is also kind of incredibly important.

One of the things that's connected to how you think about outcome versus control that I know we've discussed before, but I was hoping you could share is sort of . . . I've often quoted you, Roberto, on we're often merciless when it comes to things that we don't understand. So not only do we need to get more comfortable in the things that we don't understand and understand that things cannot be measured perfectly. But we also have a slight behavioral bias against certain things and we can get very merciless when it comes to "ESG," and yet we're very forgiving in other dimensions of financial markets. So we hold ESG to a higher standard than we hold elsewhere. Any quick thoughts on how you think about this or any examples that bring that to life for you?

Roberto Rigobon: We're moving to a world that is very easy to polarize. So people complain that the world is being polarized. I tend to say that the problem is that we have become individuals that are very easy to polarize our views. So we're merciless on both directions, and you can see a lot of the conflict in the world that is happening today. We are holding the world to different standards when we don't understand, and this is a very human reaction. A more benign example is the way we talk about finance. I mean, every single financial institution tells you “The marketing material is just fantastic.” They said, “Well, past returns are not a predictor of future returns, but here are my past returns, so you can see that I was really good. But I want to remind you that you should not pay attention to this. By the way, I have a great Sharpe ratio, low volatility, very high returns, but that is not a predictor of the future.”

And then, actually, you people invest and you just completely screwed up and then people are fine. Almost every asset manager hires Britney Spears for their quarterly report. And when you start the quarterly report, she says, "Oops, I just did it again." It is so usual to miss the predictions. Imagine a ministry of finance. If we actually ask them to, you know, you have to have this budget, and then they actually have a plan, and they never make the plan correctly. Can you imagine a central banker? When has a central banker actually nailed 2% inflation rate? You know what? It's when they're moving from three to one at one particular day of the year, it actually gets to two, but they're never at two. So look at these central bankers. We allow them a humongous amount of uncertainty in the outcomes and leeways because we trust them first. It's an important aspect. We trust they're going to do a good job. And we also understand that this is horribly measured so we don't overreact. Well, I mean not everybody overreacts, but so the point is we try not to overreact to the means measurement.

ESG — we don't understand. We truly have no clue about how to measure it, for example, even the intention to emit CO2. We measure the CO2 emissions, and by the way, we measure very badly. These are horribly, horribly measured. And in fact, you can have a firm that is actually doing a legitimate effort to reduce their emissions. Imagine that they want to measure better because they said, "Well, the only way to fix the problem is to measure better." Typically, when you measure better, the number of CO2 emissions is going to go up, no doubt. I mean, if you are going to measure better, and you were doing estimates, you are very likely, very, very likely to look worse. So in order for you to improve, you have to look worse. But imagine that now every single financial institution decides, "Wow, that company is horrible. It just deteriorated because . . . increase the emissions. So let's — just don't give them a single cent." That doesn't seem to be the right solution. And we tend to act that way because we don't understand that much how this is measured.

Every time the situation just deteriorates slightly, we tend to overreact, but the risk implies that I just don't want to measure correctly. This happens to me whenever a company tells me that they're doing a training on sexual harassment. So they tell me, we just did a sexual harassment study last year, and we trained the whole population, and my reaction always is, "So has the number of complaints gone up?" And when they said "No," I said, "Well, your training probably sucked."

Vish Hindocha: Training wasn't very good. Yeah.

Roberto Rigobon: So it is kind of interesting because many universities do these courses, and I see the courses, and because I have been working on labor treatment for a long time, I see the courses. I say, "This is useless. This is complete and absolutely useless. This is responding to a lawyer, not responding to a problem." And therefore, in that sense, you don't see changes in the measurement. So very unlikely people are truly learning about how to detect, to understand where to complain, how to complain. You have not necessarily opened more lines of dialogue and so on. We are so afraid about the overreaction of looking bad that we prefer to do something that is not attending to the problem. And I think that that's a bad equilibrium when you think about it, because then you are stuck in bad measurement and everybody looks the same as previous years, so it's not very meaningful in that sense.

Now there are some areas in which I think it's okay to have overreaction, the things that I have a lot of control. So for example, sexual harassment is one that is difficult because I have control of who I hire, but not necessarily how bad the people are. I have control on what to do after the complaint, not before. So it is complicated because of that. But marketing material, I have the ability to control immediately. When you have the ability to control the material that you're showing in the streets, if you are saying something that is inappropriate or illegal or false . . .

Vish Hindocha: The repercussions should be severe, yeah.

Roberto Rigobon: And then I can be merciless. So it's so interesting because in ESG . . . so let's think about it. CO2 emissions are horribly measured, so I will be a little bit more lenient on that. But claiming that you are CO2-neutral because you bought carbon credit and that the carbon credit is kind of useless because that is a marketing material. So that one, you have perfect control, you see? So my point is once you know that the carbon credit that you purchase is of bad quality, and you should change your market material.

Vish Hindocha: Yeah, judge things on the actions, especially where they have more control. Back to your point on trust, creating a more constructive environment in which — we think about this a lot. And we've talked about constructive stewardship in this podcast series as well before and around how do we create an environment where we want to have an open, honest dialogue with the companies that we're investing in because we're interested in how they run their business over the very long term, and we think that all of investing involves trade-offs and compromise, as you rightly said before. Therefore, we just need to have a grownup conversation around the things that we can control, the outcomes and what the future holds and not be overly anchored to the past. I want to use that maybe as a segue into the more systemic thinking because sort of getting into things like intentionality. Any kind of brief thinking around that, Roberto, that you would share with our listeners?

Roberto Rigobon: On the immediate run, which is the ESG measurements, what I would do is to have a little matrix, actually, truly, that in one it says is like a little matrix three by three. In one, it looks at what do you measure? You measure actions, you measure procedures, and you measure outcomes. Okay? And statements, you can say you have four things, okay? Statements is obviously not too binding, in general. Actions and procedures are telling you what are you doing. An outcome is what the outcome, what is the result of your actions. And then the other side, you have the degree of control and understanding and quality of measurement, if you want. So if you have something that you do not control and is measured very badly, well, I think a statement is what we should be concentrating on. If you measure something badly, but you understand, you have ways to act when something bad happens, then procedures will matter. And this is a case of labor treatment. Labor treatment is very badly measured, but the question, a good company will be one that actually acts upon that immediately.

And when you measure something that is something that you have a lot of control and you measure properly, which is kind of marketing material, then I want to pay attention to outcome. So, by the way, we're trying to produce a mapping for every one of the rating agencies to understand which bucket are you filling. Because part of the discrepancy is not only the measurement is that this is intention. So you see actions and procedures are about the intention. I want to solve the problem. So these are my procedures in order to deal with the problem. So I want to give brownie points for that. You might not actually do it.

There's a different dimension. So this was my thinking and has been my thinking for a while, but talking to Carol, actually, she made me realize of another dimension of that metric. So maybe it has three dimensions, not only two, which is the horizon at which you pay attention. You see, as an economist, the solution of the long run should be the same as the solution of the short run repeated millions of times.

But that's actually how we macroeconomists model the long run. If you're going to do something that is bad in the long run, and you will be fine for example, then you should take an action today because you are anticipating the fine. And so economists, we tend to believe that people are hyper-rational, and therefore you will not enter a path that is unsustainable in any form. And unsustainable, treating women badly, will imply that at some point in time, they will not work for you, and then you have half of the labor force, actually less than half of the labor force because people that are educated, women tend to be more educated than men. So you are less than half of the labor force. That's stupid decision.

Discriminating and hurting people, I don't understand what is the value of that. So when you think about these actions that we take, it's not very clear why on earth we do them. Because as an economist, if you're hyper-rational and you look at 20 years down the road, it makes absolute no sense to do something wrong today in anticipation to what will be the consequences in the future. And by the way, I learned a hundred percent of this from Carol, is that okay? So just to give her credit, I want to make sure I give the proper credit, but she actually made me realize that that is not the case. That my thinking about that the long run is an infinite sequence of infinite periods of time is actually incorrect in practice. Now I say in your mathematical models, it might be true, but not in reality.

And she always said something that struck me, and it's kind of an advice that I give people. I said, what will you require of a firm to be willing to hold it for 20 years? I said, well, I have to assume what is going to happen 20 years from now. So you might be doing something today that is not illegal because there's nothing illegal about what you're doing, but your behavior will lead to a fine or a retribution or some repercussions in the future.

Vish Hindocha: Some kind of deterioration of your potential value or license to exist in the future.

Roberto Rigobon: Exactly, exactly. For example, emitting CO2 is not illegal, at least it's not illegal yet. I don't know if it's going to become illegal, but we do know that we need to tax that activity. That's for sure. And what I mean tax that activity is that we need to reduce the amount of CO2 that we . . .

Vish Hindocha: CO2, in some shape or form. Yeah.

Roberto Rigobon: We have to. So if you are producing a lot of CO2, well, maybe the cost is going to go up, and the revenues are going to go down. Now, it's not going to happen in the next three months, zero chance of that happening. The question is are you willing to hold that stock? Not for three months. Are you willing to hold that stock for 20 years? And if you are in that business of producing CO2, then maybe I don't want to hold that stock for 20 years. So that's a different dimension. So it's not about the control and the measurement percent, it's about understanding that these are long-term problems that we have. And again, all of these are long-term. Think about labor treatment, product safety, R&D, all the environmental aspects, all the governance issues are all long-term.

These are institutions that we want to change and keep for the foreseeable future. We don't change the governance of a company for three weeks. It's that, again, that's a committee. But if you want to change the governance, it's your thinking about the long run. So when you actually put all these things together, you realize that a lot of the decisions that we're making are not for the next three months. That's sales and revenues and stuff like that. You want to develop a relationship, you want to develop a network. That's long-term. And when you actually think about the long-term differently, it adds a different dimension, but it also, to me, adds a simplification to the problem.

This discussion about fiduciary responsibility is a short-term discussion. If you just take the regulator and you said, "My fiduciary responsibility is on the 20-year return," then you know what? A pension fund is going to look at that transaction, said, "Well, am I willing to hold that stock for 20 years?" And when you do that, it's much easier to prioritize and determine what is good or not.

Let me do the mapping with central banking. In the world of inflation, inflation is a super fast-moving animal. It's actually daily. And in fact, in our data, I can show you that inflation rate changes daily in every single country on earth. If I had a Japanese person that says inflation prices in Japan do not change day-to-day, and I show them something like in one week, 50% of the prices, in Greece, of course, actually change. It just happens to be that, on average, they change zero.

In inflation world, day is the frequency at which the measurement changes. But central banks talk about two years. They said, my forecast for the next three years is that we're going to reach inflation rate of two in three years and two-and-a-half in two years. Do the same for financial system. Our forecast is monthly or quarterly, that's my revenues and my financial statements, and I should be actually looking at multiply that by 700, and 20 years. If we were talking in the financial markets for these type of problems, if we talk about what happens 20 years from now, there will be no discrepancy between care about labor treatment and be my fiduciary responsibility. And I am taking CO2 emissions out in case...

Vish Hindocha: Out of the equation. Yeah, yeah.

Roberto Rigobon: Yeah, in case, in case we have someone that just think that it's only about CO2. No, no. If you treat people badly, that is going to be bad for your earnings, period. I cannot imagine there's no connection there. Is that clear? You don't have an evidence, but I cannot imagine this is they have no connections. And therefore, if you take a 20-year view, if you're treating people badly today, you will pay for that, not the next month, not the next two months, but you will pay. If you manage your company badly, and you are an irresponsible CEO, and you are just partying all the time, whatever it is, you are not paying attention to the business, it is conceivable that that actually has no impact in the short run, but that company will suffer. So truly, truly, truly, truly, what I learned from Carol is this beautiful aspect of the discrepancy.

Vish Hindocha: I think your point there on how time horizon, this is certainly how mine, I think MFS' thinking has been evolving a lot over the last few years, we dig deeper into the subject, like you said, we have the great luxury and privilege of investing in this space and having lots of people thinking about this in hopefully deep ways, but there's so many false dichotomies that we set up in the financial services industry. So ESG versus mainstream, like you said, all the trade-offs. But actually, if you hold the time horizon long enough, I feel like all of those disappear. Whether we're talking about single materiality or double materiality, if your time horizon is long enough, actually there isn't a real difference, right? Because actually, if what we're doing is underwriting risk and return for the next 20 years or 15 years and thinking about what that looks like, everything would feature as part of our . . . a common-sense approach to long-term investing that doesn't require you to do the kind of mental gymnastics or think about things in sort of isolated or siloed ways.

I hugely appreciate you bringing a different perspective to that. And again, also advancing our thinking. I know, and if Carol was here, she would give you tremendous credit for helping advance our thinking on some of those issues too. Roberto, just before we finish, what's the one thing that you would leave our audience with? What's the one thing that you would have them think about as often practitioners in this space? What's the one thing they should do on Monday?

Roberto Rigobon: Two things. One, ESG is important, so pay attention to it, but do not overreact. So make sure you don't overreact. Understand that this is a bad measure, and therefore it's noisy, let me put it that way, and therefore do not overreact, but that doesn't mean that we should disregard it.

Vish Hindocha: Unfortunately. Well, that's really powerful, and what a great place to stop. Roberto, thank you so much for your time this morning.

Roberto Rigobon: Thank you. Thank you for invitation.

Vish Hindocha: We really appreciate it.

Roberto Rigobon: And yes, we'll be back whenever you need me. I love it.

Vish Hindocha: Amazing.

Roberto Rigobon: Yes.

Vish Hindocha: Thank you so much.

Roberto Rigobon: No, thank you. Thank you.

Speaker 3: The views expressed are those of the speaker and are subject to change at any time. These views are for informational purposes only and should not be relied upon as a recommendation to purchase any security or as an offer of securities or investment advice. No forecast can be guaranteed. Past performance is no guarantee of future results.

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