Dr Vuk Vukovic, economist and founder of Oraclum Capital, joins Gene Tunny to discuss elite networks, their economic impact, and the future of democracy. Delving into his research, Dr Vukovic examines how political connections affect income inequality and corporate success. He shares his innovative Bayesian approach to predicting financial and political trends, offering a glimpse into his hedge fund’s methods. The episode also tackles the dangers of centralized political power and explores solutions for empowering communities and fostering trust in democratic institutions.
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About this episode’s guest Dr Vuk Vukovic
In brief: an academic and practitioner
Academic…
- Oxford PhD, LSE Masters, Harvard, Berkeley
- 5-year university teaching experience
- Published in top journals, published a book (@Oxford University Press) => Elite Networks
- Expert member of Parliament committee
Practitioner…
- Running a hedge fund in NYC, Oraclum Capital (ORCA), based on our scientific innovation in network theory
- Before that, founded two companies: market research consultancy & boutique rating agency
- Macro-based trader & investor for over 10 years (learning by doing: lots of mistakes, lots of helpful lessons).
Timestamps for EP263
- 0:00 – Gene introduces Vuk and his work on elite networks and Bayesian analysis
- 3:54 – Vuk explains how they use social network analysis to identify “super forecasters”
- 7:47 – Vuk discusses the performance of his hedge fund Oraclum Capital
- 9:29 – Vuk goes into more detail on their social network survey approach
- 12:54 – Gene and Vuk discuss Vuk’s thesis on how political connections contribute to inequality
- 20:21 – Discussion of Lina Khan and potential risks of Trump-Musk connections
- 25:02 – Vuk discusses how corruption and concentrated power can lead to poor economic outcomes
- 33:30 – Vuk outlines recommendations for decentralizing political power and re-empowering citizens
- 39:13 – Vuk’s final thoughts on the role of elites and the need for system design to channel their influence positively
Takeaways
- Elite Networks Drive Inequality: Dr Vukovic’s research shows that corporate executives with political connections earn significantly higher salaries, fueling income inequality.
- Bayesian Analysis Enhances Forecasting: Dr Vukovic argues his approach improves financial and political predictions by weighting opinions based on network diversity and historical accuracy.
- Centralization vs. Decentralization: Dr. Vukovic argues for reducing centralized political power to lower inequality and enhance democratic processes.
- Democracy’s Resilience: Whilst acknowledging current challenges, Dr Vukovic remains optimistic about democracy’s ability to adapt through trial and error.
Links relevant to the conversation
Info on Dr Vuk Vukovic:
Elite Networks book:
https://www.amazon.com.au/Elite-Networks-Political-Economy-Inequality/dp/0197774237
Oraclum Capital:
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Transcript: Elite Networks: The Hidden Driver of Inequality? w/ Dr. Vuk Vukovic – EP263
N.B. This is a lightly edited version of a transcript originally created using the AI application otter.ai. The transcript was then looked over by a human, Tim Hughes from Adept Economics, to see what mischief the otters had been up to and to correct some of the things they might have missed whilst splashing around in the river. It may not be 100 percent accurate, but should be pretty close. If you’d like to quote from it, please check the quoted segment in the recording.
Vuk Vukovic 00:03
So you mentioned Musk before, just to briefly return to that. So the danger here would be that he would use because he’s not elected, right, the Trump administration, Trump is so it would be a danger if Musk uses his political connection to get favorable business decision for his companies, subsidies for Tesla, subsidies for his other companies, or, you know, preventing regulatory inquiries into his businesses. So that will be something that has a potential danger in terms of, you know, exploiting the system to your benefit.
Gene Tunny 00:35
Hello and welcome to the show. This episode, I’ve got a great guest to tell us all about elite networks and his Bayesian approach to analyzing financial markets. It’s Dr Vuk Vukovic, PhD, CEO and founding partner of Oraclum Capital. Vuk, welcome to the program.
Vuk Vukovic 00:57
Thankyou, Gene, thank you for having me. Pleasure to be here.
Gene Tunny 01:01
It’s good to have you on you’ve you’ve been doing some really fascinating work it appears, you’ve got your own hedge fund, and that’s come out of your Bayesian analysis of, I think it’s social networks, isn’t it, and that informs your financial market analysis. Can you tell us a bit about that please?
Vuk Vukovic 01:18
Yeah. So the network analysis is kind of the underlying, let’s say, motivational factor. But there are two different things, right? One was so the book came out as a part of my PhD thesis from Oxford, where I did use sort of network analysis to kind of look at relationships between politics and the corporate world and how it affects certain economic outcomes, in this specific case, the impact of income distributions, right? So I found that people, so corporate executives that are more connected to politicians tend to have much higher salaries than same corporate executives that are not connected to political executives, right? And this causes a very significant increase of, it explains a very large part of the rise of income inequality in the West in the past 40 years. So that was one that was kind of the academic thing, whereas the whole fund was basically that started on a also an academic paper, but it was something completely different for us, of me, me and my two my two partners and my two colleagues back then now partners in the fund looking at specifically how bubbles, social media bubbles, help us better explain and derive better signals from people making predictions right? So we use this with elections, specifically in 2016 with the Brexit referendum and the Trump election in 2016 got both of them really, really accurately. And then again, Biden, later on, Macron and a bunch of other things, and the underlying so again, the underlying factor, the underlying mechanism, is network analysis, but we used it to try to figure out which people are better at making predictions. Right? Because in our surveys, when we do a survey, not every person is valued the same way. Some people are better than others, and we’re using network analysis to figure out which people are better. So for example, if you’re in a cluster and like an echo chamber, then you’re very likely to be biased. Right? Either, think of it, elections, right left wing bubble, right wing bubble. You’re only surrounded by like minded people. You only see one version of reality. You’re own, right? But if you’re more heterogeneous groups, meaning if your friends who you hang out with in social media, if your friends are some of them are left wing, some of them are right with wings, some of them are centrist, then you have a higher probability of being right about an election outcome, right? Doesn’t necessarily mean that you’re right, but you have a higher probability. So what we basically do is we weigh people’s opinions based on the probability of them being more or less accurate. That’s the whole the whole approach,
Gene Tunny 03:54
Right! Okay, and are you scraping this data from Twitter, from or X or various different social media sites?
Vuk Vukovic 04:02
Yeah. So we started on Facebook back in 2015 like in 2016 before, before the whole Cambridge scandal, after that, and Facebook was no longer an option, but so we continued on Twitter and LinkedIn, mostly
Gene Tunny 04:15
LinkedIn, Okay, gotcha. Yeah, that’s interesting. So, I mean, what’s what’s interesting is, potentially, I’m part of your sample, and so are listeners of the podcast around the world. So I think that’s fascinating.
Vuk Vukovic 04:31
Yeah that’s the idea. We want to get it as diversified group as possible, so diverse decentralized opinions. That’s that’s the whole point. I don’t want clusters. I want people from all around, doing different things,
Gene Tunny 04:41
Gotcha, and what’s what’s your acronym? Is it based on Bayesian? Can you tell us a bit about that, please. What’s that stand for?
Vuk Vukovic 04:50
Yeah so we named it the Bayesian Adjusted Social Network Survey. Bayesian adjusted is because we asked people two questions. The first question is, what you think is going to happen? For example, who’s going to win an election, or, in case of markets, where the market is going to be by the end of the week. And the second question is, what do you think other people around you think, what’s going to happen? Now, when you get to that second question, that’s where the Bayesian element kicks in, right? Because we noticed and we did this initially, when we we were trying out this methodology, we tested on students, all three of us, myself and my two partners were academics, right? I have a PhD in economics. My partners have PhDs in physics and computer science, and we test some students by asking them to predict their test scores. And then later we did with elections, again, an experimental setting, right? So we give some some of them a question, some of them we don’t give a question, the second question. And we notice when we give the second question, the question of, What do you think your friends around you are going to do? That kind of encourages you to go back to your previous question and reverse it, or, you know, and be more accurate that way. It’s it forces you. It’s kind of, you know, Bayesian and you have a prior posterior probabilities. You, you adapt, you update them. That’s the whole idea.
Gene Tunny 06:03
That’s fascinating. And as you get into this, how did you identify this topic, and who was your thesis advisor? And I mean this, I mean this is very original work. It’s sort of not the standard sort of thing economists would look at, at least as far as I’m aware. So how did you get involved in it, and who was your advisor on it, please Vuk, I’m interested.
Vuk Vukovic 06:23
Again this was done before. So the whole thing, the network thing, analysis for the Bayes on right, what I mentioned was done before I went to Oxford. That was 2014/15. I went to Oxford, 2016 So, and this was done by myself and my two colleagues. As I mentioned, one is a computer scientist, one is a physicist, and we wanted to publish this as a paper, right? We were aiming to publish it like Nature or Science, but once we saw how good it was, we decided not to publish it, and we decided to monetize it instead, like, let’s make some money out of this. It’s very precise, right? It gives us really, really accurate results for whether it was like testing on students or when we did actual elections, it was really precise. But the thing to answer your question, so my PhD supervisor was Ben Hansel. he was a professor at Oxford. Really great guy. I But the research I’ve done there is a bit different, right, that was focused more on, like, the political outcomes of, you know, corporate and political connections and economic outcomes of corporate and political connections and its impact on inequality. So that was a bit different. That’s where the book came came out from. But again, as I said, like the underlying the common factor is network analysis,
Gene Tunny 07:37
Gotcha and you’re Oraclum Capital. So where’s that based? And I mean, how is it performing? Can you tell us a bit about that, please, before we talk about your book?
Vuk Vukovic 07:47
Absolutely So Oraclum Capital, it’s a hedge fund based in New York, and it’s performing really well. So we opened the fund in February 2023. Before that, I did almost two years of testing it, I had my own account. I took $20,000 of my own money and brought it up to 54 in over a year and a half. And we were doing this in a newsletter. So people were following us, and I was literally posting like screenshots. I bought this and I sold it so as to get like credibility from people. And once that was that happened, so we decided to launch the fund in February, we started with about 2 million AUM, and by now, by November, 2024 we’re up to 25 million, where performance has been about 56% since inception, gross return. So net is about 45 something like that, net return per investors. So pretty, pretty good.
Gene Tunny 08:38
Yeah, yeah, yeah. And again, this is for, like, on your website, this is for accredited investors. So it’s not just for, yeah, for ordinary mums and dads out there. It’s for, you know, people with significant assets.
Vuk Vukovic 08:51
Yeah there’s a minimum, we’re raising the minimum from January 1, $250,000 and yes, you have to have a status of accredited investor. Again, it’s a hedge fund. So it’s not really something that is for the retail and average retail investor, but we are planning down the line to have an ETF potentially, and that would be open to retail crowd. But that’s a, again, that’s a long term plan.
Gene Tunny 09:13
Good one. Yeah, it’s a fascinating approach. So you’re looking at, again, we were talking about it before, looking at what people are thinking in you’re scraping all this data from social networks. You’re trying to identify the people who are good at predicting and what they’re thinking…
Vuk Vukovic 09:29
Yeah and it’s and it’s all about two things, about, like, your consistency, your consistent responses. So since we have the market prediction, and that goes every week, so we’re tracking people’s performance over time, right? And it’s also about your positioning in the network. So we don’t take any data, you said, scraping. We only scrape the connections of your friends, right? And we can see your who your friends are if they also come into the survey. So we take your whole network, but we only see if your your friends, who’s friends with you, if they also come into the survey, right? We don’t have any we don’t collect any other socio economic. Like, we don’t even collect the names of these people, right? We know some of them. We reward. We give them money, right? So every quarter we reward, it’s a competition that we run. So we reward the top 20 with $5,000 for the distributed across top 20 people. We’ll probably be increasing that in the years to come. And and the whole point is, since, so since we reward them. So some of them have uncovered that they are, in fact, day traders, and they’re like trading markets, so we know their names, but this is just because we pay them the prize. Otherwise, a lot of them are even anonymous in the survey, which is fine to us.
Gene Tunny 10:35
Oh right. Okay. So you’ve got a survey, and then you you figure out who in that survey, are the best predictors based on, yeah, I guess there’s their network and also their…
Vuk Vukovic 10:47
The position in the network is number one and the number two is performance over time, right? So maybe your position in the network is like, I place you in a bubble, but you’re actually pretty good, so your performance goes up, so that means we value your opinion more, right? Yeah. And vice versa.
Gene Tunny 11:00
Yeah and one way of thinking about this, it just occurred to me, I don’t know if I’m the I’m on the right track here, but you’re identifying super forecasters, in a way. And I’ve had Warren Hatch on the show from Good Judgment. He’s worked with Phil Tetlock on the Superforecasting stuff, which is just fascinating. I think he’s in New York somewhere. He’s doing, he’s doing great work. You’ve got a you’ve got a different approach. And, yeah, sounds, sounds fascinating.
Vuk Vukovic 11:25
I read Tetlock’s book somewhere over there, right? I’ve read it, and it’s, it’s really good, and I like their approach. What we, so, yes, we do call them superforecasters, but we basically call them also our best observers, right? So people who are best at observing the environment around them. So that’s the kind of the most valuable opinion.
Gene Tunny 11:44
Yeah fascinating. That’s good stuff. Okay, I want to ask about your book Elite Networks, because I think this is an interesting thesis. It’s one that, I mean, I’ve got, yeah, I’ve got some real questions about this, because, I mean, inequality has always been with us, right? And so we understand why a significant amount of inequality exists, because there’s a distribution of talents and skills and resilience or grit across the population. And so we have people who, you know, we’ve got doctors or specialists who work, you know, ridiculous hours and have lots of stress, and so they’re going to be more highly paid. Corporate lawyers as well. But your thesis, it seems to be, is that much of the increase in inequality, if I’m interpreting you right, or a large part of the increase in inequality, particularly among that top 1% like if we look at what’s happening with income and wealth data, we do see particularly in the United States, I guess in the UK, to a lesser extent, and in Australia, to a much lesser extent, we see that top 1% or top point 1% really pulling away. And your, am I right? Your thesis is that much of this is to do with political connections. Can you tell us a bit about that? Please.
Vuk Vukovic 12:54
Mmm, absolutely. So what you mentioned is, so I’m not bothered by, as you said, like the inequality between people based on, like, unique talents and difference, again, some people are on a global market, superstars, right? On a global market, most popular singers, sports persons, etc, it’s a completely different game, right? The demand for them determines their payoffs. But what I’m looking at is, if you look at the distribution within the top 1% or even the top 0.1% which is, as you mentioned, was for the past 40 years, the biggest driver of income inequality. Is this has been shown by the inequality literature almost unequivocally when you look at the distribution within them. So there is this political effect that hasn’t been researched that much, right? So I looked at that specific issue. So he had a database of about a million corporate executives and politicians from the US and the UK. So I was totally focusing on these two countries, because that’s where I had the data from. Not a lot of data exists outside, unfortunately, even though it would be great to see that as well. So I was looking at these people, and I was trying to make the connections between who’s connected to politics among the top corporate, corporate executives. I was only looking at board members, right so C suite and board members. And I found that if you look at within companies, right, if you’re a board member that is connected to a politician, I’ll explain how we measure connections. If you if you’re connected to a politician in the United States, that means you have a salary, an annual salary higher about $150,000 from 2000 from the year 2000 in the year 2016 in the UK, it’s about 90,000 pounds, which is a very significant effect. It’s a lot. It’s a big increase in salary, right, on average. And again, so you’re looking at the tail of the distribution, and you’re looking at differences between them, meaning that some people have a much higher salary because of their political connections. The way I measure political connections is simple. I look at people who used to work together. So if you were, you know, if you’re a corporate executive, they used to work in government, or the people that used to study together. Or, and this is the most fun part, if you belong the same societies, right? So country clubs or like charity organizations or think tanks or stuff like that. Again, it doesn’t necessarily mean that these people are friends, but you can get to each other very quickly, right? So maybe, you know, you and I are not friends, but we belong to the same group, and you know, if I need to get to you and your personal power, I you know, it’s very easy for me to get to you, because we won’t belong to the same group. That’s kind of the idea. And if you have this level of connection, it shows statistically significant that it has an effect on on the increase of top incomes.
Gene Tunny 15:36
Yeah, yeah. It’s an interesting hypothesis, and there’s certainly some evidence of it. I mean, they talk about the revolving door between Goldman Sachs and US Treasury, or something like that, that sort of thing. And in Australia, we seem to have a revolving door between ministers offices and then the government relations positions in the big corporates like Qantas. And that’s become a bit of a scandal over here recently. What I’m interested though, is, you know, there’s correlation and then there’s causation. So how are you confident that this is actually a causal thing, that the political connections are what leads to the higher income or the, you know, the corporate sort of success it was, you know, higher incomes, uh, versus the fact that, I mean, if you’re in a, in a corporate, you’re, you’ve got to deal with government, right? You’ve got no choice, because government wants to get in your business, right? So you, you really have to make those connections. Can you, could you talk about that please?
Vuk Vukovic 16:37
Absolutely, that’s why I’m looking at, that’s why I’m looking at the within firm effect, right? So I’m trying to look at within firms. So you’re comparing two people that are the same level, right? One and the only difference, so there’s, you’re comparing always similar individuals, same amount of experience. So you’re controlling for like things like age, experience, the fact that they both work in the same company that has, you know, a level of connections to politics to whatever extent, and then. But the only difference between the two people you’re comparing is one is politically connected, the other is not, right, and based on it, so that’s your source of exogenous, exogenous variation, shock, right? And so because of this effect, you will see if this person’s political connections has any effect on their salary. And I found it that does, right? So the question that you asked would be, if, okay, obviously, if you look at between firm differences and yes, in some firms you’re going to have much higher salaries, and others, you can see the super the so called superstar firm effects. So obviously, some firms are more connected to politics. Look at big tech, for example, right? So they’re an example of companies that used to be that developed their business models based on economies of scale of innovation, obviously, right? Your Googles, your Amazons, your your Apples, etc. So they have this level of innovation, and this is what built their market share, right? Economies of scale as well. But then at this point, right, at this point, the life cycle of the company from innovators, they’re turning into rent seekers, because now it’s a question of preservation. Right now it’s a question of regulators trying to disrupt their monopoly positions, which, obviously they do have monopoly positions, so regulators trying to disrupt them. So what do they do? They hire former members of government to lobby the government not to do those, the legislations right? That’s how the political process works. So in that particular story, obviously, again, the between firm effect is going to be huge, which is why I look at within firms. So I go to within certain Microsoft or an apple or whatever, right across the basket of several thousand companies, and you’re looking at these connected and non connected individuals to try to see if there’s a if there’s an impact of the political connection. And it turns out it is. So again, causality is obviously difficult to prove, unless you have like, firm experiments. But this is as close as you can get to a experiment, not out of experiments. We could call it a quasi experimental approach. It’s not a real experiment, but it’s something close,
Gene Tunny 19:01
yeah, yeah, that’s interesting. I mean, there are clear, clearly, examples through history of I mean, people who are well connected politically, and that helps them out in business. We’ll have to see what happens with Elon Musk and how long his bromance with the President Trump lasts and what what that does for his business. Yeah, yeah. And then you’ve had like, someone like Donald Rumsfeld who moved between, like he was, he worked for the Nixon and Ford administrations. Maybe he was defense secretary. Then he went to Monsanto, I think, and then back to defense. So then the people like Hank Paulson, who went from Goldman Sachs, the US Treasury. And…
Vuk Vukovic 19:42
Yeah I have him in the book, right? So I have his network is drawn in the book, so you can see these connections, you can visualize them, and it looks amazing, right? I also have, like, (inaudible) saying the same impact, or Bob Rubin, who was Treasury Secretary, and then Clinton, and then went to Citigroup, and then he. He was running Citigroup during the crisis, and then got, you know, he went out of the company, got 100 and something million dollars of a bonus during the financial crisis. So that’s the kind of level, right?
Gene Tunny 20:11
Yeah yeah. Actually, he’d be a really good example now that I think about it.
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Gene Tunny 20:50
Now, back to the show.
I’ve got a couple of questions first, just so I don’t forget it. You mentioned big tech and the abuse of market power that is probably occurring in some cases. What do you think about Lena Khan? Do you have any thoughts on her and what she’s been doing at FTC and the and do you have any insight into what’s going to happen with the Trump administration? I mean, I imagine they’re going to get rid of her, but do you have any thoughts on how she’s been going?
Vuk Vukovic 21:20
No, I haven’t, I haven’t looked at that in particular, but, yeah, I mean, there is, there is a specific danger, because Trump is an example of a person, of an individual who is, you know, embodiment of an elite network himself, right? So this is a mixture of politics and business into one person, right? Where he has a strong business background. He’s obviously using this. I mean, again, the reason he was elected was not because of that. He transcended that, right, this whole pop, he created this whole populist image that people are kind of looking to towards as an agent of change. And that’s all fine, and well, um, but you know, if you, if you’re, the danger would happen if he would use his political power to promote his own businesses, right? Or to kind of prevent the people in government to do their own, to do their jobs in regulating and supervising, etc. Obviously, government itself is corruptible. That’s clear. You know, I’m so my background in academic research was corruption research, right? So I know a lot about the topic, and I’ve done a lot of research on that. So you mentioned Musk before, just to briefly return to that. So the danger here would be that he would use is because he’s not elected, right? The Trump administration, Trump is so it would be a danger if Musk uses his political connection to get favorable business decisions for his companies, subsidies for Tesla, subsidies for his other companies, or, you know, preventing regulatory inquiries into his businesses. So that will be something that’s a potential danger in terms of, you know, exploiting the system to your benefit. You know, hopefully it doesn’t happen. We’ll see. But yeah, if you look at kind of countries where inequality is high, you would see events like this happening, right, where you have a group of like oligarchs around the person of power, donating money or whatever, and getting back very, very concrete. It doesn’t even have to be like necessary corruption itself, but it can also be influence, right, misusing political power.
Gene Tunny 23:19
Right yeah, and on that. Do you have examples in your book of particular countries?
Vuk Vukovic 23:24
Oh yeah, yeah so, so I use, I go for, for example, I typically pick the most, like the autocratic ones, where you have these relationships, like like Ben Ali in Tunisia. That was an example of a person whose whose family directly controlled over 20% of the country right by allowing you know who gets the contract gets to do business in the country. You had a similar situation in Suharto’s Indonesia. You had Putin’s Russia, Fujimori’s Peru, for example, or Tangentopoli affair in Italy, where you had the whole government basically going down on corruption charges. This whole system buying political influence was institutionalized like companies had no other way of doing business unless they would give a bribe, right, a kickback, to the politician. But sometimes, you know this, this thing comes from the directionality. Goes from the politician to the business sector, but often it also goes from the corporates to the political level. The Odebrecht scandal in Brazil and South America is a great example of that. This was covered by the investigation Lava Jato in Brazil, where they found out that this, this huge conglomerate of a company, this construction company throughout South America was responsible for electing presidents, electing mayors, electing parliaments, right, determining political decisions, and by channeling over $800 million in bribes and corruption across the across the continent in order to secure huge, huge deals from the south they were building all the major infrastructure projects throughout Latin America. This company was building that’s a great example.
Gene Tunny 25:02
Yeah, okay, and there is evidence, isn’t there that corruption leads to poorer economic performance over time? Is that correct?
Vuk Vukovic 25:13
Yeah absolutely because it, over time, definitely because it channels the resources from like, more efficient to less efficient means, right? It channels the resources to a certain particular group, and it doesn’t distribute them, right? So this is, this is why you have, especially in developing country, this feeling where you have economic growth but the majority of the population doesn’t benefit from it, right? So only a narrow group benefits from economic growth. And when, whenever this happens, you get popular revolts. This happened in 2014 but you had the uprisings in a lot of countries, from Brazil to Turkey to Bulgaria to Ukraine over exactly that, right? So they had, like, 10 years of 15 years of progress, and the population is still relatively poor, so they’re not seeing the benefits. Otherwise, when you have economic growth, it’s supposed to pull everyone out of poverty, or at least, you know, towards the middle class and towards upper incomes, right? You had this in Western Europe. You had this United States, right? Even though, you know, we can, we can talk about different levels of inequality and different levels of corruption, but when you have high corruption alongside high inequality, then the people feel this most prominently, and that’s where where you have negative social outcomes and potential negative political outcomes. That’s where you vote for populist candidates to deliver change, right? And yeah, that’s why, it can become, it can become dangerous.
Gene Tunny 26:33
Yeah, yeah, absolutely. And I see on your bookshelf behind you, you’ve got a copy of Why Nations Fail. I think it is by Daron Acemoglu, and
Vuk Vukovic 26:41
I have all of their I have Power in Progress, Narrow Corridor, all great books,
Gene Tunny 26:45
Right. And they won the Nobel Prize this year for, yeah, for their work on what they call, I think, extractive institutions. And I think that’s one of the themes of your book, is it? So are you concerned that if this trend continues in advanced economies such as the United States, UK, Australia, that we could end up on a on a path towards, I don’t know, what sort of future are you sort of projecting if this trend continues?
Vuk Vukovic 27:14
Great question. I mean, I’m have to in the long run. I’m always optimistic, right? Because I’m aware of all the all the issues, right? Obviously, I write about them, I research about them, and I definitely agree with the conclusions from the Acemoglu and Robinson books. They were my inspiration throughout my PhD. But if you think about the way I coined, the phrase that I coined in the book is something they call the trial and error democracy, right? So you have in certain times, and this last, it can last for a decade or more, periods of what you can call error, right? Go back to the to the west, in the 60s and the 70s, right? Think of the outcomes that you had just in the United States. Right? You had assassination of the President, Assassination of civil rights leaders. You had the United States losing a war in Vietnam. You had geopolitical shocks with Iran, the revolution with Israel, the wars, right? Huge oil shocks because of that. So geopolitical tensions all around, the Cold War at its peak, right? The Cuban missile crisis, all those issues you had domestically. United States, peak racism, the KKK, all those groups. You had economics, stagflation, right? You had high double digit inflation, low economic growth, unemployment being high. A lot of economists in the West saying it’s matter of time before the Soviet Union overtakes the United States. Never happened. Why did it never happen? Because, you know, a democratic system learns from its mistakes, right? It’s not automatic, okay? So it doesn’t happen. Oh, you know, magically something appears, and we’re all better. No, you need to fight for it, right? So the way that people are fighting for it, because they ask for change, they vote for change, they vote for differences. Right now, you know, the whole Trump election was also something that people were asking for change. They were seeing something is wrong. We need, we need a change in the system. We want something better. Inflation was high, our costs of living went up, our living standards went down. We need, we need a change. So, so again, it’s, we’ll see to which extent this happens. But it’s always a question of, you know, people fighting for a better future. Maybe you need to go for a period of a slump in order to go, I mean, this is, you know, a life cycle, if you think about it, right, nothing ever goes up in a straight line. We can look at the average across the past 200 years of, you know, ever since the industrial revolution, we have amazing progress, but it always goes in cycles, right? You had the 1930s and 1940s you had disasters, right? Disastrous outcomes, the terrible war and the 19th century, you had all these issues and crises and social revolutions, etc. But you know, as we progress, it tends to be less and less, let’s say, dangerous to the system in the sense of destroying it, right? If you look at the mid 19th century or the mid 20th century, you were thinking, Oh, this is the end of capitalism, right? But so far, we’ve lived through 15 ends of capitalism and no end in sight, right? So again, the system is there is a problem, obviously. And you know, it’s a good, good thing that we can talk about this, and we can discuss this in a democratic setting. This is the only way to kind of get a get ahead. In an autocratic setting, you have pseudo stability, right? You think that, ah, you know, look at Russia, look at China. Look at all these countries. They’re great, you know, prosperity, etc. But this, this is pseudo stability, because as soon as you disrupt the leader, the system tends to fall apart. And I think, I mean, China didn’t necessarily have that. I think they are going dangerous in that direction with Xi Jinping. I think that before before him, they had his this level of where you don’t have one person dominating the system, right? You have a collective which is fine, but you know, I’m not that optimistic about I’m more or, less optimistic on China than I am on the west, to be honest, despite all the problems that we see there and that they’re evident, right? The problems were evident. But that’s the thing. You’re always going to see problems in a trial and democracy. You’re never going to see problems in an autocracy until it falls apart, and then all the problems surface. This is like classic Eastern Europe after socialism, right? Everything was fine until all of a sudden nothing was fine.
Gene Tunny 31:22
Yeah, yeah. Gotcha. Okay. Well, sorry you mean in terms of everything was fine until nothing was fine, you mean up until 1989 is that what you mean?
Vuk Vukovic 31:32
Yeah, so, so, I mean, I come from Croatia, so we went through for socialism and right in Yugoslavia, certain level of and you can, you can go most countries, okay, Yugoslavia is a bit different in some aspects. But then, you know, you had a system that was growing really strongly throughout the 60s and 70s, but then in the 80s, complete stagnation. If you look at, and I talk about that in the book, if you look at 10 years, the last 10 years of socialism in 1980s you will see in every socialist country stagnation or even economic decline. So the GDP per capita in 1980 1989 went down in almost every single socialist country of the Eastern Europe, Eastern Bloc. The reason is because the socialist model simply ran out of steam. That was it, right, you could no longer replicate the results that you had in the past. And that created these tensions that eventually brought revolutions different ways in different countries. In Yugoslavia you had the war, in Poland you had the revolution in Romania you had the revolution, in Russia things fall, fall apart, fell apart in a different way. But, yeah, it came to its inevitable end. As I said, everything seemed fine and stable, right? Growing. But then, you know, when you’re inside the system, you see that things are really not a fight, right? They’re brewing.
Gene Tunny 32:44
Yeah, absolutely. I want to ask about just coming back to how we you know, what we do about all of this so in the summary of the book, it it says that this book argues that to lower inequality and prevent incentives of elite network formation we must, first and foremost, lower centralized political power and re-empower the citizens and the community by rebuilding trust and relying on the Democratic trial and error mechanism. So we’re talking about democratic trial and error mechanism. Can I ask, do you have any recommendations, specific recommendations about the types of things that should be done to lower that centralized political power and re-empower the citizens please Vuk?
Vuk Vukovic 33:30
So that’s the last chapter of the book, and that was, that’s the only chapter that’s not empirically backed, in sense that I didn’t do research on it, but it was kind of a natural extension of, you know, the findings of the book, right, the findings of the other parts. So I’m looking at things like, so the logic is, if political power is responsible for inequality, if you lower and decentralize power and give more power back to the communities and to the people, then you essentially lower incentives for the misuse of, you know of elite misuse of power. So my ideas, and I mentioned this in the final part, elites are not something that’s inherently negative, right? Even though I might portray it as such in the book, they always existed. They always will exist. And you have a lot of elites that are actually can be beneficial for societies, like, look at philanthropism, right? It developed a number of things throughout in our cultures. But then again, right? When you when they are incentives to misuse power, when power is highly concentrated within a single individual or a single party, that’s always bad, right? And so you want that. You don’t want the concentration of power. You want the dispersion of power. That’s the element of decentralization. So the way you do this, I mean, it’s, it’s not easy and it’s not simple. There’s no magic bullet here, right? There’s, there’s series of reforms that we can think about like so, you know, increasing transparency of government, right? In making sure that every citizen visits has a insight into every single check that the government ever spends. That’s one thing, right? Free, transparent media Absolutely. Media freedom is essential in that kind of kind of environment, doing things like, you know, I’m talking about introducing KPIs for politics, right? So you have a certain fiscal, budgetary constraints, or debt constraints or monetary policy constraints, and if the government, you know, exceeds those limits to a certain extent, and it has like, let’s say, six or 12 months to fix it, unless it doesn’t. Everyone loses their seat and is no longer viable to run for election. That’s a very strong commitment mechanism. So I’m talking about introducing mechanisms like these that will push incentives, not in the way of exertation of power, but in a way of, you know, making power more distributed, that’s the idea.
Gene Tunny 35:43
Yeah, absolutely. I think it’s a great idea. So there’s an idea from a colleague of mine, Nicholas Gruen, who’s an Australian economist who I work with closely, and he’s been getting a lot of attention internationally for his idea. It’s not his original idea, but he’s one of the leading advocates of it at the moment, for citizens juries, sortition, this idea, which I think is a terrific idea. And Martin Wolf, the FT columnist, he wrote positively about that in his book The Crisis of Democratic Capitalism, which is I think perhaps a companion book to yours. Uh, really, I mean that, you know, you similar, similar themes about, I guess that you know, he’s got observations on inequality and what’s driving that now, I guess this is where, this is the final question.
I want to make sure I understand this. So your hypothesis is that a large part of the inequality we’ve seen is due to these elite networks, connections to politics. How do you, how do you quantify that? Have you done a quantification, so how much of the inc…, the breakdown of the increase in inequality, increase in the share of the point 1% or the change in the genie coefficient, however you want to measure it, what proportion of that is due to the phenomena that you’re studying, versus, say that you know, wider access to markets through the tournament effect, or whatever you call it, through just being able to connect with the wire the whole world via the Internet and skill bias, technological change that David Autor has written about. Have you quantified this at all Vuk?
Vuk Vukovic 37:21
No, yeah. So again, I put a direct number, right? So $150,000 higher salary if you’re connected, compared to if you’re not connected, right? So that’s a very, you know, strong, strong number. And so high ends, a big number, right? But the thing is, so obviously, if you look at so what you mentioned, the tournament effect, the superstar effect. That is fine. That’s going to happen in a globalized world. It’s always going to happen. And there’s no problem with that. And my problem is when it happens as a form of (inaudible) of power. So to quantify in terms of size, I haven’t looked at that specifically, but we can. But I can say that this is if it explains 20% of the variation, it’s a lot, even if that’s much, and I think it’s probably even higher,
Gene Tunny 38:06
Yeah, gotcha, okay, I think that’d, that’d be a good question to ask. Yep, yeah. And there’s quite a bit of like, it’s a it’s an interesting research field, and it’s something I’ve got to be I’ve got to look at more. We’ve got a local there’s an Australian economist, Cameron Murray, who’s done a bit of research for this. He’s got a book called Rigged, which was Game of Mates, which is, you know, interesting idea. So, and, you know, Cameron sort of looked at how decisions regarding property rezoning and all that sort of thing is highly correlated or, you know, is you’re more likely to get a favorable rezoning change of use of your property if you’re politically connected than if you’re not. So there, there’s some interesting evidence there of of the role of politics in all of this so…
Vuk Vukovic 38:55
Absolutely, unfortunately, you know, again, that’s the thing, right? If there’s, if power is too concentrated, you know, you just have to get the one person to change some stuff. You’re going to do that, right? That’s, that’s the idea.
Gene Tunny 39:07
Yeah absolutely. Okay. This has been fascinating conversation. Any final points before we wrap up?
Vuk Vukovic 39:13
I mean, yeah, I think we, we kind of summarized it well. Your questions were great. So, so thanks for that. But yeah. I mean, kind of the main message, the main argument from the book, is like, again, elites are not necessarily bad, right? You they’re like, politicians. You have good politicians, you have bad politicians, right? It’s up to us to try to make the system design mechanisms of the system that can be they can channel their influence into something good rather than something bad. That’s the whole idea. You’re always going to have bad people around, right? My point is, let’s not, you know, let’s not. So even if you need to elect someone who’s bad, or, you know, a psychopath or sociopath whatever, people tend to be calling their, their their elected leaders, and they call them all of them psychopaths or sociopaths, why even give a you know, a sociopath so much power, let’s, let’s not give them, let’s not give them that much power. And it’s not a new thing, right? If you look at countries like, you know, in Scandinavia or Switzerland, power is not concentrated, that’s, that’s the idea.
Gene Tunny 40:14
Right, in Scandinavia, Oh, yep, in Switzerland, with the decentralization, yeah, yeah, gotcha, yeah. Really good point. Okay, Dr Vukovic, that’s been terrific. I’ve really enjoyed the conversation. I will put a link in the show notes to your book. I recommend people get a copy of it. And yeah, this is something I’m going to be having a closer look at in future episodes. So again, thanks so much for your time. I really enjoyed the conversation.
Vuk Vukovic 40:39
So did I it was really good. Thank you very much,
Gene Tunny 40:43
Righto, thanks for listening to this episode of Economics Explored. If you have any questions, comments or suggestions, please get in touch. I’d love to hear from you. You can send me an email via contact at economicsexplored.com or a voicemail via speak pipe. You can find the link in the show notes. If you’ve enjoyed the show, I’d be grateful if you could tell anyone you think would be interested about it. Word of mouth is one of the main ways that people learn about the show. Finally, if your podcasting app lets you, then please write a review and leave a rating. Thanks for listening. I hope you can join me again next week.
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Credits
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