Episode 012: Jean-François Mercure & Hector Pollitt
Mercure
Dr. Jean-François Mercure is Senior Lecturer in Global Systems in the Department of Geography at the University of Exeter.
Pollitt
Hector Pollitt is Head of Modelling at Cambridge Econometrics, an organization that makes economic data meaningful for policy-makers.
Their work shows how different fundamental assumptions regarding the finance sector and the nature of money will lead to climate-change models with radically different results. They talk to us about the political and ecological implications.
Transcript
Cameron Graham: My guests today are Dr. Jean-François Mercure of the University of Exeter, and Hector Pollitt of Cambridge Econometrics. They're the authors of a really interesting paper comparing different models that environmental economists use to predict the outcomes of climate change. They've found that the predictions generated by these models can vary widely, depending on the assumptions being made by the modelers. At a time when some policymakers are, quite sadly, not even convinced the climate change is real, you can understand the effect that contradictory models might have on achieving political consensus around climate change. They spoke to me from the UK in June. I hope you enjoy our conversation…. Jean-François and Hector, I don't know whether to be excited or depressed after reading your paper, so thank you for joining us on the podcast to talk about it.
Jean-François Mercure: Thanks for having us.
Hector Pollitt: Yes, thank you very much. Pleasure to be here.
Cameron: So, Jean-François, just to introduce you to people, to the audience; Jean-François, you're a Canadian climate scientist working in the UK. You told me you've been there about 15 years, you spent some time in the Netherlands as well. You work on complexity and innovation. How did you end up in this field?
Jean-François: Right. I've had an interesting trajectory, where I started off as a physicist and I gradually moved across disciplines to get to things that interested me more. So I did a PhD in physics at the University of St. Andrews in Scotland, after which I moved to work on climate change mitigation, because it interested me more. As a physicist, I moved into economics and brought with me some methods that I was familiar with from complexity science, and that's how I ended up mixing all of that together. But the field demands to study innovation because climate change mitigation is a lot about changing technologies. So ultimately, perhaps you could call me an innovation scholar.
Cameron: I've looked at the topics you've addressed in your research and there's an incredible diversity. You deal with energy, food, water, the finance sector, environmental modeling, technological innovation. I understand research on complexity, but this seems to be taking it to the next level, because you're dealing with so many things at once.
Jean-François: Yes. What complexity does as a field that's interesting is it looks at emergent phenomena that come about when you've got interacting subsystems, and this happens in any kind of problem, where you might have interacting components that together give rise to complex crowd effects that you might not have been able to predict by just looking at the subcomponents. And I think it's a classic case, I suppose, to look at the interaction between the components that are involved in the climate change problem, that complexity science brings some methods that can be used there.
Cameron: Okay, so this is more than simply complicated. What would you give as an example of something that's complicated as opposed to complex? Would a chess game be complicated as opposed to complex?
Jean-François: Yeah, you could take a car engine for example, that's complicated. It's got lots of components, but if instead you take an economy with people, and people interacting with each other, it can give rise to all sorts of effects when they influence each other. So if you've got a crowd effect with people all of a sudden doing something unpredicted, like when you have financial crisis for example, that's complex.
Cameron: Okay, thank you. Hector, I was looking at videos of both of you online, and in one of your videos, you said that your day job is to be in charge of the E3ME economic model. Can you explain what that model is about, roughly?
Hector: Yes, that is my day job, indeed. I'm an economist by background. I work for Cambridge Econometrics, which is a consultancy, but is in fact originally a spin-off from the University of Cambridge, so very much with an academic background. I joined the company and was put onto working with the E3ME macro-economic model, which, it's a global tool that splits the world up into 60-odd regions and has 40 roughly sectors in each region, so very highly disaggregated representation. That was about 16 years ago I started, so I've been here a long time, and over that time I've seen the model evolve and be used for different types of applications. But along all that period, we've looked at the interaction between the economy, and the energy systems, and the climate. The model acronym E3ME actually stands for that. The three Es are energy, environment, economy, and the last ME part stands for macro-econometric, which sort of reflects the Cambridge tradition that the model is based on.
Cameron: How many people are involved in producing this stuff? You must have the group right in Cambridge, but then you must have feeder organizations of some sort.
Hector: Yeah. Originally it was a team of essentially one, just me, but over time, as the models become more widely used, have developed a big team around this of 12 people at Cambridge Econometrics who are working with the model pretty much on a day-to-day basis. So that could be just looking at the data perhaps, or doing some econometric estimation, but a large part of it is applying the model for the clients, for the company. Now externally, we do have a wider team, as well. Of course, Jean-François is an important part of this team. We also collaborate with other academic groups as well; notably our friends at the Open University in the UK, who do the climate modeling that attaches to the economic and innovation side.
Cameron: So your clients are nations, corporations?
Hector: It's a mix. Generally, because the model is designed to answer policy questions, it's typically governments or government agencies that are involved. And here in Europe, a lot of environmental policy comes from the European Union, so the European Commission is a major user of the model results. But we also do work with some UK government, and other national governments as well.
Cameron: The paper that I want to talk to you about, which is drawing on this model, is called “Modeling innovation and the macroeconomics of low carbon transitions: theory, perspectives and practical use.” I'm given to understand that this paper's had a tortured past before it finally reached publication. Could one of you describe what this went through?
Jean-François: Yeah. Well first, this is a study that was commissioned by the European Commission in 2016. Because the Commission uses different types of models when they commission an impact assessment for informing what would be the implications of policy choices they might take, they get different results from different types of models. So they were asking us a question: "Why is that? We can't just have contradictory outcomes all the time." And so this was commissioned, and we did the work. We could narrow down exactly why this is the case, and that satisfied the Commission. But then they encouraged us to publish that in the journal literature so that it could have wider impact, further out in the world. Notably in North America, for example, people might not read reports from the Commission. And being encouraged to do so, we were quite enthusiastic, but it actually took seven journal submissions before we got an editor who'd be interested in looking at it. Not that it was rejected by peer reviewers, but really people thought, "It's interesting, but not for us." Everybody said the same, and nobody would want to be involved somehow until we were giving up and met an editor in person, and talked, and she encouraged us to submit to the journal Climate Policy, which I think is really an excellent journal.
Cameron: Yeah. Yeah. That's amazing. Do you think that the reluctance was because it is critical, or is it simply that it's at almost too high a level? I know that one of the issues we struggle with in the academic community is things like replication studies, where people review the work that other people have done, and try to make sure that our discussion around papers is as solid and as clear as can be. There's always this push to just publish new studies, new studies, new studies. Your paper is kind of stepping back from that rush to publish new ideas, and looking at the ideas we've got, and whether we're actually making sense of them properly. And I don't know that many journals have a real appetite for that.
Jean-François: Yeah. I think the issue here was a lot to do with the fact that this challenges existing theory in two major branches of economics at the same time. In fact, there's a conflict in doing this. People encourage us to do it, but they don't want to be involved with it.
Cameron: Yeah, you go first, I'll hold your coat. Let's fight them, I'll hold your coat. So to do a paper like this, you've got to have a fairly comprehensive set of talents. I know you've got a number of co-authors, maybe you want to give a shout out to them if you could, since they don't get to be on the podcast today.
Jean-François: Yeah, so the Commission, when they work with models, use our model very often, and the model from the team, from the National Technical University of Athens in Greece. These people have worked with the Commission for many, many years and they've done excellent work over the years, and they are an alternate theoretical part of this theoretical spectrum compared to us. So it was good to have the open-mindedness to really work together, for them and for us, and to be able to really tease out what the reasons are for our respective models to disagree, and to be really open-minded and not just saying "My model is right," but to say, "Well, actually both models have merits," but they are different. They are both, in a way, wrong, they're both right. And so yeah, I really was very happy to have the chance to be able to do that with them.
Cameron: So you're dealing with this really complex interaction in things around climate change, and the way they're modeled, and the way we analyze the results of those models. There's this fundamental transition that needs to take place from the oil-based fossil fuel-based energy sources that we've got now to new technologies. That's that innovation part of your work that needs to come into place. We're going to have to have better solar energy panels, and batteries, and wind turbines, and stuff like that. At the same time we have to let go of this huge investment that we've made in fossil fuel technologies, everything from pipelines to the family automobile. So your question was about the assumptions in these models to be made about the role of the financial system in all of this. Is this to do just with funding innovation? What is the role of the financial system? Can you characterize what you're looking at there?
Jean-François: Well, okay, so the role of finance in this is just like any other sector of the economy, there needs to be finance put forwards for there to be expansion and development of industrial activity. When you have a large transition, like we're contemplating for the energy transition, what's challenging there is that it's possible that some of the things we've invested in stop being used and become useless, while other things are needed instead. Now this could mean that some people could lose money and other people could make more money. Such a transition is never very peaceful. So the role of the financial sector is really to enable things to happen in the economy. And if we don't understand how the financial sector works, or if we have different understanding of it, we will project different things out of the models that we have. And this is really what the paper focuses on, because if we don't improve our understanding of how finance works ... and I have to say finance is an extremely complex system, it's an enormous network. We can't even map it out completely, it's so large. And what happens in there, we don't really understand it. Now we've had the financial crisis in 2008, and we still don't really fully understand what happened then. So we can't expect then to fully understand what could happen as a result of a very deep transformation of the energy system.
Cameron: The financial crisis in 2008, as I understand it, was primarily about the housing bubble in the US; as more and more mortgages got financed on homes that were not necessarily worthwhile and as the ability to repay these mortgages began to fall apart, you had this pyramid of financial instruments resting on top of this, and as long as everything was diversified across a completely random set of homeowners, then there was a fair amount of stability in the system. But you ended up with these correlations of houses going underwater in their mortgage, because as one person can't repay their mortgage and their house gets foreclosed, suddenly the value of the homes around them on the same street go down, and you end up with this ripple effect coming out from there. And it undermined the whole foundation of the financial system. You had all these derivatives that were built on top of it, so that bubble in the housing prices themselves also had created a bubble in the finance industry around these derivative financial instruments that were built on top of all these mortgages; the mortgage-backed securities and stuff. So you talk about there being a carbon bubble; you mean that in the same way that we saw a bubble in the housing market?
Jean-François: Well, yeah to some extent. When you have a bubble in the financial sector, what you have is perhaps excess investments in particular things that might not deliver in the way that they're expected to deliver, in terms of profits, according to those people who've invested in their business plan. So if, for example, in the fossil fuel sector we invest in drilling, and extraction capital, and transportation pipelines, and tankers with a scenario of future demand in mind that is much higher than what turns out to happen in reality, what is realized, then we would end up with excess capacity and we could have any time a correction of asset prices, which would have ripple effects across the financial sector. That would be bubble scenario. Now, how we think that may be the case is by simulating what we expect to be the future demand for fossil fuels, according to how technology is currently changing. The trajectory that we see in technology means that we've become much more efficient than we used to be with the use of fossil fuels, and we are starting the transformation towards a low carbon economy. In some areas, it is already ongoing. Therefore, we could reasonably expect that the demand for fossil fuels could change drastically. Then it depends who believes what the difference might be between the capacity we're investing in, and the capacity that we're going to need in the energy sector in the future. Of course, if we have excess capacity, then you could expect there to be financial losses.
Cameron: To use a Canadian analogy here, what I have in mind when you describe this is someone trying to step from one canoe into another, and it's a precarious business to stand up in the canoe at all, let alone try to get to another canoe. As the finance industry invests in new technology around solar panels, wind turbines, whatever, all the renewable energy stuff, they're hoping that's going to pay off big time. That's why they make the investment. But the problem is that those very technologies are going to undercut the value of the investments that the finance industry has already made. So the value that's underlying this financing of the new technology could potentially collapse to some extent underneath it, as the underlying assets that the banks are relying on are no longer there to back up the credit money that's been erected on top of them. Does that oversimplify anything? This is a podcast, so I need to simplify things so that I can understand them, but tell me if I'm oversimplifying.
Jean-François: No, I think that's quite right. The problem in the financial sector is expectations, and people's belief can change instantaneously. As soon as it's changed, the values change.
Cameron: Ah, okay. So this is not just a matter of the rate at which we physically build up the capacity for renewable energy, and physically wind down the capacity in the fossil fuel sector. It's about changes in beliefs, which can happen much quicker.
Jean-François: Well, it's a mixture of both. But of course, you've got all sorts of different people in the financial sector investing in all sorts of different things, and they believe different things. Now those people investing in the fossil fuel sector believe there's going to be return there. Those people, people investing in renewable capacity also believe there will be profit there, and at some point it's possible that somebody is wrong. It could well turn out that there's too much investment on both sides at the same time, or there's overcapacity developing, just because people haven't really communicated carefully or they're competing, they don't know what other people are doing, and because they expect there to be profits, they invest. And on the day when they realize perhaps they were wrong, then the correction makes that some people will lose money.
Cameron: Hector, maybe I can bring you in on this. I'm not really clear on who's got the expertise in each of these things, so you can bounce the questions around, but I'm interested in the global political implications to this, because not everybody, not every country, is invested in fossil fuels in the same way. Some are kind consumers and some are producers. And so, if there is going to be any collapse in the carbon bubble, it's really going to affect countries differently, which is going to change power dynamics at the international level.
Hector: Yeah, I think that is definitely correct.
Cameron: I didn't think of that myself. I got it from reading your stuff.
Hector: I think credit where credit is due. When we're doing our modeling, we often get asked: What are the global impacts of the transition? And the global impacts, in relative terms, tend be quite small, and GDP goes up or down by maybe 1% compared to a baseline case without the transition. But what's really important is the distribution of the impacts. And we always see some countries gain, some countries lose from the transition. Now, we get asked quite often: Is it developing countries or developed countries that gain or lose out overall? In fact, that's not really the right question. The right question is related to who has the assets here. So we see very consistently in these scenarios, energy exporters are the countries that lose out, whereas energy importers, including Europe, can benefit overall. So I'm afraid we're sitting on opposite sides of the fence here, as Canada is one of the countries that could be severely affected.
Cameron: This is not going to go down well with my Canadian listeners. Our lifestyle depends on the fossil fuel industry, I'm afraid.
Hector: Yes.
Cameron: The first part of my kind of trying to grapple with your paper, which is this wonderfully rich paper ... it's so interesting to read, but for me to try and make sense of it, I'm trying to get everything to line up in a more linear fashion, even though it's a very complex model. The first part of it, to me, is letting go of the old investments in the fossil fuel technology, which Canada is heavily invested in, as are the States and countries in the middle East. But the next part then is: How do we understand how the development of new technology takes place, and what the role of the finance industry is in that? Because your focus is on how we understand the role of the finance industry, and what our assumptions are about that. So what is the role of the finance industry in this invention of new technologies? Do we not just simply have a whole field of rugged individual scientists, Thomas Edison working in his lab late at night, to come up with these ideas? It seems that there's a model of investment here that is quite different at a much more massive industrial scale.
Jean-François: Do you want to talk about this, Hector?
Hector: It's an innovation question, that's your area.
Jean-François: Okay. There are two views on this since a long time in economics, and economics just can't reconcile the two tracks; there's like two theories of economics. In one of them, you've got entrepreneurs wanting to improve their companies, and their production processes, and their efficiency. They know they will make money out of this. They borrow money from the financial institution, and then make an expansion or an improvement, and then generate return on this. If there are more good ideas in the economy, there'll be more borrowing, and therefore, there'll be more money that's created by financial institutions to make this happen. We know in economic history there are periods where there's less innovation happening, there's just less money around, and there's less GDP growth, and there's less sectoral growth, and less prosperity, and more unemployment. And there's other periods, when there's massive booms of expansion in technology and innovation, and these periods lead to a lot of prosperity. But in the ultimate spectrum of economics, area of the spectrum, you have another theory that contends that finance that is available for investment in new technology is allocated, is a part of total income of the country, and then becomes allocated between the different possible activities. Some people demand more, some people demand less, and if some people demand more than usual, other people will have to give up on the amount of finance they're getting. Now, depending on which one of the two you choose as a theory, you get absolutely opposite impacts for expansion in innovation. On the one hand, if you've got more innovative activity, you will have more income around the economy, while on the opposite side of the spectrum, if you have more investment in innovation, in R & D, you will have less income overall. Although perhaps you might have more in the future, because that would improve productivity, but at the moment where the investment happens, there will be less economic activity.
Two fundamental models (Mercure et al. 2019)
Cameron: So it's about whether the money is a scarce resource, basically?
Jean-François: Effectively. Yeah, exactly. Yeah.
Cameron: I've got a copy of your diagram that you had in your paper here, about these two different models or cycles. One is what you call the demand-led model. That's where the entrepreneur recognizes that there's this demand in the market for this, that could be satisfied by this new idea; goes off, borrows money, comes up with the solution, markets it, and then that generates cash, which then feeds back into the finance system, and you just keep cycling around. The other one is the supply-led one, where it's about basically the allocation of our limited financial resources between consumption and saving. So that second model, the supply-led one, is good at modeling equilibrium conditions; that supply and demand come together and they meet in the middle, and you end up with this nice, relatively stable equilibrium. The other one, the demand-led one, about entrepreneurs and innovations, this is the Schumpeter kind of a model. This is non-equilibrium economics. Although they sound like you're just talking about money, and borrowing, and saving, and stuff like that in both cases, they're really radically different ideas of what the finance industry is going to lead to. Is it going to lead to stability and equilibrium, or is it going to lead to the possibility of expansion, or potentially, I presume, retraction as well? So it's a very different mindset behind each of these models or cycles.
Jean-François: Yeah, absolutely correct. Yes. Precisely. It's the libertarian view that has the economy constantly changing and evolving. And this is also the tradition of economics that sees the great waves of innovation, we're going to make history. Meanwhile, in the equilibrium side, you have most of current economic theory and the models there looking at how markets equilibrate themselves across the different goods and services.
Cameron: This is like two schools of thought in economics. There's a characteristic way of modeling stuff in one version, and another characteristic way of modeling things in the other. Are they using the same underlying data?
Jean-François: Yes, they could do, because if you compare us with the Athens team, we have very, very similar models, partly because the development history is tied to questions from the European Commission, and therefore, they are the most similar you could probably find as a pair of models, and the results are typically opposite. I think it really elaborates on this.
Cameron: Right. Hector, you know a lot about these models. Maybe you can describe in a little bit more detail what's in these models.
Hector: Yeah, so just to turn on the data first. And there is, I think, one important difference in the data requirements in that the non-equilibrium models tend to look at changes in data over time, so time series of historical data, because they are looking at the dynamics and the changes from one position to another in the economy. So they tend to need longer time series of data to operate. Obviously, I fully agree with the discussion that the models are coming from different, and in many cases opposite, backgrounds for how they work. I think we should say it's very positive that policymakers are applying both types of models to answer the same question, and are actually getting useful information out of that. When I first started doing this 15 years ago, we ran two models side-by-side and we if the two models produced the same results, then the response was, "Well that's a waste of money. Why did we do that? We could just have used one model," because if the models produced different results, they'd like that even less. So there's a bit of a hiding to nothing on that. But now we're seeing more recently, that policymakers are trying to get additional insights from using the two tools to see when one might be more appropriate than the other rule was, what they can learn from the differences. So yeah, on a day-to day-basis using the models, because they're used to answer such a wide variety of questions, it can be absolutely fascinating work at times. A lot of our time, I have to say, is on maintaining the models, so updating the data, estimating more parameters, and getting the equations to solve. The way the model works, it's a simultaneous set of equations. It just takes one equation, knocks us off, and the whole system comes crashing down. So at times it can be an incredibly frustrating experience, particularly when you run a model year-by-year up to 2050, say, and then in 2049 it breaks down and you have to start again, right from the beginning. It can be a very soul-destroying exercise at times. But I suppose the rewards-
Cameron: These are computation intensive. How long does it take to run a model? Are we talking a few minutes, or a few hours, or what?
Hector: Yeah, it's about 15 to 20 minutes. I can see on the video, Jean-François laughing, because he knows what I'm about to say. Before we integrated his work with the rest of the model, it was a lot faster.
Cameron: Holding up the team are you, Jean-François?
Hector: Yeah. Unfortunately the more complex and the more dynamic the system is, the longer it takes to solve in the computer.
Cameron: Yeah. Let's just look a little more closely at the role of the finance sector here. You guys have used this phrase "crowding out" in the sense that if you've got a pool of money and people want to use it for a particular kind of investment, for instance, in the fossil fuel industry, then that money is not available to use elsewhere, so we've used up our supply. Is that just the case with the equilibrium model, whereas the non-equilibrium model, the banks just generate more debt finance money?
Hector: Yes, that's right. This is a finding that came from about five or six years ago, when we were again doing a model comparison exercise for different sets of results. In the policy paper the European Commission said, "What is it that's driving the differences between the two model outcomes?" After the discussions we had with the same group in Athens that Jean-François was talking about previously, and we zeroed in on finance as being absolutely critical in this sense, and the supply of money, whether it's fixed or variable, and the crowding out that comes with that really is a defining feature of the differences.
Cameron: I'm not at all an economist, but I do try and make sense of what you're writing here. In your paper, you talk about these neoclassical equilibrium models that assume that the financial capital is fixed. And if you willfully print a whole bunch more money, all that does is divide the actual value of the money by more bills, so it doesn't change the value of the money that's out there. And the same thing, in terms of inflation. As prices go up, everything just trades off, and you end up with no net effect in these models due to inflation. So the money and inflation just drop out of the model as being important factors. I find this really hard to wrap my head around, because everything I read in the news about what Mark Carney does, or whatever, is about the money supply, and whether it can relax or restrain the growth of money in the system. So I'm confused here, help me out.
Hector: It's quite incredible actually, the amount of discussion and the amount of misunderstanding about how the money system works. And even, as you say, that so many economic models do not seem to include money in them at all, other than the unit of measurement, is an extreme simplification overall. In terms of the central banking, yes, absolutely the manipulation of interest rates is attempting to make changes to the demand for money and how that then feeds into the wider economy. And if you want an even clearer example, quantitative easing was creating new money in its own rights to then push into the rest of the economy, in an attempt to stimulate real activity, which creates jobs and production for companies all throughout the economy.
Cameron: So quantitative easing, allowing the economy to increase the amount of money, is not having the Bank of England run its printing presses faster, it's actually changing the regulations on the banks and what they can do with lending. Is that the basic idea?
Hector: Well, quantitative easing was essentially creating new money to purchase assets with the aim that would push up the monetary value of those assets, which would provide us a wealth-based stimulus to the rest of the economy. It was an exercise very much in changing the supply of money. Now the difference again, from these two schools of thoughts ... the economists would see this in different ways, and it comes back to the supply and demand driven argument. In the supply-driven model, all the available resources in the economy ... and by that I mean real resources like workers, capital ... they're in use because the pricing system adjusts so that everything is in fairly optimal position, and all the available resources are used. If in that situation you create more money, all you're doing is having more money chasing the same number of real assets out there, so you just see an increase in prices, and nothing else really changes very much. But if you're going from the demands-driven perspective, then the story is quite different because there's a possibility of unused resources in the system, so unemployed workers, factories operating at less than full capacity. And by injecting more money into the system, you can create a stimulus effect that then brings these spare resources into active use within the economy, and that creates jobs, it creates incomes, and you see a boost overall.
Cameron: Help me through understanding figure two in your paper. This is the one that ... and I can post a copy of it on the website for listeners who want to click on it, we'll give them links to your paper, they can go read it in more detail there. But this figure shows, very optimistically, that after a certain transition period from the old fossil fuel economy to the new energy model of the economy, that everything comes together again, and everybody's a nice happy family. That's assuming the planet survives, of course. But so your focus then is on the transition period itself: How do we get from where we are now to that happy phase afterwards, where everything is more stable? And you show that the two fundamental models lead to different trajectories between now and then. Then is about what, 2050 in your timescale? Is it about 2050?
Jean-François: You could say that, or what is the timescale that's accepted in the climate's negotiations world effectively, so we could start by adopting targets for 2050, so you could say that.
Different paths to 2050 (Mercure et al. 2019)
Cameron: Yeah. So we're talking at a period of two or three decades to make this transition. And the supply-led model, the equilibrium model, because it assumes that the supply of money gets crowded out as we draw investments away from fossil fuels into the new energy models, that you're going to get this retraction of the economy, you get a slight lowering of GDP for that transition period. Whereas the demand-led, non-equilibrium model, you actually have an improvement in the economy during that transition, and then it all settles back down as people have to repay all that debt that they borrowed to get through the transition. These are pretty big differences. One is much more optimistic to me that if we just go ahead and make this transition, then there'll be all these new jobs, and new skills, and we'll be learning new stuff, and life will be better, and it'll be good employment. And the other is: Oh, we're screwed no matter what we do, because either the planet is going to collapse because we don't make the transition, or the economy's going to collapse because we do. It sounds very dreary. I can understand why policymakers would be frustrated, faced with these two things and not really knowing whether to believe the sunny picture that's created by the one, or to be threatened by the pessimistic picture that's portrayed by the other. How do politicians begin to make sense of it? How do you help them make sense of it?
Jean-François: Well, I suppose the step one was to write this paper. First we need to identify, because otherwise the policymakers don't know what they're commissioning. So we need to start this discussion so that people can start asking these questions, and see what it is they understand and what it is they don't understand. What is the limits of knowledge currently in the economic science, and where does it end? And it turns out there's a whole lot of people disagreeing on the fundamentals, and we need to resolve that.
Cameron: One of the things in your paper that intrigued me was a little section where you talked about the differences caused by the policy focus of a government. If the policy focus is to promote investment in new technology, you get one thing. If the technology focus is to restrict fossil fuels and to clamp down on that industry, you get another. Can you explain what you're seeing there?
Jean-François: Yeah. So one approach that's often favored is a pricing approach to make fossil fuels less competitive, thereby making other types of energy systems more competitive, is mostly based on this idea of pricing externalities, the externality being emissions of greenhouse gases, pollution in the atmosphere, and we need somebody to pay for that. And that's the rationale that goes with it. While you could completely imagine somebody thinking differently on the topic, where instead the idea would be to help develop new types of technology, new systems, investing in R & D to make things move on, and that would also result in quite different policies, where perhaps taxing is still there, but not quite the focus. And you could have investment in subsidies for technologies, companies that develop new stuff, try to help them bring about new ideas. You could also fund more universities, a completely different sort of approach. Of course, you could also mix the two, but I think that the two approaches tend to be tied to their own understanding of the process of changing the economy, which ultimately goes back to how we understand finance and the economy itself.
Cameron: Just to make sure I've got it clear in my head then, one side of things would be to say, "Look, you're paying, whatever it is, say $2 a liter for gasoline, and that doesn't nearly cover the cost of the impact on the environment, so we're going to add a dollars tax that. We're going to make it $3, and that will create a disincentive for people to use fossil fuels, and those who do pay that higher price are then helping to fund the reparations to environment and that." So it's a disincentive to use fossil fuels. The other would be to create tax breaks, or tax incentives, or subsidies for people moving into this new energy thing. So you could provide tax breaks for companies that are developing those things, you could provide a subsidy to homeowners to buy a new kind of furnace that relied on renewable energy, or something. Are those the two policy sets that you're talking about?
Jean-François: Yeah, correct. Correct. You could say that in the first case it's more of a fixing the environment focus, and the second is more of an industrial strategy focus.
Cameron: What's the relationship then ... when we're talking policy, we're talking government decisions ... what's the relationship between government policy on these kinds of things and the role of the finance industry? How does policy drive the finance industry to behave in certain ways?
Jean-François: That is a big question. Hector, did you want to say something?
Hector: I suppose the first thing I would say is when we had a workshop fairly recently, when we had some members of the finance industry in London and they were saying, "We will do everything we can to get behind the low carbon transition if the government provides the right incentives for us to do so."
Cameron: I'm fascinated by how this new technology comes about, because it requires quite a bit of faith on my part to believe that we're actually going to make this transition, and come up with these magical new products that are going to be green, and energy efficient, and save us from ourselves. So the non-equilibrium side, at least, is about technological disruption. And you guys are quite a bit closer to the field than I am. Do you have a sense of where these kinds of disruptions are going to come from? Is it around new batteries, or new ways to produce energy? Is it about harnessing tidal power? Where do you see the real possibilities that might make me a little bit more encouraged about all of this?
Jean-François: I think all the technologies are pretty much there. There's some things to resolve still, in terms of energy storage, but the challenge lies in scaling up all of that. A lot of things exist since a long time. Solar panels were invented to put on satellites 50 years ago. There's nothing new, really. None of this is new. Electric cars were developed in the 80s. But really it's the scale problem. What you need is you need people to invest enormous amounts of resources to develop large factories, just like Elon Musk is doing in America for, say, battery factories, and electric cars, and also scale up solar production; But solar production has been scaled up now in China. Now one needs to believe there is return in doing this. And that relies on what the prospects are for policy and regulations to support that, and to determine how competitive that's going to be in the markets, in comparison to the incumbent industry, which is the fossil fuel industry. Policy has an enormous role, and the financial sector also has a role in believing that there's returns to be had in those sorts of new ventures that they're not used to investing in. The challenge really lies in the scaling up, so scaling of finance, scaling of technology production, and finally having people go for it. So you need people to buy these electric cars, and you need utilities and homeowners to buy solar panels to put on their roofs. And again, the policy there is important, but also there's this whole culture around this, what people believe, et cetera. And the transition when it's starts to go, it really starts to go; when you start to see all your neighbors with solar panels, then perhaps you think, "Well that seems to be worth doing." And then it really goes on after that. While perhaps it just never takes off at all, and you'd never see them anywhere and you never think you should buy anything.
Cameron: I'm often puzzled when I see in Canada, and in France of course I've seen them as well, these fields of these huge, huge windmills that are producing energy. And it strikes me that it's almost to me like the wrong model. You have this ubiquitous energy source that is the wind, traveling over everybody, and you have a corporation making this massive investment to create a resource that then it can sell to others. An alternative model, which has been around for years and years and years, from Buckminster Fuller onwards, would be simply to have a very vastly distributed energy production model; as you suggested, solar panels on every roof, not just a solar panel farm out in the field. Little windmills, little turbines on every home, rather than these great big ones. Is there a problem with that more distributed model, in terms of what kind of returns might be promised to industry and to the finance sector for that kind of an investment?
Jean-François: Well, I think both models are valid. I wouldn't have any particular preference. I think if we get there by one or the other, or a mix of the two, I'll be very happy.
Cameron: We'll all be happy if we get there at all.
Jean-François: It's certainly a difference in the optimism or pessimism between Canada, North America, and the UK and Europe I suppose, because here policymakers seem to be more optimistic than in North America, and it seems that people have really different views about this, but Europe was invested in those sorts of renewables, solar and wind, since very long time. And while it kind of is mostly hydro-based it has been doing this for a long time. America is there too, but somewhere between where the fossil fuel industry has a much larger share of society. So obviously people have completely different views of what they think the future might look like.
Cameron: Yeah. Our future seems to be tied more and more to things like pipelines. As you know, we've had a massive debate in Canada around the trans-mountain pipeline and on the day of our recording here, the Trudeau government has just in the last few days, last week, decided to go ahead with this. There's a lot of opposition from First Nations in BC and from many others in BC and the rest of Canada. A lot of joy in Alberta; its economy depends largely on the success of this pipeline. So you have these huge, huge, investments being made at the behest of elected politicians in the old technology. It seems to me that perhaps they didn't read your paper, Hector.
Jean-François: Apparently my paper was mentioned in Parliament in Canada. Yeah?
Cameron: And yet we still have this decision.
Jean-François: Yes. And I was interviewed in various radio stations in the West to give my view on this precisely, about the Kinder Morgan Pipeline.
Cameron: Yeah.
Jean-François: Not that I want to be involved, or seen as an activist too much, but of course, it's exactly as you say: Investing in the old technology regime when things are already changing might not be the wisest thing, in terms of finance. The reason being that it's not just within Canada you have to think; you have to think, if the rest of the world transforms to a low carbon economy, you wouldn't want Canada to be left behind, or America for that matter, because that's where you'd be losing. Where you want to be is where others are going.
Cameron: Yeah. Well. We'll see how this works out for us. Just a couple more questions for you. Hector, you've talked about the importance of these kind of economic models that you manage in helping us avoid what you call "problem shifting." Can you describe what you mean by that phrase?
Hector: Yeah, it's a good question. I think, certainly amongst policymakers there's often a rather siloed view about the issues that we face in society. This is partly because they work in their own departments, so they're always focused on one or a small number of issues day-to-day, and it is possible quite easily to lose sight of the bigger picture around that. So one of the advantages of the models is that by including the whole economy, and as many different areas of sustainability as they can, you can avoid solving one problem but creating another problem elsewhere in the process. There's a very good example from something's wrong principle. I talked about quite near the beginning of our chat about the nexus of energy, water, and food. You could solve many of your energy problems by going very big on biofuels, but then you might not have a secure food supply available, and then food prices may get pushed up with, of course, implications for some of the less well-off in society. So the modeling is trying to look at all of these things within a single framework that provides consistency across all the different areas. And I think that's something that policymakers can find quite valuable from the analysis that we do.
Cameron: So it prevents us from solving one local problem and then having the real problem sneak away into some other area, by dealing with it comprehensively?
Hector: Yeah, I think that's right too. So it's not just across different policy areas, but different geographical areas as well, as you say.
Cameron: How many countries have you got in your model? You said 60 or something?
Hector: It's 61 in the most recent version. It keeps going up because people keep asking us to separate out more. But the whole world is covered, and just some of the countries are aggregated together into regions.
Cameron: Okay.
Hector: But yeah, we do, every now and then, come across exercises that are a bit more ad hoc. So one example, we once saw an exercise ... our people went and asked lots of different countries: "How are you going to reduce your emissions?" And they all said, "We're going to use more biofuels to do so." But they were all planning on importing their biofuels. Of course, they can't all import the same biofuels to get this. So the model would have stepped in and said, "That's not possible to do so." But without that framework, that was where they ended up. So it's things like that, that the modeling is really, I think, quite helpful to identify.
Cameron: Good, good. Final question for the two of you. I'm really intrigued by this collaboration between you and the others that are involved in these multidisciplinary teams, also across the boundaries of the Academy. Oftentimes young scholars are encouraged to focus on publishing with their supervisor and other academics in their field, to get academic publications out to academic journals. You guys have got a different model for developing knowledge, which involves effacing those boundaries and just working with whoever is best positioned to help. I wonder how you characterize the risks and rewards of this from your two different perspectives, because that would change maybe the possibilities for someone who's just getting a PhD in this field, and what kind of work they want to do, what kind of collaborations they wanted to enter into. Can you tell me about just the collaboration itself and how it's working for you?
Jean-François: Yeah. I think it's a good division of labor we've got because the consultancy, the role is to keep quite close to the clients, and the clients are real world institutions that do real things. That's great, because these people, we inform them, then real things happen, like climate policy, for example. Of course, the funds, they're not necessarily so large as to fund a lot of fundamental research. Now for fundamental research that could inform how to improve the methods used in the consultancy, that could be better funded using national research funds. So from the University you can apply for these funds and have projects that are typically longer term than what's done in the consultancy. It's a bit more funds. There's been more time to develop these methods that may or may not work. And I think the key is to connect the two, because once these methods work, typically the academic would go on and fight for more funding, and carry on this way, but not necessarily engaging very much with the real users of research. But then if the academic passes on all of this knowledge to the consultancy, and the consultancy uses a lot of that knowledge, in addition to what they already have, and what they've been doing for a long time, and what they develop themselves of course, altogether gives a very good tool, and toolkits, and a set of skills and abilities and knowledge in the consultancy to really go in and answer the questions that are asked by these real world actors. So I think to be successful as an academic, in my view, from my part, we get here in the UK, lots of, let's say, reward for having impact, but how do you reach the impact in that sort? And by impact, I mean engaging with the real world? Well, for me, if I engage, if I work with Cambridge Econometrics, that problem is solved because of course, the knowledge I create then gets used quite directly, and I think for Cambridge Econometrics the deal is reasonable too, because everything I've contributed there is publicly funded, therefore I give it to them for free.
Cameron: Oh Hector, let's get your opinion on this collaboration.
Hector: Yes, I obviously fully agree with what Jean-François just said. The consultancy world is pretty fast moving. There are different types of consultancy, of course. I think for any students out there wondering about why the consultancy is a good industry to go into, I think you choose the type of the consultancy you do. Certainly, public policy moves at on one pace, everything related to the finance industry moves at a different pace, and of course there are cultural clashes as well, but the importance of consultancy is communicating, and always being open, and establishing these different types of working relationships. So it's certainly something I would recommend for the students that are out there. In terms of working with academics, Jean-François and others as well, I think it's great the way that we can bring together these two ways of working and find out how to get benefits from both sides, and to be taking advantages of the different types of activities that are going on. There's a final thing I would say. As economists don't have a very good reputation for working well with people from other disciplines, and tend to sit in our own rooms in front of our own computers, talking to other economists, but only if we have to; the more interdisciplinary stuff we can do across different policy areas, different subject areas, I think we all learn a lot from that.
Cameron: Wonderful stuff. So Jean-François and Hector, I want to thank both of you for being on the podcast. It's a fascinating collaboration, it's a fascinating paper, and I'm really interested in following where this goes for you, and how you see this collaboration leading to a real effect on policy, and hopefully, ultimately one day on our climate. So it's with great self-interest that I wish you all the best, because I have a vested interest in this planet too. So thank you guys for being on the podcast. Much appreciated.
Hector: Thank you very much.
Jean-François: Thank you.
Links
Faculty page for Jean-François Mercure at the University of Exeter.
About Hector Pollitt at Cambridge Econometrics
Their paper on modelling innovation: Jean-Francois Mercure, Florian Knobloch, Hector Pollitt, Leonidas Paroussos, S. Serban Scrieciu & Richard Lewney (2019): Modelling innovation and the macroeconomics of low-carbon transitions: theory, perspectives and practical use, Climate Policy, DOI: 10.1080/14693062.2019.1617665
Credits
Host: Cameron Graham
Producer: Bertland Imai
Photos: ResearchGate, Twitter, YouTube
Music: Musicbed
Recorded: June 27, 2019
Location: York University, with guests recorded by Zoom from Exeter and Cambridge, UK
