In our second episode, host and RFF Senior Research Associate Daniel Raimi talks with Fran Moore, an assistant professor in the Department of Environmental Science and Policy at UC Davis, about her recent work quantifying the economic impacts of climate change on agriculture. Daniel and Fran discuss what the study found, and what it means for estimating the social cost of carbon.
Listen to the Podcast
Notable Quotes
- “If we don’t have a good social cost of carbon...we don’t have an accurate understanding of what climate change impacts really are” —Moore (6:08) (6:27)
- “It appears that, in most growing areas, higher temperatures generally have negative effects on crop yields” —Moore (9:01) (9:17)“You’re finding that climate change would lead to net costs of $8.50 per ton [of CO2] in the agricultural sector alone” —Raimi (21:15)
Top of the Stack
- American War: A Novel by Omar El Akkad
- The End We Start From by Megan Hunter
- Odds Against Tomorrow: A Novel by Nathaniel Rich
The Full Transcript
Daniel Raimi: Hello and welcome to Resources Radio, a weekly podcast from Resources for the Future. I'm your host Daniel Raimi.
This week we talk with Dr. Francis Moore, assistant professor in the Department of Environmental Science and Policy at UC Davis. I'll talk with Fran about a recent paper she published with colleagues on the economic impacts of climate change on agriculture. We'll talk about what the study found, what it means for estimating the social cost of carbon, and more. Stay with us.
Okay, Dr. Fran Moore from UC Davis. Thank you so much for joining us today on Resources Radio.
Francis Moore: Thanks for having me.
Daniel Raimi: Fran, one thing that we like to ask all of our guests is how they became interested in energy and environmental topics in the first place and, for you, climate change in particular. Can you tell us a little bit about that background?
Francis Moore: Yes, I've really been interested in climate change my whole career. I found it a really interesting, motivating issue to understand very broadly our planet and the human society that lives on Earth. I began in my undergrad [studying] geology and earth sciences and, in particular, paleoclimatology, so the deep history of earth's climate. Then I moved to Washington, DC, right after graduation and leveraged that knowledge into studying modern climate change and climate change policy. And since then I've used the issue of climate change to move between a really broad range of fields. Coming from the earth sciences, looking into some aspects of political science and anthropology during my master’s degree and then moving more into economics through my doctorate.
But it's all been motivated by this climate change question which is really so broad and touches on so many of these disciplines. I find the integration of all those disciplines and way of understanding the world through climate change, I find that to be really fascinating.
Daniel Raimi: That's fantastic that you can bring all those perspectives together in your work. Your work touches on so many aspects of climate. The one we'll be focused on today is agriculture, which I'll ask you about in just a couple of minutes. One of the important parts of the study that we're going to be talking about is agriculture and how it affects something called the social cost of carbon. Many of our listeners are probably familiar with the social cost of carbon (or the SCC) so we don't want to spend too much time on it, but for those of us who may not be so familiar with the social cost of carbon, can you just tell us what is the SCC and how is it used?
Francis Moore: The way I approach it is very much an accounting exercise. If we put, say, one ton of CO2 [carbon dioxide] in the atmosphere, the SCC is a number that counts up all the impacts of that ton of CO2 around the world in every different sector throughout time. That's where the challenge really is—but at heart it's really a simple idea that we want to know what these greenhouse gases that we're putting up into the atmosphere are doing. The reason it's challenging to come up with a defensible number is that these impacts are widespread—they’re disparate in terms of the type of effects they're having on human society and they persist far into the future.
A lot of the technical challenges around calculating the SCC are to do with that. The other challenge is that in order to add up and aggregate these impacts, we need to put them into common units of measurement. This is where there's a valuation step involved because the units of measurement that we conventionally use are discounted dollars. So, the present value of dollars in the future. The process of understanding the social cost of carbon, either the total social cost of carbon or in a particular sector, is really in understanding what are the effects around the world and then turning those physical units in which impacts are often measured in, say, the climate impacts literature into economic units. So attaching a dollar value to them.
Daniel Raimi: Right, so there are all these multiple steps involved in actually getting to that final number (the social cost of carbon) and it's a number that evolves over time as our understanding of both the physical sciences and the sociological impacts of climate change evolve. Your work is a great demonstration of that.
Last question before I ask you about the agriculture work is, why does it matter to have a good social cost of carbon? If the actual social cost of carbon is $100 per ton, but say we are estimating it at $25 per ton or any number you want to choose, why would that matter for policymaking and for society?
Fran Moore: I think two main reasons. We want to have an accurate understanding of the social cost of carbon so one is this link between these marginal damages from CO2 emissions and the optimal price for carbon. In that “Econ 101” world, we would ideally be in a place where the world was pricing carbon at a value equal to the social cost of carbon. Either through a carbon tax or a cap-and-trade system. We don't live in that world but the social cost of carbon is still useful in policy analysis for things like a cost–benefit analysis, which is how the federal government in the United States was using it and still is using it in its regulatory analysis.
So if you have a wrong social cost of carbon, particularly if you say your social cost of carbon is too low, then certain policies and regulations are not going to be passing a cost–benefit analysis when perhaps really they should. So that's one reason I think is well understood why it's important to have a good number. The other reason I would say is to do with this accounting exercise that's involved in creating the social cost of carbon. If we don't have a good social cost of carbon, what that means is we don't have an accurate understanding of what climate change impacts really are. The process of coming up with a well-founded, empirically justified damages that go into the social cost of carbon is really a process that's going to tell you a lot about where is climate change happening, what are the sectors in the locations that are most impacted that we should most care about, and force you to do this in a very systematic way that doesn't necessarily emerge naturally from the general research into climate change impacts.
For me doing this work on the agriculture sector that was something that I wasn't expecting but with some of the more interesting aspects of that work.
Daniel Raimi: Yeah, it's like going through a cost–benefit analysis in itself, regardless of the outcome that you come up with going through the exercise, can be really beneficial in understanding actually what your priorities are and what the impacts are in different ways. The social cost of carbon definitely helps us compartmentalize and quantify those different impacts.
One of the big areas that many people have been interested in when it comes to the impacts of climate change and the main topic that we'll be talking about today is how climate change is likely to impact the agricultural sector, both in the United States but, more importantly, globally because the global agricultural system is of course interconnected. Before we get into the specifics of this paper, can you give us a general outline of what are some of the key pathways through which climate change is likely to affect agriculture and what crops are we most interested in?
Francis Moore: I would say there are two main pathways that we understand moderately well, at least well enough to start to incorporate into SCC estimates. Those are the effects of temperature on crop yields and the effects of CO2 fertilization. It's been understood for a long time that having carbon dioxide in the atmosphere directly benefits plants because they're able to take up more CO2 and therefore photosynthesize at a high rate producing high yields. All else equal, higher CO2 is generally beneficial to plants.
This is something that was captured even in the first generation of integrated assessment models capturing the social cost of carbon. It’s been known for a long time. I think more recent science has pointed to the fairly large offsetting effects of higher temperatures and that as we have more and more work on understanding how higher temperatures affect crop yields, it appears that in most growing areas, higher temperatures generally have negative effects on crop yields.
The set of crops that we're most interested in or at least that the research community is most focused on are the large field crops. Things like wheat, rice, and maize, and soybeans to a slightly lesser extent. So these are the major commodity crops that are widely grown, traded around the world, and constitute a large part of people's diets as well as feed in the livestock sector. Other crops economically are local cash crops and so on (also potentially really important for understanding regional impacts), but at the moment we don't really have enough studies to pin down the impacts on those crops.
Daniel Raimi: Right. So the effects on things like strawberries or raspberries might be different from wheat and the economic implications might be pretty different—but we may not have the information to tackle every single one of those crops.
Francis Moore: Yes, or at least not yet.
Daniel Raimi: Right, not yet. Let's get into the paper that you published with a number of colleagues in Nature Communications a number of months ago. The name of the paper is “New Science of Climate Change Impacts on Agriculture Implies Higher Social Cost of Carbon.” So you can see there that we're touching on agriculture, we're touching on climate, we're touching on the social cost of carbon—and we'll try to address each of those points in the next few minutes as we talk.
Can you give us a broad overview about what this paper tells us about the direction and the magnitude of the potential impacts of climate change on the agricultural sectors that you looked at? And, for listeners, the paper focuses on the four crops that Fran mentioned a moment ago (maize, rice, wheat, and soy) and it looks across the world at how these crops might be affected and how the economic impacts flow from those impacts to the crops themselves.
Francis Moore: In this paper we go through two steps; so we calculate climate change in two ways. The first way is physical measure of how do yields change with climate change and this is what the agronomic community that works on understanding climate change impacts has largely been focused on is dependent variables. They're interested in crop models or empirical models of yield to understand how does temperature affect basically a measure of land productivity. For that, we find fairly widespread negative effects with just some small positive effects on yields in very cold countries. So, places like Canada, Scandinavia, parts of Argentina—and that's including the positive effects of CO2 fertilization as well as the negative effects of higher temperatures.
If you only look at the effects of temperature change, what you find is that's negative almost across the board, with some exceptions ([e.g.,] rice at colder temperatures, where rice is a more heat tolerant crop). This is coming out of a meta-analysis of over a thousand estimates of how higher temperatures and CO2 are affecting yields.
Daniel Raimi: The meta-analysis that you're pulling from, these are the studies that went into the most recent IPCC [Intergovernmental Panel on Climate Change] report, is that correct?
Francis Moore: Yeah, that's right. What we wanted to do was be able to tie the social cost of carbon in agriculture that we were estimating more directly to the consensus document on climate change impact which is represented by the IPCC. I think there's a lot of benefit in doing that, in that the IPCC does do a lot of work to aggregate the current knowledge and evaluate it and that it forms then a very natural basis, at least to the extent possible, for supporting damage functions in these integrative assessment models that calculate the social cost of carbon. For us that was really a plus—being able to say this is coming from a document that governments have approved, that's been reviewed extensively by the scientific community, and therefore we can tie our estimates of the social cost of carbon to the findings in that document.
Daniel Raimi: Right. Once we have those estimates of the effects on crops incorporating both temperature and CO2 changes, that's step one.
Fran Moore: Yeah. So step two is really taking those productivity changes and doing this valuation step. So putting them instead in terms of dollar values. If you're only looking locally and you think that climate change on the whole is not going to have a big effect, a net effect, on prices then maybe you could just take the yield changes that you estimate and multiply them by the current prices of crops. But because we're finding this very widespread net negative effect on crops, you really need to start moving to more of a general equilibrium setting that's going to allow prices to change. In some cases what we find quite substantially and therefore the economy to adjust and respond to that.
In order to do that, we use a CGE model (a computable general equilibrium model)—the GTAP [Global Trade Analysis Project] model, developed by Tom Hertel at Purdue, who's a coauthor on the paper, along with Uris Baldos. This is a model that has a very rich representation of the agricultural sector as well as the agricultural trading relationships between countries. We run it with 140 different countries and we can look at, given these productivity changes, how does trade adjust between regions and how do equilibrium prices change and, therefore, what are the resulting changes in welfare.
And it’s these changes in welfare that we're really interested in in terms of understanding the impacts of climate change. What's interesting is the terms-of-trade effect—the fact that prices are going up and that's benefiting exporters. In certain countries that kind of outweighs the negative effects of yield changes. We do find several countries where they're having small declines in yields, but because prices are going up a lot their net welfare effect is positive. These are places like Australia, and actually like the United States, and certain parts of South America as well.
Daniel Raimi: There's a wonderful figure in the paper that illustrates this figure, too, where these different effects are visualized across the globe using brownish and greenish colors. It's fascinating to see that the direct effect of climate change on agricultural productivity in a place like Brazil is negative, but then when you incorporate those terms-of-trade effects, the terms-of-trade effects are positive for Brazil. Then you have to try to combine those things to figure out overall, when you incorporate all of this stuff, does the country come out ahead or behind with these higher temperatures.
Francis Moore: I think it really illustrates the importance of bringing in the economic theory.A lot of climate change impact analysis stops at these biophysical changes, kind of leaves it at that. We are showing here that these economic adjustments are really important in distributing the gains and losses from those productivity changes. Particularly at a regional level—if you're interested in the welfare changes at anything less than a global level—you need to be considering that.
Daniel Raimi: Where globally do we see some of the biggest impacts, either from a negative or a positive perspective? Are there big differences between, say, major crop exporters and major crop importers? Or major regional trends that emerge from this type of analysis?
Fran Moore: Yeah, we see any benefits on net are really going to the major exporters—so, places like Canada do well and then also places like Australia that is a big exporter. The places that are really hurt are the places where they get this double whammy of their own productivity in their agricultural sector is declining because of climate change and they're already importing a lot of crops and the prices are going up. Those two things are both these net negative effects and it's those places that do poorly. That's a lot of places in the Middle East and North Africa as well as Mexico [who don’t] do so well in our analysis.
Daniel Raimi: Just looking at the map here, some other countries that seem to not do so well are some Eurasian countries and India as well as Pakistan. Both see pretty substantial losses. We've talked about two steps of the paper so far. The biophysical analysis, the economic analysis—and then a third step that your paper makes, which is super valuable and why we're talking about the social cost of carbon, is that it then translates those economic impacts into a change in the social cost of carbon. Can you talk a little bit about that next step and how it gets done?What are the things that you found in terms of the impact of climate change on agriculture and how that flows through to the SCC?
Francis Moore: Yeah, that's right. With these results from GTAP that gives us the welfare changes at different levels of warming, we're able to take those and this is now an agricultural damage function. And that's something that can then go into these integrated assessment models that estimate the social cost of carbon. This was work largely done by Delavane Diaz, who's another coauthor on the paper. There are really three main models that are widely used to estimate the social cost of carbon, and we focus on one of them because it's the only one that explicitly represents the agricultural sector. All we do is we take the agricultural sector in this model (FUND) and we take it out and we put in our new agricultural damages that have come out of this process and we reestimate the social cost of carbon. We find a really substantial increase relative to the previous agricultural sector damages in FUND.
We think it's largely to do with more negative effects of higher temperatures. So, FUND breaks down the effects of CO2 fertilization and the effects of temperature and most sectors had fairly positive effects of higher temperatures, particularly at lower levels of warming, which we in our analysis don't find large support for. We think that main change really increases the total social cost of carbon that comes out of FUND.
Daniel Raimi: For listeners who aren't familiar with these integrated assessment models, you can find information about them if you just do some internet searching for “integrated assessment models.” And the one that we're talking about in particular here is the FUND model, which I think I want to say “framework for uncertainty, negotiation, and decisionmaking,” which was originally developed by an economist named Richard Toll. In FUND, we have these existing estimates of the damages from climate change in the agriculture sector. Looking at the paper, it says in the abstract that FUND had previously estimated that climate change would result in net benefits to the agricultural sector that translated into benefits of about $2.70 per ton of CO2. Whereas, using your methods with these updated papers, the economic modeling, you're finding that climate change would lead to net costs of $8.50 per ton in the agricultural sector alone. So that's a total change in sign and a big change in magnitude as well.
Francis Moore: It turns out in FUND that these kinds of benefits in agriculture are fairly important in driving the total social cost of carbon estimate. Even though we're only changing one sector, that is an important sector in FUND so it does have a very large effect on the total social cost of carbon as well.
Daniel Raimi: Great. There's so much work on the social cost of carbon that's going on at RFF, at the Climate Impact Lab, and the work you're doing, Fran, and many other places. One thing that certainly emerges when you dig into these bodies of research is that we are getting better at quantifying all sorts of things. But there are still lots of big uncertainties that are out there. When we think about this paper and the effects of climate change on agriculture, what are some of the major uncertainties that stick out to you?
Francis Moore: I would probably divide even to those we are able to estimate and deal with in the paper and then those kind of “known unknowns” that we know we're not able to capture. In terms of the uncertainties we can look at in the paper, we look at two. One set of uncertainties is to do with,for a given level of temperature change, what are the effects on yield? Or for a given change in CO2, what are the effects on yield? These are large uncertainties but we're able to constrain them fairly well through this meta-analysis process. We then propagate those uncertainties through to the final social cost of carbon. Those are pretty large error bounds. These biophysical uncertainties about how exactly does climate change affect crop yields definitely are important in the overall estimate of damages.
The other element of uncertainty that we look at in the paper is to do with the parameters in DTAP and, particularly, how quickly trading relationships can adjust. And those we find that uncertainty is much smaller compared to this agronomic or biophysical uncertainty of the effects on crop yields. There are then these uncertainties that we know exist but we're not able to really deal with in the paper, and I would say one main one is the fact that when we think about the social cost of carbon, we're thinking about the effects of CO2 far into the future. With a CGE model like GTAP we fix the economy essentially at it's 2009 values.
And so, if the welfare effects of changing productivity in the future look really different because, say, people are a lot richer,their diets are very different—then that is something that we're not capturing here. We know that that might affect our estimates, but it's very difficult to incorporate that into a modeling framework like GTAP.
Daniel Raimi: That makes sense. One last question on uncertainties: How do you account for adaptation in this paper? That's one thing that always comes up with regard to agriculture and some other damage sectors on climate change.
Fran Moore: You're right, this does always come up. Because of that, we thought about it a lot. There are kind of two ways of thinking about how adaptation is included in these estimates. On the yield side, this is now thinking about farmers who are growing a particular crop and they are facing climate change and they decide to make management changes that will mitigate the negative effects of that climate change or take advantage of any benefits to a greater extent. So these are adaptations like changing the variety of crop that you grow, changing your planting date, changing the inputs you use, things like that.
The meta-analysis that we do based on this database compiled by the lead authors and the IPCC includes information on did this study include any adaptation measures and, if so, what adaptation measures did it include? A part of our meta-analysis is to estimate across these studies, you know, if they're estimating the effects with adaptation versus without, what does that do to the estimates? We're able to statistically incorporate this agronomic adaptation into our estimates.
We don't find great evidence that it's very effective in reducing the negative effects of temperature. What seems to be going on is that these things that the crop models are incorporating are beneficial today anyway. Yes, they help you in the future but they also help you today. Those are not true adaptations in the way we would normally think about them. The actual additional benefit of these things in the face of higher temperatures is relatively small. That agronomic adaptation is then included in our yield estimates.
The other set of adaptations are these economic adaptations. If we think we're not able to, say, grow maize as productively, maybe we're able to shift to other substitutes or to shift our import to another growing region, things like that. All these economic margins of adaptation, those are pretty well captured in the GTAP analysis. Those are the benefits of using this kind of model. So that aspect is that it's really designed to capture all those different economic margins of adjustment.
Daniel Raimi: That's really one of the fantastic things about this paper is that it's able to take in those global trade effects as we talked about, and many papers aren't able to make that step. There are so many questions that I want to ask you about this paper, but we're running short of time. We're going to close out with just a couple final questions. You've done a lot of work here on agriculture. I know you're interested in lots of other topics related to climate change. What are you working on now? What are you most interested in? What's coming next?
Francis Moore: One piece of work that I'm really excited about right now that's a different although kind of related topic is try to understand how people adjust their ideas of normal weather if they're repeatedly exposed to changed conditions. I just like this because it's been a really fun and creative project to do with a bunch of great collaborators. The idea is we're measuring how surprising people find the weather based on how much they comment about it on Twitter. Then we can use the lagged histories of temperature normally in particular places, in particular times of the year to see how quickly people's idea of surprising weather adjusts when they repeatedly get unusual weather.
This is what climate change is, right? You get exposed to some unusual weather. That weather quickly becomes, you know, you get that more and more frequently. This is your climate changing—and how do people internalize that in terms of what they expect the weather to be at a given point in time? We find evidence that people's idea of normal weather seems to adjust very quickly just in the space of about five years or so. That has these problematic implications in terms of whether or not people are going to really notice temperature anomalies going forward and is this really going to provide direct sensory evidence of climate change.
Daniel Raimi: Right. That's fascinating. Last question, which is the same question that we ask all of our guests. It's our ”Top of the Stack” question. Have you been reading things, watching things, hearing things—either in the academic sphere, in the policy sphere, or elsewhere that you find particularly interesting that you think our listeners might not have heard about and that you would recommend to them?
Francis Moore: Yeah, I have recently read of several books that are in this emerging genre of “cli-fi” or climate change fiction.
Daniel Raimi: Yes.
Francis Moore: I think it's just a really interesting way of engaging with this idea of what will climate change actually feel like. Using literature to project ourselves forward in time to a place where these impacts are happening and just trying to play out what would it actually feel like to live in this world. So there are three books that I've read recently. One is The End We Start From, by Megan Hunter. One is American War, by Omar El Akkad. One is The Odds Against Tomorrow, by Nathaniel Rich. They're very different books but I really enjoy being able to think about the things I think about everyday through my research but in this very scientific and dispassionate way, and just trying to bring some kind of imagination and empathy to understanding what are we really talking about here. The books are certainly depressing but I would say also enlightening.
Daniel Raimi: Yeah, that's a fantastic recommendation. I read American War maybe a year ago or so and it was really incredible. I haven't read those other two you mentioned but I'll make sure to look them up. A friend actually gave me a book just the other day called New York 2140, which is about New York City in 120 years which I've got sitting on my bedside table ready to go.
Francis Moore: Yeah, I think it's great because the authors are very clearly, they've thought a lot about what the climate change impact literature is saying. I read these and I recognize things we talk about as people worried about climate change impacts. But I see them in this way that's reimagined. It brings in new sense of urgency and interest to my research.
Daniel Raimi: Yeah. Those are fantastic recommendations and it's fantastic work you're doing on agriculture and so many other things and we really appreciate you joining us today to talk about them on Resources Radio.
Francis Moore: Thanks very much for having me.
Daniel Raimi: Fran Moore, thanks so much.
Francis Moore: Thank you.
Daniel Raimi: Thank you so much for joining us on Resources Radio. We'd love to hear what you think so please rate us on iTunes or leave us a review—it helps us spread the word. Also, feel free to send us your suggestions for future episodes. Resources Radio is a podcast from Resources for the Future [RFF]. RFF is an independent, nonprofit research institution in Washington, DC. Our mission is to improve environmental, energy, and natural resource decisions through impartial economic research and policy engagement. Learn more about us at rff.org.
The views expressed on these podcasts are solely those of the participants. They do not necessarily represent the views of Resources for the Future, which does not take institutional positions on public policies. Resources Radio is produced by Kate Peterson with music by Daniel Raimi.
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