 Hello. Thanks a lot. It's a pleasure to be here and as you might know, it's a pleasure to work with these folks. It's been a really interesting project and we're looking forward to this discussion. So now I'm going to bring it down and we're going to go to a single country and look at some economic implications at an economics conference. And this, as I said, as Ken was pointing out, this is our framework. And, you know, Adam was here, Ken was in here, and I'm going down here. And I think a couple more words on philosophy of what we're doing is really worthwhile. You know, we're not in a world where we can run a randomized controlled trial, right? We don't have another planet where we can go and insert a bunch of CO2 in the atmosphere and look at see what happens and then decide what the policies are. So as Adam was saying, you know, we're building models. And it's not, my model is not Mozambique and this is probably not exactly the climate, but is it close enough? And what we're trying to do is have two things. One, having a framework where we can look and see, okay, this is how our framework is reacting. Does that correspond with what we see in the real world? This is something Adam's term, if that is skill. And then also, then once we have this framework and it bounces, then we can look forward and now we can run lots of controlled experiments. And that's what we're doing and what I'll be presenting to you. So to do this, we're going to make an economy-wide model. And basically, this model is acting as an adding machine. It's taking all these things from Adam and from Ken and putting them in and letting them add up and see what it means for economic growth, which is what we'll focus on, but that is a critical element of development. So we have this model of Mozambique. It's a country model. It's got a lot of structural detail. It's got a lot of sectors, 40 or 50. It's got 20 or so agricultural sectors. These are all broken out by regions. We catch the regional detail that Ken and Adam were talking about. We have a lot of detail on factors and factor markets, a lot of detail on households. It's also a dynamic model because all this process is rolling in over time. And so this model is taking these inputs and running through time. And this world that we're creating is consistent. That's a serious advantage to what we're doing. It also has prices and price response. So if it's turning out that a certain crop is having low productivity for a period of time and its price isn't going up, then farmers are getting poor returns from this crop and they will exit that crop and start growing other things. So it contains autonomous adaptation inside the model. So that's our final world here. To look at what we're doing, we want to isolate the effects of climate change. So to do that, we're going to build a baseline scenario where there isn't climate change. So we're going to have a baseline where historical climate essentially repeats itself. And what we want from this baseline scenario is something that's reasonable. That kind of trucks forward into the future in a reasonable way. And then we're going to run things forward with alternative climates and the differences of the ratios of these two will give us an idea and isolate the climate effects and be able to study climate in our little laboratory and try to get some insight from that. So our baseline has labor growing at population growth rates. The economy is going at about 5% per year on an per annum expansion. We have a slow growth in the land supply. And we do capture this important empirical regularity that the agricultural sector tends to decline in size, relative size, as the economy develops. So the Mozambican agricultural sector is going to go from 22.5% of GDP now to about 10% in 2050. And this is important for impacts because agriculture is an important impact sector. We're also going to take, as Adam mentioned, there's the original global model that's producing the emission scenarios. That model is also producing prices. So we're going to take the prices from that model and apply those such that it's a consistent set of projections. So then we're going to go ahead and take these input. We start off with a scenario with historical climate, baseline everything, world price is changing, and then we're going to layer in effects. So first we're going to put in what's the impact on agriculture. So nothing else is getting impacted. It's as if climate change only affects crop yields and any irrigation demand. And then we're going to add and we're going to have it impact roads. And then we'll go on, we'll have it add impact energy. And then we'll go on and we'll take into account sea level rise. And last, we'll add in the combination of sea level rise and cyclone strike. And what we look at in particular here is the storm surge from cyclones. And this is a major, there's not much evidence according to our cyclones expert that intensity and frequency of cyclones will increase in the southern Indian Ocean. But there is very strong evidence that if the sea level is rising by about this much, and you have a storm surge of about this much, then without sea level rise you have this much water. And with sea level rise you have this much water. And it can make a heck of a lot of difference in terms of what's destroyed and how far it goes. And that's a really robust effect, and that's what we're capturing. Okay, so first we're going to start off with implications of unconstrained emissions. And what we're going to do is we're going to begin at the end. So this is kind of the distribution of results for change in or ratio of gross domestic product, change in total value added in the around 2050. And this is no change relative to the baseline. And this is, so these are the average of the percent deviations from the baseline for our various scenarios. And this is, as Adam was saying, the density. So this is kind of a likelihood of the various outcomes. And so what we're seeing is, over here we actually have, you know, some chance of a positive outcome. It's possible that climate change rolls in over out to 2050, and the economy in Mozambique is actually bigger than it would have been without climate change. That there's favorable things that go on. It's not likely, it's about seven percent of the outcomes. The vast majority of the outcomes are sitting in the zero five percent range. So most of the time, climate change is causing a reduction in economic growth by about somewhere in the zero to five percent range. And then we have a bad tail. And the bad tail extends all the way down to greater than ten percent GDP impacts. And so this is a very useful information. I mean, Ken had the same, I've now stood in front of a number of Southern African policy makers with, you know, one scenario here and a few around here and sort of said, well, gee, they're different. And what does it mean? But here we could say, there's a bad tail. And this tail down here, it's there, but it's not that likely. It's around three percent of the outcomes. So now we're going to go through and see how we came up with this. So the first impact we're going to look at is agriculture. And right now this is agriculture value added in focus. So we're looking at the reduction in total agricultural GDP or agricultural output. And we'll notice that it's pretty well behaved, a very little chance that climate change is going to favor Mozambican agriculture. It just seems unlikely to happen. The mode is about five percent reduction in agricultural output. And then we have, you know, some bad outcomes, but very few, greater than 10 percent. And this is coming out of the crop modeling. And it's, there's a diversity of crop models out there, but this is kind of in the middle of the range of what crop models would normally predict. So this is our first impact. Then going on, and Ken emphasized flooding and he talked about sort of flood events. And it turns out, as Ken was saying, Mozambique is quite sensitive to flooding. And so what we've done here is gone. And rather than just looking at sort of flood, we've looked at big flood events, looking nationally. And what happens is that in the unconstrained emissions scenario, the likelihood you get an increase, and the likelihood is you're going to get an increase in flood events. And in some scenarios, you're getting quite a lot of big national flooding events. And this, it turns out, is a major driver of things that are going on. And where these flooding events in our model really take a toll is roads. Roads are sitting out there, and when the floods come, and then we've seen it in Mozambique numerous times, there goes the road. And you've got, several hundred million dollar repair bill, and your government budget is only a billion. So it's a big deal for these countries. The change in road network length that we're getting across the scenarios, and basically everything's, except for this little tail, pretty good in the 2020s, but as you go forward, it's principally the flooding that's hitting. There's also intensity of precipitation is causing more minor washouts, and the temperature can have an effect, but the big numbers are in the flooding. And this has big implications for GDP. So if you go and you wash out several hundred million dollars from roads, then you have to go and you've got to spend several hundred million dollars to put them back. And that means you don't have investment capital to do other things. You're not accumulating. You're just sort of trying to keep your same stock. And this accumulation effect will come and get you for growth. So roads is, it's not a huge effect on average or at the mode, but it's a big variance expander. It's one where we can have scenarios that are pretty favorable to roads. You actually get less washing out, less flooding, everything. You're spending less money. It's okay. But some of the time you do a lot worse. Now we add energy. And Ken showed that, you know, the expectation is a decline in hydropower output. We already have the Kauhorabasa Mozambique is now building another dam of the same order of magnitude of Kauhorabasa. That's in the model. Mozambique will be a very large exporter of electricity. So in the scenarios when it drives, it'll be an issue. It also turns out that, of course, if you're getting more water, you can get more hydropower. And so this is part of the multi-sectoral effect. You might have more water, which is doing one effect, but it's also potentially increasing your hydropower output. So this is the next effect. The next effect is sea-level rise. And sea-level rise is just a loser. I mean, energy can be, we can get more hydropower or less hydropower. When we have sea-level rise, all that's happening is we're losing agricultural land that's close to the coast. And that's just reducing the factors of production available for the economy. And it just shifts the distribution to the left a little bit. And the same is true of cyclones. So cyclones come. They have a head start with a good 38 centimeters of sea-level rise, and they knock out some capital, and you have to put it back, and that has a negative growth effect. So what we're tending to find is that there are kind of two big effects, what's happening to infrastructure, what's being hammered on average, and what's going on with agriculture, energy, sea-level rise, and cyclones all together. So these are kind of the two effects of the mean, but it's the roads that's causing the big dispersion and the big tail. All right, so that was unconstrained emissions. Now we're going to go and look at the implications of stabilization policy. And as Adam mentioned, we're going to look at the unconstrained emissions versus level one stabilization, which is, if we want to do level one stabilization, we'd better get started. Let's put it that way. This is an ambitious stabilization regime, but it will have even stronger effects on the distribution than what Adam and Ken showed. And one of the first things that's happening that's important when we switch scenarios is, especially when we impose policy, so we get big changes in the world oil market. Under unconstrained emissions, we're allocating oil by price. And this projection, along with almost all of the others that I see, this is coming out of the model that's generating the emission scenario, so it's consistent, is that the world price is headed up towards $160 a barrel real by 2050. If we're substituting policy as the major constraint on oil use, well, then the price doesn't go up by very much. So this is the supply price, it actually goes up a little bit, and then it starts to trend down. This is really important for poor countries that import oil like Mozambique. So Mozambique spends about 14% of its imports are oil imports, and about 20% are oil and derived products. And it makes a heck of a big difference if the price is $60 or $65 versus $165. So this is something that we're also including. Agriculture is another one where there's potential. It turns out that in this part of the century, this half of the century, the upper model is not creating very much difference in ag prices. The upper model is showing an increase in ag prices, like almost all of the other projections, but it doesn't really differ drastically between the stabilization and the unconstrained emission scenario. The L1S is a little bit higher, but Mozambique is not a major net importer of ag, and so this is less of a big deal. Okay, so here we go with what are the effects, and this is just one graph of mitigation policy for a country like Mozambique. This is the unconstrained emissions that we went through and discussed. And what's happening here is this first, this red line, is the level one stabilization with unconstrained emissions prices. In other words, so this is purely the effect of the shrinking of the distributions and of the variance of the distribution of temperature and precipitation, reductions in the flooding events, all of these biophysical impacts are here. And what's happening is that the distribution is shifting to the right. The climate change effects are still on average negative because we have this little negative tail here, but they're a lot more, they're a lot closer to zero. We're staying a lot closer to historical norms in terms of temp and precip, and we've gotten rid of this big bad tail. When we go ahead and we add in the prices, the prices are favorable to Mozambique. They get a terms of trade gain, they pick up, they have additional resources for investment, their growth speeds up, and as a consequence, actually in level one stabilization, the most of the distribution is actually above the historical. So they're doing better than they would have if climate change hadn't existed at all. This presumes that everybody in the world is participating in a global mitigation regime except Mozambique, who's not, okay? So that's the topic for future research. So to sum up, we have to address the complexity and the risk and the uncertainty in this important issue. Not a good idea to use just one climate projection. You're having a big diversity of results and impacts. We really want to, of course you have to do the sectoral work, and some of it is, you know, you can arrive at conclusions straight from the sectoral work. I mean, what Ken showed on how you construct a hydro dam is a good example, but if it's also really useful to aggregate up if you really want to think. As we found before, if climate change comes and hits assets and infrastructure, that's when we get these long-run growth effects. Growth is an accumulation process, and even really small reductions in these eventually accumulate into something, you know, reasonably large. So when we're thinking also, we don't really find very powerful impacts of climate change in the 20s, this decade, and the next. But when we're thinking about long-term investments that are going to be in place, like the hydro power dam, like a major road where it's going to be, these are things that are relevant to consider climate change. You might, if you're thinking about building a road and you have an option between building it on a 50-year floodplain or a 75-year floodplain, you might really think about the 75-year floodplain, especially if it's not that much more, even if your engineering standards tell you that 50 years is what you normally do. We get quite a bit of benefit. It really matters, according to this analysis, how much CO2 and other emissions go into the atmosphere over the next 30, 40 years. It's having an influence on the climate of the future. Mozambique gets gains from a more certain and less severe climate, gets rid of some bad tails. It turns out it gets gains in terms of trade, principally due to this fuel price effect. These are factors. Of course, it's going to be different across all sorts of countries, but likely to be true for lots of countries, least-developed countries. What we're doing next is comparing results from allowing Mozambique and Zambia. We'll run all these countries together and look at what kind of diversity we're getting. We're going to make Mozambique participate in the global mitigation regime, so they have to pay the carbon tax. What does that do? How does that shift that curve backwards? We're very interested in looking at regional strategies. I think what Ken showed with the hydropower is really interesting. If you're pooling, you can get rid of some of the risk. Then, because we keep finding that flooding is an important variable, it's not easy to model. We need to go back. We need to go through it again. We need to make sure that we're doing the right thing. Those are the agendas that we're following. Thank you very much for your attention.