Strategic International Studies and last about one hour. Good morning and welcome to todays launch event for the Energy Outlook. The director here at csis, i cannot tell you how excited i am for todays event. This is focused on a biannual basis, one of the things that we got most excited about at staff level. This is a benchmark product not just in the u. S. But for the world. As we consider plans for our energy future. We will see some of the key outputs of this new idea this morning from director decarliss and his colleague. We will have a few minutes to talk about how this occurs and how industry people and Civil Service can look at the idea and where it fits into the broader constellation of forecasts and documents we have. Thank you again for joining us and if youd like to come up, director, give the podium to you. All right, good morning, everyone. Its an honor to be able to kick off our presentation of the International Energy outlook for 2023. Before i get started, i want to give a huge thanks to the eia staff. There is an enormous amount of effort going into the analysis and delivery the report so i want to thank them. Also want to thank joseph and the staff for hosting this event. I want to talk a little bit about what eia does. We are the statisticalnd Analytical Agency within the department of energy. That means that we are tasked with unique of 30 to collect ener data from u. S. Industry. We publish that data and is used by different stakeholders. We use that data internally to inform our projections. We view our data as a critical source of information within the ited states. By law, all of our products are independent of approval by any other officer or member of the u. S. Government. We prize that independence because its important to us. This particular product, the International Energy outlook, explores longterm trends in supply and demand around the world. Whats new in this years report . You will see a similar look and feel. You will see it in the narrative. I have a background in modeling and its important that analysts and modelers be able to explain th model results and translate them into a realworld context and the only way to do that is focus on the narrative. You will see technical notes that will appear as light blue boxes within theartive. Thatan opportunity to take a deeper technical dive on rtular subjects for readers who arentested. Weve got three of those technical notes, one focused on electric vehicle projections, the representation of storage and the electricity sector, and a representation of global refineries we also emphasize the range of results for the cases we model, similar to the ae. Were also introducing new cases that focus on examining the capital costs associated with zero Carbon Technologies. We have also made several improvements to the model work itself. We have new analysis regions. We have 16 different regions and we think they offer better geographic alignment. We have a brandnew oil and natural gas supply module thats been incorporated into our modeling framework. You will see results from that. We have increased the temporal resolution in our electricity model so we know model Electricity Supply and demand across 280 eight separate time slices and thats important to model wind, solar and battery dispatch. Finally, we made several assumptions about the impact of russias fullscale invasion of ukraine. You will see in appendix where we go sector by sector and talk about what assumptions we made and how its informed error analysis. I want to talk about the cases we model in theieo. We only model current lations. We freeze our consideration of current laws anlations as of march of 2023. Thisoking at policy around the world. For the united states, the reare from our and our jewel our annual Energy Outlook and those lc assumptions were frozen in november of 2022. These tions about policy carried through the cases we modeled. Getting onto the specific cases, we have a reference case. We are assuming that annual gdp grows at 2. 6 annually. We assume the price of brent crude starts at 100 two dollars per barrel and varies a bit and ends up close to 102 per barrel again in 2015 in 2050. We think there is a cost and zero technology thatsin solar, batteries and nuclear and it can achieve Cost Reductions he Cost Reduction and we achieve this through education learning. When those technologies double, cond set of cases focusesost. On Economic Growth. We assume the average annual gdp growth rate is 1. 8 and the high cases 3. 4 . These macro cases have a big impact because when you have high macro growth, it leads to high use demand and requires higher supplies of energy and the converse is true when youve lower macro growth and lower demand and less Energy Supply is required. Next we have our oil price trajectory. We have a low and a high these are formulated outside the model framework. In the low case, we assume brent crude reaches 40 per barrel in 2050. Zero Carbon Technology cost sumption is new to this idea. We look at the cost that was achieved for each of those technologies in 2050 and then we looked at the trajectory that takes is 40 below that cost. We just assume constant cost projection horizon. These are the highlights from this years report. The first is that increasing population offset the effects of Carbon Intensity on admissions and i will provide you more details in a moment on that. The second is that the ship to renewables to makeuring electricity demand is driven to make growing electricity demand is driven by energy concerns. Im going to give some high level view of that and angelina will add additional details. There are some things i want you to keep in mind. We are working on it. There some things i want you to keep in mind as you look at these results. When we model these cases, we take a deliberately restrictive approach in the ieo. They are plausible but sober. Here are some of the assumptions we make. We only account for current policies and we are looking at policies that are legally enforceable. We dont model aspirations or targets unless there is a legally enforceable policy that backs it up. We look at evolutionary reads of technological change based on recent history and we dont consider sweeping changes in Consumer Preferences are major geopolitical events that could produce durable change and shift the trajectory of the system. Its certainly possible those things can happen. Its entirely possible we could get new policies and there could be unforeseen geopolitical events or Technology Breakthroughs we dont model and thats exactly why you should not think of the ieo as a forecast. We are trying to do Something Different here. We are providing a set of policy neutral baselines that focus on the current trajectory of the Energy System. I think that provides the really useful point of reference for decisionmakers against which they can judge future actions and developments. Ok, this brings us to our first set of results. Across most of the cases, we find Energy Related co2 emissions continue to rise through 2050 under current ls. We have a regional model, 16 regis and im showing the results aggregated up to the global scale. The line represents the reference case and the great band around the reference case shows the full range across al of the cases we model. Moving lefto right, we he global gross domestic pduct which you can te is growing rapidly. In the middle, we have primary energy usage. You can see upward trend and finally to the right, we have Energy Related co2 emissions. In each of these three panels, the bounds on the great bands are due to the macro cases. They are setting the bounds on each of these. As you look from left to right, you notice the slope of the cone keeps decreasing. Gdp is growing the fastest and finally Energy Related co2 has the least slope. To get more insight, we can further break those three panels down into four panels. Some of you might recognize this as the terms in the kaya identity we have global population. There is no gray van because one population projectiocaies through all of the cases that we are modeling next w have gdp per capita which you can take to be a rough measure of per capita annual inme. Next we have Energy Intensity which is measure of energy per dollar gdp and finally carbon intensitwhh is the amount of carbonmiions you get. Th uncertainty in the two middle councils are being set by the high and low macro cases and for the carbon intensities, its being said by zero carbon cases. If you take the product of the first three terms, you get total Global Energy consumption. If you take the product of the four terms which is the way the kaya identity is designed, you get total global ca2 and missions co2 emissions. Population and gdp capita are increasing out of pretty fast rate. There is more people and they tend to demand more Energy Intensive goods and services. At the same time, we are able to e less energy per dollar of value in the ecoms of Energy Intensity is clear dlining. For every unit ofnergy we consume, we are emitting less rbon admissions. Thats brings us to theht on the title is that the upward pressure on the population tends to outweigh the downward pressures we are seeing from reduced Energy Intensity over time. We can disaggregate even further so this is just looking at gdp growth rates by regions, there are 16 regions. We have high Income Countries on the left on the low Income Countries on the right. India has the highest arage gdp growth rate but it varies quite a lot by region. Remember there is all of this detail under the surface. We can also look at total energy and disaggregate that a little bit. We are looking at fossil fuels versus nonfossil fuels. We find that increasing demand and current policies drives steady growth in fossil energy but even faster growth in nonfossil sources. You can see the reference cases align and the bands represent the range across the cases. With fossil which is the black and gray, it starts at 505 quads in 2022 grows anywhere from 140 based on thewith nonfossis all of the renewables and nuclear, we started at 100 33 quads, that grows from 72 125 from 100 to 25 . You see that with the blue line. We can, again, break it down even a bit further here, we are looking at the fossil and we have broken that down to specific fuel types. You sethe stacked bar for 2022, thelack outline represents all of the fossil sources and the grayutline represents all of the nonfosl resources, we have 2022 all the way to the left at allf the other bars reprent a snapshot across the cases in 2050. You see how each of these fuel tys is changing over time. Generally what we find is that fossil fuels hold onto their share through time buthe renewables really pick up. Most of that Renewable Development is taking place in the electricity sector. We find that if you look at the electricity sector, renewables plus nuclear combined represent roughly 55 through 65 of global Electricity Supply in 2050 across the cases. Obviously, there is a lot going on here. At the regional level, the regional patterns we are not showing here and that will depend on prevailing policy, trade patterns, and the cost of global resources. With that i will go back to the highlights and turn it back over to Angelina Larose who is our assistant administrator. Good morning. I will keep on with the trend of breaking things down and go into more detail surrounding our three highlights. I encourage you all to take a deeper dive into our website following this event we will have a lot of data and analysis we are posting related to this audio. We are walking you through the interesting findings that are her main highlights starting with our first one about increasing population and Income Growth with consumption of Energy Related admissions despite declining carbon intensities. This is Energy Consumption by sector, as joe oriented to you all, a solid line represents the reference case and the range and area represents the range of production from our side cases. Any of the Energy Consumption growth across all sectors across all cases, easy on this slide the industrial sector includes manufacturing, refining, and other subsectors. The largest share of Energy Consumption also has the largest share of growth through 2050. The industrial sector has the widest range of consumption across cases to the broad range of industrial growth output assumptions across our cases. They sensitivity to duke microeconomic drivers. The sensitivity to do micro economic drivers. Reaching a growth rate of 1. 7 per year. In our little Economic Growth case we see an industrial Energy Consumption. This slide is similar to the one we just saw but looking at the consumption across cases and sectors. Similar to what we saw in the west, liquid consumption also continues for 2050. The fastesgrowth in liquid consumion comes in our industrial sector. It is used in chemical production and legal fuel and construction and agricultural equipment. It is the largest share of liquids consumption, and the ship was ectric vehicles. Overall there is shift towards electric vehicles. Overall there is the use in transportation. We will take a closer look at the industrial consumption. This slide is looking and focusing on consumption in china and india in particular. While we are conduing increasing Energy Consumption in the industrial sector, we ar seeingnergy intensity. At regional level, there are two prevailing drivers of Energy Consumption inhe industrial sector. These are industrial output which is a measure of Economic Activity and Energy Efficiency or Energy Intensity. We see dferent trajectories in china and india. As you seen the left, in china some cases have industrial consumption declining or leveling off compared to india where we have growth across all of the cases. In china, growth output over 2024 combined with significant Energy Efficiency gains slows and decreases industrial Energy Consumption in some cases. In particular china is increasing production which is significantly less Energy Intensive. In india the growth and industrial growth output which more than tripled in most cases and even when couples in the high Economic Growth case quituples in the high Economic Growth case in india. The primary metals, chemicals, and others. I am shifting to transportation and there is a lot to unpack on this slide. I want to do my best to walk you through some of the main highlights. On the left is a graph of travel demand and on the right is the past travel demand i mowed in 2025. That graph sws an indepth up 2025. When we put jacked travel demand to return prepandemic predict travel demand to return prepandemic. You see the overall towel demand is growing. It is highly sensitiveo changes in dposable income per capita and employments. There are findings at the regional level. Much of the travel demand is concentrated in india or both where both the disposable and job growth disposable income and job growth have increased. Africa, they continue to see growth in travel demand because of increases in employment. But to a lesser degree. In regions with Slower Growth and income and employment such as western europe and japan, per capita travel demand growth is limited. Global leak travel demand per capita growth across all cases and nearly doubled in the highgrowth case. This is a strong upward prsure on Energy Consumption. Turning to the graph to the rit, travel demand for a efficient modes transportation particularly lightduty vehicles and air travel rose in regions as incomes increased. As income rising incomes allo travelers to shift from an inexpensive to more expensive modes of transportation. You see that on the graph on the right where we have growth like lightduty vehicles as well as air which is in the first two panels and Slower Growth in buses and three wheelers what you see in the fourth graph. Aircraft travel which is highly sensitive to changes in income has increased in all regions, you see in the yellow. As well as the americas region, part of the green, two or three wheelers, consistent growth compared with aircraft and other travels. Each of these modes of technology, are offset a significant portion of Energy Consumption from the travel demand as well as from the shifting towards less efficient modes of transportation. Ok. My next slide. Imagine it before a panel [laughter] just as you all imagine, i am sure [laughter] this slide is looking at the share of electric vehicles in select regions and breaking out electric and hybrid vehicles. Lightduty vehicle travel, on road suite of vehicles to grow from 1. 4 billion in 2022 to more than to hook billion by 2015 2 billion by 2025. This will show more beagle travel and the increased of the ev adoption leads to a peak in the global fleet of production lightduty vehicles between 2027 and 2033 in all cases. Looking at the eb adoption battery electric vehicles would you see in blue cannibalize plugin hybrid vehicles in yellow pretty early on in the Production Period. That make sense of plugin hybrids make more sense as battery costs drop out, but electrics are more competitive. China and europe, the adoption of the electric vehicle is largely policy driven where in india and japan, it is based on economics. That is why there is a wider range of results. By transportation the building sector shows a bout of interesting stories at the regional level. This slide is showing red, central, and commercial delivering Energy Production per capita in india. And yet has a significant gdp and population increase simplifies the relationship between energy use and income and Service Sector gwt disposable income and expanding service secto increases in Overall Energy use proposed by 2050 relative to triples by 50 of atrocity consumption increases more than any oth Energy Source in residential and coercial sector. That leads us to a shift of renewables and Energy Demand. In Energy Demand. This is the change of Electric City capacity in 2050 compad to 2050 compared to 2022 levels ross cases. The increased glol electricity dand reaching a total of 1. 5 to two timeshat it was in 2022 by 2050. Across cases of gigawatts installed by 2050, the predominantly solar, wind, or storage witjuicy. From 2022 through 2050, 0 carbon techlogies make up between 81 through 95 of new global generating capacity installs across cases. What this slide is showing is electric degeneration by fuel. As expected given the capacity i showed in the devious slide solar and wind should have the highest levels of generation growth. The last slide shows changes in capacity 4. 22 levels. Existing coal and natura gas power plants continue to operate. In 2022, natural gas, and liquid fuel constitute more than half of the worlds Electricity Generation cacy. By 2 the share of these fuels for Power Generation decreases to 27 through 38 of the worlds generation capacity. It is still a nicble share. While coal city most cases that we model, naturalass flat rising. Both gas and coal remain a stable part of the generation mix. That brings us to our last highlight out of the is related to the role of Energy Security in the transition from fossil fuels. And it is rated to the role of Energy Security in trantion from possibly fuels. Fossil based technologies, across a large majority of regions, Carbon Technologies increase through 2050 under current policies. There is regional variation however in the timing of that growth, western europe and dias growthhi is in the first two panels in zero carbon tenology capacity is projected to accompany a flat declining change in fossil fuels, china and africa see growth in zero carbon and fossil based technologies. In western europengy security considerations favoring lollavailable resources such as wd and solar increases installation and planned to bill for these technologies earlier the Production Period. In india, ze cbon technologies is seen after 20 heavily influenced by assumptions of Economic Growth. In china, coalfired generation makes up 62 of the electric generation mix in 2022 and decreases by ls an 10 througho t Production Period in all cases except the love zero Technology Case and the low Economic Growth case. Below zero Technology Case and the low Economic Growth case. Electric demand grows, the most rapid and local coal is both cheap and abundant. Africa see significant increases in installation of zero Carbon Technology over the projection it is accompanied by increasing shares of fossil fuels, the region takes advantage of locally available fossil fuel resources and the absence of any uniform policies. What fossil fuel in particular is an important part of Electricity Generation mix in the world in our production through 2050 . The power sector and its need for natural gas is a key component of the global trade dynamic which is seen on the next slide. This slide is showing natural gas trade, it represents natural gas imports below the zero axes in natural gas exports. Notable on the slide is the range of imports from asia pacific and the range of net exports out of the middle east. These differences are driven by macroeconomic assumptions, total Global Demand for natural gas, different significant it differs significantly from the higher economic case. It grows to over 240 tcf in the high Economic Growth case. That is 20 difference. Most of the demand occurs in china or consumption rises across all sectors, addictively electric power sectors. India often has important growth. Because of the growth in the industrial sector. As the region run out of costefficient resources they will import natural gas in areas that have the cheapest resources. The iel uses the most recent annual Energy Outlook for the u. S. Projection. The u. S. Which is a part of the north american grouping in this supplies natural gas on the chart, it is what we published in march. North america is the second largest source of supply on the net basis for all of the regions, it was only a limited growth in supply between the high Economic Growth case at our Energy Outlook. Given this lack of significant growth, from the united states, and in the macro case and the limited growth from russia, the middle east increases significantly in the high Economic Growth case. I will leave us with are the highlights, i want to thank you all for your attention and thank you to csis for hosting this event and all of the modelers were making this the best yet. [applause] as we get settled, lemme thank angelina let me thank angelina. The fundamental and qualitative work that comes with modeling all of these different sectors of the economy and regions. Thank you so much for coming today. Colleagues online or in the room you can all use the event page to offer questions. We are happy to answer those on a rolling basis but i want to start with your early message. This is not a projection, this is not a forecast. It is a projection. Eia has always had a practice of saying the big scenario is those laws are on the books today. That is separate from the ambition of the governments around the world related to common growth, the composition of the vehicle fleet or Greenhouse Gas emissions . When i look at the results i say oh man. This is an Energy Addition on Energy Transmission scenario. How do you guide to recommend Global Public policy makers to at the scenario that you have or interpret the outcome of the scenarios that has been crafted. I think it always comes back to the context. Any time you are looking at a modeling exercise were an outlook it is important to understand what were the assumptions that went into it . When we are thinking of the particular approach here where we are assuming a strict interpretation of the current policy where again we are assuming evolutionary reads of technological change, no major surprises, that informs the projections. The way that if i were to make an analogy is that Global Energy system is a car, it is basically looking at what happens when you shift it into cruise control. Where do we end up . We explore the key sensitivities in the models through Different Cases but looking at it as a whole, that is the perspective that we take. I was reading a lecture on the duty of the american scholar. There is a great line about the duty of the scholar is showing facts and appearances. Which facts are coming out of this i you think are important for two policymakers to understand . I think the biggest thing is we all, when we think about energy we bring our perspectives. Our own life experience, when we are interpreting the news or receive what is going on. With an exercise like this it is important on the data. It is a very careful exercise to look across the world and to see what is happening and sometimes i think in developed countries we forget about how Much Development is actually taking place. I think for me one of the Key Takeaways is as governments explore futures, just know that there is a backdrop of continued development and that is putting pressure on Energy Demand and that is informing our projections. We are seeing steady or increased use of fossil fuels or use of renewable energy. The clean energy story is taking place in the electricity sector, it is being driven by solar and wind. Then there are other groups that look at global forecasts, i do not want to get into a modeling debate. Help us understand, we are even the events, i took this from this presentation as well as our conversations in the character of the energy as Going Forward is changing rapidly in your areas as well, there is a growth in demand around the world for Energy Services in a costeffective way . How do i understand, in another modeling exercise, another set of projections as this will peak this decade or next decade, what differences are those . Four differences is what differences is that showing us . I think one thing to keep in mind is that you should expect to see big differences across outlooks. I cannot emphasize enough how much uncertainty there is that i think there is always a lot of uncertainty when you produce an outlook like this. We are entering a period of even higher uncertainty. The expectation should not be that you look across outlooks and see the same thing. When you see differences that is healthy. As a modeler i think they converged to the same numbers. Going back and looking we have a long history we have done a lot of projections. Being a modeler requires humility. In all of the outlooks it says the same, we have a problem. You see across the outlooks is healthy. To give you an idea of what drives some of those differences, even if you are looking at another outlook and there is a scenario that looks similar to the eia. How is policy interpreted . I go back to what we did, strict interpretation of existing policy that is legally enforceable. What do they assume about Economic Growth . What do they assume about Technology Innovations . What are the cost pathways for renewables and other technologies. What do you assume about technologies that might be on the horizon that are highly uncertain . Also Consumer Preferences. We are largely doing Economic Modeling here but there is a big piece of this where even with existing policies we are incentivizing consumers and nobody knows exactly how theyre going to respond. I want to touch on uncertainty in a couple of ways, there is a hard version of the question i want to ask. Looking at the various projections, you give us an envelope, i look at that and and i do not know if there is enough uncertainty . I do not know if that is a wide enough fan . In particular on the downside. As an external resource. Maybe we can dive into the example. There is rapid growth and 40 of the auto market chinese auto market is down. Five or 7 depending. Some people will tell you that somewhere around 10 of penetration is the Tipping Point and the Consumer Preferences will shift rapidly towards evs. If that happens you may see a lot of the fossil fuel demand for transportation. Your lines or Greenhouse Gases . It may go down a lot. How does the structure model that kind of . One thing i want to acknowledge as we show uncertainty bands. That is not the full scope of the uncertainty. There is a wide universe of things that can happen. We are clear about how we approach it and what assumptions we make across the bases. We are taking a narrow path through a wide universe. You are not making a forecast . That is not a probability of distribution . There are bands that are wider than that. If i was trying to interpret our outlook in the context of others , think about looking at the projections all in the same chart. Different outlooks made different assumptions and use different models. You are explain different parts of the future and i think that is a healthy exercise. Let me get to evs and i can we can talk about that, i learned a lot. I want to give a little bit of perspective, i will cite some of the numbers but angelina already gave. I think it is important to understand first of all, passenger travel demand will increase by Something Like 65 through over 100 by 2050 across the cases . And that is because there is more people but also they want to travel more miles as they gain wealth. Angelina also mentioned right now we are at about 1. 4 billion lightduty vehicles on the road. That will grow to about 2 billion by 2050 in most of our cases. You have to remember that with electric vehicles it is not just your economics. Pure economics, there are Consumer Preferences. We have some representation of that in our model. Policy interpretation also matters a lot in terms of what you project going into the future from where we are right now. As angelina said before we are finding evs are projected to make up about 30 or 55 of global sales by 2050. If there is a lot of uncertainty. Is it possible that things can unfold in a way where we end up with higher productions . Absolutely. An example, evolutionary rates of technology innovation. We look carefully at the prevailing cost of batteries and how the cost of those lithiumion batteries project into the future. The new battery chemistry, some new breakthrough . All bets are off. Things can change. Host we think about modeling you are doing Something Different because you have modeling choices. What goes into trying to assess a different way around cost curves and social trends. Guest in our National Energy modeling system, we used to produce our annual energy, we have a simplified version of the model for the International Energy outlook. Its not a full model, but it is not just about cost. The factors that go in, this is in one of the technical notes. The cost of the vehicle, cost of driving, and then there is also how many ev models are out there relative to internal combustion engines and fuel availability. As people see more models and see there is more infrastructure of levels to refuel they are more apt to make that purchase. And this is a standard methodology to look at. Vehicle update. Host i always wonder because a car dealership i do not think is a rational place to make a decision. Guest [laughter] host it is good to talk about the tax code association. We are running short on time and a lot of people let me put at put it in a different context. And then you have high and low oil prices. I did not see many differences in the results. Maybe that is in the top line, can you help us understand what we learn in the two cases with respect to the u. S. As a growing producer. Guest sure as far as oil goes, what we see total liquids is around 289 million arrows per day. Very roughly in time. And demand for liquids. The u. S. Peace for that, the u. S. Results are fixed to what we have an annual Energy Outlook. What we found there is that the exporter of petroleum across all cases theres a variation from half a service barrel of nine. Host let me ask you about the future of exercises. Ever the last year i have the pleasure of speaking with those that have different projection forecasts. How do we evolve these tools . In your academic background, im interested in how you are thinking about evolving these tools to inform the estimated inform what you do about these challenges how do you think about making these results more transparent and available to the public or a policymaker where we can get a better understanding of what these models and what these scenarios can teach us. I would love to hear your open thoughts on how we keep innovating to make sure we are meeting information standards. Guest that is a huge question how much time do we have . [laughter] so a few thoughts. The Energy System is in a period of rapid change. And that creates the challenge as energy modelers. We need to make sure our models stay uptodate with what we see happening. Very quickly, i would say with the modeling exercises that we do, we try to be as transparent as possible. I want to say that upfront. If you want to dig into what weve done you can read the narrative. You can read all the documentation for all the modules. You can request the source code and we are planning to make the source code available under a open source license. There is logistics to work through but we are trying to be as transparent as we can. There is that. Where in the process of retooling model. And were taking a break from the annual Energy Outlook in 2024 or we can add that pathways that we need to model. We will do that, but on a parallel track, separate effort, we are building a nextgeneration model. I think the key is by starting with internal and external staples, we need modeling to be nimble and flexible. We need to be able to look at a wide range of scenarios in considerations of what we need to bring to the model is increasing. You mentioned minerals. Thats something we are looking at. So i think going into Critical Minerals i can go in more or would you like to pivot . Host what have you learned . Guest the quick answer is with Critical Minerals we are currently working with the u. S. Geologic survey. Theyve done a lot of work looking at supply chain minerals. We are collaborating with them. We view ourselves as experts in viewing the energy per projections and they understand the supply chain better so were working collaboratively to figure out how we can build this into our models. So with trying to build the supply chain into a modeling framework would be part of this effort to build the next generation model. Host do we have enough information . It is the information keeper for Oil Gas Production in the u. S. We do not have an analog on the minerals. Is there a meaningful analysis in the way that they do on oil and gas side . Guest that is something we have to evaluate. My sense is that you work with the data the that you have. And we look at highlighting important risks and that is valuable. We have to look at it more carefully as we build. Host this is a question that comes from online that is interesting. A question about learning. How do you when you embark on the ipo every year or the ato, and renew the tools we have, you are learning from past successes and failures. Guest good question. I mean, we are in contact with stakeholders. We often have workshops with the next generation modeling. We are actually about to have a series of and engagement of external stakeholders and we can learn from them. We also do model benchmarking work. With the annual Energy Outlook we have retrospection when we look back and see how we did. And we are in the process of trying to expand that work. And i try to go back and look across the past projection and see what we got right or wrong and how that informs our projection moving forward. Host do you see that as a process that can be formalized . Theres a lot of allow us to take in Quantity Information or change projections. Based on what we learned about the time . Is that something we formalize . Guest absolutely. One of the things we did in the Energy Outlook was we had uncertainty costs. You can come up with different projections by putting and changing assumptions in your model. But what it does is look at the difference between the reference case and what we have and it says here are the errors and you get a distribution and then you have a cone that says you may or may not believe our references but when you look at the pass to differences this is where things get head. That is just one example but theres a lot of different ways that you can formalize that, the consideration of that. Host and as you think about putting these scenarios together, do you think about the attempts to make a perimeter estimation . I dont know if i buy this as much but lets say that i do for a moment and i give you access to the source code and you get to learn one thing with absolute precision and accuracy to inform making better projections for our energy future, what would it be . Guest i had access to the real life . Host yeah. Guest like the matrix . Host yes, exactly. Guest i think the biggest challenge we face is it is the human behavioral piece of it. We can characterize cost data. But i think we do not have a good sense for what, as we offer novel technologies, what how do personal preferences influence portable movements. You know, and how does all of that aggregate up in a way that forms whether we are going to would we end up with new policy . Do consumers referred these new technologies . That is a huge challenge we struggle with as model workers. We do the best we can with the data we have, we do not have a good understanding of how human beings are going to respond to external events. Two new technologies and so forth. Host i agree. One of the things that we think about is how we will come from the result of the bipartisan infrastructure law, how quickly does that diffuse around the world. Thats an economics question and Public Policy question and social question. There is a huge variability around that conversation. Guest that is why it is important to, we should not see outlooks expect to see outlooks conforming to the same result because we all make different assumptions. And we all get surprised by certain things, right . [laughter] host right. Ok. We are running against our time window but i want to say we are very pleased that you talked with us today. I think it is an interesting and in some parts provocative set of results. I think it will inform the conversation dodges here in washington, but around the world. In q2 you joe and joe lena. And many of the eia subject matters. Analysts have come today with wedges what is unfortunately the lamest party that i can imagine. But i am pleased we would like to send our appreciation for your hard work and dedication as a public servant. Thank you all. [applause] i wish you well. Everyone joining us in person here and then online our colleagues are signing off and we will see you next time here at csis. [applause] the atlantic council, this is about an hour