WEBVTT 1 00:00:09.999 --> 00:00:11.801 You are listening to Debt Talks, 2 00:00:12.020 --> 00:00:15.868 the podcast of Sian Spoole Chair in Sovereign Debt and Finance. 3 00:00:16.587 --> 00:00:19.485 We're going to be discussing the economics and politics of debt, 4 00:00:19.985 --> 00:00:23.446 exploring past and current episodes of debt distress, 5 00:00:23.915 --> 00:00:25.540 examining legal controversies, 6 00:00:25.837 --> 00:00:26.477 and much more. 7 00:00:27.680 --> 00:00:30.852 Join us for the latest insights and stay tuned on Debt Talks. 8 00:00:42.092 --> 00:00:42.312 Hello, 9 00:00:42.693 --> 00:00:43.354 I'm Paola Subac, 10 00:00:43.393 --> 00:00:44.235 I'm here in Sciences Po. 11 00:00:44.735 --> 00:00:46.075 Today with me is 12 00:00:46.438 --> 00:00:47.336 Thomas Melogno, 13 00:00:47.758 --> 00:00:49.239 Chief Economist at 14 00:00:49.739 --> 00:00:52.965 AFD or Agence Française de Développement. 15 00:00:54.067 --> 00:00:54.504 Welcome, 16 00:00:54.543 --> 00:00:54.942 Thomas. 17 00:00:55.809 --> 00:00:55.989 Hello, 18 00:00:56.168 --> 00:00:56.426 thank you, 19 00:00:56.465 --> 00:00:56.684 Paola, 20 00:00:56.723 --> 00:00:57.231 for having me. 21 00:00:57.684 --> 00:01:03.840 Let's begin our conversation and to focus on a simple but sobering fact, 22 00:01:04.496 --> 00:01:05.387 which is that, 23 00:01:05.512 --> 00:01:06.153 and we know this, 24 00:01:06.309 --> 00:01:08.684 this is a fact everybody's talking about, 25 00:01:08.778 --> 00:01:10.496 and it's progress. 26 00:01:10.684 --> 00:01:13.186 towards achieving the 2030 27 00:01:13.667 --> 00:01:15.249 Sustainable Development Goals, 28 00:01:15.288 --> 00:01:17.390 so the United Nations Sustainable 29 00:01:18.452 --> 00:01:19.296 Development 30 00:01:19.976 --> 00:01:23.733 Goals, has fallen behind expectations. 31 00:01:23.734 --> 00:01:25.921 So now we are mid of the way, 32 00:01:26.843 --> 00:01:30.749 and we know that these are numbers from the United Nations, 33 00:01:30.811 --> 00:01:32.546 that only 17% 34 00:01:32.905 --> 00:01:36.733 of the Sustainable Development Goals are on track. 35 00:01:36.983 --> 00:01:38.093 17%, 36 00:01:38.327 --> 00:01:38.936 one seven. 37 00:01:39.816 --> 00:01:40.737 Nearly half, 38 00:01:40.817 --> 00:01:42.098 so 48%, 39 00:01:42.258 --> 00:01:53.153 are facing serious delays and more than a third are either stagnating or even regressing compared to their 2015 baselines. 40 00:01:53.270 --> 00:01:58.473 So this really is a sober picture. 41 00:01:59.442 --> 00:01:59.739 Obviously, 42 00:01:59.770 --> 00:02:01.332 we know that in the pandemic, 43 00:02:01.457 --> 00:02:03.504 climate-related disasters, 44 00:02:03.660 --> 00:02:04.207 wars, 45 00:02:04.223 --> 00:02:07.035 the rising geopolitical tensions all have... 46 00:02:07.312 --> 00:02:09.012 clearly made things worse. 47 00:02:09.132 --> 00:02:10.712 So that's where we are. 48 00:02:11.294 --> 00:02:11.693 But still, 49 00:02:11.694 --> 00:02:13.533 the overall situation remains dire. 50 00:02:13.654 --> 00:02:15.732 So my key question to you, 51 00:02:15.857 --> 00:02:20.459 and maybe this is a good way to start or a sober way to start our conversation, 52 00:02:21.193 --> 00:02:22.154 what can be done? 53 00:02:23.177 --> 00:02:23.373 Well, 54 00:02:23.451 --> 00:02:29.357 it was clear very early after the SDGs that some of the targets were probably too ambitious, 55 00:02:29.638 --> 00:02:32.435 even before COVID and before the invasion of Ukraine. 56 00:02:33.310 --> 00:02:36.373 There was a high level panel at the UN in 2019, 57 00:02:36.482 --> 00:02:36.638 which 58 00:02:37.244 --> 00:02:41.088 identify a number of targets which probably had been sent too high, 59 00:02:41.107 --> 00:02:42.529 in particular for developing countries, 60 00:02:42.588 --> 00:02:44.932 so that they were almost impossible to reach. 61 00:02:44.990 --> 00:02:46.397 But apart from that, 62 00:02:46.537 --> 00:02:46.912 let's say, 63 00:02:47.178 --> 00:02:48.412 statistical problem, 64 00:02:49.397 --> 00:02:52.217 it's true that after COVID and the war in Ukraine, 65 00:02:53.162 --> 00:02:56.115 the SDGs have become even more difficult to reach. 66 00:02:56.443 --> 00:02:59.225 So now there are many reasons for that. 67 00:02:59.428 --> 00:02:59.693 Some, 68 00:03:00.506 --> 00:03:01.209 as we said, 69 00:03:01.272 --> 00:03:03.756 were related to what happened in the world in the meantime, 70 00:03:03.772 --> 00:03:05.990 but also the fact that we need to 71 00:03:06.552 --> 00:03:11.418 Probably we think how development finance can play a role to actually reach the SDGs. 72 00:03:12.078 --> 00:03:12.199 OK, 73 00:03:12.336 --> 00:03:13.840 can I stop you here a moment? 74 00:03:13.879 --> 00:03:15.578 Because I'm puzzled, 75 00:03:15.579 --> 00:03:15.859 you know. 76 00:03:16.164 --> 00:03:16.984 I'm an economist, 77 00:03:16.985 --> 00:03:17.781 you're an economist. 78 00:03:17.844 --> 00:03:18.945 We deal with numbers. 79 00:03:19.265 --> 00:03:21.047 We deal with facts and evidence, 80 00:03:21.383 --> 00:03:21.804 hopefully. 81 00:03:22.601 --> 00:03:23.383 And again, 82 00:03:23.414 --> 00:03:24.883 I'm surprised, 83 00:03:24.884 --> 00:03:25.351 I think, 84 00:03:25.429 --> 00:03:26.554 the level of ambition. 85 00:03:26.586 --> 00:03:27.195 So again, 86 00:03:27.367 --> 00:03:32.883 I'm basically overshooting these targets because they are too ambitious. 87 00:03:33.711 --> 00:03:35.679 and what about try to make 88 00:03:35.804 --> 00:03:55.931 targets that are achievable without being obviously not ambitious at all but you know they are achievable knowing what we are doing and obviously leaving space for the unknown for shocks the unexpected shocks well i think part of the answer lies in the fact that targets 89 00:03:55.963 --> 00:04:04.291 were not necessarily differentiated enough from the start so you cannot have the same targets in developing developed countries and even in 90 00:04:04.484 --> 00:04:05.585 amongst developing countries, 91 00:04:05.625 --> 00:04:07.786 which is a way too wide category. 92 00:04:07.827 --> 00:04:13.712 I think we should probably set targets based on an honest assessment of the starting point. 93 00:04:13.837 --> 00:04:16.118 That's the first methodological remark. 94 00:04:16.579 --> 00:04:17.454 That's the first methodological remark. 95 00:04:17.455 --> 00:04:17.837 That's to start with. 96 00:04:17.838 --> 00:04:20.298 So starting with a good assessment rather than... 97 00:04:20.337 --> 00:04:21.556 That one. 98 00:04:21.557 --> 00:04:28.790 Then I think probably one of the main advantages and I think progress of the SDGs compared to, 99 00:04:28.868 --> 00:04:29.462 for example, 100 00:04:29.509 --> 00:04:31.243 to the Millennium Development Goals, 101 00:04:31.337 --> 00:04:31.978 which were very... 102 00:04:32.288 --> 00:04:37.134 important in particular for development agencies before 2015, 103 00:04:37.135 --> 00:04:40.255 was that they tried to bring in coherence between social, 104 00:04:40.317 --> 00:04:42.060 economic and environmental objectives. 105 00:04:43.138 --> 00:04:44.458 Whereas in the past, 106 00:04:44.497 --> 00:04:47.146 there were separate agendas for the environment, 107 00:04:47.239 --> 00:04:48.161 social objectives, 108 00:04:48.442 --> 00:04:49.989 or financial and growth objectives. 109 00:04:50.099 --> 00:04:57.317 And this is very important because we can separate economic growth and development from social and human development. 110 00:04:57.349 --> 00:04:59.271 So they have to be part of it. 111 00:04:59.600 --> 00:05:00.981 and obviously environmental development. 112 00:05:01.342 --> 00:05:03.204 They have to be part of the same parcel. 113 00:05:03.243 --> 00:05:07.149 I think it was a huge move forward, 114 00:05:07.950 --> 00:05:08.489 the SDGs, 115 00:05:08.551 --> 00:05:12.770 because they managed to regroup all the various agendas of the United Nations. 116 00:05:12.771 --> 00:05:15.254 So I think that's to stay, 117 00:05:15.497 --> 00:05:17.161 and we absolutely have to keep that, 118 00:05:17.223 --> 00:05:23.364 even though probably some of the targets will not be met and they will have to be discussed at some point between now and 2030. 119 00:05:24.082 --> 00:05:24.504 But still, 120 00:05:24.645 --> 00:05:24.911 we should 121 00:05:25.346 --> 00:05:26.427 keep most of the framework. 122 00:05:26.848 --> 00:05:28.208 I think that's quite important. 123 00:05:29.251 --> 00:05:36.434 The second thing is that probably the tensions between some of the SDGs were underestimated at the start. 124 00:05:36.677 --> 00:05:39.802 We knew that we have to make progress on the environmental front, 125 00:05:40.122 --> 00:05:41.317 as well on the social front, 126 00:05:41.645 --> 00:05:42.224 economic front. 127 00:05:42.911 --> 00:05:43.099 But 128 00:05:43.661 --> 00:05:48.349 I think the tensions between the various objectives were a bit underestimated. 129 00:05:48.614 --> 00:05:50.005 And so the tensions you mean, 130 00:05:50.817 --> 00:05:53.270 what we say the trade-offs between... 131 00:05:54.711 --> 00:05:57.053 Is that what you mean by tensions? 132 00:05:57.054 --> 00:05:58.033 The scientific trade-offs, 133 00:05:58.994 --> 00:05:59.557 they are clear. 134 00:05:59.615 --> 00:06:00.037 Typically, 135 00:06:00.697 --> 00:06:04.881 most scientists will tell you that putting a price on carbon will help reduce carbon emissions. 136 00:06:05.264 --> 00:06:06.022 But at the same time, 137 00:06:06.623 --> 00:06:08.326 it's going to create social issues. 138 00:06:09.061 --> 00:06:10.889 We've seen that in France with the yellow vest, 139 00:06:10.904 --> 00:06:13.014 but we've seen that in many countries. 140 00:06:13.607 --> 00:06:15.436 So there are scientific trade-offs, 141 00:06:15.748 --> 00:06:20.982 and there are also some social trade-offs or political trade-offs for which political solutions need to be imagined. 142 00:06:21.014 --> 00:06:23.764 And sometimes transition needs to be set in place 143 00:06:24.010 --> 00:06:26.371 so that you can manage separate objectives, 144 00:06:26.391 --> 00:06:28.971 but that you want to keep in coherence. 145 00:06:29.209 --> 00:06:42.947 Probably most of the work that researchers need to do right now is precisely about designing transitions to make it possible to actually lead transitions that lead to reaching most of the SDGs. 146 00:06:43.838 --> 00:06:47.776 I think it was underestimated and there was too much evidence. 147 00:06:48.322 --> 00:06:49.088 to interrupt you, 148 00:06:49.089 --> 00:06:50.822 but it is extremely important, 149 00:06:51.463 --> 00:06:52.932 partly because in our series, 150 00:06:52.963 --> 00:06:53.276 in our... 151 00:06:53.898 --> 00:06:54.799 that talk series, 152 00:06:55.760 --> 00:06:58.462 we had some other guests with whom we discussed, 153 00:06:58.482 --> 00:06:58.782 again, 154 00:06:58.802 --> 00:07:02.728 the trade-offs between development and the various areas of development. 155 00:07:02.767 --> 00:07:03.564 Exactly this, 156 00:07:03.565 --> 00:07:03.868 you know, 157 00:07:04.392 --> 00:07:05.892 what do you mean to carbon, 158 00:07:05.970 --> 00:07:14.501 putting a tax on carbon emissions and what you mean in terms of social impact and particularly on the low-income people and so on. 159 00:07:15.001 --> 00:07:21.689 And so it's very interesting because basically we need to design a framework that brings everything together, 160 00:07:21.798 --> 00:07:22.814 otherwise you have 161 00:07:22.958 --> 00:07:25.299 a fragmented policy framework. 162 00:07:25.479 --> 00:07:26.139 Or in other words, 163 00:07:26.159 --> 00:07:30.321 you talk about economic development without thinking in terms of climate and so on. 164 00:07:30.758 --> 00:07:31.797 But at the same time, 165 00:07:31.821 --> 00:07:39.157 you are faced with this type of trade-offs and it is really difficult to find a way to reconcile these trade-offs. 166 00:07:39.766 --> 00:07:40.204 Correct? 167 00:07:40.438 --> 00:07:40.579 Yeah, 168 00:07:40.625 --> 00:07:41.579 that's absolutely correct. 169 00:07:41.580 --> 00:07:42.610 And I think 100% 170 00:07:42.625 --> 00:07:51.204 of governments worldwide are actually looking for solutions to reconcile social objectives and environmental objectives together with their public finance or debt. 171 00:07:51.360 --> 00:07:51.641 This is... 172 00:07:51.926 --> 00:07:53.708 really what they have on their plate. 173 00:07:54.009 --> 00:08:01.718 And a lot of the work we do at EFD in terms of research is precisely about helping governments design their own trajectory towards sustainability. 174 00:08:01.819 --> 00:08:02.374 Sometimes they, 175 00:08:02.975 --> 00:08:03.694 most of the country, 176 00:08:03.741 --> 00:08:03.975 I think, 177 00:08:04.038 --> 00:08:05.639 agree on the destination, 178 00:08:05.741 --> 00:08:10.569 but the way to reach actually that point of destination is very difficult. 179 00:08:10.600 --> 00:08:12.663 What you do in the short term over the next five years, 180 00:08:12.725 --> 00:08:13.069 10 years, 181 00:08:13.100 --> 00:08:13.647 15 years, 182 00:08:14.272 --> 00:08:17.147 to actually maintain the number of jobs in your economy, 183 00:08:17.335 --> 00:08:18.850 but to reduce your carbon emissions, 184 00:08:18.913 --> 00:08:20.007 protect biodiversity. 185 00:08:21.784 --> 00:08:24.145 and at the same time maintain your financial stability. 186 00:08:24.385 --> 00:08:26.948 This is the sort of questions that governments have to face. 187 00:08:26.949 --> 00:08:29.128 And the answers are not trivial. 188 00:08:29.253 --> 00:08:34.573 So they really need to build models or plans to actually implement their transition, 189 00:08:35.714 --> 00:08:38.753 which can be attractive politically speaking over the long term, 190 00:08:38.784 --> 00:08:41.643 but sometimes it's more difficult to manage in the short or medium term. 191 00:08:41.644 --> 00:08:42.346 Exactly. 192 00:08:42.440 --> 00:08:46.424 And you provide the maps for doing this transition. 193 00:08:46.753 --> 00:08:48.424 This is absolutely very true and very, 194 00:08:48.425 --> 00:08:48.862 very important. 195 00:08:48.894 --> 00:08:49.314 important. 196 00:08:49.315 --> 00:08:49.855 So again, 197 00:08:49.935 --> 00:08:50.495 how we go, 198 00:08:51.177 --> 00:08:51.456 I mean, 199 00:08:52.317 --> 00:08:54.120 the destination might be clear. 200 00:08:56.101 --> 00:08:59.788 We might know where we want to go and we want to achieve, 201 00:08:59.882 --> 00:09:07.733 but how we go there is very difficult and because of all these different trade-offs and something that now we are experiencing in the current debate, 202 00:09:07.749 --> 00:09:07.968 you know, 203 00:09:07.969 --> 00:09:08.796 the short term, 204 00:09:09.999 --> 00:09:11.202 there are costs for, 205 00:09:11.749 --> 00:09:12.358 for example, 206 00:09:12.390 --> 00:09:18.437 for environmental sustainability for climate mitigation and climate. 207 00:09:18.558 --> 00:09:18.938 adaptation. 208 00:09:19.519 --> 00:09:21.862 And many countries are reluctant now, 209 00:09:21.921 --> 00:09:24.745 many governments are reluctant to take up those costs, 210 00:09:24.886 --> 00:09:26.046 at least in the short term, 211 00:09:26.226 --> 00:09:29.288 because people feel aggravated, 212 00:09:29.405 --> 00:09:29.710 right? 213 00:09:29.913 --> 00:09:30.030 Yeah. 214 00:09:30.031 --> 00:09:30.468 And sometimes, 215 00:09:30.491 --> 00:09:30.686 I mean, 216 00:09:31.429 --> 00:09:32.530 we can be mistaken here. 217 00:09:32.991 --> 00:09:36.882 Some people believe that it requires more imagination to design the destination point. 218 00:09:37.218 --> 00:09:38.399 rather than the way forward. 219 00:09:39.219 --> 00:09:40.621 But since we are at Sciences Po here, 220 00:09:41.223 --> 00:09:47.926 I think actually imagining the political equation to manage a transition is actually very difficult and requires a lot of creativity. 221 00:09:48.012 --> 00:09:54.457 So let's not assume that what lies in the very distant future is more uncertain than the present. 222 00:09:54.489 --> 00:09:55.864 Sometimes it's the other way around. 223 00:09:56.254 --> 00:09:56.504 Okay, 224 00:09:56.582 --> 00:09:58.832 let's explore now these transitions. 225 00:09:58.942 --> 00:10:01.129 And so back to the question, 226 00:10:01.301 --> 00:10:02.364 what can be done? 227 00:10:02.457 --> 00:10:04.520 So now we've got this very ambitious... 228 00:10:04.521 --> 00:10:06.020 issues. 229 00:10:06.903 --> 00:10:08.884 but very important sustainable development goal. 230 00:10:08.966 --> 00:10:10.247 We are half the way. 231 00:10:10.708 --> 00:10:13.911 We know then it will be difficult to achieve them. 232 00:10:14.747 --> 00:10:15.614 What can be done? 233 00:10:16.349 --> 00:10:16.833 So first, 234 00:10:17.036 --> 00:10:17.169 well, 235 00:10:17.333 --> 00:10:19.333 I'm coming from a financial institution, 236 00:10:19.356 --> 00:10:21.036 so you have to look at the financial gap. 237 00:10:22.036 --> 00:10:23.606 It's been estimated between three, 238 00:10:23.685 --> 00:10:24.403 four trillion. 239 00:10:25.394 --> 00:10:28.117 three to four thousand billion dollars or euros, 240 00:10:28.156 --> 00:10:29.057 it's almost the same. 241 00:10:30.260 --> 00:10:31.842 So it's a huge sum. 242 00:10:32.240 --> 00:10:34.264 And I'd say there are two sort of gaps. 243 00:10:34.865 --> 00:10:46.818 One in the low-income countries is really a pure financial gap where more money needs to be put on the table to actually accelerate the development of these countries. 244 00:10:47.053 --> 00:10:49.615 A good share will actually come from themselves, 245 00:10:50.053 --> 00:10:51.271 from domestic savings, 246 00:10:51.865 --> 00:10:53.881 taxes that that could finance public policies. 247 00:10:55.371 --> 00:10:56.111 private savings, 248 00:10:56.912 --> 00:10:58.475 earmarked towards private investment. 249 00:10:58.476 --> 00:10:59.315 So first, 250 00:10:59.494 --> 00:11:00.615 even in low-income countries, 251 00:11:01.436 --> 00:11:04.162 most of the money or the investment needed will come from themselves. 252 00:11:04.264 --> 00:11:05.943 But still, 253 00:11:05.959 --> 00:11:07.342 there's room for international action there, 254 00:11:07.561 --> 00:11:09.568 in particular for the poorest countries. 255 00:11:09.701 --> 00:11:10.107 Can I, 256 00:11:10.529 --> 00:11:10.842 again, 257 00:11:12.451 --> 00:11:14.826 unpick this domestic mobilisation? 258 00:11:15.154 --> 00:11:19.217 I've been involved in a couple of projects recently on domestic mobilisation, 259 00:11:19.248 --> 00:11:23.686 mainly providing expertise on some policy 260 00:11:24.438 --> 00:11:24.939 on this. 261 00:11:26.360 --> 00:11:26.481 And, 262 00:11:26.482 --> 00:11:26.761 you know, 263 00:11:26.901 --> 00:11:27.442 as you said, 264 00:11:27.561 --> 00:11:29.923 we can mobilize domestic capital, 265 00:11:29.942 --> 00:11:32.266 we can have more efficient tax systems, 266 00:11:32.345 --> 00:11:34.766 we can use domestic savings. 267 00:11:35.110 --> 00:11:39.313 But the reality is that many low-income countries do not have much savings. 268 00:11:39.376 --> 00:11:40.899 They tend to have low savings. 269 00:11:41.430 --> 00:11:47.321 And so the scope for domestic mobilization of capital is very limited. 270 00:11:47.884 --> 00:11:52.868 It's clear that many low-income countries are sort of trapped in a situation where 271 00:11:53.286 --> 00:11:54.107 taxes are too low, 272 00:11:54.308 --> 00:11:55.669 between 10 and 15% 273 00:11:55.729 --> 00:11:56.149 of GDP. 274 00:11:56.890 --> 00:11:58.894 And you cannot finance your education system, 275 00:11:59.011 --> 00:11:59.632 health system, 276 00:11:59.972 --> 00:12:01.214 public investment in general, 277 00:12:01.894 --> 00:12:04.315 on taxes if they represent only 15% 278 00:12:04.378 --> 00:12:04.761 of GDP. 279 00:12:05.136 --> 00:12:06.136 Just to give you an example, 280 00:12:06.198 --> 00:12:07.058 when 50% 281 00:12:07.059 --> 00:12:08.542 of your population is below 18, 282 00:12:08.839 --> 00:12:10.362 they should be in the education system, 283 00:12:10.409 --> 00:12:13.831 but it's going to require much more than 3 or 4% 284 00:12:14.019 --> 00:12:14.440 of GDP. 285 00:12:15.362 --> 00:12:16.472 So here, 286 00:12:16.987 --> 00:12:18.409 they're going to need to have to agree, 287 00:12:18.534 --> 00:12:21.894 and that's a complex domestic political equation, 288 00:12:21.956 --> 00:12:22.237 but to... 289 00:12:22.410 --> 00:12:23.450 to raise more taxes. 290 00:12:23.690 --> 00:12:27.172 That's really for the most important public services. 291 00:12:27.609 --> 00:12:32.535 Then you have savings that in many economic models are equal to investment. 292 00:12:33.269 --> 00:12:34.472 When the economy is closed, 293 00:12:34.473 --> 00:12:35.613 when the economy is open, 294 00:12:35.652 --> 00:12:36.871 you can borrow from elsewhere, 295 00:12:36.910 --> 00:12:37.293 but still, 296 00:12:38.137 --> 00:12:38.941 generally speaking, 297 00:12:39.254 --> 00:12:42.207 most of the time investment is close to savings. 298 00:12:42.738 --> 00:12:43.207 And again, 299 00:12:43.316 --> 00:12:44.488 as you rightly said, 300 00:12:45.160 --> 00:12:46.097 when you have investment, 301 00:12:46.254 --> 00:12:47.129 which is just 20, 302 00:12:47.238 --> 00:12:47.863 25% 303 00:12:47.941 --> 00:12:48.332 of GDP, 304 00:12:48.457 --> 00:12:49.551 it's not enough to really 305 00:12:51.754 --> 00:12:57.179 Launch your growth and get out of poverty like typically the Asian tigers did. 306 00:12:57.679 --> 00:12:58.359 In their case, 307 00:12:58.902 --> 00:13:01.824 savings and investment were roughly 35, 308 00:13:01.847 --> 00:13:02.465 sometimes 40% 309 00:13:02.863 --> 00:13:03.285 of GDP. 310 00:13:03.668 --> 00:13:07.027 This is what you really need to get out of poverty quickly. 311 00:13:08.090 --> 00:13:10.308 And there are many countries in Latin America, 312 00:13:10.996 --> 00:13:11.574 in Africa, 313 00:13:11.715 --> 00:13:14.230 sometimes in some parts of Asia as well, 314 00:13:14.590 --> 00:13:18.386 where savings are too low and investment as a result is too low. 315 00:13:19.482 --> 00:13:23.103 Sometimes laws in economics are not really laws in the sense of physics, 316 00:13:23.823 --> 00:13:24.042 but 317 00:13:24.683 --> 00:13:28.780 I've never seen any country really develop without a high level of savings and investment, 318 00:13:29.163 --> 00:13:31.327 at least in the first stages of development. 319 00:13:31.366 --> 00:13:31.984 Absolutely. 320 00:13:32.187 --> 00:13:33.124 And then again, 321 00:13:33.624 --> 00:13:34.343 you mentioned the 322 00:13:35.226 --> 00:13:36.179 Asian tigers, 323 00:13:36.413 --> 00:13:39.663 obviously the integration in the world economy through trade. 324 00:13:40.288 --> 00:13:43.913 And this is a good topic now, 325 00:13:44.726 --> 00:13:48.007 particularly now that we all talk about trade policies. 326 00:13:48.270 --> 00:13:48.510 I mean, 327 00:13:48.590 --> 00:13:49.471 for these countries, 328 00:13:49.531 --> 00:13:50.271 being integrated, 329 00:13:50.332 --> 00:13:53.754 being able to export or have access to external markets was very, 330 00:13:53.755 --> 00:13:54.535 very important. 331 00:13:54.578 --> 00:13:57.359 And that obviously developed, 332 00:13:57.360 --> 00:13:57.797 you know, 333 00:13:57.859 --> 00:13:59.297 loan to also investment, 334 00:13:59.578 --> 00:14:00.664 capital inflows, 335 00:14:00.742 --> 00:14:05.891 and sort of created a virtual circle of development and growth. 336 00:14:05.892 --> 00:14:06.234 Yeah, 337 00:14:06.235 --> 00:14:08.344 openness has mattered in the case of Asia, 338 00:14:08.438 --> 00:14:08.812 for sure, 339 00:14:08.891 --> 00:14:13.578 but also having a very high level of savings and therefore investment. 340 00:14:15.062 --> 00:14:15.250 Also, 341 00:14:15.844 --> 00:14:17.703 most of them developed their education system. 342 00:14:18.014 --> 00:14:18.654 infrastructure. 343 00:14:18.655 --> 00:14:32.961 So most of the time they were also they opened their capital account to attract investment and next to investment actually it's not it was a bit about the money but mostly about attracting technology and know-how from foreign countries. 344 00:14:32.962 --> 00:14:41.258 So very clearly in early Japan at the end of 19th century but also in many Asian countries that attracted foreign direct investment. 345 00:14:42.242 --> 00:14:42.726 again it's 346 00:14:43.334 --> 00:14:45.576 Partly to limit the shortage in capital, 347 00:14:45.617 --> 00:14:46.197 but mostly, 348 00:14:46.258 --> 00:14:46.738 I would say, 349 00:14:46.777 --> 00:14:55.629 to attract technology and know-how to then boost their productivity and become advanced economies as they have in a number of cases. 350 00:14:56.027 --> 00:14:56.145 Yeah. 351 00:14:56.707 --> 00:14:57.027 Again, 352 00:14:57.106 --> 00:14:57.707 that is it. 353 00:14:57.832 --> 00:14:58.410 So again, 354 00:14:58.731 --> 00:15:06.942 harnessing where it's possible domestic capital and but also getting international capital. 355 00:15:06.957 --> 00:15:09.473 So you mentioned foreign direct investment, 356 00:15:09.567 --> 00:15:11.285 which is should be the first. 357 00:15:11.666 --> 00:15:18.012 a most important channel for investment and development in low-income developing countries. 358 00:15:18.352 --> 00:15:18.493 Well, 359 00:15:18.672 --> 00:15:19.493 FDI matters. 360 00:15:19.778 --> 00:15:25.176 Maybe I should also explain probably what development banks and international development banks can do, 361 00:15:26.301 --> 00:15:27.903 because in many instances they... 362 00:15:28.331 --> 00:15:37.419 They bring in capital but also know-how or technical and technological skills to boost investment. 363 00:15:37.458 --> 00:15:43.568 So in that case we still call that official development assistance but truly it's about development finance, 364 00:15:43.849 --> 00:15:51.146 it's about technical cooperation that are brought together by advanced economies or advanced countries towards developing economies. 365 00:15:51.521 --> 00:15:55.958 And in that case the volume of finance mobilized. 366 00:15:56.815 --> 00:15:57.876 from abroad will matter, 367 00:15:57.936 --> 00:16:04.202 but also the technical content and the sharing of know-how or knowledge between countries. 368 00:16:04.203 --> 00:16:08.464 I think it's a very important contribution that development banks can play. 369 00:16:08.909 --> 00:16:09.729 It's true for EFD, 370 00:16:09.972 --> 00:16:12.409 but also the World Bank or German counterpart, 371 00:16:13.026 --> 00:16:15.729 KfW or Japanese corporation for example, 372 00:16:16.151 --> 00:16:22.573 because typically when a country wants to invest in a metro system or in water and sanitation, 373 00:16:23.386 --> 00:16:24.276 it's not just about money. 374 00:16:25.075 --> 00:16:26.296 also about engineers, 375 00:16:26.877 --> 00:16:30.561 people who know how to run a water or electricity network, 376 00:16:30.600 --> 00:16:31.183 for example, 377 00:16:31.620 --> 00:16:38.386 and are able to provide advice on how to do it and also sharing their knowledge with their domestic counterparts. 378 00:16:38.792 --> 00:16:38.933 Yeah. 379 00:16:39.026 --> 00:16:39.526 And in fact, 380 00:16:39.527 --> 00:16:42.745 we had a couple of episodes on development banks, 381 00:16:42.839 --> 00:16:44.495 on multilateral development banks, 382 00:16:44.496 --> 00:16:45.854 on national development banks. 383 00:16:46.464 --> 00:16:47.370 And there again, 384 00:16:48.354 --> 00:16:54.370 we really look into this type of mechanism where there isn't is not just 385 00:16:54.955 --> 00:16:55.536 Finance, 386 00:16:55.596 --> 00:16:58.118 but is again technical capacity, 387 00:16:58.379 --> 00:16:59.321 expertise, 388 00:16:59.360 --> 00:17:01.262 the support to project. 389 00:17:01.840 --> 00:17:03.543 And in some cases also grants, 390 00:17:03.622 --> 00:17:06.082 because grants are important, 391 00:17:06.106 --> 00:17:06.887 because again, 392 00:17:06.926 --> 00:17:16.254 there are countries that are very poor and for whom the grant is a way to start the process of development. 393 00:17:16.379 --> 00:17:21.754 And there is no way then even a concessional loan will be able to be, 394 00:17:22.676 --> 00:17:23.348 to sort of 395 00:17:23.967 --> 00:17:26.050 trigger this type of development. 396 00:17:26.290 --> 00:17:26.409 Yeah, 397 00:17:26.450 --> 00:17:28.874 maybe just a word here because this is about debt talks. 398 00:17:29.972 --> 00:17:40.148 Just to explain that most international public development banks work against the basic market principle because we lend at higher rates to the best customers, 399 00:17:40.429 --> 00:17:43.491 meaning the most advanced developing economies. 400 00:17:44.070 --> 00:17:45.023 But in poorer countries, 401 00:17:45.132 --> 00:17:48.007 we do mostly grants or subsidized loans, 402 00:17:48.304 --> 00:17:51.898 meaning concessional loans at really low rates, 403 00:17:52.320 --> 00:17:53.195 which is not what the... 404 00:17:56.073 --> 00:18:00.776 typical commercial banks do because they tend to lend at lower rates to their richer customers. 405 00:18:01.542 --> 00:18:02.683 We do it the other way around, 406 00:18:03.159 --> 00:18:03.479 of course, 407 00:18:03.518 --> 00:18:06.401 because we have support from states and citizens. 408 00:18:06.643 --> 00:18:06.925 Yes, 409 00:18:07.003 --> 00:18:07.464 exactly. 410 00:18:07.925 --> 00:18:11.550 And the complexity also the operation of the multilateral value bank, 411 00:18:11.565 --> 00:18:12.409 because as you said, 412 00:18:12.456 --> 00:18:15.753 they are supported by what we say taxpayer money. 413 00:18:16.018 --> 00:18:18.831 And so obviously there is is an obligation to... 414 00:18:19.215 --> 00:18:24.581 be careful but at the same time an obligation to use this money to help development. 415 00:18:24.639 --> 00:18:24.882 And so, 416 00:18:24.940 --> 00:18:25.663 as you said, 417 00:18:26.280 --> 00:18:30.124 not necessarily the best customers are those who can have the best, 418 00:18:30.608 --> 00:18:31.483 actually, 419 00:18:31.530 --> 00:18:35.514 that don't get the best conditions and the most favorable conditions. 420 00:18:35.624 --> 00:18:36.092 Absolutely. 421 00:18:36.858 --> 00:18:38.155 Institutions like the World Bank, 422 00:18:38.171 --> 00:18:39.780 but also EFD or KfW, 423 00:18:40.139 --> 00:18:44.983 actually make more money in the richest developing countries. 424 00:18:45.347 --> 00:18:49.569 to make internal transfers towards the lowest income countries. 425 00:18:49.671 --> 00:18:49.850 Yeah. 426 00:18:49.952 --> 00:18:50.350 And again, 427 00:18:50.413 --> 00:18:58.460 there is this transfer mechanism that is necessary in order to get capital to mobilise in developing countries. 428 00:18:59.460 --> 00:18:59.843 But let me, 429 00:19:00.022 --> 00:19:01.163 this is all very interesting. 430 00:19:01.225 --> 00:19:01.546 Again, 431 00:19:01.780 --> 00:19:05.968 we've been kept our conversation so far at a very high level. 432 00:19:06.249 --> 00:19:08.577 So the principle of everything would be, 433 00:19:09.264 --> 00:19:09.655 you know, 434 00:19:09.827 --> 00:19:13.733 if we had the magic wand to be able to get the world as we like it. 435 00:19:14.059 --> 00:19:19.003 But let's get into more details on practical and policy-oriented, 436 00:19:19.124 --> 00:19:19.664 you know, 437 00:19:19.804 --> 00:19:21.144 intervention and actions. 438 00:19:21.648 --> 00:19:22.691 And so I was actually, 439 00:19:22.964 --> 00:19:30.128 I read one of your recent papers where you discussed the opportunities offered by artificial intelligence. 440 00:19:30.160 --> 00:19:34.566 And I thought it was very interesting to really bring the artificial intelligence, 441 00:19:34.613 --> 00:19:37.347 which is now everybody talks about it, 442 00:19:37.348 --> 00:19:37.722 you know, 443 00:19:37.925 --> 00:19:39.832 AI is all over the place. 444 00:19:40.191 --> 00:19:40.863 But then again, 445 00:19:40.925 --> 00:19:41.660 in your paper, 446 00:19:41.753 --> 00:19:42.832 you asked the question, 447 00:19:43.082 --> 00:19:43.550 how? 448 00:19:44.071 --> 00:19:45.373 Developing countries, 449 00:19:45.412 --> 00:19:47.916 and particularly the low-income countries, 450 00:19:48.275 --> 00:19:54.357 could actually have access to the opportunities offered by AI, 451 00:19:55.662 --> 00:20:02.170 be also protected by the challenges that AI obviously poses, 452 00:20:03.123 --> 00:20:08.435 but at the same time being part of this big change in the world and not be left behind, 453 00:20:08.482 --> 00:20:12.857 because there is a big risk here that countries then cannot be part of this process. 454 00:20:13.403 --> 00:20:21.568 will basically become the gap with the more advanced economies will be even wider. 455 00:20:22.232 --> 00:20:23.810 And the paper was very interesting. 456 00:20:25.294 --> 00:20:32.341 We'd like to explore a bit more the question you explore in that paper. 457 00:20:32.768 --> 00:20:33.408 Well, 458 00:20:33.428 --> 00:20:35.408 the initial question with my co-authors, 459 00:20:36.068 --> 00:20:36.449 Peter, 460 00:20:36.589 --> 00:20:36.871 Laure, 461 00:20:36.910 --> 00:20:37.390 Anastasia, 462 00:20:37.449 --> 00:20:38.351 was really about is there 463 00:20:39.808 --> 00:20:42.812 AI, is it only about the competition between China and the US? 464 00:20:44.031 --> 00:20:47.468 Maybe Europe partly in that conversation, 465 00:20:47.531 --> 00:20:51.586 but is the story over once we have said that this will be the major players? 466 00:20:52.054 --> 00:20:55.257 Or will there be a potential, 467 00:20:55.289 --> 00:20:56.039 whether in Africa, 468 00:20:56.132 --> 00:20:57.601 Latin America and the rest of Asia, 469 00:20:58.226 --> 00:21:00.367 to not only be customers of AI products, 470 00:21:00.429 --> 00:21:00.898 but also... 471 00:21:01.420 --> 00:21:03.722 participate in the production of AI products. 472 00:21:04.443 --> 00:21:06.804 And there's a variety of AI products, 473 00:21:06.843 --> 00:21:07.246 by the way. 474 00:21:08.328 --> 00:21:10.609 It's not just large language models. 475 00:21:11.414 --> 00:21:12.593 I think it's a more complex story. 476 00:21:12.632 --> 00:21:15.632 But the idea was really to ask ourselves, 477 00:21:15.656 --> 00:21:18.851 and we did not know the questions when we started this paper, 478 00:21:18.914 --> 00:21:22.695 and the conclusions were actually quite different from what I thought in the first place. 479 00:21:22.976 --> 00:21:27.179 But what we did was look at where the AI investment in the world takes place. 480 00:21:27.523 --> 00:21:28.507 Is it only in the US, 481 00:21:28.523 --> 00:21:30.804 in China or is it a little bit everywhere? 482 00:21:31.244 --> 00:21:35.429 and what are the factors that actually explain the current investment in AI. 483 00:21:36.371 --> 00:21:39.394 First it was to draw a map and in the paper you can see maps of where 484 00:21:40.074 --> 00:21:45.996 AI is actually growing but also asking ourselves what can governments do to increase their potential. 485 00:21:47.316 --> 00:21:53.566 Part of the answers I think really were straightforward and we were not surprised to see that you need infrastructure, 486 00:21:53.660 --> 00:21:56.285 broadband access to grow AI. 487 00:21:56.707 --> 00:21:58.878 I was a bit surprised to see the importance of 488 00:22:00.169 --> 00:22:00.950 of research, 489 00:22:01.210 --> 00:22:02.811 training of PhDs in AI, 490 00:22:03.292 --> 00:22:04.411 and the quality of data, 491 00:22:04.755 --> 00:22:05.755 including public data, 492 00:22:05.813 --> 00:22:06.255 by the way, 493 00:22:07.575 --> 00:22:10.020 to help grow an AI ecosystem, 494 00:22:10.380 --> 00:22:11.903 even sometimes in small countries. 495 00:22:13.184 --> 00:22:13.301 So, 496 00:22:13.864 --> 00:22:14.161 of course, 497 00:22:14.162 --> 00:22:16.966 there will be more AI companies in the US or in China, 498 00:22:17.028 --> 00:22:18.294 but relative to the economy, 499 00:22:19.012 --> 00:22:19.606 some countries, 500 00:22:19.622 --> 00:22:20.091 for example, 501 00:22:20.153 --> 00:22:21.669 Mauritius or Singapore, 502 00:22:21.731 --> 00:22:22.637 can do very well, 503 00:22:23.419 --> 00:22:25.247 despite their limited market size. 504 00:22:25.278 --> 00:22:25.387 So, 505 00:22:25.653 --> 00:22:26.950 there's still a place apart from... 506 00:22:27.312 --> 00:22:28.394 huge data centers, 507 00:22:28.395 --> 00:22:29.755 the training of very big models, 508 00:22:30.114 --> 00:22:31.376 but you can still develop apps, 509 00:22:31.696 --> 00:22:33.357 you can still develop applications, 510 00:22:33.540 --> 00:22:35.821 you can still implement AI within your companies, 511 00:22:36.439 --> 00:22:39.626 you can develop really context-specific, 512 00:22:39.704 --> 00:22:45.774 time-specific use cases for AI even in relatively small or poor economies. 513 00:22:46.384 --> 00:22:48.415 And I think that was somewhat of a surprise, 514 00:22:49.071 --> 00:22:52.899 but it leads to conclusion on where exactly a government should invest. 515 00:22:53.748 --> 00:22:55.831 to make it possible because it doesn't happen everywhere. 516 00:22:55.911 --> 00:22:58.093 It's in a limited number of countries, 517 00:22:58.112 --> 00:22:58.714 but it's possible. 518 00:22:58.854 --> 00:22:59.034 Yeah, 519 00:22:59.155 --> 00:23:08.682 it is a bit counterintuitive because what you expect is obviously investment in AI in countries that have the capacity to invest. 520 00:23:08.901 --> 00:23:10.448 So obviously in the United States, 521 00:23:11.042 --> 00:23:17.636 because we have a huge industry around innovation and technology, 522 00:23:18.167 --> 00:23:19.714 and we have an infrastructure, 523 00:23:20.057 --> 00:23:22.917 a financial infrastructure that allows this investment. 524 00:23:24.069 --> 00:23:24.329 Obviously, 525 00:23:24.409 --> 00:23:25.690 China is another case, 526 00:23:25.751 --> 00:23:26.052 obviously, 527 00:23:26.110 --> 00:23:30.255 with different sort of features of this financial infrastructure, 528 00:23:30.735 --> 00:23:32.157 but is another case and there is, 529 00:23:32.516 --> 00:23:32.876 again, 530 00:23:33.516 --> 00:23:36.704 a very strong industrial policy then. 531 00:23:37.579 --> 00:23:38.282 But then again, 532 00:23:38.345 --> 00:23:39.821 it's a bit different in Europe. 533 00:23:39.930 --> 00:23:44.102 But then you think about the really small and less, 534 00:23:45.649 --> 00:23:52.259 small developing countries and you Why do they have a cluster that will allow them to 535 00:23:52.952 --> 00:23:56.274 have these types of companies or you see them, 536 00:23:56.275 --> 00:23:56.997 you know, 537 00:23:57.255 --> 00:24:04.661 obviously say what you expect and probably that's what you expected before this research you did is like, 538 00:24:05.200 --> 00:24:05.403 well, 539 00:24:05.622 --> 00:24:08.349 they can be consumer of AI products, 540 00:24:08.450 --> 00:24:11.685 but not innovators on this. 541 00:24:12.044 --> 00:24:15.075 But obviously your research proved then that is possible. 542 00:24:15.622 --> 00:24:15.731 Well, 543 00:24:15.872 --> 00:24:18.013 just two years ago or even one year ago, 544 00:24:18.075 --> 00:24:20.685 the major AI companies were saying that because you 545 00:24:21.288 --> 00:24:22.369 huge data centers, 546 00:24:22.429 --> 00:24:24.412 a huge amount of data, 547 00:24:24.531 --> 00:24:29.836 plus very important and large models to develop an LLM. 548 00:24:29.898 --> 00:24:30.476 For example, 549 00:24:30.500 --> 00:24:33.742 it would require 10 to 15 billion to train an LLM. 550 00:24:34.242 --> 00:24:37.367 Then we have seen some open source models from China, 551 00:24:37.398 --> 00:24:39.367 but also from other countries. 552 00:24:39.461 --> 00:24:39.945 That's right. 553 00:24:40.429 --> 00:24:41.554 Making it available. 554 00:24:41.555 --> 00:24:45.179 And even the code of these models have become available. 555 00:24:45.211 --> 00:24:48.929 So we could have imagined a very closed system. 556 00:24:49.444 --> 00:24:52.447 typically similar to operating systems into these computers, 557 00:24:52.808 --> 00:24:56.450 really with a limited competition in a very big economies. 558 00:24:56.892 --> 00:25:02.275 And now even models seem to be more accessible and even they are content for other countries. 559 00:25:02.314 --> 00:25:03.079 That's one thing. 560 00:25:03.478 --> 00:25:05.220 Of course, 561 00:25:05.728 --> 00:25:09.884 we know now the part of the job will be to implement AI within companies, 562 00:25:09.978 --> 00:25:10.868 within governments, 563 00:25:11.009 --> 00:25:12.009 within NGOs, 564 00:25:12.540 --> 00:25:12.947 wherever. 565 00:25:13.009 --> 00:25:13.353 That's not, 566 00:25:13.384 --> 00:25:13.665 I think, 567 00:25:13.728 --> 00:25:14.712 not really the problem, 568 00:25:14.728 --> 00:25:16.868 but implementation of models on... 569 00:25:17.991 --> 00:25:20.594 Data within institutions will matter probably more. 570 00:25:21.235 --> 00:25:26.118 And the capacity to code will be accessible even in relatively low-income countries, 571 00:25:26.618 --> 00:25:29.641 as long as they have developed human capacities to do it. 572 00:25:30.219 --> 00:25:31.680 If you don't have the talent in your country, 573 00:25:31.766 --> 00:25:32.422 it's not going to happen. 574 00:25:33.047 --> 00:25:36.227 But you can do it with a limited number of persons, 575 00:25:36.649 --> 00:25:41.789 if you have in your higher education system particular trainings. 576 00:25:43.074 --> 00:25:43.555 We have seen, 577 00:25:43.595 --> 00:25:44.095 for example, 578 00:25:44.096 --> 00:25:49.843 the number of articles published related to AI in scientific reviews having a strong connection with actual investment. 579 00:25:50.280 --> 00:25:51.241 And it's not always the case. 580 00:25:51.280 --> 00:25:53.804 Sometimes you have research in a country and no particular company. 581 00:25:54.304 --> 00:25:55.405 But in the case of AI, 582 00:25:55.827 --> 00:26:01.452 we've seen really a stronger connection between the investment in the field and the existing, 583 00:26:02.577 --> 00:26:02.999 typically, 584 00:26:03.233 --> 00:26:04.171 universities, 585 00:26:04.249 --> 00:26:04.671 training, 586 00:26:04.749 --> 00:26:05.218 master's, 587 00:26:05.249 --> 00:26:07.937 PhD curricula in the country. 588 00:26:08.155 --> 00:26:11.999 So basically you say then investment in AI drives... 589 00:26:14.919 --> 00:26:15.478 research. 590 00:26:15.718 --> 00:26:15.839 So, 591 00:26:15.840 --> 00:26:16.439 you know, 592 00:26:16.798 --> 00:26:18.200 investment in human capital, 593 00:26:18.818 --> 00:26:19.880 in the governance of data, 594 00:26:20.302 --> 00:26:21.521 production of data, 595 00:26:21.677 --> 00:26:26.263 is strongly associated with investment in AI and the emergence of AI companies. 596 00:26:26.583 --> 00:26:26.880 Right, 597 00:26:27.083 --> 00:26:27.341 right. 598 00:26:27.404 --> 00:26:28.279 And so basically, 599 00:26:29.060 --> 00:26:29.685 the thing is, 600 00:26:29.763 --> 00:26:32.575 we could have countries, 601 00:26:32.700 --> 00:26:32.966 you know, 602 00:26:33.075 --> 00:26:34.841 developing countries can have their own 603 00:26:35.560 --> 00:26:36.638 AI companies, 604 00:26:36.825 --> 00:26:39.247 but we need to have to ensure then the 605 00:26:40.871 --> 00:26:42.172 human capital is there. 606 00:26:42.312 --> 00:26:43.293 So in other words, 607 00:26:43.314 --> 00:26:46.955 you got the skills that are necessary for developing these companies. 608 00:26:47.096 --> 00:26:48.736 And it's a message for universities, 609 00:26:48.799 --> 00:26:52.361 but also for development agencies like EFD or the World Bank or others. 610 00:26:53.025 --> 00:26:53.642 And recently, 611 00:26:53.705 --> 00:26:53.963 actually, 612 00:26:53.964 --> 00:26:54.463 the World Bank, 613 00:26:54.464 --> 00:26:54.947 for example, 614 00:26:54.986 --> 00:26:58.189 has created a vice presidency for digital economy, 615 00:26:59.002 --> 00:27:02.658 which probably is going to involve investing in creating capacities, 616 00:27:02.689 --> 00:27:03.799 including human capacities. 617 00:27:04.158 --> 00:27:05.596 Human capacity is a case. 618 00:27:05.642 --> 00:27:06.111 But again, 619 00:27:06.221 --> 00:27:07.252 this is why is 620 00:27:09.023 --> 00:27:11.244 I wouldn't say long-term proposition, 621 00:27:11.305 --> 00:27:16.608 but certainly it's a medium-term proposition because you need to create the right skills. 622 00:27:16.631 --> 00:27:20.858 You need to have the training courses, 623 00:27:21.694 --> 00:27:23.420 the university programs, 624 00:27:23.576 --> 00:27:26.280 whatever in place to train the right people. 625 00:27:26.326 --> 00:27:32.780 So it's not something that will deliver an outcome tomorrow. 626 00:27:33.045 --> 00:27:34.326 It will take a while. 627 00:27:35.155 --> 00:27:35.561 Absolutely. 628 00:27:35.623 --> 00:27:37.373 And one of the reasons why... 629 00:27:37.662 --> 00:27:40.986 we might need or countries might need their capacities that 630 00:27:41.726 --> 00:27:43.449 AI models trained in English, 631 00:27:43.488 --> 00:27:44.167 for example, 632 00:27:44.168 --> 00:27:45.953 in the US context or in Chinese, 633 00:27:45.954 --> 00:27:46.914 in the Chinese context, 634 00:27:47.312 --> 00:27:49.835 will not necessarily be relevant in Senegal, 635 00:27:49.875 --> 00:27:50.414 in Morocco, 636 00:27:50.554 --> 00:27:51.335 in South Africa. 637 00:27:52.679 --> 00:27:53.039 Recently, 638 00:27:53.078 --> 00:27:56.484 we had an experience and a program with the Bibliothèque Sans Frontières, 639 00:27:56.781 --> 00:27:57.796 Libraries Without Borders, 640 00:27:57.797 --> 00:28:03.140 to develop educational content in a number of Senegalese languages, 641 00:28:04.281 --> 00:28:04.750 Poulard, 642 00:28:04.781 --> 00:28:05.312 the language for 643 00:28:05.466 --> 00:28:06.207 the poll community, 644 00:28:06.327 --> 00:28:07.448 probably tomorrow in Wolof, 645 00:28:08.249 --> 00:28:10.349 with official content for their country, 646 00:28:10.450 --> 00:28:12.071 but in national languages, 647 00:28:12.474 --> 00:28:13.454 which did not exist. 648 00:28:14.755 --> 00:28:18.943 And I think it's very important that many countries can enjoy the benefits of AI. 649 00:28:19.380 --> 00:28:21.021 There are risks associated with AI as well, 650 00:28:21.060 --> 00:28:27.544 but it must be really adapted to their context. 651 00:28:27.966 --> 00:28:28.122 Yeah, 652 00:28:28.575 --> 00:28:35.122 because this again is very interesting and again is a way to say there's no point to just put 653 00:28:35.618 --> 00:28:35.858 You know, 654 00:28:35.918 --> 00:28:40.601 financial capital in a country and in certain investment, 655 00:28:40.945 --> 00:28:43.387 if we don't have the right skills, 656 00:28:43.508 --> 00:28:46.891 the right human capital. 657 00:28:46.969 --> 00:28:48.633 So the two need to be together. 658 00:28:48.789 --> 00:28:53.656 So it would be a waste to some extent if we don't have the right skills. 659 00:28:53.657 --> 00:28:58.953 So we need to prepare the ground before the investment can really take place. 660 00:28:59.406 --> 00:28:59.515 Yeah, 661 00:28:59.547 --> 00:28:59.969 absolutely. 662 00:28:59.970 --> 00:29:00.187 I mean, 663 00:29:00.578 --> 00:29:01.515 it goes all together, 664 00:29:01.562 --> 00:29:03.344 the governance of a particular sector. 665 00:29:03.898 --> 00:29:05.560 Infrastructure and human capital. 666 00:29:06.461 --> 00:29:07.642 Sometimes in development, 667 00:29:07.800 --> 00:29:08.121 I mean, 668 00:29:09.004 --> 00:29:10.707 it's a world where there are fashions. 669 00:29:10.726 --> 00:29:11.484 So at some point, 670 00:29:11.605 --> 00:29:13.566 microcredit was supposed to save the world. 671 00:29:13.590 --> 00:29:15.027 Then it's all about human capital, 672 00:29:15.050 --> 00:29:15.988 then it's all infrastructure. 673 00:29:16.011 --> 00:29:16.949 But truly, 674 00:29:17.215 --> 00:29:24.535 no country has developed without a combination of the various basic but essential elements of an advanced economy. 675 00:29:24.972 --> 00:29:25.144 Yeah. 676 00:29:25.582 --> 00:29:26.300 And again, 677 00:29:26.582 --> 00:29:27.925 developing human capital, 678 00:29:27.926 --> 00:29:28.379 as we know, 679 00:29:28.457 --> 00:29:33.582 because sometimes the countries they need to decide how they allocate their... 680 00:29:34.611 --> 00:29:39.077 scarce financial resources and sometimes they need to, 681 00:29:39.854 --> 00:29:41.077 they have other priorities. 682 00:29:41.116 --> 00:29:41.815 So again, 683 00:29:41.979 --> 00:29:45.901 this is an area of intervention for development banks, 684 00:29:46.221 --> 00:29:52.049 like developing skills and education or very specific skills and education. 685 00:29:52.143 --> 00:29:52.612 Absolutely. 686 00:29:52.674 --> 00:29:52.893 I mean, 687 00:29:53.487 --> 00:29:53.768 again, 688 00:29:53.846 --> 00:29:55.346 because this is a Deb Talks, 689 00:29:56.268 --> 00:30:00.221 we must actually interrogate development banks like AFD. 690 00:30:01.110 --> 00:30:02.552 on the return of their investment. 691 00:30:02.713 --> 00:30:03.793 Similarly for government. 692 00:30:04.334 --> 00:30:06.275 When you invest based on the loans, 693 00:30:06.357 --> 00:30:07.818 you will have to pay an interest rate. 694 00:30:07.819 --> 00:30:11.100 So if a project or public policy doesn't have a social return, 695 00:30:11.522 --> 00:30:13.061 you should not borrow to finance it. 696 00:30:13.264 --> 00:30:13.740 Otherwise, 697 00:30:13.803 --> 00:30:14.803 you're going to go bankrupt. 698 00:30:15.404 --> 00:30:16.826 And it's true at the project level, 699 00:30:16.873 --> 00:30:17.748 at the policy level, 700 00:30:17.951 --> 00:30:19.045 or at the government level. 701 00:30:19.545 --> 00:30:19.936 Currently, 702 00:30:20.154 --> 00:30:20.889 while we are talking, 703 00:30:21.045 --> 00:30:24.076 there are a number of countries which have too much debt. 704 00:30:25.842 --> 00:30:28.373 And because the interest rates are pretty high in the US, 705 00:30:28.639 --> 00:30:29.592 still somewhat in the 706 00:30:30.194 --> 00:30:30.615 in Europe, 707 00:30:30.616 --> 00:30:33.016 but it's very true in Africa or Latin America as well. 708 00:30:33.598 --> 00:30:36.219 We need to invest in fields where there are high returns. 709 00:30:36.602 --> 00:30:37.121 Otherwise, 710 00:30:37.520 --> 00:30:38.578 it's going to snowball. 711 00:30:39.125 --> 00:30:39.360 I mean, 712 00:30:39.883 --> 00:30:41.063 debt is going to snowball. 713 00:30:41.664 --> 00:30:49.828 And we are going to face another debt crisis if we are not careful enough to actually measure the return expected on any investment. 714 00:30:49.907 --> 00:30:51.172 I think it's very important. 715 00:30:51.282 --> 00:30:51.422 Yeah. 716 00:30:51.813 --> 00:30:52.469 So let's, 717 00:30:52.578 --> 00:30:53.344 this is very, 718 00:30:53.391 --> 00:30:54.141 very important, 719 00:30:54.157 --> 00:30:58.219 but let's unpack a bit this because we talk about 720 00:30:58.630 --> 00:30:59.671 social return. 721 00:31:00.211 --> 00:31:00.592 And again, 722 00:31:00.733 --> 00:31:03.055 something we discussed in another episode of 723 00:31:03.817 --> 00:31:05.875 Tech Talks is exactly this, 724 00:31:06.239 --> 00:31:09.422 that social returns or that are not, 725 00:31:09.758 --> 00:31:10.219 let's say, 726 00:31:10.946 --> 00:31:13.625 quantifiable in terms of profit, 727 00:31:13.828 --> 00:31:14.992 financial returns. 728 00:31:14.993 --> 00:31:22.274 So there are areas where the private sector doesn't take the risk or is not interested in investing because, 729 00:31:22.539 --> 00:31:22.789 you know, 730 00:31:22.930 --> 00:31:25.789 social returns are not something that investors, 731 00:31:25.992 --> 00:31:27.696 traditional investors care about. 732 00:31:29.679 --> 00:31:31.821 they have other goals and other objectives. 733 00:31:31.841 --> 00:31:32.382 So again, 734 00:31:32.440 --> 00:31:36.308 there is a space here for social return for multilateral development banks, 735 00:31:36.808 --> 00:31:45.534 for agents that are prepared to take the risk and let the economy or even a bunch of firms to develop. 736 00:31:45.909 --> 00:31:46.175 Right? 737 00:31:47.800 --> 00:31:47.909 Yeah, 738 00:31:47.940 --> 00:31:48.300 absolutely. 739 00:31:49.675 --> 00:31:50.800 And as you were saying, 740 00:31:51.300 --> 00:31:54.222 when you invest in a project or a public policy, 741 00:31:55.628 --> 00:31:57.050 returns can be um 742 00:31:57.610 --> 00:31:57.830 I mean, 743 00:31:57.890 --> 00:32:00.833 it can be hard to disentangle between returns for the government, 744 00:32:01.134 --> 00:32:01.772 for the government, 745 00:32:01.815 --> 00:32:02.034 sorry, 746 00:32:02.995 --> 00:32:03.897 for the company, 747 00:32:04.057 --> 00:32:04.975 if it's a public company, 748 00:32:05.358 --> 00:32:06.257 for the individuals. 749 00:32:06.741 --> 00:32:09.702 But if you want to look at financial sustainability, 750 00:32:09.944 --> 00:32:11.827 the borrower has to get some of the returns, 751 00:32:11.921 --> 00:32:14.327 otherwise he will not be able to pay the loan. 752 00:32:14.624 --> 00:32:16.468 And if you're taking international loans, 753 00:32:17.171 --> 00:32:23.093 it should be mostly in a sector typically that generates revenues in foreign currencies, 754 00:32:23.218 --> 00:32:25.014 otherwise you might have a mismatch there. 755 00:32:25.264 --> 00:32:25.405 But 756 00:32:25.738 --> 00:32:26.219 But again, 757 00:32:26.519 --> 00:32:35.588 I think the main point is that we should really look in details on the returns of any investment, 758 00:32:35.689 --> 00:32:37.791 whether it's for the government, 759 00:32:37.830 --> 00:32:38.892 whether it's for individuals. 760 00:32:39.728 --> 00:32:42.595 But if a project doesn't have sufficient returns, 761 00:32:42.674 --> 00:32:44.330 we should not finance it through loans. 762 00:32:44.814 --> 00:32:45.580 In many instances, 763 00:32:45.581 --> 00:32:51.986 there are public policies that have immediate interest and can be financed through taxes. 764 00:32:52.064 --> 00:32:52.924 But if you... 765 00:32:53.518 --> 00:32:56.942 If a particular country or company wants to borrow from abroad, 766 00:32:57.102 --> 00:32:58.461 then it's a different story. 767 00:32:59.126 --> 00:33:04.368 Which is why a bit earlier I was talking about the various sources of financing for public service. 768 00:33:04.469 --> 00:33:12.751 But my concern is that too often we rely on international debt for public policies that should be financed through domestic taxes. 769 00:33:13.422 --> 00:33:20.563 And truly international borrowing should be targeted towards sectors that have explicit return and can generate foreign currencies. 770 00:33:20.657 --> 00:33:21.172 otherwise 771 00:33:21.470 --> 00:33:25.214 you create mismatch and a risk of insolvency. 772 00:33:25.632 --> 00:33:26.413 Absolutely. 773 00:33:26.636 --> 00:33:26.937 And so, 774 00:33:27.214 --> 00:33:27.636 again, 775 00:33:27.757 --> 00:33:31.101 it's like there is an instrument for every need. 776 00:33:31.640 --> 00:33:39.249 And so it's very important to understand what type of instrument we need for each need. 777 00:33:39.749 --> 00:33:40.171 And so, 778 00:33:40.265 --> 00:33:40.796 for example, 779 00:33:40.906 --> 00:33:46.093 one thing we say here at the Sciences Po is it's very important to look at that, 780 00:33:46.609 --> 00:33:48.249 the moment that is incurred, 781 00:33:48.374 --> 00:33:48.578 not... 782 00:33:49.005 --> 00:33:50.945 When debt becomes unsustainable, 783 00:33:51.105 --> 00:33:52.685 and so asking the question, 784 00:33:53.185 --> 00:33:53.427 you know, 785 00:33:53.607 --> 00:33:55.505 is this debt sustainable? 786 00:33:55.646 --> 00:33:56.345 So again, 787 00:33:57.126 --> 00:34:01.704 if you like crisis preventions versus crisis resolution, 788 00:34:01.806 --> 00:34:10.548 so an intervention when the debt is now basically difficult to manage and they need to be restructuring, 789 00:34:10.549 --> 00:34:11.689 they need some solution. 790 00:34:11.954 --> 00:34:17.845 It's just what are the good conditions and when money should be borrowed. 791 00:34:18.361 --> 00:34:24.647 under which conditions and then when other instruments should be considered. 792 00:34:24.648 --> 00:34:25.627 And exactly this, 793 00:34:25.869 --> 00:34:26.432 exactly to avoid... 794 00:34:27.190 --> 00:34:27.573 Absolutely. 795 00:34:27.791 --> 00:34:28.893 Maybe to come back to the 796 00:34:29.291 --> 00:34:30.596 80s or 90s at the time, 797 00:34:31.073 --> 00:34:31.932 and even the early 798 00:34:32.338 --> 00:34:36.065 2000s, there were a number of debt crises. 799 00:34:36.737 --> 00:34:37.237 Mexico, 800 00:34:37.955 --> 00:34:39.237 in Asia in the late 801 00:34:39.815 --> 00:34:41.705 90s, in Africa mostly after 2000. 802 00:34:42.580 --> 00:34:46.330 And it has led to setting up debt sustainability... 803 00:34:46.697 --> 00:34:47.978 debt sustainability analysis, 804 00:34:48.018 --> 00:34:49.921 the DSA for low income countries, 805 00:34:49.960 --> 00:34:52.302 which is done by the IMF and the World Bank. 806 00:34:52.802 --> 00:34:55.204 We do it also internally at EFD. 807 00:34:55.423 --> 00:34:57.509 So we are our own rating agency, 808 00:34:57.665 --> 00:34:57.907 you know, 809 00:34:57.930 --> 00:34:59.227 rating agency between AAA, 810 00:34:59.571 --> 00:34:59.688 AA, 811 00:34:59.813 --> 00:35:00.469 AAA, 812 00:35:00.509 --> 00:35:01.094 BBB and so on. 813 00:35:02.212 --> 00:35:05.048 Because when you land over the long terms, 814 00:35:05.376 --> 00:35:05.610 20, 815 00:35:05.751 --> 00:35:05.969 30, 816 00:35:06.063 --> 00:35:07.079 sometimes 40 years, 817 00:35:08.438 --> 00:35:12.548 it's development banks do a different job from traditional capital markets. 818 00:35:12.657 --> 00:35:14.048 They land over the very long term. 819 00:35:14.063 --> 00:35:15.829 So it's really the long term sustainability. 820 00:35:16.063 --> 00:35:16.188 Yeah. 821 00:35:16.369 --> 00:35:19.652 financial sustainability of developing countries that matter because we need to be repaid. 822 00:35:19.713 --> 00:35:23.875 We don't have any subsidy to run either the World Bank or EFD. 823 00:35:24.680 --> 00:35:30.344 So we have to assess the long-term sustainability or the development path of a particular country. 824 00:35:30.726 --> 00:35:34.367 And this is why I think we should pay attention to returns to avoid, 825 00:35:35.101 --> 00:35:35.492 again, 826 00:35:36.476 --> 00:35:37.992 getting into a debt crisis. 827 00:35:38.367 --> 00:35:39.336 We have seen a number, 828 00:35:39.570 --> 00:35:40.898 and you were alluding to it, 829 00:35:41.148 --> 00:35:44.851 a number of countries going to the Paris Club because their debt needs restructuring but 830 00:35:45.165 --> 00:35:47.427 preventing this risk hugely matters. 831 00:35:47.988 --> 00:35:51.531 I think we are in a slightly better position now than we were in the 832 00:35:52.414 --> 00:35:53.355 90s, but still, 833 00:35:54.097 --> 00:35:55.839 probably we should do a bit better. 834 00:35:56.316 --> 00:35:56.480 Yeah, 835 00:35:56.597 --> 00:35:56.933 I think 836 00:35:57.699 --> 00:35:59.558 I agree that we're in a better position. 837 00:35:59.660 --> 00:36:00.324 Possibly, 838 00:36:00.839 --> 00:36:05.542 I think that the years of very basic zero, 839 00:36:06.605 --> 00:36:07.402 what we used to say, 840 00:36:07.527 --> 00:36:10.996 zero-bound monetary policies of the United States, 841 00:36:11.714 --> 00:36:12.792 the Fed monetary policy, 842 00:36:12.825 --> 00:36:15.027 policy was basically zero interest rate. 843 00:36:15.428 --> 00:36:18.832 So that means there was a search for yields. 844 00:36:18.910 --> 00:36:31.644 And so many developing countries were considered interesting investment simply because they interest rate on their debt was higher. 845 00:36:31.957 --> 00:36:32.910 But that was again, 846 00:36:33.097 --> 00:36:35.363 and that created some problems later on. 847 00:36:35.472 --> 00:36:41.941 So there was too much money searching for yield at the time without thinking whether or not that. 848 00:36:43.294 --> 00:36:45.335 that was sustainable. 849 00:36:45.596 --> 00:36:45.716 Yeah, 850 00:36:45.717 --> 00:36:45.856 I mean, 851 00:36:45.897 --> 00:36:46.776 even five years ago, 852 00:36:47.038 --> 00:36:48.800 interest rates in the US or Europe, 853 00:36:49.999 --> 00:36:51.284 even at the 10-year horizon, 854 00:36:51.745 --> 00:36:52.464 between 0%, 855 00:36:52.667 --> 00:36:52.862 1%, 856 00:36:53.182 --> 00:36:53.706 sometimes 2%. 857 00:36:54.307 --> 00:36:55.307 And in developing countries, 858 00:36:55.385 --> 00:36:56.409 over the same maturity, 859 00:36:56.464 --> 00:36:57.346 you had rates at 4% 860 00:36:57.425 --> 00:36:57.831 to 5%. 861 00:36:58.448 --> 00:37:00.448 Now it's between 4% 862 00:37:00.449 --> 00:37:00.885 and 5% 863 00:37:00.886 --> 00:37:01.479 in the US, 864 00:37:01.839 --> 00:37:02.932 but it's mostly between 8% 865 00:37:02.979 --> 00:37:03.620 and 10% 866 00:37:03.776 --> 00:37:04.292 in Africa, 867 00:37:04.370 --> 00:37:04.870 for example. 868 00:37:05.151 --> 00:37:05.901 In Latin America, 869 00:37:06.292 --> 00:37:06.604 of course, 870 00:37:06.605 --> 00:37:07.401 it depends on the country, 871 00:37:07.464 --> 00:37:08.682 but let's say 7% 872 00:37:08.683 --> 00:37:09.073 to 8%. 873 00:37:09.401 --> 00:37:12.260 So we've seen interest rates rise massively. 874 00:37:12.753 --> 00:37:18.739 And now we have a few investors still having an appetite for debt in Africa or Latin America, 875 00:37:18.798 --> 00:37:21.005 but certainly not at the same interest rates. 876 00:37:21.380 --> 00:37:23.184 And because the stock of debt is higher, 877 00:37:23.583 --> 00:37:27.348 it means the debt service has grown much higher now in Africa, 878 00:37:27.426 --> 00:37:27.887 Latin America, 879 00:37:27.926 --> 00:37:29.544 and some Asian countries as well. 880 00:37:30.309 --> 00:37:31.137 And it's a different, 881 00:37:32.028 --> 00:37:39.434 this is when we are going to measure whether or not countries have been sufficiently cautious and will be able to not default. 882 00:37:41.255 --> 00:37:41.435 Again, 883 00:37:41.474 --> 00:37:43.476 I think we'll be in a different position from that of the 884 00:37:44.338 --> 00:37:44.877 90s or early 885 00:37:45.357 --> 00:37:46.580 2000s. But still, 886 00:37:47.138 --> 00:37:51.623 we've seen already five or six countries having to go to the Paris Club for debt restructuring. 887 00:37:52.349 --> 00:37:53.584 And there might be other cases. 888 00:37:54.146 --> 00:37:56.302 My best guess is that it's not going to be massive. 889 00:37:56.912 --> 00:37:57.474 But still, 890 00:37:57.537 --> 00:37:58.787 because interest rates are higher, 891 00:37:59.912 --> 00:38:04.052 the countries that are the most at risk will probably need restructuring. 892 00:38:04.053 --> 00:38:04.224 Yeah. 893 00:38:04.225 --> 00:38:06.412 And it's not only a restructuring. 894 00:38:06.413 --> 00:38:07.927 And what concerns me is... 895 00:38:08.381 --> 00:38:10.242 There is another group of countries, 896 00:38:10.664 --> 00:38:14.906 they manage to somehow service their debt. 897 00:38:15.149 --> 00:38:15.270 So, 898 00:38:15.590 --> 00:38:16.207 in other words, 899 00:38:16.629 --> 00:38:22.754 not to be in the default or semi-default situation, 900 00:38:23.574 --> 00:38:29.895 but they are managing their debt at the expense of other priorities and other spending. 901 00:38:29.926 --> 00:38:30.676 So they spend, 902 00:38:32.207 --> 00:38:34.129 they cast spending on education, 903 00:38:34.723 --> 00:38:35.582 on health care, 904 00:38:36.113 --> 00:38:37.051 on social. 905 00:38:38.685 --> 00:38:46.132 policies and in order to sort of preserve funding for servicing that debt. 906 00:38:46.234 --> 00:38:49.011 And that is equally worrying because, 907 00:38:49.012 --> 00:38:49.339 you know, 908 00:38:49.535 --> 00:38:56.277 it's terrible to be in a debt restructuring situation because the default or debt restructuring is an uncertainty, 909 00:38:56.839 --> 00:38:58.183 it's painful and anything. 910 00:38:58.621 --> 00:39:04.027 But possibly it's even worse to be in a situation where you constantly try to... 911 00:39:05.692 --> 00:39:07.153 meet their obligations, 912 00:39:07.374 --> 00:39:10.958 but cutting social spending and education, 913 00:39:11.016 --> 00:39:11.817 anything else? 914 00:39:11.876 --> 00:39:12.239 Absolutely. 915 00:39:12.259 --> 00:39:15.704 I think the vast majority of developing countries is not going to default. 916 00:39:16.321 --> 00:39:16.680 However, 917 00:39:16.704 --> 00:39:19.548 the World Bank is talking a lot about the middle income trap, 918 00:39:20.149 --> 00:39:21.868 whereby many countries will not default, 919 00:39:21.915 --> 00:39:24.774 but will have to cut their expenses or their investment. 920 00:39:24.805 --> 00:39:25.290 And therefore, 921 00:39:25.759 --> 00:39:31.493 it's going to impact their growth and their ability to get out of that middle income trap and become advanced economists. 922 00:39:31.494 --> 00:39:32.774 There are not that many countries. 923 00:39:33.659 --> 00:39:35.041 that become advanced economies. 924 00:39:35.201 --> 00:39:35.601 Recently, 925 00:39:35.621 --> 00:39:39.324 I had a discussion with the chief economist for Europe and Central Asia of the World Bank, 926 00:39:39.344 --> 00:39:47.355 and he was reminding us that half of the countries that got out of this middle income trap were actually European countries. 927 00:39:48.011 --> 00:39:58.261 And it's really the perspective of coming into the EU that has led to huge and sometimes painful reforms even before they even got into the EU. 928 00:39:58.761 --> 00:40:01.402 And that's roughly half of the countries that uh 929 00:40:01.495 --> 00:40:03.416 later became advanced economy. 930 00:40:03.477 --> 00:40:05.778 Then there are other examples in the rest of the world, 931 00:40:06.461 --> 00:40:07.239 but not that many. 932 00:40:07.321 --> 00:40:08.942 So being trapped in that, 933 00:40:09.301 --> 00:40:09.903 in particular, 934 00:40:10.520 --> 00:40:13.747 financial difficulties is sort of a common pattern, 935 00:40:14.528 --> 00:40:26.145 while being able to get out of this trap and really have a sustained growth over the long time and maintain the capacity to invest has been rather the exception than the rule. 936 00:40:26.457 --> 00:40:26.598 Yeah, 937 00:40:27.004 --> 00:40:27.582 absolutely. 938 00:40:27.614 --> 00:40:28.067 And in fact, 939 00:40:28.145 --> 00:40:29.895 on your capacity to invest, 940 00:40:31.472 --> 00:40:36.058 One area I'd like to explore with you is that you and your team have developed this 941 00:40:36.538 --> 00:40:38.741 AI, back to artificial intelligence, 942 00:40:38.843 --> 00:40:40.741 Investment Potential Index. 943 00:40:41.483 --> 00:40:41.804 Basically, 944 00:40:41.805 --> 00:40:46.108 it's a tool designed to help development finance institutions, 945 00:40:46.366 --> 00:40:50.890 banks and governments make informed decisions about AI investments, 946 00:40:51.218 --> 00:40:51.468 right? 947 00:40:51.608 --> 00:40:58.358 But also to identify countries with substantial untapped investment potential. 948 00:40:58.827 --> 00:41:00.349 So this is really very interesting, 949 00:41:00.350 --> 00:41:07.251 but could you walk our listeners through what these tools entail and how it works? 950 00:41:07.697 --> 00:41:13.361 So the job we've done initially was to analyze the factors explaining AI investment. 951 00:41:13.744 --> 00:41:17.829 Now we've built an AI visualization platform. 952 00:41:18.126 --> 00:41:23.564 So you can go and typically if you're a minister of finance or minister of planning in any country, 953 00:41:24.814 --> 00:41:27.611 to compare your country to other countries and see if they are... 954 00:41:27.759 --> 00:41:33.746 particular fields where a country is weaker and probably could invest to expand the AI potential. 955 00:41:34.265 --> 00:41:39.433 Some countries might have infrastructure but not realize that their human capital for AI is too low, 956 00:41:39.910 --> 00:41:41.191 or it might be the other way around. 957 00:41:41.215 --> 00:41:48.574 So the idea is really to share the variables that lead ultimately to the AI potential and the realization of AI, 958 00:41:49.433 --> 00:41:55.386 to give advice or probably to analyze and compare between countries to see where they position themselves. 959 00:41:55.847 --> 00:41:58.647 and where they could invest to increase actual AI investment. 960 00:41:58.668 --> 00:42:03.168 Because some of them have invested in all the explaining factors and they're already doing very well. 961 00:42:03.852 --> 00:42:05.508 Some might be somewhere in the middle of the way, 962 00:42:05.509 --> 00:42:07.352 and probably many countries are in the middle of the way, 963 00:42:07.391 --> 00:42:10.188 that includes Europe and many other continents. 964 00:42:11.071 --> 00:42:17.727 And so it can be a sort of decision-making assistant to help design an AI strategy. 965 00:42:17.930 --> 00:42:19.039 That's one example. 966 00:42:19.352 --> 00:42:19.836 It's very, 967 00:42:19.852 --> 00:42:20.414 very important. 968 00:42:20.430 --> 00:42:20.680 Again, 969 00:42:20.711 --> 00:42:22.571 you talk about AI strategy. 970 00:42:23.071 --> 00:42:24.414 It could be another strategy, 971 00:42:24.446 --> 00:42:24.711 about it. 972 00:42:24.775 --> 00:42:25.055 To me, 973 00:42:25.696 --> 00:42:32.942 the message here is to have a tool that helps assess the investment and the potential. 974 00:42:33.044 --> 00:42:33.607 So again, 975 00:42:33.646 --> 00:42:38.591 it's a way to make capital more effective, 976 00:42:39.052 --> 00:42:49.099 which is basically one of the recommendations of the severe finance for development conference, 977 00:42:49.114 --> 00:42:49.411 which is, 978 00:42:49.536 --> 00:42:49.974 again, 979 00:42:50.146 --> 00:42:52.349 let's use the capital we got, 980 00:42:52.427 --> 00:42:53.302 given that we have now... 981 00:42:53.459 --> 00:42:56.082 competition for capital because there are so many problems, 982 00:42:56.083 --> 00:42:57.043 so many challenges. 983 00:42:57.582 --> 00:42:59.664 Let's use it in an efficient way. 984 00:42:59.863 --> 00:43:03.309 Let's not replicate effort, 985 00:43:03.527 --> 00:43:04.973 duplicate effort, 986 00:43:05.449 --> 00:43:06.473 reinvent the wheel, 987 00:43:06.590 --> 00:43:08.371 but let's stay very focused. 988 00:43:08.372 --> 00:43:08.910 Yeah. 989 00:43:08.911 --> 00:43:09.520 Earlier on, 990 00:43:09.521 --> 00:43:14.676 you were alluding to the importance of openness in the development of Asian economies, 991 00:43:14.723 --> 00:43:15.254 for example, 992 00:43:15.754 --> 00:43:16.660 openness to trade. 993 00:43:17.129 --> 00:43:17.270 But 994 00:43:17.738 --> 00:43:19.442 I'd say that openness to ideas, 995 00:43:19.785 --> 00:43:20.832 good development concept, 996 00:43:21.692 --> 00:43:22.254 innovation. 997 00:43:22.651 --> 00:43:23.672 Also UGD matters. 998 00:43:24.233 --> 00:43:25.615 And in that case, 999 00:43:26.015 --> 00:43:30.597 indexes or international studies can help countries to compare themselves with others. 1000 00:43:30.620 --> 00:43:33.441 And it's not a north versus south situation there. 1001 00:43:34.159 --> 00:43:40.402 France has to look very precisely at why other countries are doing better in their PISA score for education. 1002 00:43:40.464 --> 00:43:41.573 But in some countries, 1003 00:43:41.574 --> 00:43:45.698 they might compare themselves on their innovation ecosystem and AI ecosystem. 1004 00:43:46.089 --> 00:43:49.558 Others might look at the US as a relatively poor life expectancy. 1005 00:43:49.620 --> 00:43:50.902 Probably they should look abroad. 1006 00:43:51.816 --> 00:43:53.998 and see why other countries are doing better. 1007 00:43:54.037 --> 00:43:54.658 So again, 1008 00:43:55.219 --> 00:44:01.809 I don't like to sort of describe the world and oppose developed countries and developing countries. 1009 00:44:01.824 --> 00:44:03.168 I think it's more complex than that. 1010 00:44:03.231 --> 00:44:04.231 And in today's world, 1011 00:44:04.645 --> 00:44:06.934 being able to compare a country with its, 1012 00:44:07.887 --> 00:44:08.012 well, 1013 00:44:08.090 --> 00:44:09.840 basically with all the other countries in the world, 1014 00:44:10.246 --> 00:44:12.434 probably it's more relevant in certain groups. 1015 00:44:12.621 --> 00:44:13.012 But still, 1016 00:44:13.356 --> 00:44:16.324 I think it usually matters because how ideas, 1017 00:44:16.606 --> 00:44:18.402 good policies circulate in the world. 1018 00:44:18.739 --> 00:44:20.804 is a very important factor of development. 1019 00:44:21.304 --> 00:44:21.825 Earlier, 1020 00:44:22.764 --> 00:44:23.206 Daron H. 1021 00:44:23.207 --> 00:44:26.792 Emoglu had a Nobel Prize for stating the importance of institutions. 1022 00:44:26.815 --> 00:44:27.253 And I think 1023 00:44:28.337 --> 00:44:29.099 Both it's true, 1024 00:44:29.179 --> 00:44:31.040 but we need to go a bit more into the details, 1025 00:44:31.140 --> 00:44:33.583 which institutions provide good results. 1026 00:44:33.584 --> 00:44:38.649 And I think comparing countries between themselves is always a very important intellectual exercise. 1027 00:44:39.165 --> 00:44:39.767 Absolutely. 1028 00:44:39.868 --> 00:44:46.181 And I think this is really is a good closing point for our conversation today. 1029 00:44:46.571 --> 00:44:48.603 But generally in the current, 1030 00:44:48.712 --> 00:44:50.118 let's call it climate, 1031 00:44:50.243 --> 00:44:52.446 where now we feel the fragmentation, 1032 00:44:52.524 --> 00:44:57.524 We feel the competition and the conflict and the tensions around three. 1033 00:44:57.629 --> 00:44:58.170 policies. 1034 00:44:58.590 --> 00:45:01.854 The idea that countries can learn from each other. 1035 00:45:02.253 --> 00:45:02.772 And again, 1036 00:45:02.995 --> 00:45:07.256 I really like your suggestion and it should be the divide, 1037 00:45:07.257 --> 00:45:22.069 the sort of mechanical divide between developer developing because there are actually indicators that says and even very rich country like the United States have life expectancy indicators that are not particularly good. 1038 00:45:22.131 --> 00:45:24.710 And so they might learn from somebody else. 1039 00:45:25.029 --> 00:45:25.990 from other countries. 1040 00:45:26.171 --> 00:45:26.671 So again, 1041 00:45:26.751 --> 00:45:28.653 it's sharing practice, 1042 00:45:28.733 --> 00:45:29.512 good practice, 1043 00:45:29.575 --> 00:45:31.415 sharing policies, 1044 00:45:31.958 --> 00:45:33.380 and comparing notes. 1045 00:45:33.434 --> 00:45:35.598 And so which basically bring again, 1046 00:45:35.856 --> 00:45:39.106 everything under the umbrella of policy cooperation. 1047 00:45:39.145 --> 00:45:40.005 That's what we need. 1048 00:45:40.403 --> 00:45:43.208 And that's what multilateral development banks are for. 1049 00:45:43.630 --> 00:45:43.770 Yeah, 1050 00:45:43.802 --> 00:45:44.255 absolutely. 1051 00:45:44.333 --> 00:45:48.973 So you are talking about isolationism as a way to think about trade. 1052 00:45:49.989 --> 00:45:51.411 It's not producing very good results. 1053 00:45:51.458 --> 00:45:52.552 But anyway, 1054 00:45:53.255 --> 00:45:53.755 and personally, 1055 00:45:53.756 --> 00:45:53.895 I'm 1056 00:45:54.073 --> 00:45:56.453 pretty much against intellectually isolationism. 1057 00:45:56.513 --> 00:46:04.556 I think we should really look at good ideas that others have and not start from the fact that our country is the best in each and every public policy. 1058 00:46:04.595 --> 00:46:06.838 I think it's really a wrong way to start your day. 1059 00:46:07.556 --> 00:46:17.424 So spending a bit of time looking at how the other countries or companies are doing is certainly a good way to develop yourself. 1060 00:46:17.861 --> 00:46:19.363 If I were to talk to a government, 1061 00:46:19.364 --> 00:46:22.667 I would say compare yourself and try to find good ideas elsewhere. 1062 00:46:22.847 --> 00:46:23.488 Absolutely. 1063 00:46:23.706 --> 00:46:28.554 It's a perfect time to really perfect way to close our conversation. 1064 00:46:28.593 --> 00:46:29.492 Thank you very much, 1065 00:46:29.632 --> 00:46:29.953 Thomas, 1066 00:46:30.031 --> 00:46:31.312 for being with us today. 1067 00:46:31.874 --> 00:46:32.874 And we shall continue. 1068 00:46:33.437 --> 00:46:33.914 Thank you so much, 1069 00:46:33.915 --> 00:46:34.039 Paula. 1070 00:46:34.040 --> 00:46:34.882 Thank you.