WEBVTT - Kopi Time E133 - Dr. Jennifer Sciubba on Contextualising Demography 0:00:05.900 --> 0:00:08.770 Welcome to Copy Time, a podcast series on Markets and 0:00:08.779 --> 0:00:11.779 Economies from Devi S Group Research. I'm Tau. We chief economist. 0:00:11.789 --> 0:00:14.439 Welcoming you to our 133rd episode. 0:00:15.189 --> 0:00:18.509 Today, we will touch on demographics, a topic that has 0:00:18.520 --> 0:00:22.909 deep implications for economic growth, financial market outlook and social stability. 0:00:23.239 --> 0:00:27.010 Our guest is Jennifer Schubach, an expert on the field 0:00:27.020 --> 0:00:31.370 of political demography. She recently became the President and CEO 0:00:31.379 --> 0:00:35.639 of Population Reference Bureau. She also has affiliations with the 0:00:35.650 --> 0:00:38.598 Wilson Center and he Center for New Frontiers at the 0:00:38.610 --> 0:00:40.560 Center for Strategic and International Studies. 0:00:40.979 --> 0:00:44.889 Her latest book, 8 Billion and Counting how sex, death 0:00:44.900 --> 0:00:48.700 and migration shape our world. Jennifer. A warm welcome to 0:00:48.709 --> 0:00:48.919 Kovi 0:00:48.930 --> 0:00:50.860 Time. Thank you very much for having me 0:00:50.869 --> 0:00:53.080 and welcome back to Singapore. Yes, 0:00:53.259 --> 0:00:55.990 it is as busy as always. I think that's right. 0:00:56.220 --> 0:01:00.810 You were here, I believe about 1415 years ago. And 0:01:00.819 --> 0:01:01.830 what brings you to Singapore? 0:01:02.180 --> 0:01:05.929 I spoke yesterday at the Singapore Council on Women's Organization's 0:01:05.940 --> 0:01:10.199 first annual summit uh for Action on Gender equality, which 0:01:10.269 --> 0:01:13.019 is uh I argued that we need to look at 0:01:13.029 --> 0:01:15.849 our population issues through a gendered lens and we'll ask 0:01:15.860 --> 0:01:18.639 different questions than we might otherwise ask and get different answers. 0:01:18.769 --> 0:01:20.650 So I think it sheds a lot of light on 0:01:20.660 --> 0:01:23.209 what's happening with demographic dynamics, particularly in Asia. 0:01:23.360 --> 0:01:26.639 Fantastic. I don't think the intersection on gender and demographics 0:01:26.650 --> 0:01:29.470 are fully appreciated. So I'm glad you're taking a stab 0:01:29.480 --> 0:01:30.000 at that. Yeah. And 0:01:30.010 --> 0:01:30.089 you 0:01:30.099 --> 0:01:31.690 think it would be because, you know, 0:01:32.319 --> 0:01:36.050 biology and yet somehow it is not really on the 0:01:36.059 --> 0:01:37.260 radar of a policy maker. 0:01:37.430 --> 0:01:41.449 That's right. Great. So Jennifer, I want to take advantage 0:01:41.459 --> 0:01:44.149 of your experience and expertise on demographics as much as 0:01:44.160 --> 0:01:46.319 I can today. But I want to start with a 0:01:46.330 --> 0:01:49.940 couple of technical questions. So when I look at UN 0:01:49.949 --> 0:01:53.980 National Prospects Database, fantastic database. Great website. I use it 0:01:53.989 --> 0:01:54.699 all the time 0:01:54.989 --> 0:01:58.639 but it's not just one forecast for population, there are 0:01:58.650 --> 0:02:02.860 probability bands around population projections, then there are variants, low, 0:02:02.870 --> 0:02:07.639 medium high constant fertility, variant, instant replacement fertility. Can you 0:02:07.650 --> 0:02:12.168 break down these various measures of demographic projections for us? Sure. 0:02:12.179 --> 0:02:14.960 So you know, when you're thinking about how to approach 0:02:14.970 --> 0:02:17.149 the variant, you want to think about how are you 0:02:17.160 --> 0:02:19.570 going to use them? So 0:02:20.788 --> 0:02:23.240 there's different uses for different ones. I'm a huge fan 0:02:23.250 --> 0:02:26.529 of the constant fertility variant. It says if everything stays, 0:02:26.538 --> 0:02:28.589 stays the way that it is right now, what does 0:02:28.600 --> 0:02:30.649 the future look like? And this is what I love 0:02:30.660 --> 0:02:34.168 about demography. I'm sorry that you're an economist because you 0:02:34.179 --> 0:02:37.210 don't know what's happening tomorrow. But I do, right? Is it, 0:02:37.270 --> 0:02:39.330 it's a real privilege to be able to look out 0:02:39.339 --> 0:02:42.369 into the future, many years in the future and have 0:02:42.380 --> 0:02:44.179 a sense of what it will be because so many 0:02:44.190 --> 0:02:46.289 of the people of the future are already born. 0:02:46.639 --> 0:02:50.179 So the constant fertility variant is useful when we want 0:02:50.190 --> 0:02:51.300 to say what, 0:02:52.100 --> 0:02:54.570 you know, if everything stayed the same, how does the 0:02:54.580 --> 0:02:56.710 future look? So if you want to prepare for that 0:02:56.720 --> 0:02:59.638 type of future, then you can do so. And then 0:02:59.649 --> 0:03:02.759 as you start tweaking those underlying numbers, that's where you 0:03:02.770 --> 0:03:05.990 get this rainbow of projections. So you know, the UN 0:03:06.000 --> 0:03:09.820 actually has hundreds of projections just by tweaking those underlying variants. 0:03:10.229 --> 0:03:12.399 Most people use the medium 0:03:13.169 --> 0:03:16.509 and it is the one that the UN would say 0:03:16.520 --> 0:03:20.380 is the most likely to happen. It is made with 0:03:20.389 --> 0:03:23.750 a mathematical model and it's based on uh the past. 0:03:23.758 --> 0:03:25.789 So how do we use the past to inform the future? 0:03:27.020 --> 0:03:29.800 It's not my favorite though because my background is actually 0:03:29.809 --> 0:03:34.869 politics and political science and I'm not sure that that not, 0:03:34.880 --> 0:03:38.520 you know, failing to contextualize an economic, political and social 0:03:38.529 --> 0:03:41.279 variables is really the way to think about the future. 0:03:41.570 --> 0:03:44.990 I think I want to call this podcast, contextualizing demography. 0:03:45.419 --> 0:03:48.000 And I think you want to revisit this issue over 0:03:48.009 --> 0:03:50.550 and over again. I think I also am persuaded by 0:03:50.559 --> 0:03:54.330 the constant fertility matter and I really found resonance in 0:03:54.339 --> 0:03:56.899 it when I saw your TED talk where you had 0:03:56.910 --> 0:03:59.630 these projections that, you know, this country's population go down 0:03:59.639 --> 0:04:02.029 by 40% by the end of the century. If we 0:04:02.039 --> 0:04:03.110 go with the constant 0:04:03.350 --> 0:04:07.009 variant, uh constant fertility variant, and then to your point, 0:04:07.020 --> 0:04:09.720 you can start preparing or if you don't like that outcome, 0:04:09.979 --> 0:04:10.720 maybe you can change. 0:04:11.619 --> 0:04:14.619 And I think, you know, it's really important if you 0:04:14.630 --> 0:04:18.010 are someone who actually uses these projections in your work 0:04:18.019 --> 0:04:20.510 to make a difference as you know, economists might do 0:04:21.079 --> 0:04:25.329 to understand what, how those assumptions are tweaked for the future. 0:04:25.970 --> 0:04:28.440 And there have been some things that, that I would 0:04:28.450 --> 0:04:31.369 really disagree with. So if we look, for example, at 0:04:31.380 --> 0:04:35.839 the difference between the medium and the constant fertility for 0:04:35.850 --> 0:04:41.790 countries like Nigeria or Tanzania just over the next uh 0:04:41.899 --> 0:04:44.519 what 16 years, just out to 2040 0:04:45.269 --> 0:04:49.369 it makes a dramatic difference in the total number of people. 0:04:49.428 --> 0:04:53.350 I think it's something like um the constant fertility variant 0:04:53.359 --> 0:04:55.640 versus the medium for Nigeria, I think is a child 0:04:55.649 --> 0:04:58.178 and a half different. That would be. Now think about 0:04:58.190 --> 0:05:00.539 Singapore's total fertility rate is less than one child. So 0:05:00.549 --> 0:05:03.029 where is, is a huge difference? And so there are 0:05:03.040 --> 0:05:05.820 these assumptions that you can tweak that say, do you 0:05:05.829 --> 0:05:08.820 expect fertility rates to go up where they are currently low? 0:05:09.089 --> 0:05:11.479 And historically, the UN has put that in there? And 0:05:11.488 --> 0:05:13.339 do you expect them to come down where they're high? 0:05:13.350 --> 0:05:14.059 Correct? 0:05:14.339 --> 0:05:16.238 OK. If I were to travel back in time to 0:05:16.250 --> 0:05:21.119 your last visit to Singapore. So 2010, 2011 and we 0:05:21.130 --> 0:05:24.089 opened up un prospect probably it was not as elegant 0:05:24.100 --> 0:05:25.459 a website then. It, it 0:05:25.470 --> 0:05:26.730 was such easier to use though. 0:05:27.500 --> 0:05:30.200 And, uh, and, and we looked at the forecast sitting 0:05:30.209 --> 0:05:33.200 at 2011 and we looked at the forecast for 2024. 0:05:33.209 --> 0:05:35.779 How spot on with those forecasts would have been? 0:05:36.269 --> 0:05:39.760 What I remember the most was how optimistic 0:05:40.339 --> 0:05:43.339 they were. So they were optimistic in two ways. Um 0:05:43.350 --> 0:05:46.678 I've always been a Japan watcher and I remember noticing 0:05:46.690 --> 0:05:50.070 how uh the expectation was that Japan's total fertility rate 0:05:50.079 --> 0:05:51.238 would rise in the future. 0:05:51.940 --> 0:05:54.570 Well, that certainly has not happened. In fact, you know, 0:05:54.579 --> 0:05:56.980 most of these rates have gone lower and I think 0:05:56.988 --> 0:06:00.869 there was a sense that surely it can't stay this 0:06:00.880 --> 0:06:03.649 low for this long. So there, you know, they thought 0:06:03.660 --> 0:06:05.290 it would go up and then there was also an 0:06:05.299 --> 0:06:08.640 expectation that it would come down faster, basically in a 0:06:08.649 --> 0:06:11.410 handful of Sub Saharan African countries where it's still high 0:06:11.420 --> 0:06:15.630 because it really fell fast in most parts of the world. 0:06:15.850 --> 0:06:16.410 Um 0:06:16.970 --> 0:06:19.570 But there have been a handful of countries where it 0:06:19.579 --> 0:06:23.178 has remained high. Some demographers call it a fertility stall. 0:06:23.190 --> 0:06:25.829 I mean that in and of itself shows that there's 0:06:25.839 --> 0:06:30.390 a bias towards assuming a rapid decline. Um but they 0:06:30.399 --> 0:06:32.750 were also overly optimistic about how quickly those rates would 0:06:32.760 --> 0:06:33.219 fall 0:06:33.640 --> 0:06:37.540 so the 8 billion mark that is looming would have 0:06:37.549 --> 0:06:39.089 been at a different point in time. 0:06:39.329 --> 0:06:39.470 It 0:06:39.480 --> 0:06:42.928 wasn't really because actually they kind of canceled each other out. So, 0:06:42.940 --> 0:06:44.820 you know, we knew it was 12 to 13 years 0:06:44.829 --> 0:06:47.619 roughly in there, which is, you know, pretty close. 0:06:49.988 --> 0:06:52.820 I use a lot of these data for my work 0:06:52.829 --> 0:06:55.040 here at D BS. And as you can imagine, as 0:06:55.279 --> 0:06:57.970 a aging society in Singapore, this issue is very close 0:06:57.980 --> 0:07:00.859 to our heart. Um One question that I sometimes confront 0:07:00.869 --> 0:07:05.589 is the forecast on India versus Japan, China versus us. 0:07:05.660 --> 0:07:09.690 Are they all comparable? Are all countries producing decently comparable 0:07:09.700 --> 0:07:10.140 data? 0:07:10.309 --> 0:07:11.059 Well, 0:07:12.000 --> 0:07:16.540 no, not, not necessarily. Um And there are multiple groups 0:07:16.549 --> 0:07:19.320 who actually put out population projection. So Population Reference Bureau 0:07:19.329 --> 0:07:21.910 does one as well. We have our world population data 0:07:21.920 --> 0:07:24.859 sheet which we put out for about 60 years, comes 0:07:24.869 --> 0:07:29.529 out um in September most years and uh our demographers 0:07:29.540 --> 0:07:32.109 do their own sorts of projections. And 0:07:32.760 --> 0:07:34.929 so there are a lot of sources of data if 0:07:34.940 --> 0:07:37.959 you were to open up, for example, um the methodology 0:07:37.970 --> 0:07:40.540 for Afghanistan. So like how does the UN actually know 0:07:40.549 --> 0:07:43.070 what's happening in Afghanistan? We know that this is a, 0:07:43.100 --> 0:07:44.829 you know, there's a lot happening in this country. So 0:07:44.839 --> 0:07:47.010 how are you supposed to figure out where the population is? 0:07:47.019 --> 0:07:50.380 You'd have two paragraphs of them fig of pulling together 0:07:50.390 --> 0:07:54.649 data sources, um USA ID funds a series of demographic 0:07:54.660 --> 0:07:55.320 and health surveys, 0:07:55.404 --> 0:07:58.744 the DH S that's a really solid source for um 0:07:58.755 --> 0:08:03.445 inputs into these projections. Um But sometimes there's also a 0:08:03.454 --> 0:08:05.424 little bit of picking up the phone and calling other 0:08:05.434 --> 0:08:08.904 demographers and, and experts in these countries and these regions 0:08:08.915 --> 0:08:11.065 to say, here's what the numbers say. What do you 0:08:11.075 --> 0:08:13.584 think about these? So there's a bit of a human 0:08:13.595 --> 0:08:16.105 touch in there outside of that medium variant that I really, 0:08:16.114 --> 0:08:17.975 I think is actually very useful. 0:08:19.170 --> 0:08:22.790 But just to so, so look 0:08:24.290 --> 0:08:26.140 the sources will be somewhat different, 0:08:27.279 --> 0:08:29.739 but they're going through the same filter. 0:08:30.429 --> 0:08:33.510 So in my mind, I'm comfortable enough saying that they're 0:08:33.520 --> 0:08:37.059 comparable and that it's the filter part that matters. 0:08:37.609 --> 0:08:40.330 Are there ways of sort of triangulating the data? So 0:08:40.340 --> 0:08:44.569 you bring me demographic data, I bring you tax collection 0:08:44.580 --> 0:08:48.940 data and we can see that if a country's projection 0:08:48.950 --> 0:08:51.510 is huge pickup and the labor force in the country 0:08:51.520 --> 0:08:53.539 saying there's lots of people working, we should be seeing 0:08:53.549 --> 0:08:54.400 that in other 0:08:54.789 --> 0:08:56.869 and then some of that happens as well and they 0:08:56.880 --> 0:08:59.250 could pull from all kinds of different record keeping. 0:08:59.710 --> 0:09:02.530 Um You know, the hardest part is the migration piece 0:09:02.539 --> 0:09:05.280 because by definition, these people are on the move. So 0:09:05.289 --> 0:09:08.190 there's a lot of guessing that goes into the migration 0:09:08.200 --> 0:09:08.929 part as well. 0:09:09.669 --> 0:09:14.590 Jennifer, I was in Cambodia recently and they sort of, 0:09:14.650 --> 0:09:16.690 you know, talk about the killing fields in the seventies 0:09:16.700 --> 0:09:19.900 and how life expectancy collapsed there. I think to like 0:09:19.909 --> 0:09:24.140 23 or 24 there. It's come back amazingly well over 0:09:24.150 --> 0:09:25.978 the last 40 years. So that kind of reflects the 0:09:25.989 --> 0:09:27.460 resiliency of society that 0:09:27.859 --> 0:09:31.319 a demographic shock need not be fatal. And there are 0:09:31.330 --> 0:09:34.599 ways to rejuvenate. But also it sort of brings me 0:09:34.609 --> 0:09:36.989 to this question that, you know, what are the shocks 0:09:37.000 --> 0:09:42.150 that alter demographic trends? Did the pandemic change demographic in 0:09:42.159 --> 0:09:42.590 the world? 0:09:42.599 --> 0:09:42.919 Not 0:09:42.929 --> 0:09:46.849 really. So obviously, for the people who died in their families, 0:09:46.859 --> 0:09:48.530 it was very much a shock. But when we're talking 0:09:48.539 --> 0:09:52.469 about in these aggregate numbers, it didn't. Um In fact, 0:09:52.479 --> 0:09:55.000 I think already that's kind of worked its way out 0:09:55.010 --> 0:09:55.739 of the data 0:09:56.590 --> 0:09:59.909 in some part. It's because many of the deaths were 0:09:59.919 --> 0:10:03.010 to people who were already finished with their reproductive years. 0:10:03.369 --> 0:10:08.179 Um But even for fertility rates, they basically went to 0:10:08.190 --> 0:10:10.589 where they were before. And in the U SI, I've 0:10:10.599 --> 0:10:12.840 always talked about it as it just put the, it 0:10:12.849 --> 0:10:16.469 pushed on the gas pedal directions we were already headed. 0:10:16.479 --> 0:10:17.099 So maybe you 0:10:17.210 --> 0:10:19.510 a little bit of an acceleration, you know, life expectance 0:10:19.520 --> 0:10:22.520 in the US was already on the decline, which is insane. 0:10:22.530 --> 0:10:24.390 By the way, it should not 0:10:24.580 --> 0:10:26.179 for a wealthy industrial society. 0:10:26.200 --> 0:10:29.349 Yeah, even generally like, you know, unless absent a giant war, 0:10:29.359 --> 0:10:32.669 it is absolutely insane that it would be going down. 0:10:32.679 --> 0:10:34.119 And so it just pushed on the gas pedal a 0:10:34.130 --> 0:10:36.799 little bit. Fertility trends already headed down. Maybe you push 0:10:36.809 --> 0:10:39.260 on the gas pedal a little bit. And most demographers 0:10:39.270 --> 0:10:41.929 would say that people who were going to have babies, 0:10:42.309 --> 0:10:44.809 they might have delayed a little bit and then picked 0:10:44.820 --> 0:10:45.429 right back up. 0:10:45.900 --> 0:10:48.750 What about the pandemic bump? People were all staying at 0:10:48.760 --> 0:10:52.049 home and not working, didn't they have a lot of babies? No, 0:10:52.059 --> 0:10:54.190 not this time. Yeah. And like some of the data 0:10:54.200 --> 0:10:56.728 we've seen about even what power outages in the past 0:10:56.739 --> 0:10:58.989 and then you can kind of trace up now. 0:10:59.869 --> 0:11:02.539 Fascinating. So it seems to me that we have pretty 0:11:02.549 --> 0:11:07.390 powerful trends in motion and we have seen policy experiments 0:11:07.400 --> 0:11:10.429 here and there around the world. And so far, 0:11:11.140 --> 0:11:13.729 the power of the trend seems to be overwhelming to 0:11:13.739 --> 0:11:16.219 a large extent. Um I'm gonna come back to that 0:11:16.229 --> 0:11:17.689 uh because I want to talk a little bit about 0:11:17.700 --> 0:11:22.159 the issue related to Scandinavia and so on, but just 0:11:22.510 --> 0:11:26.200 drivers of fertility. Uh I know it's a big subject but, 0:11:26.210 --> 0:11:28.280 and I'm sure you get lots of questions on that. 0:11:28.409 --> 0:11:31.280 So let's talk about what drives fertility rates. 0:11:31.289 --> 0:11:33.880 It is a lot of things which actually is what 0:11:33.890 --> 0:11:37.580 frustrates policymakers. And I'm sympathetic to that because as an academic, 0:11:37.859 --> 0:11:40.760 you know, the the best study is when you can say, 0:11:40.770 --> 0:11:43.650 which is the mo what are the most powerful explanatory 0:11:43.659 --> 0:11:45.960 variables here? And then if you're a policymaker, you can 0:11:45.969 --> 0:11:48.010 take that research and you say, well, let's tweak, let's 0:11:48.020 --> 0:11:51.199 put a policy in place to address this and voila 0:11:51.210 --> 0:11:54.330 problem solved, but that's not really how these decisions are made. 0:11:54.340 --> 0:11:59.229 And I think anyone who has considered having Children 0:11:59.599 --> 0:12:02.950 knows exactly what we mean. When we say that it's complicated. 0:12:02.960 --> 0:12:06.010 It's never just about the money or the ti, you know, timing. 0:12:06.020 --> 0:12:09.250 It's so many things. But if you think about fertility 0:12:09.260 --> 0:12:10.979 rates as a big old pot of soup, there are 0:12:10.989 --> 0:12:12.919 a few different ingredients that go in and that are 0:12:12.929 --> 0:12:17.679 pretty standard. So modernization matters and modernization can be a 0:12:17.690 --> 0:12:21.770 whole host of variables like um education rates for women. 0:12:21.780 --> 0:12:24.630 So if you're talking about a country where fertility rates 0:12:24.640 --> 0:12:28.270 are very high, let's say 56 Children per woman. 0:12:28.489 --> 0:12:32.619 And you bring in um educational system where women especially 0:12:32.630 --> 0:12:35.070 make it to secondary school. You're gonna see those rates 0:12:35.080 --> 0:12:39.108 fall also in modernization, incomes are rising. So opportunity cost 0:12:39.119 --> 0:12:42.630 goes up, uh more opportunities to earn income outside the home. 0:12:43.130 --> 0:12:44.630 You know, all of that kind of comes in together 0:12:44.640 --> 0:12:49.010 there more robust health systems, access to family planning. And 0:12:49.020 --> 0:12:50.109 so that is one driver. 0:12:50.650 --> 0:12:53.468 You also have government policy which and it's hard to 0:12:53.479 --> 0:12:56.319 analytically separate some of these because the government policy will 0:12:56.330 --> 0:12:59.468 often be let's put in schools or put in health clinics. 0:12:59.710 --> 0:13:02.400 But I with modernization, I like to think of it 0:13:02.409 --> 0:13:06.849 as processes that are in motion that that the government 0:13:06.859 --> 0:13:10.369 may or may not have put in motion itself. Um 0:13:10.380 --> 0:13:13.309 But government policy can change the trajectory of trends as 0:13:13.320 --> 0:13:16.369 we know, think about China and many India, many other places. 0:13:16.570 --> 0:13:20.099 And then there's the family planning piece and it really is, 0:13:20.429 --> 0:13:23.530 it's often left out of discussions which I find puzzling 0:13:23.539 --> 0:13:28.309 but just the technology of being able to decide how 0:13:28.320 --> 0:13:32.069 many Children to have and when is really powerful. 0:13:33.369 --> 0:13:37.099 I bring this up with some degree of trepidation and 0:13:37.109 --> 0:13:41.609 hesitation because this is a podcast on numbers and, and 0:13:41.619 --> 0:13:45.069 trends and policy. But let me go there anyway, uh 0:13:45.080 --> 0:13:48.020 last week, there was an article came from Apple News. 0:13:48.030 --> 0:13:50.539 I can't remember the source, but it was that there 0:13:50.549 --> 0:13:54.929 is also something beyond all these macroeconomic societal factors. There 0:13:54.940 --> 0:13:56.709 is this question of purpose that 0:13:56.989 --> 0:13:59.659 there is a generational shift on sense of purpose and 0:13:59.669 --> 0:14:04.090 people feel that between climate change and geopolitics, they're not 0:14:04.099 --> 0:14:06.770 hopeful about the future and maybe that plays a role. 0:14:06.909 --> 0:14:08.969 It's hard to put a finger on it. But what's 0:14:08.979 --> 0:14:10.000 your thought on that? I think? 0:14:10.010 --> 0:14:12.260 Absolutely. Yes. And you know, if I'm trying to keep 0:14:12.270 --> 0:14:15.609 it simple, I kind of stick it under the modernization umbrella, 0:14:15.619 --> 0:14:16.770 but it is different. 0:14:17.429 --> 0:14:19.330 And it's funny because, you know, now that I'm the 0:14:19.340 --> 0:14:21.729 CEO of PR B, the first time I ever learned 0:14:21.739 --> 0:14:25.159 about the Population Reference Bureau was to attend, I mean, 0:14:25.169 --> 0:14:27.969 this is well over 20 years ago, I guess, but 0:14:27.979 --> 0:14:30.690 it was to attend a seminar that was trying to 0:14:30.700 --> 0:14:33.650 explain why fertility rates were so low in eastern Europe 0:14:33.940 --> 0:14:36.940 and I'll never forget it. Uh because they, they, they 0:14:36.950 --> 0:14:38.729 talked about all these same kind of variables we mentioned 0:14:38.739 --> 0:14:40.840 and they said really, there's just no people feel so 0:14:40.849 --> 0:14:42.090 dismal about the future 0:14:42.409 --> 0:14:46.270 and we do see echoes of that today. Um especially, 0:14:46.280 --> 0:14:48.450 you know, anecdotally, you speak to a young person, they 0:14:48.460 --> 0:14:50.630 talk about that all the time. Um 0:14:51.530 --> 0:14:54.630 There, that is some of it. But as far as 0:14:54.640 --> 0:14:57.270 how do we know for sure if that will shape 0:14:57.280 --> 0:15:00.750 fertility behavior? We don't know yet. And that's because these 0:15:00.760 --> 0:15:04.150 young people have not completed their fertility. And so there 0:15:04.159 --> 0:15:06.289 are some papers that I've seen that say, yeah, they 0:15:06.299 --> 0:15:08.719 may feel this way. But we all know you, you 0:15:08.729 --> 0:15:11.119 have a cer certain set of way. You think the 0:15:11.130 --> 0:15:13.539 world works and you're 20 you're 25 0:15:14.119 --> 0:15:16.679 and then you think a lot differently about the world later. 0:15:16.690 --> 0:15:18.859 So we will not know we have to do this 0:15:18.869 --> 0:15:21.469 again in 10 years to say, did it actually drive 0:15:21.479 --> 0:15:23.000 people's fertility behavior lower? 0:15:23.010 --> 0:15:23.030 It 0:15:23.080 --> 0:15:24.780 makes me a little sad because I'd like to think 0:15:24.789 --> 0:15:27.210 that optimism should be at the younger age spectrum and 0:15:27.219 --> 0:15:29.700 the midlife crisis and everything should be later. But it's 0:15:29.710 --> 0:15:32.099 like we're hoping it's almost the opposite. Now, you're starting 0:15:32.109 --> 0:15:34.539 out kind of jaded about the future. And then hopefully, 0:15:34.905 --> 0:15:37.434 as you make money, as you get gainful employment, you 0:15:37.445 --> 0:15:38.294 get more purpose. 0:15:38.304 --> 0:15:38.575 Well, and I 0:15:38.585 --> 0:15:42.575 think we're caught in this, this echo chamber because think 0:15:42.585 --> 0:15:44.234 about the type of news that comes in our phones. 0:15:44.244 --> 0:15:46.325 It's all that and it's right there. It's in our 0:15:46.335 --> 0:15:49.505 faces all day long. And for young people, that's all 0:15:49.515 --> 0:15:52.825 they're surrounded by. Whereas we didn't grow up with that 0:15:52.835 --> 0:15:55.054 type of flow of information. 0:15:55.400 --> 0:15:57.119 And there are, I, I was speaking to a group 0:15:57.130 --> 0:16:00.090 of young people, um, actually young people in Asia the 0:16:00.099 --> 0:16:02.950 other night, uh, in the US. And I, I said 0:16:02.960 --> 0:16:04.820 to them, you know, there are places where you can 0:16:04.830 --> 0:16:08.849 read good news. Um, Angus Hervey, who is out of Australia, 0:16:08.859 --> 0:16:11.450 I think he was at uh TED the same time 0:16:11.460 --> 0:16:14.140 I was and he has his whole shtick is, here's 0:16:14.150 --> 0:16:17.190 the good news and it's real news. It's evidence based 0:16:17.200 --> 0:16:19.390 and it's actually showing what has happened. Um Hannah Ritchie 0:16:19.400 --> 0:16:21.150 was also at, at TED the same year as I 0:16:21.159 --> 0:16:22.979 was and she, she talks about environment 0:16:23.440 --> 0:16:26.429 and she had a book out. Um, what year earlier 0:16:26.440 --> 0:16:28.599 this year, I think as well. And she says these 0:16:28.609 --> 0:16:31.119 are all the things that have gotten better, but that 0:16:31.130 --> 0:16:34.080 is like a, a grain of sand on a beach. 0:16:35.609 --> 0:16:40.020 Come back to the issue of modernization. The theory has 0:16:40.030 --> 0:16:42.700 been that when you look at a country like Sweden 0:16:42.710 --> 0:16:47.469 or Norway, once you become very wealthy, then people start 0:16:47.479 --> 0:16:50.330 behaving a little differently because there are so many safes 0:16:50.390 --> 0:16:53.429 in place and they then do have babies. I would 0:16:53.440 --> 0:16:55.039 have thought some of that would play out in Japan. 0:16:55.049 --> 0:16:55.849 That hasn't happened. 0:16:56.159 --> 0:16:59.099 So, not quite a convincing argument. 0:16:59.510 --> 0:17:02.489 Well, I think we moved the bar on ourselves. Uh, 0:17:02.500 --> 0:17:05.540 you know, when I feel very fortunate, I think mine, 0:17:05.550 --> 0:17:07.739 mine was like the last cohort of people who could 0:17:07.750 --> 0:17:10.569 basically buy houses in our early twenties before things started 0:17:10.579 --> 0:17:12.619 to get out of control. Um, 0:17:13.150 --> 0:17:16.089 but even the expectations that younger people have today for 0:17:16.099 --> 0:17:19.290 what they wanna achieve before they have Children, it has 0:17:19.300 --> 0:17:22.729 really moved up, up, up. Um And I think, I mean, 0:17:22.739 --> 0:17:25.329 we could go down a rabbit hole about a technology. 0:17:25.339 --> 0:17:28.479 I do keep coming back to, I remember um when 0:17:28.489 --> 0:17:31.609 my kids were very young was when Instagram was really 0:17:31.619 --> 0:17:35.050 starting and the only messages you'd get about parenting basically 0:17:35.060 --> 0:17:36.560 were how hard it was 0:17:37.099 --> 0:17:40.839 or the perfect mom who is throwing the perfect party 0:17:40.849 --> 0:17:44.239 that probably costs $500. Well, neither of those things is 0:17:44.250 --> 0:17:47.170 very attractive when you're thinking about having Children. Uh You're 0:17:47.180 --> 0:17:50.030 thinking just really about how incredibly expensive it is. And 0:17:50.040 --> 0:17:52.479 so a lot of the people I was speaking with 0:17:52.489 --> 0:17:57.329 actually yesterday at this summit were saying how the competition 0:17:57.680 --> 0:18:00.859 for like who can, who can just be better, more educated, 0:18:00.869 --> 0:18:03.579 have a higher income. It's really spiraled up and this 0:18:03.589 --> 0:18:05.420 puts a downward pressure on fertility 0:18:05.430 --> 0:18:06.020 itself, 0:18:06.359 --> 0:18:09.639 correct? OK. This is a medical science question. I really 0:18:09.650 --> 0:18:11.458 don't know if there's an answer to this description, but 0:18:11.469 --> 0:18:16.270 just from a women's health perspective. Are women today asked 0:18:16.280 --> 0:18:18.319 for a child? I know it's complicated because there's a 0:18:18.329 --> 0:18:21.899 choice issue there. But just from a biological perspective, well, 0:18:21.910 --> 0:18:22.359 there 0:18:22.464 --> 0:18:25.675 waiting later. So, and that is just very simple stats, 0:18:25.685 --> 0:18:27.935 you know, people are marrying later and then they're waiting 0:18:27.944 --> 0:18:29.604 later to have their first child. And when you know, 0:18:29.614 --> 0:18:35.244 sitting in Asia where mo you know, most marriages, I'm sorry, 0:18:35.255 --> 0:18:37.594 most Children are born within a marriage. 0:18:38.079 --> 0:18:41.180 That means that marriage becomes an incredibly important first step 0:18:41.189 --> 0:18:43.390 before you have Children. So if people are waiting later 0:18:43.400 --> 0:18:46.469 to get married, then they are starting their families later. 0:18:46.479 --> 0:18:49.189 And so we do see um a lot more women 0:18:49.199 --> 0:18:53.270 of older ages seeking assisted reproductive technology. And those, those, 0:18:53.280 --> 0:18:54.000 you know, we see that around 0:18:54.069 --> 0:18:56.319 world, I mean, in the US, for example, the only 0:18:56.329 --> 0:18:58.109 age group, I think that was seeing an increase in 0:18:58.119 --> 0:19:00.849 births was 40 to 45. But that's because they were 0:19:00.859 --> 0:19:01.139 waiting 0:19:01.150 --> 0:19:01.569 later. 0:19:01.750 --> 0:19:05.050 So it's not health but health, technology and choice. 0:19:05.060 --> 0:19:07.449 Yes, I think so. Now this is, you know, there 0:19:07.459 --> 0:19:10.020 are other people who have said that it's infertility. 0:19:10.689 --> 0:19:13.649 I don't buy it because if you study data just 0:19:13.660 --> 0:19:15.520