0:00:00.500,0:00:05.000 The global economic financial crisis has reignited public interest 0:00:05.000,0:00:08.416 in something that's actually one of the oldest questions in economics, 0:00:08.416,0:00:11.100 dating back to at least before Adam Smith. 0:00:11.100,0:00:16.584 And that is, why is it that countries with seemingly similar economies and institutions 0:00:16.584,0:00:19.833 can display radically different savings behavior? 0:00:19.833,0:00:24.367 Now, many brilliant economists have spent their entire lives working on this question, 0:00:24.367,0:00:27.784 and as a field we've made a tremendous amount of headway 0:00:27.784,0:00:30.217 and we understand a lot about this. 0:00:30.217,0:00:33.851 What I'm here to talk with you about today is an intriguing new hypothesis 0:00:33.851,0:00:37.883 and some surprisingly powerful new findings that I've been working on 0:00:37.883,0:00:42.589 about the link between the structure of the language you speak 0:00:42.604,0:00:47.000 and how you find yourself with the propensity to save. 0:00:47.000,0:00:50.067 Let me tell you a little bit about savings rates, a little bit about language, 0:00:50.067,0:00:52.417 and then I'll draw that connection. 0:00:52.417,0:00:56.984 Let's start by thinking about the member countries of the OECD, 0:00:56.984,0:01:00.285 or the Organization of Economic Cooperation and Development. 0:01:00.285,0:01:04.184 OECD countries, by and large, you should think about these 0:01:04.184,0:01:06.822 as the richest, most industrialized countries in the world. 0:01:06.822,0:01:10.872 And by joining the OECD, they were affirming a common commitment 0:01:10.872,0:01:14.310 to democracy, open markets and free trade. 0:01:14.310,0:01:18.995 Despite all of these similarities, we see huge differences in savings behavior. 0:01:18.995,0:01:21.445 So all the way over on the left of this graph, 0:01:21.445,0:01:26.179 what you see is many OECD countries saving over a quarter of their GDP every year, 0:01:26.179,0:01:30.860 and some OECD countries saving over a third of their GDP per year. 0:01:30.860,0:01:35.628 Holding down the right flank of the OECD, all the way on the other side, is Greece. 0:01:35.628,0:01:39.044 And what you can see is that over the last 25 years, 0:01:39.044,0:01:42.944 Greece has barely managed to save more than 10 percent of their GDP. 0:01:42.944,0:01:49.818 It should be noted, of course, that the United States and the U.K. are the next in line. 0:01:49.818,0:01:52.396 Now that we see these huge differences in savings rates, 0:01:52.396,0:01:56.062 how is it possible that language might have something to do with these differences? 0:01:56.062,0:01:59.111 Let me tell you a little bit about how languages fundamentally differ. 0:01:59.111,0:02:04.678 Linguists and cognitive scientists have been exploring this question for many years now. 0:02:04.678,0:02:09.288 And then I'll draw the connection between these two behaviors. 0:02:09.288,0:02:11.896 Many of you have probably already noticed that I'm Chinese. 0:02:11.896,0:02:14.861 I grew up in the Midwest of the United States. 0:02:14.861,0:02:17.312 And something I realized quite early on 0:02:17.312,0:02:20.903 was that the Chinese language forced me to speak about and -- 0:02:20.903,0:02:23.794 in fact, more fundamentally than that -- 0:02:23.794,0:02:27.884 ever so slightly forced me to think about family in very different ways. 0:02:27.884,0:02:29.961 Now, how might that be? Let me give you an example. 0:02:29.961,0:02:34.363 Suppose I were talking with you and I was introducing you to my uncle. 0:02:34.363,0:02:37.229 You understood exactly what I just said in English. 0:02:37.229,0:02:40.179 If we were speaking Mandarin Chinese with each other, though, 0:02:40.179,0:02:42.245 I wouldn't have that luxury. 0:02:42.245,0:02:45.078 I wouldn't have been able to convey so little information. 0:02:45.078,0:02:47.462 What my language would have forced me to do, 0:02:47.462,0:02:49.462 instead of just telling you, "This is my uncle," 0:02:49.462,0:02:52.744 is to tell you a tremendous amount of additional information. 0:02:52.744,0:02:54.563 My language would force me to tell you 0:02:54.563,0:02:57.979 whether or not this was an uncle on my mother's side or my father's side, 0:02:57.979,0:03:01.063 whether this was an uncle by marriage or by birth, 0:03:01.063,0:03:03.295 and if this man was my father's brother, 0:03:03.295,0:03:06.079 whether he was older than or younger than my father. 0:03:06.079,0:03:10.212 All of this information is obligatory. Chinese doesn't let me ignore it. 0:03:10.212,0:03:12.378 And in fact, if I want to speak correctly, 0:03:12.378,0:03:15.495 Chinese forces me to constantly think about it. 0:03:15.495,0:03:19.444 Now, that fascinated me endlessly as a child, 0:03:19.444,0:03:22.679 but what fascinates me even more today as an economist 0:03:22.679,0:03:27.980 is that some of these same differences carry through to how languages speak about time. 0:03:27.980,0:03:32.229 So for example, if I'm speaking in English, I have to speak grammatically differently 0:03:32.229,0:03:34.962 if I'm talking about past rain, "It rained yesterday," 0:03:34.962,0:03:37.194 current rain, "It is raining now," 0:03:37.194,0:03:39.628 or future rain, "It will rain tomorrow." 0:03:39.628,0:03:44.455 Notice that English requires a lot more information with respect to the timing of events. 0:03:44.455,0:03:46.462 Why? Because I have to consider that 0:03:46.462,0:03:51.245 and I have to modify what I'm saying to say, "It will rain," or "It's going to rain." 0:03:51.245,0:03:55.361 It's simply not permissible in English to say, "It rain tomorrow." 0:03:55.361,0:03:59.545 In contrast to that, that's almost exactly what you would say in Chinese. 0:03:59.545,0:04:01.861 A Chinese speaker can basically say something 0:04:01.861,0:04:04.445 that sounds very strange to an English speaker's ears. 0:04:04.445,0:04:09.012 They can say, "Yesterday it rain," "Now it rain," "Tomorrow it rain." 0:04:09.012,0:04:12.875 In some deep sense, Chinese doesn't divide up the time spectrum 0:04:12.875,0:04:19.308 in the same way that English forces us to constantly do in order to speak correctly. 0:04:19.308,0:04:20.892 Is this difference in languages 0:04:20.892,0:04:25.087 only between very, very distantly related languages, like English and Chinese? 0:04:25.087,0:04:26.045 Actually, no. 0:04:26.045,0:04:29.778 So many of you know, in this room, that English is a Germanic language. 0:04:29.778,0:04:33.693 What you may not have realized is that English is actually an outlier. 0:04:33.693,0:04:36.943 It is the only Germanic language that requires this. 0:04:36.943,0:04:39.827 For example, most other Germanic language speakers 0:04:39.827,0:04:42.844 feel completely comfortable talking about rain tomorrow 0:04:42.844,0:04:44.810 by saying, "Morgen regnet es," 0:04:44.810,0:04:48.710 quite literally to an English ear, "It rain tomorrow." 0:04:48.710,0:04:53.777 This led me, as a behavioral economist, to an intriguing hypothesis. 0:04:53.777,0:04:58.026 Could how you speak about time, could how your language forces you to think about time, 0:04:58.026,0:05:01.777 affect your propensity to behave across time? 0:05:01.777,0:05:04.677 You speak English, a futured language. 0:05:04.677,0:05:07.844 And what that means is that every time you discuss the future, 0:05:07.844,0:05:09.411 or any kind of a future event, 0:05:09.411,0:05:12.810 grammatically you're forced to cleave that from the present 0:05:12.810,0:05:15.443 and treat it as if it's something viscerally different. 0:05:15.443,0:05:17.943 Now suppose that that visceral difference 0:05:17.943,0:05:22.143 makes you subtly dissociate the future from the present every time you speak. 0:05:22.143,0:05:24.056 If that's true and it makes the future feel 0:05:24.056,0:05:27.039 like something more distant and more different from the present, 0:05:27.039,0:05:29.693 that's going to make it harder to save. 0:05:29.693,0:05:32.244 If, on the other hand, you speak a futureless language, 0:05:32.244,0:05:35.627 the present and the future, you speak about them identically. 0:05:35.627,0:05:38.610 If that subtly nudges you to feel about them identically, 0:05:38.610,0:05:40.994 that's going to make it easier to save. 0:05:40.994,0:05:43.544 Now this is a fanciful theory. 0:05:43.544,0:05:46.444 I'm a professor, I get paid to have fanciful theories. 0:05:46.444,0:05:50.678 But how would you actually go about testing such a theory? 0:05:50.678,0:05:54.744 Well, what I did with that was to access the linguistics literature. 0:05:54.744,0:05:59.127 And interestingly enough, there are pockets of futureless language speakers 0:05:59.127,0:06:01.060 situated all over the world. 0:06:01.060,0:06:04.426 This is a pocket of futureless language speakers in Northern Europe. 0:06:04.426,0:06:07.327 Interestingly enough, when you start to crank the data, 0:06:07.327,0:06:10.560 these pockets of futureless language speakers all around the world 0:06:10.560,0:06:14.494 turn out to be, by and large, some of the world's best savers. 0:06:14.494,0:06:16.660 Just to give you a hint of that, 0:06:16.660,0:06:19.410 let's look back at that OECD graph that we were talking about. 0:06:19.410,0:06:22.794 What you see is that these bars are systematically taller 0:06:22.794,0:06:24.926 and systematically shifted to the left 0:06:24.926,0:06:29.444 compared to these bars which are the members of the OECD that speak futured languages. 0:06:29.444,0:06:30.907 What is the average difference here? 0:06:30.907,0:06:34.193 Five percentage points of your GDP saved per year. 0:06:34.193,0:06:38.927 Over 25 years that has huge long-run effects on the wealth of your nation. 0:06:38.927,0:06:41.627 Now while these findings are suggestive, 0:06:41.627,0:06:43.693 countries can be different in so many different ways 0:06:43.693,0:06:48.077 that it's very, very difficult sometimes to account for all of these possible differences. 0:06:48.077,0:06:52.109 What I'm going to show you, though, is something that I've been engaging in for a year, 0:06:52.109,0:06:54.432 which is trying to gather all of the largest datasets 0:06:54.432,0:06:56.724 that we have access to as economists, 0:06:56.724,0:07:00.106 and I'm going to try and strip away all of those possible differences, 0:07:00.106,0:07:02.760 hoping to get this relationship to break. 0:07:02.760,0:07:07.791 And just in summary, no matter how far I push this, I can't get it to break. 0:07:07.791,0:07:09.556 Let me show you how far you can do that. 0:07:09.556,0:07:14.189 One way to imagine that is I gather large datasets from around the world. 0:07:14.189,0:07:17.923 So for example, there is the Survey of Health, [Aging] and Retirement in Europe. 0:07:17.923,0:07:21.757 From this dataset you actually learn that retired European families 0:07:21.757,0:07:24.390 are extremely patient with survey takers. 0:07:24.390,0:07:26.306 (Laughter) 0:07:26.306,0:07:30.690 So imagine that you're a retired household in Belgium and someone comes to your front door. 0:07:30.690,0:07:35.274 "Excuse me, would you mind if I peruse your stock portfolio? 0:07:35.274,0:07:38.806 Do you happen to know how much your house is worth? Do you mind telling me? 0:07:38.806,0:07:42.073 Would you happen to have a hallway that's more than 10 meters long? 0:07:42.073,0:07:46.574 If you do, would you mind if I timed how long it took you to walk down that hallway? 0:07:46.574,0:07:50.471 Would you mind squeezing as hard as you can, in your dominant hand, this device 0:07:50.471,0:07:51.983 so I can measure your grip strength? 0:07:51.983,0:07:56.006 How about blowing into this tube so I can measure your lung capacity?" 0:07:56.006,0:07:58.890 The survey takes over a day. 0:07:58.890,0:08:00.373 (Laughter) 0:08:00.373,0:08:04.273 Combine that with a Demographic and Health Survey 0:08:04.273,0:08:08.723 collected by USAID in developing countries in Africa, for example, 0:08:08.723,0:08:13.874 which that survey actually can go so far as to directly measure the HIV status 0:08:13.874,0:08:16.973 of families living in, for example, rural Nigeria. 0:08:16.973,0:08:18.874 Combine that with a world value survey, 0:08:18.874,0:08:23.307 which measures the political opinions and, fortunately for me, the savings behaviors 0:08:23.307,0:08:28.006 of millions of families in hundreds of countries around the world. 0:08:28.006,0:08:31.824 Take all of that data, combine it, and this map is what you get. 0:08:31.824,0:08:34.074 What you find is nine countries around the world 0:08:34.074,0:08:36.726 that have significant native populations 0:08:36.726,0:08:40.773 which speak both futureless and futured languages. 0:08:40.773,0:08:44.307 And what I'm going to do is form statistical matched pairs 0:08:44.307,0:08:49.900 between families that are nearly identical on every dimension that I can measure, 0:08:49.900,0:08:53.437 and then I'm going to explore whether or not the link between language and savings holds 0:08:53.437,0:08:56.920 even after controlling for all of these levels. 0:08:56.920,0:08:59.137 What are the characteristics we can control for? 0:08:59.137,0:09:01.901 Well I'm going to match families on country of birth and residence, 0:09:01.901,0:09:04.303 the demographics -- what sex, their age -- 0:09:04.303,0:09:06.437 their income level within their own country, 0:09:06.437,0:09:09.452 their educational achievement, a lot about their family structure. 0:09:09.452,0:09:12.970 It turns out there are six different ways to be married in Europe. 0:09:12.970,0:09:17.170 And most granularly, I break them down by religion 0:09:17.170,0:09:20.485 where there are 72 categories of religions in the world -- 0:09:20.485,0:09:22.202 so an extreme level of granularity. 0:09:22.202,0:09:26.735 There are 1.4 billion different ways that a family can find itself. 0:09:26.735,0:09:30.784 Now effectively everything I'm going to tell you from now on 0:09:30.784,0:09:33.834 is only comparing these basically nearly identical families. 0:09:33.834,0:09:36.334 It's getting as close as possible to the thought experiment 0:09:36.334,0:09:39.267 of finding two families both of whom live in Brussels 0:09:39.267,0:09:42.267 who are identical on every single one of these dimensions, 0:09:42.267,0:09:45.383 but one of whom speaks Flemish and one of whom speaks French; 0:09:45.383,0:09:48.100 or two families that live in a rural district in Nigeria, 0:09:48.100,0:09:51.933 one of whom speaks Hausa and one of whom speaks Igbo. 0:09:51.933,0:09:55.817 Now even after all of this granular level of control, 0:09:55.817,0:09:58.983 do futureless language speakers seem to save more? 0:09:58.983,0:10:02.636 Yes, futureless language speakers, even after this level of control, 0:10:02.636,0:10:06.334 are 30 percent more likely to report having saved in any given year. 0:10:06.334,0:10:08.150 Does this have cumulative effects? 0:10:08.150,0:10:12.570 Yes, by the time they retire, futureless language speakers, holding constant their income, 0:10:12.570,0:10:15.638 are going to retire with 25 percent more in savings. 0:10:15.638,0:10:18.119 Can we push this data even further? 0:10:18.119,0:10:23.418 Yes, because I just told you, we actually collect a lot of health data as economists. 0:10:23.418,0:10:27.301 Now how can we think about health behaviors to think about savings? 0:10:27.301,0:10:30.134 Well, think about smoking, for example. 0:10:30.134,0:10:33.317 Smoking is in some deep sense negative savings. 0:10:33.317,0:10:36.983 If savings is current pain in exchange for future pleasure, 0:10:36.983,0:10:38.291 smoking is just the opposite. 0:10:38.291,0:10:41.150 It's current pleasure in exchange for future pain. 0:10:41.150,0:10:44.100 What we should expect then is the opposite effect. 0:10:44.100,0:10:45.868 And that's exactly what we find. 0:10:45.868,0:10:49.635 Futureless language speakers are 20 to 24 percent less likely 0:10:49.635,0:10:53.050 to be smoking at any given point in time compared to identical families, 0:10:53.050,0:10:55.951 and they're going to be 13 to 17 percent less likely 0:10:55.951,0:10:58.168 to be obese by the time they retire, 0:10:58.168,0:11:00.631 and they're going to report being 21 percent more likely 0:11:00.631,0:11:02.918 to have used a condom in their last sexual encounter. 0:11:02.918,0:11:06.401 I could go on and on with the list of differences that you can find. 0:11:06.401,0:11:10.201 It's almost impossible not to find a savings behavior 0:11:10.201,0:11:12.800 for which this strong effect isn't present. 0:11:12.800,0:11:17.550 My linguistics and economics colleagues at Yale and I are just starting to do this work 0:11:17.550,0:11:22.717 and really explore and understand the ways that these subtle nudges 0:11:22.717,0:11:28.112 cause us to think more or less about the future every single time we speak. 0:11:28.112,0:11:30.413 Ultimately, the goal, 0:11:30.413,0:11:34.612 once we understand how these subtle effects can change our decision making, 0:11:34.612,0:11:37.562 we want to be able to provide people tools 0:11:37.562,0:11:40.370 so that they can consciously make themselves better savers 0:11:40.370,0:11:43.629 and more conscious investors in their own future. 0:11:43.629,0:11:45.896 Thank you very much. 0:11:45.896,0:11:52.264 (Applause)