1 00:00:00,500 --> 00:00:05,000 The global economic financial crisis has reignited public interest 2 00:00:05,000 --> 00:00:08,416 in something that's actually one of the oldest questions in economics, 3 00:00:08,416 --> 00:00:11,100 dating back to at least before Adam Smith. 4 00:00:11,100 --> 00:00:16,584 And that is, why is it that countries with seemingly similar economies and institutions 5 00:00:16,584 --> 00:00:19,833 can display radically different savings behavior? 6 00:00:19,833 --> 00:00:24,367 Now, many brilliant economists have spent their entire lives working on this question, 7 00:00:24,367 --> 00:00:27,784 and as a field we've made a tremendous amount of headway 8 00:00:27,784 --> 00:00:30,217 and we understand a lot about this. 9 00:00:30,217 --> 00:00:33,851 What I'm here to talk with you about today is an intriguing new hypothesis 10 00:00:33,851 --> 00:00:37,883 and some surprisingly powerful new findings that I've been working on 11 00:00:37,883 --> 00:00:42,589 about the link between the structure of the language you speak 12 00:00:42,604 --> 00:00:47,000 and how you find yourself with the propensity to save. 13 00:00:47,000 --> 00:00:50,067 Let me tell you a little bit about savings rates, a little bit about language, 14 00:00:50,067 --> 00:00:52,417 and then I'll draw that connection. 15 00:00:52,417 --> 00:00:56,984 Let's start by thinking about the member countries of the OECD, 16 00:00:56,984 --> 00:01:00,285 or the Organization of Economic Cooperation and Development. 17 00:01:00,285 --> 00:01:04,184 OECD countries, by and large, you should think about these 18 00:01:04,184 --> 00:01:06,822 as the richest, most industrialized countries in the world. 19 00:01:06,822 --> 00:01:10,872 And by joining the OECD, they were affirming a common commitment 20 00:01:10,872 --> 00:01:14,310 to democracy, open markets and free trade. 21 00:01:14,310 --> 00:01:18,995 Despite all of these similarities, we see huge differences in savings behavior. 22 00:01:18,995 --> 00:01:21,445 So all the way over on the left of this graph, 23 00:01:21,445 --> 00:01:26,179 what you see is many OECD countries saving over a quarter of their GDP every year, 24 00:01:26,179 --> 00:01:30,860 and some OECD countries saving over a third of their GDP per year. 25 00:01:30,860 --> 00:01:35,628 Holding down the right flank of the OECD, all the way on the other side, is Greece. 26 00:01:35,628 --> 00:01:39,044 And what you can see is that over the last 25 years, 27 00:01:39,044 --> 00:01:42,944 Greece has barely managed to save more than 10 percent of their GDP. 28 00:01:42,944 --> 00:01:49,818 It should be noted, of course, that the United States and the U.K. are the next in line. 29 00:01:49,818 --> 00:01:52,396 Now that we see these huge differences in savings rates, 30 00:01:52,396 --> 00:01:56,062 how is it possible that language might have something to do with these differences? 31 00:01:56,062 --> 00:01:59,111 Let me tell you a little bit about how languages fundamentally differ. 32 00:01:59,111 --> 00:02:04,678 Linguists and cognitive scientists have been exploring this question for many years now. 33 00:02:04,678 --> 00:02:09,288 And then I'll draw the connection between these two behaviors. 34 00:02:09,288 --> 00:02:11,896 Many of you have probably already noticed that I'm Chinese. 35 00:02:11,896 --> 00:02:14,861 I grew up in the Midwest of the United States. 36 00:02:14,861 --> 00:02:17,312 And something I realized quite early on 37 00:02:17,312 --> 00:02:20,903 was that the Chinese language forced me to speak about and -- 38 00:02:20,903 --> 00:02:23,794 in fact, more fundamentally than that -- 39 00:02:23,794 --> 00:02:27,884 ever so slightly forced me to think about family in very different ways. 40 00:02:27,884 --> 00:02:29,961 Now, how might that be? Let me give you an example. 41 00:02:29,961 --> 00:02:34,363 Suppose I were talking with you and I was introducing you to my uncle. 42 00:02:34,363 --> 00:02:37,229 You understood exactly what I just said in English. 43 00:02:37,229 --> 00:02:40,179 If we were speaking Mandarin Chinese with each other, though, 44 00:02:40,179 --> 00:02:42,245 I wouldn't have that luxury. 45 00:02:42,245 --> 00:02:45,078 I wouldn't have been able to convey so little information. 46 00:02:45,078 --> 00:02:47,462 What my language would have forced me to do, 47 00:02:47,462 --> 00:02:49,462 instead of just telling you, "This is my uncle," 48 00:02:49,462 --> 00:02:52,744 is to tell you a tremendous amount of additional information. 49 00:02:52,744 --> 00:02:54,563 My language would force me to tell you 50 00:02:54,563 --> 00:02:57,979 whether or not this was an uncle on my mother's side or my father's side, 51 00:02:57,979 --> 00:03:01,063 whether this was an uncle by marriage or by birth, 52 00:03:01,063 --> 00:03:03,295 and if this man was my father's brother, 53 00:03:03,295 --> 00:03:06,079 whether he was older than or younger than my father. 54 00:03:06,079 --> 00:03:10,212 All of this information is obligatory. Chinese doesn't let me ignore it. 55 00:03:10,212 --> 00:03:12,378 And in fact, if I want to speak correctly, 56 00:03:12,378 --> 00:03:15,495 Chinese forces me to constantly think about it. 57 00:03:15,495 --> 00:03:19,444 Now, that fascinated me endlessly as a child, 58 00:03:19,444 --> 00:03:22,679 but what fascinates me even more today as an economist 59 00:03:22,679 --> 00:03:27,980 is that some of these same differences carry through to how languages speak about time. 60 00:03:27,980 --> 00:03:32,229 So for example, if I'm speaking in English, I have to speak grammatically differently 61 00:03:32,229 --> 00:03:34,962 if I'm talking about past rain, "It rained yesterday," 62 00:03:34,962 --> 00:03:37,194 current rain, "It is raining now," 63 00:03:37,194 --> 00:03:39,628 or future rain, "It will rain tomorrow." 64 00:03:39,628 --> 00:03:44,455 Notice that English requires a lot more information with respect to the timing of events. 65 00:03:44,455 --> 00:03:46,462 Why? Because I have to consider that 66 00:03:46,462 --> 00:03:51,245 and I have to modify what I'm saying to say, "It will rain," or "It's going to rain." 67 00:03:51,245 --> 00:03:55,361 It's simply not permissible in English to say, "It rain tomorrow." 68 00:03:55,361 --> 00:03:59,545 In contrast to that, that's almost exactly what you would say in Chinese. 69 00:03:59,545 --> 00:04:01,861 A Chinese speaker can basically say something 70 00:04:01,861 --> 00:04:04,445 that sounds very strange to an English speaker's ears. 71 00:04:04,445 --> 00:04:09,012 They can say, "Yesterday it rain," "Now it rain," "Tomorrow it rain." 72 00:04:09,012 --> 00:04:12,875 In some deep sense, Chinese doesn't divide up the time spectrum 73 00:04:12,875 --> 00:04:19,308 in the same way that English forces us to constantly do in order to speak correctly. 74 00:04:19,308 --> 00:04:20,892 Is this difference in languages 75 00:04:20,892 --> 00:04:25,087 only between very, very distantly related languages, like English and Chinese? 76 00:04:25,087 --> 00:04:26,045 Actually, no. 77 00:04:26,045 --> 00:04:29,778 So many of you know, in this room, that English is a Germanic language. 78 00:04:29,778 --> 00:04:33,693 What you may not have realized is that English is actually an outlier. 79 00:04:33,693 --> 00:04:36,943 It is the only Germanic language that requires this. 80 00:04:36,943 --> 00:04:39,827 For example, most other Germanic language speakers 81 00:04:39,827 --> 00:04:42,844 feel completely comfortable talking about rain tomorrow 82 00:04:42,844 --> 00:04:44,810 by saying, "Morgen regnet es," 83 00:04:44,810 --> 00:04:48,710 quite literally to an English ear, "It rain tomorrow." 84 00:04:48,710 --> 00:04:53,777 This led me, as a behavioral economist, to an intriguing hypothesis. 85 00:04:53,777 --> 00:04:58,026 Could how you speak about time, could how your language forces you to think about time, 86 00:04:58,026 --> 00:05:01,777 affect your propensity to behave across time? 87 00:05:01,777 --> 00:05:04,677 You speak English, a futured language. 88 00:05:04,677 --> 00:05:07,844 And what that means is that every time you discuss the future, 89 00:05:07,844 --> 00:05:09,411 or any kind of a future event, 90 00:05:09,411 --> 00:05:12,810 grammatically you're forced to cleave that from the present 91 00:05:12,810 --> 00:05:15,443 and treat it as if it's something viscerally different. 92 00:05:15,443 --> 00:05:17,943 Now suppose that that visceral difference 93 00:05:17,943 --> 00:05:22,143 makes you subtly dissociate the future from the present every time you speak. 94 00:05:22,143 --> 00:05:24,056 If that's true and it makes the future feel 95 00:05:24,056 --> 00:05:27,039 like something more distant and more different from the present, 96 00:05:27,039 --> 00:05:29,693 that's going to make it harder to save. 97 00:05:29,693 --> 00:05:32,244 If, on the other hand, you speak a futureless language, 98 00:05:32,244 --> 00:05:35,627 the present and the future, you speak about them identically. 99 00:05:35,627 --> 00:05:38,610 If that subtly nudges you to feel about them identically, 100 00:05:38,610 --> 00:05:40,994 that's going to make it easier to save. 101 00:05:40,994 --> 00:05:43,544 Now this is a fanciful theory. 102 00:05:43,544 --> 00:05:46,444 I'm a professor, I get paid to have fanciful theories. 103 00:05:46,444 --> 00:05:50,678 But how would you actually go about testing such a theory? 104 00:05:50,678 --> 00:05:54,744 Well, what I did with that was to access the linguistics literature. 105 00:05:54,744 --> 00:05:59,127 And interestingly enough, there are pockets of futureless language speakers 106 00:05:59,127 --> 00:06:01,060 situated all over the world. 107 00:06:01,060 --> 00:06:04,426 This is a pocket of futureless language speakers in Northern Europe. 108 00:06:04,426 --> 00:06:07,327 Interestingly enough, when you start to crank the data, 109 00:06:07,327 --> 00:06:10,560 these pockets of futureless language speakers all around the world 110 00:06:10,560 --> 00:06:14,494 turn out to be, by and large, some of the world's best savers. 111 00:06:14,494 --> 00:06:16,660 Just to give you a hint of that, 112 00:06:16,660 --> 00:06:19,410 let's look back at that OECD graph that we were talking about. 113 00:06:19,410 --> 00:06:22,794 What you see is that these bars are systematically taller 114 00:06:22,794 --> 00:06:24,926 and systematically shifted to the left 115 00:06:24,926 --> 00:06:29,444 compared to these bars which are the members of the OECD that speak futured languages. 116 00:06:29,444 --> 00:06:30,907 What is the average difference here? 117 00:06:30,907 --> 00:06:34,193 Five percentage points of your GDP saved per year. 118 00:06:34,193 --> 00:06:38,927 Over 25 years that has huge long-run effects on the wealth of your nation. 119 00:06:38,927 --> 00:06:41,627 Now while these findings are suggestive, 120 00:06:41,627 --> 00:06:43,693 countries can be different in so many different ways 121 00:06:43,693 --> 00:06:48,077 that it's very, very difficult sometimes to account for all of these possible differences. 122 00:06:48,077 --> 00:06:52,109 What I'm going to show you, though, is something that I've been engaging in for a year, 123 00:06:52,109 --> 00:06:54,432 which is trying to gather all of the largest datasets 124 00:06:54,432 --> 00:06:56,724 that we have access to as economists, 125 00:06:56,724 --> 00:07:00,106 and I'm going to try and strip away all of those possible differences, 126 00:07:00,106 --> 00:07:02,760 hoping to get this relationship to break. 127 00:07:02,760 --> 00:07:07,791 And just in summary, no matter how far I push this, I can't get it to break. 128 00:07:07,791 --> 00:07:09,556 Let me show you how far you can do that. 129 00:07:09,556 --> 00:07:14,189 One way to imagine that is I gather large datasets from around the world. 130 00:07:14,189 --> 00:07:17,923 So for example, there is the Survey of Health, [Aging] and Retirement in Europe. 131 00:07:17,923 --> 00:07:21,757 From this dataset you actually learn that retired European families 132 00:07:21,757 --> 00:07:24,390 are extremely patient with survey takers. 133 00:07:24,390 --> 00:07:26,306 (Laughter) 134 00:07:26,306 --> 00:07:30,690 So imagine that you're a retired household in Belgium and someone comes to your front door. 135 00:07:30,690 --> 00:07:35,274 "Excuse me, would you mind if I peruse your stock portfolio? 136 00:07:35,274 --> 00:07:38,806 Do you happen to know how much your house is worth? Do you mind telling me? 137 00:07:38,806 --> 00:07:42,073 Would you happen to have a hallway that's more than 10 meters long? 138 00:07:42,073 --> 00:07:46,574 If you do, would you mind if I timed how long it took you to walk down that hallway? 139 00:07:46,574 --> 00:07:50,471 Would you mind squeezing as hard as you can, in your dominant hand, this device 140 00:07:50,471 --> 00:07:51,983 so I can measure your grip strength? 141 00:07:51,983 --> 00:07:56,006 How about blowing into this tube so I can measure your lung capacity?" 142 00:07:56,006 --> 00:07:58,890 The survey takes over a day. 143 00:07:58,890 --> 00:08:00,373 (Laughter) 144 00:08:00,373 --> 00:08:04,273 Combine that with a Demographic and Health Survey 145 00:08:04,273 --> 00:08:08,723 collected by USAID in developing countries in Africa, for example, 146 00:08:08,723 --> 00:08:13,874 which that survey actually can go so far as to directly measure the HIV status 147 00:08:13,874 --> 00:08:16,973 of families living in, for example, rural Nigeria. 148 00:08:16,973 --> 00:08:18,874 Combine that with a world value survey, 149 00:08:18,874 --> 00:08:23,307 which measures the political opinions and, fortunately for me, the savings behaviors 150 00:08:23,307 --> 00:08:28,006 of millions of families in hundreds of countries around the world. 151 00:08:28,006 --> 00:08:31,824 Take all of that data, combine it, and this map is what you get. 152 00:08:31,824 --> 00:08:34,074 What you find is nine countries around the world 153 00:08:34,074 --> 00:08:36,726 that have significant native populations 154 00:08:36,726 --> 00:08:40,773 which speak both futureless and futured languages. 155 00:08:40,773 --> 00:08:44,307 And what I'm going to do is form statistical matched pairs 156 00:08:44,307 --> 00:08:49,900 between families that are nearly identical on every dimension that I can measure, 157 00:08:49,900 --> 00:08:53,437 and then I'm going to explore whether or not the link between language and savings holds 158 00:08:53,437 --> 00:08:56,920 even after controlling for all of these levels. 159 00:08:56,920 --> 00:08:59,137 What are the characteristics we can control for? 160 00:08:59,137 --> 00:09:01,901 Well I'm going to match families on country of birth and residence, 161 00:09:01,901 --> 00:09:04,303 the demographics -- what sex, their age -- 162 00:09:04,303 --> 00:09:06,437 their income level within their own country, 163 00:09:06,437 --> 00:09:09,452 their educational achievement, a lot about their family structure. 164 00:09:09,452 --> 00:09:12,970 It turns out there are six different ways to be married in Europe. 165 00:09:12,970 --> 00:09:17,170 And most granularly, I break them down by religion 166 00:09:17,170 --> 00:09:20,485 where there are 72 categories of religions in the world -- 167 00:09:20,485 --> 00:09:22,202 so an extreme level of granularity. 168 00:09:22,202 --> 00:09:26,735 There are 1.4 billion different ways that a family can find itself. 169 00:09:26,735 --> 00:09:30,784 Now effectively everything I'm going to tell you from now on 170 00:09:30,784 --> 00:09:33,834 is only comparing these basically nearly identical families. 171 00:09:33,834 --> 00:09:36,334 It's getting as close as possible to the thought experiment 172 00:09:36,334 --> 00:09:39,267 of finding two families both of whom live in Brussels 173 00:09:39,267 --> 00:09:42,267 who are identical on every single one of these dimensions, 174 00:09:42,267 --> 00:09:45,383 but one of whom speaks Flemish and one of whom speaks French; 175 00:09:45,383 --> 00:09:48,100 or two families that live in a rural district in Nigeria, 176 00:09:48,100 --> 00:09:51,933 one of whom speaks Hausa and one of whom speaks Igbo. 177 00:09:51,933 --> 00:09:55,817 Now even after all of this granular level of control, 178 00:09:55,817 --> 00:09:58,983 do futureless language speakers seem to save more? 179 00:09:58,983 --> 00:10:02,636 Yes, futureless language speakers, even after this level of control, 180 00:10:02,636 --> 00:10:06,334 are 30 percent more likely to report having saved in any given year. 181 00:10:06,334 --> 00:10:08,150 Does this have cumulative effects? 182 00:10:08,150 --> 00:10:12,570 Yes, by the time they retire, futureless language speakers, holding constant their income, 183 00:10:12,570 --> 00:10:15,638 are going to retire with 25 percent more in savings. 184 00:10:15,638 --> 00:10:18,119 Can we push this data even further? 185 00:10:18,119 --> 00:10:23,418 Yes, because I just told you, we actually collect a lot of health data as economists. 186 00:10:23,418 --> 00:10:27,301 Now how can we think about health behaviors to think about savings? 187 00:10:27,301 --> 00:10:30,134 Well, think about smoking, for example. 188 00:10:30,134 --> 00:10:33,317 Smoking is in some deep sense negative savings. 189 00:10:33,317 --> 00:10:36,983 If savings is current pain in exchange for future pleasure, 190 00:10:36,983 --> 00:10:38,291 smoking is just the opposite. 191 00:10:38,291 --> 00:10:41,150 It's current pleasure in exchange for future pain. 192 00:10:41,150 --> 00:10:44,100 What we should expect then is the opposite effect. 193 00:10:44,100 --> 00:10:45,868 And that's exactly what we find. 194 00:10:45,868 --> 00:10:49,635 Futureless language speakers are 20 to 24 percent less likely 195 00:10:49,635 --> 00:10:53,050 to be smoking at any given point in time compared to identical families, 196 00:10:53,050 --> 00:10:55,951 and they're going to be 13 to 17 percent less likely 197 00:10:55,951 --> 00:10:58,168 to be obese by the time they retire, 198 00:10:58,168 --> 00:11:00,631 and they're going to report being 21 percent more likely 199 00:11:00,631 --> 00:11:02,918 to have used a condom in their last sexual encounter. 200 00:11:02,918 --> 00:11:06,401 I could go on and on with the list of differences that you can find. 201 00:11:06,401 --> 00:11:10,201 It's almost impossible not to find a savings behavior 202 00:11:10,201 --> 00:11:12,800 for which this strong effect isn't present. 203 00:11:12,800 --> 00:11:17,550 My linguistics and economics colleagues at Yale and I are just starting to do this work 204 00:11:17,550 --> 00:11:22,717 and really explore and understand the ways that these subtle nudges 205 00:11:22,717 --> 00:11:28,112 cause us to think more or less about the future every single time we speak. 206 00:11:28,112 --> 00:11:30,413 Ultimately, the goal, 207 00:11:30,413 --> 00:11:34,612 once we understand how these subtle effects can change our decision making, 208 00:11:34,612 --> 00:11:37,562 we want to be able to provide people tools 209 00:11:37,562 --> 00:11:40,370 so that they can consciously make themselves better savers 210 00:11:40,370 --> 00:11:43,629 and more conscious investors in their own future. 211 00:11:43,629 --> 00:11:45,896 Thank you very much. 212 00:11:45,896 --> 00:11:52,264 (Applause)