1 00:00:00,000 --> 00:00:01,992 [SQUEAKING] 2 00:00:01,992 --> 00:00:03,486 [RUSTLING] 3 00:00:03,486 --> 00:00:04,980 [CLICKING] 4 00:00:11,377 --> 00:00:12,210 FRANK SCHILBACH: OK. 5 00:00:12,210 --> 00:00:13,770 So let me sort of just recap what 6 00:00:13,770 --> 00:00:16,140 we discussed last time fairly quickly, 7 00:00:16,140 --> 00:00:18,180 and then I want to move to empirical evidence 8 00:00:18,180 --> 00:00:19,710 on a variety of settings. 9 00:00:19,710 --> 00:00:22,050 We might not get through all of the slides. 10 00:00:22,050 --> 00:00:23,070 That's fine. 11 00:00:23,070 --> 00:00:27,370 In that case, we'll just discuss some of this in recitation. 12 00:00:27,370 --> 00:00:30,210 So let me sort of recap what Kahneman and Tversky, 13 00:00:30,210 --> 00:00:34,140 in their 1979 article, were proposing 14 00:00:34,140 --> 00:00:36,510 based on a bunch of experiments and empirical evidence 15 00:00:36,510 --> 00:00:38,610 that they had collected. 16 00:00:38,610 --> 00:00:42,840 So their theory, it was called prospect theory 17 00:00:42,840 --> 00:00:43,950 what they proposed. 18 00:00:43,950 --> 00:00:46,050 Versions of prospect theory is essentially 19 00:00:46,050 --> 00:00:49,500 versions of reference dependent utility, have been used 20 00:00:49,500 --> 00:00:52,608 or used prominently now in economics. 21 00:00:52,608 --> 00:00:54,150 So the first thing that they proposed 22 00:00:54,150 --> 00:00:57,550 was, what matters, what the carrier of utility is, 23 00:00:57,550 --> 00:01:00,390 is changes rather than levels. 24 00:01:00,390 --> 00:01:03,370 That's to say it doesn't matter for you necessarily how warm it 25 00:01:03,370 --> 00:01:03,870 is. 26 00:01:03,870 --> 00:01:06,370 It matters kind of what's the change of temperature compared 27 00:01:06,370 --> 00:01:07,140 to yesterday. 28 00:01:07,140 --> 00:01:08,640 It doesn't matter that much how much 29 00:01:08,640 --> 00:01:10,170 money people have in total. 30 00:01:10,170 --> 00:01:13,590 It matters how much that changes relative to what 31 00:01:13,590 --> 00:01:16,290 they had previously. 32 00:01:16,290 --> 00:01:19,750 More generally, what matters for people is essentially 33 00:01:19,750 --> 00:01:23,220 a certain consumption or the like relative 34 00:01:23,220 --> 00:01:27,240 to reference point as opposed to in absolute terms. 35 00:01:27,240 --> 00:01:31,350 Second, loss aversion, this is losses loom larger than gains. 36 00:01:31,350 --> 00:01:33,910 And we had some evidence of that in the last lecture. 37 00:01:33,910 --> 00:01:37,110 That's to say, if you lose some money or some consumption 38 00:01:37,110 --> 00:01:41,040 or anything else, grades, et cetera, 39 00:01:41,040 --> 00:01:43,350 a loss relative to either your status 40 00:01:43,350 --> 00:01:47,100 quo or to your expectation looms larger, is more important, 41 00:01:47,100 --> 00:01:50,010 hurts more than a gain of the same magnitude 42 00:01:50,010 --> 00:01:52,200 in the positive direction. 43 00:01:52,200 --> 00:01:54,660 And number three, which we talked about quickly, 44 00:01:54,660 --> 00:01:58,380 is what's referred to as diminishing sensitivity. 45 00:01:58,380 --> 00:02:01,470 That is people are risk averse in the gain domain, 46 00:02:01,470 --> 00:02:04,020 but risk loving in the loss domain. 47 00:02:04,020 --> 00:02:09,539 That's to say, for example, if you think about distance, time, 48 00:02:09,539 --> 00:02:13,380 chance, and the like, going from 0 to 1 or from 1 to 2 49 00:02:13,380 --> 00:02:15,810 or from 2 to 3 is more important for you 50 00:02:15,810 --> 00:02:20,400 than going from, like, 100 to 101, 101 to 102, and so on. 51 00:02:20,400 --> 00:02:23,700 Essentially, the further you go away 52 00:02:23,700 --> 00:02:27,120 from your status quo, your reference point, 53 00:02:27,120 --> 00:02:29,490 any marginal change is diminishing, right? 54 00:02:29,490 --> 00:02:33,310 And that's true for both the gain domain and the loss 55 00:02:33,310 --> 00:02:33,810 domain. 56 00:02:33,810 --> 00:02:36,720 So these are sort of the main three characteristics 57 00:02:36,720 --> 00:02:39,728 related to what Kahneman-Tversky called the value function. 58 00:02:39,728 --> 00:02:41,520 We can think of this as essentially version 59 00:02:41,520 --> 00:02:43,267 of the utility function. 60 00:02:43,267 --> 00:02:44,850 There's a fourth characteristic, which 61 00:02:44,850 --> 00:02:46,808 is probability weighting, which we're not going 62 00:02:46,808 --> 00:02:49,170 to talk about at least for now. 63 00:02:49,170 --> 00:02:51,870 Are there any questions on these three things so far? 64 00:02:57,840 --> 00:02:58,610 OK. 65 00:02:58,610 --> 00:03:04,310 So now, prospect theory is then what Kahneman and Tversky 66 00:03:04,310 --> 00:03:05,120 were proposing. 67 00:03:05,120 --> 00:03:07,010 They were essentially saying, instead of 68 00:03:07,010 --> 00:03:10,820 having concave utility, which I showed you last week, 69 00:03:10,820 --> 00:03:13,790 instead your utility function may look like this. 70 00:03:13,790 --> 00:03:16,580 And what are sort of the features of this utility 71 00:03:16,580 --> 00:03:17,360 function? 72 00:03:17,360 --> 00:03:19,913 What are the three key features that I just showed you? 73 00:03:19,913 --> 00:03:21,830 How are they showing up in this function here? 74 00:03:32,480 --> 00:03:34,040 Yes? 75 00:03:34,040 --> 00:03:35,873 AUDIENCE: C minus [INAUDIBLE] is the change? 76 00:03:35,873 --> 00:03:36,832 FRANK SCHILBACH: Right. 77 00:03:36,832 --> 00:03:38,610 So the carrier of the utility function-- 78 00:03:38,610 --> 00:03:41,030 so what we have here is c and r. 79 00:03:41,030 --> 00:03:42,082 c is like consumption. 80 00:03:42,082 --> 00:03:43,040 That could be anything. 81 00:03:43,040 --> 00:03:43,850 That could be apples. 82 00:03:43,850 --> 00:03:44,767 That could be bananas. 83 00:03:44,767 --> 00:03:47,990 That could be sort of how much money people have 84 00:03:47,990 --> 00:03:50,840 available to consume overall. 85 00:03:50,840 --> 00:03:53,480 The carrier of the utility function is not c itself. 86 00:03:53,480 --> 00:03:56,360 It's c minus r, so it's c of relative to some reference 87 00:03:56,360 --> 00:03:57,840 point r. 88 00:03:57,840 --> 00:03:59,240 That's exactly right. 89 00:03:59,240 --> 00:04:01,520 And if r is the status quo, if r is 90 00:04:01,520 --> 00:04:04,310 how much we have right now or the person has right now, 91 00:04:04,310 --> 00:04:07,430 c minus r is the change relative to the status quo. 92 00:04:07,430 --> 00:04:10,005 Notice that r-- we're going to talk about this a little bit-- 93 00:04:10,005 --> 00:04:11,130 could be also other things. 94 00:04:11,130 --> 00:04:13,500 It doesn't have to be necessarily the status quo. 95 00:04:13,500 --> 00:04:16,100 It could be also people's expectation or their goals 96 00:04:16,100 --> 00:04:18,380 or their aspirations for the future, right? 97 00:04:18,380 --> 00:04:20,089 The key part is, however, what matters 98 00:04:20,089 --> 00:04:21,980 is-- this is the first thing I was saying. 99 00:04:21,980 --> 00:04:24,050 It's changes rather than levels, changes 100 00:04:24,050 --> 00:04:26,960 relative to some reference point or consumption relative 101 00:04:26,960 --> 00:04:28,252 to some reference point. 102 00:04:28,252 --> 00:04:29,210 That's number one, yes. 103 00:04:32,090 --> 00:04:33,155 Yes? 104 00:04:33,155 --> 00:04:34,530 AUDIENCE: The curve flattens out, 105 00:04:34,530 --> 00:04:36,140 which is diminishing sensitivity. 106 00:04:36,140 --> 00:04:36,590 FRANK SCHILBACH: Exactly. 107 00:04:36,590 --> 00:04:38,670 The curve flattens out in both directions. 108 00:04:38,670 --> 00:04:40,670 That's diminishing sensitivity. 109 00:04:40,670 --> 00:04:43,340 It's essentially concave in the gain domain, 110 00:04:43,340 --> 00:04:46,220 in the domain where c is larger than r. 111 00:04:46,220 --> 00:04:48,020 And it's convex in the loss domain 112 00:04:48,020 --> 00:04:51,870 where c is smaller than r, right? 113 00:04:51,870 --> 00:04:54,920 And that's exactly the issue that essentially the first, 114 00:04:54,920 --> 00:05:00,050 the marginal change, going from, say, 1 to 2 115 00:05:00,050 --> 00:05:02,510 is relatively large compared to a marginal change going 116 00:05:02,510 --> 00:05:03,620 from 10 to 11. 117 00:05:03,620 --> 00:05:06,350 That's both going in the right direction in the gains domain 118 00:05:06,350 --> 00:05:08,450 and the left direction in the loss domain. 119 00:05:08,450 --> 00:05:09,420 Yes? 120 00:05:09,420 --> 00:05:12,960 AUDIENCE: For the loss aversion, the left side 121 00:05:12,960 --> 00:05:14,630 is steeper than the right side. 122 00:05:14,630 --> 00:05:15,672 FRANK SCHILBACH: Exactly. 123 00:05:15,672 --> 00:05:18,290 In particular, there's a kink in this function. 124 00:05:18,290 --> 00:05:25,100 When you look at 0, where c equals r, the gain and loss 125 00:05:25,100 --> 00:05:29,720 domain intersect, there we have a kink in the value function, 126 00:05:29,720 --> 00:05:32,510 in the utility function, which essentially exactly is the loss 127 00:05:32,510 --> 00:05:35,210 domain, the loss aversion which is like going to the right 128 00:05:35,210 --> 00:05:37,190 is less steep than going to the left. 129 00:05:37,190 --> 00:05:38,870 Put differently, if you lose, if you're 130 00:05:38,870 --> 00:05:40,820 sort of below the reference point, 131 00:05:40,820 --> 00:05:45,807 that's more painful than being the same amount of units to be 132 00:05:45,807 --> 00:05:46,890 above the reference point. 133 00:05:46,890 --> 00:05:47,640 That's number two. 134 00:05:47,640 --> 00:05:49,980 That's essentially exactly the loss aversion. 135 00:05:49,980 --> 00:05:52,390 So I just wrote down all of that. 136 00:05:52,390 --> 00:05:53,480 Again, let me repeat. 137 00:05:53,480 --> 00:05:55,880 Carrier of the utility changes relative to the reference 138 00:05:55,880 --> 00:05:56,720 point-- 139 00:05:56,720 --> 00:05:58,940 excuse me-- rather than levels. 140 00:05:58,940 --> 00:06:01,010 Second, there's loss aversion. 141 00:06:01,010 --> 00:06:02,750 There's a kink at 0 in this function. 142 00:06:02,750 --> 00:06:05,640 And three, there's diminishing sensitivity, 143 00:06:05,640 --> 00:06:08,270 which is concavity in gains and convexity in losses. 144 00:06:11,920 --> 00:06:13,090 Any questions on that? 145 00:06:15,810 --> 00:06:17,343 Now, a key question here is-- 146 00:06:17,343 --> 00:06:18,510 I want to sort of flag this. 147 00:06:18,510 --> 00:06:19,740 We're going to talk about this a little bit 148 00:06:19,740 --> 00:06:20,823 at the end of the lecture. 149 00:06:20,823 --> 00:06:23,323 We're going to talk to this a little bit in the next problem 150 00:06:23,323 --> 00:06:25,740 set is kind of like how is the reference point determined. 151 00:06:25,740 --> 00:06:27,540 And does it matter? 152 00:06:27,540 --> 00:06:29,550 As I said before, in Kahneman-Tversky's work, 153 00:06:29,550 --> 00:06:31,840 a lot of the reference point is the status quo. 154 00:06:31,840 --> 00:06:34,020 So they essentially postulated the status quo is 155 00:06:34,020 --> 00:06:36,510 what really matters originally. 156 00:06:36,510 --> 00:06:39,583 I think people have moved toward saying the reference point. 157 00:06:39,583 --> 00:06:42,000 And this is what Koszegi and Rabin and others have written 158 00:06:42,000 --> 00:06:44,430 down in their models of reference dependence utility 159 00:06:44,430 --> 00:06:49,110 and recent more economics work is what really matters 160 00:06:49,110 --> 00:06:50,440 is expectation. 161 00:06:50,440 --> 00:06:54,690 So what do you expect to consume or to have and so on? 162 00:06:54,690 --> 00:06:55,710 That matters. 163 00:06:55,710 --> 00:06:58,325 That sometimes coincides with the status quo. 164 00:06:58,325 --> 00:06:59,700 For example, if you have a house, 165 00:06:59,700 --> 00:07:01,367 the status quo is that you have a house. 166 00:07:01,367 --> 00:07:04,050 You probably assume that you have a house in the future. 167 00:07:04,050 --> 00:07:05,340 These things coincide. 168 00:07:05,340 --> 00:07:06,900 If you think about wages, et cetera, 169 00:07:06,900 --> 00:07:09,210 what seems to matter often is not so much 170 00:07:09,210 --> 00:07:11,370 what people's wages are right now. 171 00:07:11,370 --> 00:07:13,770 What matters is what wage gains and so on do 172 00:07:13,770 --> 00:07:15,720 they expect to receive in the future. 173 00:07:15,720 --> 00:07:19,800 And they evaluate their future, their outcomes in the future, 174 00:07:19,800 --> 00:07:22,740 not necessarily to the current wage, but rather 175 00:07:22,740 --> 00:07:25,690 what they expect they would get in the future. 176 00:07:25,690 --> 00:07:26,190 OK. 177 00:07:26,190 --> 00:07:27,810 And so here's an example. 178 00:07:27,810 --> 00:07:30,210 And you'll have some problems set questions. 179 00:07:30,210 --> 00:07:32,040 Again, this is a problem set three-- 180 00:07:32,040 --> 00:07:34,440 which is not posted yet, but will be-- 181 00:07:34,440 --> 00:07:37,290 of that kind, which is you might have reference 182 00:07:37,290 --> 00:07:39,060 dependent utility over-- 183 00:07:39,060 --> 00:07:40,680 this is just a very simple example-- 184 00:07:40,680 --> 00:07:41,760 shirts and money. 185 00:07:41,760 --> 00:07:43,780 So you have essentially two different domains. 186 00:07:43,780 --> 00:07:45,630 You have, essentially, losses and gains over 187 00:07:45,630 --> 00:07:47,040 both of those domains. 188 00:07:47,040 --> 00:07:48,810 You have a reference point, which is rs, 189 00:07:48,810 --> 00:07:50,227 is how many shirts you might have. 190 00:07:50,227 --> 00:07:53,100 You have a reference point, rm, how much money you might have. 191 00:07:53,100 --> 00:07:54,900 Now, what's important here is that, 192 00:07:54,900 --> 00:07:57,150 essentially, when you think about buying a shirt 193 00:07:57,150 --> 00:08:00,420 or selling a shirt, there's going 194 00:08:00,420 --> 00:08:03,547 to be two dimensions which you have to sort of consider. 195 00:08:03,547 --> 00:08:05,130 And when you think about the endowment 196 00:08:05,130 --> 00:08:07,500 effect of [INAUDIBLE] and so on, you 197 00:08:07,500 --> 00:08:11,830 have to consider not only the losses 198 00:08:11,830 --> 00:08:15,173 and gains and shirts, but also the losses and gains and money. 199 00:08:15,173 --> 00:08:17,340 So that's to say, if you're trying to buy something, 200 00:08:17,340 --> 00:08:18,840 you're going to get a gain in shirts 201 00:08:18,840 --> 00:08:21,060 relative to the reference point if it's unexpected. 202 00:08:21,060 --> 00:08:22,890 But you'll also have a loss in money. 203 00:08:22,890 --> 00:08:24,720 Similarly, if you're going to sell a shirt, 204 00:08:24,720 --> 00:08:28,650 you're going to have a loss in shirts, but a gain in money. 205 00:08:28,650 --> 00:08:30,390 And these things then interact. 206 00:08:30,390 --> 00:08:31,728 Now, what's the value function? 207 00:08:31,728 --> 00:08:33,270 The value function, as I said before, 208 00:08:33,270 --> 00:08:35,909 is usually concave in the gain domain 209 00:08:35,909 --> 00:08:38,679 and convex in the last domain. 210 00:08:38,679 --> 00:08:39,630 There's a kink at 0. 211 00:08:39,630 --> 00:08:41,640 It's steeper on the left than on the right. 212 00:08:41,640 --> 00:08:47,670 Usually, we think the relative slope is about 2, 2.5, OK? 213 00:08:47,670 --> 00:08:50,010 So one version of that would be this function 214 00:08:50,010 --> 00:08:50,940 that I wrote down. 215 00:08:50,940 --> 00:08:52,920 Again, there will be some problem 216 00:08:52,920 --> 00:08:56,080 set questions, et cetera, sort of to clarify that. 217 00:08:56,080 --> 00:08:58,050 But one key question here is, then 218 00:08:58,050 --> 00:08:59,370 what are the different domains? 219 00:08:59,370 --> 00:09:02,020 And that's kind of a question of mental accounting. 220 00:09:02,020 --> 00:09:04,235 We'll get to this in the second half of the course. 221 00:09:04,235 --> 00:09:05,610 The question's kind of like, what 222 00:09:05,610 --> 00:09:06,818 are the different categories? 223 00:09:06,818 --> 00:09:07,950 Do you have shirts? 224 00:09:07,950 --> 00:09:10,800 Do you have pants, sweaters? 225 00:09:10,800 --> 00:09:13,680 Or is it just for clothes overall? 226 00:09:13,680 --> 00:09:17,490 Or when you think about earnings and consumption, et cetera, 227 00:09:17,490 --> 00:09:18,510 is it daily consumption? 228 00:09:18,510 --> 00:09:19,560 Is it weekly consumption? 229 00:09:19,560 --> 00:09:21,190 Is it monthly consumption? 230 00:09:21,190 --> 00:09:24,150 So there's lots of questions on how to exactly specify 231 00:09:24,150 --> 00:09:25,560 this utility function. 232 00:09:25,560 --> 00:09:29,590 These questions are mostly unanswered in the literature. 233 00:09:29,590 --> 00:09:31,445 So for now, for us in our purposes, 234 00:09:31,445 --> 00:09:32,820 we're going to essentially assume 235 00:09:32,820 --> 00:09:35,490 there is a value function given and then 236 00:09:35,490 --> 00:09:36,900 sort of work with that. 237 00:09:39,560 --> 00:09:40,610 Any questions on that? 238 00:09:43,440 --> 00:09:45,120 OK, great. 239 00:09:45,120 --> 00:09:47,160 So now, we're going to talk about a number 240 00:09:47,160 --> 00:09:48,310 of different applications. 241 00:09:48,310 --> 00:09:51,480 We talked a little bit already about the endowment effect 242 00:09:51,480 --> 00:09:52,380 and about insurance. 243 00:09:52,380 --> 00:09:54,660 I'm going to skip this. 244 00:09:54,660 --> 00:09:58,565 There's some of this already in recitation in the problem sets. 245 00:09:58,565 --> 00:10:00,690 We're going to particularly talk about labor supply 246 00:10:00,690 --> 00:10:02,310 and employment decisions, essentially 247 00:10:02,310 --> 00:10:03,990 how much do people like to work. 248 00:10:03,990 --> 00:10:06,150 And is effort or people's work decisions, 249 00:10:06,150 --> 00:10:08,430 are they reference dependent? 250 00:10:08,430 --> 00:10:10,180 We're going to talk about finances, 251 00:10:10,180 --> 00:10:12,540 what was mentioned last time already about investment 252 00:10:12,540 --> 00:10:13,110 decisions. 253 00:10:13,110 --> 00:10:14,963 When do people sell and buy stocks? 254 00:10:14,963 --> 00:10:16,380 We're going to talk about housing. 255 00:10:16,380 --> 00:10:21,300 When do people decide to sell or buy a house and at what price? 256 00:10:21,300 --> 00:10:23,970 We're going to talk about sports, in particular marathon 257 00:10:23,970 --> 00:10:27,510 running and golf. 258 00:10:27,510 --> 00:10:29,280 There's some papers on domestic violence 259 00:10:29,280 --> 00:10:30,990 we're going to talk very briefly about. 260 00:10:30,990 --> 00:10:32,740 And then we talk a little bit about firms. 261 00:10:32,740 --> 00:10:35,790 How do firms think about pricing and so on? 262 00:10:35,790 --> 00:10:38,340 What is sort of the market response 263 00:10:38,340 --> 00:10:40,140 to reference dependence? 264 00:10:40,140 --> 00:10:42,690 That's to say, given that we know there's lots of reference 265 00:10:42,690 --> 00:10:45,900 dependence in the world, now, as a firm 266 00:10:45,900 --> 00:10:50,070 or treating other people, how should we think about, 267 00:10:50,070 --> 00:10:52,020 how does that affect, our own behavior 268 00:10:52,020 --> 00:10:54,750 or how maybe firms interact with us? 269 00:10:54,750 --> 00:10:55,710 OK. 270 00:10:55,710 --> 00:10:58,230 So let's start with labor supply. 271 00:10:58,230 --> 00:11:02,130 Let's start with a very simple example. 272 00:11:02,130 --> 00:11:04,650 Suppose there's a worker in the following situation. 273 00:11:04,650 --> 00:11:08,110 She can freely choose how many hours she works every day. 274 00:11:08,110 --> 00:11:12,330 And there are frequent temporary changes in her hourly wage. 275 00:11:12,330 --> 00:11:14,220 Now, there's different relationships 276 00:11:14,220 --> 00:11:16,620 between wages and hours per day. 277 00:11:16,620 --> 00:11:19,080 You could always work the same number of hours. 278 00:11:19,080 --> 00:11:21,960 You could work more hours on the days when wages are high. 279 00:11:21,960 --> 00:11:26,137 Or you could work fewer hours on days when the wages are high. 280 00:11:26,137 --> 00:11:27,720 What does sort of standard theory say? 281 00:11:27,720 --> 00:11:28,590 What should you do? 282 00:11:38,440 --> 00:11:39,130 Yes? 283 00:11:39,130 --> 00:11:39,700 Two? 284 00:11:39,700 --> 00:11:40,300 AUDIENCE: Two. 285 00:11:40,300 --> 00:11:42,190 FRANK SCHILBACH: Why is that? 286 00:11:42,190 --> 00:11:46,262 AUDIENCE: Because that maximizes your expected value for time. 287 00:11:46,262 --> 00:11:47,220 FRANK SCHILBACH: Right. 288 00:11:47,220 --> 00:11:51,070 So if hours are effortful, you usually don't like to work. 289 00:11:51,070 --> 00:11:54,370 You should work during the hours when 290 00:11:54,370 --> 00:11:56,558 your payment is the largest. 291 00:11:56,558 --> 00:11:57,100 That's right. 292 00:11:57,100 --> 00:11:59,920 So what about option number one? 293 00:11:59,920 --> 00:12:02,450 Why might option number one be optimal? 294 00:12:02,450 --> 00:12:04,225 So what you're saying is exactly right. 295 00:12:04,225 --> 00:12:06,442 It depends a little bit on something else. 296 00:12:06,442 --> 00:12:07,150 And what is that? 297 00:12:10,685 --> 00:12:12,310 Why might you choose number one anyway? 298 00:12:15,490 --> 00:12:16,970 AUDIENCE: Habit-forming is nice. 299 00:12:16,970 --> 00:12:18,640 FRANK SCHILBACH: Yeah, there could be sort of habits, 300 00:12:18,640 --> 00:12:19,130 exactly. 301 00:12:19,130 --> 00:12:21,047 Or it could just be that it's really effortful 302 00:12:21,047 --> 00:12:22,750 to work 12 hours in one day. 303 00:12:22,750 --> 00:12:26,180 Maybe there's kids at home, or maybe it's just really tedious 304 00:12:26,180 --> 00:12:26,680 to work. 305 00:12:26,680 --> 00:12:29,430 At some point, you just want to go home and do other stuff. 306 00:12:29,430 --> 00:12:31,900 So it could just be that working beyond, say, eight or nine 307 00:12:31,900 --> 00:12:33,435 hours per day is really tough to do. 308 00:12:33,435 --> 00:12:34,810 So then you might say, I'm always 309 00:12:34,810 --> 00:12:35,893 going to work eight hours. 310 00:12:35,893 --> 00:12:38,385 I'd love to work more, but it's difficult to do. 311 00:12:38,385 --> 00:12:39,760 So essentially, it's just to say, 312 00:12:39,760 --> 00:12:43,930 if the function of the effort as a function of hours is convex, 313 00:12:43,930 --> 00:12:46,845 then you might sort of keep it the same. 314 00:12:46,845 --> 00:12:48,220 Surely, what you don't want to do 315 00:12:48,220 --> 00:12:52,210 is number three, working fewer hours 316 00:12:52,210 --> 00:12:55,300 on days when wages are high unless effort costs are 317 00:12:55,300 --> 00:12:56,770 particularly high on those days. 318 00:12:56,770 --> 00:12:58,750 So it could be that it's really super hot. 319 00:12:58,750 --> 00:13:00,990 Or it could be it's tedious to work on those days. 320 00:13:00,990 --> 00:13:02,990 And you might say, then you don't want to do it. 321 00:13:02,990 --> 00:13:04,480 But assuming that's not the case, 322 00:13:04,480 --> 00:13:05,788 you kind of want to avoid this. 323 00:13:05,788 --> 00:13:07,330 Because for the same number of hours, 324 00:13:07,330 --> 00:13:10,710 you're going to make less money overall. 325 00:13:10,710 --> 00:13:13,010 And so here's a concrete example. 326 00:13:13,010 --> 00:13:15,280 Suppose wage is 5 hours an hour on day one 327 00:13:15,280 --> 00:13:17,190 and 10 hours a day on day two. 328 00:13:17,190 --> 00:13:18,700 So there's three strategies. 329 00:13:18,700 --> 00:13:20,170 You can work 8 hours on both days. 330 00:13:20,170 --> 00:13:22,960 You can work 6 hours on day one, 9 hours on day two, 331 00:13:22,960 --> 00:13:26,950 or the opposite, 9 hours on day one and 6 hours on day two. 332 00:13:26,950 --> 00:13:30,313 So if you do that, you can sort of calculate how much that is. 333 00:13:30,313 --> 00:13:32,230 You can essentially work 8 hours on both days. 334 00:13:32,230 --> 00:13:33,310 You get 120 hours. 335 00:13:33,310 --> 00:13:38,980 You can work 6 hours on days one and two, 336 00:13:38,980 --> 00:13:41,200 which makes $120 as well. 337 00:13:41,200 --> 00:13:45,130 Or you can essentially do the opposite, which makes you $105. 338 00:13:45,130 --> 00:13:46,510 This is what I was saying. 339 00:13:46,510 --> 00:13:49,180 Option three doesn't make a lot of sense 340 00:13:49,180 --> 00:13:50,950 unless effort costs are particularly 341 00:13:50,950 --> 00:13:53,350 high on certain days when the wages are high. 342 00:13:53,350 --> 00:13:55,730 We're assuming that away for now. 343 00:13:55,730 --> 00:13:56,688 And so now option two-- 344 00:13:56,688 --> 00:13:58,605 and this is what you were saying-- essentially 345 00:13:58,605 --> 00:13:59,770 saves you an hour overall. 346 00:13:59,770 --> 00:14:01,950 You work only 15 hours instead of 16 hours. 347 00:14:01,950 --> 00:14:04,270 And you make the same amount of money. 348 00:14:04,270 --> 00:14:10,360 Now, unless the ninth hour is extremely costly for you to do, 349 00:14:10,360 --> 00:14:12,410 you might not want to do that. 350 00:14:12,410 --> 00:14:14,200 OK. 351 00:14:14,200 --> 00:14:19,390 Now, why might you do something else instead? 352 00:14:19,390 --> 00:14:22,000 Or where does reference dependence come in here? 353 00:14:25,010 --> 00:14:26,100 Yes. 354 00:14:26,100 --> 00:14:29,105 AUDIENCE: I see on the high wage day you make more 355 00:14:29,105 --> 00:14:31,743 than the less wage day, so I feel like stopping maybe. 356 00:14:31,743 --> 00:14:33,410 FRANK SCHILBACH: And why would you stop? 357 00:14:33,410 --> 00:14:36,686 What's causing you to stop? 358 00:14:36,686 --> 00:14:40,900 AUDIENCE: [INAUDIBLE] wages higher relative to [INAUDIBLE].. 359 00:14:40,900 --> 00:14:41,920 FRANK SCHILBACH: Yeah. 360 00:14:41,920 --> 00:14:42,520 Yes. 361 00:14:42,520 --> 00:14:45,880 And so what are you evaluating? 362 00:14:45,880 --> 00:14:53,540 Or what's the-- or what happens, for example, 363 00:14:53,540 --> 00:14:58,563 if you work only 6 hours on a different day? 364 00:14:58,563 --> 00:15:00,730 How much do you make on the sixth hour day, I guess, 365 00:15:00,730 --> 00:15:04,960 which would be $30, right? 366 00:15:04,960 --> 00:15:09,448 And so what are you comparing that to, I guess? 367 00:15:09,448 --> 00:15:11,490 AUDIENCE: You're comparing it to the actual money 368 00:15:11,490 --> 00:15:12,952 you made at the end of the day. 369 00:15:12,952 --> 00:15:13,910 FRANK SCHILBACH: Right. 370 00:15:13,910 --> 00:15:16,213 But so suppose you, on average, want 371 00:15:16,213 --> 00:15:17,630 to make a certain amount of money, 372 00:15:17,630 --> 00:15:19,870 which is $50, $60 and so on. 373 00:15:19,870 --> 00:15:22,370 Now, if on some days you make a lot of money and on some day 374 00:15:22,370 --> 00:15:24,850 you make very little money, you might sort of 375 00:15:24,850 --> 00:15:27,082 evaluate that separately and say, on that day, 376 00:15:27,082 --> 00:15:28,540 I'm essentially in the loss domain. 377 00:15:28,540 --> 00:15:31,880 I'm below my target or below my expectation. 378 00:15:31,880 --> 00:15:34,840 And so if you evaluate your utility that way, 379 00:15:34,840 --> 00:15:37,360 you might sort of not want that because it feels essentially 380 00:15:37,360 --> 00:15:39,070 you're below a certain threshold. 381 00:15:39,070 --> 00:15:41,700 It feels kind of like a loss relative to your expectation 382 00:15:41,700 --> 00:15:43,810 and so on when you might be inclined to work 383 00:15:43,810 --> 00:15:45,760 a lot of hours. 384 00:15:45,760 --> 00:15:48,110 Instead, on the days when you make a lot of money, 385 00:15:48,110 --> 00:15:48,910 why might you stop? 386 00:15:52,310 --> 00:15:53,160 Yes? 387 00:15:53,160 --> 00:15:54,705 AUDIENCE: You might have a target 388 00:15:54,705 --> 00:15:57,080 that you expect to meet every day to cover your expenses. 389 00:15:57,080 --> 00:16:00,210 And if you feel like the work [INAUDIBLE] reach that target, 390 00:16:00,210 --> 00:16:02,142 you might [INAUDIBLE]. 391 00:16:02,142 --> 00:16:03,100 FRANK SCHILBACH: Right. 392 00:16:03,100 --> 00:16:04,740 So if you target, your reference point, 393 00:16:04,740 --> 00:16:07,470 is essentially a certain number, you 394 00:16:07,470 --> 00:16:09,750 might reach that target quickly because your wage 395 00:16:09,750 --> 00:16:11,232 is pretty high on that day. 396 00:16:11,232 --> 00:16:12,690 And once you reach that target, you 397 00:16:12,690 --> 00:16:14,640 might say, well, now utility function 398 00:16:14,640 --> 00:16:16,758 is relatively not very steep anymore 399 00:16:16,758 --> 00:16:18,300 relative to being in the loss domain. 400 00:16:18,300 --> 00:16:19,500 So it's flatter. 401 00:16:19,500 --> 00:16:21,840 So then you might just stop relatively soon 402 00:16:21,840 --> 00:16:25,590 because, essentially, any marginal earnings are not 403 00:16:25,590 --> 00:16:27,900 really valuable for you anymore. 404 00:16:27,900 --> 00:16:30,560 OK? 405 00:16:30,560 --> 00:16:32,180 Any questions on that or comments? 406 00:16:36,190 --> 00:16:39,372 So why do we want the wage changes to be temporary here? 407 00:16:39,372 --> 00:16:41,080 What's an issue here when you sort of try 408 00:16:41,080 --> 00:16:43,360 to look at this in the data? 409 00:16:43,360 --> 00:16:45,110 Suppose I had persistent wage changes. 410 00:16:45,110 --> 00:16:45,610 Yeah. 411 00:16:45,610 --> 00:16:48,713 AUDIENCE: So you can have a frame of reference? 412 00:16:48,713 --> 00:16:49,630 FRANK SCHILBACH: Yeah. 413 00:16:49,630 --> 00:16:51,630 You want to kind of keep the reference constant. 414 00:16:51,630 --> 00:16:54,423 So in some sense, if wage changes are permanent, 415 00:16:54,423 --> 00:16:56,090 then you get essentially income effects. 416 00:16:56,090 --> 00:16:57,610 You'll be a lot richer overall. 417 00:16:57,610 --> 00:16:59,465 If they're only temporary, essentially, 418 00:16:59,465 --> 00:17:01,840 you can sort of argue that, essentially, your expectation 419 00:17:01,840 --> 00:17:03,050 should be the same. 420 00:17:03,050 --> 00:17:05,567 And once you reach, once you have a lot more money, 421 00:17:05,567 --> 00:17:07,150 the neoclassical model should actually 422 00:17:07,150 --> 00:17:11,020 say that there should be income affects. 423 00:17:11,020 --> 00:17:12,910 Essentially, the neoclassical model says, 424 00:17:12,910 --> 00:17:15,190 you should essentially aggregate all of your income and say, 425 00:17:15,190 --> 00:17:17,023 it doesn't really matter whether you earn it 426 00:17:17,023 --> 00:17:19,119 on Monday, or Tuesday, Wednesday, or Thursday. 427 00:17:19,119 --> 00:17:21,640 You should look at how much are you earning overall 428 00:17:21,640 --> 00:17:24,609 depending whether you earn sufficiently much, 429 00:17:24,609 --> 00:17:27,130 you're going to work fewer or more hours. 430 00:17:27,130 --> 00:17:30,520 Now, if you earn a lot, because your wages doubles or whatever, 431 00:17:30,520 --> 00:17:32,230 you might actually work few hours 432 00:17:32,230 --> 00:17:34,655 not because you reach a reference point on a given day. 433 00:17:34,655 --> 00:17:36,280 It's just because you got a lot richer, 434 00:17:36,280 --> 00:17:37,697 and then you decide it's not worth 435 00:17:37,697 --> 00:17:38,837 for you to work that much. 436 00:17:38,837 --> 00:17:40,420 So we're kind of trying to avoid that. 437 00:17:40,420 --> 00:17:43,450 We're trying to have only temporary changes, which 438 00:17:43,450 --> 00:17:47,173 is to say, for given wealth overall on any given day, 439 00:17:47,173 --> 00:17:49,090 it shouldn't matter whether you earn the money 440 00:17:49,090 --> 00:17:50,630 on Monday or on Tuesday. 441 00:17:50,630 --> 00:17:52,575 So essentially, if the wage happens 442 00:17:52,575 --> 00:17:53,950 to be really high on Tuesday, you 443 00:17:53,950 --> 00:17:56,260 should be working more, earning more, on Tuesday 444 00:17:56,260 --> 00:17:58,055 as opposed to on Monday. 445 00:17:58,055 --> 00:18:00,430 Now, what I was saying is, if you're reference dependent, 446 00:18:00,430 --> 00:18:01,990 you might actually care about this. 447 00:18:01,990 --> 00:18:04,240 You might care about on Monday you didn't reach your target. 448 00:18:04,240 --> 00:18:05,740 Therefore, you want to work more. 449 00:18:05,740 --> 00:18:08,290 On Tuesday, you reached your target very quickly. 450 00:18:08,290 --> 00:18:12,280 And you work less even though the wage is actually 451 00:18:12,280 --> 00:18:13,810 really high. 452 00:18:13,810 --> 00:18:15,190 OK. 453 00:18:15,190 --> 00:18:20,170 Now, strategy one might be optimal even 454 00:18:20,170 --> 00:18:23,587 in the neoclassical model if effort costs are convex. 455 00:18:23,587 --> 00:18:25,420 This is what I was saying is, if it's really 456 00:18:25,420 --> 00:18:30,580 sort of costly for you to work 9 hours, you might say, 457 00:18:30,580 --> 00:18:31,697 I always work 8 hours. 458 00:18:31,697 --> 00:18:34,030 I want to have a certain amount of money for my children 459 00:18:34,030 --> 00:18:35,673 and so on. 460 00:18:35,673 --> 00:18:37,840 So the extra hour, if that's really, really painful, 461 00:18:37,840 --> 00:18:39,945 you might not want to do that. 462 00:18:39,945 --> 00:18:41,320 We don't think that's necessarily 463 00:18:41,320 --> 00:18:44,913 the case in so many situations. 464 00:18:44,913 --> 00:18:46,330 The question is, can we really say 465 00:18:46,330 --> 00:18:48,413 that strategy three-- that's the strategy of doing 466 00:18:48,413 --> 00:18:50,650 the opposite, of working essentially a lot of hours 467 00:18:50,650 --> 00:18:53,560 when wages are low and few hours when wages are high. 468 00:18:53,560 --> 00:18:55,610 Can we really say it's a mistake? 469 00:18:55,610 --> 00:18:58,120 Well, it depends on kind of whether the effort costs are 470 00:18:58,120 --> 00:18:59,450 correlated with wages. 471 00:18:59,450 --> 00:19:01,120 So if cab drivers, for example, make 472 00:19:01,120 --> 00:19:04,630 really high wages on some days and low wages on other days, 473 00:19:04,630 --> 00:19:09,700 it could just be on low wage day it's much less 474 00:19:09,700 --> 00:19:11,390 effortful to drive around. 475 00:19:11,390 --> 00:19:13,210 So you would do more hours. 476 00:19:13,210 --> 00:19:15,398 It turns out, when you actually ask cab drivers, 477 00:19:15,398 --> 00:19:16,690 they actually prefer busy days. 478 00:19:16,690 --> 00:19:18,640 They actually prefer it when there are customers as 479 00:19:18,640 --> 00:19:20,710 opposed to just driving around and looking for people. 480 00:19:20,710 --> 00:19:22,335 So we don't think that's actually true. 481 00:19:22,335 --> 00:19:25,750 But in principle, you would have to sort think about that. 482 00:19:25,750 --> 00:19:29,230 Now, there's a long literature starting with Camerer et al. 483 00:19:29,230 --> 00:19:31,570 On cab drivers. 484 00:19:31,570 --> 00:19:33,490 A lot of that essentially is pre-Uber, 485 00:19:33,490 --> 00:19:37,180 like collecting trip shifts from cab drivers. 486 00:19:37,180 --> 00:19:38,830 Now, there's lots of like Uber data 487 00:19:38,830 --> 00:19:41,303 that's essentially much more powerful in some ways. 488 00:19:41,303 --> 00:19:43,720 So there will be probably more papers using Uber and Lyft, 489 00:19:43,720 --> 00:19:46,720 et cetera, data on that. 490 00:19:46,720 --> 00:19:48,370 But what Camerer et al. did at the time 491 00:19:48,370 --> 00:19:51,790 was they essentially looked at typical cab 492 00:19:51,790 --> 00:19:54,670 drivers that rent their cab for 12 hour periods for a fixed 493 00:19:54,670 --> 00:19:55,540 fee. 494 00:19:55,540 --> 00:19:57,820 And within this 12 hour window, a driver 495 00:19:57,820 --> 00:19:59,260 can choose their hours freely. 496 00:19:59,260 --> 00:20:01,030 So you just get your cab that's not yours. 497 00:20:01,030 --> 00:20:01,960 You rent it for the day. 498 00:20:01,960 --> 00:20:04,043 And then you can essentially choose how many hours 499 00:20:04,043 --> 00:20:04,960 you want to work. 500 00:20:04,960 --> 00:20:08,230 And their wages, how much money they make in any given hour, 501 00:20:08,230 --> 00:20:11,226 varies by a lot. 502 00:20:11,226 --> 00:20:14,200 The weather varies, the subway breakdowns, conferences 503 00:20:14,200 --> 00:20:15,170 and so on and so forth. 504 00:20:15,170 --> 00:20:17,128 There's lots of variation in how much money you 505 00:20:17,128 --> 00:20:19,540 make on a given day. 506 00:20:19,540 --> 00:20:22,120 So then they have trip sheets that look at how long 507 00:20:22,120 --> 00:20:24,460 cab drivers work and their overall earnings. 508 00:20:24,460 --> 00:20:27,760 And so they can essentially back out the wages from each day 509 00:20:27,760 --> 00:20:30,880 and then look at like how much do people work on days 510 00:20:30,880 --> 00:20:35,230 when wages are high versus days when wages are low. 511 00:20:35,230 --> 00:20:37,280 And then they essentially find the basic finding. 512 00:20:37,280 --> 00:20:39,363 And that's a finding that's sort of been contested 513 00:20:39,363 --> 00:20:42,070 in the literature many people have found or confirmed 514 00:20:42,070 --> 00:20:42,850 subsequently. 515 00:20:42,850 --> 00:20:44,933 And others have not, but I think eventually people 516 00:20:44,933 --> 00:20:46,780 have sort of settled on this. 517 00:20:46,780 --> 00:20:49,360 Hours are negatively correlated with wages. 518 00:20:49,360 --> 00:20:52,810 So when wages in particular are unexpectedly high, 519 00:20:52,810 --> 00:20:55,600 cab drivers tend to work fewer hours. 520 00:20:55,600 --> 00:20:58,750 And again, this is not for permanent changes, 521 00:20:58,750 --> 00:21:00,160 but for transitory changes. 522 00:21:00,160 --> 00:21:03,250 Surprisingly, on a given day people get more money, 523 00:21:03,250 --> 00:21:07,390 then drivers work few hours. 524 00:21:07,390 --> 00:21:10,360 And that's very hard to explain for the neoclassical model. 525 00:21:10,360 --> 00:21:12,758 Because, essentially, you shouldn't care about 526 00:21:12,758 --> 00:21:14,800 whether you make the money on Monday, on Tuesday. 527 00:21:14,800 --> 00:21:17,500 As I said, you should care about how much money you make overall 528 00:21:17,500 --> 00:21:20,140 and how many hours you work. 529 00:21:20,140 --> 00:21:21,940 And so it's very hard to explain this. 530 00:21:21,940 --> 00:21:26,620 And sort of the explanation that Camerer et al. and others were 531 00:21:26,620 --> 00:21:28,750 testing or arguing is essentially 532 00:21:28,750 --> 00:21:31,552 this has to do with reference dependence. 533 00:21:31,552 --> 00:21:34,010 And so what's being evaluated in a reference dependent way? 534 00:21:34,010 --> 00:21:36,040 Or how do we think about this? 535 00:21:36,040 --> 00:21:36,540 Yeah. 536 00:21:36,540 --> 00:21:37,880 AUDIENCE: I have a question. 537 00:21:37,880 --> 00:21:38,810 FRANK SCHILBACH: Yeah. 538 00:21:38,810 --> 00:21:41,420 AUDIENCE: How did they rule out the possibility 539 00:21:41,420 --> 00:21:44,990 that maybe there is reverse causality maybe 540 00:21:44,990 --> 00:21:47,630 on a day where none of the cab drivers 541 00:21:47,630 --> 00:21:49,850 want to work that much because it's supply and demand 542 00:21:49,850 --> 00:21:50,725 that they just go on? 543 00:21:56,550 --> 00:21:59,640 FRANK SCHILBACH: So that's to say effort costs are high. 544 00:21:59,640 --> 00:22:02,040 So usually, it's to do with other drivers. 545 00:22:02,040 --> 00:22:03,772 So let me actually get through-- so let 546 00:22:03,772 --> 00:22:04,980 me defer this for one second. 547 00:22:04,980 --> 00:22:06,750 I have a slide on confounds. 548 00:22:06,750 --> 00:22:08,790 And then we can see the rest of your question 549 00:22:08,790 --> 00:22:10,510 and then get back to that. 550 00:22:10,510 --> 00:22:12,220 But that's a good question. 551 00:22:12,220 --> 00:22:17,292 So what is being evaluated in reference-dependent way? 552 00:22:17,292 --> 00:22:18,750 What are people looking at in terms 553 00:22:18,750 --> 00:22:23,610 of where's the reference point in the evaluation here? 554 00:22:23,610 --> 00:22:24,870 Yes. 555 00:22:24,870 --> 00:22:28,320 AUDIENCE: I guess, if you're a cab driver, you kind of say, 556 00:22:28,320 --> 00:22:30,510 oh, I want to make this much money today. 557 00:22:30,510 --> 00:22:32,700 And then you just kind of work until you 558 00:22:32,700 --> 00:22:35,250 feel like you've made enough, and then you just stop. 559 00:22:35,250 --> 00:22:36,040 FRANK SCHILBACH: Right, exactly. 560 00:22:36,040 --> 00:22:37,822 You have to pay your fixed fee for the day 561 00:22:37,822 --> 00:22:39,030 or for the month or whatever. 562 00:22:39,030 --> 00:22:41,783 But there's an implicit fixed fee for the day. 563 00:22:41,783 --> 00:22:43,950 So you kind of want to make at least that much money 564 00:22:43,950 --> 00:22:45,180 to make not a loss. 565 00:22:45,180 --> 00:22:47,820 You probably have some positive target in some way in saying, 566 00:22:47,820 --> 00:22:52,740 like, I want to make pay back for my fee plus 567 00:22:52,740 --> 00:22:55,500 you want to make some money for the day and minus 568 00:22:55,500 --> 00:22:56,820 sort of expenses. 569 00:22:56,820 --> 00:22:59,970 And once you reach that target, you are in the gain domain. 570 00:22:59,970 --> 00:23:02,940 Below that, you are in the loss domain, right? 571 00:23:02,940 --> 00:23:04,740 And so the daily income essentially-- 572 00:23:04,740 --> 00:23:08,190 and that's essentially sort of money after paying back 573 00:23:08,190 --> 00:23:09,660 the fee, but you could also get-- 574 00:23:09,660 --> 00:23:12,658 it's essentially what's being evaluated 575 00:23:12,658 --> 00:23:13,950 in the reference-dependent way. 576 00:23:13,950 --> 00:23:16,320 What's the reference point is some daily target 577 00:23:16,320 --> 00:23:17,340 that you have. 578 00:23:17,340 --> 00:23:20,160 Often, it's expectation and so on and sort of, 579 00:23:20,160 --> 00:23:22,708 essentially, how much you think you will make. 580 00:23:22,708 --> 00:23:24,750 And then what's the feature of the value function 581 00:23:24,750 --> 00:23:25,680 that explains the phenomenon? 582 00:23:25,680 --> 00:23:26,722 Well, it's loss aversion. 583 00:23:26,722 --> 00:23:29,580 If you're falling short of the target, essentially 584 00:23:29,580 --> 00:23:31,710 your marginal utility-- 585 00:23:31,710 --> 00:23:34,080 when you drive another hour or another trip, 586 00:23:34,080 --> 00:23:37,500 the marginal utility that you get, since the value function 587 00:23:37,500 --> 00:23:39,360 is very steep below the target-- 588 00:23:39,360 --> 00:23:40,470 is very high. 589 00:23:40,470 --> 00:23:42,510 Once you reach the target, it's very flat. 590 00:23:42,510 --> 00:23:45,555 And then essentially you tend to stop. 591 00:23:45,555 --> 00:23:46,430 Does that make sense? 592 00:23:46,430 --> 00:23:46,980 AUDIENCE: Yeah. 593 00:23:46,980 --> 00:23:48,120 FRANK SCHILBACH: OK, great. 594 00:23:48,120 --> 00:23:52,170 So the main takeaway is, so if drivers often 595 00:23:52,170 --> 00:23:54,630 stop at their daily income target, 596 00:23:54,630 --> 00:23:57,780 driver with a higher wage reach their targets faster. 597 00:23:57,780 --> 00:23:58,920 And they work fewer hours. 598 00:23:58,920 --> 00:24:04,690 Again, that's variation within drivers across days. 599 00:24:04,690 --> 00:24:07,530 And sort of there's lots of subsequent work and debate 600 00:24:07,530 --> 00:24:08,670 regarding this finding. 601 00:24:08,670 --> 00:24:10,330 The debate is still ongoing. 602 00:24:10,330 --> 00:24:13,230 For example, one recent paper looks at tips 603 00:24:13,230 --> 00:24:15,460 that drivers get unexpectedly. 604 00:24:15,460 --> 00:24:18,480 So sometimes drivers get large tips, sometimes get small tips. 605 00:24:18,480 --> 00:24:21,447 It depends a lot when in the day they receive the tip, 606 00:24:21,447 --> 00:24:23,280 if they receive it really early versus late, 607 00:24:23,280 --> 00:24:24,810 if they sort of get to their target. 608 00:24:24,810 --> 00:24:26,185 And essentially, the target seems 609 00:24:26,185 --> 00:24:27,300 to be adjusting over time. 610 00:24:27,300 --> 00:24:29,550 But overall-- and this is sort of getting a little bit 611 00:24:29,550 --> 00:24:30,725 at your question-- 612 00:24:33,230 --> 00:24:35,800 we think it's not sort of aggregate supply. 613 00:24:35,800 --> 00:24:37,470 But the debate is still ongoing. 614 00:24:37,470 --> 00:24:40,260 But overall, we sort of think that lots of labor supply 615 00:24:40,260 --> 00:24:43,230 decisions, when people have daily decisions of how 616 00:24:43,230 --> 00:24:45,750 many hours to work and their wages vary, 617 00:24:45,750 --> 00:24:49,800 depend on reference points and might sort of potentially 618 00:24:49,800 --> 00:24:51,780 be at least suboptimal. 619 00:24:51,780 --> 00:24:55,320 Or put differently, people could work fewer hours 620 00:24:55,320 --> 00:24:59,230 and try to sort of adjust their overall amounts. 621 00:24:59,230 --> 00:25:00,230 For a while, I did this. 622 00:25:00,230 --> 00:25:02,160 You can ask your Uber and Lyft drivers 623 00:25:02,160 --> 00:25:04,230 what they're doing and so on and see 624 00:25:04,230 --> 00:25:07,148 whether they're a reference-dependent driver, 625 00:25:07,148 --> 00:25:08,940 sort of where they have reference-dependent 626 00:25:08,940 --> 00:25:10,050 preferences. 627 00:25:10,050 --> 00:25:12,480 Now, what are sort of potential alternative hypotheses? 628 00:25:12,480 --> 00:25:15,780 One question, one issue, could be liquidity constraints. 629 00:25:15,780 --> 00:25:18,330 This is, for example, if you just don't have enough cash. 630 00:25:18,330 --> 00:25:20,755 If you have to pay back your fee for the day 631 00:25:20,755 --> 00:25:23,130 or for the next day, you might want to not work only very 632 00:25:23,130 --> 00:25:25,110 few hours on a given day. 633 00:25:25,110 --> 00:25:27,390 It turns out that drivers who own their own medallion 634 00:25:27,390 --> 00:25:29,430 exhibit the same patterns. 635 00:25:29,430 --> 00:25:30,940 There could be things like fatigue. 636 00:25:30,940 --> 00:25:33,600 Let's just say it's really tedious to work on certain days 637 00:25:33,600 --> 00:25:34,860 when wages are high. 638 00:25:34,860 --> 00:25:37,620 We don't think that's going on in part because drivers 639 00:25:37,620 --> 00:25:40,170 themselves, they say, it's actually easier 640 00:25:40,170 --> 00:25:41,890 to drive with more passengers. 641 00:25:41,890 --> 00:25:43,920 Again, recent papers, in fact, can also 642 00:25:43,920 --> 00:25:45,100 control for this and so on. 643 00:25:45,100 --> 00:25:47,462 So we don't think it's actually fatigue. 644 00:25:47,462 --> 00:25:49,170 And this is, I think, what you're saying. 645 00:25:49,170 --> 00:25:51,510 The last one is unobserved shocks, so some 646 00:25:51,510 --> 00:25:55,490 shocks that affect all drivers' labor supply at the same time. 647 00:25:55,490 --> 00:25:58,770 Example, there are some days in which all drivers get the flu. 648 00:25:58,770 --> 00:25:59,820 Fewer drivers will work. 649 00:25:59,820 --> 00:26:02,760 And those who will work work fewer hours. 650 00:26:02,760 --> 00:26:09,330 And those who work get higher wages. 651 00:26:09,330 --> 00:26:12,630 That's a little bit trickier for them to rule out. 652 00:26:12,630 --> 00:26:15,450 In part, there's other papers, other studies afterwards, 653 00:26:15,450 --> 00:26:17,310 that sort of try to get at this. 654 00:26:17,310 --> 00:26:23,040 Usually, yeah, for this specific data, that's hard to do. 655 00:26:23,040 --> 00:26:27,000 I think for the other data where people have essentially not 656 00:26:27,000 --> 00:26:28,542 just daily-- 657 00:26:28,542 --> 00:26:30,000 so this is essentially trip sheets. 658 00:26:30,000 --> 00:26:33,150 So what they're using mostly is daily wages overall. 659 00:26:33,150 --> 00:26:34,410 They don't even have the wage. 660 00:26:34,410 --> 00:26:40,207 They only have the overall earnings and then the hours. 661 00:26:40,207 --> 00:26:41,790 And then they sort of compute the wage 662 00:26:41,790 --> 00:26:44,220 dividing the two, which causes some other trouble. 663 00:26:44,220 --> 00:26:46,020 But once you have Uber data, once you 664 00:26:46,020 --> 00:26:48,180 have specific trips and particular also tips 665 00:26:48,180 --> 00:26:51,870 and so on, you can look at, on a given day when 666 00:26:51,870 --> 00:26:56,630 I get a high tip versus a low tip, 667 00:26:56,630 --> 00:26:58,380 you can predict, essentially, how much I'm 668 00:26:58,380 --> 00:26:59,588 going to earn on a given day. 669 00:26:59,588 --> 00:27:01,590 So suppose you predict that I'm going 670 00:27:01,590 --> 00:27:04,530 to earn $100 in a given day. 671 00:27:04,530 --> 00:27:07,110 Now, I have, say, $50 or $60. 672 00:27:07,110 --> 00:27:09,810 Now, I get a large trip and a tip and so on that 673 00:27:09,810 --> 00:27:11,050 gets me over that threshold. 674 00:27:11,050 --> 00:27:12,630 You can look at whether I stop. 675 00:27:12,630 --> 00:27:14,250 You can look at the exact same thing. 676 00:27:14,250 --> 00:27:17,530 When I have only $20 and I get a large tip, do I stop and so on? 677 00:27:17,530 --> 00:27:19,810 So you can essentially control for all of that 678 00:27:19,810 --> 00:27:22,110 and then do within driver comparisons, 679 00:27:22,110 --> 00:27:25,530 like for trips that happen to be large or small that you 680 00:27:25,530 --> 00:27:26,910 happen to get in a given hour. 681 00:27:26,910 --> 00:27:29,902 And then you can sort of deal with overall market conditions. 682 00:27:29,902 --> 00:27:31,360 I think even better, in the future, 683 00:27:31,360 --> 00:27:32,735 there will be sort of experiments 684 00:27:32,735 --> 00:27:37,230 and so on where you can look at when Uber and Lyft try 685 00:27:37,230 --> 00:27:39,930 to incentivize their workers and so just, 686 00:27:39,930 --> 00:27:44,012 say, essentially, sometimes pay people more and less randomly, 687 00:27:44,012 --> 00:27:45,720 sort of explicitly randomly, because they 688 00:27:45,720 --> 00:27:48,330 want to kind of learn about how to best incentivize 689 00:27:48,330 --> 00:27:49,195 their drivers. 690 00:27:49,195 --> 00:27:50,820 And then you can control for everything 691 00:27:50,820 --> 00:27:53,940 because it's explicitly random whether a certain driver gets 692 00:27:53,940 --> 00:27:58,800 high versus low wages or sort of trip fares. 693 00:27:58,800 --> 00:28:00,380 Yeah. 694 00:28:00,380 --> 00:28:03,030 OK. 695 00:28:03,030 --> 00:28:09,650 Any questions on the labor supply? 696 00:28:09,650 --> 00:28:11,457 Yes. 697 00:28:11,457 --> 00:28:13,790 AUDIENCE: I'm a bit confused about the unobserved shock. 698 00:28:13,790 --> 00:28:16,450 Because if you get a really large tip, 699 00:28:16,450 --> 00:28:20,205 that doesn't necessarily predict that the rest of the day you'd 700 00:28:20,205 --> 00:28:22,085 have higher wages if you kept working. 701 00:28:22,085 --> 00:28:23,793 [INAUDIBLE] you get this really high tip, 702 00:28:23,793 --> 00:28:25,960 and then you would be like, oh, today's a lucky day. 703 00:28:25,960 --> 00:28:26,960 I can stop early. 704 00:28:26,960 --> 00:28:28,460 But if I have worked more this day, 705 00:28:28,460 --> 00:28:31,492 I wouldn't necessarily be making continuously more than normal. 706 00:28:31,492 --> 00:28:32,450 FRANK SCHILBACH: Right. 707 00:28:32,450 --> 00:28:35,790 So in the unobserved, in the large tip example, 708 00:28:35,790 --> 00:28:37,310 the assumption is exactly-- 709 00:28:37,310 --> 00:28:38,660 or what they show in the paper. 710 00:28:38,660 --> 00:28:40,760 This is subsequent work, not this specific work. 711 00:28:40,760 --> 00:28:42,460 What they exactly show in this type of paper, 712 00:28:42,460 --> 00:28:43,793 these are sort of random events. 713 00:28:43,793 --> 00:28:45,770 In a sense, it's precisely not predictive 714 00:28:45,770 --> 00:28:48,290 of your future earnings. 715 00:28:48,290 --> 00:28:49,310 It's random. 716 00:28:49,310 --> 00:28:51,990 Now, one interpretation that you have is to say, 717 00:28:51,990 --> 00:28:54,380 well, it could be that you kind of have some expectations 718 00:28:54,380 --> 00:28:55,605 about your future earnings. 719 00:28:55,605 --> 00:28:57,230 They could be particularly high or low. 720 00:28:57,230 --> 00:29:00,180 It's like, I got my lucky day and so on and so forth. 721 00:29:00,180 --> 00:29:01,310 That is hard to rule out. 722 00:29:01,310 --> 00:29:04,190 In some sense, if you had rational expectations, 723 00:29:04,190 --> 00:29:06,310 that's hard to explain for the neoclassical model. 724 00:29:06,310 --> 00:29:08,390 What's harder to rule out is to say, you know, 725 00:29:08,390 --> 00:29:10,717 I now think I got my lucky draw for the day. 726 00:29:10,717 --> 00:29:11,300 And that's it. 727 00:29:11,300 --> 00:29:14,030 And I'm not going to get any lucky draw again. 728 00:29:14,030 --> 00:29:15,620 Let's just call it a day. 729 00:29:15,620 --> 00:29:17,160 That is hard to rule out. 730 00:29:17,160 --> 00:29:21,390 But what is hard to explain for the neoclassical model-- 731 00:29:21,390 --> 00:29:23,210 I think we can sort of reject-- is to say, 732 00:29:23,210 --> 00:29:25,040 if you just think this is a shock, which 733 00:29:25,040 --> 00:29:27,350 really in reality it is and you just happened 734 00:29:27,350 --> 00:29:32,180 to get a bunch of money on a given day just randomly, 735 00:29:32,180 --> 00:29:34,100 then the reference-dependent model can sort of 736 00:29:34,100 --> 00:29:35,480 explain why you stop early. 737 00:29:35,480 --> 00:29:38,960 Because it just gets you over the reference point. 738 00:29:38,960 --> 00:29:41,210 The neoclassical model should just say, 739 00:29:41,210 --> 00:29:43,057 depends on essentially how many hours 740 00:29:43,057 --> 00:29:44,390 you want to work on a given day. 741 00:29:44,390 --> 00:29:46,010 It's nothing to do with a target. 742 00:29:46,010 --> 00:29:47,270 Because essentially, again, it doesn't 743 00:29:47,270 --> 00:29:48,740 matter whether you make money on Monday, 744 00:29:48,740 --> 00:29:49,670 or Tuesday, or Wednesday. 745 00:29:49,670 --> 00:29:51,920 You should just care about the overall amount of money 746 00:29:51,920 --> 00:29:53,720 that you make overall. 747 00:29:53,720 --> 00:29:56,090 But that's a good question. 748 00:29:56,090 --> 00:29:56,870 OK. 749 00:29:56,870 --> 00:30:00,870 So now, a second paper is on the housing market. 750 00:30:00,870 --> 00:30:05,470 So what is the natural reference point for housing market? 751 00:30:05,470 --> 00:30:07,340 Or how do we think about housing prices? 752 00:30:07,340 --> 00:30:08,630 Or how do you think about-- 753 00:30:08,630 --> 00:30:10,700 I guess a few of you will own a house. 754 00:30:10,700 --> 00:30:13,400 But if you owned a house, how would 755 00:30:13,400 --> 00:30:15,950 you think about selling a house? 756 00:30:15,950 --> 00:30:19,070 What is an actual reference point? 757 00:30:19,070 --> 00:30:19,940 Yes? 758 00:30:19,940 --> 00:30:22,438 AUDIENCE: Whatever it was before or how [? changes ?] 759 00:30:22,438 --> 00:30:23,353 [INAUDIBLE]. 760 00:30:23,353 --> 00:30:24,770 FRANK SCHILBACH: Yeah, so exactly. 761 00:30:24,770 --> 00:30:27,080 So the previous purchase price, it 762 00:30:27,080 --> 00:30:29,630 turns out it's a very, very salient thing for owners. 763 00:30:29,630 --> 00:30:32,180 People really know how much they paid for their house. 764 00:30:32,180 --> 00:30:34,040 It's a huge expense in their life. 765 00:30:34,040 --> 00:30:37,245 They really remember it was like 300,00, 500,000, 766 00:30:37,245 --> 00:30:38,120 a million, et cetera. 767 00:30:38,120 --> 00:30:39,890 They know exactly how much they paid. 768 00:30:39,890 --> 00:30:43,640 And when you even ask people, the majority of people 769 00:30:43,640 --> 00:30:46,370 know exactly how much they paid for their home. 770 00:30:46,370 --> 00:30:48,140 Now, one claim is that loss aversion 771 00:30:48,140 --> 00:30:51,660 makes people unwilling to sell their houses at a loss. 772 00:30:51,660 --> 00:30:54,620 And so what they would then do is they ask essentially 773 00:30:54,620 --> 00:30:58,920 for higher prices, if a loss, relative to their purchase 774 00:30:58,920 --> 00:30:59,420 price. 775 00:30:59,420 --> 00:31:03,920 And let me just show you exactly what I mean by that. 776 00:31:03,920 --> 00:31:07,250 Genesove and Mayer have Boston condominium data 777 00:31:07,250 --> 00:31:11,720 from 1992 in 1997. 778 00:31:11,720 --> 00:31:14,660 Luckily for them, there's lots of variation or fluctuations 779 00:31:14,660 --> 00:31:16,285 in the housing market during that time. 780 00:31:16,285 --> 00:31:17,785 So the housing market went up a lot, 781 00:31:17,785 --> 00:31:19,730 and then it went down a lot and went up a lot. 782 00:31:19,730 --> 00:31:23,420 Now, suppose you have two sellers, A and B, who both want 783 00:31:23,420 --> 00:31:26,660 to sell their home in 1994. 784 00:31:26,660 --> 00:31:29,540 Now, what we can do is we can look at these two people. 785 00:31:29,540 --> 00:31:31,580 Suppose they have very similar houses 786 00:31:31,580 --> 00:31:34,220 based on observable characteristics and location 787 00:31:34,220 --> 00:31:35,280 and so on and so forth. 788 00:31:35,280 --> 00:31:37,880 So once they have really comparable houses, 789 00:31:37,880 --> 00:31:44,720 we can all look at seller A, purchased their home really 790 00:31:44,720 --> 00:31:45,975 early on, in 1989. 791 00:31:45,975 --> 00:31:48,350 That person happens to be quite unlucky because they just 792 00:31:48,350 --> 00:31:51,650 bought the house really at the peak of, I guess, 793 00:31:51,650 --> 00:31:53,150 the housing boom at the time. 794 00:31:53,150 --> 00:31:58,130 Or seller number B, who purchased in 1991, that person 795 00:31:58,130 --> 00:31:59,180 was relatively lucky. 796 00:31:59,180 --> 00:32:01,820 They bought essentially at a time 797 00:32:01,820 --> 00:32:05,510 when the housing market was relatively low and appreciated 798 00:32:05,510 --> 00:32:06,600 quite a bit. 799 00:32:06,600 --> 00:32:10,940 So now, we can look at these two people and ask the question, 800 00:32:10,940 --> 00:32:14,510 is seller A or seller B more likely to sell their house? 801 00:32:14,510 --> 00:32:17,720 And the hypothesis is that seller A will sort of 802 00:32:17,720 --> 00:32:19,100 view this as a loss. 803 00:32:19,100 --> 00:32:22,190 This seller will essentially just say I'm losing money here. 804 00:32:22,190 --> 00:32:23,390 I don't want to sell. 805 00:32:23,390 --> 00:32:24,800 And that seller might essentially 806 00:32:24,800 --> 00:32:26,990 ask for a higher listing price and wants 807 00:32:26,990 --> 00:32:29,240 make more money for this house because they don't want 808 00:32:29,240 --> 00:32:32,300 to make a loss on that sale. 809 00:32:32,300 --> 00:32:34,910 Well, seller B says, I'm actually gaining money anyway. 810 00:32:34,910 --> 00:32:37,287 So let's just sort of post whatever you think 811 00:32:37,287 --> 00:32:38,870 is actually the expected market price. 812 00:32:38,870 --> 00:32:41,420 I might be happy to sell at a lower price compared 813 00:32:41,420 --> 00:32:43,040 to seller A. 814 00:32:43,040 --> 00:32:43,550 OK. 815 00:32:43,550 --> 00:32:46,008 So one thing we can look at essentially are listing prices. 816 00:32:46,008 --> 00:32:48,050 How much do people want for the houses? 817 00:32:48,050 --> 00:32:51,630 The second thing they can look at is actual sales prices. 818 00:32:51,630 --> 00:32:54,170 Are you now selling this at a higher or lower price? 819 00:32:54,170 --> 00:32:56,270 And number three, we can look at how long 820 00:32:56,270 --> 00:32:57,930 is the house on the market. 821 00:32:57,930 --> 00:33:00,510 How long does it actually take to sell it? 822 00:33:00,510 --> 00:33:02,060 That's a quite costly thing to do 823 00:33:02,060 --> 00:33:04,143 to have your house on the market for quite a while 824 00:33:04,143 --> 00:33:07,160 because, essentially, often people then don't already 825 00:33:07,160 --> 00:33:08,090 move somewhere else. 826 00:33:08,090 --> 00:33:09,500 Or they can't really live in the house 827 00:33:09,500 --> 00:33:11,500 because they have to sort of show it and make it 828 00:33:11,500 --> 00:33:13,170 available for showings and so on. 829 00:33:13,170 --> 00:33:14,420 So it's a costly thing to do. 830 00:33:14,420 --> 00:33:16,670 You really don't want to have your house on the market 831 00:33:16,670 --> 00:33:18,860 for several months. 832 00:33:18,860 --> 00:33:20,480 But is sort of the broad idea clear 833 00:33:20,480 --> 00:33:21,605 of what we're trying to do? 834 00:33:25,440 --> 00:33:26,190 OK. 835 00:33:26,190 --> 00:33:29,833 So what predictions do we want to test? 836 00:33:29,833 --> 00:33:31,500 We want to test whether house owners are 837 00:33:31,500 --> 00:33:34,290 reluctant to sell their house when the current market price 838 00:33:34,290 --> 00:33:36,970 is below the purchase price. 839 00:33:36,970 --> 00:33:39,910 So the ideal specification is essentially the following. 840 00:33:39,910 --> 00:33:42,540 We look at the list price on the left-hand side. 841 00:33:42,540 --> 00:33:45,300 And then we are going to run a regression that looks at some 842 00:33:45,300 --> 00:33:48,270 constant-- that's just kind of time trends, et cetera-- 843 00:33:48,270 --> 00:33:51,270 plus a beta, which is the coefficient of interest. 844 00:33:51,270 --> 00:33:54,010 Or one coefficient of interest is of the actual market price. 845 00:33:54,010 --> 00:33:55,680 How much is the thing worth? 846 00:33:55,680 --> 00:33:59,610 And then delta on the loss is how much do you lose relative 847 00:33:59,610 --> 00:34:02,520 to your purchase price. 848 00:34:02,520 --> 00:34:05,087 Now, if people were not reference-dependent, 849 00:34:05,087 --> 00:34:05,920 what should we find? 850 00:34:05,920 --> 00:34:09,090 Or what would be the predictions? 851 00:34:09,090 --> 00:34:12,280 The neoclassical model, what should we find here? 852 00:34:12,280 --> 00:34:12,780 Yes. 853 00:34:12,780 --> 00:34:15,195 AUDIENCE: We should find that delta 0 [INAUDIBLE]?? 854 00:34:21,248 --> 00:34:22,290 FRANK SCHILBACH: Exactly. 855 00:34:22,290 --> 00:34:23,340 Delta should not matter. 856 00:34:23,340 --> 00:34:26,880 It shouldn't matter how much you lost or gained in that house. 857 00:34:26,880 --> 00:34:29,219 What should matter is what is the actual market value. 858 00:34:29,219 --> 00:34:32,250 You should essentially try to be willing to sell it not. 859 00:34:32,250 --> 00:34:34,949 Beta could be-- it doesn't have to be 1. 860 00:34:34,949 --> 00:34:37,813 It could be everybody pays above the actual market. 861 00:34:37,813 --> 00:34:39,480 There's some housing bubble or whatever. 862 00:34:39,480 --> 00:34:42,853 Beta could be 1.1 or whatever you might be. 863 00:34:42,853 --> 00:34:45,270 That depends on, essentially, sort of aggregate conditions 864 00:34:45,270 --> 00:34:46,170 and so on. 865 00:34:46,170 --> 00:34:48,300 But delta really should not matter. 866 00:34:48,300 --> 00:34:49,800 When I'm trying to sell you a house, 867 00:34:49,800 --> 00:34:52,350 you should ask, what's the actual market value? 868 00:34:52,350 --> 00:34:54,210 And I should, essentially, then based 869 00:34:54,210 --> 00:34:58,740 on that, put it on a market on that listing price. 870 00:34:58,740 --> 00:35:02,160 But what might be the case is that the loss actually matters. 871 00:35:02,160 --> 00:35:05,670 Now, one problem here is that the actual market value is not 872 00:35:05,670 --> 00:35:06,963 observable, right? 873 00:35:06,963 --> 00:35:08,880 So I don't actually know what the market value 874 00:35:08,880 --> 00:35:10,440 is because that's endogenous. 875 00:35:10,440 --> 00:35:12,410 That's part of the transaction. 876 00:35:12,410 --> 00:35:13,500 So what can I do instead? 877 00:35:13,500 --> 00:35:14,340 Or how do I do this? 878 00:35:21,620 --> 00:35:22,160 Yes. 879 00:35:22,160 --> 00:35:25,920 AUDIENCE: By asking people, would you take this trade? 880 00:35:25,920 --> 00:35:27,130 And then see what they say. 881 00:35:27,130 --> 00:35:27,890 [INAUDIBLE] 882 00:35:27,890 --> 00:35:28,190 FRANK SCHILBACH: Right. 883 00:35:28,190 --> 00:35:30,830 So you can look at actually the market outcome overall. 884 00:35:30,830 --> 00:35:32,690 You can look at who buys it and what's 885 00:35:32,690 --> 00:35:34,460 the actual purchase price. 886 00:35:34,460 --> 00:35:37,130 Now, that might also be endogenous to the listing 887 00:35:37,130 --> 00:35:37,760 price, right? 888 00:35:37,760 --> 00:35:40,093 So if you think you know that people who are loss averse 889 00:35:40,093 --> 00:35:43,280 are listing their houses too high relatively compared 890 00:35:43,280 --> 00:35:45,590 to what the market value actually is, 891 00:35:45,590 --> 00:35:47,910 it might actually be sold at a higher price. 892 00:35:47,910 --> 00:35:50,330 So that's hard to interpret. 893 00:35:50,330 --> 00:35:53,870 It could just be that, if you list it at a very high price 894 00:35:53,870 --> 00:35:56,870 and wait for a long time, you also sell it at a higher price. 895 00:35:56,870 --> 00:35:59,245 But it doesn't mean that that's actually worth that much. 896 00:35:59,245 --> 00:36:02,870 It just means that you happen to find a buyer who happens 897 00:36:02,870 --> 00:36:04,400 to be willing to pay a lot. 898 00:36:04,400 --> 00:36:07,248 And that's more likely when you wait for a long time, which 899 00:36:07,248 --> 00:36:09,290 is not necessarily optimal, because it's actually 900 00:36:09,290 --> 00:36:11,460 quite costly to do that. 901 00:36:11,460 --> 00:36:13,923 But you're saying something else which is asking them 902 00:36:13,923 --> 00:36:14,840 about what they think. 903 00:36:14,840 --> 00:36:16,850 But what are the characteristics that we could look at? 904 00:36:16,850 --> 00:36:18,380 Or what data could we look at? 905 00:36:22,740 --> 00:36:26,340 If you had Zillow data or data on essentially a bunch 906 00:36:26,340 --> 00:36:28,400 of these apps where you can look at houses, 907 00:36:28,400 --> 00:36:29,400 what data could you get? 908 00:36:29,400 --> 00:36:29,970 Yes. 909 00:36:29,970 --> 00:36:31,450 AUDIENCE: You'd look at the houses 910 00:36:31,450 --> 00:36:33,938 in the neighborhood, similar houses that sold recently. 911 00:36:33,938 --> 00:36:34,980 FRANK SCHILBACH: Exactly. 912 00:36:34,980 --> 00:36:36,485 What Redfin and Zillow, et cetera, 913 00:36:36,485 --> 00:36:37,860 do these days is essentially they 914 00:36:37,860 --> 00:36:41,610 have these algorithms that try to predict the actual market 915 00:36:41,610 --> 00:36:42,660 sales price. 916 00:36:42,660 --> 00:36:44,190 And what they tend to do essentially 917 00:36:44,190 --> 00:36:46,530 is look at, exactly as you say, surrounding 918 00:36:46,530 --> 00:36:50,747 houses that are similar in some characteristics. 919 00:36:50,747 --> 00:36:52,080 They look at the square footage. 920 00:36:52,080 --> 00:36:55,980 They look at the number of bathrooms and rooms in general. 921 00:36:55,980 --> 00:36:58,960 They look at sort of location and so on and so forth. 922 00:36:58,960 --> 00:37:03,330 And then you can predict how much-- 923 00:37:03,330 --> 00:37:05,760 and sort of they look at all the time trends and so on. 924 00:37:05,760 --> 00:37:07,350 How much is the actual market value? 925 00:37:07,350 --> 00:37:10,110 But essentially, fundamentally, it's a prediction exercise. 926 00:37:10,110 --> 00:37:13,330 You can try to predict what the actual value is. 927 00:37:13,330 --> 00:37:15,600 And that's exactly what Genesove and Mayer do. 928 00:37:15,600 --> 00:37:17,730 They do some more fancy things that 929 00:37:17,730 --> 00:37:21,850 try to get it other unobservable characteristics and so on. 930 00:37:21,850 --> 00:37:24,330 But the essence of this is exactly the prediction exercise 931 00:37:24,330 --> 00:37:27,527 where they say, let's just look at the characteristics 932 00:37:27,527 --> 00:37:28,110 of this house. 933 00:37:28,110 --> 00:37:31,290 Let's try to predict what the market value is and then 934 00:37:31,290 --> 00:37:32,948 look at the loss, which is essentially 935 00:37:32,948 --> 00:37:34,740 the difference between the previous selling 936 00:37:34,740 --> 00:37:36,810 price and the expected selling price 937 00:37:36,810 --> 00:37:39,690 truncated from 0 because, otherwise, it's a gain. 938 00:37:39,690 --> 00:37:41,670 And then we can look at does it really 939 00:37:41,670 --> 00:37:44,070 seem that, when people are in the loss domain, 940 00:37:44,070 --> 00:37:47,910 when their loss is positive, are they now selling their house 941 00:37:47,910 --> 00:37:51,320 or trying to sell their house at a higher price? 942 00:37:51,320 --> 00:37:52,170 Yes? 943 00:37:52,170 --> 00:37:53,920 AUDIENCE: How do you account for something 944 00:37:53,920 --> 00:37:56,250 like recent renovations since the last listing 945 00:37:56,250 --> 00:37:58,980 and relative to any other similar units 946 00:37:58,980 --> 00:38:03,422 or houses or [INAUDIBLE] [? nearby ?] [INAUDIBLE]?? 947 00:38:03,422 --> 00:38:04,380 FRANK SCHILBACH: Right. 948 00:38:04,380 --> 00:38:06,242 So that's tricky to do. 949 00:38:06,242 --> 00:38:08,200 And I don't think they have this in their data. 950 00:38:08,200 --> 00:38:09,540 So what you'd have to assume here, 951 00:38:09,540 --> 00:38:10,950 and that's perhaps reasonable, is 952 00:38:10,950 --> 00:38:13,470 to say that when you look at sort of this picture 953 00:38:13,470 --> 00:38:16,200 that seller A and seller B did not 954 00:38:16,200 --> 00:38:18,450 do differential renovation depending 955 00:38:18,450 --> 00:38:20,680 on when they bought the house. 956 00:38:20,680 --> 00:38:21,210 Right? 957 00:38:21,210 --> 00:38:24,210 So if you said, it's fine if people have done renovations. 958 00:38:24,210 --> 00:38:25,920 For example, this is what I was saying 959 00:38:25,920 --> 00:38:28,260 about the beta on the actual market value. 960 00:38:28,260 --> 00:38:30,900 If you systematically underestimate or overestimate 961 00:38:30,900 --> 00:38:33,720 how much people renovate and so on, or maybe the housing market 962 00:38:33,720 --> 00:38:37,140 is really hot or whatever, that's OK. 963 00:38:37,140 --> 00:38:42,580 The main issue is that can't be correlated with the loss here. 964 00:38:42,580 --> 00:38:45,600 So if it's the case that people who lost a bunch of money 965 00:38:45,600 --> 00:38:48,810 in terms of their housing prices sort of tanked, 966 00:38:48,810 --> 00:38:50,460 if those people have done more or less 967 00:38:50,460 --> 00:38:55,620 renovations, then you're in trouble with your estimates. 968 00:38:55,620 --> 00:38:56,370 Yeah. 969 00:38:56,370 --> 00:38:58,775 AUDIENCE: Is the expected selling price the estimation 970 00:38:58,775 --> 00:39:00,668 of actual [? work ?] value? 971 00:39:00,668 --> 00:39:01,710 FRANK SCHILBACH: Correct. 972 00:39:01,710 --> 00:39:02,280 AUDIENCE: OK. 973 00:39:02,280 --> 00:39:03,155 FRANK SCHILBACH: Yes. 974 00:39:05,160 --> 00:39:07,170 So now, what Genesove and Mayer find 975 00:39:07,170 --> 00:39:08,810 is-- and there's more detail to that. 976 00:39:08,810 --> 00:39:10,393 But essentially, the main finding is-- 977 00:39:10,393 --> 00:39:12,870 and that's a fairly solid one, there's a bunch of different 978 00:39:12,870 --> 00:39:14,610 specifications-- 979 00:39:14,610 --> 00:39:17,228 a 10% increase in a prospective loss. 980 00:39:17,228 --> 00:39:19,020 So if this loss coefficient, the difference 981 00:39:19,020 --> 00:39:23,670 between the expected selling price and the purchase price, 982 00:39:23,670 --> 00:39:26,730 if that's 10% higher, then essentially the list price 983 00:39:26,730 --> 00:39:31,770 is 2.5% to 3.5% higher. 984 00:39:31,770 --> 00:39:34,410 So people list the price, the house, at a higher price. 985 00:39:34,410 --> 00:39:35,880 If the house is at a loss compared 986 00:39:35,880 --> 00:39:38,220 to a similar house who's not at a loss 987 00:39:38,220 --> 00:39:41,400 or who's in the gain domain, these effects 988 00:39:41,400 --> 00:39:45,120 then translate into higher sales prices and a lower hazard 989 00:39:45,120 --> 00:39:46,140 rate of sale. 990 00:39:46,140 --> 00:39:49,480 That's to say people actually sell it at a higher price. 991 00:39:49,480 --> 00:39:52,650 So in fact, it's hard to say here what's optimal versus not. 992 00:39:52,650 --> 00:39:55,320 It could be that, overall, people are like, 993 00:39:55,320 --> 00:39:56,940 it's actually a good thing to do. 994 00:39:56,940 --> 00:39:59,370 That depends a lot on, essentially, your opportunity 995 00:39:59,370 --> 00:40:03,840 costs of money in terms how costly is it 996 00:40:03,840 --> 00:40:06,580 for you to keep the house on the market for a while. 997 00:40:06,580 --> 00:40:10,190 But essentially, people have a lower hazard right of sale. 998 00:40:10,190 --> 00:40:13,050 That's to say it just takes them a lot longer to sell the house. 999 00:40:13,050 --> 00:40:15,930 That tends to be very costly to do. 1000 00:40:15,930 --> 00:40:19,163 But if you just otherwise would have your money in the bank 1001 00:40:19,163 --> 00:40:20,580 and you have another place to stay 1002 00:40:20,580 --> 00:40:24,820 and you don't really care, maybe then that's fine. 1003 00:40:24,820 --> 00:40:28,620 But we surely have real effects in terms of people 1004 00:40:28,620 --> 00:40:30,780 list their houses at higher prices. 1005 00:40:30,780 --> 00:40:33,030 People sell them at somewhat higher prices. 1006 00:40:33,030 --> 00:40:36,720 And people also keep them longer on the market. 1007 00:40:36,720 --> 00:40:37,410 OK. 1008 00:40:37,410 --> 00:40:38,280 Yeah. 1009 00:40:38,280 --> 00:40:39,738 AUDIENCE: Is this the same analysis 1010 00:40:39,738 --> 00:40:42,165 if it's gains on the value of the house? 1011 00:40:44,748 --> 00:40:46,790 FRANK SCHILBACH: So essentially, what we're doing 1012 00:40:46,790 --> 00:40:51,360 is we implicitly comparing losses versus gains, right? 1013 00:40:51,360 --> 00:40:57,470 So the gains here would be in the actual market value 1014 00:40:57,470 --> 00:40:58,900 already as it is. 1015 00:41:02,358 --> 00:41:04,400 But essentially, what you're implicitly doing is, 1016 00:41:04,400 --> 00:41:06,980 when comparing implicitly, this is what I was saying here. 1017 00:41:06,980 --> 00:41:10,010 When you look at this picture, implicitly what we're doing 1018 00:41:10,010 --> 00:41:13,700 is we look at people who are losing money compared to people 1019 00:41:13,700 --> 00:41:15,080 who are gaining money. 1020 00:41:15,080 --> 00:41:16,715 And explicitly or implicitly, we're 1021 00:41:16,715 --> 00:41:18,350 asking, is the increase and the gain 1022 00:41:18,350 --> 00:41:20,264 sort of predictive of that-- 1023 00:41:20,264 --> 00:41:22,610 sorry, the increase in the losses predictive 1024 00:41:22,610 --> 00:41:25,110 of your listing price? 1025 00:41:25,110 --> 00:41:27,890 Now, it's hard to do this at the same time for gains 1026 00:41:27,890 --> 00:41:30,770 because, essentially, an increase in the market price 1027 00:41:30,770 --> 00:41:34,550 overall that's sort of collinear. 1028 00:41:34,550 --> 00:41:37,120 In [INAUDIBLE],, essentially that's hard to separate. 1029 00:41:37,120 --> 00:41:38,763 You could do the same analysis, and you 1030 00:41:38,763 --> 00:41:40,430 wouldn't find that for the gains in part 1031 00:41:40,430 --> 00:41:42,388 because essentially explicitly what we're doing 1032 00:41:42,388 --> 00:41:46,080 is incurring losses to gains. 1033 00:41:46,080 --> 00:41:46,580 OK. 1034 00:41:48,960 --> 00:41:49,460 OK. 1035 00:41:49,460 --> 00:41:51,210 So then there is another piece of evidence 1036 00:41:51,210 --> 00:41:54,230 that sort of tells us perhaps this is not optimal. 1037 00:41:54,230 --> 00:41:57,057 If you look at people who are owner-occupied compared 1038 00:41:57,057 --> 00:41:58,640 to investors-- so there are people who 1039 00:41:58,640 --> 00:41:59,840 essentially invest in houses. 1040 00:41:59,840 --> 00:42:00,715 And they sell houses. 1041 00:42:00,715 --> 00:42:02,930 And they sell lots of houses over time. 1042 00:42:02,930 --> 00:42:06,410 Those people have much lower endowment effect, 1043 00:42:06,410 --> 00:42:07,730 if you want, for houses. 1044 00:42:07,730 --> 00:42:10,580 So they exhibit this behavior a lot less. 1045 00:42:10,580 --> 00:42:12,290 But people who live in that house, who 1046 00:42:12,290 --> 00:42:13,940 bought that house, for them it's mostly 1047 00:42:13,940 --> 00:42:15,107 the only house they live in. 1048 00:42:15,107 --> 00:42:16,760 It's the main purchase that they have. 1049 00:42:16,760 --> 00:42:19,400 For them, it's essentially their house for which 1050 00:42:19,400 --> 00:42:23,420 they don't want to make losses. 1051 00:42:23,420 --> 00:42:25,340 For them, these effects are twice as large 1052 00:42:25,340 --> 00:42:27,410 compared to the investors. 1053 00:42:27,410 --> 00:42:30,200 And that's perhaps some evidence that this is not 1054 00:42:30,200 --> 00:42:32,240 optimal behavior in a sense of sort 1055 00:42:32,240 --> 00:42:33,830 of the professional investors. 1056 00:42:33,830 --> 00:42:36,930 They presumably know pretty well how to price their houses. 1057 00:42:36,930 --> 00:42:39,560 So if they do this behavior less, 1058 00:42:39,560 --> 00:42:41,840 presumably that's a sign that there's 1059 00:42:41,840 --> 00:42:46,160 some form of a mistake here going on. 1060 00:42:46,160 --> 00:42:49,520 Second, there's some evidence-- and John List has some work 1061 00:42:49,520 --> 00:42:50,780 on this overall-- 1062 00:42:50,780 --> 00:42:53,360 to say that experience can mitigate 1063 00:42:53,360 --> 00:42:54,980 reference dependent effects. 1064 00:42:54,980 --> 00:42:57,200 Essentially, if you do a lot of trading, 1065 00:42:57,200 --> 00:43:00,030 if you sell a lot of houses and so on, 1066 00:43:00,030 --> 00:43:03,230 then you might still feel losses and gains, 1067 00:43:03,230 --> 00:43:05,750 but you might sort of have a lot more experience with this. 1068 00:43:05,750 --> 00:43:07,940 You kind of know that this is happening sometimes. 1069 00:43:07,940 --> 00:43:10,250 And you might be less prone to these types of effects 1070 00:43:10,250 --> 00:43:13,100 because you kind of know that you shouldn't be doing this. 1071 00:43:13,100 --> 00:43:17,150 You shouldn't sort of have your feelings of losses and gains 1072 00:43:17,150 --> 00:43:18,920 get in the way of making profits. 1073 00:43:18,920 --> 00:43:20,337 So there are some people who would 1074 00:43:20,337 --> 00:43:22,760 argue that this is very much consistent with markets 1075 00:43:22,760 --> 00:43:24,430 over time or exposures to markets 1076 00:43:24,430 --> 00:43:25,430 and several predictions. 1077 00:43:25,430 --> 00:43:28,730 Experience makes some of these effects go away. 1078 00:43:28,730 --> 00:43:30,830 And John List has some separate evidence 1079 00:43:30,830 --> 00:43:33,530 on this on traders of cards and so on. 1080 00:43:37,130 --> 00:43:37,703 OK. 1081 00:43:37,703 --> 00:43:39,620 So now, next, we're going to talk a little bit 1082 00:43:39,620 --> 00:43:42,310 about finance and stocks. 1083 00:43:42,310 --> 00:43:44,540 So interestingly-- yeah. 1084 00:43:44,540 --> 00:43:46,495 AUDIENCE: Sorry, on the previous study, 1085 00:43:46,495 --> 00:43:48,746 why [? is it ?] said reference-dependent and not 1086 00:43:48,746 --> 00:43:54,390 some informational effect, that I'm a home owner 1087 00:43:54,390 --> 00:43:57,100 and I think that my house is worth this amount. 1088 00:43:57,100 --> 00:43:59,210 And I just [INAUDIBLE] [? anchored ?] 1089 00:43:59,210 --> 00:44:01,252 to believing that that's the amount. 1090 00:44:01,252 --> 00:44:02,210 FRANK SCHILBACH: Right. 1091 00:44:02,210 --> 00:44:07,860 So one thing you could say is that-- 1092 00:44:07,860 --> 00:44:09,890 so what you always have to make the argument 1093 00:44:09,890 --> 00:44:12,870 is people who are at losses compared to who are at gains. 1094 00:44:12,870 --> 00:44:15,620 So you look at our investor A and B. 1095 00:44:15,620 --> 00:44:20,540 They might have additional information on how much 1096 00:44:20,540 --> 00:44:21,500 the house is worth. 1097 00:44:21,500 --> 00:44:24,350 So it could be, for example, that seller A 1098 00:44:24,350 --> 00:44:25,860 knows a lot about this house. 1099 00:44:25,860 --> 00:44:29,510 It's very beautiful and so much light and this and that. 1100 00:44:29,510 --> 00:44:31,623 And, therefore, they paid a lot. 1101 00:44:31,623 --> 00:44:33,290 Therefore, they have private information 1102 00:44:33,290 --> 00:44:34,560 that it's worth a lot. 1103 00:44:34,560 --> 00:44:37,340 Therefore, they list it at a really high price. 1104 00:44:37,340 --> 00:44:40,280 So there are some specification here that-- look at this. 1105 00:44:40,280 --> 00:44:43,520 What you see is this is columns two, four, and six, 1106 00:44:43,520 --> 00:44:46,760 which is the residual from the last sales price. 1107 00:44:46,760 --> 00:44:47,720 What is that? 1108 00:44:47,720 --> 00:44:50,540 That's essentially the difference between at the time 1109 00:44:50,540 --> 00:44:52,758 when previously the house was sold, 1110 00:44:52,758 --> 00:44:54,800 what was the prediction of the market price then, 1111 00:44:54,800 --> 00:44:56,040 and how much was it sold. 1112 00:44:56,040 --> 00:45:01,580 So it's kind of like, how much did you overpay, if you want, 1113 00:45:01,580 --> 00:45:03,830 relative to what we expected at the time? 1114 00:45:03,830 --> 00:45:06,230 Presumably, that's reflective and, again, 1115 00:45:06,230 --> 00:45:07,950 using the same prediction method. 1116 00:45:07,950 --> 00:45:08,900 So if you thought, you know, it's 1117 00:45:08,900 --> 00:45:11,400 really beautiful and lots of windows and this and that, lots 1118 00:45:11,400 --> 00:45:14,300 of light, and really quiet and so on, 1119 00:45:14,300 --> 00:45:16,270 if you overpaid at the time, that 1120 00:45:16,270 --> 00:45:18,500 should then sort of be predictive of the listing 1121 00:45:18,500 --> 00:45:19,160 price. 1122 00:45:19,160 --> 00:45:22,280 And sort of controlling for that then should make this go away. 1123 00:45:22,280 --> 00:45:25,280 What you see, however, there's some of that perhaps going on. 1124 00:45:25,280 --> 00:45:27,650 If you compare, for example, columns one and two, 1125 00:45:27,650 --> 00:45:29,690 you see that the effect goes down a little bit. 1126 00:45:29,690 --> 00:45:31,190 But it's still there quite a bit. 1127 00:45:31,190 --> 00:45:34,280 This is why I was saying 25% to 35%. 1128 00:45:34,280 --> 00:45:35,900 That is exactly right. 1129 00:45:35,900 --> 00:45:36,800 That's a big concern. 1130 00:45:36,800 --> 00:45:38,180 And there's a bunch of sort of robustness, 1131 00:45:38,180 --> 00:45:40,070 et cetera, checks in this specific study. 1132 00:45:40,070 --> 00:45:41,150 But that's exactly right. 1133 00:45:41,150 --> 00:45:43,220 There could be sort of unobservable information 1134 00:45:43,220 --> 00:45:46,670 that the owner might have about the house that is not 1135 00:45:46,670 --> 00:45:48,540 in Zillow or in any sort of Redfin, 1136 00:45:48,540 --> 00:45:51,410 et cetera, predictions that's available for the public. 1137 00:45:51,410 --> 00:45:54,140 That's a great question, but I think it's, to the extent 1138 00:45:54,140 --> 00:45:56,810 that that takes care of it, sort of the authors 1139 00:45:56,810 --> 00:45:58,730 have thought about that. 1140 00:45:58,730 --> 00:45:59,930 Yes. 1141 00:45:59,930 --> 00:46:01,670 AUDIENCE: On the following slide, 1142 00:46:01,670 --> 00:46:05,070 when you talk about the differences, 1143 00:46:05,070 --> 00:46:07,160 how do you control for the selection bias 1144 00:46:07,160 --> 00:46:11,930 about the people that may be the ones repeatedly selling houses 1145 00:46:11,930 --> 00:46:14,090 exhibit this less and, therefore, stay 1146 00:46:14,090 --> 00:46:17,460 in the market versus a change in those individuals' behavior? 1147 00:46:20,152 --> 00:46:21,110 FRANK SCHILBACH: Right. 1148 00:46:21,110 --> 00:46:22,110 That's a great question. 1149 00:46:22,110 --> 00:46:24,740 So the question you're asking is essentially to say-- 1150 00:46:24,740 --> 00:46:28,790 and it's, in fact, a great sort of segue 1151 00:46:28,790 --> 00:46:30,830 into behavioral finance, which is to say, 1152 00:46:30,830 --> 00:46:33,350 suppose there are some people who are really sophisticated. 1153 00:46:33,350 --> 00:46:36,200 They don't have certain behavioral biases. 1154 00:46:36,200 --> 00:46:37,790 Maybe they're not loss averse. 1155 00:46:37,790 --> 00:46:39,830 That makes you a better investor, say. 1156 00:46:39,830 --> 00:46:43,490 And, therefore, you stay in the market overall. 1157 00:46:43,490 --> 00:46:45,770 I think, from this observation that I have here, 1158 00:46:45,770 --> 00:46:53,810 I cannot tell you is it experience or is it selection. 1159 00:46:53,810 --> 00:46:59,060 So the question kind of is, when people are investors, 1160 00:46:59,060 --> 00:47:01,160 do the effects of reference-dependence of gains 1161 00:47:01,160 --> 00:47:03,170 and losses go away over time? 1162 00:47:03,170 --> 00:47:05,510 Essentially, maybe the first, second, third time 1163 00:47:05,510 --> 00:47:08,690 they feel really a loss in terms of making a bad investment. 1164 00:47:08,690 --> 00:47:11,900 But in house number 20, I'm just like, that's as usual. 1165 00:47:11,900 --> 00:47:13,910 And I shouldn't sort of really care very much. 1166 00:47:13,910 --> 00:47:15,440 Is it that this goes away? 1167 00:47:15,440 --> 00:47:17,840 Or is it that the people who are particularly 1168 00:47:17,840 --> 00:47:19,940 loss averse and sort of essentially 1169 00:47:19,940 --> 00:47:21,710 engage in this type of behavior in terms 1170 00:47:21,710 --> 00:47:26,510 of listing too high of a price for losses, 1171 00:47:26,510 --> 00:47:29,090 these are sort of bad investor in the housing markets? 1172 00:47:29,090 --> 00:47:32,070 And they sort of are essentially driven out of the market. 1173 00:47:32,070 --> 00:47:34,070 So that specific setting I don't think we 1174 00:47:34,070 --> 00:47:37,910 can necessarily account for that. 1175 00:47:37,910 --> 00:47:41,120 I think in the studies by John List, 1176 00:47:41,120 --> 00:47:44,900 it's very much people argue it's about experience. 1177 00:47:44,900 --> 00:47:47,060 But again, there also some part could also 1178 00:47:47,060 --> 00:47:51,200 be selection I think. 1179 00:47:51,200 --> 00:47:56,520 So I think, in some sense, either way 1180 00:47:56,520 --> 00:47:59,370 I think the evidence that the investors are doing 1181 00:47:59,370 --> 00:48:01,440 this behavior less sort of tells us something 1182 00:48:01,440 --> 00:48:04,920 about this is probably not at least financially 1183 00:48:04,920 --> 00:48:08,460 optimal for you to engage in this type of behavior. 1184 00:48:08,460 --> 00:48:09,840 It might be privately optimal. 1185 00:48:09,840 --> 00:48:11,215 In some sense, if you really feel 1186 00:48:11,215 --> 00:48:14,100 at selling your house at a loss, you 1187 00:48:14,100 --> 00:48:16,710 should probably list it at a higher price 1188 00:48:16,710 --> 00:48:19,050 because that sort of limits your losses. 1189 00:48:19,050 --> 00:48:21,120 That's just what a utility function looks like. 1190 00:48:21,120 --> 00:48:24,330 It's not necessarily suboptimal in the sense 1191 00:48:24,330 --> 00:48:27,000 of how you feel afterwards. 1192 00:48:27,000 --> 00:48:29,760 It might be suboptimal in terms of how much money you make 1193 00:48:29,760 --> 00:48:32,610 or how much money you have eventually on how much 1194 00:48:32,610 --> 00:48:34,950 you pay for keeping your house on the market 1195 00:48:34,950 --> 00:48:38,380 and so on for an extended period of time. 1196 00:48:38,380 --> 00:48:39,000 OK. 1197 00:48:39,000 --> 00:48:41,250 So did that answer your question? 1198 00:48:41,250 --> 00:48:42,690 Yeah, OK. 1199 00:48:42,690 --> 00:48:44,760 So behavioral finance is an interesting field 1200 00:48:44,760 --> 00:48:46,710 because, for quite a while, economists 1201 00:48:46,710 --> 00:48:48,780 thought that sort of neoclassical assumptions 1202 00:48:48,780 --> 00:48:51,930 are, in fact, most likely to hold in financial markets. 1203 00:48:51,930 --> 00:48:54,450 And why is that? 1204 00:48:54,450 --> 00:48:56,640 And some of this already I mentioned, but why 1205 00:48:56,640 --> 00:49:01,160 are financial markets particular-- 1206 00:49:01,160 --> 00:49:02,910 why might one think that financial markets 1207 00:49:02,910 --> 00:49:04,450 are particularly efficient? 1208 00:49:18,170 --> 00:49:18,740 Yes. 1209 00:49:18,740 --> 00:49:20,990 AUDIENCE: Well, you might think that financial markets 1210 00:49:20,990 --> 00:49:22,700 are very competitive. 1211 00:49:22,700 --> 00:49:24,680 And so it's actually the ones who 1212 00:49:24,680 --> 00:49:29,530 can get rid of their behavioral biases that benefit the most 1213 00:49:29,530 --> 00:49:31,948 and stay within financial market. 1214 00:49:31,948 --> 00:49:32,990 FRANK SCHILBACH: Exactly. 1215 00:49:32,990 --> 00:49:36,680 So it's very much sort of the Chicago economics assumption 1216 00:49:36,680 --> 00:49:41,400 is to say, so financial markets are extremely competitive. 1217 00:49:41,400 --> 00:49:44,848 If I'm an investor who has various behavioral biases, 1218 00:49:44,848 --> 00:49:46,640 presumably I'm going to lose some money one 1219 00:49:46,640 --> 00:49:47,690 way or the other. 1220 00:49:47,690 --> 00:49:49,940 Well, if markets are really competitive, 1221 00:49:49,940 --> 00:49:52,580 in the long run I cannot stay in this market without sort 1222 00:49:52,580 --> 00:49:55,820 of being driven out. 1223 00:49:55,820 --> 00:49:57,390 So essentially, the market favors 1224 00:49:57,390 --> 00:50:01,052 sort of results-oriented, rational, and selfish behavior. 1225 00:50:01,052 --> 00:50:03,260 So people who are not rational and so on and so forth 1226 00:50:03,260 --> 00:50:05,627 will be eliminated from the market eventually. 1227 00:50:05,627 --> 00:50:06,710 There's two parts to that. 1228 00:50:06,710 --> 00:50:08,300 That's true across firms. 1229 00:50:08,300 --> 00:50:10,100 That's to say there are some firms 1230 00:50:10,100 --> 00:50:11,330 sort of better than others. 1231 00:50:11,330 --> 00:50:13,220 But also, within a firm, if I'm an investor 1232 00:50:13,220 --> 00:50:15,890 and I'm sort of advising clients and the like-- and 1233 00:50:15,890 --> 00:50:17,510 I'm sort of not very good at this. 1234 00:50:17,510 --> 00:50:19,400 And essentially, I have certain people biases 1235 00:50:19,400 --> 00:50:22,970 that are not optimal in terms of making money for people. 1236 00:50:22,970 --> 00:50:24,530 Presumably, I will not be promoted. 1237 00:50:24,530 --> 00:50:28,880 Presumably, I will be driven out of or fired from the company 1238 00:50:28,880 --> 00:50:30,470 eventually. 1239 00:50:30,470 --> 00:50:32,720 So surprisingly, in fact, finance 1240 00:50:32,720 --> 00:50:34,940 became one of the most influential and most fruitful 1241 00:50:34,940 --> 00:50:37,470 applications of the psychology in economics 1242 00:50:37,470 --> 00:50:38,690 of behavioral economics. 1243 00:50:38,690 --> 00:50:41,430 There's lots and lots of work in behavioral finance. 1244 00:50:41,430 --> 00:50:44,030 The reason being perhaps not necessarily 1245 00:50:44,030 --> 00:50:45,123 because people are-- 1246 00:50:45,123 --> 00:50:46,790 so some people are presumably driven out 1247 00:50:46,790 --> 00:50:48,860 of the market, but surely not everyone. 1248 00:50:48,860 --> 00:50:51,530 But in particular, because there is a great data in finance. 1249 00:50:51,530 --> 00:50:56,000 There's lots and lots of daily data in terms of things 1250 00:50:56,000 --> 00:50:58,400 that you should be doing compared 1251 00:50:58,400 --> 00:51:00,200 to what models would say. 1252 00:51:00,200 --> 00:51:01,820 So it's a really great way of being 1253 00:51:01,820 --> 00:51:04,220 able to test models or test essentially 1254 00:51:04,220 --> 00:51:06,860 predictions of the neoclassical model or behavioral theories 1255 00:51:06,860 --> 00:51:07,830 and so on. 1256 00:51:07,830 --> 00:51:10,790 So that's why behavioral finance has been very influential 1257 00:51:10,790 --> 00:51:12,920 because there's so much data available for people 1258 00:51:12,920 --> 00:51:16,220 to, in fact, test theories. 1259 00:51:16,220 --> 00:51:19,140 And then why is it that people are not entirely driven out? 1260 00:51:19,140 --> 00:51:21,410 I think often the case is that, even if you're right, 1261 00:51:21,410 --> 00:51:23,750 for example, even if you're right that you can predict-- 1262 00:51:23,750 --> 00:51:28,050 and if you watch some movies on the financial crisis 1263 00:51:28,050 --> 00:51:31,430 and so on, even if you're right about in the long run 1264 00:51:31,430 --> 00:51:33,500 the market is going to tank, well, actually it's 1265 00:51:33,500 --> 00:51:34,730 going to take a lot of money. 1266 00:51:34,730 --> 00:51:37,100 And often, if everybody is wrong, 1267 00:51:37,100 --> 00:51:39,520 prices will go up for quite a while. 1268 00:51:39,520 --> 00:51:41,420 So it's not actually clear that, at least 1269 00:51:41,420 --> 00:51:45,180 in the short, medium run, we'll be driven out of the market 1270 00:51:45,180 --> 00:51:45,680 quickly. 1271 00:51:45,680 --> 00:51:49,000 But that's sort of a separate topic. 1272 00:51:49,000 --> 00:51:49,750 OK. 1273 00:51:49,750 --> 00:51:52,968 So now, one reason why or one way 1274 00:51:52,968 --> 00:51:54,760 in which reference-dependent behavior might 1275 00:51:54,760 --> 00:51:57,250 be important in finance is people 1276 00:51:57,250 --> 00:52:01,120 might be differentially likely to sell winners and hold 1277 00:52:01,120 --> 00:52:03,910 on to losers, financial stocks. 1278 00:52:03,910 --> 00:52:05,690 That was mentioned last time as well. 1279 00:52:05,690 --> 00:52:09,160 So what Terry Odean did in 1997 is he had, in fact, 1280 00:52:09,160 --> 00:52:12,160 brokerage accounts from the nationwide brokerage 1281 00:52:12,160 --> 00:52:16,090 house, which had all trades and prices for, I guess, '87 1282 00:52:16,090 --> 00:52:17,080 to '93. 1283 00:52:17,080 --> 00:52:19,600 In some sense-- a little bit old fashioned in a sense of you 1284 00:52:19,600 --> 00:52:22,150 shouldn't be an individual trading and so on. 1285 00:52:22,150 --> 00:52:24,670 You should just hold the stock market or the S&P 500 1286 00:52:24,670 --> 00:52:26,410 or some index funds and so on. 1287 00:52:26,410 --> 00:52:28,750 Here, these are people who hold individual stocks 1288 00:52:28,750 --> 00:52:31,870 and sell and buy them one by one. 1289 00:52:31,870 --> 00:52:34,270 And so during each trading day, then what Odean can do 1290 00:52:34,270 --> 00:52:36,910 is he can look at, evaluate, each stock in the portfolio 1291 00:52:36,910 --> 00:52:41,137 and look at this is a loss relative to the purchase price. 1292 00:52:41,137 --> 00:52:43,720 So you can look at, essentially, the portfolio and say there's 1293 00:52:43,720 --> 00:52:46,210 losers and winners. 1294 00:52:46,210 --> 00:52:48,230 He only has data on trading days. 1295 00:52:48,230 --> 00:52:51,610 So you can look at are they losers and winners 1296 00:52:51,610 --> 00:52:53,260 when they're being sold. 1297 00:52:53,260 --> 00:52:58,210 And he can look at then at realized gains and realized 1298 00:52:58,210 --> 00:52:58,880 losses. 1299 00:52:58,880 --> 00:53:01,570 So if you sell a stock and it's essentially 1300 00:53:01,570 --> 00:53:07,360 above the purchase price, he calls it a realized loss. 1301 00:53:07,360 --> 00:53:09,490 Sorry, if it's a losing stock, it's sold. 1302 00:53:09,490 --> 00:53:10,420 It's a realized loss. 1303 00:53:10,420 --> 00:53:11,740 It's below the purchase price. 1304 00:53:11,740 --> 00:53:13,210 If it's above the purchase price, 1305 00:53:13,210 --> 00:53:15,430 it's going to be a realized gain. 1306 00:53:15,430 --> 00:53:17,140 Now, one thing you could do is compare 1307 00:53:17,140 --> 00:53:20,702 the number of realized losses to the number of realized gains. 1308 00:53:20,702 --> 00:53:22,660 Does that work, or is that reference-dependent? 1309 00:53:22,660 --> 00:53:24,130 So what did we learn from that? 1310 00:53:40,770 --> 00:53:41,970 Yes. 1311 00:53:41,970 --> 00:53:43,770 AUDIENCE: [INAUDIBLE] people [INAUDIBLE] 1312 00:53:43,770 --> 00:53:46,200 people won't want to [INAUDIBLE] are losing stock 1313 00:53:46,200 --> 00:53:48,867 because they're comparing to the price they bought [INAUDIBLE].. 1314 00:53:48,867 --> 00:53:49,825 FRANK SCHILBACH: Right. 1315 00:53:49,825 --> 00:53:51,482 So I could look at the realized gains 1316 00:53:51,482 --> 00:53:53,940 and the number of realized gains and the number of realized 1317 00:53:53,940 --> 00:53:54,870 losses. 1318 00:53:54,870 --> 00:53:56,350 But what's the problem with that? 1319 00:53:56,350 --> 00:53:58,747 That's exactly right, but what's the underlying, 1320 00:53:58,747 --> 00:54:00,330 what's the problem with this approach? 1321 00:54:05,802 --> 00:54:08,260 How does this depend on the stock market going up and down? 1322 00:54:10,950 --> 00:54:11,590 Yes? 1323 00:54:11,590 --> 00:54:15,034 AUDIENCE: You're not looking at the magnitude of those gains 1324 00:54:15,034 --> 00:54:17,503 or losses? 1325 00:54:17,503 --> 00:54:18,420 FRANK SCHILBACH: Yeah. 1326 00:54:18,420 --> 00:54:20,040 So that's a separate issue. 1327 00:54:20,040 --> 00:54:21,900 You could look at the magnitudes themselves. 1328 00:54:21,900 --> 00:54:24,540 And you could look at, depending on where you are, 1329 00:54:24,540 --> 00:54:25,980 how does that matter. 1330 00:54:25,980 --> 00:54:28,980 But what about just a number of gains and losses? 1331 00:54:28,980 --> 00:54:31,530 What if the stock market goes up a lot? 1332 00:54:31,530 --> 00:54:34,081 What are people going to sell or [INAUDIBLE]?? 1333 00:54:37,280 --> 00:54:38,010 Yeah. 1334 00:54:38,010 --> 00:54:40,400 AUDIENCE: Well, one issue is that you don't know when 1335 00:54:40,400 --> 00:54:43,100 or for how long something has been losing. 1336 00:54:43,100 --> 00:54:45,725 So if it's been losing for long time 1337 00:54:45,725 --> 00:54:48,420 or gaining for a long time, that might impact the [INAUDIBLE] 1338 00:54:48,420 --> 00:54:50,057 hang onto it or sell it? 1339 00:54:50,057 --> 00:54:51,640 FRANK SCHILBACH: So he does have that. 1340 00:54:51,640 --> 00:54:54,010 I think I'm asking for something very basic, which 1341 00:54:54,010 --> 00:54:56,020 is, if the stock market goes up a lot, 1342 00:54:56,020 --> 00:54:57,220 you'll have lots of winners. 1343 00:54:57,220 --> 00:54:59,220 So you're going to realize lots of-- if you just 1344 00:54:59,220 --> 00:55:00,940 sell randomly, stocks, gains and losses, 1345 00:55:00,940 --> 00:55:03,775 and you just don't care, you'll have much more realized gains 1346 00:55:03,775 --> 00:55:06,400 compared to realized losses just because your stock market went 1347 00:55:06,400 --> 00:55:07,240 up a lot. 1348 00:55:07,240 --> 00:55:09,230 Similarly, if the stock market went down, 1349 00:55:09,230 --> 00:55:12,040 you will find that people have way more realized losses 1350 00:55:12,040 --> 00:55:13,487 compared to realize gains. 1351 00:55:13,487 --> 00:55:15,820 And it looked like I'm really trying to sell the losers, 1352 00:55:15,820 --> 00:55:17,695 but it's not I'm actually selling the losers. 1353 00:55:17,695 --> 00:55:19,690 I just have a lot more losers. 1354 00:55:19,690 --> 00:55:20,770 That's all I was asking. 1355 00:55:20,770 --> 00:55:23,187 I think he has actually the information about the purchase 1356 00:55:23,187 --> 00:55:23,740 prices. 1357 00:55:23,740 --> 00:55:25,700 So what he then does is something very simple. 1358 00:55:25,700 --> 00:55:27,730 It just looks at people's portfolios and says, 1359 00:55:27,730 --> 00:55:29,470 how many losing stocks do you have? 1360 00:55:29,470 --> 00:55:32,080 What's your propensity to sell the losing stocks, which 1361 00:55:32,080 --> 00:55:36,220 is what you call the PLR, the Proportion of Losers Realized? 1362 00:55:36,220 --> 00:55:38,230 The same he does for the PGR, which is 1363 00:55:38,230 --> 00:55:39,903 a Proportion of Gains Realized. 1364 00:55:39,903 --> 00:55:42,070 So he looks at each person when they sell something. 1365 00:55:42,070 --> 00:55:44,070 They look at how many losing stocks do you have. 1366 00:55:44,070 --> 00:55:45,670 How many winning stocks do you have? 1367 00:55:45,670 --> 00:55:47,770 And then he looks at what's the probability of you 1368 00:55:47,770 --> 00:55:52,340 selling any of those depending on they're winners or losers. 1369 00:55:52,340 --> 00:55:54,040 So what the main finding then here 1370 00:55:54,040 --> 00:55:57,490 is that the PGR, the Proportion of Gains Realized, 1371 00:55:57,490 --> 00:55:59,920 is larger than the PLR. 1372 00:55:59,920 --> 00:56:02,410 And that's to say that's what they call the disposition 1373 00:56:02,410 --> 00:56:05,200 effect, which is a tendency to sell winners and hold on 1374 00:56:05,200 --> 00:56:07,040 to losers. 1375 00:56:07,040 --> 00:56:08,760 Does that make sense? 1376 00:56:08,760 --> 00:56:09,300 OK. 1377 00:56:09,300 --> 00:56:10,773 And so why do we care about that? 1378 00:56:10,773 --> 00:56:11,940 Or why is this actually bad? 1379 00:56:11,940 --> 00:56:14,465 Is it's necessarily suboptimal behavior? 1380 00:56:14,465 --> 00:56:15,090 Why do we care? 1381 00:56:26,870 --> 00:56:27,422 Yes. 1382 00:56:27,422 --> 00:56:28,880 AUDIENCE: I think you had mentioned 1383 00:56:28,880 --> 00:56:31,090 in a previous class [INAUDIBLE] sometimes it 1384 00:56:31,090 --> 00:56:35,300 might be worthwhile to hold on to the winners 1385 00:56:35,300 --> 00:56:39,236 or someone who's betting on [INAUDIBLE].. 1386 00:56:39,236 --> 00:56:42,070 But probably shouldn't be an overall bias 1387 00:56:42,070 --> 00:56:44,990 towards selling losers. 1388 00:56:44,990 --> 00:56:47,700 And then probably [INAUDIBLE] overall effective strategy 1389 00:56:47,700 --> 00:56:48,582 [INAUDIBLE]. 1390 00:56:48,582 --> 00:56:49,540 FRANK SCHILBACH: Right. 1391 00:56:49,540 --> 00:56:51,310 So it depends on, essentially, how well 1392 00:56:51,310 --> 00:56:53,320 the winners and the losers are going to do. 1393 00:56:53,320 --> 00:56:56,150 It turns out, so in principle, you would say, 1394 00:56:56,150 --> 00:57:00,220 well, winners and losers should have the same expected 1395 00:57:00,220 --> 00:57:03,280 return regardless of the winners and losers in the past. 1396 00:57:03,280 --> 00:57:05,440 That's essentially the efficient market hypothesis, 1397 00:57:05,440 --> 00:57:08,620 just to say past price changes should just not 1398 00:57:08,620 --> 00:57:13,867 be predictive of future momentum or price changes overall. 1399 00:57:13,867 --> 00:57:16,450 Because the current price should have incorporated essentially 1400 00:57:16,450 --> 00:57:18,742 all information that's available at this point in time. 1401 00:57:18,742 --> 00:57:21,325 So to that degree, it shouldn't matter actually what you sell. 1402 00:57:21,325 --> 00:57:23,048 You could just randomly sell stuff. 1403 00:57:23,048 --> 00:57:24,340 Now, you should not sell a lot. 1404 00:57:24,340 --> 00:57:26,450 Usually, there's commissions involved in these trades. 1405 00:57:26,450 --> 00:57:27,867 So essentially, you shouldn't sell 1406 00:57:27,867 --> 00:57:30,783 anything that's essentially leading to over-trading. 1407 00:57:30,783 --> 00:57:32,200 Odean has another paper that shows 1408 00:57:32,200 --> 00:57:33,700 essentially, in particular, men tend 1409 00:57:33,700 --> 00:57:36,280 to be overconfident in how good they are at trading. 1410 00:57:36,280 --> 00:57:39,430 And they tend to over-trade, and that's really costly. 1411 00:57:39,430 --> 00:57:44,380 It turns out that, in their specific period, 1412 00:57:44,380 --> 00:57:45,850 in fact there's momentum. 1413 00:57:45,850 --> 00:57:48,513 And that used to be the case quite a bit in that period 1414 00:57:48,513 --> 00:57:50,680 of time, which essentially has to do with the winner 1415 00:57:50,680 --> 00:57:52,480 is actually doing better than the losers 1416 00:57:52,480 --> 00:57:54,430 by quite a big margin. 1417 00:57:54,430 --> 00:57:57,230 That is to say, you should have actually did exactly 1418 00:57:57,230 --> 00:57:57,980 then the opposite. 1419 00:57:57,980 --> 00:57:59,813 If anything, you should have sold the losers 1420 00:57:59,813 --> 00:58:02,650 and keep the winners because they are, in fact, making 1421 00:58:02,650 --> 00:58:08,890 more money in the short and medium run in that period, OK? 1422 00:58:08,890 --> 00:58:11,110 There's also the investors sell more losers 1423 00:58:11,110 --> 00:58:12,277 and winners in December. 1424 00:58:12,277 --> 00:58:13,360 This is what you see here. 1425 00:58:13,360 --> 00:58:14,020 Why is that? 1426 00:58:18,040 --> 00:58:18,540 Yes. 1427 00:58:18,540 --> 00:58:19,530 AUDIENCE: Is it that you can count 1428 00:58:19,530 --> 00:58:20,520 your losses toward your income? 1429 00:58:20,520 --> 00:58:22,603 FRANK SCHILBACH: Exactly, this is for tax reasons. 1430 00:58:22,603 --> 00:58:24,150 So that actually happens to-- 1431 00:58:24,150 --> 00:58:26,310 Jim Poterba, who's in the economics department, 1432 00:58:26,310 --> 00:58:28,020 actually did a paper on this. 1433 00:58:28,020 --> 00:58:30,380 So there you can essentially realize losses, 1434 00:58:30,380 --> 00:58:35,560 and that reduces your taxes overall. 1435 00:58:35,560 --> 00:58:36,060 Exactly. 1436 00:58:36,060 --> 00:58:37,768 But overall, essentially what's happening 1437 00:58:37,768 --> 00:58:40,620 is that people do seem to engage in this behavior. 1438 00:58:40,620 --> 00:58:42,150 In a pretty striking fashion, they 1439 00:58:42,150 --> 00:58:46,500 seem to be losing quite a bit of money from that. 1440 00:58:46,500 --> 00:58:47,190 OK. 1441 00:58:47,190 --> 00:58:50,647 Let me mention at least the marathon running and perhaps 1442 00:58:50,647 --> 00:58:52,230 the golf example, and then we're going 1443 00:58:52,230 --> 00:58:55,390 to move towards prices and firms. 1444 00:58:55,390 --> 00:58:57,045 How do firms react to these biases? 1445 00:58:57,045 --> 00:58:58,920 But what I'm trying to do here is essentially 1446 00:58:58,920 --> 00:59:00,660 show you a bunch of different settings. 1447 00:59:00,660 --> 00:59:02,430 And essentially, if you look at different settings 1448 00:59:02,430 --> 00:59:04,770 in the world, there's lots and lots of different settings 1449 00:59:04,770 --> 00:59:06,510 where reference-dependence seems to matter. 1450 00:59:06,510 --> 00:59:08,885 One way or the other, it seems to be important in shaping 1451 00:59:08,885 --> 00:59:10,180 people's behavior. 1452 00:59:10,180 --> 00:59:13,740 So this is a very nice paper about a marathon running 1453 00:59:13,740 --> 00:59:14,610 finishing times. 1454 00:59:14,610 --> 00:59:15,902 These are many, many marathons. 1455 00:59:15,902 --> 00:59:18,970 They have lots of data on finishing times for people. 1456 00:59:18,970 --> 00:59:21,030 So the law of large numbers would 1457 00:59:21,030 --> 00:59:23,790 predict that, if you look at essentially people's finishing 1458 00:59:23,790 --> 00:59:27,510 times, if people have different talents and so on and so forth, 1459 00:59:27,510 --> 00:59:30,040 the finishing times should look something like this. 1460 00:59:30,040 --> 00:59:30,540 OK. 1461 00:59:30,540 --> 00:59:31,470 Some people are faster. 1462 00:59:31,470 --> 00:59:32,428 Some people are slower. 1463 00:59:32,428 --> 00:59:36,668 But overall they're should be some smooth distribution that 1464 00:59:36,668 --> 00:59:39,210 essentially is like log normal or whatever you want it to be. 1465 00:59:39,210 --> 00:59:42,070 But essentially, it should look something like this. 1466 00:59:42,070 --> 00:59:43,950 So why might it not look like this? 1467 00:59:43,950 --> 00:59:48,260 Or what might people do instead? 1468 00:59:48,260 --> 00:59:49,100 Yes. 1469 00:59:49,100 --> 00:59:52,080 AUDIENCE: They may say, I'll beat 4:30. 1470 00:59:52,080 --> 00:59:54,770 And then you might see bunching at certain points, 1471 00:59:54,770 --> 00:59:58,312 like 4 hours, 4:30, 5 hours, 5:30. 1472 00:59:58,312 --> 00:59:59,270 FRANK SCHILBACH: Right. 1473 00:59:59,270 --> 01:00:01,430 So exactly as you say, it might be 1474 01:00:01,430 --> 01:00:03,140 that people have reference points 1475 01:00:03,140 --> 01:00:05,420 not in terms of status quo here and the like. 1476 01:00:05,420 --> 01:00:07,640 Reference points might be goals or aspirations. 1477 01:00:07,640 --> 01:00:10,460 You might say, I really want to run the marathon in 4 hours 1478 01:00:10,460 --> 01:00:13,380 or 4:30 or 4 hours if you want. 1479 01:00:13,380 --> 01:00:16,130 And then what the marathon times actually look like 1480 01:00:16,130 --> 01:00:17,295 is something like this. 1481 01:00:17,295 --> 01:00:18,920 And in particular, it seems like people 1482 01:00:18,920 --> 01:00:22,800 have lots of goals of reaching something like-- 1483 01:00:22,800 --> 01:00:24,890 if you look at the distribution, what you see 1484 01:00:24,890 --> 01:00:27,380 is exactly as you predict. 1485 01:00:27,380 --> 01:00:29,840 If you look at the half hour or even 1486 01:00:29,840 --> 01:00:33,020 the quarter hour sort of points, there's 1487 01:00:33,020 --> 01:00:35,070 essentially bunching from below. 1488 01:00:35,070 --> 01:00:37,220 So essentially, people seem to be, 1489 01:00:37,220 --> 01:00:41,540 if they're at pace to finish at 4 hours and 1 minute, 1490 01:00:41,540 --> 01:00:44,027 they try to sort of speed up and just make it to 3:59. 1491 01:00:48,800 --> 01:00:52,100 So you see a bunch of bunching at the half hour slots. 1492 01:00:52,100 --> 01:00:54,558 You see actually much less at 6 hours and 30 minutes 1493 01:00:54,558 --> 01:00:55,100 or something. 1494 01:00:55,100 --> 01:00:56,975 It seems that few people have actually goals. 1495 01:00:56,975 --> 01:00:59,413 Once you run the marathon in 6 hours and 30 minutes, 1496 01:00:59,413 --> 01:01:00,830 which is probably what I would do, 1497 01:01:00,830 --> 01:01:02,872 you know, it doesn't really matter whether you're 1498 01:01:02,872 --> 01:01:04,825 like 6:31 or 6:29. 1499 01:01:04,825 --> 01:01:06,200 But there's very ambitious people 1500 01:01:06,200 --> 01:01:10,280 who want to like finish in 4:30, 4 hours, or 3:30 and the like. 1501 01:01:10,280 --> 01:01:15,030 And there's a bunch of bunching from below there. 1502 01:01:15,030 --> 01:01:18,710 So you see the same for quarter hour times, a little bit less 1503 01:01:18,710 --> 01:01:21,110 of that. 1504 01:01:21,110 --> 01:01:23,360 And sort of that's consistent with the reference point 1505 01:01:23,360 --> 01:01:25,733 here being a goal and aspiration. 1506 01:01:25,733 --> 01:01:26,900 You want to reach 4 minutes. 1507 01:01:26,900 --> 01:01:28,460 You want to brag to your friends and so on. 1508 01:01:28,460 --> 01:01:30,050 And it's not so great if you do that and say, 1509 01:01:30,050 --> 01:01:32,570 I finished in 4 hours and 1 minute as opposed to if you 1510 01:01:32,570 --> 01:01:35,690 say I finished below 4 hours. 1511 01:01:35,690 --> 01:01:40,130 Now, when you look at the effort at the end of the race, what 1512 01:01:40,130 --> 01:01:40,880 would you expect? 1513 01:01:40,880 --> 01:01:43,910 So what we have here on the x-axis is people. 1514 01:01:43,910 --> 01:01:46,820 These are the 40 kilometer pace. 1515 01:01:46,820 --> 01:01:50,010 These are in 30 second increments. 1516 01:01:50,010 --> 01:01:57,860 So the marathon is 42.195 kilometers. 1517 01:01:57,860 --> 01:02:00,770 So what I'm showing you here is, essentially, 1518 01:02:00,770 --> 01:02:04,760 the 40 kilometer pace people are ranked or distributed 1519 01:02:04,760 --> 01:02:08,310 by the 40 kilometer pace, the first 40 kilometers. 1520 01:02:08,310 --> 01:02:10,160 Now, what you would expect for people-- 1521 01:02:10,160 --> 01:02:12,740 so there are some people who were at pace 1522 01:02:12,740 --> 01:02:17,715 to reach 3:55 and some people at pace to reach 4:05 and so on. 1523 01:02:17,715 --> 01:02:19,340 What is it that you would expect people 1524 01:02:19,340 --> 01:02:23,810 to do when you look at how fast people run towards the last two 1525 01:02:23,810 --> 01:02:24,920 kilometers of the race? 1526 01:02:31,380 --> 01:02:31,880 Yes? 1527 01:02:31,880 --> 01:02:33,297 AUDIENCE: If they're really close, 1528 01:02:33,297 --> 01:02:35,938 they're going [INAUDIBLE] especially hard. 1529 01:02:35,938 --> 01:02:36,980 FRANK SCHILBACH: Exactly. 1530 01:02:36,980 --> 01:02:38,022 And this is what you see. 1531 01:02:38,022 --> 01:02:39,670 So low means you're running fast. 1532 01:02:39,670 --> 01:02:42,740 This is minutes per kilometer I think 1533 01:02:42,740 --> 01:02:44,570 or relative minutes per kilometer. 1534 01:02:44,570 --> 01:02:46,460 So what you should expect is people 1535 01:02:46,460 --> 01:02:50,330 who are just below the goal or people who are essentially just 1536 01:02:50,330 --> 01:02:53,480 above the goal, in fact, these are the people who speed up, 1537 01:02:53,480 --> 01:02:55,040 OK? 1538 01:02:55,040 --> 01:02:56,540 And this is exactly what you sort of 1539 01:02:56,540 --> 01:03:00,180 see is that people who are just below the 4 minute mark 1540 01:03:00,180 --> 01:03:03,020 or some people who are just above, they speed up 1541 01:03:03,020 --> 01:03:04,820 to just make it to that goal. 1542 01:03:04,820 --> 01:03:06,320 And sort of Allen et al. 1543 01:03:06,320 --> 01:03:08,270 Have a sort of analysis of this. 1544 01:03:08,270 --> 01:03:12,050 Essentially, what they find is that everybody 1545 01:03:12,050 --> 01:03:14,090 gets sort of slower towards the end of the race. 1546 01:03:14,090 --> 01:03:16,280 But if you're sort of in reach of reaching 1547 01:03:16,280 --> 01:03:20,180 the goal by reaching the time of 4 hours, 1548 01:03:20,180 --> 01:03:23,750 you're going to slow down less or speed up a bit to just reach 1549 01:03:23,750 --> 01:03:25,620 that specific goal, OK? 1550 01:03:28,400 --> 01:03:32,120 Let me show you one more thing of sports, which is golf. 1551 01:03:32,120 --> 01:03:33,410 So how does golf work? 1552 01:03:33,410 --> 01:03:37,520 In case you don't know, you hit a ball with a club from a tee 1553 01:03:37,520 --> 01:03:38,960 into a hole. 1554 01:03:38,960 --> 01:03:43,610 The way this works is there's usually 4 rounds of 18 holes. 1555 01:03:43,610 --> 01:03:48,830 There is very convex incentives in the golf tournament. 1556 01:03:48,830 --> 01:03:50,600 So you get a bunch of money if you win, 1557 01:03:50,600 --> 01:03:52,010 if you're sort of at the top. 1558 01:03:52,010 --> 01:03:54,165 For an average performance, essentially you 1559 01:03:54,165 --> 01:03:55,290 don't make that much money. 1560 01:03:55,290 --> 01:03:58,430 I mean, you make good money, but the prize money 1561 01:03:58,430 --> 01:04:02,010 is really in terms of when you do really well. 1562 01:04:02,010 --> 01:04:03,230 So now, what is par? 1563 01:04:03,230 --> 01:04:08,110 Par is how many strokes, many shots, do you need to-- 1564 01:04:08,110 --> 01:04:10,280 how many shots a very good golfer should require 1565 01:04:10,280 --> 01:04:13,880 to complete a given hole. 1566 01:04:13,880 --> 01:04:17,840 So par is usually 3, 4, or 5 shots. 1567 01:04:17,840 --> 01:04:20,280 And then eagle is 2 below par. 1568 01:04:20,280 --> 01:04:22,700 So if you have a par 4 hole, if you do 2 shots, 1569 01:04:22,700 --> 01:04:23,660 that's an eagle. 1570 01:04:23,660 --> 01:04:26,120 If you do 3 shots in that case, that would be a birdie. 1571 01:04:26,120 --> 01:04:27,110 4 would be par. 1572 01:04:27,110 --> 01:04:29,030 Bogey would be 1 above par. 1573 01:04:29,030 --> 01:04:32,900 And double bogey would be 2 above par, OK? 1574 01:04:32,900 --> 01:04:36,380 So knowing all that, so what matters for golf 1575 01:04:36,380 --> 01:04:38,600 at the end of a tournament is how many shots do you 1576 01:04:38,600 --> 01:04:40,065 make in total. 1577 01:04:40,065 --> 01:04:42,440 So how can we now look at reference-dependent preferences 1578 01:04:42,440 --> 01:04:44,870 here in this setting? 1579 01:05:02,090 --> 01:05:02,750 Yes. 1580 01:05:02,750 --> 01:05:04,980 AUDIENCE: The reference is the par [INAUDIBLE].. 1581 01:05:04,980 --> 01:05:05,855 FRANK SCHILBACH: Yes. 1582 01:05:05,855 --> 01:05:06,980 The reference is the par. 1583 01:05:06,980 --> 01:05:11,090 Now, suppose you are putting, which is at the end, 1584 01:05:11,090 --> 01:05:12,398 you know, on the green. 1585 01:05:12,398 --> 01:05:13,440 What are you going to do? 1586 01:05:13,440 --> 01:05:15,005 What kinds of behaviors do we expect? 1587 01:05:17,920 --> 01:05:18,765 Yes. 1588 01:05:18,765 --> 01:05:19,890 AUDIENCE: Well, it depends. 1589 01:05:19,890 --> 01:05:22,870 So if you're under par, then you might 1590 01:05:22,870 --> 01:05:24,530 try-- like, you're shooting for birdie, 1591 01:05:24,530 --> 01:05:26,530 or you're shooting for par and it's a long putt, 1592 01:05:26,530 --> 01:05:29,290 you might try to make sure that you get it to the hole. 1593 01:05:29,290 --> 01:05:32,740 Whereas, if you are already over par or double over par, 1594 01:05:32,740 --> 01:05:34,650 you might try to play a little safer, 1595 01:05:34,650 --> 01:05:35,992 make sure you're not way over. 1596 01:05:35,992 --> 01:05:36,950 FRANK SCHILBACH: Right. 1597 01:05:36,950 --> 01:05:39,490 So some of this is about risk preferences, 1598 01:05:39,490 --> 01:05:41,673 how risky your shots are. 1599 01:05:41,673 --> 01:05:43,090 Another way to think about this is 1600 01:05:43,090 --> 01:05:45,130 kind of how much effort do you put in your shot. 1601 01:05:45,130 --> 01:05:49,750 In some sense, to the extent that you can sort of allocate 1602 01:05:49,750 --> 01:05:52,210 attention or really focus an effort, 1603 01:05:52,210 --> 01:05:54,580 maybe that's sort of limited over the course of 18 holes 1604 01:05:54,580 --> 01:05:59,830 and 4 rounds of each of those. 1605 01:05:59,830 --> 01:06:03,250 You might sort of try particularly hard to do well 1606 01:06:03,250 --> 01:06:06,190 on shots that make you reach par compared 1607 01:06:06,190 --> 01:06:10,100 to shots that might get you a birdie or even better. 1608 01:06:10,100 --> 01:06:12,610 And so this is exactly as you say. 1609 01:06:12,610 --> 01:06:15,130 The fairly obvious reference point for each hole in golf 1610 01:06:15,130 --> 01:06:16,570 is reach par. 1611 01:06:16,570 --> 01:06:19,510 Importantly, it doesn't matter whether you 1612 01:06:19,510 --> 01:06:23,020 have birdie, par, and bogie, versus par, par, par. 1613 01:06:23,020 --> 01:06:26,050 Essentially, that gives you exactly the same amount 1614 01:06:26,050 --> 01:06:27,400 of shots overall. 1615 01:06:27,400 --> 01:06:32,110 But now what Pope and Schweitzer ask is the question, 1616 01:06:32,110 --> 01:06:35,757 are putters more likely to make their par 1617 01:06:35,757 --> 01:06:37,090 than their birdie points, right? 1618 01:06:37,090 --> 01:06:42,340 So essentially, depending on are you at possibility of losing 1619 01:06:42,340 --> 01:06:45,130 or at gaining, essentially if you're 1620 01:06:45,130 --> 01:06:48,730 worried about losing par, are you going to behave differently 1621 01:06:48,730 --> 01:06:51,520 compared to when you can make a birdie, which is in the gain 1622 01:06:51,520 --> 01:06:52,780 domain potentially? 1623 01:06:52,780 --> 01:06:55,240 The same you could say about bogies, where you're already 1624 01:06:55,240 --> 01:06:57,615 in the loss domain because you're already doing terribly. 1625 01:06:57,615 --> 01:07:00,310 And you're trying to avoid a double bogey. 1626 01:07:00,310 --> 01:07:01,810 So now, what they find, essentially, 1627 01:07:01,810 --> 01:07:04,830 is the par putts are much more likely to be made. 1628 01:07:04,830 --> 01:07:06,910 There's 2 or 3 percentage points more likely 1629 01:07:06,910 --> 01:07:09,040 to be made compared to equivalent birdie putts. 1630 01:07:09,040 --> 01:07:11,380 The authors rule out a bunch of different explanation. 1631 01:07:11,380 --> 01:07:13,780 It doesn't have to do with the heterogeneity of player 1632 01:07:13,780 --> 01:07:14,680 ability. 1633 01:07:14,680 --> 01:07:16,737 They even have sort of like GPS information 1634 01:07:16,737 --> 01:07:18,820 of exactly where the ball is compared to the hole. 1635 01:07:18,820 --> 01:07:20,278 And they do all sorts of comparison 1636 01:07:20,278 --> 01:07:21,348 of how hard the shot is. 1637 01:07:21,348 --> 01:07:23,140 They don't think it has to do with learning 1638 01:07:23,140 --> 01:07:24,112 from earlier putts. 1639 01:07:24,112 --> 01:07:25,570 And it seems to also not have to do 1640 01:07:25,570 --> 01:07:26,910 with hole specific preferences. 1641 01:07:26,910 --> 01:07:28,660 Some holes are really hard, and some holes 1642 01:07:28,660 --> 01:07:31,520 are really simple and easy and so on. 1643 01:07:31,520 --> 01:07:34,790 So it doesn't seem to do with any of that. 1644 01:07:34,790 --> 01:07:37,690 So again, that's sort of another instance of reference-dependent 1645 01:07:37,690 --> 01:07:40,850 that seems to be in quite a few settings. 1646 01:07:40,850 --> 01:07:43,450 Let me sort of skip the Deal or No Deal TV show, which 1647 01:07:43,450 --> 01:07:46,720 we can do briefly in recitation, and talk a little bit 1648 01:07:46,720 --> 01:07:50,890 about prices and firms. 1649 01:07:50,890 --> 01:07:54,160 So one fact that we see in the world 1650 01:07:54,160 --> 01:07:56,770 is that demand often responds more strongly 1651 01:07:56,770 --> 01:08:00,100 to price increases than to price decreases of frequently 1652 01:08:00,100 --> 01:08:01,000 purchased items. 1653 01:08:01,000 --> 01:08:02,920 And we already discussed this last time. 1654 01:08:02,920 --> 01:08:06,730 That's to say, so usually people have a reference point 1655 01:08:06,730 --> 01:08:08,530 in terms of either the price they pay 1656 01:08:08,530 --> 01:08:11,000 or the expenditures on certain items. 1657 01:08:11,000 --> 01:08:12,850 So now, as something becomes more expensive, 1658 01:08:12,850 --> 01:08:14,308 what they tend to do is essentially 1659 01:08:14,308 --> 01:08:16,720 reduce how much the, for example, gasoline or the like. 1660 01:08:16,720 --> 01:08:20,229 They tend to then sort of just reduce their expenditures 1661 01:08:20,229 --> 01:08:24,040 because they have a budget for, say, gasoline or certain items. 1662 01:08:24,040 --> 01:08:25,600 And so what they tend to do is then 1663 01:08:25,600 --> 01:08:27,580 the reference point is either the past price 1664 01:08:27,580 --> 01:08:29,229 or the past expenditures. 1665 01:08:29,229 --> 01:08:32,050 And people tend to sort of be loss averse 1666 01:08:32,050 --> 01:08:39,970 then over their expenditures over the specific domain. 1667 01:08:39,970 --> 01:08:42,080 Now, that then leads to-- 1668 01:08:42,080 --> 01:08:44,229 so if a firm knows this, so essentially if you 1669 01:08:44,229 --> 01:08:49,569 know that essentially people react a lot to price increases 1670 01:08:49,569 --> 01:08:54,050 compared to price decreases, that leads to sticky prices, 1671 01:08:54,050 --> 01:08:54,550 essentially. 1672 01:08:54,550 --> 01:08:56,890 So raising your price above a past price 1673 01:08:56,890 --> 01:08:59,470 is very costly because you lose a lot of customers 1674 01:08:59,470 --> 01:09:00,680 from doing that. 1675 01:09:00,680 --> 01:09:03,760 So now, lowering your price below the past price 1676 01:09:03,760 --> 01:09:05,020 won't actually do very much. 1677 01:09:05,020 --> 01:09:06,728 Essentially, you're not going to generate 1678 01:09:06,728 --> 01:09:07,990 a lot more extra demand. 1679 01:09:07,990 --> 01:09:10,060 Plus, raising the price in the future is costly. 1680 01:09:10,060 --> 01:09:11,590 You know, essentially, once you lower the price, 1681 01:09:11,590 --> 01:09:12,840 it's hard to get up any more. 1682 01:09:12,840 --> 01:09:16,060 So for these frequently purchased items, 1683 01:09:16,060 --> 01:09:17,890 you see a lot of price stickiness and price 1684 01:09:17,890 --> 01:09:24,460 equalization across markets, across time and products. 1685 01:09:24,460 --> 01:09:27,729 Now, that's sort of one thing about prices in the world 1686 01:09:27,729 --> 01:09:29,352 that you would see. 1687 01:09:29,352 --> 01:09:31,060 But more generally, I want to sort of ask 1688 01:09:31,060 --> 01:09:32,859 the question in the last few minutes 1689 01:09:32,859 --> 01:09:35,830 about, if you were a company, suppose 1690 01:09:35,830 --> 01:09:39,130 you did an internship somewhere in the summer. 1691 01:09:39,130 --> 01:09:41,895 You took behavioral economics. 1692 01:09:41,895 --> 01:09:43,270 Hopefully, you learned something. 1693 01:09:43,270 --> 01:09:49,383 But what can we learn about the firm policies and so on now 1694 01:09:49,383 --> 01:09:50,800 that you know about loss aversion? 1695 01:09:50,800 --> 01:09:52,467 What would you tell them they should do? 1696 01:10:11,130 --> 01:10:11,730 Yes. 1697 01:10:11,730 --> 01:10:14,310 AUDIENCE: You could start with having a really high price 1698 01:10:14,310 --> 01:10:15,430 and then lowering them. 1699 01:10:15,430 --> 01:10:18,270 Because people will feel like, oh, I'm 1700 01:10:18,270 --> 01:10:19,542 getting [INAUDIBLE] deal. 1701 01:10:19,542 --> 01:10:20,500 FRANK SCHILBACH: Right. 1702 01:10:20,500 --> 01:10:23,010 So that was what previously was mentioned is I say, 1703 01:10:23,010 --> 01:10:26,640 you could sort of, in particular when you introduce a price, 1704 01:10:26,640 --> 01:10:29,278 new product and so on, you might want to start at a high price 1705 01:10:29,278 --> 01:10:30,570 and then sort of lowering them. 1706 01:10:30,570 --> 01:10:32,190 And people really like having deals, 1707 01:10:32,190 --> 01:10:33,940 and they feel good about it. 1708 01:10:33,940 --> 01:10:36,990 Notice that that doesn't work so well for products that you 1709 01:10:36,990 --> 01:10:38,160 already have and so on. 1710 01:10:38,160 --> 01:10:40,350 Because then essentially, once you start with a high price, 1711 01:10:40,350 --> 01:10:41,350 people get really upset. 1712 01:10:41,350 --> 01:10:43,180 And you will lose the customers. 1713 01:10:43,180 --> 01:10:46,110 But once you introduce a new product, be it like an iPhone 1714 01:10:46,110 --> 01:10:49,333 or be it like some whatever, new computer or whatever, 1715 01:10:49,333 --> 01:10:51,750 it makes a lot of sense to start with a really high price. 1716 01:10:51,750 --> 01:10:53,333 That sort of sets the reference point. 1717 01:10:53,333 --> 01:10:55,110 And then people sort of feel like they 1718 01:10:55,110 --> 01:10:57,092 get good deals overall. 1719 01:10:57,092 --> 01:10:58,050 What else could you do? 1720 01:10:58,050 --> 01:10:58,550 Yes. 1721 01:10:58,550 --> 01:11:01,308 AUDIENCE: You could offer [INAUDIBLE] price. 1722 01:11:01,308 --> 01:11:02,850 You could offer a temporary discount. 1723 01:11:02,850 --> 01:11:04,770 That was you keep your reference point. 1724 01:11:04,770 --> 01:11:06,900 [INAUDIBLE] offer discounts when you 1725 01:11:06,900 --> 01:11:09,328 want to lower the price temporarily [INAUDIBLE].. 1726 01:11:09,328 --> 01:11:10,370 FRANK SCHILBACH: Exactly. 1727 01:11:10,370 --> 01:11:12,120 That's what a lot of companies tend to do. 1728 01:11:12,120 --> 01:11:14,670 They tend to do, essentially, these special occasions 1729 01:11:14,670 --> 01:11:17,502 with Black Friday and the like. 1730 01:11:17,502 --> 01:11:18,960 Exactly as you say, it's temporary. 1731 01:11:18,960 --> 01:11:22,520 It's not a thing that prices are permanently lower. 1732 01:11:22,520 --> 01:11:25,040 It's just, right now, you get this great deal. 1733 01:11:25,040 --> 01:11:26,990 And then things go back to normal. 1734 01:11:26,990 --> 01:11:29,240 And somehow you have to hope that people don't sort of 1735 01:11:29,240 --> 01:11:31,850 adjust their reference point towards the temporarily 1736 01:11:31,850 --> 01:11:34,910 lowered price. 1737 01:11:34,910 --> 01:11:35,450 What else? 1738 01:11:35,450 --> 01:11:36,110 Yeah. 1739 01:11:36,110 --> 01:11:38,490 AUDIENCE: Kind of down that line, you have free trials. 1740 01:11:38,490 --> 01:11:39,860 So companies sends you-- 1741 01:11:39,860 --> 01:11:40,735 FRANK SCHILBACH: Yes. 1742 01:11:40,735 --> 01:11:43,040 AUDIENCE: --for [INAUDIBLE] and then take it away, 1743 01:11:43,040 --> 01:11:45,900 people will feel more compelled to get it back 1744 01:11:45,900 --> 01:11:47,440 because it's loss aversion. 1745 01:11:47,440 --> 01:11:50,610 And that's what [? creates ?] [INAUDIBLE] people value it 1746 01:11:50,610 --> 01:11:53,535 at higher price than otherwise. 1747 01:11:53,535 --> 01:11:54,410 FRANK SCHILBACH: Yes. 1748 01:11:54,410 --> 01:11:55,250 AUDIENCE: So [INAUDIBLE]. 1749 01:11:55,250 --> 01:11:55,800 FRANK SCHILBACH: Yes. 1750 01:11:55,800 --> 01:11:57,758 So if you shop online, you might have wondered. 1751 01:11:57,758 --> 01:11:59,508 Lots of companies have this thing on like, 1752 01:11:59,508 --> 01:12:01,038 oh, you can order whatever you want. 1753 01:12:01,038 --> 01:12:02,330 Essentially, it's free returns. 1754 01:12:02,330 --> 01:12:04,638 And you kind of wonder, that seems like a bad deal 1755 01:12:04,638 --> 01:12:05,930 from the company's perspective. 1756 01:12:05,930 --> 01:12:08,300 Because people buy a lot of stuff and send it back. 1757 01:12:08,300 --> 01:12:09,685 The hope is exactly as you say. 1758 01:12:09,685 --> 01:12:11,810 It might be just in part people like to experiment. 1759 01:12:11,810 --> 01:12:13,160 And they like some stuff and not others. 1760 01:12:13,160 --> 01:12:14,385 And that's worth doing it. 1761 01:12:14,385 --> 01:12:16,260 But the hope, in particular, is to say, well, 1762 01:12:16,260 --> 01:12:17,802 I want you to try it out for a while. 1763 01:12:17,802 --> 01:12:19,460 You get used to it. 1764 01:12:19,460 --> 01:12:20,930 Then the endowment effect kicks in. 1765 01:12:20,930 --> 01:12:22,040 You value it more. 1766 01:12:22,040 --> 01:12:23,660 It essentially becomes yours. 1767 01:12:23,660 --> 01:12:28,700 And then essentially you become loss averse towards that. 1768 01:12:28,700 --> 01:12:30,180 By the way, I should have mentioned 1769 01:12:30,180 --> 01:12:33,335 this is really a fascinating book by Cialdini who 1770 01:12:33,335 --> 01:12:37,760 was talking about the psychology of persuasion. 1771 01:12:37,760 --> 01:12:40,310 He spend a lot of time with salespeople, 1772 01:12:40,310 --> 01:12:42,410 in particular sort of car salespeople and so on, 1773 01:12:42,410 --> 01:12:45,350 trying to learn what are they actually doing in markets. 1774 01:12:45,350 --> 01:12:48,380 And he has these amazing stories of salespeople, what's 1775 01:12:48,380 --> 01:12:50,300 all sorts of tricks they use. 1776 01:12:50,300 --> 01:12:53,177 It's psychologically extremely rich and interesting in terms 1777 01:12:53,177 --> 01:12:55,010 of just trying to understand what people do. 1778 01:12:55,010 --> 01:12:59,390 And that ranges from things, once you purchase a car, 1779 01:12:59,390 --> 01:13:01,190 they let you test drive in the car. 1780 01:13:01,190 --> 01:13:02,030 And you sit in it. 1781 01:13:02,030 --> 01:13:03,620 And it feels like yours. 1782 01:13:03,620 --> 01:13:05,387 Or when you try to buy a house, then 1783 01:13:05,387 --> 01:13:07,970 people would say, oh, you know, this will be your living room. 1784 01:13:07,970 --> 01:13:09,887 And this is where your baby is going to sleep. 1785 01:13:09,887 --> 01:13:12,590 And there's lots of sort of ways in which people 1786 01:13:12,590 --> 01:13:14,870 make sort of something feel yours and really try 1787 01:13:14,870 --> 01:13:19,940 to sort of get the endowment effect to kick in. 1788 01:13:19,940 --> 01:13:21,800 If you were to work in an insurance firm, 1789 01:13:21,800 --> 01:13:24,560 what would you do, somebody who offers insurance 1790 01:13:24,560 --> 01:13:28,070 in one way or the other or products 1791 01:13:28,070 --> 01:13:29,720 that offer insurance in some ways? 1792 01:13:34,650 --> 01:13:35,193 Yes. 1793 01:13:35,193 --> 01:13:37,860 AUDIENCE: We talked about this a little bit in a previous class. 1794 01:13:37,860 --> 01:13:39,930 But this is why, I think, companies 1795 01:13:39,930 --> 01:13:43,080 will sell things like Apple Care or operative warranties. 1796 01:13:43,080 --> 01:13:45,360 Because they know they'll make money off of it 1797 01:13:45,360 --> 01:13:46,868 because people tend to over-insure. 1798 01:13:46,868 --> 01:13:47,910 FRANK SCHILBACH: Exactly. 1799 01:13:47,910 --> 01:13:50,460 There's lots of different products 1800 01:13:50,460 --> 01:13:52,470 where there's extended warranties and all sorts 1801 01:13:52,470 --> 01:13:55,740 of things, like Apple care, et cetera, where people 1802 01:13:55,740 --> 01:13:59,880 are very risk averse, what it looks like, presumably loss 1803 01:13:59,880 --> 01:14:02,760 averse where, in fact, actually the claim 1804 01:14:02,760 --> 01:14:04,230 rate tends to be very low. 1805 01:14:04,230 --> 01:14:06,720 So you can make a lot of money with this by saying, yes, 1806 01:14:06,720 --> 01:14:08,520 I'm going to exchange it and this and that. 1807 01:14:08,520 --> 01:14:10,530 Because, essentially, it doesn't happen that 1808 01:14:10,530 --> 01:14:13,477 often at the end of the day even if there's 1809 01:14:13,477 --> 01:14:15,060 moral hazard or other issues of people 1810 01:14:15,060 --> 01:14:19,600 not treating their stuff that well once they have insurance. 1811 01:14:19,600 --> 01:14:26,070 What about wage setting, like when 1812 01:14:26,070 --> 01:14:27,750 you set your employees' wages? 1813 01:14:30,710 --> 01:14:31,210 Yeah. 1814 01:14:31,210 --> 01:14:34,440 AUDIENCE: Could that be linked to mass unemployment 1815 01:14:34,440 --> 01:14:37,720 in recessions because you know that, if you lower the wage, 1816 01:14:37,720 --> 01:14:39,590 then morale will go down a lot? 1817 01:14:39,590 --> 01:14:43,472 And you can actually decide just to kick them out? 1818 01:14:43,472 --> 01:14:44,430 FRANK SCHILBACH: Right. 1819 01:14:44,430 --> 01:14:44,930 Exactly. 1820 01:14:44,930 --> 01:14:53,040 So there is a large literature on wage stickiness, 1821 01:14:53,040 --> 01:14:57,990 essentially exactly as you say, where people are extremely 1822 01:14:57,990 --> 01:14:59,910 reluctant to lower wages. 1823 01:14:59,910 --> 01:15:02,250 Companies are very reluctant to lower wages. 1824 01:15:02,250 --> 01:15:05,310 Because, essentially, workers are really unhappy. 1825 01:15:05,310 --> 01:15:08,192 And these are often nominal wages or real wages. 1826 01:15:08,192 --> 01:15:09,650 It doesn't really matter that much, 1827 01:15:09,650 --> 01:15:11,130 but usually it's nominal wages. 1828 01:15:11,130 --> 01:15:16,080 People really, really dislike nominal wage reductions. 1829 01:15:16,080 --> 01:15:21,270 And so, now, in some times when companies would actually 1830 01:15:21,270 --> 01:15:24,840 need to lower wages and sort of to be able to keep workers 1831 01:15:24,840 --> 01:15:27,990 not to make losses, companies might rather sort of fire 1832 01:15:27,990 --> 01:15:31,830 some workers rather than sort of lowering 1833 01:15:31,830 --> 01:15:33,090 the wages for everybody. 1834 01:15:33,090 --> 01:15:36,492 Because, essentially, the remaining workers, 1835 01:15:36,492 --> 01:15:37,950 once you lower wages for everybody, 1836 01:15:37,950 --> 01:15:39,090 everybody would be unhappy. 1837 01:15:39,090 --> 01:15:41,760 If you just fire one worker, everybody else 1838 01:15:41,760 --> 01:15:45,960 will be less unhappy than about their wage reductions. 1839 01:15:45,960 --> 01:15:48,750 Similarly, firms are sort of reluctant to hire people 1840 01:15:48,750 --> 01:15:51,510 at lower wages, if there's other people who make higher wages, 1841 01:15:51,510 --> 01:15:54,155 because people really dislike weight dispersion. 1842 01:15:54,155 --> 01:15:55,530 So essentially, overall, you want 1843 01:15:55,530 --> 01:15:59,280 to avoid wage cuts as much as possible. 1844 01:15:59,280 --> 01:16:01,190 And that leads to essentially then sort 1845 01:16:01,190 --> 01:16:03,247 of macroeconomic inefficiencies. 1846 01:16:03,247 --> 01:16:04,830 And people have argued, in particular, 1847 01:16:04,830 --> 01:16:10,410 it leads to unemployment because, essentially, wages 1848 01:16:10,410 --> 01:16:13,410 are not going down as much as they should in recessions. 1849 01:16:13,410 --> 01:16:14,460 And that's bad for firms. 1850 01:16:14,460 --> 01:16:16,200 And, therefore, they hire fewer workers 1851 01:16:16,200 --> 01:16:18,983 or retain fewer workers overall. 1852 01:16:18,983 --> 01:16:20,400 I think I mentioned, we mentioned, 1853 01:16:20,400 --> 01:16:23,110 all of those kinds of things. 1854 01:16:23,110 --> 01:16:26,833 So now, that's sort of what firms are doing. 1855 01:16:26,833 --> 01:16:28,500 Now, another thing you might think about 1856 01:16:28,500 --> 01:16:31,472 is what are you going to actually do in your real lives. 1857 01:16:31,472 --> 01:16:33,930 I think there's many different things that you can actually 1858 01:16:33,930 --> 01:16:37,093 think about is the framing of situations, for example, can 1859 01:16:37,093 --> 01:16:38,010 make a big difference. 1860 01:16:38,010 --> 01:16:39,720 If you present something to your friends, 1861 01:16:39,720 --> 01:16:43,500 different options, whether you present that as gains or losses 1862 01:16:43,500 --> 01:16:45,930 makes a big difference potentially. 1863 01:16:45,930 --> 01:16:48,540 Managing people's expectations is really important. 1864 01:16:48,540 --> 01:16:50,610 If there's some big goal that they could reach 1865 01:16:50,610 --> 01:16:52,380 or some lower goal they could reach, 1866 01:16:52,380 --> 01:16:54,030 if you sort of oversell the high chance 1867 01:16:54,030 --> 01:16:56,048 of reaching some big goal, they might 1868 01:16:56,048 --> 01:16:58,090 reach the other goal that's actually pretty good, 1869 01:16:58,090 --> 01:17:01,020 might feel really disappointed about that, 1870 01:17:01,020 --> 01:17:03,310 be it in job search or the like. 1871 01:17:03,310 --> 01:17:04,810 So managing people's expectations, 1872 01:17:04,810 --> 01:17:07,810 including your own expectations, seems really important. 1873 01:17:07,810 --> 01:17:10,080 There's something about aggregating losses and gains, 1874 01:17:10,080 --> 01:17:12,960 which essentially is to say, since people seem 1875 01:17:12,960 --> 01:17:18,810 to be risk averse over gains-- 1876 01:17:18,810 --> 01:17:22,170 so since value function is concave over gains and convex 1877 01:17:22,170 --> 01:17:25,020 over losses, what you should do is 1878 01:17:25,020 --> 01:17:29,790 potentially be really careful about when you give people 1879 01:17:29,790 --> 01:17:34,320 a positive or negative feedback or bonuses and so on. 1880 01:17:34,320 --> 01:17:37,950 You might want to sort of be careful whether you 1881 01:17:37,950 --> 01:17:39,600 aggregate the losses or-- 1882 01:17:39,600 --> 01:17:43,050 so aggregating losses makes sense because essentially it's 1883 01:17:43,050 --> 01:17:45,480 convex in the loss domain, as opposed to you 1884 01:17:45,480 --> 01:17:48,013 want to give small increments of gains overall. 1885 01:17:48,013 --> 01:17:49,680 Now, one thing that I do want to mention 1886 01:17:49,680 --> 01:17:51,480 is you want to be kind of very careful 1887 01:17:51,480 --> 01:17:53,100 with loss-framed incentives. 1888 01:17:53,100 --> 01:17:57,240 There's a company who was trying to do this. 1889 01:17:57,240 --> 01:17:59,010 These are car manufacturers who were 1890 01:17:59,010 --> 01:18:02,910 trying to give essentially their car dealers incentives, 1891 01:18:02,910 --> 01:18:09,802 sort of targets for their sales of their cars. 1892 01:18:09,802 --> 01:18:11,760 What essentially happened in the end of the day 1893 01:18:11,760 --> 01:18:15,540 is there was a bunch of multitasking. 1894 01:18:15,540 --> 01:18:17,280 The company or the car salespeople 1895 01:18:17,280 --> 01:18:20,400 were essentially selling certain cars, but then not others 1896 01:18:20,400 --> 01:18:21,900 and were essentially multitasking 1897 01:18:21,900 --> 01:18:24,970 and then sort of reverting, sort of reallocating efforts 1898 01:18:24,970 --> 01:18:27,570 to one thing versus the other, which then 1899 01:18:27,570 --> 01:18:28,950 seemed like a really good idea. 1900 01:18:28,950 --> 01:18:31,858 There was recently a valuation that sort of showed that that 1901 01:18:31,858 --> 01:18:33,150 was actually a pretty bad idea. 1902 01:18:33,150 --> 01:18:35,067 And the company would have lost a lot of money 1903 01:18:35,067 --> 01:18:37,545 overall if this had been scaled. 1904 01:18:37,545 --> 01:18:39,420 We're going to have this, the Deal or No Deal 1905 01:18:39,420 --> 01:18:40,980 and this specific paper in recitation 1906 01:18:40,980 --> 01:18:42,540 to tell you in more detail because I 1907 01:18:42,540 --> 01:18:46,620 want to move towards social preferences next time. 1908 01:18:46,620 --> 01:18:50,010 So as I said, next time we talk about social preferences. 1909 01:18:50,010 --> 01:18:50,790 Bring your laptop. 1910 01:18:50,790 --> 01:18:52,415 And I'll send you further instructions. 1911 01:18:52,415 --> 01:18:54,020 Thank you.