SIO379: Does Which College You Go To Really Matter?

Transcript

This transcript was generated automatically and may contain errors — the audio is the record.

0:00:15 Thomas: Hello and welcome to Serious Inquiries Only. This is Episode 379. I'm your host, Thomas Smith. Thank you so much for joining me. Today we're going to be talking about college and whether your choice of college makes any difference in your life. This up because of a Dear Old Dads episode, actually somewhat recent one, we were talking about college, and should we send our kids to college, how much should we worry about it, all that stuff, and Tom claimed that studies showed which college you go to doesn't really make a difference. There's some more nuance there, and my guest will get into it, but that launched my guest today, Dr. Elizabeth Deitch, who has a PhD in organizational organizational psychology, on a bit of a massive research deep dive as she kind of wondered if that was true. She wanted to check all available cities and kind see what this data, the science, was. So does college selection make a big difference in your job, in your life, that sort of thing?

0:01:09 Thomas: Beth Deitch is a little bit like me in that once she goes in on something, she goes a million percent. And so this is actually a two-parter. Beth did so much research, she had tons of studies to go through that this, and it actually divides somewhat neatly, more than I would have thought, into a two-parter. And it was, she did a ton of work and we recorded for over two hours. So there's plenty to go. I would, to actually, worry about giving this to you in any less than two parts, because it's impossible to retain that much information. So part one is going to be about that original claim. "Oh, it makes no difference which school you go to." And as with a lot of this stuff, it turns out that's kind of based on like one study that's old, and that's cited, you know, in pretty much all this.

0:02:00 Thomas: And, you know, there's some complications there. Will it hold up? Will it not? I'm going to leave you in suspense. She'll take us through it, but that's going to be kind of the first part. And then part two goes more into what Beth found subsequently. So, like, newer stuff, slightly different questions being answered. So this two -part series will contain so much on shouldyoucare, where your kid goes to college, how much does it matter, all is het just a crapshoot and it kind of doesn't matter, all these questions and related ones in the next two parts. There's a lot here, it was a ton of fun, and I can't wait to get it to you, and I've completed both parts already, so if you'd like to go to part two, go to patreon.com/seriouspod. And in edition to enjoying no ads, totally ad -free free episodes, and the Seriously Awful Movies, which will be Memento this month.

0:02:50 Thomas: Can't wait to do that. In addition to all that, you will get part two whenever you want it, because I'm going to post these right away, essentially back to back. Great reasons to join patreon.com/seriouspod. you'll consider it. And to my supporters who have, all right. With that said, let's get to part one with Dr. Elizabeth Deitch on how much college you go to really matters just I'm joined by Dr. Beth Deitch, long -time friend of the show. Good to talk to you. It's been too long. How are you doing?

0:03:19 Beth: I'm doing great, how are you? Oh, excellent

0:03:21 Thomas: I'm doing well. I, of course, always remember going down to NOLA, going down to New Orleans for that talk.

0:03:28 Thomas: We still have some of the stuff that we bought Phoebe. I think we got like a... we went to the aquarium, I want to say, and got like an albino alligator thing we still have. It was super fun.

0:03:28 Beth: Yeah uh -huh, yeah we have those at the aquarium, we do have albino gators, yeah it's a million degrees here right now, yeah.

0:03:37 Thomas: Yeah, yeah, yeah. So so much fun. So, God. Yeah. It's a million degrees. As they say, it's the dry heat here, but it is, you know, like an oven. So it's still 110.

0:03:47 Beth: No, it's the wet heat here, so, so, yeah,

0:03:51 Thomas: So the dryness doesn't, uh... doesn't help too much.

0:03:53 Beth: Yeah, we're only at 95, 100, uh,

0:03:55 Thomas: Yeah, which probably feels like 120, I'm sure. Um, so you contacted me after the Dear Old Dads episode where, uh Tom made some claims kind of about college outcomes and, you know, whether or not it matters what college you go to, which is, of course, over there, we're parents, we're dads, we're thinking about our kids and education and all that's certainly an important topic to a lot of parents is how, you know, how much should I worry about trying to get them into the best colleges and do all that prep and SAT, blah, blah. And you emailed me wanting to maybe look into that, which I think is great because I would love to know kind of the more, you know, we 'Re not scientists over there. We don't have credentials over there. So you were kind enough to take a look at that. So first off, if you'd like to give any more introduction to the audience, feel free. And then, you know, maybe take us through what you found.

0:03:58 Beth: -uh, right. Right, okay.

0:04:41 Beth: Well, I have a... a PhD in Industrial Organizational Psychology, which is basically like psychology at work and in organizations. It's a lot of social psychology, mostly. Yeah, I was really interested when I heard Tom saying that there is no difference five years out from graduation in any measurable outcome, depending on what school you went to. That was verbatim. I went back and re -listened.

0:05:02 Beth: That's a little, yeah, And that's a little over much, much.

0:05:01 Thomas: Oh, yeah. I was going to say that's pretty strong. Yeah. Yeah.

0:05:07 Beth: Um, but he did kind of, you got talking more and you finally understood the concept of control variables, kind of get around to the question, which is a very different question, of does it matter if you go to one school versus another school, that's like public versus private, but About the same level, as opposed to Ivy League versus, you know, community college. But I went to look at like where he was probably getting this stuff from, just did the Google search, came up with with some articles in around 2012, 2014, that were all saying, like, it doesn't matter where you go to college. Like there was one in Time, there's one in The Atlantic. And they're all referring to these papers by Stacey Dale and Paul Krueger. And if the name Paul Krueger sounds familiar, that's because he was President Obama's Assistant Secretary for the Treasury of Economic Policy and then chair of his Council on Economic Affairs. So he's a big deal economist.

0:05:21 Thomas: Mm-hmm. Okay.

0:06:02 Beth: Yeah. So this is an economics paper, which is a little far afield from, it was interesting to read. They have some different conventions than they do in psychology. I had to figure significance levels myself with math and that was annoying. Yes. They mentioned them in the text and I'm like, but you're, they give me the information I could figure it from, but apparently they don't just put little stars on things like we do in psychology. Okay. So Dale and Kruger, they did these two papers. First one was published in 2002, and then they did a follow-up in 2014. And they both are being based on this data set that comes from, it's called the College and Beyond Survey. And College and Beyond has linked data from the applications of people who went to 34 different colleges that four public universities, four historically black colleges and universities, and then 11 liberal arts colleges and 15 private universities. One thing that's very important to note, though, is that these are all pretty elite schools.

0:06:13 Thomas: Really? Wow. Yeah.

0:07:04 Beth: And in fact, in the first paper, they decided not to use the HBCUs. I'm not exactly sure why. They were just like, nah, we didn't want that data.

0:07:14 Thomas: Well, that's already pretty fucking important, right?

0:07:18 Beth: Right, well, they did bring some of that in in the second paper, but the first one, they just left those out. So the lowest ranked school in there, I think, is Penn State. Yeah, I mean, they're like high, higher, and highest.

0:07:21 Thomas: Okay. Wow. So you said this started, what, 2002 was the first one, did you say?

0:07:34 Beth: Yeah, but they're actually looking at people who went to school in like 1976 and following them. That's another thing Tom said five years out, but this is going way, way past five years.

0:07:41 Thomas: Oh, geez. Okay. Yeah. Well, yeah. Who knows if he saw another study or something.

0:07:49 Beth: Which is actually good to, you know, to go and see further. But it does mean that some of the stuff that they're asking about is retrospective. But they did link to their actual transcripts from college and actual SAT scores and school SAT scores. And when I'm reading this, I'm like, FERPA was a thing there, which is the Family and Educational Rights or Privacy Act, where they can't just give out your academic data. So I'm figuring they must have had this de -identified in some way where everyone just gets assessed by a number or something.

0:07:52 Thomas: Yeah. Sure.

0:08:25 Beth: But, well, it was voluntary to do the survey.

0:08:25 Thomas: Or it wasn't like voluntary. They got, hmm.

0:08:29 Beth: And they did actually have pretty decent follow-up rates on that. They did the survey in 1996, and they first mailed it, but then people who didn't respond to two different mailings were surveyed over the phone. And they ended up getting a response rate of about 80%, which is really good, actually.

0:08:49 Thomas: Yeah. No kidding.

0:08:50 Beth: Although something that they don't really address is that those 20% of people may be different than the 80% of people who did, in fact, respond.

0:08:58 Thomas: Yeah. Yeah. There's got to be a selection effect. People who want to talk about like how well it went for them, maybe, or their lives are are going well, or there's a bunch of reasons, right?

0:09:02 Beth: Right, right. Right. And one of the things that's really important for this data set is that they said that questionnaire asked, in rough order of preference, please list the other schools you seriously considered. Because the idea of where you applied and not just where you went is going to be a really important feature in their model.

0:09:22 Thomas: But I want to step back just a sec to say right away, just with this first study we're looking at, the question of, hey, what was the best college to have gone to in the 70s, is quite a bit different than what I took Tom to be talking about. Not, again, this is not a critique of Tom when he's not here. You you took away from that episode any information like that, I want To make sure, you know, we keep track of what we actually are, you know, proving here or maybe not proving, but, getting you information on. So, so far, we're looking at historical data. We've taken out, you now, any, it's just elite colleges. Do you get a sense of the goals that they had in mind when they were researching this? I mean, it feels like it's very elite in a certain way, like it is trying to answer questions for maybe a more elite group of, to use that shitty word, like of privileged people and figure out how they did.

0:09:36 Beth: Right.

0:10:09 Beth: Right? And this was an existing data set. And actually, after we go through these two main Dale and Kruger papers that are what what everyone keeps referring to in the popular press. I did then go look for more recent things, and there are some things that follow up. And pretty much that's what everyone is doing, is there are these huge data sets out there. And the College and Beyond survey was done by an organization called Mathematica Policy Research. Asked a whole lot of questions, and then you can buy their data set and use it to do your own secondary analysis.

0:10:13 Thomas: Hmm. Hmm.

0:10:41 Beth: They do try and get a little bit of a more representative sample, something that's not quite so elite, by looking at the National Longitudinal Survey of the High School Class of 1972, which is one done by the Department of Education. There's one that some of these studies use called the High School and Beyond Study, which was by the National Center for Education Statistics. They also did a National Education Longitudinous Study. So there's these, some of them are government agencies, some of them are like educational policy research organizations that have these great big data sets.

They have decided we're going to survey everyone who went to college, you know, in 1976. Now we're in 1996, it's 20 years later, we're gonna follow up and see where all of these people went and how they've done, you know, like if I had an interesting question that needed the kind of data that's in one of these data sets, I could contact them and usually for a minimal fee get the data and try my hypotheses on it. It's like secondary data research. So they did not collect the data themselves. Although interestingly, Stacey Dale now works for Mathematica, which she did not when these were published, I don't think. I think she was still at Princeton with Krueger. I'm guessing she was one of his graduate students would be my guess. But yeah, so they didn't collect this data fresh. They obtained the data from other places that had

0:11:41 Thomas: Right? Yeah. So maybe Maybe it was a case of just using whatever they could find. Like, okay.

0:12:09 Beth: It. Right. Well, and one of the things that they really liked about this data set for their model was that it had asked them where else they applied. Because this is the thing that's actually a really interesting thing that Dale and Kruger set out to investigate, but that none of the popular press things really seem to grasp very well. I mean, it's complicated. It's a 50-page paper full of statistical equations. I don't fault, you know, The Atlantic for not having picked through all of it. But their main point was that they were saying there was this literature showing that students that attend more elite colleges earn more later. And by the way, that's pretty much the outcome we're looking at, how much money you make later, which pin in that.

0:12:50 Thomas: You did say it was an economics -y thingy rather than a... So, sure. Fair enough.

0:12:53 Beth: Yes, this is an economics paper. Yeah, this was published in the Quarterly Journal of Economics. But they say they point out the problems of this other research that is usually in a fairly short short time frame, more like the five years Tom was referring to, but these people are looking at 20 years later. And they do always control for what we call observable characteristics of the students, which include things like your student's own SAT score, your parental income, parental education, race, gender, high school rank, whether you were an athlete, things like that. And so it's always those things being equal, you know, so unless we're actually looking at those things specifically, that is controlled for, because who are just better off are going to do better in life, and if you want to see the effect of college you've got to hold that constant, they have parents income, they apparently they apparently have that, yeah, they have parental, parental income, I'm sure it's a range, and parents' education.

0:13:32 Thomas: Right, sure, right.

0:13:45 Thomas: Well, specifically, I would think like zip code would be pretty important, right? I mean, oh, that's better. Yeah, that is probably better. Yeah, yeah, yeah.

0:13:59 Beth: That's why these data sets are awesome. They have all sorts of information. Really fantastic that you can get a hold of these then, because there's actually a couple of other more recent papers that use the same data set to do some follow-up.

0:14:00 Thomas: Yeah, now when you say same data set, is it like the same survey but done later years or no, literally the same data from the same years.

0:14:20 Beth: Literally the same data from the same College and Beyond survey, because one of the things that Dale and Kruger do is they restrict their sample only to people who are working full-time in 1995. And so one of the ones that uses the same data is one that follows up looking at effects due to gender, according to different genders. And women, one of the things that really affects their outcomes in life is how much they work and when they work, and whether they take breaks from their work life. And when you go only everyone who worked full - time this year is included in our study, you may be missing a lot of the, yeah, that's a different, totally a different outcome. And that is one of my complaints about some of this research is that they are very focused on earnings. How much do you make?

0:14:21 Thomas: Yeah. Okay. Yeah. Yeah. Yeah. Aren't you also missing job placement? Like, let Let me make sure I said the right thing. Like if there was a school where, oh, actually, you know, only half the people ended up with full-time jobs versus this school, like 75% of people ended up with full-time jobs. Even if they made the same average amount, would this survey say, oh those two are equal. Whereas, you know, you or I might say, yeah, but you have a way better chance, apparently, of getting a job if you go to this school versus this school.

0:15:30 Beth: Yeah. And that's not something that was examined in this paper. That is something in some of the follow-up things that I found.

0:15:33 Thomas: Okay. Gotcha. So for this one, it's kind of a gap. It's like missing in this one. But okay.

0:15:41 Beth: Right. I did follow all sorts of rabbit trails from this. And part of the thing is, I think there's a sort of misunderstanding of what they were wanting to do here.

0:15:44 Thomas: Mm-hmm. Mm -Mm-mm. Mm -hm.

0:15:50 Beth: Because they wanted to point out that when we look at the outcomes of, and usually in earnings, of people according to the different colleges they went to, we can control for these things that we can observe and measure, like your own SAT, your parents' income, that sort of thing. But selection committees make decisions based also also on things that we as researchers coming later cannot observe. You know, they get recommendations, they get essays, they give community service, they, you know, maybe work experience, all of that kind of stuff that may show characteristics like motivation, ambition, your social skills, your organizational skills. And those are the things when we're looking at, well, we have your SAT score, we aren't seeing all of this other stuff that can, in fact, figure into whether they are admitted and whether they decide to go to a college. They are the

0:16:02 Thomas: Mm -m.

0:16:42 Thomas: Right.

0:16:42 Beth: Unobserved characteristics of the students.

0:16:45 Thomas: But for our purposes of which school did you go and did it make a difference, I feel like we can kind of set those equal, right?

0:16:51 Beth: Now, this is the whole point of what they wanted to do, was they wanted to see if adding in this idea of things we can't observe, and I'll get to how they've decided to infer things we can't observe in a minute, does that change the observed relationship between college you go to and later earnings, which a lot of the earlier research was showing better college, more earnings, even holding those things that we can observe, like income and race and gender and stuff, constant. Um, they said, yeah, okay, you see a difference there, but maybe the difference isn't because of the school they went, maybe the difference is because of the kind of student they are, maybe it's because these are people who are more ambitious, or these, these are people who have better social skills.

0:17:11 Thomas: Oh, I see. Okay. Oh, okay. I think I understand you. Yeah, I misunderstood. So it's saying, we could have two students. I'm just trying to keep it in mind for everybody who's not as, you know, doesn't do this stuff like you. So we have student A, student B, one went to one school, one went to the other. We're kind of trying to just loosely speaking, we're trying to know like, oh, how much difference does the school make setting everything equal?

0:17:51 Beth: Yeah.

0:17:51 Thomas: So now you're saying if in some of these papers, they've tried to account for everything, but if they didn't account for like, well, Well, there may be reasons that this person got into the school that would set them on a good life trajectory, hard work, work ethic, whatever it may be that we can't measure. We couldn't we couldn't for sure say like, yep, it's school A versus school B rather than the kind of person who got into school A is going to do better regardless.

0:17:52 Beth: Right? Uh -huh. Exactly. And also, they look at the kind of person who maybe got into school A and B and chose A versus the kind person who got into school B and A and A. A and chose B.

0:18:22 Thomas: Interesting. Yeah. Yeah, which that could make sense, too. Too. I know, I mean, I know it's, it's probably different, but like, I remember back when we were doing, you know, in high school and we were doing college stuff and there was the, there are a lot of people who are like, well, I got in this school, got in the school, but you know this one is like UC Santa Cruz and I want to go just smoke weed the whole time and, you Know, to say nothing bad about the school but a lot of, you, know, there were schools that were considered like, yeah, I kind of want to have a good time in college, which, which is interesting. That would say something about the person perhaps and like their, their, uh, their goals in life, not making any value judgments, but just saying like that, that might give you information. Uh, so I see what you're saying there.

0:18:27 Beth: Yeah. Yeah. Right. Right? Yes, exactly. That is exactly what they were trying to get at. They say, you know, we have these things that look at the effect of school, and they control for all these student characteristics that we can measure, that we have numbers on, like their parents' income, like the students' own SAT scores.

0:19:01 Thomas: Cool. But number of bowls they smoke per day.

0:19:14 Beth: Yes. Yes, not characteristics that maybe we can't observe that may have an effect. And so that was their main goal in doing the analyses they did.

0:19:27 Thomas: When you say they, I've lost track now of which level of, so you're saying there's kind of earlier research we're not going to go into that didn't do this as much. And they're like, "All right, let's actually do this as much, like, to a greater extent."

0:19:29 Beth: Oh, Dale and Kruger. Yeah, yeah. And they said, oh, going to an elite school associated with earning more. But Dale and Krieger are like, wait a minute, wait a minute. Maybe there's things you aren't looking at that make a difference with these people that isn't in fact the school they went to, but some of these other characteristics instead.

0:19:38 Thomas: Right.

0:19:51 Thomas: Gotcha, right.

0:19:53 Beth: They talk about the observables and unobservables, and they're interested in the effect that these unobsergables might have. And they consider that your school choice has basically a three-step model. The student decides where to apply, and then the colleges decide, admit or reject decisions, and then the student decides where to attend. And All of those things could be affected by stuff that we can't observe in our numbers, in our data set, because, again, remember, we're looking at existing data, we're taking an existing data set, so If there's nothing about ambition in there, there's just nothing about ambition. It's not like they could just give them a survey about their ambition or something.

0:20:14 Thomas: Yeah. Right. I will Flag, I don't know if this matters or whatever, but just flagging, I, uh, just in case, I know a big question for me was, "Oh, can I afford to go to this fucking school?" And That That feels like Something that might be hard to capture if that was the decision.

0:20:34 Beth: Yes. Yes. Indeed. Yeah. That, again, go, go, remember, 1976. So

0:20:51 Thomas: So All of them were five Dollars, or what. But, oh, okay. Yeah, yeah, yeah. I got you.

0:20:53 Beth: Yeah. Um, it was, it is an issue, but it is not as much of an issue as it is in more Recent Years. The

0:21:02 Thomas: It's just ballooned the cost and stuff.

0:21:03 Beth: Uh Yeah. Yeah. Yeah, and there is, uh, some stuff on that. I did follow that path Too, um

0:21:03 Thomas: Yeah, sure. We're going to do a five -hour series. Yeah.

0:21:10 Beth: If you had given me another month, I would have, I would've followed more threads, you know, because I did, at least, because mostly I, I have academic access to journals and stuff. And so I can get full text Online. But I did make myself stop when I would actually have had to go to the library and get a book or interlibrary loan it.

0:21:21 Thomas: Right. Yeah.

0:21:30 Beth: I was like, okay, stop. Stop now. Which actually there's getting more information on this College and Beyond survey went to a book. There's a book about it, of how precisely they collected it and all of that. So all all of those three steps are are affected by or can be affected by things we can't observe. The student deciding where they apply, the college making their decision, and then the student deciding which of the colleges that accepted them they want to go to, which could also have to do with whether you get financial aid or intentions. And so they look at first the just basic model of let's see if college makes a difference.

Holding constant the student's own SAT score, their sex, their race, whether they are in the top 10 percent of their high school, whether they are an athlete in high school. I think. When they do that, when they hold those things constant and say, does going to a school of higher quality, and I'll get to how that's measured in a minute, relate to you having more income later on? And just looking at those things, it does. What they're using as the measure of school quality, because of course, all of these are really good schools, is the average SAT score of incoming freshman class.

0:21:39 Thomas: Wow. Sure. Right. Yeah, Yeah. Sure. Right. Okay.

0:22:50 Beth: So the idea being that a school that has a higher average SAT score coming in is more selective, more elite, and that's their way of determining school quality in this case. Know, no surprise, being female means you earn less, being black means you earn less. Being Asian means you earned a little bit more. Okay, that's the basic model, just totally unrestricted on the observables, just sort of replicates what other people have done.

Then they try and get at these unobservables in a couple different ways that are based on where students apply. It's based on the assumption that students are knowledgeable about their own academic potential. They know, like, sort of how ambitious they are, how much they might fit with a particular school, and that they show us that by showing us where they applied, all the places they applied. Applied that their College application behavior can be used to infer some of these unobservable characteristics. So they measure that by the number of schools people apply to and the average SAT of the schools they applied to. So not just where they got in, but where they applied. And they're calling this the self-revelation model. Then went even a step further to to try and take that application behavior and see if they could make groups of students who were matched in that case, who applied to the same colleges, received

0:23:37 Thomas: Yeah. Oh, yeah!

0:24:09 Beth: The same admission decisions, but went different places.

0:24:09 Thomas: Yeah. Trying to do some like twin studies, twinsies.

0:24:16 Beth: Yeah, yeah, basically, yeah. Did near matches where they just made them similarly situated schools, that took their data set from the original 14,000 down to 6,335 people that they could do the similar matches, exact matches of exact same schools and decisions. That took their data set down to 2,330. So, you know, each time you do these things, you have fewer people that you can actually use. Then they looked at those things and see if adding those in made a difference to the effect of school quality, school SAT. In fact, once you added in the self -revelation model, you added in how many schools they applied to and the average SAT of the schools they replied to, the selectivity of the school they went to actually goes to zero effect.

0:25:07 Thomas: Wow.

0:25:08 Beth: It no longer has an effect on the earnings.

0:25:11 Thomas: Interesting.

0:25:11 Beth: Yeah. And so they're saying really, it's probably something about these students, you know, like if you're good enough to get into to Harvard. Even if you didn't go to Harvard, you're probably going to earn like a Harvard person. All else being equal.

0:25:25 Thomas: Think that's a creative and probably pretty good way, it seems to me, to get at some of those intangibles or whatever, those unobservables, because it did really matter thinking back again to when I was in this process, there was a real difference between the people who are like, all right, got my schools. Here's my top schools. There's my every school. Here'S my reach school. There'S my safe school. And then like, you know, me who was like, oh, fucking, I don't know how I'll apply to a couple of schools. I don't know. Cause I, I didn't know what to do.

0:25:49 Beth: Yeah, yeah. Well, actually, students that apply to more than one school is like, I think, less than half. I think a lot of people just kind of apply to their state school or whatever that they think they can get in. And, you know, I mean, we have a thing, a program where like, if you're in the top 10 % of your class, you get a grant to go to various state colleges. And so people are like, well, I'm going to go where my top's grants is usable. You know, and that's where they apply and that is where they go.

0:25:55 Thomas: Right. Right, right. Yeah. Yeah. Right. But in trying to set things equal, we're still looking at like, if someone got into Harvard or whatever, but one person chose to go, the other person chose, they both got in, but they chose to get into different schools. It's you're looking at those people and you're saying, well, one person applied to Harvard and every single other, you know, Ivy league school or something, you know, and then this other person, maybe they just applied lied to Harvard kind of, I don't know, maybe not on a whim is probably not accurate, but like less, maybe less seriously in some way.

0:26:40 Beth: I applied to Harvard Law School, got in and turned them down. So, apparently there are assholes there and I didn't want to go. So, I went to Stanford. I didn't finish, but I did half of law school.

0:26:43 Thomas: There you go, and so glad you didn't learn your ethics from there, we'll just say. And so, yeah, so that's kind of saying something meaningful, and this paper now is controlling for for that. And, and all of a sudden, or trying, yeah. And all of a sudden the difference in income is going away.

0:26:54 Beth: Yeah. Yeah. Are trying to. Yeah. Yeah. The effect of how selective the school you went to, actually went to goes away. First of all, the self -revelation model just uses it as a variable, as a continuous variable of what was the average SAT score of the schools you applied to. And then what you actually went to, does that add anything above and beyond that? And the answer is no.

0:27:10 Thomas: Yeah. Gotcha.

0:27:26 Thomas: Hmm.

0:27:27 Beth: Then they also did this for the matched applicants group, which is a smaller group, but more specifically looking at people who got the exact same results, maybe went different places, versus again near zero. There is this really weird little effect that is in fact significant, that the when they get down to the exact match data set of a little over 2,000 people, it shows a negative effect of of average SAT. In other words, going to the higher school was negative, like, you were had a little less earnings. They don't talk about it in the text at all. I could not find anything. They were like, oh, interesting, moving on. Um, because you know, there are other things, didn't took it to zero, and that like didn't show up in any of the other models.

0:27:58 Thomas: Interesting.

0:28:10 Beth: But it was just like a yeah, I thought that was weird and I was me.

0:28:10 Thomas: That is really weird. I'm not even sure I could come up with a theory for that just

0:28:16 Beth: Either me either. And why only that, why only the reduced data? It may it may just be a fluke, you know, the idea of when we set uh significance level to like p equals 0.05, that's saying we're accepting a five percent chance, or or less, that these results are due to merely random chance, and not actually in effect in the larger population. So there is some, it could be random chance.

0:28:20 Thomas: Be an artifact. Yeah, sure.

0:28:39 Thomas: Yeah.

0:28:39 Beth: And maybe that was because it was just, it was just so weird. Again, I had to figure my significance rates on that. But P came out to 0.003, which is quite significant.

0:28:49 Thomas: It's a pretty significant coincidence. If it is a coincidence, that's interesting.

0:28:53 Beth: Yeah, although I think maybe when they do some later models that add in things like occupation and stuff that may go away. So their basic idea is like, hey, look, it's not really the college you go to. Also, I do want to say it's go -to. It is not graduate from. These are not graduates per se. This is who went there.

0:29:09 Thomas: Interesting. I didn't know that.

0:29:11 Beth: And that's something that's often misrepresented in the popular accounts of this. They're like, oh, the grads from this school and the grads from that school. And it's like, uh-uh, no. So their idea is that when people are looking at these effects and they're only basing their control variables on the things that we can see, and then assuming people are otherwise all the same, they are mistaken. That in fact, there are other unobservable variables of applicants that we are not seeing in just their numbers, and that we kan infer that from their application behavior. And so then once you do that, the effect of school quality as measured by average SAT goes to zero.

0:29:15 Thomas: Yeah. Right. One more reminder only for these top whatever, you know, down to Penn State or whatever it was.

0:29:56 Beth: Right. Right. Yeah. So yeah, so they do have some variations that they kind of attempt to address the issues. Do control for they say, maybe your selectivity is related to occupation. So if you're just being in higher paid occupations, but they control for occupation. Yeah, and then actually, they stop doing that tiny sample of exact matches.

0:30:08 Thomas: Sure.

0:30:21 Beth: And effect. So it just kind of goes away and later that whole subsample just goes away. I don't know. It's weird. Then they try using Barron's rankings for their selectivity measure instead of just average SAT scores. And Barron, they assign four -year colleges to selectivity categories based on their admissions rate, the average characteristics of their freshman cohort, cohort, which does include their SAT scores, but also things like cumulative high school GPA, high school class rank, things like that. So they tried using that as their quality measure instead of just average SAT, still no effect of quality.

0:30:59 Thomas: Actually, now that I think about it, average SAT of your incoming class doesn't say anything about how good the school is. Right? I mean, it just says something about how quality the students are. Yeah. Well, I know. But if you're trying to evaluate, like, what effect does a good school have on your outcome or what effect doesn't school have in your outcome? That I think about it, it's like, well, what affect does a school that had a higher SAT score of the incoming class have on Your Outcome? That don't think that directly says anything about how good the teachers are, how good those knowledge is that you're getting from that, you know, which may be questions that people think this is answering and it isn't. You know?

0:31:08 Beth: Selectivity. Right. Oh, no, no. No, no no no. Oh no. Right, right. Yeah. And I think some of that is what Tom eventually kind of got around to in in that episode of Daryl Dads, he finally got into like, yeah, yeah. Okay. It matters, but it just doesn't matter in the way we're telling high school students that it matters, what matters and what they should be striving for. And there is this conflation of selectivity and quality. The idea that higher SAT score of your average freshman is used to infer that it's a more selective school, harder to get into.

0:32:04 Thomas: Yeah.

0:32:04 Beth: And thus it is better. And so that's, again, another trail I went down. But this one is just using basically selectivity. Barron's rankings in this case are still a measure of selectivity, and the authors of the paper and all are very careful to be saying selectivity. It's when they get in popular press like Time and The Atlantic, that it starts turning into "better schools," higher quality, and much more vague sorts of qualifications there. They did try looking at a less selective data set, this National Longitudinal Survey of the High School Class of 1972 that followed up several times up to 1986. And they did find similar zero effect of the college selectivity once they controlled for everything else. However, that is a fairly small data set. It was like not the thousands that they had for their more selective schools data set. There's some stuff about tuition and expenditures. That's not super clear in this one. I think they get a little more into that in the second follow-up study that does seem to show that spending per student may have an effect.

0:32:23 Thomas: Mm -hmm. Yeah, yeah, yeah. That makes sense.

0:33:14 Beth: Yeah, and so in that sense, a school that costs more might be better.

0:33:18 Thomas: Well, does spending per student mean that it costs more necessarily? I could see. Isn't that also about decisions of what the colleges do with the money?

0:33:24 Beth: Yeah. I think in this one, they may have tried to infer from tuition. I have some things that actually look at expenditures. That was actually not super clear in this paper. The results on that were kind of murky, but there might be something there. They did model for men and women separately, but they have a nice little note there that the sample's not big enough for women to get good estimates. Meh, forget it. Again, remember only full -time workers here.

0:33:50 Thomas: Well, Not only that, the historical nature of it, I mean, I'm sure that, you know, we still aren't in modern anywhere near now, right?

0:33:59 Beth: Yeah, another kind of weird finding was that in the matched applicant model, the average SAT of the schools that rejected the applicant was associated with higher earnings. What that would suggest to me is you're someone who shoots high, maybe higher than you're actually, you got rejected, you aimed for really high schools, they rejected you, but you aimed high.

0:34:00 Thomas: Oh that's interesting. Yeah, yeah. Yeah. Yeah, the C student who's like, I can get into Harvard, that's easy.

0:34:26 Beth: But that's associated with later earnings.

0:34:28 Thomas: Yeah, it could be, yeah.

0:34:29 Beth: If your schools that rejected you had higher SATs, that was associated with higher earnings.

0:34:29 Thomas: Yeah. That's interesting, that's funny, yeah.

0:34:34 Beth: That does, again, get back to the idea that there's these unobservable characteristics like ambition, like self -image, you know, like willingness to try for things that are maybe unlikely, you Know, that's something that we don't see in your GPA and your SAT scores and all. But seeing where you applied gives us some hints on that. So I thought that was really, really fascinating. They did try to just model black students in the working paper that this was based on, because actually this came from a working paper that was for the National Bureau of Economic Research, and it's kind of interesting to see the things that got changed between that and the peer -reviewed published version. They didn't really have any useful conclusions for black students, and they admitted that the number of black students and their sample was fairly small, so 839 out of, what was of some several thousand. So they ended up dropping that in the published paper.

0:34:39 Thomas: There's

0:35:27 Beth: And I didn't see that they tested any interactions with race or gender, which can possibly have an effect, but they just didn't. They had so many white men.

0:35:36 Thomas: So much missing. I mean, there's, well, and there's no HBCUs. And There's

0:35:39 Beth: And so they got good stuff for white men, right. But one interesting interaction there was of school quality as measured by tuition and parental rental income on your future earnings. So that the lower your parents' income is, the more you get a boost from school selectivity. Yeah. And that actually does kind of make sense with some of the stuff you were talking about in the Dear Old Dads episode of networking and such. And the idea that people who are very wealthy, they already have these connections for things like internships and initial job prospects and stuff. And so whether they go to the super high quality school or not, they have those connections. But when you come from a poor family, you don't have those things, and so the school provides those things, it plugs a hole, basically.

0:35:40 Thomas: Yeah. Yeah. Right. Yeah. Right.

0:36:27 Beth: There was a neat quote somewhere on one of the articles I read that referred to the idea that schools act in loco parentis, have you heard that, that's in the place of the parents, you know, it used to be their reason for why they locked up all the girls in virgin vault dorms that men couldn't get into, you know, because we are acting instead of your parents. Um, now it's mostly a duty of care, but they said the results from this study were kind of like, oh, so schools act in loco rich parentis, you know, if you're a poor person, they are in the place of the rich parents, they will give you those same connections, yeah.

0:36:36 Thomas: Yeah. Yeah. Yeah.

0:36:54 Thomas: I mean, that's good. Like I would want, yeah. If we helped people who don't make as much as families don't makes much get into these schools, that would be a good way to do something about income inequality, class inequality.

0:37:03 Beth: Right. Yeah. Actually, I did get into another paper that went to economic mobility and school selectivity that showed that it could be a really good way to equalize some economic inequality, but we don't do it. So actually, as school gets more and more expensive, it kind of sorts in the worst way. Fewer and fewer low socioeconomic status students are getting in. There were some other things that they looked at in the working paper that they dropped in the the publication, probably because they just didn't find anything, but they did look at probability of graduating as an outcome measure. Like instead of future earnings, did you graduate, and didn't find anything. I am not sure why they didn't try using that as a predictor variable in their measure rather than an outcome, but they didn't.

They did look at things like your grades and your class rank. Who went to more selective schools tended to end up with a lower class rank, I guess, then higher rank is associated with higher earnings, so it's possible that those things could kind of create an overall wash for selectivity. I honestly, I have no idea what my college rank was, do

0:37:28 Thomas: Yeah. Yeah, I don't

0:38:20 Beth: You know, I don't know, maybe if I, I went to Harvard, I would know or something. But

0:38:21 Thomas: Either. No clue. If you're in the top one or two, I bet you probably know, but I bet that's something that may correlate with these fancy schmancy schools, right, like I don't think anybody at

0:38:25 Beth: Yeah. Yeah, if you're not valedictorian or salutatorian, I don't freaking know. Yeah. I guess I got a magna cum laude, so does that, like, I don't know, know, 5%, 10%, something like that. Top something.

0:38:42 Thomas: My college, I first off, I didn't know about that whole system, which sucks because that would have helped me do way better because it's like the exact kind of gamified bullshit my brain needs to like actually do stuff, and then secondly, for me it was actually based on just GPA, so it was like cum laude was, uh, I think I got the second one, isn't there, I can't remember but uh, it was like three five, yeah, I think I got SUMA And I didn't get the top. It was like three, five, three, eight through four.

0:38:48 Beth: -huh. Yeah. Yeah, there's a summa, I think. I think summa is the top. I think summa is higher than magna and then just cum laude.

0:39:11 Thomas: Gotcha. Or I got just cum laude. I don't know. It was weird to have cum all over my diploma. Yeah. But yeah, anyway, for us, it was GPA based. It wasn't rank based, but I don't know if that's the same everywhere or not.

0:39:16 Beth: Yeah. So I thought it was really weird that they found effects of like class rank in college because they're like, who even knows?

0:39:29 Thomas: Yeah, that's interesting. It may be something where the people who are affected by it don't necessarily know like the number they are, but the people around them are doing better in classes and that I could see that having impact psychologically.

0:39:41 Beth: Know, and I can see that is actually one of the reasons why I did not choose to go to law school at Harvard was because of the extreme competitiveness that I heard about that was just, you know, people backstabbing each other a lot. So I bet they know. I mean, law school classes are fairly small, but I bet that they knew. Did find that the likelihood of getting a postgraduate degree was positively correlated with selectivity. So the more selective school you went to, the more likely you were to get a postgrad degree. So this was their first one that basically said, once you control for these unobservable characteristics that we're inferring from your application behavior, the effect of school selectivity from highly selective to super duper duper highly selective does not matter. I also do wonder about the data being collected 20 years later about the where did you apply? Because I feel like, do I remember where all I applied? I don't.

0:39:49 Thomas: Yeah, yeah, yeah. Yeah, sure. Oh, Oh, 20 years later. Yeah, that's a oof.

0:40:36 Beth: Yeah, that's asked in the 1995 survey about the application behavior.

0:40:40 Thomas: About the same. So they went back to the same cohort or whatever and asked them.

0:40:43 Beth: Yeah, yeah, it's the same people who were, yeah.

0:40:45 Thomas: Oh, yeah that's interesting.

0:40:46 Beth: They entered college in 1976, but they were collecting the data, the how are you now, in 1995.

0:40:55 Thomas: About a selection effect. The kind of people who would remember what the fuck they applied to 20 years later might be a certain kind of person.

0:40:58 Beth: Right, right. And also, maybe, you know, your life experiences bias your memory of which ones you remember applying to and not.

0:41:08 Thomas: Yeah, Yeah ,Yeah. So this is all just the first study. The Okay.

0:41:12 Beth: Yeah, yeah, that's the first one. So then they did a follow-up paper that was published in 2014. And it extends that previous paper by following the cohort over an even longer time period. So they follow them now, same cohort to 2007.

0:41:27 Thomas: So Same Cohort Still though. And I would love to have some more relevant information. But

0:41:32 Beth: And they add a somewhat more recent cohort, which is 1989.

0:41:32 Thomas: Okay. Oh. Okay, I can't wait till we get to this millennium, Beth, that's gonna be cool.

0:41:38 Beth: I know, of course, you do have to have some time pass if you're You can't be like straight out of college. How much are you making? Although that is another question, like what kind of job did you get out of college?

0:41:42 Thomas: No, that's that's true, yeah. Yeah. Placement? Right out of

0:41:50 Beth: Right, Right, right. So the 1980, they did a 1989 cohort that also was a College and Beyond survey by the same people who they did this again for a later cohort. So they had collected all this data on the people entering college in 1976 that they measured in 1995 and then they went back and measured them again later and also surveyed people who had entered college in 1989. They did a whole nother big survey and they get another big data set. And so they're trying to see who does this hold for the ones later on. And the thought was that maybe it might make a difference in whether there was an effect because things do change, as we know. They again did focus only on people who were were working.

0:41:50 Thomas: College, yeah, sure.

0:42:37 Beth: It's the same 30 colleges for the College and Beyond survey, although in this one, they did include two of the HBCUs and three of the public universities. So they were still not using two HBCUs and not using one public university. And I think it was just because they couldn't get all of the data that they needed from those, because they're trying to tie their responses to these college and beyond surveys to their applications, their transcripts, freshman surveys that were done. There's an organization that does freshman surveys. So still, it's just attendance at school, not necessarily graduation. Still, it's only people who are working. And they restricted their sample to people whose earnings were at least the equivalent of earning minimum wage for 2,000 hours in that year.

0:42:59 Thomas: Yeah. Yeah. Well You know, I gotta say, just going back, you know, to all of that, sorry to repeat, but but it's a lot of data. I just want to make sure we're all on the same page.

0:43:33 Beth: Know it is.

0:43:33 Thomas: Yeah, trying to see if I'm a parent and I'm thinking, what impact does this school have? You know, that's the basic question I think that we're kind of trying to get at and we're doing our best given the data and the studies that have been done. If I'm saying, okay, does a good school make a difference? I think a non-insignificant factor would be, again, what percentage of people get a job after they graduate? And I do think that that's entirely not answered from what I've heard so far.

0:43:41 Beth: Right.

0:43:59 Beth: Well, I mean, they're looking at them 20 some years later. So it's like, who has a job 20 years later? But if you didn't have a job, 20 years late, or a full time job 20 years later, they weren't including your data. And Kruger chose to just look at people who are working full time. They don't really give a reason for that. But

0:44:16 Thomas: You go to school for somewhere, especially, you know, historically, and you're like, I want to be a, I don't know what the fuck, lawyer, engineer, I had a doc, no, I don't know if it's medical school, but and you And you don't gets placed right away, I would say that it's more. More likely, I think that maybe you didn't even end up in the career that you went to school for. Don't you think?

0:44:24 Beth: This is undergrad, yeah.

0:44:36 Beth: Right.

0:44:36 Thomas: I mean, I don't know if that's just the millennial in me speaking, but for millennials and everybody in the world that I know, almost nobody got a job in the thing they went to school for, yeah, historically, I bet it was probably maybe higher just because I don't know, but like I could imagine that being a factor, you know, like if you didn't get a job in the thing you went to school for. You didn't have a full-time job. Oh, but it is 20 years later. Okay.

0:44:45 Beth: I think it's like 30 or something like that.

0:45:01 Beth: Right.

0:45:02 Thomas: You know, that is a significant amount of time, I I suppose. Keep thinking they looked at them right away and that's my mistake I'm making. Okay.

0:45:02 Beth: Of No. No, and And they did remember, um, find that people who went to the more elite schools were more likely to then go get a graduate degree, wouldn't get a job straight out of school because they're staying in school, but it does give them a restricted sample. And I, you know, I mean, some of it is again, what their goal was, was to see, does this self-revelation model show us something? This idea that there are things that we aren't measuring that may have an impact, that it's not the school, it's actually the students that go there. And they would do just as well if they went somewhere else. So I think people want to draw other conclusions from the paper that were not necessarily what they were wanting to look at. And so I think they were willing to minimize as much as possible some other sources of variation. And so by only looking at people who have full-time jobs, that allowed them to minimize that as a source of variation,

0:45:15 Thomas: Okay. Sure. Mm -hmm. Right. Yeah, right. Oh no, yeah, yeah. Don't get me wrong. This, this isn't really a critique of the study. It's more like, I'm sure you know this, but after going through a lot of these with experts, it is really clear that it might not necessarily be so clear to just the layperson how much of this stuff is often just based on the limitations of the data set that you can get, you know, where it's like, oh, why didn't they look at, you Know, HBCUs? And it's like, well, I don't know, nobody collected that shit or something, or they didn't have access to it. And so it's not necessarily a critique of the study, but it is important for, okay, what can the average person take away from this? I think it's very important for that. Yeah.

0:46:12 Beth: Right? Right. Yeah. Yeah, yes. Yes. And that's where popular press is just terrible. They are just awful. Because the whole question is like, how far can you generalize these results? Can you generalise them to the larger population of college students that go to less selective schools? Can you generalize this as a difference between this state school and that school? State school, can you generalise it to people of colour or women or whatever? And this isn't telling us that. For this, We do know about a lot of white men, some women, but still mostly white people, because that wasn't really their goal in this one, was not to investigate race and gender effects, but to investigate the concept that there are features of students that we can't measure with with these numbers of SAT scores and income of family and stuff that are the determining factor of how well they do rather than the school they go to.

0:46:30 Thomas: Yeah. Yeah. Yeah. Right. Yeah. Yeah.

0:47:18 Beth: That was their goal. And they did show that, you know, so that's an important thing then to bear in mind when you look at other studies that are only differentiating students by those observable factors and seeing what effect something else makes of that there are these unobservable factors too that they just don't have data on.

0:47:38 Thomas: Well, and you say goal, I mean, they could have had way broader goals, but we're like, well, shit, this is the data we have.

0:47:43 Beth: And it's already a 50-page paper full of equations and tables. I mean, there is a, like I Said, some of those things that I mentioned that were in the working paper that for the National Bureau of Economic Research that didn't really pan out, they didn't end up in the published paper, I'm sure just because it was way too long already. You know, they were like, okay, that didn't really pan out. Yeah, so I doing this follow up paper that that they are a 1976 cohort and also following them longer period of time and also adding a more recent cohort.

And they did their basic model and they did their self -revelation model, which is the looking at what schools you applied to and what their average SAT score was as a measure of selectivity. And they didn't do the matched applicant thing. That was apparently a huge pain in the ass and it didn't really give them different results. And so they're just doing their self -revelation model, which has your unobservables and the basic model. And controlled for race and sex and high school GPA and students' own SAT score, parental income, whether they were a college athlete. And they did try different measures of college quality. In addition to using average SAT score They also looked at Barron's Index, and they used tuition as a possible outcome.

0:47:49 Thomas: Yeah. Cool.

0:49:02 Beth: Also, in this one, this was wild, they got earnings from Social Security data. So they're like, it's better than self -reported data.

0:49:09 Thomas: Rather than self reported.

0:49:10 Beth: Yeah, yeah. And it turns out the SSA ran programs for them. They didn't give them the data, because I'm like, how did you get that? But apparently, I don't know how you get the Social Security Administration to run. Okay, I know, I'm sorry, you're Paul Kruger. Forgot. Never mind. You're in Obama's cabinet. Right. Okay. But yeah, the Social Security Administration did the matching up for them and did not give them identified data. Yeah, and again, they're ridiculously selective schools. And one of the things that I find interesting is they talk about how that makes their data set so great for modeling this because most of these students applied to a lot of schools. Schools.

0:49:10 Thomas: Yeah, yeah. Yeah. Yeah. Sure. Yeah. Sure.

0:49:49 Thomas: Yeah, so

0:49:49 Beth: They note that many students who go to schools of lesser selectivity don't do multiple applications. Only 46 percent of students who attended college in 1972 applied to more than one school.

0:50:00 Thomas: They're trying to make the best of the fact that like they don't have data that would be right

0:50:04 Beth: So they're like, this is great. We have people who did a lot of applications.

0:50:08 Thomas: But we don't have the schools that people went to most, we have just have the elite schools right at the top whatever, yeah still doesn't answer the fucking question well

0:50:11 Beth: They're elite, elite students, elite school students. They apply to a lot of things. So, you know, again, this is what they're trying to go is, does this application behavior show us something else? And so they're like, we got a data set with lots of application behavior. It doesn't answer other questions that people try to take it from. So their results generally replicated the results of their earlier paper. When they don't control for unobservables via application behavior, it does show a positive return of more selective school. But once you add in that self-revelation stuff, that drops basically to zero. And that's true for the 1989 cohort as well as the 1976 cohort. Cohort and the 1976 cohort, remember, it's not just a total replication because now they're looking at, let's see, 2007, so another 20 years later for them, so now we're 40 years out of college, or 40 years out of entering college, right.

0:51:07 Thomas: And at that point, like, doesn't the college effect kind of washed off of you, you know like

0:51:12 Beth: But Apparently it hasn't, if you just look straight up school and you don't look at the application behavior. It's small, but there does seem to be a little bit of a difference, because sometimes things that are very small differences can accumulate over time, you know and so yeah, that's actually important in several of the studies that I looked at that found small but significant effects, and then they start measuring like, okay, but what would that mean over 20 years of career, or 40 years of Korea, it starts to add up.

They didn't really find any difference in the two cohorts, they thought they might, you know, different effects over time, but no, and do have a smaller return in the uncontrolled model, yeah, but they similarly dropped to zero effect in the standard, or the self-revelation model. So they did at least have enough women now to look at that. But again, only working full-time people. So that is probably going to leave out a lot of women.

They use all the different quality measures of SAT, tuition, or Barron's Index, and the results are the same. They did group together Black and Hispanic students to try and have a decent sample size of racial ethnic minority.

0:51:12 Thomas: Hmm. Yeah. Oh. Right, yeah. Yeah.

0:52:16 Beth: The 1976 cohort wasn't very useful on that. There was so much variation that their values didn't reach statistical significant. But for the 1989 cohort, some of them did. And a school SAT score increase of 100 points was associated with higher earnings of 7 .6 % for Black and Hispanic students. For Black and Hispanic students, there did seem to be an effect of college quality. But again, our range of quality is fairly narrow. Do you remember that? And there was an interesting interaction between selectivity and parent education, showing that attending the more selective school had a benefit for those whose parents were less educated. If you only had parents with a 12-year education, so high school graduates, going to a college with a 200-point higher average SAT score would lead to 5.2% higher earnings in 2007.

0:53:11 Beth: But for students whose parents averaged 16 years of education. So college graduates, virtually no return. So again, I think you see that selectivity can take the place of some of the benefits that people who already have very educated, very wealthy parents and they're white already have. They did find some effects for racial minorities, for people whose parents had less education.

0:53:35 Thomas: Which again, so it, it does feel like going down the socioeconomic ladder, this could make more and more of a difference, which is why I'm still annoyed that we only have the top X schools or whatever because I feel like, you know, maybe I'm sure there's definitely some people who got into the schools from lower socioeconomic backgrounds, but not as many as, like, just your state schools, your, you know, your fucking UC system.

0:53:45 Beth: Yes, I do have a paper that looks at what they call the undermatching hypothesis, the idea that low -income students go to lesser schools than their scores and performance could get them into, probably because it's closer, it's cheaper, you know, things like that, and That that actually does perpetuate income inequality. It does seem to be, and they even say this in their that, you although you most students who apply to selective colleges may be able to rely on their families and friends to provide job networking opportunities, networking opportunities that become available from attending a selective college may be particularly valuable for Black and Hispanic students and students from less educated families. That they don't have that stuff from their families, the connections, and so the school helps provide that. I was really kind of frustrated, though, that they didn't include graduation in any of these analyses.

0:54:02 Thomas: Oh, good. Hmm. Hmm, oh, interesting. Right, right.

0:54:54 Thomas: Yeah,

0:54:54 Beth: You know they They obviously had it for the 1976 cohort because they tried using it as an outcome variable in the working paper. But no.

0:55:03 Thomas: And it would be interesting even to go with, like years that you were there. Did someone leave after one year, two year, three years, and then you could see, like if there is any effect, does scale it, or something? Something really.

0:55:11 Beth: Right. So basically, these are the papers that all of these popular articles like to refer to of see, like from the Atlantic in 19 2018. 18. You know, they're still like, they are even referring to the first paper. In November 2002, the Quarterly Journal of Economics published a landmark paper by economists Stacey Dale and Alan Kruger that released the startling conclusion that for most students, the salary boost of going to a super selective school is generally indistinguishable from zero.

0:55:18 Thomas: Even even now, wow. Yeah, it's like they're assuming this is some ironclad fact about the world that just, well, we determined it back then and it's still true. I just think things have changed so much, you know, like they can think about the kinds of jobs. I don't know, it'd be hard to quantify, but you know, in the age of the fucking internet, you know, if we had, if we had people who graduated in the 2000s, it'd be interesting to see if there's more of an effect, less than effective because I could almost imagine too, like, I don't know, maybe during the tech era, less of an affect if you know, all the dropout, all the people who started these companies dropped out and just did it on their own. I don't know, like it, it feels

0:55:46 Beth: -hmm. Mm. Oh, Oh yeah. Oh yeah, right. Yeah. Yeah, uh huh. Uh huh. Yeah, and

0:56:19 Thomas: Like at the very least, we don't have a firm answer on this to me.

0:56:22 Beth: I do Have a whole bunch of studies that I looked at on various things like that, but it's surprising that people still do like to rely on these Dale and Kruger studies. You know, in Time piece, which was in 2014 that it was published, and they are still referring to Kruger and Dale. They at least do the follow-up study as well that they have released in 2011, but that was the working paper and reached a similar conclusion that they also keep saying college graduates, which was not what they measured. And so they're misrepresenting there too. But yeah, I mean, even now they still like to refer to those papers and say, look, it doesn't matter. And they're, they're very much over -generalizing.

0:56:23 Thomas: Yeah.

0:56:53 Thomas: Fair, yeah, yeah, well, That's the just part one, that's merely part one, there's so much more, lots more studies actually, for part two, and again, that's available to patrons at patreon.com/seriouspod right now. Go there, enjoy the ad-free episodes, the bonus stuff, and part two right away. Otherwise, I'll see everybody else on Thursday day. Thanks so much for listening.