Emily Fair Oster is an American economist and bestselling author of “Expecting Better” and “Cribsheet”. Emily is a Professor of Economics and Public Policy at Brown University.<\/p>\n
P. Richard Hahn also joins the show as a guest interviewer. He is an associate professor of Statistics at ASU. His specific research interests include regression tree methods, causal inference from observational data, and foundations of statistics.<\/p>\n","protected":false},"excerpt":{"rendered":"Emily Fair Oster is an American economist and bestselling author of \"Expecting Better\" and \"Cribsheet\". Emily is a Professor of Economics and Public Policy at Brown University.\n\nP. Richard Hahn also joins the show as a guest interviewer. He is an associate professor of Statistics at ASU. \u00a0His specific research interests include regression tree methods, causal inference from observational data, and foundations of statistics.","protected":false},"author":13,"featured_media":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"_genesis_hide_title":false,"_genesis_hide_breadcrumbs":false,"_genesis_hide_singular_image":false,"_genesis_hide_footer_widgets":false,"_genesis_custom_body_class":"","_genesis_custom_post_class":"","_genesis_layout":"","episode_type":"audio","audio_file":"http:\/\/podcasts.la.utexas.edu\/cepa\/wp-content\/uploads\/sites\/21\/2019\/11\/19-11-11-Policy-at-McCombs-Podcast-Emily-Oster-and-Richard-Hahn.mp3","podmotor_file_id":"","podmotor_episode_id":"","cover_image":"","cover_image_id":"","duration":"","filesize":"71.78M","filesize_raw":"75263888","date_recorded":"14-11-2019","explicit":"","block":"","itunes_episode_number":"","itunes_title":"","itunes_season_number":"","itunes_episode_type":""},"tags":[42,41,40,29],"categories":[],"series":[2],"class_list":{"0":"post-291","1":"podcast","2":"type-podcast","3":"status-publish","5":"tag-daycare","6":"tag-maternity-leave","7":"tag-parenting","8":"tag-policy","9":"series-policymccombs","10":"entry"},"acf":{"related_episodes":"","hosts":[{"ID":693,"post_author":"38","post_date":"2020-10-29 17:58:44","post_date_gmt":"2020-10-29 17:58:44","post_content":"\n
Carlos M. Carvalho is an associate professor of statistics at McCombs. Dr. Carvalho received his Ph.D. in Statistics from Duke University in 2006. His research focuses on Bayesian statistics in complex, high-dimensional problems with applications ranging from finance to genetics. Some of his current projects include work on large-scale factor models, graphical models, Bayesian model selection, particle filtering and stochastic volatility models.<\/p>\n\n\n\n
Before moving to Texas Dr. Carvalho was part of the faculty at The University of Chicago Booth School of Business and, in 2009, he was awarded The Donald D. Harrington Fellowship by The University of Texas, Austin.<\/p>\n\n\n\n
Dr. Carvalho is from Rio de Janeiro, Brazil and before coming to the U.S. he received his Bachelor's degree in Economics from IBMEC Business School (Rio de Janeiro) followed by a Masters's degree in Statistics from the Federal University of Rio de Janeiro (UFRJ).<\/p>\n","post_title":"Carlos Carvalho","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"carlos-carvalho","to_ping":"","pinged":"","post_modified":"2020-10-29 17:59:59","post_modified_gmt":"2020-10-29 17:59:59","post_content_filtered":"","post_parent":0,"guid":"http:\/\/podcasts.la.utexas.edu\/cepa\/?post_type=speaker&p=693","menu_order":0,"post_type":"speaker","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":580,"post_author":"42","post_date":"2020-07-03 19:53:40","post_date_gmt":"2020-07-03 19:53:40","post_content":"\n
Mario Villarreal-Diaz is CEPA\u2019s Managing Director and Senior Scholar. Mario joins CEPA from the University of Arizona where he was an Associate Professor at the Department of Political Economy and Moral Science and taught in the Philosophy, Politics, Economics, and Law undergraduate major.<\/p>\n","post_title":"Mario Villarreal-Diaz","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"mario-villarreal-diaz","to_ping":"","pinged":"","post_modified":"2020-07-03 19:53:41","post_modified_gmt":"2020-07-03 19:53:41","post_content_filtered":"","post_parent":0,"guid":"http:\/\/podcasts.la.utexas.edu\/cepa\/?post_type=speaker&p=580","menu_order":0,"post_type":"speaker","post_mime_type":"","comment_count":"0","filter":"raw"}],"guests":[{"ID":601,"post_author":"42","post_date":"2020-07-03 20:11:18","post_date_gmt":"2020-07-03 20:11:18","post_content":"\n
Emily Oster is a Professor of Economics at Brown University. She holds a PhD in Economics from Harvard. Prior to being at Brown she was on the faculty at the University of Chicago Booth School.<\/p>\n\n\n\n
Oster\u2019s academic work focuses on health economics and statistical methods. She is interested in understanding why consumers do not always make \u201crational\u201d health choices \u2014 why do people not eat a fully healthy diet, or pursue all recommended preventative health behaviors? Her work also concerns methods for learning causal effects from observational data. Earlier academic work included studies of HIV in Africa (the topic of a 2007 TED talk<\/a>) and medieval witchcraft.<\/p>\n\n\n\n In addition to her academic work, Oster has written two books. \u201cExpecting Better<\/a>\u201d analyzes the data behind many common pregnancy rules, and aims to improve decision-making for pregnant women. \u201cCribsheet<\/a>\u201d does the same for early childhood \u2014 what does the evidence really say on breastfeeding, co-sleeping or potty training.<\/p>\n\n\n\n Oster lives in Providence, RI with her husband (also an economist) and two children.<\/p>\n","post_title":"Emily Oster","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"emily-oster","to_ping":"","pinged":"","post_modified":"2020-07-03 20:11:19","post_modified_gmt":"2020-07-03 20:11:19","post_content_filtered":"","post_parent":0,"guid":"http:\/\/podcasts.la.utexas.edu\/cepa\/?post_type=speaker&p=601","menu_order":0,"post_type":"speaker","post_mime_type":"","comment_count":"0","filter":"raw"},{"ID":798,"post_author":"38","post_date":"2021-03-24 18:32:47","post_date_gmt":"2021-03-24 18:32:47","post_content":"\n Richard Hahn is an associate professor of Statistics at Arizona State University. He develops probability models and computational techniques for applied data analysis, with a focus on the behavioral, social, and health sciences. His specific research interests include regression tree methods, causal inference from observational data, and foundations of statistics.<\/p>\n","post_title":"Richard Hahn","post_excerpt":"","post_status":"publish","comment_status":"closed","ping_status":"closed","post_password":"","post_name":"richard-hahn-2","to_ping":"","pinged":"","post_modified":"2021-03-24 18:32:47","post_modified_gmt":"2021-03-24 18:32:47","post_content_filtered":"","post_parent":0,"guid":"https:\/\/podcasts.la.utexas.edu\/cepa\/?post_type=speaker&p=798","menu_order":0,"post_type":"speaker","post_mime_type":"","comment_count":"0","filter":"raw"}],"transcript":" Welcome to the Policy McCombs podcast, a data driven conversation on the economic
\n\ue5d4
\nissues of today in this series. We invite guests into our studio to provide a highlight
\nof their work presented during a visit to the University of Texas at Austin Policy. Emma
\nCombs is produced by the Center for Enterprise and Policy Analytics at the McCombs School of Business.
\nWe have two guests with us today. First, professors at the six, Richard Horne from Arizona State, Richard Worksman,
\ncausality in decision making. And he joins me today to help with this interview. Now, turning to our main guest,
\nour guest today is Emily OSTER, professor of economics and public policy at Brown University. Emily
\njoined us to talk about her two bestseller books, Expecting Better Why the Conventional Pregnancy Wisdom is Wrong
\nand What We Really Need to Know. And the More recent creep sheet, a data driven guide to better and more relaxing parenting
\nfrom birth to preschool. Emily, welcome to Policy McCombs. Thank you for having me. So let’s start with the story
\nbehind the writing of this book. How do you tell us how an economist gets gets to display? So writing
\nthis this two books. Yeah. So so this short answer is that I got pregnant,
\nthat I was an economist, and then I and then I was a pregnant, an economist. And I got really
\ninto kind of what I can only describe as using my job in my pregnancy.
\nAnd so there were a lot of things that came up when I was first pregnant. Why I wanted to understand
\nwhat is the evidence behind this restriction or this recommendation or this rule.
\nAnd I was spending a huge amount of time at home basically doing doing things that were sort
\nof like what I would do at my jobs or reading academic papers, trying to think about decision making
\nand good decision making in the face of the data that we that we have. And
\nand that was me that was really in the service of my own pregnancy, not in the service of of writing anything like
\nthis. But I had always kind of liked to write for a more general audience and think
\nabout how do we explain the ideas that I think are really valuable about from economics, from data,
\nfrom statistics. How do we explain that to two people and how do we help them use
\nthose data to make good decisions? And so at some point and this part, I
\nhave to say, is a bit murky in my head at some point. I moved from doing this for my own pregnancy
\nto trying to actually write something for for a general audience. And what we found
\nwas I really liked doing that. I really like the process of of writing in this way. And then I
\nsort of wrote some and then I had an agent and then I and then I had a book, got a
\nyadayada. And so then I published the first book, which is now is came out in 2013.
\nAnd I had had my daughter, who was born in 2011. And then
\nI was fairly sure I was I could write a second book because it’s a lot of work to write
\na book and it’s had a lot of work to have a kid. And it seemed like maybe you doing both of them was not
\nwas not really feasible. I think the other thing is that I you know, with your first kid,
\nI know you have two of them also. But I feel like with my with my first kid, every decision
\nabout the kid was like made in this sort of totally like chaotic, haphazard way.
\nSo we would just be like constantly like trying this, trying this and sort of obsessing about a lot
\nof really tiny decisions that not seem ultimately important in in retrospect, it was very hard to focus
\non kind of what are the big things we’d want to make choices about. We had a second kid,
\nyou know, with your second kid, at least for me, I was like a lot more relaxed. Not I’m not a relaxed
\nperson, but relatively I was relatively more relaxed. And it was much easier
\nfor us to focus on on kind of what are the main things I would want evidence about. And it was then much easier
\nto see. Okay, well, what kind of book what I write that would help people make choices about those those things.
\nAnd so then, you know, at some point a few years ago, I decided maybe it was time to time to
\nwrite another one. And so crib sheet is the kind of more or less the sequel sort of looking at the same
\nkinds of what does the evidence say? How do you make good decisions around early, early
\nparenting? So did this combination of data and economics. You talk a lot, a lot in the book
\nand trying to separate associations from causality. So give us a couple examples
\nthat comes to mind when I’m thinking about crib sheet that I found very instructive in not only talking about the
\nevidence of this particular issue, but more to describe the endeavor overall to connect. Is
\nit for me that information to the general public is about breastfeeding and peanuts? That doesn’t mean those two
\nchapters. I mean, it’s a good summary of what what goes on there and is seeking causality. Yeah. So so let’s sort
\nof start with the question of breastfeeding. So when you sort of think about breastfeeding and the kinds of ways that breastfeeding
\nis talked about for four new parents, you really get a lot of the message that like breast milk, breastfeeding
\nis is the best. It’s good. The thing that is going to make your kid not only healthier and
\nbetter in the first year, but really forever is going to have these like very long term impacts impacting
\ntheir I.Q., their obesity, other kinds of other kinds of illness. And
\nthis sort of basic issue with with data on breastfeeding is a lot
\nof the data that we have comes from studies which compare the outcomes for kids who are breastfed
\nto kids who are who are not in what we think of as a sort of correlation association
\nkind of way. So like to take a concrete example saying about something like IQ. So it is certainly
\nthe case if you compare kids who are breastfed to kids who are not and you look at differences in. Their IQ, you will see differences
\nin IQ, some of them are very large, but when you look at the
\ncharacteristics of a parents, you will find that the moms who choose to breastfeed,
\nwho breastfeed for longer, tend to be better educated. They tend to be richer, they tend to have more other
\nresources, they tend to be white. They have a bunch of other features which we know in the
\ndata is also correlated with outcomes for their kids. So we know that maternal education
\nmatters for kids test scores, and we also know that it matters for breastfeeding.
\nAnd so it’s hard to isolate the impacts of breastfeeding from the impacts of all of the other things that are
\nthat are that are different. And so so in the book, I try to kind of go through and help
\npeople understand how might we get better evidence on that. So we have millions and millions.
\nWe have tens, maybe hundreds of studies of these correlations between
\nbreastfeeding and and good and good outcomes for for kids. But we don’t have that many
\nstudies which do a better job on causality, but we do have some. So, for example, there’s one
\nkind of randomized controlled trial of of breastfeeding, which has some of its own issues. But
\nbut does does it bit better on this? And then we have actually a number of
\nof what we call sibling Fixx Effect studies. So studies where they actually compare to
\nkids within the same family and they look one of whom is breastfed and one of whom is not. And they look at
\nwhether there are differences in IQ that show up there. So if you thought it was really the breast milk as opposed to other
\ncharacteristics of the mother, you would expect the differences to show up there. And they they don’t. So kids who are
\nwhen one siblings breastfed, one sibling is not, you really see basically no difference in their in their IQ. So
\nso I sort of tried to use that as a frame to help people think about, you know, what really are
\nthe benefits of breastfeeding. And I think in the end, when you do that in a in a sort of,
\nyou know, meta way for all of these outcomes, you do find that there are some things where breastfeeding does seem to benefit
\nthe kids who particularly some early life digestion, maybe some early life allergy stuff
\nseems to be improved by breastfeeding. There actually seems like there’s maybe some evidence of reductions
\nin breast cancer for the mother, sort of long term, long term impacts. But on
\na lot of these kind of long term impacts for kids like IQ and obesity and other kinds of health. The best data just does not
\nsupport those those things. So I think the message of sort of breast is best,
\nyou know. Yeah, it’s it’s best, but isn’t it maybe not as as much best as
\nmight be implied by the phrase breast is breast is best. So it’s kind of a classic
\nsort of like coat correlation versus causation, causation space.
\nSo seasonally the peanuts are sort of. I agree it’s another interesting place. So. So here the question
\nis, is how you expose your kids to to allergens.
\nSo peanut allergies have gone up a lot over time. There has been sort of historically and not by historically.
\nI mean, this is the advice I was given with my 8 year old. You were told we were told not to
\nexpose our kids to peanuts, because if because that would make them more likely to be allergic or you wanted
\nto. You know, we didn’t. And so when they did, if they did have a bad reaction, they were older.
\nThere was sort of like some stuff in that in that space. But at some
\npoint, somebody did a very simple study where they just looked at the difference between
\na peanut allergy rates between kids in Israel and kids in the UK. So Jewish kids in the U.K. and
\nkids and kids in Israel. And they found that basically rates of peanut allergies are way, way, way lower in
\nIsrael than they were in the UK. So this is just like a correlational study and it’s fact. It’s like in some ways
\neven worse than the breastfeeding self because it’s like literally like a cross-country comparison. It’s like Israa. I mean,
\ncould could you imagine something like, oh, I’m sure that that’s the only thing that’s different. You know, Israel versus the UK,
\nlike a lot of Jewish kids in both places. Yeah. OK. And that really fixes you’re. Exactly. It fixes your problem.
\nBut what they say in the in the in that paper, their theory is that Israeli kids eat
\na lot of this peanut snack as like a 4 as an early foods is a peanut. Michael Bomba is very
\npopular and in Israel is like a Puft. My daughter loves those. Yeah. I mean, it’s delicious.
\nWho doesn’t like peanuts? And so kids kids are eating a lot of this at very young ages. And so they had this idea that, like, okay,
\nexposure is, you know, is good for preventing allergies. What’s
\ngreat about that literature is that they didn’t stop there. So if they sort of just had that, you’d be like, OK, what can we what
\ncan we learn? But then they actually did a randomized controlled trial where they randomly exposed some kids
\nto peanuts early and some kids not. And the effects there are huge like the difference
\nin allergy development is like 70 percent.
\nAnd so basically exposing kids to peanuts. And I think it turns out other allergens as well
\nearly on, like pretty much, you know, for months, kind of as soon as you’re exposing them to any foods
\nthat turns out to be very good at preventing allergies. So that’s a kind of a good example
\nwhere we sort of started with the kind of evidence that you would say. Really? We would use
\nthis as suggestive evidence and not as the as the sort of all piece of evidence. And then
\nthey actually did the next thing, which is they like real randomized control trial where you can be more confident about causality.
\nSo in the case of breastfeeding, that’s not they haven’t done that. The best we have is the sibling
\nstudy. So there is one randomized control trial of of breastfeeding. It was run
\nin Belarus in the 1990s. It’s it’s pretty big
\nand it’s an encouragement designed. So basically, they they encourage some women to breastfeed in some women.
\nThey don’t encourage them and they get pretty large, a pretty large wheezy first stage. So pretty large
\ndifference across groups in in their incentive of breastfeeding.
\nBoth ever breastfeeding, but especially sort of continuation. So so people views, S.I.D.
\nYou look at outcomes like both sort of short and long term outcomes. And there
\nyou see very consistent with what you see from the sibling studies, you see sort of some evidence
\nof kind of digestive benefits, maybe some rash reduction early on,
\nbut you don’t see sort of consistent differences in in IQ or test scores later. You don’t
\nsee differences in obesity or other kind of health measures later. So on the one
\nhand, I think it’s a good it’s it’s a good study because it’s randomized.
\nIt also isn’t necessarily the most comparable
\nsetting to the sort of current kinds of questions people would ask. In the U.S.,
\nso, you know, it’s now actually pretty old. So I would like to see that people do
\nmore of that. It doesn’t seem to hear you describe it. It doesn’t sound particularly
\nequivocal. In other words, at this point, would you say that the
\ndata is in and the effect sizes are definitely smaller than the
\nmedia would suggest? Yeah, I think that’s right. I mean, look, I always like I always want
\nmore data. And I think that, you know, we mostly the estimates we
\nhave at the moment come with a fair amount of error. So, you know, could. Like, I think
\nthat they they suggest that the effects are smaller than the kinds of things that are that are stated in the media.
\nDoes that mean that they’re zero? You know, I think that’s that’s like outside the range of what we can do with our with our
\ncurrent. Sure. So but yeah, I mean, I I think we have a lot of there are some places
\nin the book where I say like, you know, the problem is we just don’t have a lot of data on this. There’s a place where we do have a lot of
\ndata. And so that raises the question sort of why or why. It’s
\ndoesn’t seem clearcut to people. And we were talking earlier about opportunity cost reasoning.
\nCan you speak to the way you think about that in terms of specifically the breastfeeding example?
\nYeah. So, I mean, I think one with one way to think about it is let’s imagine that breastfeeding was something that was
\nlike super easy. And you could do like just in a just it would be trivial.
\nSo it would be you know, it’s like vitamin D drops or something, something where you just kind of like
\nput a little thing on your kids for head every morning. Then probably we would say you should do it
\nbecause there do seem to be some some benefits. Right. So so I think in in that world
\nit’s you would see why you would want to get people to do it. And I think a
\nlot of the approach to breastfeeding has kind of taken on that frame of
\nlike, well, everyone should do this. So let’s just like let’s really spend a lot of time talking about how great it is.
\nMaybe we overstate the benefits a little bit. You know, so we just really want people to get care to do this. And
\nI think what that misses this is where it argument is like. Actually, this is both very difficult
\nfor a lot of people, like literally very hard to do. But also it it is
\nvery costly in terms of your of your time. So one of the things he will say about breastfeeding is it’s it’s it’s
\nit’s free. Like, it’s such a great deal because it’s free. That’s that’s like the crazy
\nlike, you know, I mean, I sort of think about the the kinds of time that people spend, you know,
\npumping nursing like time out of a labor force. Like, you know, even if you just
\njust think about the pumping time, like how many people realize if you want to exclusively breastfeed a baby and you’re at your job
\nlike you need like 30 minute pumping breaks every, you know, three hours
\nand it’s not that easy to work while you’re pumping. You can do it, but
\nit’s distracting. It’s distracting. So it is exactly to emphasize
\nthe cost. There’s a lot of costs that are unnecessarily think about ahead of time. Yeah. And and, you know,
\nI think that the to me, the most impressive aspect of both of your books is this is fit make people
\nface that issue. The fact that these decisions are not made in a vacuum. They have costs, they have opportunity cost to have
\nthey have tradeoffs that you have to to to think about. And when you do, I guess,
\nwhat what is the advantage to do it? Do you do any calculations on that when the breastfeeding? Do you have a sense
\nof, you know, the typical labor force costs associated with potentially breastfeeding?
\nThat’ll be very nice. I don’t think we I think that would be interesting to see. And I don’t think we have a great sense of it. I mean, in
\npart it’s very complicated by the fact that actually, like the people who are doing the most of this, the people are most
\nlikely to breastfeed are actually also people for the high value of time. Right. So I think they’re sort of like
\nthe like the breastfeeding rates are much higher among particuarly continuation of breastfeeding or much higher among more
\neducated, you know, higher income women where you might have thought that that would sort of go the other go the other
\ndirection. And I think there’s another piece of this which is sort of different from the average training costs, which is just
\nabout support where, you know, actually it’s not like it’s physically difficult
\nto get to sort of get started doing this. So one of the things you see is that actually breastfeeding initiation rates
\nat the moment are very, very high. So very, very, very large share of of women in the U.S.
\nreport trying to breastfeed or doing it for, you know, a day or two. But when you look at continuation,
\neven, you know, for a few weeks their way, they’re way lower. So it suggests that there’s a
\nsort of like pretty big drop off where people try to do this and either just
\ndecide it’s not for them or it doesn’t or it doesn’t work. And I think that that we spend a lot of time
\ntelling people that they should do this and maybe not as much time like helping them do
\nit, which is another cost there, too. People get really frustrated and they feel that they are failing their kid and depressed.
\nExactly. So you have had the use of the story of
\nyour book, starting with your pregnancy, essentially that your interest research wise has been related to
\nthe medical field for longer than that. Yeah, I’m sort of. Did you what was your reasoning?
\nWas this something you had always been interested in? How did that come about? Yeah. So I. I
\nwhen I was in when I entered college, I thought that I would be a doctor or like I’ve always been very
\ninterested in research. And so I guess I thought it would be like a medical research answer some specific ideas about being a more
\nof a hard scientist kind of person. And then I am the summer after my freshman year, I had sort of two
\njobs. I was like a like a kind of Part-Time research assistant for an economist, Chris Avery,
\nwho’s the Harvard Kennedy School and was doing some stuff about schooling. And then I worked at a fruit fly lab,
\nwhich was like my you know, like I’m going to be like a like a scientist. And it was
\nawful. I mean, I I like I. There’s nothing wrong with this person’s fruit fly lab. And like,
\nobviously, like, we’ve learned a tremendous amount of from fruit flies. But what I learned is that I was not cut out
\nfor this for this experience of kind of hard science, for a bunch of different for
\na bunch of different reasons. So I sort of pivoted into and I pivoted and in more into into
\neconomics. But I I’ve retained a lot of interest in in medicine. And I’ve sort of a lot
\nof if you look at a lot of my work, it has this sort of flavor of kind of
\noverlapping a little bit with with medicine and and kind of being
\nin reading a lot in the medical literature. So there’s. So I think part of what made it possible to
\nto do these books and to do the kind of research that led into them was that I had a pretty
\ngood sense of the medical literature and how it like how one would sort through that
\ncoming into into doing this, which is going to be true of everybody in economics. And what
\nhas been your experience as a social scientist, a very quantitative one working
\nin a medical field? Has the reception been mainly smooth and positive
\nor, you know, so I mean, I think there’s kind of two
\ntwo sets of people that that I interact with a lot. One is like
\ndoctors. And, you know, I would say have I have mixed but mostly pretty positive
\nrelationships with people actually practice medicine. And it’s particularly true as the as
\nthe books have kind of age. So I think I get more pushback on the first book when it first came out
\nbecause could talk about. But some of the stuff about alcohol and some of these other things. And I think the first book also feels
\na bit more confrontational with sort of my own experience with the medical system during pregnancy
\nwas very frustrating. And I think that comes out in the book a little bit. And that was like last is
\nmuch less true with with the second book. And so my kind of my all of my pediatrics experience has
\nbeen great. I love all the pediatricians that I encounter. And so so there
\nI I you know, I think I’ve had sort of more positive, positive interactions. I will say
\nwhen I I spend a lot of time in the epidemiology literature and this isn’t a comment
\nabout interacting with epidemiologists, but or, you know, I would say sort of public health literature in
\ngeneral. I find that literature incredibly frustrating. And I think that I just like
\nthe the lack of really
\ntaking seriously concerns about causality in analysis of observational data
\nis just. I like something I say. I don’t. Still
\ntotally get it here. I know. I just I mean, I find it like
\non the one hand, they’ve got a lot of RTT is like, that’s great. But then when they’re not using r-s.d, you know, we’re we’re
\nregressing them again. This is like I’m overgeneralizing. There is there are, of course, people in this space that take causality
\nseriously. But there are so much of this. You know, The New York Times is covering, you know, eggs kill
\nyou, eggs don’t kill you. You know, eggs are great for you. Coffey’s the death coffee is going
\nto make you live forever. It’s like, you know, it’s it’s election. It’s all just selection. Different
\nkinds of selection. Yeah. So do you think that you’ll be. I mean, right now you’re
\nsort of a the representative of a certain type of
\nresearch in this space. And I was asking people because they knew I was going to talk to you. What should I ask
\nher? And one of the questions was, do you think that there are gonna be more people that do this type of work or you just always
\ngoing to be a. I hope so.
\nI mean, I would really like to see more of a push
\nin this towards like the credibility revolution in this in this
\nlike medical literature space. So if you sort of think about the path of
\nof economics and I understand I’m not reveal here that like I’m an economist and I think that what we do is like the right stuff.
\nBut that’s okay. That’s part of the thing. You know, I think that that over time we have
\nreally improved our ability to do inference out of observational data and the sort of seriousness with which
\npeople think about research design as a way to understand causality and observational data. I
\nwould like to see more of that in these other spaces. And I think that, you know,
\nas people have started talking more about publication bias in P hacking and I
\nfeel like that’s that’s in this, guys. You know, I look like GPA any he’s like there’s like a
\nI feels like there’s a moment where maybe we could push a little bit more on on
\nthat. And I also feel like there’s more public interest in kind of thinking seriously
\nabout about causality. You know, I feel like when I when reporters call me now
\nabout to comment on medical studies, they are more skeptical
\nsometimes like they are sometimes we’ll call and be like, you know, but that’s election again right there. Are you
\nwriting for. Yes, I agree. Yeah. Thank you. Thank you. Gala’s I appreciate that.
\nBut it’s a question that I think Richard had as well. But but let me get there.
\nIs it. I agree with you that that that in the social sciences, economies are far ahead in terms of thinking hard
\nabout causality, in observation studies and being very you know, they lead the way to other fields to
\nfollow and has been happening for a long time. And here’s another field where it where it can take advantage of that. But
\nthe framework of of a causal inference based on on no testing, for example, was not particularly
\nwell suited for decision making. And that’s something that you bring in the book, this connection
\nbetween evidence, decision making, which is fantastic. That’s how we know in particular statisticians like Richard. I
\nlike to think about the world as everything is decision making problem. So have you ever given any thought
\nto that issue and thinking about maybe even frameworks of inference that might actually be useful
\nto make the connection between the evidence we collect and the decision making process? No, it’s super understanding.
\nI haven’t thought that much about that. But I think you’re exactly right that sort of you could frame the whole the
\nyou could frame the sort of the whole thing as kind of ultimately the goal is the goal is decision
\nmaking. The goal is not to know is there a causal impact of X on why it is like to know
\nlike should I do behavior? You know, what should I basically show I do this behavior and
\nthat and that can do. Yeah, that’s very no. The answer is I haven’t thought that much about that, but that seems
\ngreat. That seems like more like the set sort of statistician approach. Yeah. We’ve been we’ve been involved in
\na couple of studies in psychology now where where, you know, it’s obvious that the traditional that the
\ncredibility revolution going on there, there’s this huge endeavor and trying to make sure that we pre-register everything
\nthat you know and almost like a completely overcorrection to the situations where
\nall the studies were not being able to be replicate and so on. But we tried to work on
\nwith tools that hopefully would help people in thinking about, okay, what I learned from this r_s_t_
\nif I were to now run the second one, you know how reprioritized, for example, the groups that might be more susceptible
\nto the treatment and so want to think about it, but that’s a long endeavor is not it’s not an easy
\nthing. And I think the psychology of been open more open to receiving
\nthat kind of tools that we been working with then quite honestly, the economists and
\nthat at making a connection, it’s something that would be kind of neat. Yeah. I mean, there’s also a space for sort of more
\nlike kind of a Bayesian approach to some of these things like
\nyou what’s right? This is sort of like. Yeah. I mean, I think we we have a lot of in a lot of these spaces.
\nOne of the things that seems kind of weird is like we’re kind of everything is sort of sort of some frequentist
\nthing. And so you’ll have like, you know, a. I was in pieces of like a huge amount of like biological and other
\nkind of Prior’s that basically acts does not affect wire, couldn’t you know. And then it’ll be like, well, at least one study where
\nX effects is effects. It’s like, well, you know, like, yeah, okay. But like, could you do you know. You know, real eBays.
\nAnd so I think that’s. And that feels to me like pretty important for the decision making piece piece of this year. Like
\nhow do we bring these pieces of evidence together to oversimplify a bit. You must have noticed this when writing
\nthat the old saw that absence of evidence is not the evidence of absence. And
\nyou have to write around it all the time because you would find in your writing you would say it’s
\nstatistically significant. We can’t show that it’s not zero. Right. But then in the very next sentence, you
\nhave to basically say, but to the extent that we have estimated it, we think that it might be positive.
\nRight. And then you have to take them to account. It’s a difficult. The whole framework is difficult to talk about. I think we’ve all taught statistics
\nand it’s just a nightmare. Yeah, I agree.
\nI have some more questions. Just so. So
\nI think the two themes that are coming up here and I think it’s a correct me if I’m wrong, but causality
\nand then utility, there are the two things that come up. And,
\nyou know, both of those things are hard. The utility one is kind of interesting because
\nthere’s some evidence that people don’t actually know their utilities that well.
\nDo you think that like how in some of these problems, in some cases, when it has
\nto do with an infant death or something horrible like that, the utility function is kind of obvious. But I
\nthink there’s a lot of cases, especially in your second book, that are sort of lifestyle things that’s really hard to
\nhard to say. Do you have an approach for that? What do you tell people when they ask you? I don’t actually. You know
\nmy mind. Yeah. I mean, I think I I I think that a lot of progress
\non this can be made by just being a little bit more deliberate about the weight,
\nabout the fact that things are our choices. So,
\nyou know, rather like I think you’re right that like when we think when we talk about utility as as economists or statisticians,
\nwe had this sort of like you have some Udalls and you’re right. Like nobody knows what they’re what they’re they’re Udalls.
\nThey’re you know, nobody is aware of their of their to know what that what that is. It’s like a Dr. Seuss.
\nExactly. They read the star Udalls and the nonstory. But
\nbut I do think sort of framing. Just just trying to sort of say, okay,
\nthese are your two like these are your two choices and think about your life with this and with, you
\nknow, without this or, you know, think about this in the context of other choices you
\nand you will make or what is the alternative? I think those are, you know,
\njust like there’s not a lot of deliberateness almost. I would say people are not deliberate about these
\nthese choices. And I think sometimes that reveals sometimes that kind of
\nframe can can help reveal. I can’t reveal what people or
\npeople want. Yeah. But, you know, there are a lot of there are a lot of things like, you know, potty training is like the biggest
\nthing in the book. Rush is like whatevs. You know, sort of like people like what is the right age to potty train? Basically,
\nlike there is no right age. If you wait longer, it will take less time, but you will have to change woobie
\ndiapers for longer. And, you know, if you try to do it earlier, like it’s going to take more time, they’re going to be on the floor
\nsome of the time. But, you know, they then you’ll be then you’ll be done. And, you know, you need to like
\ninterrogate what is your feeling on diapers and that’s it. But there’s no, like, Zellick
\nsecret way to make that choice. So, I mean, you advocate a lot for for thinking
\nabout collecting the data, thinking about the costs and then making a decision and for some of the
\nproblems that you’re using in your books. You let off with do it, eat as a family
\nor do we eat separately and we take out and you know, it seems to me some of those cases
\nare distinct or different from the medical cases in that you get feedback immediately.
\nAnd so in those cases, is it profitable to encourage people to experiment? And you might say luck with
\nbreastfeeding might to some extent be the same way to the extent that that you can less so. And
\nit seems to be a spectrum of experimentation versus we have to make this decision figuring out there you tell it and then
\nfigure it out. Yeah. Yeah. I think that that sort of good decision making, if you sort of think about like how do we
\natabaki people make decisions and you know, outside of the home context, good decision making would involve
\nthinking about the choice, making the choice, reviewing the choice, you know, having like a structured process
\nfor making some of these these decisions. I think that sort of saying like you should experiment is maybe.
\nExactly, exactly right. There are many things where it’s it’s a little like a little bit hard to
\nreally like kind of experiment. And I think the other thing that happens is, is people
\ndon’t think carefully about the sort of review piece of this. You just sort
\nof fall into like doing something. And then that’s the thing you’re you’re doing. And there isn’t a moment where you step back
\nand you’re like, okay, actually, is this like, is this something it’s working. You just wait until sort of things
\ncrash around, down, around you and then you’re like, oh, god, that’s working like I thought
\nit would. Yeah. Just to switch, switching a little
\nbit to two other areas in which this approach of data and economics you think might be helpful. You mentioned a little
\nbit about the fact that that you would like to see more in the medical field. Did
\nyou. Did you start a trend? I mean, do you think that there are other folks out there trying to bring that kind of approach to
\nareas that you didn’t expect or not? Anyways, I’m asking, have you read something recently, any interesting book
\nthat sort of mimics that approach and try to apply to different areas? I mean, I think, you know, I’ve
\nI think that there’s you know, there are some people who have worked on kind of like school.
\nI mean, economist have gotten more into like writing popular books. Since I wrote this. I don’t think because
\nof me. But just like whatever. There’s been more of this or maybe a short me. It’s probably it’s I actually that’s
\nnot telling me how to present. Nothing to do with tickety. Who goes by that guy.
\nNo. But, you know, I think that there’s there are a bunch of spaces where economists are working where you can imagine sort of
\ntranslating that work in a way that’s sort of more direct into like it’s sort of like work, unschooling
\nor, you know, the. There actually is another economist parenting book by like The TimeStep
\nKey and Sloboda. I think that’s like about like kind of the theory
\nof of of parenting. So, you know, I think that there’s some there’s some
\npush in in that in that direction. But I don’t know that there’s anything quite in
\nthis quite in this space. Yeah. OK. So.
\nSo this is maybe the most confrontational question that I have for you, which is that
\nnot everybody’s credit equal in their decision making skills. Sure. And, you know, this is certainly something
\nwhen medical bodies or institutions have to come up with policies. What
\ndo they think? They kind of have to go for a lowest common denominator approach.
\nAnd so, in short, maybe more information is not always
\nbetter for outcomes. Surely you’ve thought about. Yes. I’m interested
\nto hear your thoughts. Yeah. So, I mean, I think I think a lot about this when we’re we’re kind of talking
\nabout something like sort of safe sleep guidelines or even something, you know, like alcohol
\nand pregnancy, kind of like if we if we think if we agree, let’s us take safe
\nsleep. So there’s an issue of like, you know, should your kids their sleep guidelines urge kids you sleep like alone in their crib, not
\nin your bed with no stuff around. And in some pieces of those safe sleep guides are easier
\nto to do than others. It’s easy to not have bumpers in your crib. And I have a lot of pillows in there,
\nbut it may be much harder to get your kid to sleep alone. And I think from the standpoint
\nof the of the of the AP, there’s kind of a feeling like, okay, we’re just going to we’re gonna
\nsay these things with this is the safest way. And if everybody did this, that would be like kind of the safest
\nthe safest thing to do. But what I think is is hard
\nabout that messaging is that then if people can’t do that
\nor or don’t do it, you haven’t given them any guidance about how bad
\nit is to deviate in different directions. And so there’s a sort of piece of like,
\nyes, it would be best if everybody did this one thing. So let’s just tell them to do that one thing and not give them any information about
\nthe other, the other things. But then if they choose not to be
\nin the box that you have given them, they they may deviate in a way that’s that’s really
\nbad. So let’s take the example of of a sleep’s. You tell people you can’t have your kids leaving your. It’s dangerous
\nto have your kids sleeping in your bed. But the truth about the data is that it
\nis probably slightly riskier to have your kids sleep in your bed. But that risk is really different
\nif you are sleeping like you know, if the adults are not smoking and not drinking.
\nIf there aren’t a lot of other covers in the bed, if you sort of think if you’re.
\nSo those are kind of the big factors. And what we don’t really tell people
\nthat, we just say it’s not safe to do this. So then you can you can people sort of exit
\nthe almost like accidentally do it or they’ll they’ll do it, but they they won’t do
\nit in the safest way possible because no one’s told them that there is a safer and less safe way. It’s just like, don’t do this while once I’m doing
\nit, I might as well like sleep on the sofa. But actually, no, sleeping on the sofa with your infant is like,
\nreally, really, really dangerous. Way more dangerous than sleeping in a sort of the safest kind of co-sleeping
\nenvironment. So I think that’s the piece where we want to be a little bit careful about
\nthis idea that just telling people the safest thing is right because it may be
\nvery hard for them to actually achieve that. It’s notable that what you describe still
\nentails some processing of the data. It’s not like you’re just providing the tables. You’re actually giving a rank ordered
\nmenu and you’re saying that one might be on the top. But then, you know, and it reminds
\nme of some colleagues of a one time colleagues of ours,
\nDick Thaler, Cass Sunstein, their book Nudge, which basically
\nsounds sort of a similar process. Did you ever talk to them about your book in the context
\nof their idea of. Well, not no. I mean, I’ve talked to Dick a lot about this, a Richard a lot about the
\nabout this book, about the books. But I haven’t talked to him on that. But I think you’re right, it sort of has this that kind of feel
\ngood, some way to behavior take on all day. Is that. Well, no, we lay people utility functions make the decisions
\nbecause they have all these problems in their psychology. Therefore, we need to nudge them in some way. A be paternalistic to some extent.
\nRight. And I think your presentation in more traditional econ sense of like now mean here’s the data.
\nYou have your utility, go ahead and empower yourself to make a decision, right? Yeah. I think I mean, I think in these species,
\nin both of the parenting, all the press, even more so in the in the pregnancy space, I think there is too
\nlittle credit given to people about their ability to sort of
\nlike ascertain their utility functions, make decisions, think about risks and and benefits from themselves. And I
\nthink that’s you know, I think that can border on disrespectful, honestly,
\nparticularly in in those sort of pregnancy games that they’re also sort of like, oh, don’t worry, I’ll tell
\nyou what to do. You know, you’re just like a little pregnant lady. You know, as opposed to to recognizing
\nthat a lot of women are actually perfectly capable of making choices for themselves,
\nhas to be has to be sort of somewhere in between. Right. Because if it’s in respect versus exposed
\noutcomes, you know, I mean, is I really like the articulation of having a menu like that. Seems
\nlike I’d never thought about that in particular. That seems like a. MiddleGround. I think there’s a way.
\nI mean, there’s also a lot of these things like there’s a way to like be be respectful of people’s decision
\nmaking and timing while not just being like do whatever, you know, sort of like, you know, Italian,
\nbasically. Like, I recommend that you you don’t make this choice about your birth. And, you know,
\nhere’s why I think that’s important. Is that is it something which, of course,
\ndoctors should be empowered to say, in fact, is like their their job, but maybe different than saying
\nlike, you have to do this or your kid is going to, you know, have some terrible,
\nterrible outcome. I mean, I wouldn’t. When my son I’ll tell you, when my my son was born,
\nhe had jaundice and they came in like me, like a couple of days, you know, we went home.
\nSomebody came. They took his blood. They called the doctor called us. And she was not a regular doctor.
\nAnd she was just basically like, you know, your kid is this is his number.
\nAnd I said, okay, can you help me understand, like, you know, like what? What exactly? Like,
\nhow do you where’s the data on the cutoff? My first kid hadn’t had this in have any data like where’s the data on the cutoff? Like,
\nhow do I understand? How do I understand this? And she was just like, you know, I’m telling you what to do if you don’t bring
\nyour kid in to back into the hospital like he’s gonna have brain damage. And, you know, that was there was.
\nAnd of course, that was like just to be clear in our case, 100 percent wrong. Like there was nothing.
\nI mean, jaundice can cause brain damage, but we were like distantly far from any number
\nthat would even actually would even recommend hospitalization, let alone be a risk for.
\nBut it was sort of like presented in this way. That was that was really
\nnot respectful of the fact that like perfectly reasonable people could differ on this. And then, in fact, the question
\nof just, can you help me understand where these cut offs come from? And you know, how you
\nprocess this like that, that this sort of the frame was kind of like, I can’t believe you would even suggest
\nthat you would have an opinion about this and that you would even think to ask this question. I told you what to
\ndo. I’m the doctor. There has to be infuriating. Yeah, it was. And it was
\nreally I was so angry at actually the next day this person sort of what I ETSA
\nlike I did bring him back to the hospital because of course, you know, three days postpartum and somebody tells
\nyou if you don’t bring your kid by glass, he’s got brain damage. I guess you’re breaking my glass bottle. That’s the vulnerability. Also, that’s
\nreally irresponsible. Was like, what are you going to. You know, what are you in it? So we brought it back to hospital. And, you know, this is he was finding
\nreally have any edge on us. And but then the next day, she did come in and say and she. She
\nhad like figured out. I mean, she came in the next morning before rounds and told
\nme, oh, I figured out who you were at, how. Now I figured out who you are. And I think we can work together.
\nAnd I just want to be clear. This is not like a person who is a pediatric. This is
\nlike some hospital. You know, this was like some random person, but it was a very it was sort of very telling mom
\naround to be like, okay. Like, I understand that. I I know why you’re
\nreacting that way. But just to be clear, it doesn’t matter whether I’m a professor or a parenting book
\noffer. Anything else like that is a perfectly reasonable question. What cut off did you enter
\nand where? Like, where are you getting your your evidence from? That’s a question that could be asked by anybody.
\nYou should be respectful to people, even if they’re not going to go on the radio and the five guys to talk
\nabout your behavior. Time for one more. Yeah. There’s a few
\nmore. Go ahead. So here’s a half baked idea of mine. One of the things that
\nI’m interested in my own research is heterogeneous treatment effects. So not every drug affects everybody
\nelse. Does that translate to. Yeah. Yeah. Well, it’s just different. People have different responses to
\ndifferent treatments. And one of the things that’s occurred to me is that almost all of the medical
\nliterature has been focused on average treatment effects. There’s good reasons for that and not so good reasons for that.
\nBut in particular, it as a thought experiment, I was wondering maybe
\ngetting anecdotal advice with multiple anecdotes. So from people close to you
\nwho are more like you can sometimes be better than knowing about an underpowered
\nmedical study based on a population that might not be like you and
\nas a as a logical matter of course that’s the case. But I
\ndon’t know to what extent it’s real. So if you just what are your thoughts on heterogeneous effects and whether or not it
\nsalvages folk wisdom in any circumstances? So this this is a sort of source
\nof a lot of when you ask doctors like why do they rely so much on their own experience in giving
\nin giving advice? You know, either sometimes the answer is just like mine. That’s how I that’s how I do
\nit. But I think if you if you kind of there are many thoughtful people who would say, look, the reason I give this
\nadvice is because even though I know these the sort of average treatment effect from these studies,
\nI have a lot of expertise on my population and I am kind of triangulating between the sort of
\nlike trying to to use my population to figure out the treatment effects that are specific
\nto the people that I work with and kind of combining that in some way with these others.
\nSo, I mean. I think the zouk, super important, super important space, it comes off all the
\ntime, even in in the sort of RTT, a good RTT evidence around something like obstetrics. So you’ll have like a
\ngood r-s.d that is about the impacts of induction on C-sections
\nor something. This is like the most recent thing that that has come out. But if you sort of dig into like that’s
\na those are can be great studies. They’re big, they’re powered that, you know, they’re they give you a lot of evidence.
\nThey come out of fancy teaching hospitals. Right. So this sort of really big trial that recently
\ncame out about induction C-sections, the the C-section rate in the trial, in the hospitals
\nand the trials like 18, 20 percent for the for the drug for the control group.
\nThat’s, you know, the C-section rate in the U.S. is like 35 percent. So if these places are very selective
\nin a particular way, are those adverse treatment effects relevant for the for the other? I mean, is it a little
\ndifferent than heterogeneous, but not really. I mean, it sort of says like your Yahtzee dieselgate for an average treatment effect for
\nthe people who are willing to be in, you know, where the hospitals can do a protocol on this. In this
\nr-s.d. So, you know, I think the the idea of you
\neven using some of these tools that people have taken to try to kind of combine observational
\nlike sort of battled like bias, observational evidence, but where you can get heterogeneity with
\ngood, you know, average treat with with good randomised evidence where you can like that, that feels like
\nsomething where economists, again, have sort of probably also statisticians have like, you know, try to make some progress
\nand where where you could sort of do more do more here. Yeah. Okay. So that’s an
\ninteresting I’m not really listening. I’m not sure I would have put like listening to your friends in this space.
\nWell, I see grandma, as you know, was there in the sense that, you know, we’ve seen this here
\nin this group. In some ways that somehow is different because I was imagining in particular a population that
\nis distinct in some very particular way, indigenous group, in a particular geography,
\nthat the advice passed down from generation there might be contra the controlled studies, but might make
\nperfect sense in the context of that climate or that seems that seems totally.
\nThat’s my one more. One more. Yes. Well, this is this is too easy. That
\nmakes it go in the close. So medical info is gonna change. Have you signed yourself up for
\na lifetime of doing edits day? So I’ve seen the book. So
\nwe have updated the first book a few times and I think we’ll do like a much bigger update in the next couple
\nof years. And so, you know, I think I don’t know if I ever signed myself up for like
\na lifetime of it, but I think as long as people are buying the books, I would like them to be.
\nI would like them to be updated. And, you know, I don’t know. It’s like it’s it’s fun.
\nIt’s sort of fun to stay up on this. This literature. Well, for what was worth.
\nThank you so much for writing this book. As a parent and as a husband, there were incredibly useful
\nfor it for for our family. And I think a lot of families can take advantage of that. And thank you, Richard, for joining us today.
\nThank you. Absolutely. Thank you, guys, for. Before we wrap
\nup, you can get more information in our medium page. Thanks for listening to Policy McCombs.
\nSee you next time.<\/p>\n"},"episode_featured_image":false,"episode_player_image":"https:\/\/podcasts.la.utexas.edu\/cepa\/wp-content\/uploads\/sites\/21\/2021\/05\/SC_PolicyMcCombs_Art-scaled.jpg","download_link":"https:\/\/podcasts.la.utexas.edu\/cepa\/podcast-download\/291\/emily-oster-on-maternity-leave-policy.mp3","player_link":"https:\/\/podcasts.la.utexas.edu\/cepa\/podcast-player\/291\/emily-oster-on-maternity-leave-policy.mp3","audio_player":null,"episode_data":{"playerMode":"light","subscribeUrls":{"apple_podcasts":{"key":"apple_podcasts","url":"","label":"Apple Podcasts","class":"apple_podcasts","icon":"apple-podcasts.png"},"google_play":{"key":"google_play","url":"","label":"Google Play","class":"google_play","icon":"google-play.png"},"google_podcasts":{"key":"google_podcasts","url":"","label":"Google Podcasts","class":"google_podcasts","icon":"google-podcasts.png"},"spotify":{"key":"spotify","url":"","label":"Spotify","class":"spotify","icon":"spotify.png"},"itunes":{"key":"itunes","url":"","label":"iTunes","class":"itunes","icon":"itunes.png"}},"rssFeedUrl":"https:\/\/podcasts.la.utexas.edu\/cepa\/feed\/podcast\/policymccombs","embedCode":"Emily Oster on “Cribsheet”<\/a><\/blockquote>