Ian is an Associate Professor at the University of Liverpool and received his Ph.D. in Economics from the University of California-Irvine in 2017. Ian's research focuses primarily on the economics of discrimination and its impact on labor market outcomes and health. He has focused on discrimination against women, older workers, and the LGBT community.
Thank you so much for joining us on discover economics. How did I get here? So just who or what is an economist, there's an economic lens for every topic that you can possibly think of. The economists in our podcast are motivated by a desire to change the world. And their belief that better data and better understanding are key to achieving this change. I'm very excited and enthusiastic about learning more about what economics can offer us as a society. And what are the options when it comes to careers for young people. It's been an absolute delight to do this series. And to learn more to indulge my noisiness and to get to ask so many questions. The questions I'm hoping you as listeners will also have wanted to ask. So thank you so much for listening. So today we're joined by Ian Burn. And Ian is an associate professor at University of Liverpool and received his PhD in economics from the University of California Irvine in 2017. His research focuses primarily on the economics of discrimination, and its impact on labour market outcomes and health. He is focused on discrimination against women, older workers on the LGBT community. Welcome, Ian, lovely to meet you. Thanks for having me. I'm looking forward to chat. So I'm gonna go straight in with the, you know, the gotcha question of where did you grew up? And what were you like at school? Oh, I think I was described as precocious. Which as a child, I thought was a good thing. I realise people say with a bit of like, Yeah, he's precocious. It was Yeah, I was definitely I come from a very opinionated family. That is values learning. And I think that was surprising to a lot of my teachers that, you know, I'm from a family of academics and academics love to debate, love to argue. And my parents never, I think my parents were very good about letting us explore whatever we were interested in, no matter how weird or, like, not connected to the curriculum, it was. And I think that drove my teachers nuts growing up, that I sort of had this passion. I didn't like following the rules of like, why do we think this way? You know, why do we do it this way? Like, I always had to know why. And I think that drove everyone around me nuts. But it's great, as you know, when you become an academic that sort of drive to question everything, no matter how big or small or when, when we sort of settled on that law of physics or something like, you know, always questioning why I think, is the passion for the job that I have. Now. I'm having flashbacks to the like a similar thing. I was brought up Catholic, and loved questioning everything in my kind of catechism classes. I'm like, What do you mean? Why is it like this, and you could see all of the other people in the class like groaning like, oh, Jennifer, just let us get through it. We all agree. But just let us get through this. Just do what we need to do. I can definitely relate. I mean, it's often because my dad's from Yorkshire. And then my grandfather is from Yorkshire as well. My grandfather did his PhD in physics, like he's literally a nuclear physicist, and then moved to Massachusetts. And so you know, I'm the joke in the family is that I am the third person to get a peach, the third generation to get a PhD. So since our last name is Burn, we are I am a third degree, third degree burn. I love it. There's the Yorkshire for you. So yeah, I grew up in Massachusetts for a couple years, my dad did his postdoc at Harvard, and then graduated, my mom was like, we have four children, you need a real job. academia doesn't pay enough. And so my dad went into pharma, they're very fair. And so then we moved on to Delaware. And so I grew up in Delaware, and then went back to Boston for college, and then went to Irvine for my, for my PhD. So every time I graduate school, I just move further and further away from my parents. Whoa, I hope they're not offended by that. Oh, no, they love visit. Oh, that's the best part is, you know, I live in places that they would never kind of normally visit because I did my PhD in Irvine, and then moved to Stockholm for a postdoc, and then moved to Liverpool after Stockholm. So it's like, yeah, it's like, every couple years, I just move again. And it's, you know, it's that's what I love about academia is the ability to just travel and go places, and the job is universal. And the knowledge is universal. You know, it's sort of economics transcends sort of these cultures where I think if you were in the humanities, you might be a bit more kind of bound to a area just because, you know, I always enjoy the fact that like, you have American Studies departments in Great Britain, and I'm like, Oh, that's so weird that you have an entire department and it's like, oh, like my existence is now a department. Okay? It does sound DOJ when you see it, like, it's like someone's like, oh, there's a British Studies Department. And, yeah, but economics is kind of universal in that way, where it's like everyone uses the same textbook, like, I was laughing because we have this with there's this experiment that was run in Tennessee in the 1980s, I think, called Project star, and it's about class size. And it's one of those things where it's like Every one has taken and studied this programme because it's just how you teach a couple different things. In economics. We're like, oh, we're gonna teach this method, we're gonna use project star. And it's like, it's just this sort of everyone's taken it. It's kind of funny to come to Europe and like, still people know about this random experiment that Tennessee ran on kindergarteners. That's the universal language we use when we're talking about weirdly comforting. Oh, yeah. Okay, imagine. Yeah, I mean, it's you definitely feel spoiled when you go in to talk to people. And it's like, everyone has the same cultural touchstones in terms of all the same policies. Like when we're gonna study taxation, everyone studies that the earned income tax credit in the US, and it's like, what does that do? Like, even when you're going to study a British policy, all the evidence is kind of coming from America or Scandinavia, it's sort of like everyone's drawing on sort of different experiences around the world. And it just everyone just goes, Well, it's close enough, you know, the big clause of economics should be the same. And it's kind of fun. to kind of have that, I think it's, it does make it less scary, I think, to move around when you're not, which doesn't sort of depend on where you live, but it is kind of funny when you're like, talking to people, and it's like, everyone has the same experiences, you know, just with these different, weird programmes that the US did. And it's like, it's like, okay, you know, and were you always interested in economics as a subject did you do? I didn't do it at school, I actually came into it, because I was taking in the US, we have advanced placement courses. So these are college level courses taught to high school students. And I was taking a monkey Yeah, AP, I was taking a bunch of AP courses. And it sort of was going through it is like, heavily social sciences. Like I love history. I really wanted to do history. But you know, my mother was like, there's no money. There's no careers in history, like, do something practical, find something that does history related, that you can actually make money with. She's a smart woman. Yeah, she's just like, try economics. And you're like, Okay, fine. It's a lot of math. I like math, I'm good at math. And so I was like, I did it. And I took my first micro economics course, and just absolutely fell in love. And I don't know why it just sort of clicked, like, I loved how logical things were, then like you, you had a mathematical model of the world, and you would analyse that, and whatever you wanted to talk about, as long as you put it in that structure of sort of mathematical quantitative, we're bounding the rules of nature with this, it was this sort of, you know, I always love science, like, my family is all full of scientists. And this was me, being a social scientist, it was kind of like, I felt very, like I could talk to my family of physicists and biologists, using their language about a social process. And it sort of was just like, Oh, this is like, this makes sense. This is I get this, it just sort of it clicked. And then Ever since then, that's what I've been doing. But it's always been, I think, sort of my own flavour to it. Like I love to bring in sociology, I love to bring in history, I love to bring in politics and law. And it sort of was nice, because I get to do something that I get to connect with my love of the social sciences, and always go back to it without having to sort of, even though I'm publishing an economics, like, I'll spend like a month, pretty much doing the history of something. And you're like, Okay, great, you know, it ends up being a paragraph in the final paper. But in terms of my ability, just to learn and to explore it, I want to explore I thought economics, you know, I've found that economics lets me be practical, but still do what I love. And I thought that was the nice balance is that you could, you know, as an economist, you can kind of go between these two things that you'll find people who are just like pure math, no connection to the real world, just sitting there talking about abstract widgets, and you're like, that isn't me, I want to talk about people, I want to talk about history, I want to talk about, like, our lives, like I want to understand the world we live in, and like economics, lets me kind of do that. But still then like, you know, it's very mathematical. It's very quantitative. Like there are definitely applications to business and industry and government and there's like, I like it because it's sort of so practical, like you get this fun exploring the sort of Social Sciences, like the Frou Frou kind of like oh, we're just going to talk about history for like a paragraph and go into that, cuz I did one thing where I have a paper on non discrimination laws, and I got really annoyed because like, you read these laws and everyone's just like, these laws are all identical. And then you start going into the laws and they're not at all they're so different. Each state in the US brought their own sort of views about how do we regulate discrimination, and you just get these big differences between like what California thinks should be illegal and how bad they think you should punish discrimination. And then you get like Texas and Oklahoma and other states who are like completely different and so you just get these you know, everyone's like, okay, discrimination against older people's illegal but Then how they discriminate how they regulate that is so different. And you know, the quantitative economists were just like, let's just assume all the laws are identical, and the effects of these laws are going to be the same. So you pass the law. That's it, you know, but then I got to be sort of, like, indulge my passion for policy and like, study, how are these policies passed? Why were they passed? Why are some states stronger or weaker than others? What's the history behind this? What's the sociology or the politics? You know, it's vital. Yeah, it's not just the research, but the impact of the research Exactly. You got to do that you got to kind of be an expert on how are these laws passed, but then also have this whole very strong quantitative focus on what did the laws do. And so you kind of marry this qualitative quantitative approach to research and learning and I think that's when economists are strongest is when they don't ignore how connected all the other social sciences are, you know, and it's sort of like, it's like a bit like biology, I think in that like to be a good biologist, you need to understand chemistry, you need to understand physics, you know, just the human body, or life itself doesn't operate in a vacuum. And, you know, economics and business and sort of everything we think about as terms of the economy doesn't operate independently of the other social sciences that said, you need a lot more math that you think you do, but you still then need to have a good understanding of these other qualitative approaches to knowledge. And Was that something that you know, when you went to do economics at university, did you always know that you wanted to focus on the area of kind of discrimination and the politics and the policy side, I actually felt like my first love has always been the history of economic thought that was what I really enjoyed. I loved reading about how do we how did we get here in economics, and it was interesting to me, because all of the history of economic thought is sort of like when you go through it, it's sort of after like, 1950, the entire discussion just ends up being macro. It's all about the macro economy, GDP inflation, the Phillips Curve, yeah, that just doesn't interest me. I am a bad economist in that sense, where I, like I understand it, I've studied it, but like, it doesn't get me going in the morning. Fair enough. Yeah. Which baffles my family, like, my grandfather love him, cannot understand that I don't understand, like, the macro economy at this intense level, like he studies the stock market. He's like talking about all these things, and going into really, he's going into detail. And it's like, I know it, I've studied it, but like, I've also haven't like intensively studied it, since I had to pass the comprehensive exams on that. And like my second year of my PhD, absolutely. So it's like, it's literally been probably seven years now, since I've really done hardcore macro. But like he so he, like talked about, like, oh, what's the stock market gonna do? And you're like, that is not my field. Let's talk about the labour market. Let's talk about like, sort of, what's the effect of this tax change? Great, I got you. But like, it's just one of those fun things where it's like, sometimes you just can't comprehend that, like, macro is literally only like half of what economics is, there's another entire field in the history of economic thought I kind of was like reading these textbooks and like, stopped the 1950s with micro, you know, like, literally, you know, Great Depression onwards, the entire history of economic thought was always about, at least in the textbooks that we were being taught from sort of macro, and then random, we came across Gary Becker. And it was just like, I love I had to write a term paper I did on Gary Becker, sort of how he took sociology, and made it quantitative in the 1950s. And like, he was like the economics of discrimination, the economics of Education and Human Capital, the economics of the family, it just sort of, he literally looked around the world looked at what sociology, anthropology, political science was kind of doing in terms of people and like, the way we lived our lives, and realise that like, you could take this whole marginal benefit, you know, marginal cost comparison, and apply it to everything. Like when you're a parent and raising a child, you have scarce resources, so we can apply marginal cost marginal benefit to an allocation of any scarce resource. So like, let's study the human capital investment into children, like how do you raise your children? How do you allocate as a family? How do we treat the family as a verb? And so it was just reading about how he sort of took these really simple models, and they are far too simple, but this was like 1950s 1960s. So like, we'll give it to him. We'll let them off with it. Yeah. Not to say that there are like, the more you dig into it, the more you're like, that's a really weird way of doing it. And I think that's, you know, Gary Becker was sort of this eye opening experience where you're just like, Oh, I again, it was like, the first time macro click, micro click with me, you know, was like, Oh, this is great. We have this mathematical way of describing how firms operate and how we make choices as consumers. And then it was like seeing Gary Becker, apply that to a bunch of things that you never would have thought about. Like, that was really cool to me. And then I got into discrimination because Gary Becker started discrimination has always focused on African Americans and gender. That was where the focus was probably like, from much of the 1960s until much of the 1980s, I think that was the dominant strand of literature, you start getting in the 1990s, some movement towards other minorities. I mean, the big problems always data, like, you know, you don't get really good data on minority groups very often. So you're kind of trapped by the census cycles. But I remember studying Gary Becker thing, just getting annoyed because I was studying the economics of the household. And so we it was this entire thing about like, how do household allocate resources? And it's always like a man and a woman. And it was like, okay, but like, if you have a gay or lesbian couple, how does that work? How do you and like Gary Becker has like this throwaway line in one of his papers about like, same sex couples, which is fascinating for the 1980s that he was even thinking about this, but it was just like a throwaway line where he's like, yeah, someone's gonna be a man, and someone's gonna be a woman or something like that. You know, Bill, it's as good as they'll orient themselves around some sort of breadwinner norm and go for it. You know, it was interesting to kind of go like, well, is that true? Like, how do they do it, and then that sort of, I got kind of annoyed in my precocious sense of looking around and seeing all these heteronormative things, or all of these sort of, it was sort of definitely the LGBT aspect that caught me to discrimination of just everyone writing these models and then ignoring they were just like applying it to the LGBT community without thinking you just go kind of like, oh, let's assume X, Y, or Z, because it holds true for the African American experience. And it was like, well, that's maybe like, some cases, okay, probably not. Are these assumptions valid? Hard to say? I don't really think so. And it was like, can I do better? And I thought I could. jury's still out if I can do better in the long run. But you know, I don't know. But I think you're being modest there. I mean, yeah, definitely, in that sense, but you know, it's certainly, you know, it got me going, you know, that's the York shooting, not like to beat yourself up. Like, what you're critiquing, like, people who've won Nobel prizes, and being like, we're gonna throw out this model, it doesn't apply. The world moves on know, for sure. But it's still there's something weird to be like, I know better. Like, it's still strange to me to be like, Oh, I'm a world leading expert in something like there's like literally very few people in the world. Yes. So as much as I do, that's still very uncomfortable for me, because you're like, if I know the most about this topic, what does that say about the world? You know, well, it's probably a safe reflection of kind of where because I even think when you were, when you were talking about that, you know, I think about growing up in the 80s and 90s. And then you know, the language about same sex couples or non gender conforming couples and, and how that works. And it was always, always always one of the main ones a woman and that's it. But I think about just in the UK about how recently it was legalised to even be gay. But you know, it's it's everything is so much more recent than I think young people certainly today even realise, because they've obviously grown up with different laws. And it's always been legal. And it's so interesting to me, when I look back at old films, and I always do this little calculation in my head, you know, if there's a gay presenting character of a very old movie, and I always go to myself, like, how many years before or after that was legalised? Was this film made? And if you even just add that into the equation, and think about, like, I'm not surprised that you at your very tender age is, you know, that is, you know, very much the expert in this field, because it's very recent, that, you know, any of these laws have changed. And like I said, the access to data, therefore, is is more available. Yeah, no, this LGB data is one of those things where it's just, I think that's what's held back the field the most. I mean, we didn't the first paper to even look at LGBT individuals in the economic sort of sphere. Let's look at like 1995 like, that was the first time that was published. And so it I mean, it's one of those things where you're like, Oh, well, so what I'm doing my undergraduate and just starting to think about my PhD in like 2011. It's really only been 16 years, and like, between 1995 and that point, there are maybe 2030 papers in the world, on the topic. So it is like, I kind of came into this field when it was quite young. And it's an interesting field because it has sort of, you have this very neoclassical, very quantitative approach to discrimination. That's sort of this Gary Becker of Chicago School. And then the LGBT stuff is kind of coming from a bit more of a sort of feminist, heterodox critiquing the sort of way that Chicago will think about things because Chicago is gonna be very much old school. I mean, it's very rigorous, but it sort of will make a lot of assumptions to make the math look nice. And those assumptions can be quite unrealistic. And the maths is messy. Yeah, I mean, so like, one of the things I've been struggling with is that you always get this in the field. And it's just one of those things where it's, it's such an interesting problem. But it kind of highlights this, it's like, if you don't know if someone's gay, and you have to guess all of a sudden, the math goes haywire. So everyone just assumes that if you're gay on a survey, you tell your employer that you're gay, like, because otherwise if they if the employer has to guess we are in this world of like probabilities and like, people trying to guess but then what are they basing their guesses off of? And how accurate? Are they guessing? You know, if they're systematically wrong, Does that suggest something about their prejudice towards the LGBT community that like, you're always going to guess these people with a separate characteristic are gay, even though that's only true X percent of the time. And it just makes the math absolutely crazy. It's a problem that no one in the field has really been able to solve convincingly, partly because we can all think of a model, but then we can never find the data to actually test it, it's just trying to find people's like, Oh, yeah, I present this way people guess. And then how accurate is the guessing it's really crazy, but it's sort of like Chicago is just gonna be like, and you present gay 100% of the time, everyone knows perfect information, the math that follows, the proof is trivial enough to the reader, you know, and then the heterodox kind of engages with this a bit more, because they think for ly on a lot more narrative, logical conclusions that you don't need to have the mathematical proof, as long as you have the logical consistency of X causes Y, we don't need to mathematically prove it, we just need to show that logically, this follows from that argumentatively. And so it allows you to bring in sociology models into the economics without complicating the math such that, like, you start getting indeterminate equilibrium, that you can't identify in the data. And so that's sort of where the heterodox kind of really allowed the field, I think, to go forward for many, many, many years. But now that the day is getting better, it's been easier, because it's one of those things like you mentioned, you know, in the beginning kind of things being equated to, say, the African American experience and, and let's see much more visible identifiers of people's minority status. So, you know, with ethnicity with disability often, and I suppose now, what's quite interesting, you know, in the next few years, there's a lot more conversations about invisible disability, and how do we quantify, measure and do the economics of that. And I think that definitely sounds to me, like the research, you're doing it in or have done sorry, in the LGBTQ areas, is taking the invisible. And as the generations moved on, as the laws moved on, and people were allowed to be a little bit more open, that the data sets started to appear, but you're so right, in all the things you're saying like, but that doesn't mean the employers knew that doesn't mean that parents and families knew and, and where where the data is being collected is that one person or the identifying themselves in this data set, but not in this data set? Because of it? Or in this? so fascinating? Yeah, I think there's more minorities is something that's sort of at the forefront. Now, the sort of identity is fluid. And like, again, quantitatively economics is ahead of most other social sciences. But when it comes to a lot of like, the theories of identity and sociology, and like, how do people like the human experience, economics is always a bit behind, like, in terms of gender, they're still thinking gender as a binary construct, because it makes the math easier. That's where it's like, it's nice, because it makes math easier, but then you do lose some sort of nuance in the conversation. So like, the gender as a construct, you know, that's binary versus a bit more continuous is something that economics is like barely moving into. And when they do, I think they talk about it along individual dimensions. So you'll talk about like, oh, there's variation in competition amongst women. And so like, that's gonna be there's variation in women, you know, so some, some women are more competitive than other women, but we don't think about like, it's still sort of siloed into men and women, not a continuous spectrum of human experience or expression. That then people you know, sure it's by modal but like you still have movement around. So I actually do have a paper on that, that we're trying to publish It's about what gender nonconformity does to your economic outcomes. Not interested is it? I mean, it started because we were thinking of there's this huge problem with LGBT where the moment you publish work, they see that lesbian women earn a bit more the same or more than heterosexual women and gay men earn less always. And so the moment you see that asymmetry, immediately, people who don't want to think about discrimination, just go Oh, clearly is gender conformity. Gay men are feminine. lesbians are masculine. Because masculinity is rewarded and led market lesbians are more because femininity is penalised. So they market gay men are less soft. And so what we did in the paper was we went to the gender studies literature, and they had some people were making some really big advances in public health, about how do we think about gender performance in terms of, you know, we know there's problems amongst teenagers with teenagers sort of wanting to behave like their peers. So what you'll find is that risky behaviours are highly correlated with gender performance. So people who behave much more like their peers are much more conforming to norms of behaviour, or engage in much more risky behaviour. It's just because you certainly get peer pressure. And so what we did was we took these quantitative measures of gender performance and gender adherence to gender norms, which is this great way of taking this really abstract Judith Butler idea from sociology and thinking, Okay, well, how would that actually work quantitatively? And it's quite brilliant, the people who came up with that. And so what we did was we kind of took that and then we said, okay, if we calculate that measure, and then we try and calculate the gay and lesbian wage gap, does it disappear, because if all of this is being explained by gender conformity, once we know your adherence to gender norms, we should start seeing changes in the wage gap or the wage premium. And that should tell us what's going on. No effect, none whatsoever. On the gay wage gap, I mean, really impactful for wages, which was quite surprising. So like, more masculine men get paid more, more masculine women work more, and then thus get paid higher wages, or earn more not get paid higher wages, interesting, but they work longer hours, they work more weeks a year. And so they have higher incomes, because they have higher labour supply. What I love about these conversations that I am privileged to be able to have with with all of you guys in this in this such interesting field is like I as you're talking about your research to start to think about what are the factors that may so be really interesting, and I'm sure this is covered already. But immediately I start thinking, Okay, well, how does having biological children come into this? How does the increase in adoption availability and, you know, legal adoption in kind of gay non conforming couples? How does that because thinking about it, from the economic side, I do a lot of work with women who've been out of the workplace. And you know, I'll pick because I work in the era of digital skills, and I work with a lot of women who've been out of the labour market and want to come back in digital skills isn't a good in to get them into back into work. And there's such variation in that already, that must also have an impact. And again, the new laws in these areas for gay and non conforming couples does that, what's the impact of that? It's hard to say, only because the sample sizes are so small, you actually have very few gays and lesbians with children, and then getting them in enough with enough geographic variation to identify the effect of laws. So there's been a lot of work on it. I think typically, it increases wages, when you have these laws, and you give people security, the more likely to have children. But it's much more common in the lesbian couples. I think biological technology for gay couples is just sort of like a huge barrier, you know, it's not without IVF, of course, you only have surrogacy or adoption and surrogacy is extremely expensive. adoption is not expensive, but not cheap. So you get sort of a very much differences by class in gay couples, in terms of having children and lesbians is much more, you know, easy. And so depending on how expensive in vitro fertilisation is, you'll see these laws having a lot more effects on lesbian couples, to the point where we're actually starting to get data to be able to study these couples, but it's still extremely new. I mean, we know some things about how the gay rights movement has improved labour market outcomes. But it's, I mean, it's still a very active field. A lot of it is sort of piecemeal, because you're like, Oh, I finally have a data set that covers these people in these years. Let me look at that, but it's speaking to a cohesive whole. I think we know that the gay rights movement has improved outcomes, but it's so new and Yeah, exactly. It's very open for debate. We could all be horribly wrong with our conclusions. And it's just going to take some brilliant grad student to prove us all wrong. Most of the interest directionality of all which, you know, we haven't talked about, and I'm sure it comes up all the time, you know, I just can't imagine how difficult it is to break down this data set that you are watching in real time, my mind blowing as me, like not an economist, sits and tries to unpick all of the contributing factors here. Because, you know, if you throw in like disability, ethnicity, and all of those, and how they impact the labour market, how do you possibly get a big enough data set to look at something just to kind of evaluate the one side of it, you don't often, and that's a big downside. And I think that's something that everyone in the field wants to better on, I think you will find that a lot of this research ends up being extremely Western, extremely high income, and yes, very, very white. And that's just because, yeah, where's the data gonna come from, you get good data in Scandinavia, good data in the US. And you know, who's going to be willing to come out to a random survey person. And even if you have a big survey, like in the American Community Survey, we get a couple 1000 gay and lesbian couples. But again, if you're bisexual, we don't see you because we only see couples status. So we only see two men living together or two women living together. If you're bisexual, we can only classify you as being a same sex male couple or same sex female couple. Yeah, I mean, I'm, I am extremely excited because the UK census asked sexual orientation and gender identity for the first time. And I think that is going to be such a huge contribution to the literature, just because it's one of the first times anywhere in the world, honestly, that we have self reports of this from a full population is really exciting. It is, I mean, it's one of those ones where you just they, and then they tell you, you'll get the data in 2024. And you're like, looking at your watch going, okay? How do I schedule my life so that when this data becomes available, I have time to do these projects, just on that point, I've been reading a lot of stuff recently on gender conformity and, and Asia and South Asia and the communities across the Indian, and how people present and those gender and conforming markers and how different they are in those populations. And, and that to me, well, one, it's just it's just fascinating, a bit like you when you were saying earlier that you're just and endlessly curious about lots of different things. And this is one of the things I kind of find myself curious about recently, is, you know, what are the data sets there on those populations? And also, what's the language of that data set? Because it depends on how that community talks about it. I mean, I'm no, I'm talking to someone you're nodding along, I know that these are the things you've, you've kind of already come across. But it's fascinating, isn't it? Yeah. I mean, it's really always interesting. I think the lack of understanding there are no big datasets with gender nonconforming people in part of the world. Part of it, I think it's just a lot of these countries don't have the infrastructure to do these large censuses. And part of it, I think, is that there's a bit of a disconnect, I think, between the politicians in power and the people living these lives. And in terms of what they want to invest in, I mean, asking these questions is expensive, it is taking up valuable real estate on a form. And, you know, I wish everyone prioritise these, because I make my datasets so much more interesting. But we have a lot of qualitative research from that part of the world. And that's what's fascinating. But then, as an economist, you look at the qualitative research and go, that's great. I can use it somewhat. But like, I can't, I can use it as context. I can use it as narrative structure, but I can't use it as my main analysis. So I'm working on a project right now on transgender people and their experiences with transitioning in scan in Scandinavia. So I have data on in Sweden. And so we're really working on how do you identify transgender people in these large scale public datasets? And it's not easy because you end up having these really to create a definition. You know, you're putting people in boxes, and that is not necessarily the right way to go about it. You know, you have to start making assumptions about people you have to start, you know, and the thing is, they are just a line in your spreadsheet, they and you're trying to take that and turn it into something, ignoring everything about them, that you don't know is. So we're doing a lot of work with that. And I think it's been really interesting because I think what was surprising to people when we presented some of our early results, was how their preconceptions of what the transgender community looked like in Sweden when we were talking to Swedish care providers, with slightly different than what they were expecting to see. And a lot of it was quite surprising because when you have this full population, we No, everyone has been diagnosed with gender dysphoria by going to a gender identity clinic, between 1987 ish, we have some data earlier than the 1980s. But it's very, very, very few people, and we have them going to 2017. It's a huge dataset, I mean, we have from the moment you are if you were over the age of 18, so Adults Only if you go to a gender identity clinic, we see your entire transition journey from your first diagnosis with gender dysphoria to when you change your legal gender, if you change your legal gender, we were shocked at how few people change their legal gender, we thought it would be much higher. Because in Sweden, you actually have this thing where your national insurance number is gendered, if you know someone's National Insurance number, you know, their Natal sex. So, you know, you have this huge, yeah, but so if you are transgender, and you that is not your gender on that number, every time you go, you were presenting one way and everyone looking at your forms, you can't hide it to anyone who knows your number. So we thought you'd see a bit of a much higher percentage of people going through this process. But it wasn't, I think our early results are suggesting it's about 40% are going through the full process. It does take time. So we've had a huge I mean, what's fascinating to us is how rapid the increase in the transgender population has been. And I think you see that everywhere in the world, that just acceptance has allowed people to engage with the transition process a lot more. So it's not to say that these people weren't transgender, when we couldn't see them, just we only see them the moment they enter the, the register for the for the NHS in Sweden. So we see when you start seeking treatment, and from then we can say, Okay, well, this is a approximation of the community of people who are gender dysphoric and seeking care to change their legal gender. I also wonder and I don't know if this is the case in Sweden, obviously, the National Health, there's a health service. But when you're looking at these datasets, also taking into account people get those, you know, access to HRT, or testosterone, depending on which direction you're transitioning for want of a better term, you know, not always through legal means, or not always through traditional means. So where do those datasets go? Yes. So that was something we've run into and have been trying to struggle with is that if you are higher income and start using private insurance, or going abroad for care, we don't see that ensue. You know, when you have sort of just the way government collects data defines identities in a way, it's quite fascinating. That if you have to use, you know, like, we don't, the transgender community has never talked to the government in Sweden about how are you collecting our data? How are you defining us? It's just all these sort of backdoor paths of like, Oh, well, you know, because we have all these diagnosis codes. If you go to the doctor, the doctor has to say why you went to the doctor. So we can approximate the population using this, I think that's what the UK census is going to be so important for is because it's not a backdoor path, it is people, the community saying here is who we are, I think it's one of the first times you're going to be really able to look at a full population, and tell their stories, because they've told you who they are, you know, you don't have to guess you don't have to assign someone into a category. And I think that's what's really exciting, what makes me feel so warm and fuzzy like, because knowing like my friends who you know, identify as gay and bisexual and lesbian and, and how, I mean, as we've already touched upon how much of their lives, even going back 10 or 15 years just wouldn't have been reflected or represented, even if they were open with everyone. There's so much about government policy and what they're allowed to do legally, and how they're represented within the population that just isn't there 10 or 15 years ago, and honestly, just makes me quite emotional thinking about it and thinking about, it's a small thing, but it's also such a big thing. It's one of those things where it is really fun to do this research, and then talk to the community and then see their reactions to your research. Because a lot of people it's always funny, everyone kind of people who aren't mathematical, don't think in distributions. And so people always forget that there's like an average effect. And then around that average, there's a distribution. And you could come from any direction of average, on anything, and it's not, you know, there is no like the average LGBT member of the community is not a single, it's not a person like you cannot find someone who's perfectly average on everything. You're going to be weird in some dimension, you're going to be an outlier. So it's always funny when you're like, my friends, look at my work and then see themselves somewhat, but then they always go well, that's this one assumption you've made doesn't hold and or that one thing doesn't hold it. That's a gross simplification of the process. And you're like, Yeah, but like, if I don't do that, I can't then get to this analysis. So like, just bear with me, guys. It's close enough. But it's Yeah, I'm trying really hard here. Yeah, I mean, the thing is, you have to be very careful. And I think this is where we have done a lot of work with transgender community to make sure that the assumptions are realistic, the we understand the process, we know how they approach the process, I think, you know, it's in a social setting, you can be a bit more flippant with your friends about some things, but like, you know, in a, when people are going to read your work, and it is going to influence government policy, it is you do have to be very careful, yes, it's impacts real lives. But it's, it's fun to have your friends see themselves in that process, and kind of understand things because I think that's what this is where I always encourage people who aren't sis white male, you know, to really think about an explore science, because everyone's like, Oh, it's mathematical. Like, it's, there's a natural truth, and we're just scientists seeking it. But a lot of it, and I think this is something where I was teaching, I was teaching the other day, and one of my students came up to me and started complaining about the course, because he's like, because every time you make us read a paper the entire time, it's like, because the first 75% everyone is so confident in what they're doing. And then everyone spends the final 25%, saying, Here's why everything that we've talked about could be horribly wrong, trust me, it's still fine. He's like, because it just kills your confidence in it. And it's like, but I think that section where you go through Oh, what are the mechanisms that underlie this? What are the assumptions? How realistic are the assumptions? I think that is where people marginalised communities make a huge impact on science is that, you know, it because the fact that we're observing, so like, if we say that this law change, increased wages by 10%, that's kind of what we can say, and we can do some work in the data this to the kind of the candidate possibilities for what caused that change, like, we know the policy led to that change. 100%. But we don't know how the policy led to that change? Is it because workers changed their behaviour? Is it because employers change their behaviour? It's because families changed their behaviour, you know, is it because you know, two or three of these lovers bully, it's black box. And so where's social scientists from non marginalised communities get in trouble when they do this research I myself have been guilty of this with transgender research, is, it's a black box, and you just go, it's a black box, and then you start talking about various things that could potentially be going on to the black box. So potential mechanisms, you know, if this is the case, we kind of expect to see X, Y, or Z, you know, we see some of that, but it's not perfect. But when you show it to someone from the marginalised community, they immediately go, not that one, not that one, maybe this one, that one's pretty likely, I've experienced that one. And they kind of just, they know those lovers. They've seen them, they've experienced them, it just sort of it makes you a better scientist, just be part of the martial arts community and studying it, definitely, I think there is a bit of a, what you do find in economics is that a lot of times people say, Oh, well, if you're a member of that martial arts community, you must be interested only in the economics of that community. It's, you know, I think that's not the right path to go down to kind of force these people only to study that. But like, their comparative advantage, if we want to talk about economics is in understanding those mechanisms, like they're better and smarter than the average person, not of that community, when it comes to understanding these mechanisms, just because they lift these mechanisms. So the insights that the community can give you, I mean, it saves you so much time in agony going, is this the answer? Is that the answer? You just go? Let me talk to these people, like economists have this aversion to talking to people? You know, I think we in the transgender work, that's been one of the joys I've had is to talk to the community to show them some of these results and get their feedback, and have them tell me what's going on, you know, is that sort of where they don't know how to do the analyses, but they certainly understand the mechanisms, the sort of policy sphere, and when you show them the your model of their experiences, they know is it real or not real? They know where have you probably sort of, they just know a lot more than you do all along. These sort of this is where the art of research comes in. And that's like, where they can help you a lot. Like think you know, and so, I think that's been fascinating, but I still think it's kind of cool though. To have citizen scientists in this sphere, and a lot of times, we don't encourage them to engage in that sort of, you know, I think that's where maybe it's less intimidating for younger marginalised people to get into economics if they're studying their own community. But that's not where they should be limited to, like, if you can do this, you can do that next step is not big, like, if you think you can do better than other people study at your community, well, you could be just as effective at studying this other thing. You know, the skills that make you good at that, once you've gained them, you know, from your PhD, are applicable to a wide range of things. And it's so important, and it's that thing of if you're from a marginalised community, and you're involved in research about that community, like you said, you have that input, but then you're also super aware when you go into research and marginalised community that you're not part of, you remember the questions that people needed to ask you, and you can then go out and you know that that you don't assume that you are the baseline, you don't assume that you know everything, because you're used to people doing that to you. jokingly, I always laugh because the reception I get from my age discrimination work as someone who was clearly not have that community. Many, many years listeners, he's very young. I mean, the work I've focused on is typically people who are 65 ish. So just around retirement age and sort of that process of how do you leave the labour market and transition into retirement. And again, it's an invisible minority. So it's coming directly from the experiences and the skills I have in the LGBT community just applied slightly differently. And it's been it's always fascinating, because the people that critique the research, the referees, when we submit papers, if I submitted LGBT paper, the odds of me getting an LGBT referee, very low. I mean, Flynn, yeah, very slim. I mean, it's a bit higher, because they send it to people in your field. So like, the people in our discipline, but they, you know, you don't get it all the time. And so, you know, there's only maybe 50 or 60 of us in the world that do LGBT economics. So some of us will be busy, your paper won't end up with them. And you just get so much more pushback. If I send it to my work on people who were 50 to 65. You know, that range, the odds of me finding a economist in that range, pretty decent, a lot less pushback. It's fascinating, the things that you can get away with, mathematically an assumption wise, when the person doing the critiquing intimately understands their community. And it's just kind of like, the assumptions that people make are kind of like they will buy it when it's talking about older workers. But that same assumption for LGBT workers, there's this visceral reaction to question it proved to me this assumption is valid, where it just sort of skates by with older workers. And it's kind of funny that you just get this extra challenge. It is it I mean, but it's again, because the people doing the work understand the model intimately. So they read your assumptions and go, Okay, this is fine. But when they don't understand it, they kind of, you know, for a very similar model, they just kind of go and no, like you, it could be these X, Y, or Z other things, no matter how unlikely they are, prove to me that still the answer that this can't be explaining what's going on where, you know, they already know that can't be the answer for older workers. So they're not going to make you jump through those hoops to prove it is kind of fascinating. And it's like it's an interesting time to be in this field. Oh, yeah, it is. It's it's brand new. I think it's extremely young. You know, as I said, 50, or 60,000. The entire world that do this, like we fit into a single ballroom, when we go to a conference, citing you can go to a cocktail hour and know everyone. But what apart? That's great, in some ways, but again, the people involved in this, I mean, they've just made the impact this field has had on the lives of LGBT individuals is huge in an invisible way. Like you don't quite realise the work that the generation before me did in the 90s in the 2000s. Like Lee Badgett The one who wrote the very first paper to do this field. I mean, she was the one writing economic arguments about why same sex marriage should be legal, like what's the economic reasons why we should allow same sex marriage, showing that like this discussion is like, even beyond moral grounds, there are economic reasons, really like this is increasing poverty, this is increasing the precarity of family structures, like the economics of this community is harmed because we don't have same sex marriage. We don't have the stability. So her economic arguments for same sex marriage, I think were extremely influential amongst a lot of the sort of centre centre right. I think in terms of putting it in a language they are going to understand, you know, coming at you broadening the discussion beyond just sort of moral rights to more fundamental, you as a policymaker are increasing power. No one wants to do that, like, and but just the data reports, the policy briefs that they were working on, it's, you know, it was really impactful, it's kind of, you know, it's like you hear them tell their stories, and it's just like, it's fascinating to not be that far away, compared to like, the, you know, I don't want to be flippant compared to the civil rights leaders of the 1960s. But like that, sort of, in terms of LGBT rights, not a bad comparison, the work that these people were doing from the policy standpoint, and it's like, it's not sexy work, it's not going to be front page news, but it's important, behind the scenes, it is extremely influential. And to, you know, to know that, like, I'm one generation beyond them, maybe two, if you kind of take Lee as the person that it is the two people in the 2000s, I came in the 2010s. And then you see people coming after me, it's even more exciting. I mean, the hard part is when they start critiquing your work and saying you did something wrong, 10 years ago, like someone was like picking at like, the first paper I ever wrote, they were critiquing errors, and it saying I'd miss done things. And you're like, no one one thought. I mean, it's funny, because it's like, it's completely fair. He, the author is 100%, right? There are things that I didn't do, but it's just like, that was 10 years ago, child, like, throw me some code and tell me like, you know, like, how much the people you know, it's the thing, it's like, you know, it's now the people that I am talking about, you know, when I critique their work coming in now, and I know them, it's like, oh, my god, did I do this to you? Like, you know, it was like, Is that what you feel like, every time you get thrown back, they can sit back and be like, yeah, yeah, you did? Yeah. I mean, that's just science again, you know, I do something, someone else comes along and says, I did it slightly wrong, here's how to do it better. And it's not a reflection on anything. But it's just when you read it, you still have to, like sit there and be objective, as they critique you in like, no uncertain terms. So personal, like it's so personal, when it's an area that is so new, like you said, there's a handful of people in the world that do it. So yeah, it's everything is much more personal in that scenario. So it's really difficult to separate yourself from it. So with all of the work that you've been involved in, what is it that you are most proud of? And I know that's going to be a hard one? I think the one that I'm most proud of, is this a study of age discrimination in the US, it was, it was the first like, groundbreaking paper I think I ever really worked on. It was so my dissertation advisor, studied age discrimination, probably a bit, you know, back in the mid 2000s. And there are some problems with the field. Like when you study age discrimination, you run into the problem where older workers are, by definition, different than younger workers, you just have huge differences in skills and experience if you can't make an older worker perfectly identical to a younger worker. So there's this famous paper by Bertrand Deval Nathan, where they send out two resumes one white, one black, you know, it's like our Emily and Greg, as employable as location. Jamal, it's very easy when you just have to change a name. But if you want to do that for age, how do you do that? How do you make someone who's 65 had the exact same resume as someone who is 30. And so my advisor had done a lot of work, theoretically figuring out how do you build in this assumption to make them comparable? And so I was then brought, you know, I love running experiments experiments are if I could do them, I would do them all the time. They're just insanely expensive to run. So I got this huge grant to run it, we sat down and figured out how do we do this? So we worked on how do we create resumes that are commensurate with age. So the experience profiles were perfect for what we thought the average 65 person problem we ran into was, like, you know, you start with one thing you think is gonna be simple, and then it just keeps branching and exploding. So we ended up figuring out that ability, the number of years you list on your resume grows with age, but so does the variance in it. So you know, if you're 2525 year olds really only have a handful of experience, you know, as you grow people's experience profiles are much different. You know, some people leave the markets stays, you just get huge variance. So what we do is we made nine different older worker resumes, and then we sent out three resumes to each job and we sent out 45,000 resumes in a year. And then we figured out did they call back the older workers or the younger workers, and it was, I think, you know, it was the paper I think that really showed people. How do you do h discrimination? Well, it's It really I mean, the paper was 150 pages when we submitted it, the appendix is longer than the paper itself, because we just did so much work experimentally showing you how do you do this? What do you need to be thinking about? And I think that that paper, really got people talking about age discrimination again, and it's sort of that discipline, I think of how do you do these resumes? Just it's exploded, you know, we were on the uprise of it. So like Austin, a couple other people were kind of coming back to it in that timeframe, when we're running our experiment. No one's quite come to the number that we did. 45,000 is insane. I had to listen to you. I think it's not that long. I think I did listen to 6000 voicemails where people called in and classify who were they trying to call it? Yeah. I mean, we started that paper in 2013, and published it in 2019. So six years of work. I mean, I think that's what I'm most proud of, and the fact that we're still working with that experimental data, I mean, we're still coming back to it. We have a working paper where we use machine learning to understand the language of job ads, and how do stereotypes in the language employers use on their job ads correlate with discrimination? So I mean, it's, it's a project that's just gone on forever. And, I mean, it's still cool because it will get cited and like, it's been talked about in the Washington Post, The New York Times, PBS got to use it. And I think, I think the crowning moment was, my advisor convinced David demarks, my advisor, he convinced the PBS people we, in our paper, we see that older women are more discriminated against an older men. And we don't quite know why. Because when we just send out resumes, you're a bit limited in terms of it is a very big black box. And one of our thoughts was that a lot of the discrimination we were seeing was coming from administrative assistants, and retail sales for our women as compared to our male occupations of retail sales, janitors, and security guards. And so you saw a lot more female facing jobs. And so older women are a lot more customer oriented, and people oriented in their jobs. And so we thought about, you know, there was a great SNL skit, like, a couple of weeks before we first published in the paper, trying to get news, news people to talk about it. There's an SNL skit about the older female celebrities, and how you transition very quickly from being the leading lady to like the side, I remember this exact sketch. Yes, I will not say that they will that skit because it's not inappropriate, but he got them to air parts of that clip, including the title of the clip on PBS in the US. It was just one of those moments where like, being able to have like an SNL skit correlated with my work is kind of stupid. But it was funny, and it just was like, yeah, or it's like, you know, having my parents listening to NPR on the radio, and then hear my name talked about or like reading the Washington Post and seeing my name talked about. So I think that's the paper I'm most proud of, because it sort of To me, it showed me that I can compete at this level, like my work is really good. I am innovative, where I think I got a I think that paper just really, you know, not to rest on my laurels as it were. But it really, for me, it felt like I had arrived as a professional. When I completed that paper. Amazing. I mean, you're rightly proud of it. And I, I will link to the SNL sketch and warning to teachers and parents listening. It is not appropriate for younger children, but we can link to it in the notes. My final question, just just to finish up, what advice would you give just to teachers and parents who want to kind of present economics as a field to their young to the young person in their life? Because as you probably aware that the kind of impression of what an economist is or what research economist is, or what you guys focus on, is quite different to what most of you do day to day. So what advice would you give to teachers and parents about getting that across? Freakonomics is a great one to be showing kids. It's a bit, you know, pop science. I think it presents economics in that pop science way. But I think it shows you the range of what people are doing in a nice way. For me, if you want to study, how do we allocate scarce resources? I think that's what economics is, is the allocation of scarce resources. And everyone thinks about money as being a scarce resource. But I think the moment you think about other scarce resources, and how do we allocate those scarce resources, I think economics has a bad reputation as being a very imperialist discipline. Because what we will do is we will take anything we want to study economics have in front of it, and go hog wild and like, it doesn't matter if the sociologists have been studying this for decades. We're going to come in and we're going to think we know how to do better, as bad as that is from an academic standpoint, if you're trying to like if you're interested in economics or you're, you're thinking about how do I present economics to people who don't want to study widgets, or they don't want to start the stock market. The thing is, is that economics can be anything. I mean, if you like history, there's economic history, like there's people studying, you know, mercantilism and British taxation and the economics of British taxation in the 1960s. One of my friends, her dissertation was the highway laws of like, 1740 I'm getting I'm butchering this year, I'm so sorry. So but yeah, she so she got to go to the British or the National Archives, and go through the tax records for each individual highway, and studying land consolidation amongst landlords and how that affected highway revenue in the 1700s. Or I know someone in Sweden, Randy hjalmarsson, again, butchering her last name, I apologise, but she got digitised the entire court records of the London courts from the 1800s. Wow. So every person arrested at 1800s was written down, and she digitised it. So she has this great paper about what did introducing juries due to various outcomes, you know, so economic history is completely valid. I mean, you have, if you'd like to study the environment, there's environmental history, environmental economics, it sort of economics is a toolkit that you use to study a social science, you can come at it, if you were interested in something, there's a way to take economics and apply it to that. I think you study economics, because you want to study social sciences, and you'd like math, I think that's the joy of economics is that it is the quantitative social science, you'll get very similar flavours in quantitative sociology or quantitative political science, like the difference between quantitative sociology and economics at times is very narrow. So like, it's certainly valid pathways there. But in terms of, you know, being a very wide field, that you can use the toolkit to study, anything you're interested in. I think that's what economics gives you. And, you know, I think my mother's perspective, why she pushed me into it was that economics makes a great career, because it's so versatile. Like, you can have this passion for economic history, and still gain all the skills that you need to have a career outside of history, you know, and so you sort of don't shut any doors when you take economics because you're so quantitative mathy, and you're still very much oriented in social science. So I think that's how you get kids interested in economics is that you just show them the breadth of what economics has to offer, which is what I love about this podcast, because I think you're talking to people from a wide range. Yeah. I'm very lucky. It's fascinating. So basically, what we're saying is listen to Mrs. Byrne, she gives good advice. It's not Don't tell her that. I mean, it's your mother's always right. So children, listen to your mother. Yeah. There's a lot of people listen to this going, No, my mother's know always right. I know. This very one thing she was corrected. So I thank her a lot for that. Amazing, amazing, thank you so much. I mean, as you can tell, I could probably talk to you about all of your, you know, all of your work for a long time. And I'm hoping that we get to do another series that we can invite everyone back, and possibly get some questions from teachers and students, so that we can really grill you. If you'd be willing, if you'd be Oh, totally. Thank you so much. It was wonderful. Thank you so much. And that's that for that episode. Thank you so much for listening. We hope you enjoyed it. And if you want to get in touch with any questions, please visit our website, discover economics dot code at UK, where you'll also find loads of useful resources. And if you've enjoyed the podcast, remember to go to Apple podcasts rate and review. Also remember to subscribe through whichever podcast app you're using to view. Always get any new episodes as soon as they're published. See you in the next episode.