This episode of Economics Explored analyzes Australia’s new gender pay gap data reported by large companies. Are the data useful or are they nonsense, as some critics have alleged? Host Gene Tunny interviews Dr Leonora Risse to discuss the methodology, findings, and criticisms of the report. Risse provides context on factors influencing the gender pay gap, like occupational segregation. Tunny and Risse also debate the impact of societal norms and long work hours or ‘greedy jobs’. While acknowledging limitations, Risse argues the data highlights the need to address remaining gender inequities.
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About this episode’s guest Dr Leonora Risse
Dr Leonora Risse is an Associate Professor in Economics at the University of Canberra and a Research Fellow with the Women’s Leadership Institute Australia and serves as an Expert Panel Member on gender pay equity for the Fair Work Commission. She formerly held roles with the Women and Public Policy Program at Harvard University, the Australian Government Productivity Commission, and RMIT University. She earned her PhD in Economics from the University of Queensland. Leonora is a co-founder and former National Chair of the Women in Economics Network (WEN) in Australia.
What’s covered in EP230
- Introduction to the Episode and Topic (00:36)
- Overview of Gender Pay Gap Data Reporting (02:59)
- Calculation and Implications of Gender Pay Gap Data (04:48)
- Insights on Compositional Factors and Industry Dynamics (16:28 & 16:41)
- Critical Analysis of Gender Pay Gap Reporting (33:29)
- Claudia Goldin’s Work and Nobel Prize Discussion (41:02)
Takeaways
- The new gender pay gap data reveal significant disparities across companies in male and female median earnings, with factors like occupation and industry composition playing crucial roles.
- In Leonora’s view, transparency in reporting pay gaps is crucial for raising awareness but also poses some risks of normalization and misinterpretation.
- Leonora argues societal norms and gender biases significantly influence occupational choices and bargaining power, contributing to the gender pay gap.
- Future research and data analysis are essential for understanding the drivers of the gender pay gap.
Links relevant to the conversation
Link to WGEA Data Explorer (can look up each company’s pay gap and other gender equality statistics)
https://www.wgea.gov.au/data-statistics/data-explorer
Leonora’s Twitter exchange with Senator Matt Canavan:
https://twitter.com/leonora_risse/status/1762395543366717877?s=20
Gender wage transparency and the gender pay gap: A survey
https://onlinelibrary.wiley.com/doi/full/10.1111/joes.12545
Do Firms Respond to Gender Pay Gap Transparency?
https://onlinelibrary.wiley.com/doi/abs/10.1111/jofi.13136
Pay Transparency and Gender Equality
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3584259
Claudia Goldin
“Career and Family: Women’s Century-Long Journey toward Equity”
https://press.princeton.edu/books/hardcover/9780691201788/career-and-family
Leonora’s book review in Economic Record (copy attached)
https://onlinelibrary.wiley.com/doi/epdf/10.1111/1475-4932.12716
Leonora’s Conversation article on WGEA pay gap data
Transcript: The Gender Pay Debate: Understanding the Factors Behind the Gap w/ Dr Leonora Risse – EP230
N.B. This is a lightly edited version of a transcript originally created using the AI application otter.ai. It may not be 100 percent accurate, but should be pretty close. If you’d like to quote from it, please check the quoted segment in the recording.
Leonora Risse 00:04
The risks and opportunities of publishing pay gaps transparently. It does come with potential risk of misinterpretation. It even comes with the risk that some people some employers might look at this list and go you know what? Yes, our gender pay gap is pretty bad but so are all the other companies in our industry and it normalises it and it legitimises going, you know what we’re not that out of step as it is?
Gene Tunny 00:36
Welcome to the economics explored podcast, a frank and fearless exploration of important economic issues. I’m your host gene Tunny. I’m a professional economist and former Australian Treasury official. The aim of this show is to help you better understand the big economic issues affecting all our lives. We do this by considering the theory evidence and by hearing a wide range of views. I’m delighted that you can join me for this episode, please check out the show notes for relevant information. Now on to the show. Hello, thanks for tuning into the show. In Australia, big companies have been forced to disclose differences between male and female median earnings. The Australian Workplace Gender Equality agency published its first set of gender pay data in late February 2024. And these data have prompted a fierce discussion. Do they show a real gender pay gap that we should be concerned about? Or are the figures nonsense as some prominent critics argue? Joining me to discuss the data is returning guest Dr. Leonora Reese, Associate Professor in Economics at the University of Canberra. She’s a research fellow with the Women’s Leadership Institute Australia, and she serves as an expert panel member on gender pay equity for the Fair Work Commission. Previously, Leonora has held roles with the women and public policy programme at Harvard University, the Australian Government Productivity Commission, and RMIT University. Leonora is co founder and former national chair of the women in economics network in Australia. As always, please let me know what you think about what you hear on the show and about ways that I can improve it, including suggested topics and guests. Right? Oh, we’d better get into it. I hope you enjoy my conversation with Dr. Leonora Reese on the gender pay gap. Leonora thanks for joining me again on the programme. Thank you, Jane for having me. Oh, of course, it’s a big week in your field of research, which broadly is, am I correct in calling agenda economics? Right. Okay, great. Because there’s been a really interesting report that’s been published by the Workplace Gender Equality agency, which is an Australian government agency, and it’s on the gender pay gap. And what it does, it reports the gender pay gaps for one of the largest companies in Australia. Can you tell us a bit about it, please?
Leonora Risse 02:59
That’s right. So this is new data that’s now been publicly released. It’s the gender pay gap for all private companies in Australia that have at least 100 staff. So this is not just a sample, this is every large company. And they have to report this data to the agency to Weijia. Anyway, and this is the first year that this data is now publicly available. Previously, companies could voluntarily share this data, they could share the size of the gender pay gap. Now it’s mandated and that came about through reforms to the Workplace Gender Equality Act. And the idea is that this transparency, this openness of information, is designed number one, to raise awareness and attention and get people talking about the existence of the gender pay gap, which I think has achieved, we’ve ticked that box. And then secondly, to really focus attention on what do we need to do to narrow this gender gap? And how do we understand the drivers behind it? Yeah,
Gene Tunny 04:10
look at certainly started a conversation and in terms of reports of data, so economic or financial data, I can’t think of many others that have generated so much discussion and debate and, and controversy and really strong opinions as this one. So it’s, it’s been quite extraordinary. I must say that. So you, you mentioned private companies. Do you mean companies in the private sector? Is it publicly listed companies traded on the stock market as well? Or is it
Leonora Risse 04:41
I think it’s to the exclusion of the public sector that doesn’t include the government but they have other reporting? Right?
Gene Tunny 04:48
Okay. So it’s the largest companies in Australia and they’re required to disclose this gender pay gap and how do they calculate this gender pay gap? Yeah, so
Leonora Risse 04:59
there are various Ways to calculate the gender pay gap, although most, most of them you still see this, in fact, all of them, you still see a gender pay gap. What this particular data is based on is what we call the median. So like the midpoint of salaries that men are earning in a company, compare that to the midpoint, the median of what all women are earning in a particular company. So within the company comparison, if people are curious to know, what is the median compared to the average, the median is a way of controlling for some of those really extreme values, like very, very large values that can skew or distort the data. So we control for that. So you can’t say all this data is being pushed off or distorted by some extreme values, because statistically, we try to control for that this data also does not include remuneration of CEOs. That will be coming in future years. So it’s not being skewed by say, an over representation of men at CEO level. And it is disaggregated or so according to male concentrated industries, and female concentrated industries, and more what we would call more gender balanced industries. And what we see is that it’s in the male concentrated industries, where this overall gender pay gap seems to be the widest, you asked also how its measured. So this is annual salaries. And it’s includes full time workers, of course, but it also factors in, say, part time workers by working out what would be the annualised equivalent of those work. So it’s not skewed towards, you know, still just a segment of the of the workforce and excluding part time workers as well. Yeah. So
Gene Tunny 07:00
if you’ve got somebody who’s working for simplicity, they’re working half time, they’re only working two and a half days a week, then you would double their, what their earnings are to get a full time equivalent earnings. So
Leonora Risse 07:15
effectively, yes, yeah. And also a real added bonus to this data is that you, you have base salary, so you know what your standard salary would be for the year. And then it also includes a calculation which they’re calling total remuneration. And that’s where you factor in overtime payments, bonuses. Extra commission, for example. And when we factor that in, that’s when the pay gap tends to the gender pay gap widens even further, that extra layer of information. And
Gene Tunny 07:49
so it’s reported as a percentage. So one one that stood out to me is and was widely reported Jetstar, so the budget airline carrier in Australia, that makes huge amounts of money flying Australians to barley, among other places, 53.5% pay gap or something like that, if I got that right. Now, this is where I want to get into a bit of, you know, we, it’d be good to sort of ask, I’d like to ask you about the methodology and to what extent is, is giving us reliable estimates. Because like, that must be, that must be because pilots are disproportionately male, and the cabin crew is disproportionately female. So there are compositional issues there that will make it you know, when we interpret this data, we have to consider those sort of things. So yeah, I’m keen to get your thoughts on that. And also what really stood out to with this data, what do you think it really tells us? What are the highlights? What can we read into it?
Leonora Risse 08:51
You’re exactly right, Jane, that this number, this percentage, reflects a combination of different factors that feed into that. And one of those factors is the composition of the workforce within a company. So I’ve heard many people give the example that the aviation and airline industries tend to be characterised by on average, having more men in the roles of pilots or engineers, which tend to be higher paying roles, and proportionately more women, say in the administration or flight attendant roles, which tend to be relatively lower. So I think that’s great that people have picked up on that because yes, that’s one of the reasons there’s different composition. And instead of saying, well, then there’s no such thing as the gender pay gap that gives us reason to pause and think, Well, hang on, why do we see such stark gender patterns exist? Why aren’t more women being attracted into or working their way into into pilot roles? Why aren’t more men attracted to being a flight attendant so that already starts prompt us to think how are those factors conditioned by societal norms, gender biases, gender stereotypes, gender barriers to women going into fields that are traditionally male and vice versa as well. But then that compositional effect we know from other research, academic research that people like myself and many other economists in the field have carried out is that that’s not your complete explanation. So we use other data sets. And I think, over time, we’ll be able to dig deeper into this big data set, because the beauty of it is that he collects a whole bunch of other information about all these companies where we can plug that into our models and start to decompose, we’ll unpack and use decomposition analysis to figure out what are the contributing factors. So you might still see that even in the same sort of occupation, where you have men and women, so for example, say university lecturers, we know there are still pay scales, we know there’s still opportunity for some university lecturers to negotiate for a slightly higher pay, very high pay, then, then others. Because there’s still room for bargaining, there’s still room for negotiation, even if your job description on paper is the same. Often that’s perpetuating an existing salary that someone brings from a previous employer. So they say, This is what I was paid at my previous organisation or my, my previous company, someone might put that forward as that their their case for saying, This is why I should be paid more than my colleague, because this is, this is what I’m worth, if you need to attract me to this role, this is what you’re going to have to pay me not saying that’s valid or legitimate. But that’s some of the everyday realities of how these these gender nuances factor in. And it also speaks to the cultural norm or the societal expectation that it’s more legitimate for men to be more assertive in bargaining more so than women. And it’s very well to say, women, you just need to be more confident when you when you bargain, or, you know, put your facts on the table and say, I deserve a pay rise. But what’s really fascinating is that the research, including behavioural research in this space suggests that that can still be a really risky approach for women, because it’s not a society as societal norm that women demonstrate that behaviour. So it’s it doesn’t always work. It can backfire. Yeah,
Gene Tunny 12:43
I think we chatted about that in a previous episode. I might link to that because I thought that was a good conversation where we went over some of those factors. Can I ask you about some particular companies now? Hopefully, I got Jetstar. Right. Look at what please do just in case, because I don’t want to accidentally defame Jetstar and then have them sue me. But yeah, but I guess this does raise public relations issues for companies and some companies must be pretty annoyed at what the findings are. So that’s a median gender pay gap on base salary for Jetstar group are 53 and a half percent. And now we’ve got a median gender pay gap for total remuneration of 43.7%. So that’s when they factor in is that bonuses or overtime, then that narrows a little bit? Not, you know, it’s still it’s still significant. And it’s got to do with those compositional issues? Or, you know, that’ll that’ll be a big part of it. What are some of the other companies that stood out to you, Leonora?
Leonora Risse 13:41
Oh, I think you’ve got to have good reason to pick on one company than another. But I look at one observation, I think, is that there weren’t there weren’t really big surprises. For me, I have to say in this data, like we’re aware that there are some quite extreme gender pay gaps amongst some of these companies. I think it was to be expected that in some of these traditionally, male companies like transport and Postal Service’s warehousing, that suppose some of those gender pay gaps are quite stark, because it’s, it’s, it’s harder for women to work their way up the ranks in those companies. But then you also see these gender pay gaps still exist across even female concentrated fields like health care, social assistance. So it’s still it’s still pervasive across all of these, all of these industries. I do see some commentary. I think Dan zippers article on the ABC pointed out that some of these companies that have very large gender pay gaps are companies that perform ought to be being supported or catering to the female client group. You know, they they gave the example of some fashion retailers that, you know, really specialised in producing products for women, and yet they have this big gender pay gap. So that’s goes to show I think that some companies, it’s not all what it seems to be. And especially with the International Women’s Day coming up, I think what would be great is if you see companies that are saying, Yes, we support gender equality, and we’re having an International Women’s Day event will go and check their gender pay gap and see if the rhetoric stacks up with, you know, what are some of the dynamics in their company? Again, you don’t know, we you can’t make judgments just based on that pure number, you want to sort of go under the hood and figure out what’s going on? Is that compositional effects is that is there pay inequity. But all the companies also have the opportunity to provide what’s called an employer’s statement on the Wiggio website. So they’ve got a voice to then explain. This is why we have this percentage pay gap that you see. And it’s also a platform for them to explain what actions what policies, what new strategies they’re going to implement, to do something about it.
Gene Tunny 16:28
Okay, a couple of things. I’d like to pick up on there or ask about that. Company. You. You mentioned, the athletic leisure wear company, that’s Lorna Jane. I imagine
Leonora Risse 16:41
that’s the one that was mentioned. Right? Yeah. Dan Zephyrs article. And I think
Gene Tunny 16:46
I saw they had a law firm, did they have their lawyers say, if you’re going to talk about us in this regard, you’ve got to bake, you’ve got to provide the context or whatever. I’ll try and find that article and put it in the show notes. Right, I
Leonora Risse 16:58
think, I think it’s an example of companies feeling the pressure, which is partly what the intention was of these new reforms is to put the onus on companies to at least explain what’s going on and then try to take action. The whole logic behind this pay transparency is that companies care about their public perception. They don’t want to be caught out or perceived as being inequitable, presumably. And these reforms are meant to, I guess, prompt attention, but also give them a chance to explain and an act. So it sounds like you know, some of the ways that the companies have responded is a signal that they they do feel pressure, they are worried about reputational damage. And so the thinking is that that could be an incentive, I would like to also balance that by saying you do have a fair number of companies on this list that have a really narrow gender pay gap in some, and some have ones that are reversed the other way and are in favour of women. So we have examples of companies that are achieving gender equity in PE, what can we learn from those companies? What has worked? What is it about the culture or the practice or the industry characteristics that has given rise to these narrower gender pay gaps? And can we learn something from their experience that can be transferred to some of these worst performing companies? Or is there something really unique and an ongoing and particular struggle or challenge for some of these industries that have perpetually high gender pay gaps? What extra attention or investment do we need? So that these particular companies that are struggling can can improve over time so that how do we be constructive about this rather than just treating it as naming and shaming and like a punitive measure?
Gene Tunny 19:09
Yeah. Do you remember the high level figures? I might put them in the shownotes? Because is it about is it half of the companies have a gender pay gap, favouring males and there’s a like 30% or 40% that are sort of in where there’s no real difference statistically, and then there’s 10% that are if I got that wrong, you’ve got the figures, well,
Leonora Risse 19:30
they those percentages that you’re quoting yet that they are available, the numbers we’re looking at here. For a start, let’s give people a sense of what that reference point is. So a gap of 14.5% That’s the median across all these companies based on base salary, and if we add in bonuses, etc, then it widens to 19%. What we did in This article in the conversation as we calculated how many of these particular companies were kind of in the upper range the spectrum, right, so you’ve got almost 5000 companies on this spreadsheet on this list. So almost 1000, so around 20% have a gender pay gap that exceeds 20%. If we keep going further and further to the worst end of that, that list, 350 of them have a gap of over 30% gender pay gap of over 30%. And then you’ve got 100, at the worst end, where the gender pay gap is greater than 40%. You’ve also got quite a number of companies at the other end that have gender pay gaps that come negative. Yeah, it was, that was a little surprising as well, I guess, you know, in a good way, perhaps. But what we saw is these are particularly concentrated in Health Education and Disability Services where you have proportionally more women in those industries or those companies already, and therefore, your senior roles and more likely to be women. And also they’re just generally lower paid. So you might have a gender pay gap that mathematically comes out looking like women are being paid more, or in more of the senior roles. But compared to the other industries and sectors is an absolute sense. They’re all a bit lower. Yeah. So
Gene Tunny 21:31
they’re about 1000 companies. So that’s 20% of the 5000. And what you found is that they’re mainly in health education, Disability Services. So I’ll put a link in the show notes to that. And that’s getting to that point you were making. As part of like, there is value you see value in this data, because it can allow further research into what could be driving gender pay gap. So I’ll might explore that with you a bit in a moment. Because it just seems to me this issue of the composition is it’s a big deal, the, you know, the importance of the composition of the workforce. And I wonder if have they got enough warnings on this data? Do you think that they explained the data well enough? Do we shoot should this be up in lights, this is just, we’ve got a really simple, straightforward way of calculating this. There are all these other factors that are involved. So just be careful interpreting this data, give the maybe give the don’t sort of jumped to the conclusion that this company is discriminating against women. Is that clear enough? Or does that need to be clear? Look,
Leonora Risse 22:39
I think people’s reaction is a sign that they’re curious to know those answers. So companies can publish their their workforce profile, you know, in their annual reports, you know, they can publish this is this is the gender composition of, you know, our pilots or flight attendants, nothing stopping them from publishing that type of information either. And, indeed, Weijia does collect a lot of other data and statistics from companies that also reflect gender equality indicators, not just just pay. So it is in that data set, and I think, which is very research oriented and evidence based. So they will be looking to dig deep into that data through an analytical lens to you know, make sense of this. It means some of the policy implications could be okay, what are we doing in schools, and training to encourage more women will not just encouraged but support more women into aviation and airlines, and to ensure they thrive and succeed and feel respected and don’t don’t encounter sexism, which is, you know, currently still still an issue. So that in the future for these companies, they can say these compositional effects. We are acting on that, in terms of this, this pipeline, and also retention and career advancement. Of course, once once people are in the company. I think one one big takeaway, a positive takeaway from having this data out there is that we know that there’s a lot of backlash and resistance and scepticism, there’s no such thing as the gender pay gap. As someone working in this field. I hear that all the time. People feel like it’s not justified. It’s not it’s not warranted that you know, it’s against the law to pay women less than men. So really, this is all just an accounting trick. I heard that response in that comment, those comments and they flared up again, obviously, I think when you look at this data, this is these companies missing, saying yes, we have a gender pay gap, but the companies themselves are reporting This number. So you can’t really dismiss an argue and saying there’s no such thing as a gender gap in earnings basically, because the companies themselves now have publicly declaring that they do. So at least that gets us, you know, one step further along in this ongoing argument or case that we, you know, up till now, a lot of our time and energy is spent just simply trying to verify that there isn’t gender passion in earnings, a gender pay gap, partly due to composition, partly due to a whole lot of other factors. At least the companies themselves now are on record is reporting publicly, yes, this is the gender pay gap in our company.
Gene Tunny 25:47
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Gene Tunny 26:22
Now back to the show. So in terms of the criticism, so you you mentioned this, there has been some very strong criticism. And some of that has come from economists. So well, at least one prominent economist Judith Sloan commentator at the Australian former commissioner Productivity Commission. She has been on various boards. And she said that it’s nonsense. She thinks that it’s not comparing like with like soy, because you’ve got. So I’m just wondering, is there a way that they could do this? So it’s just not this one indicator where we’ve got these compositional issues? We’re not comparing, like with like, would it make sense to, like have a narrower, like habit for specific occupations or particular types of work in the company? Would that be? I mean, that could be a better way to do it. And it could be less controversial? Because I think it’s like, I like data. And I think this is interesting in terms of public conversation. This is it’s quite extraordinary. I mean, my mother’s actually contacted me about this, with her thoughts on it. So that’s an indication of how wide the reach. I mean, not that I mean, she does follow current affairs and all that, but usually she’s not getting in touch about the latest economic report. But this time she has because it certainly has. Yeah, it’s really gripped people’s attention more than any other report in recent times. So yes, I’m just wondering about that, whether there’s a better way they could present the data, or, you know, just more just make it clear. Yep. This is just be careful. Don’t read too much into this at the moment. We need, you know, you really need more data than this to make judgments.
Leonora Risse 28:15
Yes, look, this is the first year this data has been published. And even I put in a submission to the Workplace Gender Equality Act review, highlighting what some of the overseas experiences were about the risks and opportunities of publishing. pay gaps transparently. It does come with potential risk of misinterpretation, it even comes with the risk that some people some employers might look at this list and go you know what, yes, our gender pay gaps pretty bad, but so are all the other companies in our industry and it normalises it, and it legitimises going, you know what we’re not that out of step as it is, so we’re not that different from our competitors. So you’ve got all these potential risks around this. And I think you’ve you have articulated one there as well, but just with one number, people might dismiss it because they don’t feel like it adequately explains the whole picture, and therefore they disengage, and they put down and criticise the whole effort based on that reaction, so you kind of you kind of can inflame or agitate people because they might be a bit sceptical to begin with, or quite unsure. And this can push them just to disengage and spread rumours or misinterpretations or myths about inaccuracies and how to interpret the data. So I think you are pointing towards the fact that I think what people are searching for is a more complete explanation. That takes into account some of these compositional effects. That’s where economists come into the picture. So how do we how do we communicate I hate that in a way, and how do we build trust in the public to say, look, these methodologies, these analytical processes, they might sound technical, but you, you have to trust some of the way that we do this analysis, because we have rich data sets, like the Hilda survey that I’ve used previously, ABS data, where we can unpack and we don’t want to come up with ideologically driven inaccuracies in how we interpret it, that’s not really helping, because we’re not going to solve the problem if we, you know, diagnose this incorrectly. So, in terms of our role as scientists and evidence based and data driven, professionals, we have to treat this data, right. So I think the capacity is there to unpack it and to relay that interpretation and that story, to the general public and to decision makers and employers and employees. One example could be here is that, you know, there will be some employees of these companies that look at that data. And, and want to understand why there’s a reported gender pay gap of that magnitude, and want to understand what’s driving it. So should they be entitled to more pay? Or is it because they happen to be in the occupational category that’s relatively lower pay, I think employees deserve to have that type of explanation, as well, so they don’t lose morale. So they don’t feel underappreciated. Hopefully, there is there are opportunities where employers do pick up on where there are some gaps that can be can be narrowed. So I think it’s in the interests that we get the diagnosis. Right? Look, one thing I would also say with the analysis, and when when we run these econometric models, and we plug in all this data, what we can use are these decomposition tools that will tell you this is the component of that overall percentage that can be explained by industry confidence, or occupation, composition, or can be explained by that particular industry. Or it can be explained by educational background, for example, that’s something that works in favour of women, because they have overall average higher education levels. Something that is attributed. What part is due to more experience in the workplace and women on average, having more time out, we can actually get a grip on all of those percentages. I think where there’s also controversy is where people say, well hang on, is that, is that by choice? Or is that because of societal insufficient or cultural norms that that’s happened. So that’s another point of contention, where some very liberal thinkers will say, Well, yes, that can be explained by women going into lower earning occupations are spending time out, but that’s their choice or their preference. But then I think sociologists and other types of economists will, will contend that and say, No, actually, that’s not that choice isn’t made in a vacuum, that choice is made, because the full suite of opportunities, weren’t there for that, that person. So I think that’s another point of difference of interpretation.
Gene Tunny 33:29
So just to recap, is it true that the bulk of that gender pay gap can be explained in a way statistically, by differences in occupational choice or, or the industry, they’re working in educational qualifications, and there’s a small, just a small percentage that you really can’t and it’s
Leonora Risse 33:49
unexplained. Look, most of the time, what we try to do in these models is add more and more observable data and variables into the model so that the explained portion expands and that unexplained portion gets smaller and smaller. Now, some of the explained portion can still be interpreted as discrimination, and bias. So for example, you might say, Well, women are more likely to be in some of these care oriented professions, and then lower paid. And so that is one of the explanations for the overall gender pay gap. But then you might say, Well, hang on, what are the gender biases in society that don’t value that workers as much or that that still have gender norms and stereotypes that say that’s a woman’s job, right? So even if it’s explained, it doesn’t necessarily mean it’s free from biases and inequities as well.
Gene Tunny 34:52
Right? Okay. Yeah, yeah, yeah. Yeah, I understand the role of societal norms. And yeah, I think we chatted about that before. So I might put a link back to that conversation. I thought it was a good one. I want to ask about Claudia Goldin because Claudia Goldin, she won the Nobel Prize for Economics last year. Judith Sloan quoted her work in so in Judas article and Judas, because Judas is saying, Well, this is all nonsense, because this is just all yes, you’re not comparing like with like, it’s it’s all just explained by difference differences in composition, different choices people make, and she was interpreting Claudia Goldin to the students is interpreting 40 Golden is saying that the gender pay gap, it’s mostly due to the fact that there’s this premium for long and unpredictable hours and men are more likely to to work those jobs pursue that pursue those jobs, because women are more likely to be care as in they don’t have the Yeah, they, they’re more Yeah, they’re less likely to want to pursue those jobs like as as males, pursue them. So disproportionately, so what do you think about that? As a theory? I mean, what, because I think we’ve chatted about Claudia Golden’s work before or since the Nobel Prize was announced. So would you be able to comment on that, please? Sure,
Leonora Risse 36:20
absolutely. So, Claudia Golden’s. The concept that she’s coined here is, is greedy jobs to reflect these particular jobs in the workforce that demand a lot of you as a worker, to work long hours to be on call on weekends on late shifts, and to be rewarded for that. That’s the important part. So should be paid overtime rates to be fast tracked to promotion to get bonuses in reward for, for being, I guess, more available to your employer, I think it’s partly a symptom of capitalist society as well, you know, to really, to really draw as much of the worker that you can out in terms of their time, their loyalty, their commitment. And so the Claudia Golden’s work brings the gender dynamic into that this concept brings the gender Knight dynamic into that because the way that society and policy is structured is that it forces couples, if we’re looking at a male and female couple should make a choice with as a household as to which of them are going to be that particular worker and be on call, and which of them are going to attend to carrying responsibilities to household tasks at home. So collectively, they’re maximising or optimising their total income and trying to balance, you know, both both spectrums. So the way that gender norms give rise is that it tends to be on average, the male partner who will put their hand up for those greedy jobs. And females who, who would opt to, you know, be on call at home, basically. And so the gender pay gap widens, even on an hourly basis, because this there’s this premium attached with those types of jobs. And they’re rewarded, you know, it’s it’s seen as a positive thing in workplace culture. And so the, my, you know, the way that I interpret Claudia Golden’s work, and she articulates this, I think pretty clearly in her book, career and family is that unless you have gender equity at home, it’s very hard to achieve gender equity in the paid workforce. So as long as there’s some sort of gender division at home, you just don’t have that time availability in the paid workforce. So she’s actually advocating for, for gender equality, she’s not saying this rationalises or legitimises the existence of the gender pay gap, she says it’s a an explanation that needs attention. And that we should be looking at how do we look for ways to reduce this culture of expecting workers to be working such extensive hours and to be on call? How can they be more substitutable with each other, so you know, if you’re not available, it doesn’t matter because your colleague can step in. And she gives examples from the industry of pharmacy, the pharmacy industry where that that is, is a change in cultural practice, and that allowed more women actually to advance in that industry. So that, you know, the action or the policies that emerge from that are ones that start to address that existing inequity in the city. system and steer us towards something that’s more equitable. And I would say also healthier as well. Now, other people might interpret that differently. But I think that’s a very, very, you know, firm and widespread way of expressing Cambodia Golden’s work, I did write a book review of her book, and it’s published in the economic record. Yeah, I’d be very pleased for people to have a read of that and see what see what they think of the points that Claudia Goldin has expressed. And of course, yesterday, Jean, she was awarded the Nobel Prize in Economics, in recognition of decades and decades of work, looking at women’s participation in the workforce, and how that has changed over time, from an historical perspective, right up to contemporary time, so she is a big advocate and champion for working towards a more gender equitable economy.
Gene Tunny 41:02
Yeah, I have to read that book of hers. I read your book review and then read her book. She’s at Harvard, isn’t she? Correct.
Leonora Risse 41:08
She’s in the Harvard economics department. And I believe she was the first female to be tenured as appropriate and reach a professor status at Harvard University.
Gene Tunny 41:20
And you visited Harvard a few years ago. Did you did you get to meet Claudia Goldin? Yes,
Leonora Risse 41:24
that was an absolute highlight. Yes, absolutely. This was before she won the Nobel Prize. But even then, it was a huge honour. She was also very closely involved in the American economics Association’s women’s group, which is the equivalent of our women in economics, here in Australia, so we had a great conversation about that. But what was fascinating, I think, is that she has spent so much of her time and focus, telling this story of how women’s opportunities have changed over time. But effectively, they’re still not entirely a free choice. They’re still governed by, by policy, it’s governed by or shaped by technology. A great example of her work was the economic effects of the invention of the pill, the oral contraceptive, which really, you know, liberated women from a lot of it opened up more opportunities for them to control their their family planning and participate more fully in the paid workforce. So fascinating research over time that looks at what, what factors have shaped women’s opportunities in positive as well as negative ways?
Gene Tunny 42:44
Yeah, absolutely. I’m gonna have to read your work and try to get her on the show one day, for sure. Right? Oh, well, we better start wrapping up because I’ve, I’ve taken a lot of your time. It’s been it’s been really fascinating, good, good having this conversation and sort of delving into this and what it all means. And I think the way that you’ve, you know, you’re making me go beyond what the data, what the exact, you know, the data or just arts industry, its occupation, or think about what’s the other societal factors or norms that are leading to these occupational choices. I think that’s a good point. So certainly worth considering. on that issue of, you know, this greedy jobs, and I think this gets to what, why someone like Matt Canavan, Senator Matt Canavan, an old friend of mine, he’s a Senator for the conservative LNP party, Liberal National Party here in Queensland. And he’s come out very aggressively against this report. Matt’s been on the show before we had a chat about Net Zero. I’ll put a link in the show notes to that. And I think Matt was saying, look, the problem is that you can’t just scale up these jobs, like a point eight, you can’t just multiply it by one divided by point eight to get what the equivalent salary is, and then do a comparison because there’s that premium for the long and, and predictable hours. So that was, I think that’s what his point was, wasn’t it, but that he doesn’t think this exercise is particularly valid at all. And then you had a bit of an exchange with him on Twitter. So could you tell us about what that exchange was about? Please? Leonora? Sure.
Leonora Risse 44:23
So yeah, I mean, again, this is an example of this data, getting people talking, first of all, trying to understand the methodology, how were these gender pay gaps being calculated? So we get a grip on that, and it sounded like, you know, the way you’ve described it there, I think, was a good, good example of then people prompting, or is that the appropriate way to, to analyse this, this data? So I think on Twitter, I mean, I tried to use social media very mindfully and simply really to express what could be or to offer input to correct inaccuracies of interpretation just in the interest of public knowledge and public information is there something I can add so that there there is less risk of misinformation and debunking misinterpretations. So I pointed out, you know, this is the way the data is calculated, it does account for hours worked, it is annualised to a full time equivalent. So it does include people across the different hours spectrum. And it excludes CEOs, and it is calculators, medians, as I mentioned earlier, so we don’t have those statistical effects of extreme outliers. But then I think the way you’ve articulated it was that, you know, I guess Matt Canavan response was, Well, is that really how we should be going about it? Because if you’re working full time, does that mean that your contribution, even per hour is worth more than part time? That’s effectively I guess, one way to interpret it? I guess what he’s saying then is He’s agreeing with the greedy jobs phenomenon. And then that’s a question for all of us. So what is the greedy jobs phenomenon? Actually fair? And is it? Is it also reflective of productivity? Because if you’re working very, very long hours, is your productive value chain is a marginal decline? Is it actually worth more, as well? So you’ve got these other potentially offsetting rationale to think that maybe extra long hours, additional hours? Is that actually worth more per hour? This for hours? You know, so is there a premium? Is that premium justified? If people aren’t able to work more than part time hours, because they have care responsibilities, and so they miss out on that premium for overtime? Well, that will come through in the data. But then again, we should be questioning well, is that actually fair? Is that how we want society to function? Or can we restructure our policy so that if you have predominantly women who are working part time who aspire to work more hours, that can because effective marginal tax rates mean they actually take home less or they don’t have childcare places available? Or, you know, there are other carrying demands that it basically brings up a whole lot of other gender patterned inequities? I mean, what I would also say, I think the exchange with Matt Canavan online, also revealed, I think, some level of an underlying response, which was that we’re talking about masculinity norms coming undone. That there’s another there’s a deeper narrative here that the more that we try to advance women’s opportunities in the workforce, there will be some people out there whose responses? Well, there are still jobs that require physicality that’s associated with masculinity. And that’s worth more I think, I think some of the posts that Canavan posted could have been sort of along those lines, or has made allusions to people feeling that the gender pay gap or gender equity initiatives are unfair for Superman. And therefore that can, in his eyes, rationalise why men might look for highly masculinized icons and role models to gravitate towards for a sense of identity and solidarity. I think that’s potentially one interpretation of this undercurrent of reactions that was coming through,
Gene Tunny 49:01
right. Yep. So Matt, Matt suggested that reports like this could actually widen the gender divide, could actually lead young men to embrace Andrew Tate, for example. So I think that was the example
Leonora Risse 49:13
what is the conclusion he drew, but I think that’s a very, yeah, I wouldn’t enter into Logic.
Gene Tunny 49:18
Okay, I want to just want to go back on the greedy jobs, just so I characterise what Matt was saying, but the technical point he was making, so yeah, there’s the greedy jobs aspect of it. But there’s also the fact that if you’re full time, even if you’re just working 38 hours a week, or 40 hours a week, you’re more valuable, like say, compared with someone who’s only working half time, you’re actually more than you’re more than twice as valuable than that person, because you’re there all through the week and you can respond to the issues that come up and you’ve got continuity of the work so you’re more you can fit more into the the processes that are at play. You’re more reliable, you’re more diverse. In the world to upper management, for example,
Leonora Risse 50:02
I think that’s one party can go down based on that logic. I’m not sure if that if really, he was. He was expansive on that logic or based on on the Twitter post, but I think that’s, that could be one way of some people attempting to rationalise or legitimise why workers who work more hours in absolute terms should be given a higher pay rate per hour. Now, for some employers, that might be their logic, again, I would come back to is that really a measure of your true productive contribution per hour? Or is that a sense of some strategy for some employers to? You know, to really attract and retain and, and extract excessive time and energy from their employees and potentially, in an unsustainable way over time, if you’re working very, very long hours, if you’re always on call? Is that healthy and sustainable over the long run as well?
Gene Tunny 51:25
Possibly not I mean, that was one of the things i There are a lot of good things I liked about when I was working at Treasury. But one of the downsides was that you’re often always on call, depending on the area you’re in. So when I was in budget policy, for example, you were just always on call almost. And you you’d often have to come in on weekends work late at night, if the treasurer wanted a briefing or something. Yeah, it was, it wasn’t I don’t think it was, I don’t think
Leonora Risse 51:50
and also to Gene like, you can control for that in your model as well. So I’ve done analysis using the Hilda data for the gender pay gap based on hourly wages, and I put in a variable to control for overtime, and you still see an unexplained gender pay gap. Right.
Gene Tunny 52:07
Okay. I just finally, well, over time is this. This is both paid and unpaid overtime, because a lot of overtime. Maybe we can we can I can know,
Leonora Risse 52:21
in terms of the data that I’ve been Yeah, yeah. So it does ask, do you usually work more than I think it’s 50 hours, we’ll see it’s got all these different thresholds that you can choose. So you can put that in? And then of course, if you don’t control for that, then you are diluting your hourly wage calculation because you’re dividing by a bigger number. So you really have to control for that. Okay. Yes, yeah. But basically, I’m saying that even if you were to say and accept the logic that say, with the big data where we can’t use annualised full time equivalent, because there’s a premium associated with working sets of hours and overtime being on call, okay, if you want to buy into that logic, we can kind of control for that and adjust the calculations. Okay. It doesn’t, yeah, doesn’t explain away the gender pay
Gene Tunny 53:15
gap. Right. But this is where I think, yeah, yeah. This is where we need to use data sets like Hilda household income labour dynamics Australia, ABS data, to what extent does this do you think you can use this to to help improve the analysis? Or is this just a novelty? Or is this just something that, you know, makes the news? That is that is not really valuable for research and insights? What are your thoughts on this big
Leonora Risse 53:43
data set is one of the most valuable data sets? I would say internationally, right? It is a census. It’s not even a sample. It’s a census of all these companies. And we’re GIA collects a whole bunch of other information about these companies that can be plugged into an analytical model to conduct that type of decomposition analysis. So I know they have that research orientation, and they’re looking to conduct that type of research in the future.
Gene Tunny 54:14
Okay, well, I’ll look out for I’m sure you’re going to be analysing the data, you’ll be looking at the data, that can
Leonora Risse 54:21
be one of those researchers doing that, again, just to make sense of the data. There’s a lot of explanatory power in there. We use the analytical models to get under the hood. Okay,
Gene Tunny 54:33
good. Good. Finally, should have asked, Are we the only country that’s doing this?
Leonora Risse 54:38
Oh, good question. So my understanding is, no, there are a few other countries around the world. So a lot of this was informed by international experiences as well as that sort of gave rise to why these laws changed in Australia. So in the UK, they do it in Denmark. They do it could be a few other companies, but you know what, that’s where some of these lessons learned come from? So one example that I’m aware of is in the UK in universities, they had pay gap transparency. Yes, they saw the pay gap narrower. But mainly, by virtue of senior women negotiating for higher pay or leaving to go to a high paying employer, the junior women didn’t have the same sort of capacity to leverage that data or to bargain. So not all women, for example, can use this data. In Denmark, when they had pay gap transparency, they saw a narrowing of the overall gender pay gap through a slowdown in men’s wage growth on average. So it wasn’t because women’s wages accelerated and caught up. It was because over time, men’s ongoing wage growth, it didn’t go backwards, but it just didn’t go up as much. And so it meant overall, the wage bill for companies doesn’t necessarily go up because you saving maybe there was some men that you were paying more than what they said.
Gene Tunny 56:05
There hasn’t been a causal study of that, though, has there? This is just observation. This is Oh,
Leonora Risse 56:11
no, this is this is a proper academic journal study. Really? Okay.
Gene Tunny 56:15
I have to look at that, that I’ll have to look at the methodology to see how they draw that conclusion. Because it sounds like I mean, yeah, it’d be interesting if it were true. I mean, I’d be interested in seeing the methodology to just to check that, you know, it’s just not something that, you know, happened. I mean, the whole the whole post hoc, ergo Propter. hoc, as
Leonora Risse 56:33
in there could have been some external shock. Potentially, I think you always want to ask those questions. Yeah, sure. I think what was interesting was that it was yes, it was a narrowing, but it was because of this slowdown from men’s wages rather than accelerates it. So it shouldn’t just be expecting all women’s wages are going to catch up now. Yeah. And narrowing of the gender pay gap involves two moving pieces.
Gene Tunny 56:56
Right. Yeah. Okay. Well, you know, this has been great. I’ve really grilled you over the the geo data, and you’ve been doing great in answered a lot of my questions. And yeah, it’s been great to have you on the show. I think this is a very important topic. We’ve talked about it before. Other Any other thoughts? Anything you’d like to say to wrap up?
Leonora Risse 57:23
Open question there. I think I think you’re right, we covered we covered a lot here. I think the takeaway is so how do we act on this data in a constructive way, is to make sure we don’t put the onus on individual women to now go and get this data and expect them to rock up to their employer and say, I deserve a pay rise. Really, the onus should be on employers and companies to care enough about these pay gaps to want to at least explain it and do something about it. So that fix the system rather than fix the women is a recurring piece of advice that I think applies. In this context, if companies are asking or if you’re thinking, What can I suggest to my company? What should I do? What should we recommend that our company does? One evidence based strategy is to make closing the gender pay gap, part of your KPIs, your key performance indicators for your managers and executives. And that’s an evidence based way that really seems to get the ball rolling. Yeah,
Gene Tunny 58:34
yeah, that’s a yeah, that’s, that’s one thing that certainly could motivate the executives to pay attention to it for sure. I mean, I, I expect that for some of these companies, for jet staff or others that you look at the data and like, whoa, that’s, that looks like a much higher gap than I’d expect. you’d hope or Well, I think I would expect that they would have a board paper, the next board meeting, delving into it, trying to explain why there is this gap. Okay. Well, it’s because of the composition of the workforce, right? Yeah. So I think they’ll they’ll have to do
Leonora Risse 59:09
and one, one takeaway there is like, if we are going to judge companies, perhaps one way to look at it is which companies are improving the gender pay gap over time, so not just the absolute amount now, which in some ways might be slightly outside of their control. But if you look from one year to the next, which ones are narrowing, and getting better, in addition to other indicators, we should be looking at, like, other measures of safety and other things that matter for gender equality. So yeah, this is the first of a series of data points. And I think that indication of progress over time, could emerge as a more important indicator than a simple snapshot in time. Yeah,
Gene Tunny 59:55
yeah, I think that’s good point. Okay, Leonora thanks so much for your time. I really Lily enjoy the conversation.
Leonora Risse 1:00:01
Thank you, Jane for having me likewise.
Gene Tunny 1:00:04
Right. Oh, thanks for listening to this episode of economics explored. If you have any questions, comments or suggestions, please get in touch. I’d love to hear from you. You can send me an email via contact at economics explore.com Or a voicemail via SpeakPipe. You can find the link in the show notes. If you’ve enjoyed the show, I’d be grateful if you could tell anyone you think would be interested about it. Word of mouth is one of the main ways that people learn about the show. Finally, if your podcasting app lets you then please write a review and leave a rating. Thanks for listening. I hope you can join me again next week.
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Credits
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