 Mae'r ydych chi wedi'i gweithio'r ffordd i gael y ffordd yma, ac ydych chi'n gweithio'n gweithio'n hyfforddol wedi'i gweithio'r gweithio'n hosed. Mae'r rhaglen oherwydd mae gael eu ddefnyddio yn gweithio'n hefyd a'r ysgolio'n hefyd. So d!!!!!! Thank you very much. I'm an economist, I specialize in family economics and one of my papers, my PhD thesis I was working at the impact of trying to visit the cause of the impact of education on marital age gaps between spouses and actually the paper transformed into looking at the trade off between… heated off between age gaps and matching on education. So, the standard disclaimer. So as an economist I would say to you that your choice of spouse is an economic decision. It's probably the most important economic decision that you will make in your lifetime. Your choice of spouse may affect where you actually participate in the labour market. that it may affect the level of wages that you're willing to go and work for. Your choice of spouse may affect your health. There's a lot of literature that looks at that. I would argue that most people would agree that your choice of spouse is going to affect your happiness. It may affect whether you have children in the first place, how many children you have, and also, the outcomes of your children. Looking at all of these things, we can also think that Abertaf, everyone who unit, and zest when it takes society the people in society of those chooses to marry, it's going to feed on an important determinant of intergenerational mobility as well as income equality. For these reasons marriage is either of interest to economists such as myself. But we also know that most people who are making a marriage decision, Not that people who are making a marriage decision probably don't have economics at the forefront of their minds. However what we do see is that a number of very nice features emerge in the majority of marriages. Firstly, uspans tend to be slightly older than the wives. Note spouses tend to be of a similar age but husbands are slightly older than their wives. a'iostau bod ydych chi'n lleistau sydd gyda'r defnyddio'r gadwiau yn edrychu gyda'r sparse. Rhywbeth, ddyn nhw, eu chynhedgau cyflymau hynny, ydych chi'n meddwl cy heroi wedi eu chynhedgau clywed mewn newidau a ddaethau'r hwn. Mae'r fforddo panemod yn ystod i gyfenybeth symudol, ac mae'r 180 cyfnod yn gweithio cynogi ar gyfer y Gwyd Nde, yn y syniad yn ei gwin iddo… mae yn cael ei gwybod bod yn ffraith hynny yn gwybodaeth sydd oesiaid ar gweithio ar gyfer gwaith, There's also a large literature in the economics marriage literature that talks about a sortative match in education. There's been some work using US census data that shows over the past five decades there's been an increasing degree of homogamy, i.e. that there's equal levels of qualifications between spouses. Oooh. It is amazing so this leads to a polarization of the higher quality spaces бел and call it is, be it between households. So there is a number of explanations that have been forwarded for this positive Asia One of the leading ones is about gender specific roles this is very much of a traditional argument that men are breadwinners and go out and work in the labor market and it takes time for their attractiveness to be revealed because they have to go improve that they are very good at earning whereas women are attractive for other things that are more readily observed. Y llif arfer mae eispas o ballw o'r mynd i'r hyffaith mai nodi'r llyfr. Mae'n ddiwylliannod oherwydd mae hwnna'r llyfr yn y lleol, mae oedd drwsod i'r rhaid o'r lleol. Unrhyw y gweld yn damnedwyr pan fydd yn y gallu bwysig iawn, yn blaes Cymraeg, fel gymryd bod nid,acheo'i chyfion. Mhen i'r bwysig i'r bwysig i'r bwysig i'r bwysig i'r bwysig i'r bwysig i'r bwysig i'r bwysig a'i gwyn i'n cael bwysig i'r bwysig i'n cendrygiadau, 주는 amdano. Felly, mae gynnyddol wedi gwrth gofod i weithredol yn merydd yng Nghymru iddo a'n gwneud roi arall gwneud yn ceisio'n gyflaenrwydd i'r hyn o'ch chi, a chael hyn i'n ddod mewn gweithio'n gyffredinol mewn gydigol wrth opponenti yn br jour, na'n gweithio'r gweithredinol yng Nghymru i gyrtodol am gweithredinol. Felly, yn fawr iawn yn ei'r hun o'r eich cyfodd, mae'n cael ei wneud ei'r cyfrifoedd ond mae'r gweithio gweld yn cael hwn o'ch cyfranio gwahanol, sy'n leol gyfo dechrau, mae'r hun ar y mawr iechyd yn cael eu ddau'r honig, mae'r tornol yn cael ei ddechrau. Dyna, ei ddefnyddio, mae'n bwysig roedd eich reform yn ei wneud sefydlogiol yn ei wneud yn ei ddechrau. Mae yw'r reform bwysig yw ei ddechrau i eich wneud o'r effeithiau. Mae'r cwmhwm yw'r cyhoeddol yn ei gael, a hynny'n cael ei fod yn ei gael o'r mewn o'r adroddau a'r adroddau. Rwy'n credu bod y cyhoedd yn ymlaen o'r adroddau'r cyhoedd o'r adroddau'r adroddau'r adroddau'r adroddau. Felly, yn y cwmhwm, ac mae'r adroddau o'r adroddau, rwy'n cael eu oed yn ymgylch yn ymgylch yn ymgylch yn ymgylch o'r adroddau. is likely that I have more education than he is. This is the imbalance that we are going to be looking at. What we do find is, society, that in the neighbourhood of this discontinuity it is not possible to... We find that these typical matching patterns cannot be obtained and we find that speltes specifically choose smaller age gaps. a maestrach wedi ei gael i gael o gydag o'r cyhoeddiadau. Yn y merasgrifennwyd, oedd ysgolwydau iawn i'i gael i'r marasgrifennwyd. Mae'r sgwlaenau a'r sgwlaenau a'r sgwlaenau a'r sgwlaenau sydd fe-nw yn ymgyrch yn y marasgrifennwyd. Mae'r sgwlaenau a'r sgwlaenau i'r marasgrifennwyd. Mae'n mynd i fi'n ei gael i'r sgwlaenau i'r sgwlaenau i'r sgwlaenau. Aeth yn amlwg i'n ffwrdd llwyaf fel yr ëEducationí. Dwi'n rhoi wneud yma i amlygu yma, a ddrwnyddu ddyn nhw'n dechau drwygyn nhw. Mae rherwydd ein ddechrau, yoko rherwydd a y ddechrau, nworking age, wrthy drwy sydd yn yng Nghymru yng Nghymru yw yw 1972. The likes of all the individuals who were born after September 1957 were required to stay in school until they were 16. Prior to that, they could leave school when they were 15. What is very interesting about this particular reform, is that it required individuals to stay in school up to the age where the first tier of qualifications are set. byddwch i gyd y cyfnod o unig o ddysgu ddweud o'r ffordd, ac mae'n ddweud i hollwch gyrfa pob y byddwch i'r hollwch, ac mae'n gweithio'r ddegwyd, sy'n edrych i'w cyfun o'r ddegwyd. Mae'n ddegwyd wedi gwneud y stryd o'r gweithio'r ddegwyd, a'u ddegwyd yn cael ei wneud i'r gweithio'r ddegwyd, oherwydd o'r ddegwyd i'r ddiogelol yng Nghymru, ac oherwydd o'r ddegwyd o'r gweithio'r gweithio, er swydd o'r wath i gynhyrchu iawn i ddwyloedd a'r ddwyloedd a'r ddwyloedd yn gweithio'r llywedd, felly'r idea a dydy'rnt oedd eraill gwneud yn'n mynd i ffordd oedd yn y cerddau sydd wedi'u gael byddwch I have more education. My candidate spouse is going to be on this side who hasn't been treated. Or we can think about it the other way, but that's for me as a woman. If I am a man, which just attends, and I'm born here, I'm going to be able to go and match with someone who is younger than me. They're born out of their birth also being treated. There's also a gender difference in how these two things are manifested. So, why did I use the ONS NS for this? Well, the analysis of course requires relatively rich information on both spouses. So, a lot of the survey data that it is possible to get, you have a lot of information from the respondent. You might not have as much information about their spouse. Also, sample size was a very important issue here. So, this is why for me the ONS longitudinal study was an ideal study to use. So, created samples, so did a separate analysis for husbands and wives. And if you're interested, this is the method, but to the graphs. So, first of all looked at the impact on qualifications, I realised that this is probably not coming out too well. This is for wives, this is for husbands, we can go and see. These are the cohorts before, cohorts afterwards. And there's a very, very large jump in the probability of leaving school with an academic qualification. If I look at the impact on the sparse of age difference, we see that there's this large downward impact for women, but not really for men. And remember, for men who are affected by the wasps, they're going to be looking for younger women who are also being affected by the wasps. Because why we don't see this big impact for men on age differences that we do for women. We see that women are really switching into, around this special, they're switching into marrying younger partners, i.e. partners from the same cohort of themselves who are also, would have been affected by this educational report. If we look at the impact of the qualifications difference, we can really see what's happening here. So, the qualifications difference of the difference between a husband having a qualification and a wife, we can go and see that these differential effects by a gender really will appear that, for men, the adjustment actually happens before the threshold, whereas for women, the adjustment happens after. So, this is the analytical result, but it basically says exactly what I just went to show you in the graphs. So, what we found is that the reform induced a substantial decrease in the marital age gap for women, specifically that they were switching partners and marrying younger individuals who would have also been affected by the increase in education. We do find the corresponding bottom of first affected in men. For men, it's those individuals who were born just before the threshold who cannot receive, who cannot achieve these typical marital matchets. So, yes, this is very, very interesting, but this actually has very important implications for some of those papers, the types of papers that I was talking about earlier, that use this type of reform to elicit causal effects of education on a number of different outcomes. If you're thinking about an individual outcome such as your wages, then the marriage effect is another channel of this education effect. But when we're thinking about household level outcomes such as the impact of parental education on children, if the education reform changes who you marry in the first place, then any effect that you see on the children is attributable to both the fact of parental education and also that a different spouse may have been chosen. So, just a quick reflection of my experience of using the ONS. I'm going to go and say exactly the same as Fran and Matt earlier. There are some set-up costs involved. So, when I was applying, there was a very, very detailed application that was required. This was the first time that I had actually applied to use this type of data. So, I think I had my application vetted a couple of times and returned to me and changed it. Probably a couple of weeks ago and get that application done. In order to use the data, you need to go in and do some training on data security. At the time, this is a few years ago, I ended up doing this training, almost exactly the same training for three different types of data that has actually all been amalgamated into this short training now. So, once you've done that, not only can you use the LAS, but there are certain other data sources that are covered by this training. One of the big set-up costs is, of course, that you can only access via the secure settings. So, when I was in my PhD, I was actually based in West London. So, I was able to come in one day a week for a couple of months in order to go and clean the data. So, it wasn't actually that much of a problem for me. Probably because of that reason, it took me longer to go in and get the data together, because I didn't have the set-up costs, for instance, that you had. The clearance procedure takes a little while to get used to these, but in order to go and take anything out, you have to first have it vetted and there are some procedures that, the first time you do it, you do it wrong and they won't allow you to have everything, and then you slowly learn how to do this. However, there are many advantages. So, there is a help desk, and it's a very, very helpful help desk. So, that will talk you through all of the stages, and, at least with me, we're incredibly patient. There's incredibly detailed documentation, as well as this was, for me, very, very important, that not only is there helpful documentation, but there are people on site, especially if you're working in the Pymlaco site, who will carry you towards where to go and get help. And once you have, and I think this is, again, the same thing that we were saying earlier, once you've got your head around how the longitudinal study works, there is a possibility of remote coding. So, in my analysis, I ended up, I actually set up what I called a mirror dataset. So, I used a different data source, so I used the end-user license version of the labour force survey, where I created a sample with exactly the same variables so that I could write my do file to make sure that they worked in the mirror, and then I would send the do file in to go and do one, and that was very, very useful. But, of course, there's this huge, vast potential for doing future work. So, where I'm working on at the moment is rather a complicated title. I'm looking at the long-run health and mortality effects of being exposed to universal healthcare at birth. Basically, what I'm looking at is whether there are long-term effects of the introduction of the National Health Service. This I'm able to go and do, precisely because the data source exists such as the longitudinal study. So, within the longitudinal study, there's information, very rich information of individuals that has been linked to administrative records, such as death records. So, I have information in here of not only when people were born, but where people were born, and so we know that, and then we can observe when they fall out of the sample due to mortality. Go ahead. You talked about administrative records and mortality data and the first presentation mentioned that, too. Are there any other administrative records that you've looked at as long as you think of it? So, this is my first foray of using the administrative data that's linked here. I mean, there are other data records that are linked and no fertility records are linked. I think cancer registrations? Yes. So, one thing that we're thinking about doing as well, especially with this early chess thing, is looking at cancer registrations as well that might be interesting for us. I'm going to hold my hands up and say that's what I know from the linkage, but we might be able to say more. So, will you repeat the same thing? Oh, of course, yeah. Which you used in some health, how that happened to you. So, yes. Cancer incidents, and mortality, we want to find cancer mortality in there. And also, there is a birth, births that caused two births in half this. So, there you have birth rates, infant mortality, and two birth birth rates. Yeah. I would. Yes, please. Oh, sorry. What, the regression equation? Oh, that's one. I'm happy to go and talk to you about this afterwards if it's a technical question. I'm fighting that I might lose the room if we go and get to the table. We can talk over the line if you like. OK.