And now we need to go full screen.
Okay. All right. Gosh. All right. All right. Here we go again. All right. Is that good?
Okay, brilliant. Okay, so I'm going to talk about some ongoing research with Leander Heldring and Bohan Yang, who are both at Northwestern — sorry, Kellogg School of Management and Economics Department respectively. And this is about how developmental states work. So we're going to talk mostly about, show some evidence from Rwanda. But you know, I think the bigger set of issues is about state capacity and what constitutes state capacity. And you know, there's a lot of emphasis at the moment on fiscal capacity and raising taxes and strategies to raise tax and tax morale and all sorts of other things like that. But I think, you know, even holding constant the fiscal capacity of states, there's an awful lot of variation in their capacity more generally, meaning their ability to get things done, to implement policy and organize society, both today and historically. And I think a fact that, you know, like contrary to the obsession with the fiscal state, a fact, you know, that's relevant to this discussion is that actually, you know, frequently many people who work for the state don't get paid. Okay? And that's not just a kind of feature of what you might call late development. It's also a feature of early development. So for example, in the British case, you know, we've all had this idea in our heads for a decade, you know, which has come from John Brewer's book, 'The Sinews of Power', which is about the construction of the fiscal state, the excise tax bureaucracy after the Glorious Revolution. You know, Brewer points out for the first time customs was bureaucratized, excise tax system was bureaucratized. There's this kind of wonderful Weberian state. What do I mean by a Weberian state? I mean a state organized along, you know, what Weber called rational-legal lines, with bureaucracy and incentives solving principal-agent problems and all that kind of wonderful stuff, you know. And it's true, you know, that that bureaucracy did exist, you know, but actually, you know, it was very small relative to the number of people who were actually working for the British state, and most of those other people were not getting paid. So here's some estimates, you know, of another parallel project that Leander and I are doing with Davis Kedroski and Matias Vigant, looking at the organization of the British state. It's actually not Britain, it's England and Wales, but we don't have a nice terminology for England and Wales, you know. So with all the due apologies to the Scottish people in the audience, the British state, you know. So I don't want to spend too much time talking about this because I want to talk about Rwanda, but just to kind of give you a sense of this, you know, which is up here in 1835. Here's the 21,000 people. This is what John Brewer is talking about. You know, there's professional bureaucrats and civil servants in London, in Whitehall, and you know, and then there are these excise officers, but there's only about 4,000 of them. Okay. What about in the rest of the country? Well, there's 95,000 people running parishes. So there's about 14,000 parishes kind of throughout Britain, the lowest level, lowest administrative unit. There's 95,000 people running parishes. None of them get paid. There's county administration and there's borough administration. So the borough administration are the cities, if you like — Liverpool, Manchester, London, Birmingham, Norwich, etc. Okay. And what's kind of amazing about that is at the county level 90% of people are unpaid, and even at the borough level 70% of people are unpaid. So these people are providing judicial services, you know, dispute resolution, the jails, law and order, they're building roads and bridges, lights, sewers, all sorts of kind of critical local public goods. 70% of them are unpaid.
Okay, so I'm going to talk about Rwanda, but just, you know, to kind of get some sense that this is actually a feature probably of most states in their early phase of development, right? So you might ask, okay, well, how on earth, you know, I didn't learn anything in principal-agent theory. I learned something about high-powered incentives when you can use them and when you can't, but I never learned anything about when you can't pay people at all. I don't think there's any models of that. So how do you motivate people when you don't pay them? Okay. And our hypothesis, and the sort of big agenda here in which Rwanda is going to seamlessly fit, is, well, you exploit the nature of society. Society is not actually a whole kind of group of atomized individuals. They have all sorts of connections and all sorts of social preferences. And in fact, in the English case, you know, the English and Welsh case, how you motivate these people is by exploiting notions of status and prestige, and allowing status and prestige to accumulate from holding various offices in local and county and borough governments. You could exploit career concerns also, meaning some job is a stepping stone to something else that could get paid or will get paid. But you kind of exploit the sociology of society to get things done. Okay? And of course, the instruments you have to use depend on the sociology, and that's going to be very different in different contexts. Okay? So that's all I have to say about Britain. Today we're going to talk about Rwanda, but hopefully, you know, you can fit it into this bigger picture. Okay. Why Rwanda? You know, why do research on Rwanda? Well, you know, Rwanda is a poor country, of course. You know, I looked at the World Bank, you know, web page yesterday. GDP per capita just got over about $1,000, you know, in 2015.
But it's experienced very rapid economic growth, as you can see here, since the genocide in 1994. So I think everyone's heard of Rwanda, you know. So, you know, here's an interesting experience of rapid economic growth, like what's going on in Rwanda. And I think also probably what everyone knows about Rwanda is it's extremely well governed. Okay, if you look at data on governance, you know, here's some data from WGI, just sort of, you know, we could all discuss these numbers, you know, but trying to characterize how effective the government is. Rwanda looks something like Greece, you know, it looks something like Colombia, you know, but of course relative to GDP per capita, you know, Colombia is $65,000, Rwanda is $1,000, Greece is, I don't know, 20-something thousand. You know, of course, Greece is not the most fabulously governed country in the world, you know, but there's an enormous gap between Rwanda and any other place you might look at in sub-Saharan Africa, or maybe not Botswana, you know, but I just plot, you know, Nigeria at the bottom here, you know, and the sub-Saharan African average just to show you that, you know, like there's real governance in Rwanda. So if any of you have been in Rwanda, you'll know that this is picking up something real. And you know, and where does that come from? Where does that come from? You know, we kind of think this governance is connected to that successful economic growth. I'm going to show you some evidence that that's true, but you know, where does it come from? Okay, here's some evidence that, you know, there really is good governance other than as rated by, you know, the World Bank or WGI, you know, which is access to electricity, you know. So here's something we care about as development economists. So, you know, let's go, you know, if you go back to 2005, it's sort of zero basically, you know, at the time after the genocide, Rwanda is like black basically, and now what you have, it's up to 80%. So 80% of people have access to electricity, either kind of grid or some off-grid, you know, solar or some other way of generating electricity. So here's, you know, here's a remarkable expansion of public goods. And of course, this 80% is way over the — I should have got the sub-Saharan Africa level here, but 80% is way over the sub-Saharan African level. So Rwanda has gone from sort of nothing to something far above, you know, sub-Saharan African average electricity access. Okay. So here's a payoff of effective governance. All right. So how has it done this? Well, not through taxation. So, you know, here's again the data I dredged off the World Bank web page yesterday. Tax revenues relative to GDP are 13.5% at the moment. You can see, you know, if you go back to the time of the genocide, it's like less than 10%, and today it's 13.5%. That's what they say. So according to the International Monetary Fund, you know, whose opinion we all take extremely seriously, you have to raise 15% of national income to have a serious government. And the point here is not that having 15% of national income might not be good for running the government, but there's many other ways to run a government. And Rwanda has this fantastically effective government, but it's below 15%. Okay? And in fact, you know, there's a big gap in the series here, but you know, for a lot of this, a hole in the data, and maybe somebody has better data than this, but this is what I could get from the World Bank web page. You know, it's way below. It's not just like below 15%, it's way below 15%, it's around about 10%. Okay. So how have they done this? Now, you know, given the British example I started with, you might be already kind of joining up the dots, you know, and sort of saying, well, you know, maybe they've been doing it by not paying people. And that's actually true. So this is a reconstruction of the organization of the Rwandan state from a Belgian anthropologist called Bert Ingala, where we're kind of working now to do something like really nice with the government at the moment. But just to give you a sense of this, here's — and this is useful later for when I start talking more about the organization of the state in Rwanda. There's lots of levels. There's the umubakumi — like you'll have to forgive my dreadful Kinyarwanda pronunciation — and this is just a kind of group, this is the most informal part of the state. It's like a group of 10 households. So we're not going to spend much time on that. There's the village level. Okay. So at the village level there's a bunch of people working for the state. You're going to see the village is important in a minute. No one gets paid. Okay. It's a bit like the British parish. No one got paid in the British parish either. Up from the village, you have the cell. Okay. Well, there's one person, the secretary executive of the cell, they get a salary, but everybody else, they don't get paid at the cell. I go up to the sector. Well, now there's a couple of people, the secretary, executive secretary gets paid. There's one other person that gets paid. Other people don't get paid. Okay? So there's a lot of people working for the Rwandan state. So we don't know the exact number here, we're working on that, but we guess that the majority of people working for the Rwandan state are not getting paid either. Okay. So, oops.
So then the question is, like in the British case, I sort of waved my hands and talked about prestige and status. So the question here is, how do you make such an effective state work? You don't have a lot of resources. You're not paying these people. How do you incentivize them? Why do they do stuff? You know, why do they do stuff in such a fantastically effective way that electricity provision goes from zero to 80% of the population over that period? Okay. And so the entry point into this, our entry point, is to look at the sort of biggest public policy in Rwanda, which is called Imihigo. Okay. And it's useful to know a little bit about the history of Imihigo to get where we're going to go on this. Okay. So President Kagame in 2006, he was at a meeting of mayors. And the mayors, you know, this is like the mayors of — this is like the districts. I think there's 30 if I remember correctly. Someone can contradict me, you know, correct me. The mayors were making these exaggerated promises of what they were going to deliver, and 'I'm going to be the best mayor in Rwanda' and stuff. And Kagame says, you know, in Rwandan culture, you don't make promises you can't deliver on. And he invokes a pre-colonial norm or practice called imihigo, which was, I think my understanding is that, you know, this in some sense originates in the army, that a warrior would promise to do something or achieve something in battle, and if this was not accomplished, they'd be kind of humiliated. All right, talking about status. So Kagame takes this principle and he sort of reinvents it in the context of the modern state as a tool of policy implementation. So you can make promises, but you'd better deliver on those promises. And then he sort of converts this, you know, with the help of the Ministry of Local Government, into a massive kind of system of policy implementation. So let me give you a sense of actually how that works today. It starts at the village level. So those villages I showed you with the unpaid officials, each village comes up with like three priorities. Okay, what do we want? We want a new school, or we want a bridge over that river, you know, or, you know, we need — there's terrible flooding, we need to stabilize these hills, or whatever it is. They come up with some — I'll show you some real promises in it, or real priorities in a minute. So they come up with three priorities. Each village's priorities go up to the cell, which is the next level up, and the cell aggregates these priorities, and then it goes up to the sector. And at the sector, the priorities of the government — which also the government has a development plan and they have their priorities, you know — the priorities of the government come down, and these are sort of reconciled. So there's this enormous process of kind of outlining priorities, kind of aggregating priorities. That's a process, you know, we're trying to study how that works exactly, and reconciling the kind of priorities at the lower level with the priorities coming down from the top. Okay. So this is just off — you know, you can look at the Imihigo web page, you know. Here's the — you know, starts with the village, there's that village executive committee which I sort of outlined, you know. They come up with these. And you know, the way this sort of works in Rwanda, if you know something about Rwanda, is, you know, is that, okay, you know, we have our priority, meaning we'd like a new school, and the government sort of says, okay, fine, we're going to sort — there's this complicated process that I've been describing, you know, some complicated collective choice problem, and we're going to give you the school, and we're going to give you this, you know, we're going to give you some concrete and the bulldozer. We're going to lend you a bulldozer, or we're going to send some people from Kigali with a bulldozer and whatever, but you have to do this. You have to input labor. You maybe you have to raise resources. You know, in Kigali, if you have a kind of unpaved road, for example, if the people on the road can collect 50% of the necessary funds, they can go to the city government in Kigali with the money, and the city of Kigali will put the rest of the money in and give them the equipment, and then they have to contribute labor in order to pave the road in their neighborhood. So everywhere in Rwanda there's this kind of collective kind of input into public good provision. So this is a sort of systematizing in some sense that whole thing and trying to, you know, reconcile different objectives with the amount of resources available, and, you know, through this collective choice problem that we can only imperfectly observe at the moment, but we're working on it. Okay. So, you know, here's a sense of the citizens' priorities, you know, which comes from the Ministry of Local Government in Kigali, who we've been working with. And, you know, just to give you some sense, like here's the — these are different districts: Muhanga, Gisagara in the Southern Province. Here's the sector, you know, and this is the — you know, these are the priorities that kind of come up from the villages. So, you know, within a — there's a cell, and then there's a — you can see here there's a cell, there's a sector, and, you know, these are coming up from the bottom. So at the moment we don't have all of the priorities of all the villages, we just have them at the cell level, but just to give you a sense of what these things look like: construction of the road linking Tenya–Gatovu, construction of this particular road. So they like roads, a drying ground for rice, rehabilitation of this office and office materials. Okay. Construction of a health post. All right. So these are all kind of public goods which are being asked for. And then what the government does is there's this collective choice problem. Out of this comes, you know, okay, we're going to do this, we're going to give you this, we're going to give you that. You have to put these inputs in, and then the government, through the National Institute of Statistics, kind of evaluates how well all of these things have done. Okay. So the imihigo — there's a very elaborate process of evaluation of these imihigo. So all of these agreements that I'm sort of describing, that, you know, this aggregation of these all these different inputs, there's a bunch of decisions that are made about what the state is going to produce, and then these have imihigo contracts associated with them. Okay. So, and then the National Institute of Statistics evaluates these contracts. Okay. So we have all of this data here. I'm just going to — we're still playing with this, as I said, and there's other things we don't have here. But what we do have is all of the information about the evaluation of imihigo contracts from 2019 to 2024. So we really have a kind of measure of how well these different projects were implemented. So one of the things we're going to do is to kind of look at the variation in that, you know, as a measure of kind of state capacity. All right. So, you know, I mentioned social status. It's not just British people who love social status, you know. Everyone loves social status. No. So, you know, here's President Kagame right in the middle, and this is the Imihigo Awards in 2015–2016, where, you know, people who were most successful — these are mayors who are most successful at implementing imihigo, at kind of implementing all these things, are awarded with, you know, cool little, you know, things to put on their desk and stuff like that. So, you know, okay, so what I'm going to show you to start with in the empirical results is, you know, based on these imihigo marks from the National Institute of Statistics. As I said, you know, we have them over this period, 2019 to 2024. These imihigo contracts are sort of annual. The government does this annual process, this social choice problem I'm describing happens annually, the imihigo contracts get signed annually, and then the National Institute of Statistics has this kind of evaluation team that goes in and kind of basically marks these projects. So a mark is like something from zero to 100, like how well was this implemented? Okay. Now, what they do is, you know, so we can look at the variation in that, but of course, you know, you might also be concerned that, you know, how is that connected to any real development outcome. I showed you the rural electrification. There's a real development outcome. So we're going to merge this data on the evaluation of these imihigo projects with household survey data on all sorts of different things. And what's interesting about the way the imihigo is organized is that the National Institute of Statistics kind of organizes the sort of different types of imihigo projects into different sectors, you know, into education, energy, health, ICT, etc. So there's eight different kind of development sectors. So what we can do is, you know, we can look at, you know, the performance of imihigo projects within these different sectors, and then we can match that to the household data to look at like real development outcomes in education, in health, in energy. So, you know, do you have access — in these surveys, for example, in these household surveys, they ask about, you know, are you connected to the grid, for example. So we, you know, we can measure that directly in the household survey, and then we could look at, you know, the connection between how well implemented imihigo projects in that particular development sector are in energy. You know, we could link that to the probability that a household is actually linked to the electricity grid. So we have like real outcomes. Okay, we're not just — you know, I don't know how skeptical you might be about the government evaluation, the National Institute of Statistics evaluation of government policy. You might be some kind of cynic who thinks that, well, the government is going to massage all this data and stuff like that. And, you know, I have to say, like, our impression of like working with these people for a few years now is that they're like unbelievably serious. And I, you know, I should say something about that data on priorities also. You know, you might think, you know, President Kagame has a bit of a reputation as an autocrat, but like what we found sort of fascinating is that that data kind of exists. You know, the Ministry of Local Government, a subsidiary part of the Ministry of Local Government, has all that information, which they shared with us. You know, and what was fascinating is that what we realized was nobody knew that data existed. Like the World Bank people didn't know it existed, the British government, you know, the DFID people didn't know that it existed. So if it's some elaborate kind of hoax, you wonder, like, who's the audience? You know, like, if there was an elaborate hoax of kind of participation, you'd think that the audience would be the donor community in order to get resources. But actually that doesn't seem to be the case at all. They collected the information because they're sort of trying to understand how this whole process works. So I, you know, we could talk about that if people — maybe it's too boring to talk about, but my own experience, once you start talking about Rwanda, people start coming up with these conspiracy theories, and, you know, and we don't have anything to say about elections or anything like that. We're just trying to understand state capacity, and I think if you've been in Rwanda, you can see there's a heck of a lot of state capacity compared to anything else, you know, in maybe Botswana, you know, but even compared to Botswana here, there's a kind of ability to kind of get stuff done that's not even true in Botswana. So all right, just to sort of air those kind of issues. All right, so...
What we're going to do with the data is we have, you know, there are these different levels. As I said, there's, you know, there's districts, but there's 416 sectors, and underneath that there's cells and villages. So we're going to look at this kind of data at the sector level, but we have a lot of variation here, you know, within these geographical sectors, you know, but also within these different development sectors to which we can match this household data. Okay. So the first thing I'm going to show you — I think I have about 10 minutes left. The first thing I'm going to show you, or 15 minutes if you're really indulgent, you know, the first thing I'm going to show you is just some sort of cross-sectional thing where, you know, we can control for — we can look at like real development outcomes, you know. We can look at success, is going to be a measure of imihigo success, the success of projects in a particular sector in a particular district. We can control for the number of projects. You know, you might think that's going to be — you know, there's variation in actually how many projects you implement in a particular development kind of sphere and in a particular district. So of course there's more projects, you might think development's bound to go up. So we can just control for that, and then we can have sector fixed effects, and we can have, you know, like geographical sector fixed effects, and we can have these development sector fixed effects also. Okay. So that's, you know, just looking at that kind of cross-section to see, you know, is there a connection between the success of the implementation of imihigo and these development outcomes. You know, I don't know if that's — you know, I kind of — I'm going to get to what explains, you know, the variation in the success of imihigo, but that's where the sociology comes in. But just as a kind of reality check, you know, to kind of hard-nosed development economists, we thought we'd start with some real development outcomes on the left-hand side. And then we can look at this in a kind of event study. We have, you know, we have quite a few waves of this household survey. It's not a panel, you know, so it's a repeated cross-section. We have quite a few waves of this household survey over time. And we can sort of look at with our imihigo evaluation data...
You know, from the period 2019-2024, we can look, we can kind of think of that as a sort of treatment, and then we can use that pre-data to look for kind of trends, you know, pre-trends or something like that. And you know, so, so, uh, you know, here's what the cross-section looks like. Okay, so partialing out these fixed effects, you know, uh, uh, we find a very strong relationship between Imigo success and kind of average development. So developing, you know, average across all these different health and education, etc., etc. Okay, very strong cross-sectional relationship. So there's different ways you can measure IGO success. So as I said, it basically, you can score these things between zero to 100. I think what we, whoops, okay, let me look at the regression, uh, table. What we, what we've done, what we've done here is just, you know, to like look at, say, you know, uh, within a, within a development sector, you know, uh, the proportion of Imigo projects get 100%. So quite a lot of projects get 100%, like fantastic, really well implemented, and then there's a, there's a kind of range of scores, but a lot of the action seems to be, you know, was it, was it 100% or not. Okay, so the first two columns here are just basically using that, and then the last two columns are just, okay, let's just use the marks, let's just use the average Imigo marks. Okay, that you just, you know, so it all, it all works, but, but you know, I'm, um, I don't have a strong view, view on that. Uh, um, and you know, so again, this is a sort of cross-sectional thing. We can use these different sorts of fixed effects for the geographical sector, for the development sector, because you know, there's enough variation there, and we find a kind of strong relationship between Imigo success and these different development outcomes. So here, average development, just kind of averaging across kind of all of these different outcomes within these different kind of eight domains. But you know, you might take, you know, what representative development that would be, you know, in the energy would be, you know, was your, did your household, was it connected to the grid? Okay, so just picking like one question, I don't have strong views on this, maybe Leander and Bohan does, but so we find a very strong relationship between the National Institute of Statistics evaluation of the effectiveness of Imigo and these development outcomes. Okay, so we like this Imigo success data because it's really, it's a measure of government effectiveness. It's like a measure of capacity. It's like, did you manage to actually get this thing implemented, you know? So that seems to be quite unusual to have a measure like that. And here we're just showing this is really connected to development outcomes. Okay, so, so I want to talk about sociology. So, you know, we can do this kind of event study thing. You know, um, you know, you get the idea that we have some, you know, we have some kind of pre-periods here. You know, if I look at this, we can, you know, we have round three, round four, you know, uh, we omit round five, you know, so these are different rounds of this household survey. There was supposed to be a round six, but it happened during COVID, so it was kind of incomplete and it was abandoned in the end without covering the whole country. So we just dropped round six. Um, so we have three and four, we drop five, and then we have round seven, which is the most recent round. And then we interact that with this kind of Imigo success, which is that data I just showed you, basically like averaging across the period for which we had these Imigo scores, you know, and the success means, you know, fraction of 100, you know, projects that were, were evaluated at 100%. And you know, this is very preliminary, obviously, you know, but just kind of get, think about, you know, pre-trends here. All right, and we can use, you know, lots of different types of fixed effects here. Okay, so, so let me unpack Imigo. Uh, and you know, so that's, that's, you know, that's important, but let, let's get to the sociology. Okay, so, so, you know, uh, what explains this variation in, we have all these fixed effects and stuff, and we know we could talk about identification, but like, let's think, you know, about what explains the variation in the effectiveness of Imigo. Okay, so to that we need to go back to the sociology of Rwanda society and the fact that, you know, if I thought about the history of the state and the state formation in Rwanda, you know, Rwanda has a very particular sort of state formation historically, and it's an example of what, you know, the great social anthropologist Aidan Southall called a segment state. So the best study of the construction of the state in 19th century Rwanda is by Katherine Newbury, which looks at the expansion of the state into the southwest of the country in the 19th century. And I, I feel like I don't have too much time to talk about this diagram, but it's a beautiful diagram. Up here is the Mwami. The Mwami was the king of the pre-colonial state in Rwanda. Mwami was around, you know, until they were deposed in the 1950s. But if you, if you get a chance to go to Nyanza, the, the Mwami's cows are still there. And if you haven't seen the Mwami cows, I really recommend the experience. And what this diagram here is sort of capturing is how the state spread. So the state was called the Nyinginya Kingdom. And Nyinginya was a kinship group, it was a clan. And the state spread by integrating other groups into the clan. It would take kind of local states, local polities that were autonomous from the Nyinginya kingdom and kind of integrate them into the Nyinginya clan. How did it do that? Well, basically by making them a segment in the clan. Okay, it kind of created a fictional kinship relationship so that they became part of the Nyinginya clan. It also, you know, of course, marriage as a strategy for integrating other kinship groups, you know, into the clan. And this diagram, you know, is sort of a description, Katherine Newbury's description of how these different other alternative groups basically became integrated into the Nyinginya. Like here's a hill, you know, the land of a thousand hills, Rwanda. Here's a hill, you know, here's what, what, what is called a hill chief. And the hill chief was basically integrated into the Nyinginya kinship system. Okay, so, so, so this was, the whole state was built around, uh, kinship. Okay, so, so, so, you know, how does a state work like that? You know, according to the anthropologists, reciprocity. Okay, so, so this is a, this is a, that the whole thing hangs together with, uh, reciprocity. How could we look at that in our data? Well, here's a very crude way of doing that. We're working on it. So I told you we have all these priorities. Imagine you're, you're, you're, you know, you're, you're a village or a cell, and imagine, think of the difference between the government giving you what you ask for or the government not giving you what you ask for. A natural hypothesis would be, well, if the government actually gives me what I wanted, then it's much more likely that I'm going to reciprocate with effort and resources, and that the thing is going to be done properly. Okay, so with that data and priorities, we can break it into basically like, you know, what, what we're going to call an alignment sample, meaning like we ask how aligned are, you know, what the lower levels ask for with the priorities of the national government, and we can kind of break that by the median, and we could look at bottom and top, and we can ask here, you know, uh, like how, how effective is Imigo, you know, in these different, uh, in these different, uh, you know, these two different subsets, okay, and what we see is Imigo is much more successful in the aligned sample. So, so again, you know, what we're doing at the moment is trying to use this to build like real measures of reciprocity. In some sense, there's a lot of variation here. We're still trying to understand some of the data, uh, but, but the basic idea here is that this is going to, you, you, you expect Imigo to be more effective, you know, when there's more alignment, because, okay, I'm more willing, the government gives me what I want, so I'm more willing to, you know, maybe people ask the government for what they think is appropriate, and the government is willing to put more effort and more resources into it. So, you know, it's a kind of two-way street. So we think we can use this data on priorities to try to kind of capture, you know, this process of reciprocity, you know. Now you might think, okay, but like there must be other sources of recipro-, must be other sources of variation in reciprocity, and we think the answer to that is yes, you know, and, and in some sense the strategy we're going to use to unlock that is an amazing, um, 1961 census, uh, that, that we located in the archive, in the historical archive in Tervuren, in the suburbs of Brussels. And we haven't found the microdata yet, unfortunately, uh, but we have it at the sector level, you know, and in 1961, in this electoral census, people were asked for their clan identity. Okay, so we know in 1961 where the Nyinginya clan were, more than that, as I'll show you in a second, but here just to give you a kind of flavor of what this data might look like. Here's the share in different sectors of the population that were Nyinginya, you know. So the dark red, so Kigali is sort of here somewhere. And the dark red, you know, to the southwest, this is exactly what Katherine Newbury was talking about, you know. So dark red means a greater proportion of people are members of the Nyinginya clan. This is exactly where the state was spreading in this period. But you can see here there's a, there's a lot of variation in the membership of the clan. And a simple hypothesis would just be like where the Nyinginya clan is denser, that's people that were more kind of connected to this historical state, and that's where this reciprocity and this is going to be much more powerful, and other things equal, that policy implementation is going to work better, uh, in those places. So we can run a simple regression, you know, where we put the Imigo mark on the left-hand side. Just trying to, now we're just trying, I showed you like, you know, how the variation in this Imigo mark is connected to real development outcomes. Now we're trying to look at the kind of, the first stage, you know, without running any IV thing here, of course, but just to say what could create variation in, uh, the effectiveness of implementation in the Imigo mark. You see that it's very, uh, robustly correlated with the share of members of the Nyinginya clan at the, uh, sector level. Not just that, the Sindu clan. Who, what were the Sindu clan? Well, that was the clan of the queen mother. So the queen mother, you know, interesting topic for another day. The queen mother was extremely powerful constitutionally within the traditional state in Rwanda. And what about the Ega and the Gera clans? Well, they were the clans of the ritualists. So there was this famous Nyabinghi cult, which was the main kind of religious cult of traditional Rwanda, although it's hard to find out much about it nowadays. Nobody, everyone claims they don't know anything about the Nyabinghi cult anyway, if you believe the historians. This was, you know, and the ritualists came from these two clans, and you find that's also robustly related. So this is all part of the construction of, uh, the state, and it predicts variation in, uh, Imigo effectiveness. Okay, so I'm going to wrap up now just to say, you know, tax, tax is great, you know, you know, but there's many ways to, um, what do they say in Britain? You know, skin a cat. I don't know how that translates into Kenya, Rwanda. Uh, we haven't tried yet, I don't think. So there's many ways to skin a cat, uh, and many examples. It seems like there's lots of tools and instruments you can use to get things done. And raising taxes may be great, but it doesn't seem to be necessary, uh, and it's probably not sufficient either, uh, for getting things done. And I leave you with one, you know, puzzling, uh, example also, which, you know, we find very interesting, which is South Korea. We're all very interested in South Korea, and how did South Korea implement policy, and why was the South Korean state so effective? You know, how did President Park, and not just President Park, but President Roh Tae-woo and Chun Doo-hwan in the 1980s, how did they implement policy? You know, well, the interesting fact is just plotting without putting a caption on the slide. How embarrassing. You know, if I plot taxes as a percentage of GDP per capita on the horizontal axis, you know, against real GDP per capita, you know what's fascinating is right the way through from the mid-1970s here, President Park, you know, kind of full steam ahead, export-driven industrialization right the way up, you know, uh, whatever, 30 years later, there's more or less no change in tax revenue as a percent of GDP, but over this period, and it's actually below 15% also, but of course over this period there's enormous, uh, capabilities in terms of getting people to work and implement policy and kind of, you know, so how did that work, you know? I'll leave you hanging with that, with that question.
