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- [00:00]
A
So, good evening, everyone. My name's Tim Besley. I'm a member of the Economics Department and stick at here at the lse. And we're here this evening to hear about the third in the series on Palampur, this one called How Lives Change, Palampur, India and Development Economics. And I'm not going to even attempt to steal the thunder of our presenters by framing any prior knowledge of the content, but I should say that like many people who studied development over the years, the Palompur project has been a really important one in bringing to the fore some very important issues that can really only be studied with the kind of long run approach that the project takes. Just to reinforce that, before I came over, I pulled my copy of Bliss and Stern from the shelves and to my surprise and rather pleasantly found that I was given a copy to celebrate my entry into graduate school. So it was obviously the book I prized most at that point in my career. We have a panel of five, and I'm going to give only very brief introductions in order to maximize the time that they will have for their remarks. We have the three authors. We have Himanshu, who's an associate professor of Economics at the center for Economic Studies and Planning at JNU and a visiting fellow at the Centre de Science at New Delhi, India. We have Pete Lanyau, a former PhD student here at the LSE who's now at the Free University of Amsterdam, formerly of the World Bank. We have Nick Stern, who's here as the IG Patel professor of Economics and Government and Chairman of the Grantham center and head of the India Observatory. And I should have said I was remiss not to mention that this is an event organized by the India Observatory and Stickard. Then as discussants, we'll have Oriana Bandiera, who's the Suttoni Atkinson professor of Economics and the Director of stikard. And then last but not least, we will have Michael Lipton, who's an Emeritus professor of Economics at Sussex and an emeritus Fellow at the Institute for Development Studies. So we'll hear from them in that order. And start with Nick, in fact, who's going to give a brief introduction, then Himanshu, Pete, and then over to the discussants. So, Nick, it's over to you.
- [02:28]
B
Thank you, Tim, and thank you to all those on the platform. Working together, obviously with Himanshu. And Pete has been a delight. And Michael Lipton was somebody we went to see in. It must have been late 73 or early 74. We went to Sussex to see the Great Scarlett Epstein, the great Michael Lipton and our great friend Clive Bell. And we asked them for advice about doing Village Studies. I won't repeat the advice that we got, but we did it anyway and we've learned a lot from Michael all along the way. And Orianna Bandiera, Chair of Sticker, a wonderful colleague. We hope that this is the beginning of Orianna's work on Palanpur. And of course, since Michael is eternal, we hope that Michael's work on Palanpur will continue as well. So this is a very long project I'm going to introduce to set up the questions of development economics and just say a word or two about how we collected the data. The funders have been. Well, the major funder has been DFID, really from quite close to the beginning, and they've been both generous and patient and I hope that they enjoy what has come out at the other end. Anyway, we're going to go to DFID to present it to them before too long. But it was also, in my case, the very first research grant I got from the British Academy to work on Palanpur. And the British Academy has come in again in funding Himanshu's visit as a British Academy fellow. So lots of people looked after us. But I did want to mention those in particular. That's the book How Lives Change. This is the outline of what we're going. You can buy it outside for a modest 35 pounds, should you be so rich, and we'll sign it for you if you do the. I'm going to talk about the first two blocks here. First to set it up as a book about development economics, because that's what it is. Then say a little bit about the data. The data has been real blood, sweat and tears, but we think it's really high quality now. And then Himanshu will say something about the work on the village and how it's changed. Pete will. Lanyau will say something about poverty, inequality and mobility. And in the few minutes that remain, I will come back and say, well, how did we do on the lessons of development economics that we've set up? So what were the ideas? Well, basically, the central question of development economics should be how lives change. That's the question. It's development economics. In order to do that, we have a data set which allows us to do exactly that. Take us through from the beginning. And what we want to ask is the big classical questions of development economics, which are growth, distribution, structural change. That's what Smith, Ricardo and Marx were on about. That's what Kuznets and Lewis were on about, and they were rightly so. It's growth and distribution and how those interweave with structural change. But it's more than that, and that's something that we can do in a village study. It's also very intimately related with the very detailed micro of institutions and behavior of that village. So what we've tried to do in thinking about theory is interweave the, the big growth distribution, structural change story with a very detailed microstudy of institutions and behavior. And one of the great advantages of a village study, certainly a longitudinal one like ours, is they allow us to put those big growth distribution questions together with the very detailed behavior and micro. Now, we wanted to say a little bit about what we're not talking about. We're not talking in this presentation much about the very quite detailed series on social institutions, technologies and so on. We're going to focus here on mobility and inequality. But on the back of the story of structural change, there are other things which are very important in the book which we're not going to talk too much about. But we did look into them in some detail. But I just wanted to tell you they're not forgotten. They are important. And the whole story, human development, women, society and politics, their interactions and their interactions with the rest of the story is of great importance, but not our subject matter. Tonight I'll say just a few things about future prospects right at the end. This is the third book. In each book we predicted what might happen next. Sometimes we got it right, sometimes we got it wrong, but it doesn't stop us having another go. And I'll just mention that right at the end. So I've already argued that village studies can tell us a great deal about that interweav of the big growth distribution stories and the more micro. And this is underlining it here. But basically, if you want to understand the Indian economy, you'd better understand villages because still, you know, a majority, a big majority of the people live in villages in India. And if development economics can't help us understand what's going on over time in a village which is not particularly peculiar in Palanpur, then it's got problems as a subject. We will argue that there's a lot of things it does help us understand. And we'll argue that there's quite a lot of things missing from that story which we can say something about in the future. We'd like to develop some of that theory. So what about the surveys? Why did we Go there in the first place is the first question that you might want to ask. Well, we had a number of criteria because we wanted to look at change in Green Revolution occurring as a result of Green Revolution or perhaps more specifically the whole story of expansion of irrigation. So we wanted something that had been studied before. My great friend Christopher Bliss has just arrived at the back and we went to see which were good quality studies. And so we went to see a number of villages where there were good quality studies. But we applied other criteria. We wanted to live independently of a caste and household, not too far from Delhi, but because we were doing some teaching there, but not too close. So it wasn't overly influenced Green Revolution in large measure about wheat. So it should have a lot of wheat. And a lot of the theories you wanted to look at were about tenancy. And so there should be a lot of tenancy and nothing particularly unusual about the village. So some villages are dominated by a particular activity of weaving or brass making or whatever they might be. So we wanted to have something that was not particularly unusual. There are now what, 600,000 or more villages in India. And what you can't say is that this is a representative, but this is the set of criteria we brought to the table. That's where it is in Moorallabad district of up. A couple of hundred million people of course is rather important part of the world. And this is something which is up, the sort of east end of West Up. So it has a lot of characteristics of the east side which are not particularly, well, which are poor, but it's not sort of a classic west up, really dynamic village at all. So they have the initial surveys. I've already mentioned that Christopher Bliss and I were involved in the first one and we hired S.S. chaghi Jr. Who was the younger brother of S.S. chaghi Sr. Who had done the first two studies. And they looked rather alike, which was helpful too. Gendry and Naresh Sharma very prominent role in the next one. And then there was a very quick survey in 93 by Jean and Naresh on the back of the DEC that they'd had. That was a thinner survey, but given that they'd done the preceding one in great detail and lived in the village for 15 months, that quick survey was still pretty good. Now by far the biggest is the two year survey, 2008, 2010. And again we did a follow up survey in 2015, partly from embarrassment that we hadn't yet finished the earlier analysis. And as time went by we felt we ought to keep going. So one study for every year since one study for every decade since independence and I hope in 30 years time we'll come up here and say we've got one study for every decade and that's I have to sort of eat well and live well. But basically the story of this is that if you want to do longitudinal studies, you've got to start young, live long, but most important, find wonderful collaborators who are even younger than you are. So little bit of pictures. That's the first book that came out and I know there are a number of proud owners in the audience of that book with the green cover, that's the Indian one, it's the red cover, that's the British one. The middle there is SS Chaghi junior The right hand side is VK Singh and that's me when I was even younger. The team photo there very important to recognize that we had many more. We had quite a few women involved in the 2008.09study and that makes a big difference. This is difference between a dirt lane and a brick lane. This is a village that's moved forward. It's still very poor and we're going to talk a lot about the advancement. It's still very poor, don't get us wrong. But the difference between mud and brick really matters. If you look at the drainage there on the 2009, that is much. And you could imagine what that dirt lane would look like if it had been raining. These things are big differences. Outdoor less 1983, quite good school buildings by 2009. So progress. But of course what goes on and what the school teacher does and whether the school teacher turns up is a different kind of question. So that's the big questions, how we collected the data, lots of qualitative data along with the quantitative data. These are not some data point that we don't know. These are people with names. We know the names and we know the people. So that's the story. And then let me now hand over to him, An Xu. Oh, one last thing. That's a village compound there and you can see the difference between 74 and 2009. Everything is hand and bullocks in the 1974. But there you've got a mechanical Menta oil press. But let me, as I note the progress, as we mark and discuss the progress, don't get carried away. This is still a very poor village.
- [13:30]
C
Thanks Nick. I'll quickly give you a snapshot of what has happened to the village over a period of time. And there's a long period of time that we are talking about and in this period, the change that we have seen in the village is not a uniform change in the sense the first 30 years was change which was basically driven by what was happening to agriculture and green revolution was a big part of the story. But it is the next 30 years which actually went out of the prediction, which was not the prediction that they had in the book, in the second book that they had. And that's something which is a deeper story, the dynamism of what is happening in the last 30 to 40 years, a very important period for India's growth and looking at what is happening to overall structure in the rural areas as well as the integration with the rural and urban. So let me try and briefly give you roughly broad picture of what has happened to the village in that sense. So village is not, as Nick has more pointed out, it's not unusual in the sense of the growth rate of the village. Per capita income is not something which is very different from what you find in a normal average Western UP village in that sense. Obviously there is an acceleration in the last three decades which is what is there in the Indian case also. And that has also impacted how people have. Lives have changed. In a sense there is materially more assets which are there, production assets, consumption assets. But still, as Nick has pointed out, it is not something which is a village has become a prosperous village. It's still a very poor village ways not just in terms of income, but also in terms of other aspects of development, particularly education, health and those issues. But the drivers of change have been different in the sense. And the first one, as I mentioned, is agriculture, which we'll come back to in a minute. But the second part, which is the growth which was driven by the non farm or the integration of the village economy with the outside world which has impacted different groups in the village. And I'm using caste as a group here, but we can do it in different ways and it has been different ways, taken up opportunities in different ways. The Muraos, the so called agricultural caste, the traditional agricultural caste, the dominant caste in the village, who were quite successful in the very first 30 decades and took advantage of green revolution in the second period, which is the last three decades that we are talking about, the non farm sector is where the jot ups, the Scheduled caste, the Untouchables, earlier Untouchables are the ones who have taken these opportunities in a big way and have seen rapid change, I mean dramatic change in the way they have accessed labor markets, credit markets and different forms of market. And I think Those are the different dimensions of the changes, is what we are more interested in. And some of the nuances Peter will bring out when he's talking about change over a period of time. But also just to say that the other aspects of development and education and health, we have seen improvements. And again, improvements are better compared to what the improvements were there in the first 30 to 40 years. But still lot is desired in the sense particularly the quality of public services. Schools are there, buildings are there, but the quality of teaching and the presence of teachers. So is the case with the health centers. Those are really things which have not improved to that extent. And so is the case of the role of women in the village society. It still is something which is at the periphery. Women are no longer, I mean, still not part of the village economy in that sense, economically not very active and therefore not very visible in the village sphere. But things are changing, and we hope that in the next 20 to 30 years these things will change because there is obviously more women are going to schools and it will have some impact at some point of time. And the third is again the institutional society, partly driven by what is happening to the village itself, what is happening to the tenancy market, labor market and the credit market. And that has been driven by changes within the village, the integration with the outside economy, but also driven by external factors. For example, the 73rd and 74th Amendment, which brought in the election to the Panchayati Raj system, has brought in reservation for the village headman, which is. We had a village headman who was a settled caste, and now we had a village headman recently a woman as a village headman. Those have also impacted the way. And also more money going into the village through various schemes has led to different ways of people interacting with the elected institutions. But in some senses, the more things change, the more they remain the same. So, for example, the Thakurs, which are the dominant caste groups and the richer caste groups, they still control a large part of the. Say, for example, the formal and informal institutions. Not directly what they were doing earlier, but maybe in a different ways through collaborations and through collision. So those are things which are important. But let me just quickly run through the basics of what the village is all about. It's not a big village and it has. The population has grown by roughly two and a half times over a period of time that we are talking about, and not very unusual in terms of what is happening in a normal village in western Uttar Pradesh. But in terms of income and output, we have already told you about what has happened to income growth. And you can see the poverty rates have declined quite dramatically from around 85% to around less than 40%. And not very again, very similar to the average that you get to see. And I'll not talk about inequality, which Peter will talk at some point of time, but if you just look is happening to daily product wages, which is like how much does your daily wage buy in terms of wheat? And you can say that there is again improvement. So those are material improvements that we are seeing in the village. And those are important indicators, important markers. But more than the processes as to who benefits, who gets who is benefiting and who is losing out, who is getting excluded from the process. I'll just talk about agriculture because that was the focus in the 1970s when Nick was going, Enoch and Bliss were there trying understand what is going on in the village economy in terms of. And you can see, I mean those yields increase that you see between 62 to 74. And they have continued to grow. And by up to 2008, that's something which is there in the wheat paddy, mostly in the wheat and paddy, not so much in bajra and other smaller crops. So those things have happened. And how did that happen? That happened simply because there are two things that. And the process continued. And the technical change in the sense is something which is mechanization has continued, but also irrigation. And irrigation has increased. It used to be less than half or almost half of the village that was irrigated of almost 100% of the village is irrigated. And irrigated very intensively. And irrigated intensively has also meant that the cropping intensity has gone. So the number of crops that you can grow in a particular plot of land has almost doubled from around one to it has gone to almost close to two. And again machines have come in in a big way. The track number of tractors in the village is quite high now. And something which is 15 tractors that we had in 2008, nine. By 2015, the number of tractors were close to 25, 30, 25, 26, which is quite big for a small village like that. But also they have concerns in terms of the overuse of natural resources. But what it did end up doing is that it released labor from the agricultural sector. And that is the labor which was trying to find employment in the non agricultural sector. Tenancy market also changed. And partly driven by. Because people were now more occupied with the non agriculture sector, they had less time to supervise. So the contracts changed. People sold land and there were outsiders who Got access to land. And therefore that has changed as it is there. So the overall extent of tenancy hasn't changed and the number the area that is under tenancy. But the forms have changed, the contracts have changed, new form of contracts have emerged. For example, Chauthai is a very important contract that has emerged over a period of time. More taken by the Jata lower caste people. And those are things where we see. I mean we say a lot in the book, but this is the part which I thought was important and I'll spend a little bit of time on this. What is basically changing in the last three decades. And this is the non farm activities. One sense the non farm is a residual category. What is not farm is non farm. But it's also a very dynamic category that we are looking at. And three things. Again, the way people are accessing non farm is different from what was there in the 1980s. In a sense it is not the regular formal kind of jobs where you go in a job, take a job in a factory, but mostly casual kind of jobs and without moving out from the village. It's the commuting, the transportation and the communication links have made it much more easier for people who are at the bottom end of the distribution to access those jobs which are not earlier available simply because they require skill, contacts and social connections. Those are things which are not required. So more in these kind of informal jobs they had an impact. And it has not only impacted in the sense people are now getting more, but also all the households now. I mean if you look at the number of income sources that households have, so this is what we call as a pluri activity. So the number of single source households have obviously come down. More and more people are diversified not just in terms of income sources but also the number of income sources. And that has led to increase in non farm income sources from around 13% to around 47%. And also been something that has been reflected in increasing employment in non agricultural sector. Quite a dramatic increase in the last two to three decades. That's the same thing on thing. But let me say how did it impact the different caste groups and Thakur are the most dominant. Grass caste groups are the ones which had access to land. They also had access to non farm jobs. At least the regular ones in the beginning of the period. But in the 1950s, if you look at it, almost 90% of them were. More than 90% of them were actually in agriculture. By 2015, the share of population which is working among the thug was working is less than 1/3, and you can see that the huge diversification happening to the non agriculture sector, not just in the regular ones but also in self employment, little less in casual employment, but regular still predominates. The startups also have more or less the same kind of transition going from more than 90% in agriculture in the 50s and 60s to almost more than 70% by 2015. They were all in. But compared to the Thakurs you can see that Jatar entirely. I mean almost all of the non farm diversification is actually in casual, very little in regular and very little in self employment. So that transition into a non farm has taken two different routes for us. These groups are there, but the third group which was the most entrepreneurial and took advantage of the green revolution was the morals and the most industrious and they call themselves, take pride in the fact that they're agricultural community are the ones who have seen the least diversification. 50% of them are still in agriculture. Very little have actually moved out in the non agricultural sector and not certainly in the regular sector. And remember the Morales and Thakur were almost same economic status in the 50s and the 60s. But the trajectories that they have taken and the way they have taken opportunities in the non farm sector is completely different in the three groups that we are talking about. The details of this is what Peter will work out. And so let me hand it over to.
- [24:06]
D
Hi. And so I'll follow up from Nick and Himanshu's introductions of the village to focus on a theme that has been a real interest to us in studying the economic development in Palampur. And that's really to look at the distributional consequences of what we have observed in terms of the changing structure of the economy, the population growth, the overall economic growth. But what we're going to try to look at here is I just wanted to note the following items. What we've seen in the village is considerable economic growth that has occurred on a year by year basis. It's been fairly gradual and steady and this has been associated with a fairly significant decline in poverty. When we think about poverty in sort of conventional terms, thinking about an absolute poverty line, an official poverty line, we're seeing poverty fall from around 80% in 1950s to somewhere in the vicinity of 35, 40% by the end of the survey period. So that's a really significant decline in sort of conventionally measured poverty. What we've also seen over the same time period in this village is a rising increase, a rising inequality. This is something that's rather unusually observed or discussed in development economics. I think because it's conventionally the practice is to measure inequality at the national level, at the aggregate level. And it's rare that we have information that allows us to meas inequality in a kind of credible way at the very local level. But one of the insights that's coming out of the Palanpur study is that this process of economic development that has been taking place has been associated with rising inequality in the village. And the rise in inequality has been particularly pronounced during the second half of the survey period. Alongside the question about what's happening to inequality is a related question about, well, what is the nature of this inequality change? Is it a story of sort of a stretching out of the income distribution, or are we actually seeing some sort of frogging and transitioning from in relative positions of different parts segments in the village society? So that takes us to an inquiry into economic mobility. And what we do in the Palampur story, again, is we are able to investigate this in considerable detail and we can document considerable increases in mobility over time as well. There's a nuance around that increase in mobility which relates to intergenerational mobility, which I'll come to, which is quite intriguing and is worth, I think, further, further analysis and research. So in the end, what we see is a relationship, a story of economic development that's not an unadulterated positive story because it's a story of economic growth, poverty, decline, all very good on the one hand, but also a story of sort of increasing differences in relative standards of living between different individuals and households and groups in the village. One of the nice things about the Palanpur study is that we're able to employ both sort of quantitative data on incomes and so on, and then juxtapose that and also with impressionistic information that we have just from sheer exposure to the village. The fact that the fieldwork has taken over over a very long period of time. In most of the years during which data was collected, as Nick mentioned, Jean Dres and Naresh Sharma spent 15 months in the village in the 1980s, and then we spent two years collecting data in the 2008 round of the survey. So that gives us a wealth of information which is not necessarily always easily translated into sort of quantitative information, but does give us a means to sort of provide, get an assessment of the living conditions or standards of villagers. And we use that information to construct a ranking variable which we call an observed means indicator. And that provides us an additional way of looking at relative standards of living between different households in the village alongside the information we have about their incomes. We can use that information to then look at different indicators or ranking variables and to try to see what kind of stories are they telling us. And it's somewhat reassuring to see that most of the different indicators that we can use, whether it's consum or whether it's income, or whether it's an asset indicator, or whether it's an observed means indicator that I just described, or whether it's a participatory sort of ranking assessment variable, we can see that the correlation between these different indicators is positive, but at the same time it's far from perfect. The correlation and there's important differences and different type of insights that one gets from looking at these different types of indicators. An important dimension of the differences is the fact that we have some indicators that are capturing long term living conditions. Conditions and other indicators that are much better at capturing sort of short term, are much more prone to be affected by short term events such as the quality of the harvest, or an attack of pests in the fields, or the fact that some households are preferring to save rather than consume their incomes and so on. So we can have explanations for understanding why there may be differences across these different ranking variables. Looking at them all collectively, we can get a much richer perspective on what it is that's sort of driving and sort of what is the nature of the distribution of well being in the village. The data on inequality conventionally measured is on the basis of income. And we can see in this table here that inequality was actually relatively stable and even showed some decline during the first sort of half of the study period. And we relate this declining inequality, perhaps somewhat surprisingly to those of you who are familiar with the literature, to the fact that there was this green revolution, this agricultural intensification, which in Palampur was heavily associated with the expansion of irrigation in the village. This expansion of irrigation from around 50% of the village to 100% of the village by the mid-1970s was associated with kind of an equalizing effect as some of the households who had previously been un irrigated were now able to catch up and cultivate in the same intensive manner as the previously irrigated farmers were. So there was an equalizing effect in the village in the first half of the study period. And then as Himanshu mentioned, we had the diversification process really kicking off with non farm activities becoming ple and different types of non farm activities, casual wage work, regular employment, self employment activities, businesses and so on. And this then Generated sort of differences across households. And so we see quite a significant rise in inequality. Such that if you look at this table, across any of the different measures of inequality that you may want to employ, the final year inequality estimates are much the highest in the different survey years. So inequality in the second half of the period really registered this significant increase. One of the interesting dimensions, and this is bringing the story beginning to sort of investigate this assessment, this story of mobility is to look at the relative fortunes of different population groups in the village over time. So if we look at this table here in the 1980s, we see that the Morrows, which were this traditionally cultivating caste, were actually quite high up in the village ranking. The ranking here is in terms of this observed means category that I had described. And we see that the Maraus were quite high up this ranking because they had really taken advantage of all the new opportunities from technological change in agriculture and so on. So they were ranked quite highly. And the Jatabs, this traditional agricultural labor caste, was very much positioned at the lower end of the village ranking in terms of this observed means category. When we then go back to, when we go to 2008, 2009, we see that there's a stretching out of the moraos. We now find moraos also in the lower segments of the observed means classification. And similarly we see jatabs now appearing in the upper rankings of the village in terms of this observed means. The Morales are suffering from the fact that they did not take such an advantage of the opportunities in the non farm sector, tended to stay focused on agriculture. Agriculture was just not generating the same kind of growth and returns that it had been generating in the first half of the survey period. Whereas the Jatabs, on the other hand, who had historically been agricultural laborers, were now beginning to move out of agricult labor into the non farm sector. And those that were doing that were seeing their economic fortunes improve. So we see this is the kind of nature, some mobility going on there. With the jatabs moving up in rankings and the Morales moving down. So this analysis suggests that there has been an increase in mobility over time. There's more if we construct transition matrices, for example, that sort of document the relative position in different quintiles or so of the income distribution. We see that there's more households now appearing off the diagonal than there were in the earlier rounds of the data. And this is probably in all likelihood due to this expansion of the non farm sector. We see the rise of the jatabs and the decline of the Morales as being A really important part of the story of this income mobility, there's some nice things about Palampur again is that these data points that we're working with are not just anonymous data points, but we can actually go and investigate the specific circumstances of these individual data points. So here are just a few examples of upward mobility. There's a tele household. A tele is a particular group in the vill comprised of Muslims. And this particular telia household really moved up very sharply in the welfare rankings in the village by diversifying very effectively and very efficiently into the non farm sector. Setting up a motorcycle repair shop. This menta mill, this mint oil pressing mill that we saw a photograph of was owned by this telly household. They diversified into a variety of activities. They remained unified over the study period rather than splitting up, which is something that is often associated with downward mobility. And so this telly household is an example of clear upward mobility. A Jatab household is also another example of upward mobility by engagement into the non farm sector, getting a job as a casual laborer in the railway yard, then developing contacts in that sector, and then slowly rising in the rankings to become the foreman of one of these labor gangs. So this is an example of upward mobility of one of these Jatab households. Of course, downward mobility is also occurring. The re rankings are associated with both upward and downward mobility. An example of a downward mobility is of the household in which illness has been playing a very significant role. There's a household where there's the head of the household became ill and died. Subsequently, another family member had an accident and was unable to work in the same way as before. And this directly translated into downward mobility of this health household. Dissipation is also something that we have observed in the Palanpur case in the sense that households taking on certain behaviors that just really are not in the long term interest of their economic well being, gambling, drinking, taking on loans to usurious money lenders and so on. This is the kind of pattern of behavior that then spells downward mobility. Now I had mentioned that there were some interesting nuances to the process of mobility in the village. And one of those dimensions that's particularly interesting is the pat intergenerational mobility. So we've seen rising mobility, leapfrogging, transitioning in and out when we compare from one year to the next. But we're also able because of the long nature of the data for Pampur to actually compare two whole generations across time. We can look at the relationship between a father's income and his son's income. And we can do that comparison between 1957 and 1983 and then again between 1983 and 2008 and 2009. And we can see, we can document in the Palampur case that over time a father's income has become a better predictor of his son's income than it was the case in the early first half of the study period. There seems to be some decline in the intergenerational mobility in the village, something of an intriguing finding that we haven't noticed elsewhere in the literature and something that we definitely want to pursue further in future work. So I will turn now back over to Nick for the final remark. Remarks.
- [36:30]
B
So thank you, Pete and Himanshu. Let me go back to the questions which we set out at the beginning. What do we learn about development economics from all this? Well, the big story that you get in dual economy models, in people looking at the economic history of the sectoral makeup of economies, is that you see a move out of agriculture into other things. Those other things could in principle be manufacturing or services, but out of agriculture into other things. That is indeed the story of Palanpura, as we've seen very clearly. But the rest of the story about how that process happens, what people are moving from and to, does actually look very different. And here are half a dozen ways, important ways, in which it looks different from a standard dual economy model. This is about commuting on the whole, rather than migration. The very dense population on the Indo Gangetic plain means that there are towns which service that population not so far away. And Palanpur no exception. You can get to a decent sized town within an hour or so. So it's commuting. The mixture of activities on farm and off farm are not simply moving out of one sector into another, far from it. It's what's called pluri activity. People do lots of different things. It is not moving out of sector, a backwards sector, into another sector which is more advanced and capitalistic. It's different from that. The it's not a story of agriculture being sort of dreary and backwards and people just prodding around, not using very much capital. There's a lot of investment in the agricultural sector. It's driven a lot of the increase in incomes in the early stages and it's released labour to move into the other sector later on. Again, that's not part of the story. The information flows are a very important part. It's not that everybody knows exactly what's going on. Information has been very important and the mobile phone has been a important, very, very important part of that informational change in recent times. So you can go off and get a job. It might be all these jobs are pretty rotten. Not all of them, but most of them are pretty rotten. Jobs like moving mail bags, sorry, moving bags out of a truck in Muralabad station into, out of a rail truck, into a road truck, brick kiln making. A lot of the jatabs have been involved in that. That's a truly rotten job. I mean, patting out the mud and then in rather dangerous ways, baiting, making it. But the information flows, particularly around mobile phones, have been very important here. And we've seen also that the advance of the new sector or new sectoral activities fundamentally change what goes on in the old sector. There's a great endogeneity there. As people move out, they supervise less and they can supervise less. And the land contract changes as a result of that. Much more fixed renting, you see, you see the endogeneity of institutions in that sense. And we'll look at that in a bit more detail. But basically those very big differences are crucial to understanding what's going on. They're not minor, they're major. And informal is basically normal. And we have to be very careful then in thinking through, in policy terms, how far we push against informality. Informality eventually will move and eventually become more formal. But again, you know, you see in our own economies the gig economy in some ways moving away from formality. So how those change, I think is a very big issue in the way in which development occurs, including actually in advanced sector economies. Also on entrepreneurship is a big part of the story. And in this story we like to refer to the Kuznets insight rather than the Kuznets and Lewis model. The Kuznets insight is the same as Deng Xiaoping's insight is that some people get richer before others. That's a very important insight, but it's not. The model itself actually doesn't do very well. The agriculture, we haven't dwelt on it. There's an awful lot in the book, an awful lot in the data collection on agriculture you follow right through all the activities, what goes on, what the inputs are, who's doing what work. It's incredibly labor intensive activity for researchers, never mind about agriculture being labor. And so all the graphs you've seen, there's huge amounts of effort behind putting those together. But I won't dwell on that. Basically agriculture and Christopher Bliss and I can came to, roughly speaking, that it was moderately efficient and Markets do function, particularly markets for services do function. And that stands. But what is different, I think is two things. One is now we see much more deeply the importance of information and trust. And if you're renting out your land to somebody on cash rent, they can look after the land well, they can look after the land badly. And we want somebody who's more likely to look after the land well. And so information and trust is important, important in that story. Secondly, investment in agriculture, which has continued to be strong, is now much more labor releasing into other activities than before where the investment in agriculture, particularly the double cropping, led to greater labor intensity. So it's gone from investment intensifying the use of labor to investment releasing labor from agriculture into other places. We've seen that mobility and entrepreneurship, which in the early part of the period were around investing in agriculture, can lead to reductions in inequality. When that mobility in entrepreneurship is about catching up. But then in the second part of the period it went the other way that as new opportunities are now emerging, the Deng Xiaoping Kuznets insight came kicks in. And some people get richer before others. So the answer to the question does mobility increase or decrease inequality? Well, it depends what sort of mobility and what sort of opportunities are being taken. And we know where to look. And this helps us I think know where where to look. Entrepreneurship has been very important in all this. And that's behaviour in institutions is the fourth part of what we've learned learned about development economics and the principles of development economics. Institutions really matter. Zamindari Abolition, which gave the rights to tenure. I mean nothing is ever full but much better rights to tenure than you had before allowed and fostered that investment in agriculture. It was very important the institutional structure to the economic consequences, particularly tier investment. But we see also rather interesting stories about endogeneity of institutions themselves. I've already emphasized the way in which the whole method of labor contracts has started. Sorry, the whole method of land contracts has started to change as a result of the less time available for supervision. That's the expansion of the outside affecting the institutional structure of contracts, if you like, on the inside, where we use institutions in standard sense of rules and and organizations. But we've also seen that the nature of the tenancy contracts is influenced also by an interaction between technology and social institutions. Let me explain. The jatabs couldn't hire inland in the early stages because they didn't have the draft animals. And without the draft animals you wouldn't be a respectable valuable tenant. They couldn't hire in the Draft animals because the people who own the draft animals wouldn't let them out without their being with them because people would misuse the bullocks and he buffalo. But at the same time they couldn't come and do the plowing themselves because that would be degrading. But now you've got tractors and tractor services are rented out and the guy sitting up high on the tractor is not at all degraded when he's actually selling the tractor services, actually showing off his tractor in circumstances where it's quite good to have a tractor. So you've seen the interaction between the technology, the social institutions and the outside opportunities because you have to have the money to hire the tractor. But now if you've got a job outside you can. So it's a rather interesting interaction between the outside jobs, the social institutions and the technology which changes the nature of contracts and institutions within the village. Finally, in developed economics, people don't talk enough about entrepreneurship. Entrepreneurship. But these people, very poor, not particularly inspired many of them. But they identify opportunities and they embrace risks to take those opportunities. That surely is a reasonable meaning of the term entrepreneurship. And we've seen how different people respond in different ways. We've emphasized that some castes have different kinds of advantages relative to others and that influences how they respond. But in all these things, the within caste variation is bigger, a lot bigger than the across caste variation. So there are systematic elements to who's entrepreneurial or who's successfully entrepreneurial. But they're also elements associated with who people are. And that's not in the jargon, unobserved heterogeneity. It's observed, observed heterogeneity. We know who they are and we've told you something about who they are. And looking at them tells us a lot about entrepreneurship. It's called qualitative data, but it helps. Quantitative data helps too. They're not in competition one with the other. So we haven't said. I've said we're not dwelling on society here. Please do look at the book from that point of view because we don't want to give the impression it's unimportant, extremely important in what we've been doing. But it's a pretty inferior politics that's going on in Palanpur. They don't assert very well. Other villages are much better at insisting on what they're entitled to than Palanpur. But at the same time, when bad behavior of the pradhan, the head man got absolutely egregious. I mean, molesting, drunkenness, making off with the school dinner money and all that stuff. Eventually they said enough is enough, and they threw him out. So it's a very weak set of politics, but it's not totally inept. It's just inept politics. But there's a real set of questions here, and that's something that would be great to look into. Why is it that politics is weaker in Pollenple than elsewhere? Now, we did go around and look at a lot of other villages. We walked and walked and Christopher and I did it, and we did it later on. We walked and walked to see other village. We've compared this village with other village studies. And Iman Shu, with Jerry Rogers, edited a book on comparing, one main purpose of which, comparing Palampur with the other villages. But we're still left with wanting to know more about why. So this, then, is the final slide they're offering. I'm not going to go through it in detail, but what I want to emphasize in this slide is that the stories we've told, told you could not have been told without not only the long passage of time, but also the living there and the qualitative data. We've got a big quantity of qualitative data and we've got high quality of quantitative data. And you need both those things to tell the kinds of stories. Now, it's not one or the other. It's just in our case, we learned a lot by putting them together. We've tried to tell you the story of. Of growth, distribution, structural change in a way which is intimately related with the behavior and the institutions that are going on. And we couldn't have done it without the data set that we had. I promise to say just a little bit about prediction and then I'll stop. I think the informal is normal, and the importance of informal in growth and expanding opportunities will continue from a while and probably within it. An increase in inequality will continue for a while. At some point that will probably flatten out, but we've still got a way to go on that one. There are quite a few things which have been unimportant up to now. Education's been unimportant up to now, really in job opportunities and income. Migration's been unimportant up to now. The environment and climate. You'd expect me to say this has. You'd expect me to say something about that, but you wouldn't expect me to say what I'm about to say. The environment and climate has not been particularly important up to now. My goodness, that's coming. Give it another 20, 30 years, you'll see changes in the monsoon, you'll see be changing in the flows off the Himalayas. There's some nasty stuff coming, but not yet, it hasn't happened. So what we're saying is those things which we're saying are relatively unimportant up to now, education, migration and climate environment are going to get more important as time goes by. Now, we said that education would get more important last time, but we're going to keep at it. We're going to say education to get more important this time and I think this time we get it right. And there's one final prediction that I will make, is that there'll be more studies on Palanpur. And I hope that the people on this platform, from the eternal Michael to the youthful Oriana and of course my wonderful colleagues, that they'll keep going, but I hope I'll keep going as well. Thank you very much.
- [51:12]
A
So we have Michael next and then Orianna. Is that all right?
- [51:15]
B
We could be right.
- [51:17]
A
You're right.
- [51:31]
E
I'm going to first of all make some general statements. Then I'm going to suggest some things which might be done with this absolutely marvelous work inside this great book. There are other good books waiting to get it out. First of all, the analysis of gross village product and then via a food, labour price, quantity picture of Palanpur. I'll say a little more about that when I get to it. I'm going to look very briefly just at the results on population and on agriculture and then I'm going to look at any other. Many congratulations on the longest completest and in my view, best village analysis and data set that we've got, not just from India, but from anywhere. It's an investment of lifetimes and your lives have certainly changed our understanding of the lives of other people and will for a long time to come. Village data are useful in themselves because relations within them, village matter a lot. Both relationships of land ownership and a whole lot of relations within the village are specific to the village. But those village data, of course, are composed of things below village level. First of all, group data by castes and so on, and below that level, primary household data, farm data and individual data. So there is an awful lot of hypothesis testing that can be done on the basis of this work. And I know you've done a great deal of work to and make computable the findings of earlier surveys right back to 57 to 8. So I hope that there is good database access here. Now, looking beyond the village level, that's Looking below the village level one, there's a lot of embedding here and quite a lot of it is done in the book the village in the context of Maradabad district, Uttar Pradesh State, India, rural data within India and data from elsewhere where we can make some comparisons. Secondly, looking beyond means, comparing this village with other village studies, now there's nothing quite so good, but there are others that are very interesting and there are also cross sections of village studies. And it's very interesting to ask the question, is there anything that we can say about the time series that we can then look at in the context of other cross sections? For example, the village studies program program produced some quite interesting generalizations about the relationship between migration in a village and inequality within that village. Does this apply to the trend data as we read them from Palanpur? So this goes for a lot of further work. I very much like this work to be used used to make a set of gross village product tables looking at product approach, income approach and expenditure approach separately. Quite a lot of that is done indirectly in the discussion of poverty, but it's not actually done in respect of the total village or relationship to village means and medians. And I think that would be very useful in the case of output to compare the structural change given for India with what we find in Palanpur. Sectoral change in the case of income. To look again at the comparisons between Pal and poor and others when we have GDP type measures of income. And in the case of expenditure, again, both composition and distribution can be compared on the basis of a gross village product approach between Palanpur and elsewhere. As I say, a lot of this has been done for poverty. I'd like to see it done for the village as a whole and to relate that to the excellent qualitative, to quantitative comparisons that are made in this village. A lot of what I'm saying is rather square. I'm saying that having done this wonderful work, qualitative work and work on pulling the quantitative and qualitative together, there are things that can be done with the quantitative that would deepen it and give it a different context. Now, the main thing I want to say, it's a sort of key proposition that comes out of the Malthus debates that if you know the initial level and trend of population and staples production, you can predict most of how lives change for the poor. Now, is that right or is it not right? My suggestion is that it starts being right in 1957 to 8 in this village and becomes less right as time goes by. So going back to 57 to 8, a large proportion of consumption is food not only, although even more for the poor. And a large amount of food is staple food and labor goes overwhelmingly to producing staple food. So if we know how the conditions of those things change, we know how wages rates and the price of the main staple change. Putting those together, we'll be able to track what happens to poverty. So village welfare can be tracked largely from the price of staples and the price of labor, which themselves will depend on changes in population, labor supply and changes in agricultural technology. And I think one could probably do quite a lot of that on the basis of the Palanpur work. Looking at village demographics and looking at agricultural production and that the extent to which such welfare tracking via the corn wage, if you like, fails, indicates the role of changing migration and commuting, the role of the changing non farm share within the village and the role of changing distribution of income in the village in distribution of land as it's affected by other things. I think all the materials to do that analysis are there in this book and I'd very much like to see it done. Looking briefly at population agriculture separately now we have population between the first the 57.9survey and the latest 2015 measure going up 2.4 fold, much the same as rural India in the same period. But we have a big demographic transition here. The rate of growth is 2.5% up to 74 to 5 and then to 2015 it falls to 1.7%. So a big reduction in population growth and rising baby survival. Now what that rising baby survival does is in the first period greatly improve your. So I'm sorry, rising baby survival. First of all, the babies survive to be children. So that 100 working age people in 1957-8 have to carry 74 dependents people of not working age. But if we go up to 1983 to 4, I'm sorry, 74 depends. If we go up 1957 to 8 to 1983 to 4, that has risen to 92 dependents that 100 workers have got to carry. And if we go to 2015, it's fallen right down to 2017 to 67 in 2015. So dependency ratio of 74 up to 92 then down to 67. These are massive changes in implicit well being. If nothing else happens, they would on their own mean big falls in welfare from 57 to 83 and big rises in 83 to 25. But a whole lot is going on as a result of these changes. Population growth is affecting labor supply and labor demand. And those in turn are affecting the real wage both via the money wage and via prices. And all this can be followed out and tracked through the information given in this work. But increasingly as time goes by, migration and commuting, the rural non farm sector affect this. And I think we can trace all this very well through these data embedded in data for Muratabad, the District Census handbook and in data for Uttar Pradesh. And we can really track the extent to which population change and agricultural technology change alone account for the changes in poverty and income distribution which attract elsewhere were in this report. So what's happening then in agriculture? How long have I got?
- [60:22]
B
One minute.
- [60:22]
E
Okay, what's happening in agriculture? First of all, you can compare 57 to 8 and 089. Second, what we're noticing in this comparison is that cultivation income has only gone up from about from one to one and a third. It's gone up by about a third. Whereas total income in the same period has gone up more than five times. So what's the gap? The first thing is obviously farm profits, but the second gap is that non farm income is rising dramatically faster than farm income, including income from remittances. And so we're getting rather slow growth in net cultivation income, yet enormous growth in gross farm output measured here by these very huge rises, particularly in wheat and paddy output. Wheat output rises 12 fold and paddy output rises 126 fold. And no, that is not an arithmetical or a typo mistake. It was on a low base. But these two main staples have absolutely increased extremely rapidly in growth output. It's translated into a much smaller rise in cultivator income. I should say one thing about agricultural growth. Briefly, there's been a big change in the sources of agricultural growth in the village and that's echoed in all India. In the first period, irrigation leading to a higher growth cropped area. In the second period, a shift to high yielding variety based fertilizer yield based growth. And in the third period, in the last 10 years or so, growth in total factor productivity. And it's very interesting to see where that is coming from. Finally, one minute. Any other business? Nationally, as in Palanpur, agricultural GDP accelerated much less than non agricultural. Is that a worry? I don't think it's a worry. It's what we call development and it also follows the patterns of consumer demand growth. We can periodize this, as I've said, and we can see in fact agricultural growth rates rising over time and no apparent falling off. There was a great worry in India that there would be a falling off in agricultural growth rates as the green revolution faded out. This is not happened either in Palanpur or in India as a whole. But it does leave a worry and that worry is whether this more rapid agricultural growth in recent years without a big rise in input means soil and water mining. Whether this is sustainable and particularly the wheat paddy double cropping year after year is known to raise major sustainability problems and I'd like to hear a bit more about that. And I want to leave you with a final question. Has Palanpur's development path shifted from a grid based pattern already connected to grids by being with by having its own railway station, more use of commuting, more use of migration the entry introduction of electricity standard grid based development. Now are we seeing the possibility of more non grid based development development with solar cells, smartphones, very rapid price information reducing the need for travel that would dramatically change the capital intensity of development in Pah and poor in the future. Congratulations on a marvellous work.
- [64:08]
F
Okay.
- [64:22]
G
Great. So thank you so much. It's really a pleasure to be here. I think I can change the title of this book to how my life changed thanks to Palanpur. Little do they know, the authors that I was studying economics only to find out that economics was about things like the public debt and inflation and things of the utmost importance but also in my opinion of the utmost boredom. And I was about to change and go back to philosophy where I wanted to be when Nick's son came to Bocconi, my alma mater in Italy and gave a one week course on Palanpur. That's where I changed my mind and I said if this can be economics, I can do economics now. About two weeks ago I found out that my husband went through the same process. He saw genres presenting Palampur and also decided not to abandon economics. So clearly you've given lots of hope to lots of economists and it's not just the life of the Palampur people who changed for the best you might case now I couldn't resist. This is a strange font. I can assure you I didn't choose it. I couldn't resist looking at the data that Himanshu kindly shared with me. And so I'm going to make two very quick points. I have the data with me and I'm waiting for somebody to ask me what did I do to the standard errors given that I have the entire population. Never happened before, it would never happen again. So I'm going to to look at which change we should measure the change of who that is, how should we define the unit of observations here? And then how should we measure the change in poverty? So coming to who, we can look at the lives change of the individual households. But clearly the caste plays a very important role in palampur. And to the extent that there is very high risk to sharing within caste, to the extent risk sharing is perfect even then it makes sense to look at the cast income and how that changes, how the distribution changes. So because we can do this, we will do it. And there it goes. That is the cast share of total village income. So I sum up all the income of the morale or that occurs and other JDFs and plot them in there. And as you can see, not much changes. The two top groups have about 27%, 26% on average of total income. The bottom guys have about 18% and there they stay. Now it's interesting of course to relate this to the share of the population because if these share of income are the same as the share of the population then the distribution is perfectly equal. But it is not so. So the line at 1 is the equality line because this is the ratio between the share of income of the caste and the share of the population. And as you can see the mura that occurs get more than the fair share and the jatabs get less. But as you can see, you see a pattern there that both the mura and the takurs are going down and the jatabs are not going up. So what's happening? Who's taking that extra income? Well, there is a story that says that if the caste provides insurance that will keep people in the village that will stop fruitful migration, even fruitful commuting or change of occupation. But then there is one group which doesn't really fit the description of caste and it is defined by religion. And these are the. And the tallies have a much slower population growth. Okay, that's the average population growth is 30%, 30% for the top two groups. It's 27% for the jatabs and it's only 18% for the jellies for the tallies on average. So now if we look at the increase in income that they experience, especially relative to the shareholder population, you see that there is a big upshot. They gain a lot more than their fair share. By 2009 the tallies have almost twice the share of income than they have the share of population. Of course these are small shares of the population, they're about 10%. But still the increase in income is quite considerable. And even they get households in the top 5%. So if you rank all the households from richest to poorer and you get the top five, which is about 10 households by 2009, half of them are in the green line. And as you can see, both the murao and the takur go down dramatically. There was at some point in the 1970s where the Murao had 70% of the households in the top 5%. Why is that? But, well, one should look a lot more, of course, we should look at insurance arrangements. And if they're not group based, individuals can move and they're not taxed. That means that you can exploit more opportunities, you can have more incentives to accumulate income because you don't have to share it with the group. And maybe that in the end results in a better opportunity to gain income. So this is a very interesting story that can be explored. The second part is much shorter. I want to see how to measure poverty. And I think that this is the most striking table I've seen in a very long time. This is a table that compares the ranking of households according to income, assets, score observed, means PRA and consumption. Now, if you look at those correlations, the only thing that doesn't correlate with anything is consumption. Why is that the most shocking table ever? Because if you look at every measure of poverty, we define our development goals on measures of poverty that are based on consumption. Policies are judged according to whether they increase or decrease the number of people above the poverty line, which is defined on consumption. So this is, I think, a word of warning. I mean, it's not a surprise. I think that if you measure poverty by what one actually eats versus what one can afford to eat, you get two very different answers because preferences go in the middle and all sorts of transfers go in the middle. But I think it's important to make this distinction because the policy implications are very different. In the first case, you can just give food to people and that will reduce poverty. The second case, if you want to improve people's potential and people's opportunities, then you have to increase their earning potential, which is a much harder, a much harder thing to do. And that's what I have to say. Thank you so much to the authors for changing our lives for the best with this wonderful project.
- [71:37]
A
Okay, so we have a few minutes for questions. Can I ask you to keep your questions brief, say who you are and we'll take them in batches of three. So I don't know who would like to start in back there? Christopher Bliss, one of the original Palimpur authors.
- [71:56]
F
Hello, I'm Christopher Bliss. I'll keep it as short as I can. It's clear that the major health problem in Palumpur is malnutrition, and it's a very serious problem. So I've been thinking about that, particularly using what I can draw from the lives of Chains books. Putting it very simply, there are three sources of malnutrition. One is just insufficiency of food, lack of energy to sustain growth and good health. The second is imbalance in the diet, missing important components. And the third is things that affect absorption, notably diarrhea and intestinal worms. I want to refer to the second. If you look at a typical Indian village diet, North Indian village diet, they're eating rotis, which is wholemeal flatbread, a very good source of protein, by the way, about 14%. And they're eating also some dal and some vegetables. So the central thing to look at is fat, particularly essential fats that are vectors from vitamins. Now, the most important source is going to be milk, and we have very little data in this book on consumption of milk, which is a very important thing. I speculate that any household that has a draft animal, cows or buffaloes, will be drinking milk from them. Buffalo milk particularly is a very good source of nutrition. Other households may well not be able to afford to buy milk. And so maybe a future study we could look more carefully at who's buying milk and how much they're consuming.
- [73:28]
A
Thank you. We'll come back to the panel. Do we have a next question? So I'm not missing anyone coming down there. Rachel, it's coming to you.
- [73:43]
B
I just wanted to follow up your point that education hasn't had any impact or as much impact as you would expect. You know, one would expect that it would have an effect on take up of technologies, on demography. So I just. And we've also been doing some work in an African context looking at how traditional governance structures mean that villages don't take into account unable to utilize the benefits of increased education because younger people are more educated and it's still dominated by older people who are less educated. So do any of those, you know, talk a little bit more about why education isn't having more impact?
- [74:35]
A
Okay. And then there's a question in front and I'll come back to the panel.
- [74:40]
E
I have two questions, quick ones.
- [74:43]
C
The first thing that I didn't understand.
- [74:45]
E
Was how this bit of information about Muslims are not affected or they are doing better.
- [74:53]
C
If this can be explained a little bit more.
- [74:56]
E
And the Second one is.
- [75:00]
C
With regard.
- [75:01]
E
To the ecosystem and the environment.
- [75:03]
C
Has the book looked at that and.
- [75:05]
B
How what the future holds for these.
- [75:10]
C
Villages, if they are exhausted, sourcing the land now, what's going to happen in the future, especially when the population is still increasing. Thank you.
- [75:21]
A
Okay, so I don't know who wants to take which question. Nick, why don't you slide?
- [75:29]
B
Why don't I say something briefly about the ecosystem and the environment? And then Himanshu, do you want to say something about milk? And perhaps also something on education? And then perhaps you say something about Muslims as well. Chip in as you wish. Michael Lipton first had some. Those are really lovely. I've never had such good comments, so thank you. And you've given us lots of work to do. And I think the picture of a number of books trying to get out within this book is absolutely on the button and we hope others will come and join us and liberate those books from within this book. But Michael referred to it as data mining, as land mining, water mining, and that has gone on. The water table has dropped quite a lot from maybe 15ft or so when Christopher and I were first there, down to something like 30, 35, 40. And that is essentially water mining. It's still not nearly as deep as you'd find in many places elsewhere, including in South India, but it's increasingly an issue because you have to spend more energy on lifting the water further. And the use of fertilizers has been very sort of haphazard hazard and rather unbalanced. And you chuck on the urea because you get a very quick response. And of course that undermines the soil quality. I suspect those issues will get worse as time goes by. Just one remark on the environment. There are major environment issues, of course, in hut air pollution is still a very serious issue issue. And we've had irresponsible factories discharging waste into streams, which have been problems as well. So the ecosystem, environment, there are issues. My remarks at the end of what I had to say is I think those issues will get worse. I actually think that the big expansion of the teles will be interesting to see what Pete and Himanshu have to say about that. They happen to be Muslims, but what you found is you've got one or two very entrepreneurial people, Nana particularly, who was described in the talk, and I wouldn't overdo the Muslim part of that story. He's just a very smart guy and he took the family and the relatives with him. And so there's quite a small group in the village. So my interpretation of that would be more individualistic than systematic. Actually.
- [78:21]
C
Let me quickly answer the questions and then I'll have a small comment on Orianna's discussion. Chris, your question on nutrition is very, very. And we do look at it, I mean, in the 2008-10 round we actually did anthropometry. In fact, we measured it in two periods of time just to check if you're consistent with that. In fact, the milk story is very much related to the whole livestock economy. In a sense it has become and it has affected the poorer section of the population much more in the sense, I mean, if you remember if you were there in the 70s when there are goats in the village, now there are no goats in the village. I mean the commons have disappeared. The commons which were like fairly easily available, those have disappeared. And if you are having livestock, you need to work, buy fodder or grow fodder to feed them. So one of the groups which have basically cut off from this access to cheap meat or livestock or milk in that sense is certainly the group which is the poorest section of the group because it's become much more monetized. But we do have really good data on consumption pattern and where we kept the diaries as to how they're consuming and we looked at it. So that's one part of the story on that. And we will be looking more closely into it. In fact, there is a PhD on that. As to. As you shift away from home produced consumption to more market based consumption, does it affect the groups the same way? And the answer is no. I mean the people at the bottom end of the distribution do get adversely affected and that is why some kind of a transfer for example from public distribution system, it has helped. So in the secondary data also it is very clear that the PDS kind of a system or supports Social Security security nets do help them in getting better nutrition. On education, I think there's lots that is happening and there is a huge demand for education. A result of that is that the public services may not be doing that well. The school, public system, primary school which is there in the village, but it has led to creation of large number of private schools where people are spending huge amount of money, even the poorest to acquire education. And so they do see education as something which is, is playing a big role. And this is true for even girls and even the poorest section of the population. So they actually pay a huge amount of money to get the so called English medium education which is not very different from what you get in the schools. But there is a huge premium for education that is there. We don't yet see it because the nature of diversification as of now in the current juncture is not something which has taken into account the advantages that come from having a good skilled education, education or those things. But we do see that it's going to shape up the way women are interacting in the village, the caste interacting in the village, or demand will go up and at some point of time there'll be pressure on the local public schools also to work on that. So that's something which is there. On the second point, I think the point that you made about the consumption and the transfers in the sense we looked at it. I mean, since if you. There's a 2013 that we paper. We looked at it and just did one, one simple example of it. I mean, if you start quantifying the transfers that come from say public distribution system, which is free in some senses or very, very cheap, or say for example, the midday meals, the noon meal screen, which is. It's a transfer, it's a free. That comes to you. And we did a quantification as to how much did it contribute. So you realize that it actually contributed almost one third of the total poverty reduction. But in terms of squared poverty gap, which is talking the depth of the poverty, it was almost 50% of the total reduction in poverty because it did us. But I think the bigger issue that we had was in terms of not looking at consumption poverty in that sense, but also the transition matrices. And you do find a huge amount of convergence in those issues as far as the movements up and down over a period of time.
- [82:12]
A
Pete, over to you. And it'll be the final word, I suspect maybe if you want to ask another question, I. We probably don't have time, so why don't you answer?
- [82:20]
D
I would just simply, if I may just add the one thing that we have been emphasizing and noted in the Palampur study, when we look at these inequality across the different groups is as Nick also emphasized, while the caste categorization seems to be very useful in some respects in terms of understanding what's been going on in the village, it does remain that we've seen a considerable amount of heterogeneity in terms of living standards outcomes within these different castes. It's far from the case that we're seeing these groups sort of all enjoying sort of an equal income level or consumption level. We see real considerable differences also in the movements upwards and downwards. So it seems to be useful up to a point. But then at another point these issues of entrepreneurship and how individual and ideal idiosyncratic opportunities can be does really start to come and play a role as well. And finally on the consumption issue it's a challenge. I think in our particular study we've been able to devote an enormous amount of attention on collecting what I think is probably very accurate income data. And the consumption data on the other hand were designed to mimic the consumption data data as closely as possible that are collected in India's national sample Survey Organization data. We tried to do that because we wanted to make those comparisons to the Indian aggregates data. At the same time there's huge debates about the quality of those consumption data. Even in the NSS surveys there's issues about the way housing is treated, the way the consumption services from consumer durables are incorporated. And my hunch is that if we were to actually devote more time to constructing the best possible consumption measure in the palampur data, we would find that it starts lining up much better with some of the asset data and some of the observed means findings that we have simply because they would start to reflect more of the ownership of assets and so on than the way that they currently do. So to some extent the issue about consumption and it's sort of standing out differently from the other indicators indicators is partly the construction of the consumption aggregate that we're working with.
- [84:35]
A
Okay, so we've reached the final.
- [84:40]
B
Could we just have a quick from K&PK?
- [84:43]
A
Oh okay, okay but sorry, sorry yeah yeah.
- [84:50]
H
My name is PK Misra actually I must congratulate it's a very excellent study and 25 years ago I had gone through the earlier book 1982 and I was very happy that there was some one of the point which was made that it has brought out certain aspect of farmers approach to risk and uncertainty. That time I was working with Professor Michael Lipton at Ideas for my PhD and I was very impressed by the Palanpur study. But today after hearing this I really compliment the author. 23 Comments I would like to make this last one I think 2015 it was was not as elaborate as the earlier ones so I think now that the earlier study was of 2008 or so and one decade has passed maybe it will be very useful to have a comprehensive study for another decade say 18, 2018 or so and that I am saying that not because it is a unique study study and has brought out many important aspects of development but also because a question which comes to Me that though I have not gone through the book. Can we also, because it is such comprehensive and rich database, how much of the change was due to certain policy initiatives or policy induced? Because simply because of the time. Time passes, some of the changes will take place. Can you identify some period? Because it's a very long period study, how much due to what sort of policy? So that is one comment I would like to make. Another thing which slightly I was not very clear, is that some of the conclusions which are drawn based on only a village level data, and that too the number of families, I think about 200 to 300. It's a small, relatively small village. So when we say that during the first period something happened, say I think one example was the dependence ratio. It increased and then it declined. Similarly, there are other figures. Can we draw such conclusion based on simply one village study or just a. Or when you talk, when you were calculating the variation or Gini coefficients and so on? I think that is one methodological issue which I would like to raise.
- [87:58]
B
We're out of time, but you should know that Mr. P.K. mishra is the principal secretary in the Prime Minister's office. We have the chief economist of DFID here. And I would like to record, Rachel, that the Prime Minister's office has said there should be another study of Palanpur fairly soon. We tell stories about what happened in the village, and then we ask, do those stories resonate with the experience of other places? So you're not actually simply multiplying Palanpur by half a million and saying, this is India, but you're saying experiences, stories, the way in which people's lives change in what we see there. Does it look something like what we see elsewhere? Do we understand those stories? Is there a logic, a perspective behind them that can be extrapolated? So the way in which we build from the village to development economics or to village to India is not simply multiplication or breadth representativeness. It's whether the stories that are told are plausible stories where they're in the data and whether other stories like that might be seen elsewhere. And. And then you can, I think, start to say, well, you've learned something.
- [89:21]
A
Okay, well, I think now I'll draw things to a close. A really fascinating panel, a project that I'm sure you're all incredibly proud of with good reason. And I'd just like you to join with me in thanking the panel for their very interesting presentation.