text large_stringlengths 3 2.54k | complexity_ari float64 -16.22 180 | complexity_coleman_liau float64 -39.6 210 | complexity_flesch_kincaid float64 -11.28 117 | complexity_gunning_fog float64 0 122 | complexity_smog float64 3.13 50.2 | complexity_dale_chall float64 0 22.7 |
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Well it's just that, you know, a pound, or a hundred pounds today, is not the same as a hundred pounds in a year's time, or two, two years' time. | 11.782 | 3.706667 | 9.09 | 12 | 3.1291 | 7.229833 |
So that would be opportunity cost? | 4.335 | 6.333333 | 6.416667 | 9.066667 | 8.841846 | 6.565767 |
That's right, yes, that's right, so, in actual fact, this area here, right, is going to be the discounted sum of all future rural incomes. | 12.5476 | 7.144 | 10.68 | 14.8 | 13.023867 | 8.6661 |
Alright, now if we look at the, the rural instead of the urban wage rate, right, up here alright, now let's just say that it takes that amount of time before this individual gets a job in the urban area, alright, now if we discount alright the erm, the rural, the urban wages right, that's all this | 27.066842 | 7.084211 | 22.580351 | 24.203509 | 11.208143 | 11.172998 |
Why have you just discounted it to there? | 2.5875 | 4.425 | 2.28 | 8.2 | 8.841846 | 6.00705 |
Why have you discounted it to W R? | -1.53375 | -0.65 | 5.23 | 13.2 | 11.208143 | 9.95455 |
Well it's, well, er, there's no need why that should be the case, it could be, you know, it could look something like that. | 10.195 | 4.958333 | 6.061667 | 9.6 | 3.1291 | 6.142733 |
But, up in the, there the migrant's decision making process will be, is this area here right, is that area there, greater than that area there. | 12.946154 | 7.823077 | 11.796154 | 16.553846 | 14.554593 | 9.177254 |
Alright, so this is the discounted sum in er, in non-agriculture, in the urban area, and this is the value, the discounted sum in agriculture. | 13.3012 | 8.768 | 13.04 | 18 | 15.903189 | 9.9293 |
Now, clearly on the, on the way I've drawn this diagram it is. | 3.185385 | 2.446154 | 4.003077 | 8.276923 | 8.841846 | 7.925146 |
Right, but that's going to depend on right, not only the wage differential, now if the wage differential is very large it's likely that this discounted sum is going to, you know, be larger than that. | 18.026667 | 8.511111 | 15.166667 | 17.733333 | 13.023867 | 8.053767 |
But it also depends on the time it takes to get the job. | 1.011538 | 1.107692 | 3.095385 | 5.2 | 3.1291 | 6.710531 |
I mean if we got a job somewhere out here then it clearly wouldn't be. | 3.654 | 3.106667 | 4.42 | 6 | 3.1291 | 5.433167 |
So it's this, it's the time taken to get this erm, er, to get the job's going to be important. | 6.2325 | 2.44 | 6.37 | 8 | 8.841846 | 6.997 |
Now if we think of W U as being er, the expected value of the urban wage, and that equals the probability of getting a job, multiplied by the actual urban wages, alright then this probability of getting a job is going to be important as well. | 21.711702 | 7.140426 | 21.569787 | 23.906383 | 18.243606 | 10.671104 |
And that's it then, scruffy diagram, but what more have we got? | 4.98 | 4.933333 | 3.84 | 8.133333 | 8.841846 | 6.863367 |
An urban wage, a rural wage, right, we discount those wages over time, right and that area there, shading the area in the blue sort of box, then this it's erm, it's going to be rational for this er, migrant, this person to become a migrant. | 21.536304 | 6.630435 | 18.51087 | 21.008696 | 13.023867 | 10.723752 |
Even though, I mean this doesn't say anything about unemployment levels, levels of unemployment. | 13.493571 | 14.814286 | 12.627143 | 11.314286 | 13.023867 | 8.842329 |
Unem the level of unemployment is subsumed between, well, within the time it takes to get a job, and also the probability of, of getting a job. | 12.48 | 7.162963 | 12.858519 | 13.762963 | 11.208143 | 8.484589 |
So this sort of, even that's just what the Harrison model erm, tells us, right, so that's, unemployment rates are, are virtually erm, unimportant in the migrant's decision. | 16.961071 | 10.9 | 13.872857 | 18.342857 | 15.903189 | 11.228514 |
Unemployment rates now, it's because they may well be, if they're acting rationally, discount over a very large, long period of time. | 13.548182 | 10.536364 | 11.762727 | 14.254545 | 13.023867 | 9.034064 |
Okay just er, just to ask, is this erm, migration, it, does it cause a problem? | 5.41 | 3.375 | 5.4 | 8.9 | 8.841846 | 9.364475 |
I mean I thought that migration was the er, would be the cure of all ills, in that, you know, we've got wage differentials here in this, in this hypothetical economy. | 14.733226 | 7.380645 | 12.867742 | 17.56129 | 14.554593 | 8.739584 |
Surely if you migrate that increases the supply of labour, it reduces the supply of labour in the rural sector, it increases the supply of labour in er, the urban sector, unless wage, wage rates should equalize? | 19.347027 | 9.891892 | 17.337297 | 19.124324 | 14.554593 | 13.580078 |
What, what, why don't, why doesn't, why don't wage rates equalize? | 8.048182 | 6.818182 | 3.718182 | 8.036364 | 8.841846 | 8.488464 |
Because erm, the urban sector is normally considered to be capital intensive a sector, and the rural area in L D Cs are considered more labour intensive, and so erm, obviously when you get an influx of labour, and changes to the capital to labour ratio | 22.765 | 9.026087 | 22.102174 | 25.356522 | 21.19439 | 13.469839 |
erm, and you would see er, a shift in capital to, to agriculture as the return on capital in urban falls, | 8.134286 | 5.161905 | 9.457143 | 10.304762 | 13.023867 | 9.189529 |
and this would, you would think, because there's a shift back of capital to agriculture you'd get a rise in agricultural wage rates because that changes the capital to labour ratio again and so this would counteract the movement. | 21.136923 | 11.102564 | 17.773846 | 19.702564 | 17.122413 | 10.02449 |
However, there is a problem, capital is not perfectly mobile, like you can apply a new machine into, well maybe you could cos that's . | 11.294 | 8.1 | 11.47 | 11.266667 | 13.023867 | 8.116483 |
Whatever, you can't apply the urban type of capital back onto the land, so it's okay to say this would work if capital was completely and perfectly mobile, but it isn't so, you don't get that and you don't get balanced growth of that. | 21.015682 | 7.386364 | 17.929091 | 20.327273 | 15.903189 | 9.7664 |
Because er, everything shifts in the wrong direction. | 9.6525 | 12.4 | 6.705 | 3.2 | 11.208143 | 7.9808 |
That's right, I mean, in order to eq equalize wages between sector, labour and also capital has to be perfectly mobile. | 11.274286 | 8.752381 | 11.704762 | 12.209524 | 13.023867 | 9.941433 |
Now, if it's not, we know that labour isn't, isn't perfectly mobile, it appeared, migration would seem to suggest it's, it's pretty mobile geographically, but it may not be particularly mobile occupationally. | 20.622188 | 13 | 18.64625 | 19.05 | 15.903189 | 10.651513 |
So that these people go to the urban areas to get the jobs, they're not trained erm, for these jobs right and as a result, these wages rates still, may still be maintained despite the fact there are lots of people who are quite happy to take wages erm, in, take up jobs in the urban sectors, it's the fact that sort of, ... | 35.873919 | 7.705405 | 27.94027 | 31.221622 | 13.023867 | 11.574468 |
Also, where, what are the erm, what're the highest paid jobs in the urban sector? | 7.108 | 6.2 | 5.993333 | 6 | 3.1291 | 10.6965 |
They are essentially in developing countries. | 12.97 | 16.966667 | 12.316667 | 15.733333 | 11.208143 | 11.8291 |
They are essentially government jobs. | 12.156 | 15.4 | 9.96 | 10 | 11.208143 | 10.2005 |
Now, er, without wishing to generalize too much, bribery, corruption, you know, it's not what you know, it's who you know, are very important factors in er, in employment in developing countries. | 18.70875 | 10.825 | 15.69625 | 19.05 | 17.122413 | 10.158075 |
And as a result they are | -3.515 | -2.366667 | 0.516667 | 2.4 | 3.1291 | 6.565767 |
It's much nicer to say patronage, you promise to say patronage. | 6.763636 | 7.872727 | 6.936364 | 11.672727 | 11.208143 | 8.488464 |
Ah, patronage, okay, that's er, a nice euphemism to see the | 5.050909 | 4.709091 | 6.936364 | 11.672727 | 11.208143 | 9.923918 |
That's right, in that erm, you're, the probability of you getting a well paid job is greatly enhanced, if not guaranteed if you know er, the people who are employing you. | 15.340968 | 7.941935 | 12.867742 | 16.270968 | 13.023867 | 8.739584 |
And this sort of thing goes, is, is rife in developing countries. | 5.765 | 6.383333 | 4.823333 | 8.133333 | 8.841846 | 8.1792 |
I mean the old boy network is pretty bad in this country, but er, it's similar sorts of things go on in developing countries, and because there's much less of an industrial sector there, the government sector itself, erm, plays a very important role in, in employment. | 24.317234 | 9.731915 | 20.314468 | 22.204255 | 17.122413 | 11.007062 |
Now, was it you Lyn who had some statistics some saying er, what proportion | 6.428571 | 6.942857 | 5.884286 | 11.314286 | 11.208143 | 9.970186 |
Fine I've got,I've got to use stat statistics to | 4.003333 | 4.755556 | 2.342222 | 8.044444 | 8.841846 | 9.346233 |
Well it works, erm, there were some | 1.582857 | 2.342857 | -1.06 | 2.8 | 3.1291 | 8.495129 |
I can't remember if it was you or somebody else, had er, some data as to how many of the er, jobs in urban areas where the government | 10.400714 | 4.271429 | 11.765714 | 12.628571 | 14.554593 | 8.408871 |
I put erm, studies by Helen and Tate, nineteen eighty three, found public sector employment averaged forty four percent of non-agricultural employment in twenty L D Cs and in extreme cases were Tanzania and Zambia, were as high as seventy eight and eighty one percent respectively. | 25.734348 | 12.556522 | 22.615217 | 23.617391 | 18.243606 | 12.440057 |
And I think he quote those, or they didn't quote them in much, as much detail as I did in the lectures. | 7.125455 | 3.418182 | 6.399091 | 8.8 | 3.1291 | 7.598609 |
I'd got these figures down, but I hadn't really got anything against them, he just quickly went through the percentages so yes. | 12.263636 | 9.481818 | 10.153636 | 10.618182 | 11.208143 | 6.163155 |
Okay, so | -3.945 | -13.2 | 2.89 | 0.8 | 3.1291 | 11.6307 |
And developed countries averaged twenty four percent, so it's twice as much as developed countries. | 12.76 | 13.933333 | 9.14 | 11.333333 | 11.208143 | 10.6965 |
Right, so given sort of erm, public and semi-public institutions, right, represent a large proportion of the non- agricultural erm, employment opportunities, and as a result, alright, the rates of pay in the, in the civil service, essentially, are going to, going to determine erm, the urban, the urban wage rate. | 28.358824 | 11.596078 | 23.735294 | 26.67451 | 19.287187 | 12.358257 |
Now if those, erm, wages in the civil service are set, not through sort of market process, but sort of through institutional er, constraints, you know, it's unlikely there's going to be sort of er, union power erm, in these sorts of jobs, but nevertheless, civil servants tend to do quite well at giving themselves pay i... | 29.545789 | 10.035088 | 23.408421 | 25.607018 | 14.554593 | 12.004051 |
Conservative government. | 33.735 | 33.2 | 26.49 | 20.8 | 11.208143 | 11.6307 |
and er, and as a result, you know, institutes, the wages in government bodies tend to be quite high, and because gov government bodies represent such a large proportion of er, non- agricultural employment they, they represent a much more sort of, a much more potent influence than they would do in a, in a developed coun... | 33.533077 | 10.335385 | 27.550769 | 30.923077 | 22.076136 | 11.233115 |
Erm okay what was the importance of implication of er, Harrison model? | 7.7275 | 9.283333 | 9.74 | 14.8 | 13.023867 | 13.442533 |
There was one policy implication. | 8.388 | 10.76 | 9.96 | 18 | 11.208143 | 10.2005 |
That, what was it, that erm people still move. | 2.956667 | 3.466667 | 1.031111 | 3.6 | 3.1291 | 5.837344 |
Obviously, we that right, people will still move if unemployment's high, but if you try, if the government tries and gets rid of unem urban unemployment, say people have moved because of it, so there's unemployment there to start with because of the reasons we've discussed earlier, so then the government said okay, wel... | 70.637338 | 10.566906 | 55.853094 | 59.053237 | 25.980085 | 14.733994 |
And, erm, you won't solve anything. | 5.12 | 4.4 | 2.483333 | 2.4 | 8.841846 | 9.197433 |
That's right, so, if you want to try and erm, minimize urban unemployment, right, or it's futile to try and minimize urban unemployment by erm, er, establishing employment er, job creation schemes in urban areas, because that will increase the probability of getting a job if you're a migrant. | 26.62 | 11.057143 | 22.785306 | 26.946939 | 20.267339 | 12.511798 |
Right, so there are these government job creation schemes, alright. | 10.888 | 13.14 | 6.01 | 8 | 11.208143 | 8.8695 |
Now, because it's typically observed in the Harrison model shows this under certain circumstances to be the case, that, erm, a sort of erm, migration elasticity with respect to income differentials, right, is much greater than the erm, | 22.111579 | 12.268421 | 18.482632 | 21.515789 | 17.122413 | 11.338668 |
The rate of unemployment, the level of unemployment | 8.475 | 11.675 | 9.655 | 13.2 | 11.208143 | 7.9808 |
That's right, yes, yes, that's right, because erm, there's a gre there's a higher elasticity of migration inelasticity in respect to income differentials than there is to unemployment, any job creation schemes will lead to more migration, rather than, rather than less, so how, how best to get round the problem? | 28.266471 | 11.709804 | 22.578431 | 25.890196 | 18.243606 | 10.810218 |
If job creation schemes aren't in urban areas, are the best way to get round them, isn't it, if we can show, quite simply, that job creation schemes lead to more migration, which lead to more unemployment. | 18.583243 | 8.481081 | 15.423784 | 20.205405 | 15.903189 | 9.312511 |
The policy's self repeating, what policies might ? | 7.38625 | 13.114286 | 9.054286 | 19.942857 | 13.023867 | 10.750843 |
A policy of cross-training,for all areas. | 9.83 | 11.166667 | 10.35 | 22.4 | 13.023867 | 11.8291 |
Okay, yeah, so, what might those, what form might those policies take, what might they be? | 8.648125 | 7.3625 | 4.6625 | 8.9 | 8.841846 | 7.390725 |
on it . | -12.58 | -19 | -3.01 | 0.8 | 3.1291 | 0.0992 |
Where's the population growth highest? | 13.098 | 15.4 | 7.6 | 10 | 8.841846 | 16.5165 |
It's at its highest in rural areas, this is what's being done. | 4.5875 | 4.45 | 5.806667 | 8.133333 | 8.841846 | 8.1792 |
Erm, population control is always focused out in the rural areas,the most difficult place to do it, because populations are dispersed, er, that's where population growth, right, is the highest. | 19.318 | 13.18 | 16.17 | 18.666667 | 15.903189 | 11.966833 |
Any other? | 0.765 | -7.4 | 8.79 | 0.8 | 3.1291 | 0.0992 |
Making incentives to actually raise the wage rates in the, in the rural areas so, sort of to, to increase production or, and through, through farming. | 14.214231 | 9.607692 | 12.25 | 16.553846 | 14.554593 | 9.784562 |
To improve their situation, | 8.83 | 10.15 | 9.57 | 11.6 | 8.841846 | 7.7824 |
Right, yeah | 3.12 | -4.5 | -3.01 | 0.8 | 3.1291 | 11.6307 |
improve their wages through farming and perhaps | 9.657143 | 13.942857 | 5.682857 | 2.8 | 3.1291 | 6.239414 |
That's right, | 7.83 | -1.6 | -3.01 | 0.8 | 3.1291 | 0.0992 |
put more infrastructure in so that then the farmers can send their children to school rather than work on the land. | 10.377143 | 8.752381 | 7.771429 | 10.304762 | 8.841846 | 6.18191 |
yeah, that's right, what we want to try and do is to improve the erm, the returns to, to agriculture which is the main form of er, sort of income in rural areas. | 13.481818 | 4.745455 | 12.298182 | 15.624242 | 11.208143 | 9.101179 |
I mean if you do things like that while improving infrastructure, erm, setting up credit, government credit facilities, er, so, so, so we can lend, we could lend money to small farms. | 16.9425 | 9.19375 | 13.8525 | 16.55 | 14.554593 | 9.664638 |
Increase in information about unem unemployment itself, that is a, that is a problem, people have this misapprehensions about the probability of getting a job | 16.3156 | 13.408 | 16.344 | 16.4 | 14.554593 | 9.2977 |
You could also erm, start to recognize the benefit of the rural sector, and one reason why they were discriminating, L D Cs tended to want to ignore that and sort of shun it, because it's not sort of a glamorous image they were trying to hope for in the urban sector, and, so, if they did help them, say give them units,... | 83.708929 | 8.880952 | 66.787143 | 71.485714 | 27.36623 | 16.574717 |
It's not going to disappear, cos it's quite a large part of urban areas. | 5.419286 | 4.871429 | 6.727143 | 11.314286 | 11.208143 | 8.842329 |
They could do that. | -0.59 | -1.45 | -2.23 | 1.6 | 3.1291 | 0.1984 |
Yes, we want to try and improve resource allocation in the economy and one way of doing that is not necessarily subsidizing agricultural production, but remove the taxes on agricultural growth. | 18.835484 | 13.180645 | 18.958065 | 21.432258 | 18.243606 | 10.777003 |
Alright, and effectively what's, what's happening is that the government sectors in erm, in developing countries are very highly subsidized. | 17.0655 | 16.07 | 14.04 | 16 | 15.903189 | 11.734 |
Right, they're overmanned, alright, they have very high wages, alright, er, that is one of the major courses of er, causes of resource mis-allocation, it's this very large, very inefficient government sector. | 20.622188 | 13 | 16.43375 | 15.3 | 13.023867 | 11.14495 |
And er, one way to, to get people to stay on the land is to introduce some sort of, what we might call market disciplines, if that wasn't such a dirty word, er, into the government, the government sector where there are clear inefficiencies. | 21.765 | 8.440909 | 18.197273 | 20.327273 | 15.903189 | 7.972082 |
Okay, right, erm it's nearly time to go, but before we do, can I just give you some bits and pieces, you, you may well have copies of last year's exam paper, but if you haven't, this is for development and integration of trade er, have a look at those sorts of essays you're being asked to do. | 26.734828 | 5.889655 | 22.085172 | 24.57931 | 11.208143 | 10.052438 |
But also, look as those er, those short answers, now it's important that you answer the short answer questions well alright, because it's, it's a lot easier to get good marks on a short answer question, providing you do it well, than it is on a long answer question. | 24.024694 | 8.097959 | 19.413878 | 21.232653 | 13.023867 | 8.322614 |
Alright, erm, but most people don't, don't ans don't answer short answer questions very well at all, and that's why they get low, low marks for them. | 13.526667 | 7.377778 | 9.362222 | 10.8 | 3.1291 | 7.899774 |
Always re bear in mind, that whenever you do a short answer question, right, you've only got fifteen minutes to do it in. | 10.343478 | 6.617391 | 9.284348 | 9.2 | 8.841846 | 6.150343 |
Right, there, there isn't a great deal that you can get in, in fifteen minutes. | 6.48 | 5.426667 | 4.42 | 6 | 3.1291 | 5.433167 |
But what, what you must have, right, is a definition of erm, the er, sort of thing that you're asked to write about. | 9.319565 | 4.852174 | 7.232174 | 10.93913 | 8.841846 | 7.523387 |
I mean, factor price equalization, intra-industry measuring intra-industry trade, optimal intervention, reciprocal dumping, they're all jargon, bits of jargon effect effectively, so you must, you must have a definition. | 24.091034 | 18.97931 | 20.133793 | 24.013793 | 20.267339 | 13.242141 |
Right now, although the determinals in industrial specialization within countries, alright, now although you can't really define that, you might be able to say something about industrial specialization. | 22.0075 | 18.15 | 18.508571 | 18.342857 | 15.903189 | 11.228514 |
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