Well my project is going rather well  -   it looks to me as though the prospect of exposing the World Bank's research as academic fraud is getting closer.    

I'm trying to write my ideas up for public and academic consumption in various forms.   I'll send you one that's suitable for other people to see sometime.   Here's something I'm not going to tell many people yet:  if no-one can prove me wrong, I'm intending to get

I've been very encouraged by the interest shown by Ravi Kanbur, economist at Cornell, in what I had to say.   He was in charge of the Bank's latest big book of development progress and policy (which countries follow in their policies) until he resigned last year, reportedly because the US Treasury Secretary Larry Summers told him to alter the content so it would be more in line with the views of the economists who I think are the least credible.  He said to me something like, "Sen looked at capabilities but maybe should have been looking at the point you're raising".  I've got a book of a seminar in Cambridge where Ravi Kanbur, Sen and Bernard Williams discuss Sen's theories.

This is all very odd, since I can't believe that I am saying something so fundamental about how social science has to be done if it is to give credible conclusions.   The statistical effect I talk about  -  at root, if the poorest die, then average wealth is higher even if no individual gets richer  -  is clearly possible in theory, and so it's only unimportant in practice if the effect is small.   And to me, this is wildly implausible.   If Cuba has saved the lives of the poor over 40 years, and child mortality is drastically different for the income-poor there than for the income-poor in another country, this must have a significant effect on the demographics.  You just can't expect  -  for demographic reasons and also for reasons of practical economics (saving lives costs money)  -   a country to have the same per capita income if the poor survive.   In Uganda, in the poorest 10% by asserts, nearly half the children born in the five years up to 1999 were dead by 1999.   Experts say the children get replaced, but rates of early deaths among adults vary too.

I now think I don't necessarily have to prove anything with numbers   -   I can raise a serious question about the validity of any social science-based policy conclusions which ignore mortality risk.    A bit embarrassingly (again, I can hardly believe I am saying this) this means I have to tell those who have tried to grapple with similar issues they're wrong, as well as the people who don't try at all.  What we are talking about is researchers ignoring many millions of deaths, or to put it another way, adding up figures in a way that not only gives no credit to countries that save the lives of the poor, but penalises them.   This is highly relevant to practical development policy, since countries are rewarded for better-looking statistics.   

Rich countries' development policy is being heavily influenced, staggeringly, by one piece of World Bank research on the income of the poor which is full of schoolboy mistakes.   Meghnad Desai told me he thought it was crap, and the policy director of Oxfam told me Sen thought the main author was a third-rate economist.   It's still widely quoted as the basis for policy in the UK and elsewhere, which is in practice emphasising the International Development Goal of reducing the proportion of poor people (again fairly staggering, if you think about this being used as a measure of success).   One big problem with the research, I think, is the one I'm talking about here.  It looks at income gains which are in practice so small that I think they are easily knocked out by any hint of increased mortality risk.

What I now think is that economists simply haven't realised how different poor countries are from rich countries, in that every policy decision affects life and death, and this affects demographics, and this affects outcome indicators for the living.   It's not the level of mortality that's important, it's the variability.   

Anyway, if you change the demographic composition of a population you are now looking at different people, so rises in the average of any welfare index of those living at different times tell you nothing about the progress of individuals.   

In all of this, there are some problems which are statistical, some which are methodological, and some which are conceptual  -   economists talk about "the poor" in various different contexts, and give a misleading impression by confusing "the poor" as a conceptual class (all those who are poor at any one time, which of course counts different people at different times, partly dependent on whether the poorest die earlier, which they usually do) with "the poor" as a group of real people alive today.   What happens to the average welfare of the conceptual class is not the same as the sum of welfare over time of real people.  But they use a rise in the welfare of the conceptual class to justify policies as good for the real poor of today.  This causes two problems.   First, it ignores any past effects of policies on survival, and so gives no idea of survival chances for the future.   This is in fairly sharp contrast to what we expect from research on options for ourselves where survival chances are affected by choices  -  if a doctor used statistics that ignored mortality risk, they would get the sack.    Second, the average rises if the worst-off die.  The estent to which this happens in practice doesn't seem to have been looked at by anyone.   I now think that it's not up to someone like me to prove it has a significant effect  -  it is a potential problem in social science which has to qualify any conclusions made.   If someone wants to show that something was good for a group of real poor people, they have to show they had good grounds for believing that their measurements reflected the progress of those people during the period.

Actually this is a big can of worms, because it's not just mortality that's relevant to the difference between the conceptual group and the real group.   It's demographics.  The problems extend to birth rates in families at different levels of welfare, the changing ratio of adults to children (because sometimes there is adjustment of welfare measures to fit the different needs of children and adults), and who replaces who in the group  -  the fact that someone is replaced at the same level of welfare does not mean that the average for the conceptual group will reflect the average outcome for real people.

If I am right with my basic point, different statistical effects occur with different statistical methods and groups, but the principle is the same.

last week I talked to Ravi Kanbur, who resigned a few months ago as team leader of the World Bank's big development policy book, and has discussed Sen's ideas on philosophy with Sen and Bernard Williams