Subj:    Logic and inference in economics

Date:   9 January 2003



File:     D:\Current articles\Logic and inference in economics.doc (72704 bytes) DL

Time (32000 bps): < 1 minute



Dear Professor Deaton


Logic and inference in economics:  the implications of PPP flaws, and

demography, for analysis of economic gains


I am writing to you because of all the development economists who write about

theoretical issues, I have found the most comprehensive treatment in your



For the past two-and-a-half years I have been researching the inferential

procedures behind the most influential recent pieces of development research. 

What I am doing is to look at the implications of all the major flaws, in order

to present an accurate picture of the limits to current knowledge in those

areas.    I am aware that insiders know of many flaws in development economics,

while most outsiders do not.  


This is a spare-time activity which has turned into a book-length document:   my

main document is now 44,000 words and rising.    My own training includes

philosophy and experimental psychology. 


On PPP, I've pointed out to Thomas Pogge and Howard Nye that the flaws

invalidate not only the poverty counts but also the results of cross-country

regression analyses on poverty.     I am quite keen to publish this fairly soon,

while there is attention on PPP.    The document I attach presents this argument

in relation to analyses of per capita income and poverty, along with the

argument that the failure to exclude demographic factors also invalidates the



I've spoken to many people about some of the flaws I describe, including Frances

Stewart, Ravi Kanbur, John Broome, Dan Hausman, Gary King, Uskali Maki, and

officials in government, UN organisations and the World Bank.    People often

mention some of the relevant flaws when arguing about conclusions, but not all

of them.  


My work is intended for public consumption;   and also to stimulate discussion

as to whether the theory of welfare economics needs revision.   In my opinion

the theoretical problems which you have yourself raised about per capita income,

death rates, and PPP are issues for economic theory, not just for the analysis

of poverty.    If economic theory cannot cope with a significant proportion of

the world's population, then it is inadequate.    In any case, many of the

issues are not primarily about poverty, but about inferences  -  after all,

demographic change influences per capita statistics in rich countries as well as

poor.    Also, the theory of poverty statistics today applies to the history of

rich countries.  


There's one oddity which keeps coming back to me, and which I haven't yet

thought about very deeply:   the cutoff point between income and

consumption-expenditure measurement.    Where these two different measures are

used, either in combination or in comparison, or both, I think there may be some

strange statistical effects.  


Another is the fact that there is a lower cutoff point to consumption.   How can

we design meaningful measures of inequality  -  or even of aggregate welfare

levels  -  bearing this in mind?   Perhaps by taking as zero the lower level of

possible consumption (something like what someone could just survive on for a

whole year), not zero consumption.  


But then all these things are subject to both measurement error and the

inferential problems of dealing with aggregates.    The more I know about

problems with population averages, the more I think that we can easily judge

someone's seriousness about helping/enabling poor people by their keenness to

raise and measure survival rates.  


I'm also doing a review of the Millennium Goals, their targets and indicators,

from the point of view of their coherence and possible logical relationships

between them:   e.g. if child mortality statistics are bad in a country, would

we expect the proportion of poor people to fall faster?


In my larger document I have various speculative ideas, such as that extended

lives of the poor  have caused lower GNI increases in Cuba/Kerala/Sri Lanka, and

the perhaps more easily inferred one that "missing women" in Asia have made GNI

go up faster.   


There are very few people who successfully separate sense from nonsense in

development economics.     When I've mentioned to economists (prominent

professors) the problem of death rates making the figures look better, they have

generally gone blank.   There are, in fact, ways to increase the chances that

social scientists make true statements about the progress of real people, even

where death rates are high.  


So here is my short version, which I would be very grateful for any comments on.

   It is harsh, but I can't see how I can tell the truth without stating it

clearly.    I hope that  I have not made gross errors.    Various potential

titles include "Sense and nonsense in economics";   "Science and speculation in

economics" and "Logico-mathematical structure of arguments from economic

statistics to income gains and losses".    In this version, I would ask you to

skip over if necessary the rather grandiose (but I think necessarily true)

points about Theil and game theory.    The points about fraud have to be made by

someone, and I wondered whether to leave them out in this initial approach to

you.    There is a distinction between work which is competent and open to

interpretation, and statements which are untrue from any reasonable standpoint.

   How I can phrase this is something I need to think about.    Thomas Pogge,

and Ray Thomas (secretary of the Official Statistics section of the Royal

Statistical Society) have read versions of my longer document.  


Best wishes,


Matt Berkley