Five axioms, four puzzles and four
suggestions on hunger in the human species
Matt Berkley
Draft for correction, revised 27 October
2004
Summary
Contents
A. Introduction
B. Five axioms
C. Two overarching problems
in development economics
D. Ten confusions in
development economics
E. The real problem is structural bias
F. What makes the author
think that these are serious problems?
G. Four puzzles in
international statistics
H. Responsibility and
accountability of elected officials
I. Four suggested solutions to world hunger
J. Economists and prosperity
K. A personal note
A. Introduction
The
language of this document is more direct than that of academic papers. It is an attempt to make sense of international
statistics.
The
observations below stem largely from the author's reactions to economic
research documents. The texts of the
documents seemed not to reflect the content of statements to the press.
For
instance, a policy document from the World Bank resulted in the following
reactions:
"The authors cannot know the average outcome for the poorest
people, because they do not know survival rates";
"The authors show no signs of having assessed the purchasing
power of poor people's money".
In brief,
two problems with the theory behind international studies of "poverty" are: One, it left out the benefit of
living. Two, it failed to estimate the
cost of living.
Economists
traditionally treat statistics about the economy as referring to changes for
real people. But if people live longer,
the economists say they have done worse.
Economists have here confused cross-sectional statistics (about the
economy) with longitudinal statistics (about people over time).
In
philosophical terms, they have confused "average utilitarianism" with
"the greatest good for the greatest number".
What is
measured by economists in international studies of countries where most humans
live cannot rationally be described as poverty, if poverty is unmet need. That is so because none of the following are
estimated: food needs, other needs, food prices, other prices, or survival
rates.
We might
say that in official documents "poverty" is vague, and
"reduction" is morbidly ambiguous.
Economic
theory in the international studies confused inflation with the cost of living
(the cost of living depends on what you need);
and expenditure statistics with consumption (in reality to know about
consumption you would need to look at not only the money but also at food
prices).
The
existence of such confusions may help explain several puzzles in international
statistics:
1) the
life-money puzzle: why Cubans, Sri Lankans and Keralans have
lived a long time despite economists saying they were very poor;
2) the
FAO-Bank puzzle: how the World Bank ended up
reporting good progress for the poorest while the FAO reported bad progress for
the hungry;
3) the
overall Millennium Goal puzzle: why Millennium Goal Indicator 1 is
significantly ahead of most of the others.
If
malnourished people get richer, we might expect them to eat better. If they eat better, we might expect their
health to improve. So why are health
indicators not moving with economic indicators?;
4) the
health puzzle: why are global health goals not being met?
B. Suggested axioms for social scientists
Some
fundamental principles such as the following may seem to a reader to be both
self-evident and necessary. See
sections F and G especially for why the author thinks it is a serious matter
that social scientists violated them.
Axiom 1 (Survival axiom)
It is not possible to aggregate outcomes
for people during any period without knowing how many survived.
Notes on
axiom 1: To claim to have aggregated outcomes
in such a case is a cross-sectional fallacy.
It is to confuse cross-sectional with longitudinal statistics.
One
classic error of reasoning is to claim to infer the "average outcome"
without knowing how many people survived the period. This error appears in all economists' studies of
"distribution" where the authors claimed to know average benefits of
policies to people in poorest fifths.
Another
error is to use the proportion in poverty as an outcome measure for poor people
as if it were an aggregate outcome measure.
It is not; it is a selective statistic.
Axiom 1 is
necessary to state because the errors have been widespread among economists and
statisticians. Classic forms of this
error appear in World Bank documents such as "Growth is Good for the
Poor" (which claims to know the "average benefit" of policies
without considering survival rates) and "How did the World's Poorest Fare
in the 1990s?" (which is not possible to assess without survival rates).
Even where survival rates are known, the notion of an "average
outcome" makes little sense where survival rates vary. The problem of the "value" of
life is a philosophical problem with no solution. It is a moral matter
- a matter of opinion.
The
solution is for social scientists to provide accurate descriptions of their
data trends, and not to infer longitudinal trends without grounds for doing
so.
Where
survival rates vary, there is no aggregate longitudinal trend. There are outcomes for survivors, and
outcomes for the rest.
Axiom 2 (Price axiom)
In order to estimate consumption amounts
from financial data, relevant price information is necessary.
Note on
axiom 2: Quantities of goods cannot be
estimated from financial statistics without looking at the prices faced.
This axiom
needed to be stated because economists claimed from studies of
"distribution" how much worse or better poor people did better or
worse under different policies. The
distribution of income (for families who do have incomes) is only part of the
equation. The distribution of costs is
another essential part.
Axiom 2 is
necessary to state following repeated claims from macroeconomists in
governments, the World Bank and universities to have data on extreme poverty in
the species and/or under different policies, without looking at the price of
food.
Axiom 3 (Requirements axiom)
In order to estimate economic gains and
losses to a person, it would be necessary to know their level of need at the
start and end of the period.
Notes on axiom
3:
i) An inflation rate does not tell a
researcher the cost of living. The cost
of living is dependent on both prices and quantities needed.
ii) It is not possible to infer consumption
adequacy without specifying consumption needs.
iii) It is
not possible for an economist to infer a poverty trend (trend in unmet need)
without estimating the proportion of children's meals required.
iv) In
some countries, people may need to spend more on rent while in others they may
tend to live on their own land.
v) Many needs are matters of opinion, not
science.
Axiom 3 is
necessary to state as a result of the widespread practice among economists of
using per capita figures (such as the World Bank's claims concerning global
poverty) despite the fact that the proportion of children varies across
countries and times; and failure to
estimate needs.
On
September 18, 2001 David Dollar, who became Director of Developmental Policy at
the World Bank, gave a speech at the Cato Institute in Washington DC. In that speech he claimed to have measured
how people's nutritional levels changed under different policies. This claim was entirely untrue. First, he did not know about longitudinal
trends: he did not know about survival
rates. Second, he did not know about
food prices under different policies.
Third, he did not know about quantities needed, of food or anything
else. He did not know how many people
were children, or about needs for expenditure on rent or fuel, and so he had
not measured consumption or consumption adequacy. Nor did he know the quality of the food: he mentioned having measured the amount of
protein people had eaten. Perhaps Dr
Dollar was in shock after his country was attacked. But substantially the same mistakes appear elsewhere in his
writings on policies and poverty.
Axiom 4 (Wealth axiom)
Economic wealth includes assets and
freedom from debt.
Note on
axiom 4: For people with the least economic
resources, land ownership may make the difference between life and death in a
crisis.
Debt
levels may determine a person's basic needs for money. Interest can be expensive.
Wealth may
also include environmental assets.
Axiom 4 is
necessary to state following repeated claims from World Bank staff and others
to have measured "average benefits" to people under different
policies, and "gains" and "losses" to poor people, for
example from 1981 to 2001.
Landlessness
is a known problem. Land reform
sometimes takes place. People borrow
in crises.
Axiom 5 (Axiom on the boundaries of social
science)
How "well" or "badly"
people fared is not a scientific matter.
C. Two overarching problems in development
economics
Overarching
problem 1 (Macroeconomics is a cross-sectional science):
Statistics
about the economy are not statistics about people
The first
problem with economists' claims about global poverty is that it is not possible
to aggregate outcomes for people without knowing how many survived the
period.
Cross-sectional
statistics are about people alive at different times.
Longitudinal
statistics are about people as they go through their lives.
"Poverty
reduction" is ambiguous, since if the number of poor people falls, this
does not mean that the poor people got richer.
In that
respect, economists worldwide have confused not only cross-sectional with
longitudinal statistics, but also "classical utilitarianism" (the
idea of maximising good for the greatest number) with "average
utilitarianism" (the idea of maximising the average at a later date".
The
economists did not realise that in a country where people live longer, the
resources are shared among fewer people during any period. Common sense says that people do better,
other things being equal, if they survive longer. But also in economic terms, people have more use of resources if
they live longer. They are more
prosperous.
There
could be no objective solution to the longevity problem, since the relative
worth of life versus money is a matter of opinion.
So the
question "how serious has the economists' error been in real-life
studies?" cannot be answered in a scientific way, even where survival data
are available.
The size
of the economists' longevity error is a matter of opinion.
Overarching
problem 2: Income is not profit, and
nor is expenditure.
Some
influential economists have claimed to measure poverty without estimating the
cost of living.
The second
problem is that poverty is a state of need, but the theory behind the
economists' claims failed to define needs.
Whether or
not poverty can be quantified is a reasonable question to ask. It is perhaps equivalent to the question
whether prosperity can be quantified.
What is
perhaps unreasonable is for someone to claim how much better or worse the
poorest people did under a policy without any reference to the following:
a)
survival rates
b) food
prices
c) other
prices
d) food
needs or
e) other
needs
f) changes
in assets
or
g) changes
in debts.
It is
important to understand what economists refer to when they write about
"income". It is a shorthand
word for something more complex. In
respect of countries where most humans live, the statistics often refer to a)
consumption expenditure and/or b) the monetary value of food eaten.
From these
statistics, economists have claimed to find "average benefits" of x%
from a policy, or that y number "rose out of poverty".
But these
statistics about money cannot tell a researcher about food. Economists have not yet compiled food
prices for the target group in each country.
Nor have they compiled prices for anything else which the target group
need.
Let us be
clear on this. The fact that someone
spends 1% more does not mean that they bought 1% more.
What about
people who grow their own food? If the
economist sees the money value of their food go up 1%, does that mean they ate
1% more? No.
Do the
economists have some reason to ignore this inflation problem? Apparently not. The present author found very little reference in the academic
literature to this fundamental problem:
economists have assumed policies always affect food prices the same as
other prices. When approached on this
subject, professors of economics could only agree that it was a problem.
The
economists appear simply to have confused inflation in the economy with
inflation for the target group.
Economists
have not yet estimated inflation for the poorest people under different
policies.
Therefore,
it would seem economists cannot know which policies resulted in which increases
or decreases in consumption for hungry or malnourished people.
That is
the inflation problem, one part of the general cost-of-living problem.
The
next part of the cost-of-living problem is this. The statistics are per capita statistics - per person.
Why is
that a problem? Because the proportion
of children varies between countries, and globally the proportion of children
is going down. Adults need more food
than children.
Suppose
the FAO are right that the ratio of children to adults is falling in their
target group, due to falling birth rates.
The FAO make this assumption for their global hunger reports (which are
not very good for other reasons, including the longevity error).
Other
things being equal, a World Bank dollar per day is not enough in 2004 to feed
people at the same level as in 1990.
The
present author was unable to find any reference to this problem in economists'
discussions of the trend in world poverty up until the end of 2003. Again, when professors of economics were
approached they merely agreed that it was a problem.
A third
problem with treating inflation as showing the cost of living is this: How much you need does not only depend on
your size. It also depends on the
weather, on your need for rented accommodation, transport, and other
factors.
The ten
confusions I list below may appear to amount to a bold claim. Certainly, World Bank statements to the
media, and DFID statements to Parliament during the last few years have been based
on these confusions. The people
making the statements include Chief Economists, the President of the World Bank
and British Governors of the World Bank.
They have
made claims concerning the economic effects of policies on poor people without
reference to survival rates, food prices, food needs, other needs, assets or
debts. That is perhaps not the way
people would assess their own progress, and it is not clear why people might
think it a suitable way of assessing the progress of anyone else.
They have
made statements concerning the overall progress of poor people in the world,
without reference to survival rates, food prices, food needs, other needs or
assets or debts.
There are
certainly economists who understand that assets are important to people. Some economists have recognised their
fundamental mistake about longevity.
D. Ten confusions in development economics
In
relation to international macroeconomic studies of the distribution of
income/expenditure/monetary value of own produce, it appears to be standard in
development economics to confuse:
1. Inflation with
the cost of living
2. The
average rose 1% with on average people had rises of
1%
3.
Consumption expenditure with consumption
4.
National inflation rate with
inflation rate for poor
people
5. Poverty reduction with poverty
alleviation
6.
Income rises with
real income rises
7.
Income rose 1% with expenditure rose 1%
8. The proportion of low spenders with economic
gains to poor people
9. Expenditure rises with economic
gains
10. World Bank expenditure data with poverty
statistics
We might
add that there are more dimensions to human welfare than financial. But the point is that the macroeconomists
have not even got the financial part right.
Notes: Cost of living = prices x quantities
required. Not just prices.
Average
income, perhaps especially in poorest fifth, is influenced in wrong direction
by survival.
National
inflation rates are mathematically dominated by unnecessary goods.
Economic
gains include changes in assets and debts.
E. The real problem* is structural bias
(* in the
financial part of macroeconomists' analysis)
The
problem with these confusions is not simply that they introduce elements of
unreliability into economists' statements.
The
problem is that they introduce structural biases into the conclusions.
(Note:
These are not errors of data analysis, or problems of data availability. They are problems of the inaccurate
description of research results.)
It is
important to understand that economists do not just look at one country at a
time. The relevant question is whether
the policy advice is based on plausible assumptions in comparisons between
countries.
Logically,
using these methods, an economist would say
i) that a country which keeps luxury prices
low has helped the poor to eat more;
ii) that a country which keeps food prices from
rising fast has not helped the poor as much as it really has; and
iii) that
a country which helps the poorest survive looks as if it has "failed to
reduce poverty".
Someone
might say "maybe none of these mistakes matters, because the statistics
generally move in the "right" directions".
But we
have to realise that what we are looking at are general theoretical
errors: misdescriptions of
numbers. Where the "income share
of the poorest fifth" rose 1%, the economist does not know whether this is
due to falls in the prices of luxury goods, or to rises in consumption among the
people in the "poorest fifth", or excess deaths of people in the
poorest fifth; food prices may have
risen 50% or fallen 50%. The
macroeconomist cannot tell what has happened to those people's consumption.
What is
certain is that the economists do not know how much more, or more adequately,
the poorest people ate under each policy.
What is also certain is that there are going to be cases where these
methods give the wrong answer, and economists cannot know what the
circumstances are.
We also
have to realise that the general theoretical errors underlie economists' claims
that particular policies help poor people by certain amounts. To assume that all policies affect food
prices in the same way seems strange.
These are
structural biases, in that if countries save the lives of the poorest they get
penalised; if they subsidise food they get penalised.
Even
supposing economists knew that none of these things had been problems in the
past, that would not mean it was reasonable to ignore the problems in the
future. But in any case, it is easy to
think of past situations where poor people have died in large numbers, and food
subsidies are not unheard of.
So we know
that there is a tendency in these methods of describing data towards
discounting the effects of food subsidies and survival of the poorest
people; we know that there is a
tendency towards discounting the effects of landlessness and debt. We know that there is a tendency towards
discounting the effects of changes in prices of basic services.
F. What makes the author think these are
serious problems?
Two
things.
First,
economists have not been very aware of the problems.
I was
astounded to find any economist, let alone the World Bank, using statistics which
would look better if the poorest died as the basis for policies to help the
poorest. But it emerged that this was
how macroeconomists usually went about their business. When I raised this with well-known
professors, they either did not reply or made it evident that they had not
thought about the problem as a general theoretical problem.
I was
astounded to find any economist would assume inflation rates for the poor and
rich were the same under all policies.
This also is standard in macroeconomics.
Broadly,
the same appeared to be true of the children's meal requirements error. I was unable to find any economist who had
made the point about the World Bank "halving poverty" statistics
being wrong through failing to estimate food needs.
The same
appeared to be true of the confusion between the inflation rate and the cost of
living. In the academic literature on
poverty and policies, this seemed not to feature.
Where
people have ignored a problem, they cannot in general know whether it is small
or big.
Note: The longevity error is not quantifiable in
any case, since the value of life is not objectively measurable. How important survival is to people is a
moral and therefore a political matter, not a scientific one.
The
second reason why
I think these are serious problems for economists' policy advice is that the
existence of the confusions provides neat, if partial, solutions to:
G. Four puzzles in international
statistics
Puzzle 1 (the longevity-GDP puzzle)
Why do Cubans, Sri Lankans and Keralans
live a long time despite economists saying they are very poor?
1. A
partial solution to this puzzle is in the question. In countries where people live a long time, the resources are shared
among fewer people during any period.
Therefore,
they are better off economically, other things being equal, than in other
countries.
In
countries where poorer people survive longer, the average falls because of
this.
In
countries where retired people survive longer, the average falls because of
this.
The
statistical effect on the economic figures may be small. But it is undeniable.
2.
Remember that economists' inflation rates are biased in favour of the
minority. Plausibly, in countries where
people live a long time, healthy food is cheap and needs are few.
It is
important to understand how economic statistics ("gross domestic
product", "average income") are derived. The raw figures are deflated by a price
index (inflation rate). The important
thing to understand is that national inflation rates are disproportionately
affected by prices of luxury goods. It
is the total amount spent on a type of item which determines how influential it
is in the overall inflation rate.
Let us say
that in a small country £1 million is spent on cake, and £1 million on
bread. Even if only a few people eat
cake, cake prices influence the overall inflation rate (and so the
"income" statistics) as much as bread. The inflation rate for bread is not reflected properly in the
overall rate.
If cake
prices fall, the macroeconomist says "the poor have got richer", and
the World Bank says "the policy was good for the poorest!", and the
British Government Target Strategy Paper (2000), or background document for the
White Paper (2000), or the Cabinet Office report "Adding it Up", says
"the policy reduced poverty".
In reality
the economists have not distinguished between inflation rates for people who
buy different things.
What about
people who do not have an income and/or grow their own food?
In the
case of people who grow their own food, national statistical offices look at
the food which people eat, then value it in money. The economists then look at the money value and adjust it by the
national (wrong) inflation rate. The
World Bank scientific method is to then say that people did x% better or
worse.
This is
especially odd because they could find out from the surveys how much people
consumed (if the surveys were reliable and comparable, which is doubtful). The surveys measured the food amounts and
then gave the food a money value. The
economists looked at the money value assigned to the food. The problem is that that money value was
adjusted by the luxury-dominated inflation rate. The economists then implied they know how much food people ate,
which is not only the long way round, it is the wrong thing to say about the
money.
Macroeconomists
have not adequately distinguished between inflation for necessary and
unnecessary goods.
A flippant
person might say this:
"In a
country where prices rise for luxury goods for the minority, the economist
worries about inflation more than the people do on average; and that in a
country where prices for basic goods rise for the majority, the economist
worries less about inflation than the people do on average."
Some goods
are more necessary for survival than others.
Governments have different priorities in respect of keeping people
alive. So it is not surprising that
economic statistics do not correlate very well with life length.
GDP will
rise if the government pays people to do useless jobs - such as economists
spending time adding up the wrong numbers.
GDP rises
if people take more addictive drugs - alcohol, nicotine - and have earlier
deaths (the Economist magazine has noted this point in the past, without
noticing the implication concerning statements about how well or badly people
have done: the difference between
"the average gain" and the "change in the average").
GDP will rise
if the government encourages people to take commuting jobs which increase
transport costs.
3.
Remember that not all activities leading to more GDP are useful. The bus fare error: Economists and double counting of income
Suppose
the government creates jobs out of town.
Suppose you take one of these out-of-town jobs and have to take the
bus. Is it not true that in counting
the prosperity of the people, the economist counts the bus fare twice?
Surely,
they count it once as a benefit to you (which it isn't) and once as a profit to
the people running the bus (which it is).
Child care
is another example of this kind of extra expense.
So is
rent, if people move to the city and begin paying it. Rent can be a very large expense.
This
kind of double-accounting by economists may help explain not only why income is
not well correlated with life length, but also why people do not always report
being happier with more GDP.
The bus
fare error is a variation on the confusion between income and profit.
It is
perhaps surprising that people familiar with business would confuse income with
profit. The fact that it is possible
for economists and politicians to make such fundamental errors as claiming to
know the level of profit for poor people in different countries without
thinking about expenses is somewhat puzzling. Theoretically it could be that necessary items (so far as they
could be objectively specified, which is problematic in itself) have not varied
and will not vary between countries or times or policies. But why anyone should assume this is a
mystery.
I think
there is some kind of collective blind spot, or groupthink, which has stopped
people from thinking about these things.
The fact that governments benefit financially from greater per capita
declared taxable income may not be a coincidence.
We could
also note here that not only wasteful purchases of goods, but also financial
services concerned with debt lead to higher GDP. If someone persuades you to buy something you don't need, and
you borrow money to pay for it, the people lending the money make money. This is recorded in GDP. It is part of "growth" -
but not necessarily useful to anyone.
The
time cost error
We might
also note the time cost of commuting.
Many workers, with or without families, may feel that they have enough
money but not enough time.
A second
time cost error is to omit working hours from the measure of
"benefit". Many people might
think they are better off if they get the same money for fewer hours.
What
economists' statistics leave out
GDP per
person or "average income" as adjusted by economists do not take into
account
- survival
rates
- the
trend in prices of necessary goods
- food
needs
- other
needs
- changes
in assets
- changes
in debts.
The
question then arises as to how macroeconomics based on "income" can
reasonably be said to measure economic gains and losses.
How can
capitalist economics ignore capital gains?
Most
people think of wealth in terms of assets.
It is strange that a system labelled "capitalism" uses social
science which ignores capital gains and losses in inferring how well or badly
people have done!
Without
looking at prices of basic goods, and needs, and asset and debt levels, an
economist perhaps cannot reasonably be said to have measured prosperity even in
the most narrow sense.
It is
hardly surprising that life length is sometimes badly correlated with
economists' claims about prosperity, since prosperity is not what economists
measure.
If you own
your own land, you do not need to pay rent; and you have something to sell if
bad times come. If you have debts, you
pay interest. Neither of these cases is
dealt with by the theory behind economists' claims from "income"
(often in reality expenditure) statistics.
There is
no reason why the concept of
"macroeconomics" should exclude changes in assets or debts, but that
is how the word is used. In terms of
"big economics", land ownership and debt levels may be very
important. Whether this is on the scale
of "microeconomics" (looking at families) or
"macroeconomics" (looking at countries) makes no difference.
It may be
that people in countries where they live a long time have fewer debts, and/or
that landlessness has been prevented, so that people are in fact more
economically prosperous than they look to the macroeconomist. It may be that there is less waste by
governments in those countries.
The
alternative - to think that people in countries where they live a long time
have less land, higher food prices, and more things to buy - is
perhaps less plausible.
There are
many factors which influence life length.
The question I am raising is whether the economists' mistakes, in combination,
are relevant.
Other
puzzles explicable at least partially in terms of economists' mistakes are:
Puzzle 2 (the FAO-Bank or Poverty-Hunger
puzzle).
How can the World Bank report success for
the poorest, while the FAO reports failure for the hungry?
This is a
puzzle because we might expect the two groups to be mostly the same
people. It is relevant here to note
that the survey data for both are similar in origin. See below for notes on the FAO method. The point I make here is not that the FAO are right in their
hunger estimates.
Undeniable
if partial solution to the poverty-hunger puzzle:
The FAO
do adjust crudely for food needs of hungry people (see L.Naiken account of FAO
methodology in FIVIMS documentation).
The Bank do not (see Chen and Ravallion documentation).
The FAO
assume that hungry people's needs have gone up, because there are not so many
children per adult: birth rates have
gone down.
The Bank
(and all economists making statements about the progress of the poorest people
in the world) have assumed that the food needs of the poorest have been the
same throughout history.
The FAO
and the economists cannot both be right.
Note a):
The FAO are fundamentally mistaken in any case: they make the assumption that the faster the number of hungry
people falls the better they have eaten.
This is the longevity error.
Note b):
It may be that the poorest people are living longer or shorter lives than
before. If they are living longer
lives and having fewer children, then someone might say the economist's
longevity error and their meal-requirements error cancel out under some
circumstances. We don't know the
numbers. And in any case the
economists' muddle is not helped by the existence of a conceptual difficulty in
weighing children's meals against deaths.
Note c):
Martin Ravallion of the World Bank co-wrote an article in the Royal Economic
Society's Economic Journal in 1995 advising economists to look at children's
food needs before talking about poverty.
He made the point that smaller families are less efficient per
person. Dr Ravallion ignored his own
advice for his statements on global poverty.
His research, which ignored food needs as well as food prices, was the
basis of the World Bank's claims on global poverty ("halved since
1981" without knowing either food prices or food needs!) The fact that this makes the World Bank look
better may be a coincidence. (Title:
"Poverty and Household Size").
It is also
worth noting here that Martin Ravallion wrote a World Bank working paper in
1996 (Issues in Measuring and Modeling Poverty) in which he mentioned the fact
that poverty is less if poor people die.
Despite this, he and Chief Economists persisted in claiming up until 2004
the level of "gains" to poor people without knowing survival
rates. The Millennium Goal methodology
paper for "halving poverty" (indicator 1) was entitled "How did
the World's Poorest Fare in the 1990s?".
My first reaction on seeing this title was "they can't know that if
they don't know how many survived".
That is true, and so is the fact that they can't reasonably say that
without specifying food prices or food needs.
To halve
the proportion of people under a consumption line is not to halve the
proportion of people under a consumption-adequacy line. And so, even in the absence of other
problems, this World Bank method would not measure a halving of world poverty,
but exaggerate success somewhat.
The notion
that the proportion of children among the poorest people will not have varied
between 1981 and 2015 is perhaps implausible given the fact that it is the aim
of UN agencies to reduce population increases, and spread the use of birth
control.
Notes
on FAO method
The FAO do
not estimate hunger, or consumption, directly. They look at national food statistics, then infer how much
poorer people ate from income/expenditure surveys. This method seems to present some problems:
a) the
FAO make the mistake about longevity;
b) the
method does not estimate the quality of food;
c) the
method ignores the fact that the distribution of money does not tell a
researcher about food without data on
food prices. This appears to be the same mistake as that
made by the economists: confusing
consumption expenditure with consumption, and income with consumption. The survey data are adjusted by the national
inflation rate. But the national
inflation rate is dominated by luxury goods.
The national inflation rate (and so the figures in the
national-inflation-adjusted survey results) do not tell a researcher about
purchasing power for food.
d) the
method confuses income with profit: the distribution of
income or consumption expenditure (or the money value of consumption) cannot
tell a researcher how much food people ate, because that also depends on what
else people needed to buy. In a
country where more poor people begin paying rent, they end up with less money
spare to buy food.
Puzzle 3 (WHO-Bank, or Money-Health
puzzle):
How is it that Millennium Goal Indicator
1, as reported, is significantly ahead of most of the other 47 indicators
including health indicators?
This is a
puzzle because:
A. The
World Bank claims the poorest are getting richer.
B. This
seems to imply they are eating better.
C. If they
eat much better, we might expect them to get much healthier.
Undeniable
partial solution to this "World Bank's figure is statistical outlier"
puzzle:
As
above (children's food needs mistake by the Bank).
Other
partial solutions: Are any of the
other confusions by economists over inflation, assets, debts and so on
relevant? Other factors (culture,
education and so on) have effects as well.
But let us think. Is it more
plausible that
a) the
Bank are right in implying people are eating much better, or
or
b) poor
performance on health goals is more consistent with a mistake by the Bank: that the economists have exaggerated
consumption adequacy as time goes by?
Personally
I think that the question of consumption adequacy is far more complex than it
looks. In theory the quality of food
may go up or down. In practice the
quality of food is a subject about which people have different views in all
countries. It could be that in a
country people begin eating more and as a result are more ill. Certainly, what people consume is important
as well as how much. Personally, I
think that the sensible thing to do in inferring consumption adequacy is to
look at survival rates first.
Extra
slightly complex and inessential note:
If people
in the target group are both living longer and having fewer babies, the Bank's longevity error and food-needs
error would tend to be in opposite directions. The question of whether these two errors would have cancelled
each other out would be a matter of opinion (or as an economist might say,
something which philosophers have not yet solved) even if the data were
available.
If that
were true then it would also be the case that the FAO had other things being
equal underestimated the progress of hungry people. But then because of the inflation problem, the extra-items
problem, the data scarcity problem, and the data unreliability problem, neither
the economists nor the FAO can, perhaps, reasonably claim to have good evidence
in any case. And that is even before
we begin to think about the other problems with economists' claims to measure
how good or bad policies were for people.
Puzzle 4 (Health failure puzzle)
Why are global health goals not being met?
This is a
different puzzle from number 3. Puzzle
3 is "what is the reason for discrepancies between the statistics?".
Puzzle 4
is "why is health apparently making bad progress?"
Many
people might say "because rich countries are not giving enough
money".
Could
part of the reason for failure on health goals be that:
a) the
aim of "poverty reduction" has caused an emphasis in policy decisions
away from measures which increase life length or keep down food prices, or keep
down landlessness,
and
b) the
methods recommended by lender countries for improving people's lives are based
on elementary mistakes?
The aim of
"poverty reduction" in the economist's sense, rather than poverty
alleviation, is philosophically and theoretically mistaken, and some might say
morally mistaken as well. Economists
do not know survival rates of the poorest people. And yet they have still claimed to know average benefits to
poor people. How serious this mistake
is, is a matter of opinion even where survival rates are known.
The
longevity error by economists is not simply to forget that statistics go the
wrong way according to survival rates.
It is to fail to note survival rates in outcome measures.
The FAO
have committed the same mistake in using proportions of people alive at any one
time.
It is
undeniable that economic policies have been based on misdescription of past
statistical trends. A long list of
confusions is above. Also above is a
list of axioms for future reporting of economic statistics by academics, civil
servants, international civil servants, politicians and campaigners.
Aiming to
help the poorest by increasing "income" without looking at food
prices, assets or debts or food needs appears to have no philosophical,
empirical or theoretical basis.
It is
worth repeating that the word "income" does not describe accurately
the referent of the statistics which economists have. It is a shorthand term used by economists to represent three things: a) consumption expenditure, b) income and/or
c) the value of food eaten.
It is not
clear from where came the idea that "income" measures prosperity, or
why anyone should believe it.
What is
certain is that:
i) current availale global statistics do not
indicate success on health goals;
ii) progress on health goals is not always well
correlated with economists' reports;
iii) the
most influential economists and politicians making claims about the progress of
poor people, and the success or otherwise of policies, have been at best deeply
confused about what they were reporting;
iv) the
recommendations of the economists had a tendency towards bias against long
life, cheap food, high land ownership and low expenses.
Is it
plausible to think there is a causal connection between a) policies devised on
the basis of the misdescription of statistics, and b) failure on health
goals? See Puzzle 1 above for
descriptions of economists' omissions.
If a
government encourages average economic activity without looking at costs (in
terms of landlessness, mortality, time at work, time commuting, changes in need
to rent accommodation, food prices, water prices, commuting costs, debt levels)
then we might not be surprised if income or expenditure statistics (or the
nominal monetary value of food) to rise while the standard of living (in terms
of food consumption, at least) falls.
Is that
what has happened in some or many countries?
Perhaps. It is true that
governments, and lender governments through the World Bank, do not base
decisions solely on dodgy economic statistics. Nevertheless, these have been prominent in policy advice given
to borrower countries.
It is
possible that through multiple errors, macroeconomists have over a period of
many years convinced themselves that their measures of prosperity were
meaningful and did not need checking against anything else; and that the result was systematic bias
against some policies which a helped consumption adequacy and health
indicators.
Since
macroeconomists have not compiled international data on food prices, food
needs, other prices, other needs, assets, debts or survival under different
policies, it would seem that the burden of proof is on them to justify their
assumptions that those things do not matter.
What is
clearly wrong is for macroeconomists or politicians to claim to know about
poverty trends or which policies brought which benefits, without thinking about
the basics.
H. Responsibility and accountability of
elected officials
1.
Accountability of World Bank Governors for errors in pronouncements and policy
advice
There is a
common view that the World Bank is unaccountable. That view appears to be mistaken.
The policies
of the Bank are in the hands of its Governors.
Governors from democracies are accountable to voters.
2.
Voting power and responsibility for policies and Bank staff statements
The
institutional structure of the World Bank is such that lender countries have
voting power in proportion to financial input. The influence of the United Kingdom (with under 1% of the
species in headcount terms) is much more per head of population than, say,
India.
Responsibility
for mistaken statements by staff of the Bank therefore lies largely with
Governors from lender countries.
Responsibility for policies made on the basis of errors in the
description of statistics also lies largely with Governors from lender
countries.
3.
British Governors
The
British Governor of the World Bank is the Secretary of State for International
Development.
The
Alternate Governor is the Chancellor of the Exchequer.
The
British Governor of the International Monetary Fund is the Chancellor of the
Exchequer.
The Chancellor
has been Chair of the IMF's main decision-making body for several years.
The
Millennium Goals were agreed by the Organisation for Economic Co-operation and
Development, the IMF, the UN and the World Bank.
Note: The Development Assistance Committee of the
OECD is a body for which similar considerations must apply as in the case of
the global financial institutions:
since elected politicians are on the Committee, it would seem that they
are answerable for actions in the name of their voters.
4.
Responsibility for reporting errors
It would
seem that where they have been informed of errors in World Bank statements
about global poverty, and about the effects of different policies on the
world's poorest people to the Bank, the
Governors are responsible for informing staff at the Bank and other governors.
To know of
errors and not to share that knowledge with other Governors or senior Bank
staff with a view to the errors being corrected could be construed as failing
in a public duty.
5. Responsibility
for oversight of British teaching of social science
It would
seem that this responsibility would lie with the Education and Skills Select
Committee of the House of Commons.
6. Responsibility for oversight of British
board members of international bodies
It would
seem that responsibility for oversight and scrutiny of the actions of the
British Governors of the World Bank and International Monetary Fund must lie
with
a) the
International Development Select Committee of the House of Commons
and/or
b) some
other public body or bodies (such as the Treasury Committee)
or
c) no-one.
I. Four suggested solutions to the problem
that a self-described intelligent species cannot, despite the stated intentions
of its most powerful elected officials, feed itself
Partial solution 1
A new emphasis on survival as a measure of
success.
Life is
mentioned in the UN Declaration of Human Rights as the first right.
Whatever
the morality of that, it is odd that international development goals do not
specify survival as an aim for the main target group.
The
statistics with which we measure success are determined by our aims.
Therefore
an emphasis on survival in measures of success is equivalent to aiming to keep
people alive longer. It is not clear
why anyone claiming to wish to help hungry people might oppose such an aim.
The above
is not to say that longevity is the most important thing about human existence
in any or all circumstances.
But even
with the best data on food prices, it is not possible to infer the adequacy of
the food (quantity and quality) without reference to survival rates.
Aggregation
of outcomes is not possible without survival rates. Economists' claimed outcomes have been based on the erroneous
presentation of selective statistics (on survivors each year) and a confusion
between cross-sectional and longitudinal statistics.
Statistics
on survivors each year are not aggregate statistics. Statistics on survivors each year do not tell a researcher about
average outcomes.
The notion
of an "average outcome" is problematic in any case, because you
cannot compare objectively life length with any other variable. This philosophical problem - that the value of staying alive is a
matter of opinion - exists in all cases
where survival rates are not known to be very close.
But then,
the relative value of various aspects of human well-being is not objectively
measurable either.
There are two
parts to the equation for prosperity: the quality of a life, and its length.
Only one
is measurable.
Partial solution 2
A replacement of the term
"poverty" in the vocabulary of governments by more specific terms
with more meaning.
Without
data on:
food
prices,
food
needs,
other
prices and
other
needs, and
changes in
assets and
debts,
economic
statistics are of questionable use in inferring either prosperity (surfeit) or
poverty (need).
The idea
of collecting food prices may seem attractive, but it is not clear how, without
estimates of survival, food needs, other needs, assets and debts, an equivalent
standard of "poverty" could be inferred in different places or at
different times.
The present
author is strongly of the opinion that such an enterprise would be too complex
to be practical or useful.
That
opinion has been arrived at after consideration of the existing failures by
governments and economists even to recognise the implications of having omitted
survival rates, food needs, food prices, other expenditure needs, assets and
debts.
Part of
the author's reasoning is this: If the
economists could not even describe their existing statistics accurately, and
seemingly did not understand the basic elements of extreme poverty, how could
they be trusted with something more complex?
The
solution to hunger in the human species does not, I think, in making something
which politicians can easily claim not to understand into something even more
complex.
We might
also note here again the successes of Cuba, Sri Lanka and Kerala in
health.
Those
governments did not need highly-paid mathematicians to help the poor to live
longer. Incidentally, the idea of
gathering food prices is somewhat too complex in any case. Survey data already look at consumption
levels and then value the food.
To a) look
at the money value of food and then b) gather prices and then c) convert the
money back to food amounts is the long way round. A simpler way would be to estimate consumption from the surveys
in the first place. But there are
problems with estimating consumption adequacy from consumption.
It is not
just the quantity of food which matters.
It is certainly not just the quantity of calories which matters (a
common reference point). It is also
the quality of food.
To
determine the quality of food, some outcome measure is necessary. And this brings us back to life length.
The
quality of food is not always uncontentious:
Western scientists decided that coconut oil, which is plentiful in both
Kerala and Sri Lanka, is bad for people.
That opinion seems to have been wrong.
But it is
very complex to decide the value of food in different places. It is a task for a nutritionist, not an
economist. And I am not sure that there
are any easy answers except in terms of outcome measures (how healthy people
are and how long they live). So in a
sense we might as well use health indicators.
The alternative is to assess people's diets in terms of freshness,
vitamins, calories, proteins, essential fatty acids, balance and so on - yet
another potentially endless task.
It is my
impression of economists that some mathematicians like endless tasks. In my reading about what economists call
"poverty measurement" I see professors calling for more and more
complexity. The complexity involved in
adjusting for children's food needs is great.
Add to that the complexity of working out economies of scale (households
with more people are more efficient) and we end up with vastly complex
equations. How to add up the
nutritional value of each item of food in each country?
What about
the value of water consumption? Here
again, what matters to people is the outcome.
Unhealthy water is worth less. How
to compare the value of food and water across countries - let alone variables
such as rents, services, commuting costs and so on - is a vast question.
Partial solution 3
A rapid move towards the correction of past
statements concerning the progress of people described as extremely poor, and
the reassessment of policies devised on the basis of these statements.
Erroneous
statements include many from the World Bank:
- in 2004
the Chief Economist announced that 400 million people rose out of poverty in
China since 1981. But this statement
was made without the Bank compiling data on the price of rice -
and without adjusting food needs for the one-child policy! [Estimating economic need without estimating
food needs!]
- a past Chief Economist announced that a
policy gives "average benefits" of x% to the poorest people without
data on food prices, or food needs, or asset changes, or debt changes, or
survival rates;
and from
many of the Bank's critics. The
confusions I note above are standard in macroeconomics.
Partial solution 4
A rapid move towards replacing the
ambiguous language of "poverty reduction" with clear and specific and
meaningful statements about statistics, described accurately without value
judgements or unfounded inferences about the level of need.
Axioms for
the use of economic statistics appear at the beginning of this article.
It is
self-evident that economic statistics without prices of staple foods are not
statistics on extreme poverty.
It is
self-evident that economic statistics without survival rates do not tell a
researcher average outcomes.
The
sources of global statements on the progress of people deemed extremely poor
are survey data on
1) income
and/or
2) consumption
expenditure and/or
3) the
money value of people's self-grown food.
These have
been adjusted using the wrong inflation rates.
It is
inaccurate to describe these statistics as showing "income poverty"
or "gains".
Where the
macroeconomist's average rises for the "poor" and the economist does
not know survival rates, they do not know aggregate trends. They do not know whether the poor ate more
or whether the figures for the poor are inflated by low inflation for the
rich.
It is
inaccurate to describe the economic statistics as referring to longitudinal
trends for real people.
It is
inaccurate to describe the World Bank statistics using an international dollar
as "poverty statistics".
There are no global food prices for the target group for any year; there are no survival rate data for the
target group for any year; there are no
estimates of amounts needed in any year, due to changing food needs, changing
needs for rented accommodation, changing needs for expenditure on debts, changing
needs for savings to offset landlessness, or anything else.
It is
inaccurate to refer to the statistical results of studies of the numerical
distribution of "income" as if they represented consumption amounts,
or consumption adequacy (consumption poverty), or "income poverty"
without estimating necessary expenditure.
It is the
tradition among macroeconomists to confuse income with profit.
Inflation
does not measure the cost of living, because a) income is not profit (needs for
expenditure may rise) and b) inflation is disproportionately affected by prices
of unnecessary goods.
Ultimately
the cost of living is not something which can be measured, since that would
necessitate specifying an equivalent life at another time or in another
place. Since the combined benefits and
costs of climate, culture, working conditions, and various physical, emotional,
intellectual, and spiritual wants are not measurable, all comparative
statements in this general area are laden with subjectivity. The benefit of living longer is not
measurable against any other benefit while alive. No single number could measure prosperity even if there were some
objective way of measuring prosperity while a person was alive.
There are
two parts to the equation for prosperity:
the length of life, and its quality.
Only one of these is measurable.
K. A personal note
Perhaps we
all tell ourselves on occasion that the picture the world presents to us
confirms our pre-existing notions.
So it may be
that I have deceived myself into thinking that the errors above by social
scientists are significant. It may be
that the problems are minor, in the sense that they do not matter to the
happiness of any human. However, the
matter of social scientists' leaving out outcomes for people who die is not a
scientific matter: it is a moral
matter, as I hope I explained above.
To me, the
picture I have presented - of puzzles partially solved by reference to
social scientists' errors - makes sense. It also seems to me that the burden of proof is on a scientist
to justify their assumptions.
Contact information
Matt
Berkley
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