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
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
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
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
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
- 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
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+44 (0)7868 397699
Email: matt at mattberkley dot com
This version placed on mattberkley.com in 2004 as “Draft for correction, revised 27 October 2004”
Contact information revised 29 August 2008. Correct numbering reapplied 10 October 2008.