Five axioms, four puzzles and four suggestions on hunger in the human species
Version of 27 October 2004
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
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
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
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
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?
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
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,
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
b) some other public body or bodies (such as the Treasury Committee)
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:
other prices and
other needs, and
changes in assets and
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
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.
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This version placed on www.mattberkley.com in 2004 as “Draft for correction, revised 27 October 2004”
Contact information revised 29 August 2008. Correct numbering reapplied 10 October 2008. Description changed to “Version of 27 October 2004” on 9 August 2011.