To:martin.wolf@ft.com June 2003 G8 and poverty Dear Mr Wolf I thought you might be interested in the following, which I have just sent to your colleague Larry Elliott at the Guardian. There are a number of serious flaws in official statements concerning poverty measurement and poverty. You are welcome to contact me if you would like further detail. Yours sincerely Matt Berkley … -----Original Message----- …Sent: 01 June 2003 08:17 To: larry.elliott@guardian.co.uk Subject: Fixing the broken model of development Dear Mr Elliott Africa, Millennium Goals and “poverty reduction” I think you may be interested in my work. In “Do not let the rich cry poor” (May 19) you refer to the broken model of development. It is broken in ways which are not widely known. All studies of poverty suffer from the following flaw: if more poor people die early, the figures look “better”. In the age of AIDS, this is not just a theoretical possibility. The idea of “poverty reduction” as reducing the proportion of poor people is conceptually flawed, if the aim is to help poor people. I have undertaken what seems to be the most thorough review of assumptions in poverty research by economists, and theoretical assumptions in welfare economics. I have written extensively about the points below and related issues: the concept of utility, flaws in the World Bank’s claims on the progress of poor people, inflation and the poor. The research is based on hundreds of academic papers and official documents, and on conversations with people including the Chief of Statistical Services at the UN, the head of the World Development Indicators project at the World Bank, the co-designer of the global poverty count methodology at the World Bank, heads of university departments, statisticians in DFID, the FAO, and many others. My own background is in philosophy, history and experimental psychology. People who agree that I am raising important questions include Uskali Maki, John Broome (professor of moral philosophy in Oxford), senior academic economists such as James Galbraith; and Thomas Pogge (see “Poor but pedicured”, Guardian, 6 May). The following are some brief notes which give an idea of the scope of my work. You are welcome to contact me if you would like further information. In other documents I make practical suggestions as to how welfare outcomes for the estimated 800 million hungry people could be measured cheaply and reliably. The argument on hunger is basically this: Existing statistics on poverty are cross-sectional. But all of them look “worse” if poor people survive longer. So you cannot come to conclusions about how well or badly people did without looking at changes in life length. Also, if economists did solve all the problems I describe below, what would they end up with? They would end up having adjusted their data to make it reflect consumption adequacy. But in the case of hungry people (?800 million) this would be the same as measuring food adequacy. So there are two choices in relation to measuring daily consumption. a) You can measure food adequacy using the original survey data on consumption. Or b) You can convert the food to money (which is what statistical offices do) and then back to food (which is what economists would like to do). Of these, (a) involves fewer sources of uncertainty. For economists to try and estimate average food prices paid by poor people is far more complex than many people might think. And the statistical offices’ methods for setting a money value on food consumption are often not comparable with each other. But food adequacy itself is a very complex and expensive thing to measure. It involves weighing the food people eat and asking them many questions, which, again, yield different answers according to different methods. The simple solution is staring us in the face. People who eat more usually live longer. So life length is an indicator of economic success. The only sane definition of extreme poverty is this: Vulnerability to early death through hunger. The appropriate measure of success should be obvious. Yours sincerely Matt Berkley Fundamental problems in the theory of welfare economics Draft Matt Berkley 29 May 2003 I am not an economist. If there are some errors in what I write below, then I shall be pleased to hear of them. We all make mistakes: in much of life, the task is to make small mistakes rather than large ones. I suggest that several large errors of reasoning are widespread in both the theory and practice of welfare economics - the branch of economics in which claims are made as to aggregate gains and losses to people. Here is what seems to me an accurate description of several aspects in which the theory is defective. 1. All existing measures of income inequality - for example income ratios between rich and poor, and Gini indices - fail to take into account the fact that more poor people than rich people are absent from the data due to earlier death. In all countries, more poor people than rich people are absent from this year’s figures due to early death. In that respect, all existing measures of income inequality underestimate lifetime income inequality, and underestimate inequality of distribution to people during a period. 2. All statements by economists as to the economic progress of poor people, based on trends in their measures of income inequality, have failed to take account of the following fact: Trends in inequality of life length during a period partially determine the inequality of annual income among living people at its end - but in the wrong direction. Economists claim to have measured inequality of distribution to people during a period. But that is not what they have measured. Changes in income differentials are merely one kind of determinant of the level of “inequality” recorded at the end of a period by an economist using an income ratio or a Gini index. Economists have mistakenly treated income gains and losses to people as the sole determinant of the ratio or index. That is not the case. If poor people live longer, the Gini index will look “worse” to an economist who makes the usual but erroneous assumption. The assumption is this: “a trend towards less equality in annual income at the end of a period shows, other things being equal, more losses to poor people”. That is the common belief among economists, and it is not true. We might call this the “distribution fallacy” or “inequality fallacy”. There is a meaningful and important distinction between a) trends in inequality of distribution when comparing people alive at different times and b) inequality of distribution of income to people during a period. Without information on life length, you cannot calculate from (b) from (a) You cannot calculate the change in distribution to people from comparing populations whose composition may have changed. 3. All statements by economists as to average income gains in a population, based on income per capita in different years, suffer from a related flaw. The traditional assumption in economics is that “the people must have had income gains if the average rose and income inequality was unchanged.”. Not so. If poor people live longer, the average will be lower. That is caused by a better average outcome to people, not a worse outcome. A fall in the average is consistent with income rises for every single person in a population during the period. A rise the average is consistent with income falls for every single person in a population during a period. World economic growth would fall if the hungry were kept alive longer. There is a general fallacy of inference by economists in respect of what population averages measure. We might call this the “economic fallacy” - the fallacy that what is good for the economic statistics is good for the people. But then that is a fallacy for several other reasons - see below. Perhaps we should call this the average-income fallacy, or the “growth” fallacy - whichever is easier to keep in mind. 4. All economists’ statements as to average gains or losses to people in poorest fifths or other abstract segments of the economy suffer from a related flaw. The demographic factors in relation to “fractiles” - a jargon word for these abstract segments - are more complex than in the case of averages for the whole economy. Consider the poorest fifth. If people in other fifths live longer, the average for the poorest fifth will rise. If people in the poorest fifth live longer, the average for the poorest fifth will fall. So it is quite hard to see how this kind of data on poorest fifths relates to costs and benefits to the people who were in them at different times. It is also hard to see why anyone would use such data, whose meaning is unknown, to form policies to help poor people. To use data on poorest fifths to talk about whether the incomes of people in them went up or down, or by how much, you need to know quite a lot about demographic change; and to talk about economic gains or losses you need to know quite a lot more (see below on prices, assets, children and so on). 5. All economists’ statements as to “better” or “worse” outcomes to poor people, based on the proportion of people below a per-day consumption poverty line, or the poverty gap ratio or any such static measures of the depth of poverty among living people, or any combination of these with other cross-sectional statistics of living poor persons, suffer from a related flaw. If very poor people die earlier, all of these measures look “better” to an economist unaware of the flaw. They look “worse” to that economist if very poor people live longer. They look “better” if the non-poor live longer. Unfortunately economists do not generally have consumption lines in any case. If a “poverty” line is defined by income level, then it is subject to the expenditure fallacy, the extra-items fallacy and the children fallacy (for all of which see below). 6. All economists’ statements about welfare gains or losses using all the above kinds of statistics - population averages, measures of inequality, quintile averages, proportions of people below a certain level of income, poverty gaps and so on - suffer from an additional flaw which is in addition to and more serious than the other mortality flaw: they have not taken into account the welfare benefit of living longer or the welfare cost of dying early. If you die early, it is not only in failing to take account of the effect of your absence on the cross-sectional statistics that an economist inferring welfare gains or losses has made a mistake. It is also in failing to count the welfare cost to you of dying early. That cost is not quantifiable in any objective sense. The cost of dying early and the benefit of living longer is not objectively comparable to welfare gains or losses to people while they are alive. It is an entirely subjective value judgement. That is so both in relation to statements about the outcome for one individual and in relation to statements about aggregate outcomes among many people. Supposing a social scientist says that it was a better outcome for x number of people to die and y number of living people to have z welfare gains which outweighed the deaths. That judgement is not objective in any way: it is based on a personal opinion. Nor is it possible for someone to make such a comparison in relation to welfare outcome for even one person, without basing their judgement on a personal opinion as to the value of life. Think of your own life. If you have a higher welfare level every year in a short life, is that better or worse than having a lower welfare level in a long life? For every welfare level (even if we could have an objective measure of welfare) and every length of life, the answer would be a matter of personal preference. For a doctor to say that there was a better aggregate outcome if some patients died but many got slightly better would be an expression of a personal opinion. The same would apply to economists who made similar claims on the basis of measures of lifetime economic welfare. One additional problem with looking at lifetime economic welfare would be that it would value the life of a poor person as less than the life of a rich person. This also is a value judgement. Is a country less poor if the poorest people die early than if richer people die early? If anything, to me the reverse seems to be true. If the poorest people begin to die earlier, then the problem of poverty is worse. Another problem is that the relationship between a measure such as economic statistics and welfare is not linear. At some levels of consumption, a lower level of consumption per day may be far more preferable to a person if it means longer life. The non-linearity of the relationship between daily food consumption and daily welfare level among hungry and malnourished people is a complex matter to think about. If lifetime income were the measure of welfare, with the implication that a poor person had gained less by surviving than a richer person, then for even that dubious idea to have credence the income would have to be a reliable static indicator of welfare. If we think about it (see below) we realise that it is not. It would thus be especially dangerous to go round saying that people on lower incomes had less to gain by living longer. 7. All economists’ statements about income gains and losses, based on all the kinds of statistics above, where these were derived from per capita figures, fail to take account of the facts that a) adults need more food than children and b) the ratio of adults to children varies across countries and times. Where, for instance, birth rates fall, the average gain (the average people have for their age now compared to what they would have had on average at that age in the past) is less than the increase in income per capita. Similar considerations apply to traditional measures of income inequality, the proportion of people in poverty, and so on. To take another example: The change in the proportion of people below a consistent poverty line is not knowable from per capita statistics, if changes in the age structure among poor people. There is no requirement on professional economists to avoid the assumption that adults and children need the same amount. There should be. 8. All economists’ statements about the progress of poor people, based on statistics based on the proportion of people below what is termed a poverty line, fail to take into account that the proportion of poor people is affected by not only a) economic gains and losses to poor people and b) demographic changes among poor people, but also c) demographic changes among people above the line. If a government helps people above the line to live longer, the proportion in poverty will fall. If people above the line have more babies, the proportion in poverty will fall. If richer people reduce fertility rates more slowly than poor people, the observed “income inequality” will change. None of these means that poor people did better. 9. All economists’ statements as to income gains or losses to poor people during a period, based on existing measures of income inequality, suffer from the flaw that the inflation rate for poor people’s goods was not taken into account. An income rise is consistent with a rise in prices which outweighs the benefit of that rise. Without any specific data on price trends in poor people’s goods, any conclusions as to economic gains or losses are therefore invalid. For instance, if there is a) a 1% increase in income per capita, and b) zero change in annual income inequality (measured by Gini index, income ratios or anything else) and c) zero consumer price inflation in the economy that cannot possibly tell us that d) “poor people had 1% gains in purchasing power”. A 1% increase in poor people’s incomes (which is in any case not calculable without taking changes in differential mortality and differential age structure into account) does not tell you that they were able to buy more. That is because there is an inflation rate for poor people’s goods. If the price of bread triples, the impact on the overall inflation rate will be far less. The fact that the overall inflation rate is zero, or -1%, or 10%, tells you nothing about the inflation rate for the poor. Without knowing how the price of wheat or rice and other basic goods changed, you cannot tell whether poor people had gains or losses in real (inflation-adjusted for the goods they can afford) income. For people who can only afford a very limited range of the items whose price changes influence the overall consumer price index: a change in income, adjusted by the overall inflation rate, is not rationally described as a change in real income. It is merely the nominal, numerical value of income adjusted by a rate which is of unknown relationship to the inflation rate for poor people. It is hard to see how a description of income statistics among poor people which have not been adjusted by the inflation rate for poor people’s goods could be accurately described as showing economic gains or losses. The statistics cannot tell us about economic gains or losses to poor people. The above means that all past work on, for example, the relationship between GDP per capita and economic gains to poor people using poorest fifths has included a failure to take this logical step into account. The work could not have told us the level of economic gains to poor people even if demographic factors had been taken into account. Additional reasons why the last sentence is true are found in point 10 below: changes in assets and items of necessary expenditure were not taken into account. An assumption that these were of zero importance (or alternatively that changes in these are always proportional to income or expenditure changes) has no theoretical or empirical support, but is crucial to any argument that income or expenditure statistics show the level of economic gain or loss. An additional reason why welfare gains and losses could not have been assessed using such a method is found in point 6 above: it places zero value on the welfare value of even a very short life being extended. In different countries, poor people live for different lengths of time; and life length changes over time. 10. All economists’ statements as to economic benefits to people during a period, based on statistics for declared income, suffer from this flaw: Income, even where adjusted by a) age structure, b) death rates, and c) trends in prices paid by the people being studied, is only one of several key aspects of economic welfare. A lower declared income is consistent with a higher degree of economic power, capabilities, status or welfare: a) If you have a large house, you are, most people would think, richer than someone with no house and slightly more income. b) If you want to become more prosperous, there are at least two ways you can achieve this: 1) increase your income or 2) decrease your expenditure. But the minimum cost of living in a place is not a matter of choice. That is not only because of prices. The cost of living includes both relative prices and relative need for extra items of expenditure. For instance, if more items of expenditure are needed in cities and a higher proportion of people, as time goes by, live in cities, then the cost of living has gone up more than the consumer price index. The cost of each of the extra items (which may include water, rent, transport, fuel and so on) may even fall - which would bring the inflation rate down. Then the cost of living according the consumer price index would have fallen. But in reality it has risen. The cost of living is the cost of living, not the cost of items irrespective of which items are necessary. To make credible and reasonably scientific statements as to economic gains and losses - rather than gains and losses in purchasing power of income, which is what the adjusted statistics would refer to - an economist would have to take into account all the key aspects of economic welfare. Many people might think that for an economist to claim that “assets have no importance in economic welfare” would not correspond to reality. Many people might also think that for an economist to claim that “changes in the list of necessary items of expenditure have no importance in economic welfare” would not correspond to reality. And yet economists’ use of income statistics to infer the direction and level of changes in economic welfare depends logically on both claims. The assumption is this: “Changes in declared income show a proportional benefit or loss to people, in the same direction”. Many people might think that is not rational. Here are three question for theorists of welfare economics: 1. Given the omission of data on key aspects of economic welfare above, in what way would it be accurate to say that income statistics measure a) welfare outcomes or b) economic-welfare outcomes in the aggregate to real people? 2. Is omitting changes in any of the following not a serious omission? a) assets, including gifts and inheritance; b) debts c) undeclared income including employment perks and monetary gifts d) inflation to the poor e) extra items of expenditure f) age structure g) life length 3. What, if any, would be a practical and cost-effective way, in the real world, of measuring enough of the key variables that a reasonable person would say that economic welfare had been measured? [End of email 2003 to Martin Wolf of the Financial Times]