Measuring Poverty (16): The Capabilities Approach and the Unstraightening of the Poverty Line

We usually define poverty as a level of income or financial assets below a certain “poverty line”. This poverty line is set, often implicitly, at a level that is supposed to make the difference between decent survival and a life unworthy of human beings. The line is typically a single line, identical across all individuals – or even across nations. The best example is the $1 a day line. This is a single, universal line, adjusted only for purchasing power parity. Many national poverty lines are also fixed and identical for all citizens.

The problems with these fixed and uniform lines have been noticed by many, notably by Amartya Sen. According to Sen – and he’s right I think – being poor means being unable to achieve certain minimally satisfactory states of being and doing, for example the state of being sufficiently nourished, of being mobile, of being free of disease and ignorance, of being sheltered against the forces of nature etc. Poverty is about what people are or are not able to do and about who they are able to be. Poverty is capability-deprivation.

A poverty line only makes sense if it’s set at an amount of money, income or resources that is sufficient to guarantee the required capabilities. A first problem: it’s not at all clear that existing poverty lines are indeed set at a level sufficient to guarantee this. $1 a day in particular seems low, intuitively. Of course there are pragmatic reasons to set the line at a low level (one has to make priorities in life and help the worst off first). But then you’ll have a hard time calling it a poverty line, given the definition of poverty as the inability to achieve certain minimally satisfactory states of being and doing. Call it a survival line instead.

A second, and more serious problem arises from the fact that poverty lines are fixed and uniform. People, however, are obviously not uniform. Different people require different things in order to achieve the same capabilities. A pregnant women or a young mother needs more nutritional resources than the average person in order to achieve the state of being sufficiently nourished. A physically handicapped person needs more resources to achieve the capability of being mobile. If you focus on the average person – which is what you do with a uniform poverty line – then you’ll fail to identify some as being poor, while erroneously identifying others as being poor. And the environment also plays a role. A person living in unsanitary conditions may be forced to drink infected water. This affects his or her calorie absorption, implying a larger than average amount of food necessary to be sufficiently nourished. Cold weather means more effort to protect against the environment. And so on.

Identical capabilities require different levels of resources or income. A single, fixed poverty line obscures this reality. The only good poverty line is individually specific. However, that’s completely impractical. Differentiation across demographic groups, regions, occupations, lifecycle etc. might be more feasible, but at the cost of simplicity. Be that as it may. I would already be happy with increased awareness that there is indeed a problem. Talk of a “line” reduces this awareness, but I’m realistic enough to understand the appeal of something as simple as a line.

More posts in this series are here.

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Measuring Poverty (15): A Common Misconception About Relative Poverty

Yesterday, I had a short email exchange with Tim Harford, in which I reacted to one of his claims in this article, more specifically the claim that the use of a relative notion of poverty in poverty measurement implies that poverty will always be with us:

Eurostat, the European Union’s statistics agency, … defines the poverty line as 60 per cent of each nation’s median income. (The median income is the income of the person in the middle of the income distribution.)

This has an unfortunate consequence: poverty is permanent. If everyone in Europe woke up tomorrow to find themselves twice as rich, European poverty rates would not budge. That is indefensible. Such “poverty” lines measure inequality, not poverty.

This argument against relative poverty is as common as it is mistaken. Here’s my email to Tim:

I read your article on poverty measurement a moment ago, and I wanted to object. You say that using a relative poverty measurement of income below 60% of median income makes poverty “permanent”. It does not. True, someone with an income of 61% of the median does not suddenly become poor because the median person receives a pay rise. But it’s also true that it’s perfectly doable – mathematically if not in reality – to raise every single poor person’s income above 60% of the median without changing the median. Poverty is only permanent when one would use 60% of the average as threshold, but no one proposes such a foolish thing, fortunately.

In fairness to Tim, his article does list some advantages of relative poverty and he qualified his views in our email correspondence.

More posts in this series are here.

Measuring Poverty (14): Measuring Income Inequality

Income inequality may or may not be the best definition of poverty,  but it’s certainly one that is often used. In many European countries, you’re counted as poor when your income is below 50% or so of the median income. Maybe this is the wrong way to measure poverty, but if you use absolute measures for poverty (such as a basic income, minimum consumption etc.) you’ll also face some problems. So it’s worthwhile to examine some of the usual methods for measuring income inequality and see how they hold up, while at the same time bracketing the discussion about poverty as either absolute deprivation or unequal distribution.

Methods for measuring income inequality

The Gini coefficient is the most widely used. It’s based on the proportion of the total income of a population that is cumulatively earned by a % of the population; a value of 0 expresses perfect equality where everyone has equal shares of income and a value of 1 expresses maximal inequality where only one person has all the income. A low Gini coefficient indicates therefore a more equal distribution. (The complete formula is here).

A disadvantage of the Gini measure is that it doesn’t capture where in the distribution the inequality occurs: is a society unequal because the top 1% has astronomically high incomes, because the poor are very poor, because there is practically no middle class, or because of some other reason?

Other measures are

  • the ratio of the incomes of the top 10% (best paid) to the bottom 10% (worst paid)
  • the proportion of a population with income less than 50% of the median income
  • a population may be split into segments, e.g. quintiles or deciles, and each segment’s income share is then compared to each other segment’s (for example, the top 10% of the population – “top” in income terms – has x % of total income)
  • some other measures are here.

These different measures can give contradictory numbers: two societies with the same Gini score can have different ratios of top-bottom, top-middle or middle-bottom incomes (see an example here). Hence, no single measure will tell us the last word about inequality in a society.

What is income?

The focus of all these measurement systems is income, but we should first decide what to count as income. Income doesn’t have to be cash or currency. A farmer in a poor country who grows his own products has non-cash income. Perhaps public services such as healthcare or education should count as income. And how about tax reductions, tax refunds, government benefits such as unemployment insurance, food stamps and various vouchers?

All those forms of non-cash or non-labor income are important when measuring income inequality because the poor profit disproportionately from those non-cash or non-labor related forms of income. Hence, including them in total income can make a large difference in income inequality numbers. (Higher income groups may have less or different tax refunds and their education may represent a smaller portion of their total income – the returns of their education may of course be higher, but those returns are typically cash based in the sense that they lead to higher labor compensation).

We should also decide if we want to use income before or after taxation; depends if we want to measure the effectiveness of redistribution or simply gross inequalities. And what about capital gains, imputed house rents from home ownership, inheritance etc. In general, how should wealth be included in income? Or shouldn’t it be?

How do we measure income?

Once we’ve solved the difficult problem of defining income, we’re still left with the practical problem of measuring it. Most cash income is captured in tax return data, but not all, and not equally well in all countries. Sometimes, you’ll need to use consumption data as a proxy for income data, or surveys about living standards. “Informal” income typically does not show up in tax data, but does in consumption data.

Another problem with measures of inequality is that they may be contaminated by notions of fairness. Some deliberately design their measurement system in such as way that inequalities look bigger than they actually are. For example, they use pre-tax inequalities because those are often larger than post-tax inequalities – a lot of tax systems are redistributive towards the poor (e.g. progressive taxation systems). Or they focus on income inequality when consumption inequality may have diminished. Others may mistakenly deduce evaluations of fairness or injustice from the simply fact of income distributions and forget that measures of income inequality are silent about who is on which side of the divide. If person A in a two person economy has twice the income of person B, then the measurement of inequality would be absolutely the same when B switches places with A. Measures of income inequality say nothing about who deserves what, about how income has been acquired, about whether some occupations should yield higher compensation (for example because we want the right incentives), or about how income should ideally be distributed.

And then there is the opposite mistake: assuming that income inequality is always necessary and just because it’s the automatic result of the fact that people have different levels of human capital and productive abilities. This is a mistake because it ignores a number of facts: no one has ever been able to prove that some abilities or occupations deserve higher wages from a moral point of view, and a lot of inequality is the result not of different abilities or efforts but of differences in luck and connections. Hence, fairness remains a legitimate concern. Contrary to the “left-wing mistake”, the “right-wing mistake” will not distort the measurement of inequality: if you believe inequality is not a problem you hardly have a reason for measuring it, let alone distort the measurement.

What I want to stress is how difficult it is to measure income inequality and how many mistakes we can make. This doesn’t mean that the numbers are rubbish. We should just be careful when drawing sweeping conclusions, that’s all.

Something more about the causes of income inequality, rather than the measurement of it, is here.

Measuring Poverty (12): The Experimental Method

The so-called experimental method of poverty measurement is akin to the subjective approach. Rather than measuring poverty on the basis of objective economic numbers about income or consumption the experimental method uses people’s subjective evaluation of living standards and living conditions. But contrary to the usual subjective approach it’s aim is not to ask people directly about what poverty means to them, about what they think is a reasonable minimum level of income or consumption or a maximum tolerable level of deprivation in certain specific areas (food, health, education etc.). Instead, it uses experiments to try to gather this information.

For example, you can set up a group of 20 people from widely different social backgrounds and some of them may suffer from different types of deprivation, or from no deprivation at all. The group receives a sum of money and has to decide how to spend it on poverty alleviation (within their test group or outside of the group). The decision as to who will receive which amount of funding targeted at which type of deprivation has to be made after deliberation and possibly even unanimously.

The advantage of this experimental approach, compared to simply asking individual survey respondents, is that you get a deliberated choice: people will think together about what poverty means, about which types of deprivation are most important and about the best way to intervene. It’s assumed that such a deliberated choice is better than an individual choice.

More posts in this series are here.

Measuring Poverty (11): The Subjective Approach

Usually, we measure poverty on the basis of objective numbers about income or consumption. Income or consumption levels are put on a continuum from lowest to highest and somewhere along the continuum we put a threshold that indicates the difference between poor and non-poor. For example, the Indian government uses a consumption threshold of 2,400 calories a day in rural areas and 2,100 in urban areas. The World Bank uses an income threshold of one dollar a day (corrected for purchasing power).

There are numerous disadvantages to these objective approaches. One is the inevitably arbitrary positioning of the threshold. One dollar a day, even after correction for purchasing power, means different things to different people in different areas, circumstances, groups etc. Calorie intake also means different things to different people, depending on people’s way of life etc. Moreover, income levels are notoriously difficult to measure (poor people in particular have a lot of informal income, e.g. “income” coming from all sorts of assistance from relatives etc.). Consumption as well is a difficult measure: it doesn’t necessarily have to mean just calorie intake for example. Poverty can mean a lack of non-food consumption. And if you focus on calorie levels after all, you’ll miss the issue of the quality of the food.

Also the third most common approach to poverty measurement suffers from some disadvantages. This approach, also called the multidimensional approach, tries to assess to what extent people suffer from a series of different types of deprivation: do they have access to water, to electricity, are they literate, malnourished etc. Rather than purely quantitative these measurements can be qualitative: a binary yes/no is often enough. Unfortunately, also this measurement system has some drawbacks: it fails to distinguish between deprivation and choice; there’s necessarily a level of arbitrariness in the determination of the “basic needs” or forms of deprivation that are measured; and these needs are often overly general, obscuring some very specific needs for some people in some areas or groups.

That’s why people have been searching for alternative measures of poverty. One such alternative is the use of surveys that ask people about poverty. You could ask people what they believe is “the smallest amount of money a family needs each week to get along in this community”, “what is the level of income below which families can’t make ends meet” etc. That would remove some of the arbitrariness of the cutoff line between poor and non-poor, and putting that decision in the hands of the people rather than the scientists.

Or you could also present people with evocative descriptions of different family situations, of types of families according to their level of income or consumption or according to the type of deprivation. People would then have to decide for every family situation what they believe the standard of living is and which situation can be described as “poverty”. That would specify what poverty means to people. And what it means to people is much more important than what it means to researchers and statisticians.

A disadvantage of this subjective approach is the wellknown effect that people’s income levels affect their judgments about income adequacy. In short, relatively rich people overestimate the level of income inadequacy. A solution to this problem could be to ask only poor respondents about poverty, on the reasonable assumption that poor people are the best experts on poverty. But that’s a circular reasoning: you already think you know what poverty is before you start asking about it. Since you focus only on the poor, you’ve already decided what poverty is.

An advantage of the subjective approach is that researchers don’t have to list basic needs or types of deprivation in order to assess what poverty is; people tell you what poverty is. There’s also no need for researchers to specify regionally or socially undifferentiated and general cutoff levels of income or consumption below which people are considered to be poor.

Measuring Poverty (10): Multidimensional Poverty

Poverty can be many different things. It can be different things to different people in different countries or circumstances. It can mean one thing for people in Africa and another for people in the favelas in Rio, and still another for those in the inner-cities in the U.S. It’s probably different for men, women and children. It can be absolute deprivation or relative poverty (i.e. inequality). It can be insufficient income or insufficient consumption. It can be a lack of one thing or another. For some people it means inadequate healthcare, for others it means insufficient water. It can be physical suffering or the stress inherent in insecurity. It can be malnutrition or a lack of self-esteem. It can be illiteracy or child mortality. Etc.

Most poverty measurement systems try to keep it simple. The most common systems just measure income. Poverty is then insufficient income (typically below $1-a-day, corrected for purchasing power; this measures the number of people incapable of buying a basic basket of commodities). That makes sense, because without sufficient income, you’re likely to experience child mortality, illiteracy, malnutrition, inequality, water shortages, stress, insecurity and all the other nasty things that come with poverty.

However, it is important to know those details of poverty. Two people who both have an income of less than one dollar a day, may experience very different consequences: one may be deprived in lots of areas, the other one maybe in just a few. One may lack good health, may be starving and may be illiterate. The other one may just be illiterate. If we want to help people, it’s important to know what the exact nature of their problem is. Which we don’t if we just focus on how much their income is.

That is why some researchers at the Oxford Poverty and Human Development Initiative at the University of Oxford have tried to come up with a so-called Multidimensional Poverty Index (MPI).

The index seeks to build up a picture of the prevalence of poverty based on the fraction of households who lack certain basic things. Some of these are material. Does a family home have a dirt or dung floor? Does it lack a decent toilet? Must members of the household travel more than 30 minutes on foot to get clean water to drink? Do they live without electricity? Others relate to education, such as whether any school-age children are not enrolled or whether nobody in the family has finished primary school. Still others concern health, such as whether any member of a household is malnourished. A household is counted as poor if it is deprived on over 30% of the ten indicators used. Researchers can then calculate the percentage of people in each country who are “multidimensionally poor”. (source)

Such a multidimensional approach has the advantage of identifying which specific aspect(s) of poverty is/are most common in certain areas or among certain groups of people. It shows how people are poor, and what contributes most to poverty in a specific place and among a specific group. This will obviously greatly enhance response capacity. Rather than just trying to generally increase income, we can target our efforts more specifically: in one area or among one group of people we know that we should focus on nutrition; elsewhere we know that we should focus on literacy for instance. The MPI also shows us how different aspects of poverty overlap: for example, how many people who are illiterate also have health problems?

If 30% of people are malnourished and 30% of children are out of school, it would be useful to know if these deprivations affect the same families or different ones. (source)

The approach also helps us to distinguish between deprivation and choice. People may actually prefer mud floors to concrete floors in some places, and don’t consider having a mud floor as a form of deprivation. It also helps to identify the depth of poverty: deprivation along a wide spectrum of indicators means that poverty is deeper.

Unsurprisingly, the results of the MPI are substantially different from traditional poverty measurements:

Also the totals are different:

About 1.7 billion people in the countries covered – a third of their entire population – live in multidimensional poverty, according to the MPI. This exceeds the 1.3 billion people, in those same countries, estimated to live on $1.25 a day or less, the more commonly accepted measure of ‘extreme’ poverty. (source)

One of the disadvantages of this new approach is the weighting of the different measures: there’s inevitably some arbitrariness involved. Is the death of a child equivalent to having a dirt floor? Worse? How much worse? More criticism of the MPI is here.

There’s a really cool interactive map of the MPI here.

Measuring Poverty (9): Absolute and Relative Poverty Lines

There are many ways you can measure how many people in a country are poor. Quite common is the use of a so-called poverty line. First you decide what you mean by poverty – for instance an income that’s insufficient to buy life’s necessities, or an income that’s less than half the average income etc. Then you calculate your poverty line – for instance the amount of income someone needs in order to buy necessities, or the income that’s half the average income, or the income of the person who has the tenth lowest income if the population was one hundred etc. And then you just select the people who are under this poverty line.

I intentionally chose these examples to make a point about absolute and relative poverty. In the U.S., people mostly use an absolute poverty line, whereas in Europe relative poverty lines are used as well. As is clear from the examples above, an absolute poverty line is a threshold, usually expressed in terms of income that is sufficient for basic needs, that is fixed over time in real terms. In other words, it’s adjusted for inflation only and doesn’t move with economic growth, average income, changes in living standards or needs.

A relative poverty line, on the other hand, varies with income growth or economic growth, usually 1-to-1 since it’s commonly expressed as a fixed percentage of average or median income. (It obviously can have an elasticity of less than 1 since you may want to avoid a disproportionate impact on the poverty line of very high and very volatile incomes. I’ve never heard of an elasticity of more than 1).

Both absolute and relative poverty lines can be criticized. Does an absolute poverty line make sense when we know that expectations change, that basic needs change (in contemporary Western societies, not having a car, a phone or a bank account can lead to poverty), and that the things that you need to fully participate in society are a lot different now than they once were? We know that people’s well-being does not only depend on the avoidance of absolute deprivation but also on comparisons with others. The average standard of living defines people’s expectations and when they are unable to reach the average, they feel excluded, powerless and resentful. Can people who fail to realize their own expectations, who lose their self-esteem, and who feel excluded and marginalized be called “poor”? Probably yes. They are, in a sense, deprived. It all depends which definition of poverty we can agree on.

It seems that people do think about poverty in this relative sense. If you compare the (rarely used) relative poverty line of 50% of median income in the U.S. with the so-called subjective poverty lines that result from regular Gallup polls asking Americans “how much they would need to get along”, you’ll see that the lines correspond quite well.

So if relative poverty corresponds to common sense, it seems to be a good measure. On the other hand, a relative poverty line means moving the goal posts for all eternity. We’ll never vanquish relative poverty since this type of poverty just moves as incomes rise. It’s even the case that relative poverty can increase as absolute poverty decreases, namely when there’s strong economic growth (i.e. strong average income growth) combined with widening income inequality (something we’ve seen for example in the U.S. during the last decades). (Technically, if you use the median earner as the benchmark, relative poverty can disappear if all earners who are below the median earner move towards the median and earn just $1 or so less than the median. But in practice I don’t see that happening).

Measuring Poverty (8): Deep Poverty

Most systems for measuring poverty use a so-called poverty rate or poverty line (that’s the case in the U.S. for instance, or in the UN’s Millennium Development Goals). That’s a level of income (or consumption etc.) which is considered to be the minimum that’s necessary for a decent human life and for the satisfaction of basic needs. These systems are also called “headcount” measures of poverty: they simply count how many people fall below the fixed point that determines the difference between poverty and non-poverty.

You can see the problem coming: according to these systems, you’re either poor or you ain’t. They just tell us how many people are poor, not how poor they actually are. This is a big problem in developed countries that use such poverty measurement systems. The poverty rates in those countries are rather high in dollar terms. For example, the thresholds in the U.S. are, as of 2008:

  • One adult: $11,200 annual income, not including the EITC or non-cash benefits (Food Stamps, Medicaid, housing assistance, employer health-insurance contributions, etc.), and including taxes
  • Two adults: $14,400
  • One adult, two kids: $17,300
  • Two adults, two kids: $21,800.

By “rather high” I don’t mean to say that the people under those poverty lines aren’t really poor and that the U.S. measurement system is too generous (if anything, it’s the contrary). What I want to say is that in developed countries, people need a substantial income in order to escape poverty. If you want a job, you’ll probably need a car, a phone, internet connection, child care etc. If you want a place to live, you’ll need to spend a huge amount of money on a house, and so on. Poverty lines in developed countries are therefore not so low that being poor means being on the brink of starvation. They are set at such a level that being poor means being unable to afford a job, quality housing, healthcare and education.

Given the fact that poverty rates are rather high, there’s a lot of space below them. Hence, you have different kinds of poor people: there are those who have a job and an income, albeit a rather low one, but who struggle to survive because of their expenses; and there are those who just live on the street. You have people who are poor for some years and people who are poor their entire lives.

All these people are equally poor in the measurement system we’re discussing here. This system doesn’t provide data on the distance from the poverty line, or, in other words, on the depth of poverty. In the worst case, people who are already poor according to the system could become much poorer, without any change in the headcount of poverty. If the 13% or so of Americans who are currently under the poverty line all became homeless beggars, you wouldn’t see a change in U.S. poverty statistics.

In order to solve this problem, people have come up with the concept of the poverty gap (incidence * depth of poverty): the mean distance separating the population from the poverty line (with the non-poor being given a distance of zero), expressed as a percentage of the poverty line (see also here). Unfortunately, this hasn’t become a very popular number. It’s probably too complicated. A clear and simple poverty line is much more appealing yet deficient.

More post on the problems of poverty measurement are here.

Measuring Poverty (7): Different Types of Poverty

I already mentioned the obvious but consequential fact that poverty measurement depends on the choice of the type of poverty you want to measure. Definitional issues are always important, but when it comes to poverty the choice of a definition of poverty determines who will benefit from government benefits and who won’t. For example, in the U.S. you’re poor when you’re income is below a certain poverty line. If that’s the case, you’re eligible for certain benefits. So poverty is a function of income.

1. Insufficient income

Usually, and not only in the U.S., poverty is indeed understood as insufficient income (preferably post-tax and post-benefits). Measuring poverty in this case means

  1. determining a sufficient level of income (sufficient for a decent human life); this is usually called a “poverty line” or “poverty rate”
  2. measuring actual income
  3. counting the number of people who have less income than the sufficient level.

There are some problems with this measurement system or this choice of type of poverty. Actual income levels are notoriously difficult to measure. People have a lot of informal income which they will not disclose to people doing a survey. Likewise, there is tax evasion and income in kind (market based or from government benefits, e.g. social housing), and material or immaterial support by local social networks. None of this is included correctly if at all in income measurement, leading to an overestimate of poverty. Another disadvantage of income based measurements: they neglect people’s ability to borrow or to draw from savings in periods of lower income. Again, this overestimates poverty (although one could say that it just estimates it a bit too early, since borrowing and eating up savings can lead to future poverty).

2. Insufficient consumption

Because of these problems, some countries define poverty, not by income levels, but by consumption levels. Measuring poverty in this case means

  1. determining a sufficient level of consumption (sufficient for a decent human life)
  2. measuring actual consumption
  3. counting the number of people who consume less than the sufficient level.

However, this measurement isn’t without problems either. As is the case for income levels, actual consumption levels are difficult to measure. How much do people actually consume? And what does it mean “to consume”? Is it calorie intake? Is it financial expenses? Or something else perhaps? Consumption levels are also deceiving: people tend to smooth their consumption over time, even more so than their income. If they face a financial crisis because of unemployment, bad health, drought etc. they will sell some of their assets (their house for instance) or take a loan. If you determine whether someone is poor on the basis of consumption levels, you won’t consider people dealing with a crisis as being poor because they continue to consume at the same levels. However, because of loans or the sale of assets, they are likely to face poverty in the future. They may also shift their diet away to low quality food, taking in the same amount of calories but risking their health and hence their future income. Similarly, they may be forced by their crisis situation to delay health expenditures in order to smooth consumption, with the same long term results.

And even if you manage somehow to measure consumption, you’re still faced with the problem of the threshold of sufficient consumption: that’s hard to determine as well. Consumption needs differ from person to person, depending on age, gender, occupation, climate etc.

3. Direct physical measures of real consumption

Rather than trying to measure total income or consumption, you can choose to measure consumption of certain specific physical items, and combine that with some easy to measure elements of standard of living, such as child mortality or education levels. It’s possible to argue that poverty isn’t an insufficient level of overall income or consumption, but instead the absence of certain specific consumption articles. People are poor if they don’t have a bicycle or a car, a solid floor, a phone etc. Or when their children die, can’t go to school or are undernourished. These items or indicators are relatively easy to measure (for example, there’s the Demographic and Health Survey). While they may not tell us a lot about relative living standards in developed countries (where few children die from preventable diseases for instance), they do provide poverty indicators in developing countries.

The OECD has done a lot of good work on this. They call it “measuring material deprivation“. It’s the same assumption: there are certain consumer goods and certain elements of living standard that are universally considered important elements of a decent life. The OECD tries to measure ownership of these goods or occurrence of these elements, and when people report several types of deprivation at the same time, they are considered to be poor.

Take note that we’re not talking about monetary measures here, contrary to income and overall levels of consumption. Sometimes, all that has to be measured is a “yes” or a “no”. Which of course makes it easier.

Unfortunately, not easy enough. This type of poverty measurement has its own drawbacks. Measures of material deprivation often fail to distinguish between real deprivation and the results of personal choices and lifestyles. Some people can’t have a decent life without a car or a solid floor; others voluntarily choose not to have those goods. It’s likely that only the former are “poor”. Furthermore, since these measurements are often based on surveys, there are some survey related problems. The really poor may be systematically excluded from the survey because we can’t find them (e.g. the homeless). These surveys measure self-reported poverty, and self-reported poverty can be affected by low aspirations or habit. People may also be ashamed about their poverty and hence not report it correctly.

Conclusion

There isn’t a perfect system for poverty measurement. And that has a lot to do with the fact that poverty is an inherently vague concept. It really shouldn’t be a surprise that people choose different definitions and types, and hence different measurement methods that all provide different data. There’s no “correct” definition of poverty, and hence no correct poverty measure.

More posts in this series on the difficulties of poverty measurement.

Measuring Poverty (6): The Poverty Line in the U.S.

The poverty rate or poverty line in the U.S. is based on a system pioneered by Mollie Orshansky in 1963. In the 1960s, the average US family spend one third of its income on food. The poverty line was calculated by valuing an “emergency food” budget for a family, and then multiplying that number by 3. (Some more data here).

This results in a specific dollar amount that varies by family size but is the same across the U.S. (the amounts are adjusted for inflation annually). To determine who is poor, actual family income is then compared to these amounts. Obviously, if you’re under, you’re poor.

Amazingly, this system hasn’t changed a lot since the 1960s, yet it suffers from a series of measurement problems, resulting in either an over- or underestimation of the number of families living in poverty. The problems are situated both in the calculation of the poverty rates and in the calculation of the income that is subsequently compared to the rates:

  • Obviously, the system should take regional differences in the cost of living, especially in housing, into account. It doesn’t.
  • As already apparent from the image above, a family today spends relatively less on food and more on housing, health care and child care etc. yet the poverty line is still dollars for emergency food times 3. So the question is: should the system take today’s spending patterns into account? We would have to know which it is: 1) Either the increased spending on non-food items has occurred because people can now afford to spend more on such items. 2) Or the increased spending on non-food items has occurred because these items got disproportionately more expensive (housing for instance) or because there wasn’t really any need to buy those items in the old days. Only if 2) is the case should that have an influence on the poverty line. And I think that to some extent it is the case. Child care for instance has become a necessity. In the 1960s, many mothers didn’t go out and work. Now they do, and therefore they have to pay for child care. Those payments should be deducted from income when measuring disposable income and comparing it to the poverty line. The same is true for cars or phones. Today you can’t really have a job without them so they’re no longer luxuries. A society would show very little ambition if it continued to designate the poor as those who have to wash by hand, read with candlelight, and shit in a hole in the floor. In fact, what I’m advocating here is some kind of relative concept of poverty. I’ll come back to that later. All I can tell you now is that this isn’t without complications either.
  • The current poverty measurement doesn’t take into account disproportionate price rises (it merely adjusts for general inflation) and changing needs. An obvious improvement of the U.S. measurement system would be to adjust for exceptional price evolutions (such as for housing) and also to revisit the definitions of basic needs and luxuries. Hence, a better poverty measurement should subtract from income some work-related expenses, child care expenses, and perhaps also some health expenses to the extent that these have become disproportionately more expensive. But that’s not easy:

There is considerable disagreement on the best way to incorporate medical care in a measure of poverty, even though medical costs have great implications for poverty rates. But costs differ greatly depending upon personal health, preferences, and age, and family costs may be very different from year to year, making it hard to determine what exactly should be counted. Subtracting out-of-pocket costs from income is one imperfect approach, but if someone’s expenses are low because they are denied care, then they would usually be considered worse off, not better off. (source)

  • Another problem: the current poverty rate doesn’t take all welfare benefits into account. Income from cash welfare programs counts, but the value of non-cash benefits such as food stamps, school lunches and public housing doesn’t (because such benefits weren’t very common in the 1960s). Those benefits successfully raise the standard of living for poverty stricken individuals. There’s a bit of circular reasoning going on here, because the poverty rate is used, i.a., to decide who gets benefits, so benefits should not be included. But if you want to know how many people are actually poor, you should consider benefits as well because benefits lift many out of poverty.
  • The poverty measure doesn’t include some forms of interests on savings or property such as housing.
  • The poverty measure doesn’t take taxes into account, largely because they didn’t affect the poor very much in the 1960s. Income is counted before subtracting payroll, income, and other taxes, overstating income for some families. On the other hand, the federal Earned Income Tax Credit isn’t counted either, underestimating income for other families.
  • And there’s also a problem counting the effects of cohabitation and co-residency, overestimating poverty because overestimating expenses.

Because the poverty measurement disregards non-cash benefits and certain tax credits, it fails to serve its purpose. Poverty measurement is done in order to measure progress and to look at the effects of anti-poverty policies. Two of those policies – non-cash benefits and certain tax credits – aren’t counted, even though they reduce poverty. So we have a poverty statistic that can’t measure the impact of anti-poverty policy… That’s like measuring road safety without looking at the number of accidents avoided by government investment in safety. Since the 1970s, the U.S. government implemented a number of policies that increased spending for the poor, but the effects of this spending were invisible in the poverty statistics.

This had a perverse effect: certain politicians now found it easy to claim that spending on the poor was ineffective and a waste of money. It’s no coincidence that trickle down economics became so popular in the 1980s. The poverty measurement, rather than helping the government become more effective in its struggle against poverty, has led to policies that reduced benefits. Of course, I’m not saying that poverty reduction is just a matter of government benefits, or that benefits can’t have adverse effects. Read more here.

Fortunately, the US Census Bureau has taking these criticism to heart and has been working on an alternative measure that counts food stamps and other government support as income, while also accounting for child-care costs, geographic difference etc. First results show that the number of poor is higher according to the new measurement system (it adds about 3 million people). For some reason, I think the old system has still some life in it.

Some details of the new measurement:

when you account for the Earned Income Tax Credit the poverty rate goes down by two points. Accounting for SNAP (food stamps) lowers the poverty rate about 1.5 points. … when you account for the rise in Medical Out of Pocket costs, the poverty rate goes up by more than three points. (source)

More posts about problems with poverty measurement are here.

Measuring Poverty (5): The Mystery of the Feminization of Poverty

Some have called it a baseless claim: 70% of the world’s poor are women. This is a number that seems to have come from nowhere yet it has taken on a life of its own. The reason is probably that it has some intuitive appeal. Theoretically, the claim that being female places someone at a greater risk of being poor is convincing. Gender discrimination – which is a deceptively neutral term meaning discrimination of one gender only – is a widespread problem and it’s highly probable that women who suffer discrimination are more likely to be poor and to remain poor. They

  • receive less education
  • receive lower wages
  • cannot freely choose their jobs in some countries
  • have less inheritance rights than men in some countries
  • perform the bulk of the household tasks making it relatively hard to accumulate income
  • are responsible for the household income (men are often culturally allowed to escape into leisure and get away from the burdens of poverty)
  • suffer disproportionately from some types of violence
  • and face very specific health risks related to procreation.

All these problems faced by women who suffer discrimination make it more likely that they are relatively more burdened by poverty, compared to men who usually don’t suffer these types of discrimination.

Moreover, when young women begin to enjoy better education and employment we often see that the discriminatory features of the family structures and patriarchal systems in which they live make fresh appeals to their newly found human capital. As a result, their improved capabilities only serve to push them more into poverty. Poverty, after all, isn’t merely a question of sufficient income and capabilities, but is also determined by the availability of choice, opportunities and leisure.

So it’s obvious that men and women are poor for different reasons, and that some of the reasons that make women poor make them relatively more poor compared to men.

This is the intuitive case, but it appears that it’s very difficult to back this up with hard numbers. The “70%” claim is unlikely to be correct, but if we agree that discrimination skews the distribution, then how much? And how much of it is compensated by factors that skew the distribution towards male poverty (e.g. male participation in wars). The problem is that poverty data are usually available only for households in aggregate and aren’t broken down by individuals, sex, age etc. So it’s currently impossible to say: “this household is poor, and the female parent/child is more poor than the male parent/child”. In addition, even in households that aren’t poor according to standard measures, the women inside these households may well be poor. Women is non-poor households may be unable to access the household’s income or wealth because of discrimination.

Given the problems of the current poverty measurement system, I think it’s utopian to expect improvements in the system that will allow us to adequately measure female poverty and test the hypothesis of the feminization of poverty.

Measuring Poverty (4): The Problem of the Definition of Poverty

Before you can start to measure poverty, you first have to decide what you actually want to measure. What is poverty? That’s not just a philosophical problem because depending on the definition of poverty you use, your measurements will be radically different (even with an identical definition, measurements will be different because of different measurement methods).

Among people who measure poverty, roughly 6 different definitions of poverty are used:

  • insufficient income
  • insufficient consumption spending
  • insufficient calorie intake
  • food consumption spending above a certain share of total spending
  • certain health indicators such as stunting, malnutrition, infant mortality rates or life expectancy
  • certain education indicators such as illiteracy.

None of these definitions is ideal, although the first and second on the list are the most widely used. A few words about the advantages and disadvantages of each.

Income

Advantages:

In developed countries, income is a common definition because it’s easy to measure. Most people in developed countries earn a salary or get their income from sources that are easy to estimate (interest payments, the value of houses, stock market returns etc.). They don’t depend for their income on the climate, crop yields etc. Moreover, developed countries have good tax data which can be used to calculate incomes.

Disadvantages:

In developing countries, however, income data tend to be underestimated because it’s difficult to value the income of farmers and shepherds. Farmers’ incomes fluctuate heavily with climate conditions, crop yields etc. If you ask them one day what their income is, there’s no guarantee that this is a good estimate of their yearly income.

Another disadvantage is that people are generally reluctant to disclose their full income. Some income may have been hidden from the tax administration or may have been earned from illegal activity such as corruption, smuggling, drug trade, prostitution, theft etc. For this reason, using income to estimate poverty means overestimating it.

And, finally, some income may be difficult to calculate (e.g. rising value of livestock).

Consumption

Advantages:

The main advantage of using consumption rather than income to measure poverty is that consumption is much more stable over the year and over a lifetime (see above). Hence, if you ask people about the level of their consumption, they can just tell you about their current situation, without having to go back in time or to predict the future – which they would have to do if you asked them about income. Their current consumption is likely to be representative of their long term consumption, which isn’t the case for income. This is even more true in the case of farmers who depend on the weather for their income and hence have a more volatile income. If you know that farmers are often relatively poor, then this issue is all the more salient for poverty measurement.

Another advantage of using consumption is that people aren’t as reticent to talk about it as they are about certain parts of their income. It’s also appears that people tend to remember their spending better than their income.

Disadvantages:

If you want to measure how much people consume, you have to include durable goods and housing. And consumption of those goods is difficult to measure because it’s difficult to value them. For example, if a household owns a house, you have to estimate what it would cost to rent that particular house and add this to the total consumption of that household, at least if you want to compare their consumption to the consumption of the household next door who has to rent its house. And you can’t make poverty statistics if you don’t make such comparisons. Then you have to do the same for cars etc.

Another difficulty in measuring consumption, is that in developing countries households consume a lot of what they themselves produce on the family farm. This as well is often difficult to value correctly.

And finally, different people have different consumption needs, depending of their age, health, work etc. It’s not clear to me how these different needs are taken into account when consumption is measured and used as an indicator of poverty.

Other definitions

Calorie intake: the problem with this is that different people need different amounts of calories (depending on their type of work, their age, health etc.), and that it isn’t very easy to measure how many calories people actually consume.

Food spending as a fraction of total spending: if you say people who spend more than x % of their total spending on food are considered poor, you still have to factor in relative food prices.

Stunting as an indicator of malnutrition and hence of poverty: stunting (height for age) is a notoriously difficult thing to measure.

Other issues

Some aspects of life tend to be excluded from poverty measurement, even though they have a huge impact on people’s wellbeing. The amount of leisure time people have is perhaps a good indicator of poverty, in certain circumstances (excluding CEOs and US Presidents), but it’s hardly ever counted in poverty measurements.

Another thing: people may have comparable incomes or even consumption patterns, but they may face very different social or environmental conditions: an annual income of $500 may be adequate for people living in a rural environment with a temperate climate where housing is cheap, heating isn’t necessary and subsistence farming is relatively easy. But the same income can mean deep poverty for a family living in a crowded city on the edge of a desert. The presence or absence of public goods such as quality schools, roads, running water and electricity also makes a lot of difference, but poverty measurement usually doesn’t take these goods into account.

Measuring Poverty (2): Some Problems With Poverty Measurement

The struggle against poverty is a worthy social goal, and the absence of poverty is a human right. But poverty is also an obstacle to other social goals, particularly the full realization of other human rights. A necessary instrument in poverty reduction is data: how many people suffer from poverty? Without an answer to that question it’s very difficult to assess the success of poverty reduction policies (such as development aid).

And that’s were the problems start. There’s some uncertainty in the data. The data may not reflect accurately the real number of people living in poverty. There are definition issues – what is poverty? – that may reduce the accuracy of the data or the comparability between different measurements of poverty (or between different measurements over time), and there are issues related to the measurements themselves. I’ll focus on the latter for the moment.

Poverty is often measured by way of surveys. These surveys, however, can be biased because of

  1. sample errors: underreporting of the very rich and the very poor (more on sample errors here), and
  2. reporting errors: failure of the very rich and the very poor to report accurately.

The rich are less likely than middle-income people to respond to surveys because they are less accessible (their houses for instance are less accessible). In addition, when they respond, they may tend to underreport a larger fraction of their wealth as they have more incentives to hide (for tax reasons for example).

The very poor may also be inaccessible, but for other reasons. They may be hard to interview when they don’t have a fixed address or an official identification. In poor countries, they may be hard to find because they live in remote areas with inadequate transportation access. And again, when they report, it may be difficult to estimate their “wealth” because their assets are often in kind rather than in currency.

Because we can have underreporting of the two extremes on the wealth distribution, we believe that income distribution is more egalitarian than it really is. Hence we underestimate income inequality and relative poverty.

But apart from relative poverty we also underestimate absolute poverty since we’re often unable to include the very poor in the reporting for the reasons given above. By “cutting off” the people at the poor end of the distribution, it seems like most people are middle class and society largely egalitarian.

However, absolute poverty can also be overestimated: if the poor respond, we may fail to accurately assess their “wealth” given that much of it is in kind. And it’s unlikely that these two errors – underestimation and overestimation – cancel each other out.

These and other problems of poverty measurement make it difficult to claim that we “know” more or less precisely how many poor people there are, but if we make the same errors consistently we may be able to guess, not the levels of poverty, but at least the trends: is poverty going up or down?

Measuring Poverty (1): Measuring Poverty in India

The government of India uses a consumption based method to measure poverty: given that an average adult male has to eat food representing approximately 2000-2500 calories per day in order to sustain the human body, how much would it cost to buy these calories? Those who have an income that is lower than this cost, are poor.

Actually, the Indian government uses the thresholds of 2,400 calories a day in rural areas and 2,100 in urban areas. (City dwellers are thought to exert less energy, so they should need to consume less. See here).

Of course, this measure, like all measures, isn’t perfect. A person may be able to afford to buy food that contains 2,400 calories, but the quality or nutritional value of this food (in terms of vitamins etc.) may be so low that we can hardly exclude this person from the population of the poor. He or she may be able to buy 2,400 calories, but not enough nutritional value to lead a decent life.

However, I wonder whether India’s poverty measurements include only consumption of food. Poverty is more than just a nutritional issue. People may be able to buy enough food of sufficient nutritional quality, but may be left without resources for shelter, healthcare, education etc.