1.1a Proportion of population below national poverty line

Modified on 2012/03/01 14:35 by MDG Wiki Handbook — Categorized as: Goal 1



Goal 1. Eradicate extreme poverty and hunger Target 1.A Halve, between 1990 and 2015, the proportion of people whose income is less than one dollar a day


Definition The proportion of population below national poverty line is defined as the proportion of the total population living below the national poverty line.

This indicator is expressed as a percentage.

Concepts National poverty lines are thresholds defined at the country level below which a person is deemed to be poor. National poverty lines are commonly set as the consumption expenditure or income level at which food energy intake is just sufficient to meet basic requirements, or they are set by stipulating a consumption bundle (incorporating both food and non-food items) deemed to be adequate for basic consumption needs, and then estimating the cost of the consumption bundle for each of the subgroups being compared in the poverty profile.

Method of Computation The proportion of the population that lives below the poverty line is calculated using either consumption or income data, gathered from nationally representative household surveys. Whenever available, consumption data are preferred to income data for measuring poverty, because income is more difficult to measure accurately and can vary over time even if the standard of living does not.

Consumption, including consumption from own production (or income when consumption is unavailable), is calculated for the entire household and then divided by the number of persons living in the household to derive a per capita measure.

The sample distributions of poor people are weighted by household size and sample expansion factors so that they are representative of the population of each country. This generates an estimate of the number of people living in households with levels of per capita consumption or income below the poverty line. The total number below the poverty line is divided by the total population to estimate the proportion of the population that is poor. This number is multiplied by 100 to derive a percentage.

The formula for calculating the proportion of the population living below the national poverty line, also known as the headcount index, is as follows:


where P0 is the headcount index, I(.) is an indicator function that takes on the value 1 if the bracketed expression is true, and 0 otherwise. If individual consumption or income (yi) is less than the poverty line (z), then I(.) is equal to 1 and the individual is counted as poor. Np is the number of poor and N is the total population.

Poverty lines can be determined based on different methods. Some of these methods are based on objective information and define poverty lines in terms of absolute standards of minimum material capabilities (such as food-energy intake or cost of basic needs). Other methods consider subjective information on perceptions of welfare. In practice, the use of subjective methods to determine poverty lines has been more evident in developed countries. In some cases, national poverty lines may be set at a specific quintile level or as a proportion of average income or consumption.


National poverty lines reflect local perceptions of the level of consumption or income needed to avoid poverty. The perceived boundary between poor and not poor rises as the average income of a country rises, so national poverty lines do not provide a uniform measure for comparing poverty rates across countries. Nevertheless, national poverty estimates are clearly the appropriate measure for setting national policies for poverty reduction and for monitoring their results. International poverty measurements, on the other hand, provide a uniform standard for comparing poverty rates and the number of people living in poverty across countries.

National poverty rates may range from 0 (no population living below the national poverty line) to 100 (the entire population of a country living below the national poverty line).


Data on household income, consumption and expenditure, including income in kind, are generally collected through household budget surveys or other surveys covering income and expenditure. Household budget or income surveys are undertaken at different intervals in different countries. In developing countries they typically take place every three to five years.

To be useful for poverty estimates, surveys must be nationally representative. They must also include enough information to compute a comprehensive estimate of total household consumption or income (including consumption or income from own production) and to construct a correctly weighted distribution of consumption or income per person. Despite these quality standards, there are numerous potential problems associated with household survey data.

First, consumption is measured by using household surveys questions on food and nonfood expenditures as well as food consumed from the household’s own production, which is particularly important in the poorest developing countries. This information is collected either through recall questions using lists of consumption items or through diaries in which respondents record all expenditures on a daily basis. However, difficulties emerge because these methods do not always provide equivalent information, and depending on the approach used, consumption can be underestimated or overestimated. Different surveys use different recall or reference periods. Depending on the flow of expenditures, the rate of spending reported is sensitive to the length of the reporting period. The longer the reference period, the more likely respondents are to fail to recall certain expenses—especially food items—thus resulting in an underestimation of true expenditure.

Secondly, best-practice surveys administer detailed lists of specific consumption items. These individual items collected through the questionnaires are then aggregated afterwards. But many surveys use questionnaires in which respondents are asked to report expenditures for broad categories of goods. In other words, specific consumption items are implicitly aggregated by virtue of the questionnaire design. This shortens the interview, reducing the cost of the survey. A shorter questionnaire is also thought to reduce the likelihood of fatigue for both respondents and interviewers, which can lead to reporting errors. However, there is also evidence that less detailed coverage of specific items in the questionnaire can lead to underestimation of actual household consumption. The reuse of questionnaires may result in the omission of new consumption goods, leading to further underreporting.

Thirdly, some sampled households do not participate in surveys because they refuse to do so or because nobody is at home. This is often referred to as “unit non-response” and is distinct from “item non-response,” which occurs when some of the sampled respondents participate but refuse to answer certain questions, such as those pertaining to consumption or income. To the extent that survey non-response is random, there is no concern regarding biases in survey-based inferences; the sample will still be representative of the population. However, households with different incomes are not equally likely to respond. Relatively rich households may be less likely to participate because of the high opportunity cost of their time or because of concerns about intrusion in their affairs. It is conceivable that the poorest can likewise be underrepresented; some are homeless and hard to reach in standard household survey designs, and some may be physically or socially isolated and thus less easily interviewed. If non-response systematically increases with income, surveys will tend to overestimate poverty. But if compliance tends to be lower for both the very poor and the very rich, there will be potentially offsetting effects on the measured incidence of poverty.


It is sometimes possible to disaggregate this indicator by urban-rural location. In some cases, the national poverty line may be adjusted for different areas (such as urban and rural) within the country to account for distinct economic and social circumstances and differences in prices or the availability of goods and services. Typically the urban poverty line is set higher than the rural poverty line, reflecting the relatively higher costs of living in urban areas. In such cases, a clear definition of urban and rural areas needs to be established and included in the metadata.

Gender disaggregation of the indicator would also be very useful. Unfortunately, when computation is based on household income or consumption, this is not possible. To measure sex-disaggregated poverty rates, consumption or income of individuals, rather than that of households, needs to be recorded and analyzed. Alternatives to determine sex disaggregated measures include calculating poverty rates of household members according to the household head’s gender, measuring the age and gender composition of households at or below the poverty line, or measuring outcomes of welfare indicators other than consumption or income.


National poverty lines are used to make poverty estimates consistent with a country’s specific economic and social circumstances, and are not intended for international comparisons of poverty levels. National poverty lines tend to increase as the average level of income in a country increases.

Issues arise when comparing poverty measures within countries where urban and rural poverty lines represent different purchasing powers. For example, the cost of living is typically higher in urban than in rural areas. One reason is that food staples tend to be more expensive in urban areas, so the urban monetary poverty line should be higher than the rural poverty line. However, the difference between urban and rural poverty lines sometimes reflects more than the difference in the cost of living. In some countries the urban poverty line has a higher real value—meaning that it allows people to purchase more commodities for consumption—than does the rural poverty line. Sometimes the difference has been so large as to imply that the incidence of poverty is greater in urban than in rural areas, even though the reverse is found when adjustments are made only for differences in the cost of living. As with international comparisons, when the real value of the poverty line varies it is not clear how meaningful such urban-rural comparisons are.

Consumption is the preferred welfare indicator for measuring poverty for a number of reasons. For one thing, income is generally more difficult to measure accurately and can vary over time even if the standard of living does not. For example, the poor who work in the informal sector may not receive or report monetary wages; self-employed workers often experience irregular income flows; and many people in rural areas depend on idiosyncratic, agricultural incomes. Moreover, consumption accords better with the idea of the standard of living than income, which can vary over time even if the actual standard of living does not. Thus, whenever possible, consumption-based welfare indicators are used to estimate the poverty measures reported here. But consumption data are not always available; for instance, in Latin America and the Caribbean the vast majority of countries primarily collect income data. In such cases there is little choice but to use income data.

Even if survey data were entirely accurate and comprehensive, the measure of poverty obtained could still fail to capture important aspects of individual welfare. For example, using household consumption measures ignores potential inequalities within households. Thus, consumption- or income-based poverty measures are informative but should not be interpreted as a sufficient statistic for assessing the quality of people’s lives. The national poverty rate, a “headcount” measure, is one of the most commonly calculated measures of poverty. Yet it does not capture income inequality among the poor or the depth of poverty. For instance, it fails to account for the fact that some people may be living just below the poverty line, while others experience far greater shortfalls (see also Indicator 1.2).

Policymakers seeking to make the largest possible impact on the headcount measure might be tempted to direct their poverty alleviation resources to those closest to the poverty line (and therefore least poor).

Lastly, this income/consumption based poverty indicator does not fully reflect the other dimensions of poverty such as inequality, vulnerability, and the lack of voice and power of the poor.


In many settings, households headed by women tend to have lower incomes and members of those households are therefore more likely to live below the poverty line. However, this relationship should be examined taking into account national circumstances and the definition of head of household adopted in data collection, which is not always defined as the chief source of economic support. Gender relations, including whether households are headed by women or men, may also affect intra-household resource allocation and use.


In principle, poverty indicators derived using national poverty lines are intended to reflect a specific country’s economic and social circumstances and the data are not adjusted for international comparability. Therefore regional or global data based on national poverty figures are not produced. The World Bank publishes data on the proportion of the population living below the national poverty line for developing countries in its World Development Indicators (WDI) Online database.


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