1.6 Proportion of employed people living below $1 (PPP) per day

Modified on 2012/10/20 06:50 by ILO Employment — Categorized as: Goal 1



Goal 1. Eradicate extreme poverty and hunger. Target 1.B Achieve full and productive employment and decent work for all, including women and young people.


The proportion of employed people living below the poverty line, or the working poor, is calculated as the proportion of individuals who are employed, but nonetheless live in a household whose members are estimated to be living below the poverty line. Either the national poverty line or the international poverty line of $1.25 purchasing power parity (PPP) per day may be used as threshold.

This indicator is expressed as a percentage of total employment.

Working poor refers to employed persons living below the poverty line.

The poverty line is the minimum level of income deemed necessary to achieve an adequate standard of living in a given country. National poverty lines are thresholds defined at the country level, below which a person is deemed to be poor (see Indicator 1.1a) For international comparisons, a poverty line of $1.25 a day measured at 2005 international prices and adjusted for PPP is used (see “DEFINITION AND METHOD OF COMPUTATION” for Indicator 1.1).

The purchasing power parity (PPP) conversion factor is the number of units of a country's currency required to buy the same amounts of goods and services in the domestic market as one United States dollar would buy in the United States.

Employed refers to persons above the nationally defined working age (different in every country, but generally close to 15 years) who worked or held a job during a specified reference period. Included are persons who worked for pay or profit (or pay in kind); persons who were temporarily absent from a job for such reasons as illness, maternity or parental leave, holiday, training or industrial dispute; and unpaid family workers who worked for at least one hour, although many countries use a higher hour limit in their definition. The measure of employment is intended to capture persons working in both the formal and informal sectors.

Method of computation

The number of working poor is calculated on the basis of cross-tabulations from household survey data sets that include variables on both poverty status and labour force characteristics. An individual is classified as working poor if he or she is 1) employed and 2) living in a household with per-capita consumption or income that is below the poverty line.

The working poverty rate is the proportion of working poor in total employment: Working poverty rate = number of employed persons living in a household with per-capita consumption or income below the poverty line / total employment * 100.


The proportion of working poor in total employment gives an indication of the lack of decent work in a country. Jobs that do not provide incomes high enough to lift individuals and their families out of poverty, at the very least, do not fulfil the income component of the definition of decent work. Within the development process, the share of working poor should decrease, and in turn, further foster development.

The working poor definition combines poverty data with countries’ specific labour market characteristics, such as the size of the labour force. Working poor estimates thereby provide a picture of the relationship between poverty and employment that is not depicted by standard poverty data.


To estimate the number and proportion of the working poor, it is necessary to establish the poverty line. National poverty lines are defined differently across countries based on different calculation methods (see Indicator 1.1a).

Data on the labour market (labour force and total employment) are obtained from population censuses, labour force or other household surveys, establishment surveys, administrative records and official estimates based on results from several of these sources. Labour force surveys can be designed to cover virtually the entire population of a country, all branches of economic activity, all sectors of the economy, and all categories of workers, including own-account workers, unpaid family workers and persons engaged in casual work or marginal economic activity. For this reason, household-based labour force surveys offer a unique advantage in obtaining information on the labour market of a country and its structure.

However, labour force and household surveys may have limited geographical and population coverage. The ideal geographic coverage is the entire country (no geographic exclusions) and the entire population (with no exclusion of population groups).

Other sources such as population censuses and administrative records differ in scope, coverage, units of measurement and methods of data collection. Each source has advantages and limitations in terms of the cost, quality and type of information gained.

The best method for calculating the number of working poor is on the basis of cross-tabulations from micro survey data sets that include variables on both poverty status and labour force characteristics. However, these data are usually not available.


While it might be desirable to disaggregate the proportion of working poor by sex or age groups, disaggregation is frequently not feasible for the main reason that it is difficult to produce disaggregated poverty data. However, if estimates are derived from survey micro datasets, disaggregation is sometimes feasible.


If the methodology used for the surveys from which poverty data are derived changes over time, it is extremely difficult to make useful temporal comparisons. However, if the same poverty line is used consistently over time and the same survey methodology has been used for collecting income and expenditure data, it should be possible to make valid temporal comparisons. Even if these conditions are met, however, poverty rates may vary quite substantially from year to year because of economic or weather conditions. For example, natural disasters or financial crises can have a major effect on poverty rates, at least in the short term.

This indicator is also limited because of the way in which non-market production and consumption are valued. In some countries these activities may represent an important part of income and consumption, and decisions must be made about the value to attach to these items. The attached value will have an important effect on poverty rates.


If disaggregation by sex is feasible in view of data availability, the indicator can be used to analyse gender differentials in the incidence of working poverty.


The International Labour Organization (ILO) produces estimates for this indicator. Estimates of the working poor are based on labour market input data (working-age population, labour force and employment) from econometric models that utilize available national data and apply multivariate regression techniques to impute missing values at the country level. The first step in each model is to assemble all available data for each indicator in question. It is important to note that only data that are national in coverage and comparable across countries and over time are used as inputs. This selection criterion is fundamental because models are designed to use the relationship between labour market indicators and their macroeconomic correlates—such as per-capita gross domestic product (GDP), GDP growth rates, demographic trends, country membership in the Highly Indebted Poor Country Initiative, geographic indicators and country and time dummy variables. Comparability of the labour market data used as inputs in the imputation models is essential to ensure that the models accurately capture the relationships between the labour market indicators and the macroeconomic variables.

For the calculation of the number of working poor, ILO uses poverty data from the World Bank based on the international poverty line of $1.25 a day. Because country-level estimates are model-driven and produced so that harmonized data are provided for every country and every year, there may be discrepancies between international and national data.


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See “REFERENCES” for Indicator 1.1 and Indicator 1.4.