Indicator description: Earnings


Earnings are important from the workers’ point of view and represent a measure of their purchasing power and an approximation of their standard of living, while labour cost provides an estimate of employers’ expenditure toward the employment of its workforce. The indicator complement labour cost because they reflect the two main facets of existing employment-related income measures: earnings aims to measure the income of employees, while labour costs show the costs incurred by employers for employing them.

ILOSTAT features statistics on the minimum monthly wage, the average monthly and average hourly earnings of employees, employees earning low pay and the gender wage gap. For users interested in more detailed statistics, ILOSTAT includes the indicator on earnings disaggregated by sex, economic activity and occupation. Whenever possible, only harmonized series of earnings are available, with local currency units converted to a common currency. ILOSTAT also includes closely related statistics: harmonized series on labour cost and ILO modelled estimates on labour income share. 

Concepts and definitions

Minimum wage

Statistics on the minimum wage presented refer, to the extent possible, to the statutory nominal gross monthly minimum wage, effective December 31st of each year. The scope and coverage of statutory minimum wages vary from country to country. In countries where there are regional minimum wages, ILOSTAT includes the minimum wage in place in the capital city (or region), the largest city (or region), or an average of the largest cities (or regions) in order to capture the minimum wage which affects the largest percentage of employees. In countries with sectoral or occupational minimum wages, ILOSTAT presents the minimum wage in place for the sector or occupation which has the greatest employment coverage (if known).


The concept of earnings, as applied in wages statistics, relates to gross remuneration in cash and in kind paid to employees, as a rule at regular intervals, for time worked or work done together with remuneration for time not worked, such as annual vacation, or other type of paid leave or holidays. Earnings exclude employers’ contributions in respect of their employees paid to social security and pension schemes and also the benefits received by employees under these schemes. Earnings also exclude severance and termination pay. Statistics of earnings presented in ILOSTAT refer, to the extent possible, to employees’ gross remuneration, i.e. the total before any deductions are made by the employer in respect of taxes, contributions of employees to social security and pension schemes, life insurance premiums, union dues and other obligations of employees. Earnings include direct wages and salaries, remuneration for time not worked (excluding severance and termination pay), bonuses and gratuities and housing and family allowances paid by the employer directly to the employee.

Unlike the information presented as reported from national sources, the harmonized series on average monthly earnings and monthly minimum wages include only average monthly earnings and monthly minimum wages, respectively, with the following conversions applied:

  • Hourly earnings are multiplied by actual weekly hours worked, if available, for each gender for monthly earnings and for both sexes for monthly minimum wages, and then multiplied by 4.33 weeks
  • Daily earnings are multiplied by 5 days and 4.33 weeks
  • Weekly earnings are multiplied by 4.33 weeks
  • Annual earnings are divided by 12 months

Similarly, the harmonized series on average hourly earnings present only average hourly earnings, with the following conversions applied:

  • Weekly earnings are divided by actual weekly hours worked for each gender, if available
  • Monthly earnings are divided by 4.33 weeks and then by actual weekly hours worked for each gender, if available
  • Annual earnings are divided by 52 weeks and then by actual weekly hours worked for each gender, if available

In addition to converting the figures to a consistent time unit, the harmonized series present data converted to a common currency. Local currency units are converted to US dollars using market exchange rates and also using 2011 purchasing power parities (PPPs).  PPPs are the rates of currency conversion that equalize the purchasing power of different currencies by eliminating the differences in price levels between countries.

In cases where ILO experts process the household survey microdata in order to produce the indicators published on ILOSTAT, international statistical standards are strictly applied to ensure comparability across countries. Thus, ILOSTAT data may differ from what is nationally reported. The magnitude of the differences depends on the extent to which a country is applying international statistical standards. 

Gender wage gap

The gender wage gap is calculated as the difference between average hourly earnings of men and average hourly earnings of women expressed as a percentage of average hourly earnings of men. This indicator is not adjusted according to individual characteristics that may explain part of the earnings difference.

Low pay

The low pay rate is an indicator of earnings distribution and refers to the number of employees whose hourly earnings at all jobs were less than two-thirds of the median hourly earnings, calculated as a percentage. There is no international definition for low pay. The female share of low pay earners is the number of females earning low pay divided by the total number of employees earning low pay, calculated as a percentage. This differs from the low pay rate for women which refers to the number of female employees earning low pay as a percentage of all female employees.

Recommended sources

The most common source for earnings data are labour-related establishment surveys. They collect data at the source, namely from establishments that employ workers. Since establishments usually keep accurate records of all wages paid for their own bookkeeping and for tax purposes, this approach has the advantage of producing reliable earnings data without having to rely on the re-call of individual employees. However, in countries where enterprises routinely pay wages outside their normal bookkeeping (so-called “envelope wages”) in order to avoid taxes and social security contributions, the establishment-based approach has limitations.

Household surveys, the second major source for earnings data, have the advantage that they cover all employees regardless of where they work. Earnings data from household surveys usually cover the public and private sector, formal and informal enterprises and all industrial sectors. There are, however, a number of methodological differences that can affect comparability between countries of earnings levels based on household surveys. Also, the reliability of earnings statistics from household surveys depends heavily on the accuracy of the respondent.

A few countries rely on administrative data sources such as social security records to compile earnings data, or combine several different primary sources to produce a synthetic earnings series. In some countries the national accounts sections of central statistical offices produce the wage series that match the desired concept most closely. However, national accounts are only a useful source for data on average wages when compensation of employees is disaggregated into its two major components – wages and salaries and employers’ social contributions – and when matching data on total wage employment exist.

Interpretation and use of the indicator

The real earnings in an economic activity are a major indicator of employees’ purchasing power and a proxy for their level of income, independent of the actual work performed in that activity. Real earnings trends are therefore useful indicators, both within countries and across them. Significant differences in the purchasing power of earnings, over time and between countries, reflect the modern world economy, and comparisons of the movement of real earnings can provide a measure of the material progress (or regression) of the working population. Real average earnings are therefore an important indicator for monitoring changes in working conditions. And they should be reviewed in conjunction with trends in working poverty and the low pay incidence. Real earnings are obtained adjusting nominal earnings for inflation.

Trends in nominal earnings and low pay can be used to inform adjustments in minimum wages, the lowest remuneration that employers may legally pay to workers under national law.1Note that minimum wages are set in nominal terms, so nominal average wages are the primary comparator. For a review of minimum wage legislation, see ILO: “Working Conditions Laws Report 2010” (Geneva, 2010). While there is no single, recommended ratio between minimum wages and average wages, information on average wages can inform policy-makers when setting minimum wages and enable them to monitor whether those at the bottom of the distribution fall behind general wage increases.2See Chapter 5.2 of ILO: Global Wage Report 2010/11: Wage policies in times of crisis (Geneva, 2010).

Social partners – workers’ and employers’ organizations – rely on wage data for collective bargaining. A fundamental concern of employees and trade unions is to protect the purchasing power of earnings, particularly in periods of high inflation, by raising nominal wages in line with changes in consumer prices. Real wage increases become feasible without putting the sustainability of enterprises into jeopardy when labour productivity is growing. When used together with other economic variables such as employment, production, and income and consumption, trends in average real wages are valuable indicators for the analysis of overall macroeconomic trends, as well as in economic planning and forecasting. Importantly, they can indicate the extent to which economic growth and rising labour productivity translates into income gains for workers. 

The gender wage gap measures the extent to which the wages of men differ from those of women and therefore directly addresses the target of “equal pay for work of equal value”. When the gender pay gap equals “0”, it denotes equality of earnings. Positive values reflect the extent to which women’s earnings fall short of those received by men, where a value closer to “100” denotes more inequality than a value closer to “0”. Negative values reflect the extent to which women’s earnings are higher than men’s.


Country-specific practices differ with respect to the sources and methods used for earnings data collection and compilation, which in turn have an influence on the results and comparability across countries. The main sources of information (establishment censuses and surveys, and household surveys) usually differ in terms of objectives, scope, collection and measurement methods, survey methodology and so on. The scope of the information may vary in terms of geographical coverage, workers’ coverage (for example, exclusion of part-time workers) and establishment and enterprise coverage (based on establishment size or sector covered). While most countries include firms regardless of size into establishment surveys, some countries exclude small firms with fewer than five or ten employees. Some countries also limit the coverage to the private sector (i.e. exclude the public sector) or to specific industries within the private sector (such as manufacturing). If small enterprises pay lower wages than large enterprises or wages differ between the public and the private sector, these exclusions will affect the level of the collected wage data – depending on how large the differences are, and how many employees are excluded from the coverage. However, if wages in the excluded establishment move roughly in line with those enterprises for which data are available, these exclusions will only have a marginal effect on trends over time. Even data with less than full coverage can therefore be a useful proxy to analyse wage growth in an economy.

Establishment surveys usually draw their sample from an establishment register that is maintained either by the central statistical office or another institution, such as the Registrar of Companies. In developing countries with a large informal sector, this is a serious limitation since many small, unregistered establishments are missing from the sample frame. Also excluded are individual households employing paid domestic workers, which account for a significant proportion of total paid employment in some developing regions. In some developing countries, establishment surveys therefore capture only a small proportion of all wage employees (those in the public sector and those in large, modern enterprises). Under these circumstances, collecting information from the recipients of wages can be the better alternative.

Household surveys encompass a greater range of jobs and workers than establishment surveys, however they tend to experience problems associated with self-reporting of earnings. Furthermore, methodological differences across different household surveys can affect comparability. For instance, some surveys collect data on the usual monthly wages while others ask for the actual wage received in the past month. At times it is also not clear whether respondents are asked to report their gross or net wages (i.e. before or after deduction of taxes and compulsory social security contributions). These differences can have a material effect on the reported level of wages, while they are less likely to have a major impact on trends over time as long as the survey instrument remains unchanged.

Even when using the same concept of earnings, there are likely to be differences with regard to the inclusion or exclusion of various components (such as periodic bonuses and allowances, or payments in kind). Earnings statistics show fluctuations that reflect the influence of both changes in wage rates and supplementary payments. In addition, daily, weekly and monthly earnings are dependent on variations in hours of work (in particular, hours of paid overtime or short-time working), while hourly earnings are influenced by the concept of hours of work – hours actually worked, hours paid for, or normal hours of work – used in the computation.

Since the gender wage gap is calculated for paid employees only, it does not cover large numbers of own-account workers or employers, especially in the informal sector where income differences between men and women may be larger. It also does not capture income differences between the sexes that result from uneven access to paid employment. For instance, when men are over-represented among paid employees (with relatively high incomes) and women are over-represented among the self-employed in the informal sector (with relatively low incomes), the overall gap in incomes may be greater than what can be captured by the gender wage gap.

For the low pay rate, the varying coverage of employees counted significantly affects comparability. For example, data may refer to full-time employees or all employees (full-time and part-time employees). In general, employees working part-time are more likely to be low paid than those working full-time. The prevalence of part-time work within countries and the incidence of low pay among part-time workers relative to the share of low paid full-time employees, can affect the estimated incidence of low pay.

Table of contents

Statistical standards
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