Earnings and labour cost
Earnings and labour cost are two distinct but complementary concepts. They differ in their nature and primary objectives. 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 indicators complement each other because they reflect the two main facets of existing employment-related income measures: one aiming to measure the income of employees, the other showing the costs incurred by employers for employing them.
ILOSTAT presents information from national sources on various indicators pertaining to earnings. It 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. ILOSTAT also contains information from national sources on hourly labour cost per employee, disaggregated by economic activity. In addition, harmonized series of earnings and labour cost are available, with local currency units converted to a common currency. Lastly, ILOSTAT includes an indicator on the labour income share in Gross Domestic Product (GDP).
The manual's main purpose is to help national labour statisticians engaged in or proposing to start the compilation of statistics of wages and hours of work.
Concepts and definitions
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.
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.
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.
Labour cost is the cost incurred by the employer in the employment of labour in a specified reference period. The statistical concept of labour cost comprises remuneration for work performed, payments in respect of time paid for but not worked, bonuses and gratuities, the cost of food, drink and other payments in kind, cost of workers’ housing borne by employers, employers’ social security expenditures, cost to the employer for vocational training, welfare services and miscellaneous items, such as transport of workers, work clothes and recruitment, together with taxes regarded as labour cost.
Labour cost and compensation of employees are closely related concepts, with many common elements. In some cases, where data on labour cost are not available, ILOSTAT presents data on the compensation of employees, a concept defined in the United Nations System of National Accounts as the total remuneration, in cash or in kind, payable by an enterprise to an employee in return for work done by the latter during the accounting period. The compensation of employees has two main components: a) wages and salaries payable in cash or in kind and b) social insurance contributions payable by employers, which include contributions to social security schemes; actual social contributions to other employment-related social insurance schemes and imputed social contributions to other employment-related social insurance schemes. This concept views compensation of employees as a cost to employer, thus compensation equals zero for unpaid work undertaken voluntarily. However, it does not include taxes payable by employers on the wage and salary bill, such as payroll tax.
The harmonized series on average hourly labour cost present only average hourly labour cost, with similar conversions to those of hourly earnings for the time unit and currency.
Labour income share
The labour income share in GDP is the compensation of total employment, on account of labour input provided to production, given as a percentage of GDP. Total employment is comprised of employees and the self-employed. GDP represents the market value of all final goods and services produced during a specific time period (defined as a year for the purposes of this indicator) in a country’s territory. By construction GDP is equivalent to the overall income earned in a country’s territory. Hence the labour income share in GDP describes the share of overall income that accrues to labour.
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.
The preferred sources of information on labour cost are establishment and labour cost surveys, but in their absence, administrative data can be used.
The primary source for unadjusted labour income share in GDP is national accounts, which provide information on compensation of employees. Adjusted labour income share estimates, which account for the labour income of the self-employed, are produced on the basis of national accounts and household survey microdata.
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.
Information on hourly compensation costs, like total labour cost, is valuable for many purposes. The level and structure of the cost of employing labour and the way costs change over time can play a central role in every country, not only for wage negotiations but also for defining, implementing and assessing employment, wage and other social and fiscal policies that target the distribution and redistribution of income. At both the national and international levels, labour costs are a crucial factor in the abilities of enterprises and countries to compete. When specific to the manufacturing sector, labour costs serve as an indicator of competitiveness of manufactured goods in world trade. This is why governments and the social partners, as well as researchers and national and international institutions, are interested in labour cost information that can be compared between countries and industries. Also, the measurement and analysis of non-wage labour costs have become an important issue in debates on labour market flexibility, employment policies, analyses of cost disparities, and comparisons of productivity levels among countries.
The labour income share in GDP provides information about the relative share of output which is paid as compensation to the employed in exchange for their work as compared with the share paid to capital in the production process for a given reference period. In order to interpret this indicator effectively, it is important to consider it together with economic growth trends. The share of labour compensation in output can highlight the extent to which economic growth translates into higher incomes for workers over time. In periods of economic recession, the labour income share provides an indication of the extent to which falling output reduces labour incomes relative to profits. If labour incomes fall at a greater rate than profits the labour income share will be expected to fall. By contrast, if there is a sharper decline in profits than in labour incomes, as it is often observed, the labour income share will rise. For any given level of GDP and profits, the labour income share can fall as a result of falling employment, falling wages or a combination of both. Increased production and GDP often lead to improved living standards of individuals in the economy, but this will depend on the distribution of income and public policy among other factors. If there is a large number of non-resident border or seasonal workers or inflows and outflows of property income such that the value of production differs from the income of residents, there may be a situation of over or understating the living standards of residents.
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.
Regarding labour cost statistics, care should be taken not to interpret hourly compensation costs as the equivalent of the purchasing power of worker incomes, for two reasons. The first relates to the components and nature of labour costs. In addition to the payments made directly to workers, labour cost also includes other costs borne by the employer. The second reason for differentiating hourly labour costs from the concept of workers’ purchasing power lies in the fact that the prices of goods and services vary greatly among countries, and the commercial exchange rates used to convert national figures into a single currency do not indicate relative differences in prices.
As for the unadjusted labour income share in GDP, it will underestimate the proportion of GDP accrued to total employment on account of the provided labour input, as it covers only the compensation of employees and does not include the labour income of the self-employed. Thus the indicator may be less relevant in countries where a large proportion of employment is in self-employment, a common situation in developing countries. Hence the unadjusted labour income share is not well suited for international comparisons. Nonetheless, an adjusted labour share may be estimated to take into account the labour income of self-employed workers, hence improving its international comparability. Limitations also arise from the denominator of the measure. GDP may exclude or under-report activities that are difficult to measure, such as transactions in the informal sector or in illegal markets, thus understating actual production. Moreover, GDP does not account for certain social and environmental costs of production, and therefore is not a direct measure of the level of overall well-being.