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GB.276/ESP/2
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Committee on Employment and Social Policy |
ESP |
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SECOND ITEM ON THE AGENDA
Key Indicators of the Labour Market (KILM)
Contents
I. Background to the KILM project
1. The need for labour market information
2. Organization and scope of data coverage
II. Eighteen ILO Key Indicators of the Labour Market
1. Participation in the world of work
3. Unemployment, underemployment and inactivity indicators
KILM 10. Long-term unemployment
KILM 11. Unemployment by educational attainment
4. Educational attainment and illiteracy
IV. Plans for the future of KILM
1. In 1996, the International Labour Conference requested the ILO to develop and disseminate an expanded range of up-to-date and relevant labour market indicators. The ILO's Employment and Training Department, in collaboration with the ILO's Bureau of Statistics, was charged with responsibility for the project, now known as the ILO Key Indicators of the Labour Market (KILM) project. The KILM project was designed with two objectives: (a) to develop a set of labour market indicators, and (b) to widen the availability of the indicators to monitor new employment trends.
2. In 1997, after consultation with the Organisation for Economic Development and Co-operation (OECD), the Statistical Office of the European Union (EUROSTAT) and several national statistical offices, the ILO completed the selection of the initial set of indicators for the KILM. These indicators were chosen based on three criteria: conceptual relevance, data availability, and comparability across countries and regions. The resulting set of 18 indicators was designed to satisfy the ever-increasing demands of governments and the social partners for timely, accurate and accessible information on the world's labour markets.(1)
3. This paper is in four parts:
- The first gives a description of the scope and organization of the Key Indicators of the Labour Market and provides an explanation of how and from where the information was assembled.
- The second section explains each labour market indicator in greater detail -- what variable is measured and how.
- The third section describes how KILM highlights gender issues.
- The fourth section outlines the future direction of the KILM project. The KILM is a "living data set" which should evolve to wider country coverage of current indicators, introduce additional labour market indicators and improve functionality and ease of use, all in response to the fluid demand for information from ILO constituents and researchers interested in labour markets. The appendix shows the availability of indicators for the world, with a count of the number of countries for which data exist for each indicator.
I. Background to the KILM project
1. The need for labour market information
4. As economies and societies become more interdependent, the need to enhance our understanding of the world of work becomes increasingly important. Timely and focused information on the world's labour markets is essential to answer such questions as:
- What types of economic activity are people engaged in?
- What is the size and composition of the labour force?
- How many hours do people work and how much do they earn for this work?
- How many people are without work and looking for work?
- What types of employment inequalities exist?
- How are women faring in the labour market?
- What are the specific employment problems faced by young people?
5. Answering these questions requires detailed analysis of a large volume of statistics. At the national level, statistical information is generally gathered and analysed by statistical services and ministries. At the global level, the ILO plays a vital role in assembling labour market information and disseminating it to the world community. In this tradition, the KILM complements the perennial ILO Yearbook of Labour Statistics, which will continue to be published. There are, however, significant differences between the two publications. While the Yearbook relies on national sources, the KILM is able to harvest information from national statistical services as well as from outside sources, including international data repositories, and can thus cover a broader range of countries and offer indicators that had yet to be explored by the ILO.
6. KILM opens up vast new opportunities for policy-centred research both inside and outside the ILO, and should thus offer ample opportunities for networking. Consultation with research foundations and other international agencies in the area of labour market collection and dissemination have already begun. The KILM team expects to see increasing demand for its participation in discussions among the research community on the issues relating to labour market information.
2. Organization and scope of data coverage
7. Based on the latest information available, there are approximately 240 countries, areas and territories.(2) The Statistics Division of the United Nations compiles statistics for slightly more than 230.(3) The ILO has made an intensive effort to assemble the indicators for as many countries, areas and territories as possible. However, not all countries(4) were in a position to provide information for every indicator. For example, the employment by sector indicator (KILM 4) contains information for almost 200 countries, while the hourly compensation cost indicator (KILM 16) currently contains information for only 29 countries (see appendix). On average, the scope of coverage per indicator is 100 countries. Such breadth of coverage and subject-matter makes KILM unsurpassed in the realm of labour market indicators put forth by the international community.
8. For the purpose of the 1999 issue of KILM, countries have been organized into six major groupings, based on a combination of development and geography.(5) There are two developmental groupings -- developed (industrialized) countries and transition economies -- and four geographic groupings: Asia and the Pacific, Latin America and the Caribbean, sub-Saharan Africa, and the Middle East and North Africa.(6) Each country appears in only one major grouping; for example, Japan is included in the developed (industrialized) countries grouping and is therefore excluded from Asia and the Pacific.
9. KILM collects and disseminates information for the years 1980, 1990 and all available subsequent years. Thus, the emphasis is on current labour market developments, while presenting a recent historical perspective. While statistics are available for the additional years in the 1980s in the KILM CD-ROM (on sale with the publication or separately), these years are excluded from the publication. As the various statistical services require time to collect, process and disseminate the information, the latest data shown in the publication are for 1997, with few exceptions.
10. The information for the indicators is presented in tables by country. If information for a given country and/or year were unavailable at the time of production, that country and/or year is excluded from the table. With few exceptions, the data elements are expressed as ratios or percentage changes (for example, labour force participation rates, percentages of employment by sector, proportions of part-time to total employment, unemployment rates, inactivity rates, and changes in manufacturing wages).
11. In order to meet the needs of users, the ILO is making the KILM information available in a variety of formats. The two main KILM products are the publication and the CD-ROM, available separately or together. The CD-ROM version of KILM contains the data sets for the indicators and interactive software that enables users to select the indicators by country, year and type of source and to choose user-defined functions that correspond to their specific research needs. It duplicates the bound publication, while adding features unavailable in printed form. For example, for the long-term unemployed measures of KILM 12, CD-ROM users may choose to view the numerator (number of persons unemployed one year and longer) or the denominators (the labour force and the population) for a particular year or series of years, for any number of countries. Such input data are not included in the printed KILM data sets, which generally show only the specific indicators. The CD-ROM software also allows users to export data in formats suitable for use with other software packages.
12. To accompany the CD-ROM, the ILO has produced the Key Indicators of the Labour Market -- 1999 Country Profiles. For each country with available data, data are shown for each KILM, as well as various background indicators -- population, GDP, education, human development, etc. -- for two years, 1990 (or the maximum year of data availability between 1985 and 1990) and the latest year of data availability between 1991 and the present.
13. An additional KILM product is the new Internet site. Up-to-date information about the KILM project can be found on the site. It should serve as a useful reference tool for obtaining brief summaries of the definitions of indicators and the availability of information. Updates and amendments to the data tables will also be posted on the website for downloading by users who have purchased the CD-ROM.
4. Data providers and primary data documentation
14. Unlike similar efforts to assemble international indicators on the labour market, KILM concentrated on pulling together information directly from international data repositories. In other words, KILM does not directly use national sources, but rather takes advantage of existing compilations of data held by various international organizations, including the following:
- International Labour Office (headquarters and regional offices)
- United Nations Statistics Division
- Organisation for Economic Co-operation and Development (OECD)
- World Bank
- United Nations Industrial Development Organization (UNIDO)
- Statistical Office of the European Union (EUROSTAT)
- United Nations Educational, Scientific and Cultural Organization (UNESCO)
- United States Bureau of Labor Statistics (BLS)
15. Information maintained by these organizations was generally derived from questionnaires completed by national statistical sources and/or based on official national publications. In turn, the information was commonly drawn from the results of labour force and/or establishment surveys conducted by the various national statistical sources or compiled from administrative records.
16. Regional and national sources were sought directly only when information was unavailable from one of the repositories. The ILO regional offices and multidisciplinary advisory teams (MDTs) assisted by providing regional labour market data sets developed and maintained by regional staff. The regional offices and MDTs also actively participated in locating and analysing a variety of information from national and regional statistical sources. As KILM evolves as an information bank, the programme will strengthen its collaboration with the ILO regional offices in the hope of expanding the coverage of the current indicators, while gathering more timely data.
17. Whenever information is available from more than one data repository, KILM reviews the data and background documentation in order to select the data most suitable for inclusion. Factors used in making the appraisal include the general reliability of the sources providing the data, the availability of notes regarding such issues as scope of coverage, availability of gender and age statistics, and degree of historical coverage. Occasionally, two data repositories were chosen, and any resulting breaks in the historical series are duly noted.
5. International comparability
18. KILM statistics give users the ability to compare data for one country with similar data for another country; however, international comparisons are not a simple matter. There are caveats relating to the methodologies of measurement that require time and effort to sort out before reasonable comparisons can be made. Limitations to comparability are often indicator-specific, and there are standard issues that require attention with every indicator.
19. In order to minimize misinterpretation, care has been taken in developing detailed notes that identify the data repository, type of data source (household and labour force surveys, censuses, administrative records, and so on), and changes or deviations in coverage, such as age groups and geographical coverage (national, urban, rural, capital city, and so on).(7) When analysing or making reference to a particular indicator, users are advised to examine closely the text relating to the "limitations to comparability" sections and the notes to the data tables.
II. Eighteen ILO Key Indicators of the Labour Market
1. Participation in the world of work
KILM 1. Labour force participation rates
20. Labour force participation rates are a primary indicator of the level of labour market activity within a country. The labour force is defined in accordance with the standard adopted by the 13th International Conference of Labour Statisticians (ICLS).(8) The labour force participation rate is expressed as the ratio of the sum of the total employed and the unemployed to the population of working age. Trends and levels of participation in the labour force by age and sex can vary significantly, both within and across countries. The indicator, therefore, has been broken down by sex, as well as by selected age groups. The breakdowns by age were chosen so that analysis of the trends can also be prepared separately for youth, workers of prime labour market age (25 to 54 year-olds) and older workers.
21. The next six indicators -- one-third of the total -- are directly associated with employment. The indicators start with the employment-to-population ratio (KILM 2), include several of the important specifications of employment (KILM 3 to 6), and conclude with the "urban informal sector" (KILM 7), a category of employment that is not easy to measure or identify.
KILM 2. Employment-to-population ratio
22. This indicator measures total employment as a percentage of a country's working-age population, the group generally viewed as potentially available for work in the broadest sense. The employment-to-population ratio is one of three labour market measures in the United Nations Minimum National Social Data Set (MNSDS).(9) Employment ratios inform us of the extent to which the population is engaged in productive labour market activities. Although close in definition to the labour force participation rate (KILM 1), the employment-to-population ratio can show different trends, as it is more likely to be affected by changing economic conditions within a country.
23. Indicators of status in employment distinguish between three important and useful categories of the employed: (a) wage and salaried workers, (b) self-employed workers, and (c) contributing family workers, with each being expressed as a proportion of the total employed. Categorization by employment status is useful for understanding both the dynamics of the labour market and the level of development of economies. KILM 3 is strongly linked to the employment-by-sector indicator, KILM 4. The method of classifying employment by status is based on the 1958 and 1993 International Classification by Status of Employment (ICSE). The ICSE classifies jobs held by persons at a point in time with respect to the type of explicit or implicit employment contract the person has with other persons or organizations. Such status classifications reflect the degree of economic risk, an element of which is the strength of the attachment between the person and the job.(10)
24. This indicator disaggregates employment into three broad classifications -- agriculture, industry and services. As with KILM 3, employment in the three sectors are taken as percentages of total employment. The indicator shows job growth and decline on a broad sectoral scale, while highlighting differences in trends and levels between developed and developing countries. Sectoral employment flows are an important factor in analysis of productivity trends, because sources of within-sector productivity growth need to be separated from productivity growth that results from shifts from lower to higher productivity sectors. The addition of further industrial detail within the three sectors would be useful, in part owing to the interest of policy-makers in trends within the public sector. It is hoped to undertake this for subsequent issues of KILM. The branches of economic activity are defined in terms of the International Standard Industrial Classification (ISIC) of All Economic Activities, Revision 2, released in 1968, and Revision 3 released in 1989.
25. The incidence of part-time work has grown substantially over the past two decades in many countries. This is occurring as part of the movement of women into the labour force and is also a function of the need to provide jobs for younger and older workers (who are unable or unwilling to work full time). Currently, there is no defined dividing line for full- and part-time work recognized by the ILO, and thus dividing lines are determined exclusively at the country level. The OECD has carried out extensive research to harmonize this indicator for its member countries, utilizing a 30-hour cut-off. The OECD estimates are a major data source for this indicator, and the 30-hour cut-off is therefore used for displaying the proportion of part-time to total employment in the table for OECD member countries.(11) When the data are presented based on alternative (country) dividing lines, the number of hours is provided in the table notes.
26. KILM includes three measures related to hours of work. The first measure concerns the number of persons working a "marginal" number of weekly hours (less than ten); the second refers to those working "excessive" hours, that is, more than the "normal" work-week; and the third is an estimate of the total annual hours worked per person. The first two measures are intended to provide information to users who wish to assess the employment experience more extensively, that is, beyond the very broad ILO definition of total employment.(12) The "total annual hours of work" measure accounts for the hours actually worked by the employed population throughout the course of a full year; it excludes time off during the year for holidays, sick leave, lay-offs, seasonal work, and so on.
KILM 7. Urban informal sector employment
27. Urban informal sector employment is an indicator relating the estimated number of persons employed in the informal sector in urban areas to the total number of employed persons in the same areas. In terms of size and growth, the informal sector is an important part of economic, social and political life in most developing, as well as some industrialized, countries. In countries with high rates of population growth and/or urbanization, the informal sector tends to absorb most of the growing labour force in the urban areas. The indicator represents an attempt to capture labour market situations that are inadequate but not covered by other indicators, such as the unemployment rate (KILM 8) and time-related underemployment (KILM 12).
28. The 15th ICLS defined the informal sector as economic units of production within unincorporated enterprises owned by households.(13) Accordingly, those employed in the informal sector comprise all persons who, during a given reference period, were employed in at least one production unit that meets these informal sector guidelines, irrespective of their status in employment and whether it was their main or a secondary job. The ICLS resolution provides allowances for some country variations. As a result, data for the indicator are often based on national definitions and measurements of the informal sector that are generally not strictly comparable across countries.
3. Unemployment, underemployment and inactivity indicators
29. The measure of overall unemployment, provided here as KILM 8, is often the best known of all the 18 indicators, certainly among the media and the public at large in countries where data on the labour market are collected and published. Three other measures that look at parts of the unemployment experience follow KILM 8. Youth, the group with the greatest incidence of joblessness, is covered in KILM 9, while KILM 10 concerns the long-term unemployed, the group experiencing most difficulty in overcoming unemployment. KILM 11 looks at unemployment according to a person's educational attainment, with the principal focus on those with inadequate education and training. Other important measures of unemployment could certainly be selected, many of them popular and useful within countries; however, the four presented here are believed to display the inadequacy of employment to the greatest, and most meaningful, extent.
30. The final two indicators in Chapter 3 do not relate specifically to unemployment. KILM 12 covers "time-related underemployment", which exists when the hours of work of an employed person are insufficient in relation to an alternative employment situation in which the person is willing and available to engage. Finally, KILM 13 covers the "inactivity rate", a measure of persons of prime labour market age (25 to 54 year-olds) who are not in the labour force.
31. For a number of countries, the unemployment rate is viewed as the principal labour market indicator. The resolution concerning statistics of the economically active population, employment, unemployment and underemployment, adopted by the 13th ICLS, defines the unemployed as all persons above a specified age who, during the reference period, were without work, currently available for work and seeking work.(14) However, it should be recognized that national definitions of, and/or coverage for, unemployment can vary in regard to a large number of factors. Among these factors are age limits, criteria for seeking work, and treatment of such circumstances as persons temporarily laid off, discouraged over job prospects or seeking work for the first time. Household labour force surveys are generally the most comprehensive and comparable source of unemployment statistics, but other sources, such as population censuses, "employment office records" and "official estimates", are commonly utilized as well.
32. Youth unemployment represents an important policy issue for many countries, regardless of the stage of development. For the purpose of this indicator, the term "youth" is defined as persons aged 15 to 24, while the term "adults" is defined as persons aged 25 and over. The indicator presents youth unemployment in the following ways: (a) the youth unemployment rate; (b) the youth unemployment rate as a percentage of the adult unemployment rate; (c) the youth share in total unemployment; and (d) youth unemployment as a proportion of the youth population.
33. KILM 9 measures should be analysed in association with one another; any of the four, when analysed in isolation, could give a distorted image. For example, a country might have a high ratio of youth-to-adult unemployment but a low youth share in total unemployment. The presentation of youth unemployment as a proportion of the youth population recognizes the fact that a large proportion of youth enter unemployment from a status outside the labour force. Taken together, the four indicators provide a fairly comprehensive indication of the problems facing youth in the labour market.
KILM 10. Long-term unemployment
34. Unemployment is more severe the longer it lasts. The indicator on long-term unemployment makes the basic assumption that duration of a full year and longer is too long, and is thus worthy of special attention. Two separate measures of long-term unemployment are included: (a) unemployed one year and more as a percentage of the labour force; and (b) unemployed one year and more as a percentage of the total unemployed. All the data on duration of unemployment come from household surveys.
KILM 11. Unemployment by educational attainment
35. In developed (industrialized) countries, unemployment rates are consistently lower the higher the level of educational attainment. This is often not the case for developing countries, where a shortfall of jobs may exist for the more highly educated. The unemployment by educational attainment indicator can have important implications for both employment and education policy. By allowing the present educational and skill levels of the unemployed to be taken into account, these data can be useful in improving the efficiency of training programmes for jobless workers or in designing employment creation programmes.
36. Data for this indicator are measured according to categories of schooling -- less than one year, less than primary level, primary level, secondary level and tertiary level -- and are presented as the proportions of total unemployed in each of these five educational attainment categories. The categories used in the indicator are conceptually based on the levels of the International Standard Classification of Education (ISCED). ISCED was designed by UNESCO to serve as an instrument suitable for assembling, compiling and presenting comparable indicators and statistics of education, both within countries and internationally.(15)
KILM 12. Time-related underemployment
37. Time-related underemployment is the most visible and measurable form of underemployment, involving a shortfall in the quantity of work. The indicator includes two percentage measures -- time-related underemployment as a percentage of the labour force, and as a percentage of total employment. The international definition of time-related underemployment was adopted in 1982 by the 13th ICLS.(16) It includes all persons in employment "involuntarily working less than the normal duration of work determined for the activity, who were seeking or available for additional work during the reference period".(17) Few countries apply this definition consistently, however, because the criteria on which it is based are not well specified. The latest revision of the definition occurred in 1998 at the 16th ICLS.(18) However, this relatively new definition has not yet been implemented in many countries (except for a handful that are already using it). The data for this indicator are derived exclusively from household-based surveys.
38. The inactivity rate is defined as the percentage of the population aged 25 to 54 -- considered to be of "prime age" -- that is neither working nor seeking work (that is, not in the labour force). The inactivity rate within the prime working ages provides some insight into the shortfall of a country's ability to create jobs. It should be noted that the indicator for inactivity rates for prime-age workers, when summed with the labour force participation rate (KILM 1) for this group, will equal 100 per cent. The indicator is of interest when used for comparison across countries; those with low percentages of inactivity for persons in the prime-age range are providing market activity at a significant rate. Among women, high percentages tell us a lot about the social customs of a country and attitudes towards women in the labour force. Future KILM work on this indicator should look into the reasons for inactivity, including labour market discouragement.
4. Educational attainment and illiteracy
KILM 14. Educational attainment and illiteracy
39. An increasingly important aspect of labour market performance and national competitiveness is the skill level of the workforce. Education and skill acquisition are necessary to compete in the global economy and to make use of rapid technological advances. Data on education are available from international sources and are currently the best available indicators of skill levels. As with the indicator for unemployment by educational attainment (KILM 11), KILM 14 presents information in accordance with the ISCED.
40. Educational attainment data are presented according to the following categories of schooling -- less than one year, less than primary level, primary level, secondary level and tertiary level. The KILM 14 indicator focuses on the percentage distributions of educational attainment in the labour force and in the population. Four measures pertaining to educational levels are presented, and there is a fifth measure on illiteracy as a percentage of the adult population. The indicator covers the educational attainment of the entire labour force and also focuses on the educational attainment of a young group of workers, aged 25 to 29 years. The statistics on this younger group provide a better picture of recent changes in the level of educational attainment in a country.
41. Two indicators are used to cover wages and labour costs. The first, KILM 15 (real manufacturing wage trends) shows the movement of average real wages in manufacturing, while the second, KILM 16 (hourly compensation costs) shows the trend and structure of employers' average compensation costs for the employment of production workers in manufacturing. These indicators are complementary, in that they reflect the two main facets of existing wage measures, one aiming to measure the income of employees and the other showing the costs incurred by establishments for the employment of such employees.
KILM 15. Real manufacturing wage indices
42. Wage statistics are a widely used measure of the general level of workers' earnings. The indicator covers real wages in manufacturing. Two main sources of wage indices are presented for this indicator, in order to broaden the scope of coverage. The first series draws on the ILO Database of Labour Statistics.(19) Wage data from other databases and national sources are added to the ILO statistics to improve coverage. The second series of wage indices comes from the UNIDO Industrial Statistics Database. For most countries, the wage indices are calculated using 1990 as the base year.
KILM 16. Hourly compensation costs
43. Differences in hourly compensation costs are only one factor in international competitiveness and, when used alone, can be misleading. However, in conjunction with other indicators, such as labour productivity and unit labour costs (KILM 17), the relative changes can be helpful in assessing trends in competitiveness. In addition, non-wage labour costs have become an important issue in debates on labour market flexibility.
44. For the purposes of this indicator, the definition for hourly compensation costs of manufacturing production workers is expressed in United States dollars at market exchange rates; comparisons in index terms show the position of countries in relation to the United States (on the basis of US=100). The indicator also shows non-wage labour costs as a percentage of total compensation costs -- the sum of gross earnings and the employers' contributions to legally required insurance programmes, contractual and private benefit schemes (plans) and labour taxes -- as well as the annual percentage change in total compensation costs over the period 1980-97.
6. Labour productivity and unit labour cost
KILM 17. Labour productivity and unit labour cost
45. Productivity and unit labour costs, combined with hourly compensation costs, comprise a set of essential tools that can be used to assess the international competitiveness of a labour market. Productivity measures also contribute to an understanding of how labour market performance affects living standards. Two measurements are calculated under KILM 17. The first, labour productivity, or the output per unit of labour input, shows the trends in business sector and/or manufacturing sector output per hour. The second, unit labour costs, defined as the ratio of hourly compensation cost(20) to output per hour, represents a measure of cost competitiveness that is relevant as an indicator for both the manufacturing industry, which produces most internationally tradable products, and the share of labour costs in output creation.
7. Poverty and income distribution
KILM 18. Poverty and income distribution
46. An estimate of the number of poor people in a country depends on the choice of the poverty threshold. However, what constitutes such a threshold of minimum basic needs is subjective and varies with culture and national priorities. Definitional variations create difficulties when it comes to the ability to make valid international comparisons. Therefore, this indicator presents, in addition to national poverty measurements, the World Bank international poverty lines based on the US dollar: US$1 and US$2 per person per day, respectively. The poverty gap has been included as an overall measure of the depth of poverty. The Gini index is also used, as it is a convenient summary measure of the degree of income (or expenditure) inequality.(21)
47. A special effort is made within the KILM to highlight gender issues, paying particular attention to the economic position of women in labour markets around the world. The data generally allow for comparisons between and within countries and regions concerning women's access to labour market work and schooling, and provide insights into differences in the quality of work that women carry out as opposed to men. The overall picture painted by the information available supports the view that, worldwide, women's experiences in the labour market differ substantially from men's. Women typically work in different sectors, work fewer hours, have lower rates of schooling and literacy, and are more likely to be unemployed, underemployed or out of the labour force altogether. "Gender perspective" boxes are provided for the first 15 KILM indicators, which all include gender-related data.
48. In many of the indicators, the data for women show more variation between countries than those for men. This may suggest that culture, societal norms and traditions, and government policies, all play a differential role in women's economic activities, more so than they do for men. Significantly, many of the gender differences in the KILM data point to the fact that paid work represents only a portion of women's overall activities. Most of the world's women devote a large portion of their time to unpaid household responsibilities, childcare and subsistence labour. Labour market statistics, therefore, tell only a comparatively minor part of the story of women's overall economic contribution. Information beyond that currently available through the present KILM analysis -- in such areas as "not in the labour force" activities, informal sector work, unpaid work, occupational segregation and wage differences by sex -- would be necessary in order to further our knowledge of gender differences in the world of work.
IV. Plans for the future of KILM
49. While the primary focus of the 1999 KILM was placed on the selection, refinement and dissemination of the initial set of 18 indicators, the ILO has already begun the task of updating and widening the availability of the indicators to monitor new employment-related trends. Information regarding work on the KILM and the release of future updates can be found on the KILM website.
50. The ILO hopes, by presenting a set of indicators in a systematic and coherent manner, that KILM will serve as an essential reference tool for anyone involved or interested in labour market issues. It is important to recognize that the 1999 KILM represents work in progress; improvements and expansions of the current indicators, as well as in country coverage, remain a top priority for the ILO. The KILM programme will continue to refine the current data and explanatory documentation in collaboration with international, regional and national data repositories. The ILO acknowledges that several labour market indicators of potential interest to researchers, policy-makers, etc., are not yet covered. As KILM evolves, it is hoped that additional indicators -- covering topics such as occupational wage indices, detailed industry breakdowns of employment, and others yet to be identified -- may be included in future issues of KILM.
51. One additional goal of the KILM programme is to decrease the time lag between the point of data collection and dissemination. ILO headquarters will work closely with its regional and field offices in order to gather additional information, while expanding the geographical coverage of the indicators, on a timely basis. Information relating to the updates will be issued on the KILM website. When 1998 data is currently available for some countries or some indicators, there is no need for the user to wait the year or more that it usually takes to ready the data for printed publication when the data can be transferred electronically.
52. One statistical implication of economic globalization is the requirement for more precise, comparable data for different countries. The 18 KILM indicators offer a response to this need. Globalization also increases expectations for information on broad geographical regions and the world at large. The ILO, recognizing the need for such information, has begun the process of developing world and regional estimates for five of the indicators, KILM 1 (labour force participation), KILM 2 (employment-to-population ratio), KILM 4 (employment by sector), KILM 8 (unemployment) and KILM 9 (youth unemployment). The world and regional estimates will be included in future issues of KILM (publications, CD-ROMs and the KILM website.
Geneva, 24 September 1999.
Appendix
Availability of KILM data
The following tables show summaries of the availability of indicators for the world, as well as by region and country. First, a summary by regional and subregional grouping (table 1) gives a count of the number of countries for which data exist for each indicator. Coverage ranges from 200 countries in KILM 4 (employment by sector) to 29 countries in KILM 16 (hourly compensation costs). Next, a country table is given (table 2). The numbers placed in the columns indicate the latest year for which data are available for that country for that indicator. For example, a "97" for KILM 1 indicates that KILM publishes data for that indicator with the latest year being 1997.(22) A blank indicates that no data are available for that country for any given year. The tables represent the results so far of data collection at ILO headquarters, mainly from international databases. The ILO hopes to expand country coverage with the assistance of its field structure and with further efforts at headquarters in locating data from national publications.
Key to KILM numbers
|
1. |
Labour force participation rate |
|
2. |
Employment-to-population ratio |
|
3. |
Status in employment |
|
4. |
Employment by sector |
|
5. |
Part-time workers |
|
6. |
Hours of work |
|
7. |
Urban informal sector employment |
|
8. |
Unemployment |
|
9. |
Youth unemployment |
|
10. |
Long-term unemployment |
|
11. |
Unemployment by educational attainment |
|
12. |
Time-related underemployment |
|
13. |
Inactivity rate |
|
14. |
Educational attainment and illiteracy |
|
15. |
Real manufacturing wage indices |
|
16. |
Hourly compensation costs |
|
17. |
Labour productivity and unit labour costs |
|
18. |
Poverty and income distribution |
Table 1. Availability of KILM data, worldwide and by regional and subregional grouping
Number of sources
|
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|
KILM No. |
|||||||||||||||||||
|
| |||||||||||||||||||
|
Total |
1 |
2 |
3 |
4 |
5 |
6 |
7 |
8 |
9 |
10 |
11 |
12 |
13 |
14 |
15 |
16 |
17 |
18 | |
|
| |||||||||||||||||||
|
Developed (industrialized countries) |
38 |
28 |
27 |
30 |
30 |
24 |
25 |
1 |
33 |
29 |
25 |
23 |
24 |
28 |
31 |
31 |
23 |
18 |
20 |
|
Major Europe |
20 |
20 |
20 |
20 |
20 |
20 |
20 |
1 |
20 |
20 |
20 |
14 |
18 |
20 |
20 |
20 |
17 |
14 |
15 |
|
Major non-Europe |
5 |
5 |
5 |
5 |
5 |
4 |
5 |
5 |
5 |
5 |
5 |
5 |
5 |
5 |
5 |
5 |
4 |
4 | |
|
Other Europe |
9 |
2 |
1 |
3 |
4 |
3 |
3 |
2 |
4 |
||||||||||
|
Other non-Europe |
4 |
1 |
2 |
1 |
3 |
1 |
1 |
1 |
1 |
2 |
1 |
1 |
1 |
||||||
|
Transition economies |
31 |
28 |
16 |
13 |
29 |
8 |
2 |
8 |
22 |
16 |
9 |
16 |
8 |
28 |
25 |
22 |
19 | ||
|
Central Europe and Eastern Europe |
16 |
13 |
7 |
8 |
14 |
7 |
2 |
3 |
10 |
9 |
7 |
7 |
7 |
13 |
10 |
11 |
9 | ||
|
Baltic States |
3 |
3 |
2 |
3 |
3 |
1 |
2 |
3 |
3 |
1 |
3 |
1 |
3 |
3 |
3 |
3 |
|||
|
Commonwealth of Independent States |
12 |
12 |
7 |
2 |
12 |
3 |
9 |
4 |
6 |
12 |
12 |
8 |
7 |
||||||
|
Asia and the Pacific |
49 |
32 |
15 |
15 |
33 |
1 |
10 |
9 |
19 |
10 |
1 |
8 |
3 |
32 |
32 |
27 |
5 |
8 |
14 |
|
Eastern Asia |
7 |
6 |
5 |
4 |
7 |
1 |
2 |
5 |
4 |
1 |
3 |
1 |
6 |
6 |
6 |
3 |
3 |
2 | |
|
South-central Asia |
8 |
8 |
2 |
8 |
4 |
4 |
4 |
2 |
8 |
8 |
7 |
1 |
2 |
5 |
|||||
|
South-eastern Asia |
14 |
12 |
7 |
5 |
11 |
3 |
6 |
4 |
2 |
2 |
12 |
10 |
3 |
6 |
|||||
|
Melanesia |
3 |
3 |
3 |
1 |
1 |
1 |
3 |
2 |
3 |
1 |
|||||||||
|
Other Melanesia |
2 |
1 |
1 |
||||||||||||||||
|
Micronesia |
6 |
2 |
1 |
2 |
2 |
1 |
|||||||||||||
|
Polynesia |
9 |
1 |
2 |
2 |
1 |
3 |
3 |
||||||||||||
|
Latin America and the Caribbean |
47 |
33 |
17 |
38 |
43 |
10 |
14 |
17 |
40 |
36 |
10 |
21 |
9 |
33 |
43 |
30 |
1 |
5 |
21 |
|
Caribbean |
28 |
16 |
8 |
22 |
26 |
9 |
8 |
2 |
22 |
19 |
8 |
11 |
1 |
16 |
25 |
13 |
5 | ||
|
Latin America |
19 |
17 |
9 |
16 |
17 |
1 |
6 |
15 |
18 |
17 |
2 |
10 |
8 |
17 |
18 |
17 |
1 |
5 |
16 |
|
Sub-Saharan Africa |
50 |
44 |
14 |
44 |
16 |
18 |
6 |
6 |
44 |
47 |
35 |
27 | |||||||
|
Eastern Africa |
18 |
15 |
6 |
15 |
7 |
6 |
3 |
5 |
15 |
15 |
13 |
11 | |||||||
|
Middle Africa |
10 |
8 |
1 |
8 |
1 |
2 |
1 |
1 |
8 |
10 |
5 |
1 |
|||||||
|
Southern Africa |
5 |
5 |
3 |
5 |
2 |
5 |
5 |
3 |
|||||||||||
|
Western Africa |
17 |
16 |
4 |
16 |
6 |
8 |
2 |
16 |
17 |
12 |
12 |
||||||||
|
Middle East and North Africa |
24 |
20 |
4 |
5 |
20 |
3 |
7 |
3 |
4 |
20 |
18 |
14 |
6 | ||||||
|
Middle East |
17 |
14 |
1 |
2 |
14 |
1 |
2 |
1 |
2 |
14 |
12 |
9 |
2 | ||||||
|
North Africa |
7 |
6 |
3 |
3 |
6 |
2 |
5 |
2 |
6 |
6 |
5 |
4 |
|||||||
|
Former USSR |
1 |
1 |
1 |
1 |
|||||||||||||||
|
Total |
240 |
185 |
79 |
115 |
200 |
43 |
51 |
54 |
139 |
100 |
45 |
78 |
44 |
185 |
197 |
160 |
29 |
31 |
107 |
|
| |||||||||||||||||||
Table 2. Availability of KILM data, by country and latest year
|
| |||||||||||||||||||
|
KILM Code |
KILM No. |
||||||||||||||||||
|
| |||||||||||||||||||
|
1 |
2 |
3 |
4 |
5 |
6 |
7 |
8 |
9 |
10 |
11 |
12 |
13 |
14 |
15 |
16 |
17 |
18 | ||
|
| |||||||||||||||||||
|
Developed (industrialized) countries | |||||||||||||||||||
|
Major Europe |
|||||||||||||||||||
|
407 |
Austria |
97 |
97 |
97 |
97 |
97 |
96 |
97 |
97 |
97 |
97 |
95 |
97 |
96 |
95 |
97 |
97 |
87 | |
|
409 |
Belgium |
97 |
97 |
92 |
92 |
97 |
96 |
97 |
97 |
97 |
95 |
97 |
89 |
96 |
97 |
97 |
92 | ||
|
415 |
Denmark |
97 |
97 |
97 |
97 |
97 |
96 |
97 |
97 |
97 |
97 |
95 |
97 |
96 |
97 |
97 |
97 |
92 | |
|
421 |
Finland |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
96 |
95 |
97 |
95 |
96 |
97 |
97 |
91 | |
|
423 |
France |
97 |
97 |
96 |
94 |
97 |
97 |
97 |
97 |
97 |
95 |
97 |
96 |
93 |
97 |
97 |
89 | ||
|
424 |
Germany |
97 |
97 |
97 |
97 |
96 |
97 |
97 |
97 |
96 |
97 |
95 |
97 |
95 |
94 |
||||
|
427 |
Germany, Fed. Rep. of (western) |
96 |
96 |
93 |
94 |
96 |
96 |
96 |
90 |
96 |
90 |
96 |
89 |
96 |
96 |
96 |
89 | ||
|
431 |
Greece |
97 |
97 |
97 |
97 |
97 |
96 |
97 |
97 |
97 |
97 |
95 |
97 |
95 |
97 |
96 |
97 |
||
|
435 |
Iceland |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
96 |
95 |
|||||
|
437 |
Ireland |
97 |
97 |
97 |
97 |
97 |
96 |
97 |
97 |
97 |
97 |
95 |
97 |
96 |
97 |
97 |
97 |
87 | |
|
441 |
Italy |
97 |
97 |
96 |
96 |
97 |
96 |
97 |
97 |
97 |
96 |
93 |
97 |
96 |
96 |
97 |
97 |
91 | |
|
445 |
Luxembourg |
97 |
97 |
95 |
90 |
96 |
96 |
97 |
97 |
96 |
95 |
97 |
96 |
96 |
96 |
91 | |||
|
451 |
Netherlands |
97 |
97 |
97 |
97 |
97 |
96 |
97 |
97 |
97 |
97 |
95 |
97 |
96 |
96 |
97 |
97 |
91 | |
|
453 |
Norway |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
91 | ||
|
457 |
Portugal |
97 |
97 |
97 |
97 |
97 |
96 |
96 |
97 |
97 |
97 |
95 |
97 |
97 |
96 |
97 |
97 |
||
|
417 |
Spain |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
95 |
97 |
97 |
97 |
97 |
97 |
90 | |
|
465 |
Sweden |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
95 |
97 |
97 |
97 |
97 |
97 |
92 | |
|
464 |
Switzerland |
97 |
97 |
94 |
97 |
97 |
96 |
97 |
97 |
97 |
97 |
80 |
93 |
97 |
82 | ||||
|
467 |
Turkey |
97 |
97 |
96 |
97 |
96 |
96 |
93 |
97 |
97 |
97 |
94 |
97 |
95 |
96 |
||||
|
469 |
United Kingdom |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
95 |
97 |
96 |
97 |
97 |
97 |
91 | |
|
Major non-Europe |
|||||||||||||||||||
|
505 |
Australia |
97 |
97 |
97 |
97 |
96 |
97 |
97 |
97 |
97 |
97 |
93 |
97 |
95 |
97 |
97 |
97 |
89 | |
|
219 |
Canada |
97 |
97 |
96 |
97 |
97 |
96 |
97 |
97 |
97 |
97 |
93 |
97 |
96 |
97 |
97 |
97 |
94 | |
|
331 |
Japan |
97 |
97 |
97 |
97 |
96 |
96 |
97 |
97 |
97 |
97 |
97 |
97 |
96 |
96 |
97 |
97 |
92 | |
|
519 |
New Zealand |
97 |
97 |
97 |
97 |
96 |
97 |
97 |
97 |
96 |
93 |
97 |
97 |
97 |
97 |
||||
|
291 |
United States |
97 |
97 |
97 |
97 |
96 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
94 |
97 |
97 |
97 |
94 | |
|
Other Europe |
|||||||||||||||||||
|
405 |
Andorra |
||||||||||||||||||
|
317 |
Cyprus |
95 |
95 |
92 |
95 |
96 |
96 |
96 |
95 |
92 |
97 |
||||||||
|
419 |
Faeroe Islands |
||||||||||||||||||
|
429 |
Gibraltar |
92 |
96 |
95 |
|||||||||||||||
|
439 |
Isle of Man |
91 |
97 |
97 |
|||||||||||||||
|
443 |
Liechtenstein |
81 |
|||||||||||||||||
|
447 |
Malta |
95 |
91 |
97 |
96 |
97 |
95 |
85 |
94 |
||||||||||
|
449 |
Monaco |
||||||||||||||||||
|
461 |
San Marino |
97 |
97 |
97 |
96 |
97 |
96 |
97 |
|||||||||||
|
Other non-Europe |
|||||||||||||||||||
|
241 |
Greenland |
97 |
|||||||||||||||||
|
329 |
Israel |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
96 |
97 |
96 |
96 |
97 |
92 | |||||
|
523 |
Norfolk Island |
||||||||||||||||||
|
283 |
St-Pierre and Miquelon |
89 |
93 |
82 |
|||||||||||||||
|
Transition economies |
|||||||||||||||||||
|
Central and Eastern Europe |
|||||||||||||||||||
|
403 |
Albania |
95 |
91 |
91 |
95 |
95 |
96 | ||||||||||||
|
410 |
Bosnia and Herzegovina |
95 |
90 |
95 |
|||||||||||||||
|
411 |
Bulgaria |
95 |
95 |
94 |
97 |
97 |
97 |
97 |
97 |
97 |
95 |
97 |
97 |
92 | |||||
|
412 |
Croatia |
95 |
93 |
97 |
97 |
97 |
95 |
91 |
96 |
||||||||||
|
413 |
Czech Republic |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
96 |
93 | |||
|
414 |
Czechoslovakia |
91 |
|||||||||||||||||
|
428 |
Germany, 5 new Länder |
||||||||||||||||||
|
425 |
Germany, former Democratic Republic of (eastern) |
94 |
94 |
94 |
94 |
||||||||||||||
|
433 |
Hungary |
97 |
97 |
97 |
97 |
97 |
96 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
93 | |||
|
455 |
Poland |
97 |
97 |
97 |
97 |
97 |
95 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
96 |
93 | |||
|
459 |
Romania |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
94 |
94 | ||||
|
462 |
Slovakia |
97 |
97 |
97 |
97 |
97 |
96 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
92 | |||
|
463 |
Slovenia |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
93 | ||||
|
446 |
The Former Yugoslavia Republic of Macedonia |
96 |
91 |
94 |
97 |
97 |
96 |
95 |
90 | ||||||||||
|
477 |
Yugoslavia |
95 |
95 |
91 |
95 |
||||||||||||||
|
475 |
Yugoslavia (former) |
90 |
81 |
||||||||||||||||
|
Baltic States |
|||||||||||||||||||
|
418 |
Estonia |
97 |
90 |
94 |
94 |
96 |
94 |
96 |
97 |
95 |
96 |
94 | |||||||
|
442 |
Latvia |
97 |
97 |
97 |
97 |
97 |
96 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
93 | |||
|
444 |
Lithuania |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
97 |
93 | |||||||
|
Commonwealth of Independent States |
|||||||||||||||||||
|
302 |
Armenia |
95 |
90 |
95 |
89 |
||||||||||||||
|
304 |
Azerbaijan |
95 |
95 |
97 |
97 |
97 |
95 |
89 |
97 |
||||||||||
|
408 |
Belarus |
95 |
94 |
97 |
97 |
97 |
95 |
89 |
96 |
93 | |||||||||
|
319 |
Georgia |
95 |
90 |
95 |
89 |
||||||||||||||
|
335 |
Kazakhstan |
95 |
89 |
95 |
96 |
96 |
95 |
89 |
95 |
93 | |||||||||
|
342 |
Kyrgyzstan |
95 |
95 |
97 |
94 |
97 |
96 |
97 |
95 |
89 |
96 |
93 | |||||||
|
448 |
Republic of Moldova |
95 |
95 |
94 |
96 |
95 |
89 |
96 |
92 | ||||||||||
|
460 |
Russian Federation |
95 |
95 |
95 |
95 |
97 |
96 |
96 |
96 |
95 |
96 |
95 |
94 | ||||||
|
376 |
Tajikistan |
95 |
95 |
96 |
97 |
97 |
95 |
89 |
97 |
||||||||||
|
379 |
Turkmenistan |
95 |
90 |
95 |
89 |
93 | |||||||||||||
|
468 |
Ukraine |
95 |
95 |
97 |
97 |
97 |
96 |
97 |
95 |
89 |
89 |
95 | |||||||
|
382 |
Uzbekistan |
95 |
95 |
90 |
95 |
95 |
89 |
||||||||||||
|
Asia and the Pacific | |||||||||||||||||||
|
Eastern Asia | |||||||||||||||||||
|
315 |
China |
95 |
95 |
97 |
97 |
95 |
95 |
96 |
95 | ||||||||||
|
320 |
Hong Kong, China |
97 |
97 |
94 |
97 |
92 |
97 |
97 |
96 |
97 |
95 |
97 |
97 |
96 |
|||||
|
337 |
Korea, Democratic People's Republic of |
95 |
90 |
95 |
|||||||||||||||
|
339 |
Korea, Republic of |
97 |
97 |
97 |
97 |
97 |
96 |
97 |
97 |
97 |
97 |
97 |
96 |
97 |
97 |
96 |
|||
|
346 |
Macau |
97 |
97 |
93 |
97 |
97 |
97 |
97 |
97 |
91 |
95 |
||||||||
|
353 |
Mongolia |
95 |
96 |
95 |
95 |
95 |
95 | ||||||||||||
|
999 |
Taiwan, China |
96 |
97 |
97 |
97 |
96 |
97 |
97 |
96 |
97 |
96 |
||||||||
|
South-central Asia | |||||||||||||||||||
|
300 |
Afghanistan |
95 |
90 |
95 |
95 |
88 |
|||||||||||||
|
307 |
Bangladesh |
96 |
96 |
96 |
96 |
94 |
93 |
96 |
96 |
96 |
95 |
92 |
96 | ||||||
|
309 |
Bhutan |
95 |
90 |
95 |
95 |
89 |
|||||||||||||
|
321 |
India |
95 |
95 |
93 |
97 |
94 |
95 |
95 |
96 |
95 |
94 | ||||||||
|
351 |
Maldives |
95 |
90 |
90 |
95 |
95 |
|||||||||||||
|
355 |
Nepal |
95 |
95 |
94 |
95 |
95 |
94 |
95 | |||||||||||
|
359 |
Pakistan |
95 |
95 |
96 |
95 |
94 |
92 |
95 |
95 |
95 |
95 |
95 |
94 |
91 | |||||
|
373 |
Sri Lanka |
95 |
96 |
96 |
94 |
85 |
96 |
95 |
95 |
95 |
97 |
96 |
95 |
90 | |||||
|
South-eastern Asia | |||||||||||||||||||
|
311 |
Brunei Darussalam |
95 |
90 |
95 |
95 |
||||||||||||||
|
313 |
Cambodia |
96 |
93 |
96 |
93 |
||||||||||||||
|
378 |
East Timor |
95 |
90 |
95 |
|||||||||||||||
|
323 |
Indonesia |
95 |
95 |
92 |
97 |
95 |
96 |
96 |
95 |
95 |
96 |
95 |
95 | ||||||
|
343 |
Lao People's Democratic Republic |
95 |
90 |
95 |
95 |
94 |
93 | ||||||||||||
|
347 |
Malaysia |
95 |
90 |
93 |
97 |
94 |
97 |
95 |
95 |
96 |
89 | ||||||||
|
348 |
Malaysia: Peninsular Malaysia |
80 |
80 |
||||||||||||||||
|
349 |
Malaysia: Sabah |
||||||||||||||||||
|
350 |
Malaysia: Sarawak |
||||||||||||||||||
|
354 |
Myanmar |
95 |
90 |
97 |
96 |
97 |
95 |
95 |
97 |
||||||||||
|
361 |
Philippines |
97 |
97 |
94 |
97 |
95 |
97 |
97 |
96 |
97 |
95 |
95 |
95 |
94 | |||||
|
371 |
Singapore |
97 |
97 |
97 |
97 |
92 |
97 |
97 |
97 |
97 |
96 |
97 |
97 |
||||||
|
377 |
Thailand |
97 |
97 |
96 |
97 |
94 |
95 |
97 |
97 |
97 |
97 |
97 |
95 |
97 |
96 |
92 | |||
|
383 |
Viet Nam |
95 |
90 |
96 |
95 |
95 |
93 | ||||||||||||
|
Pacific | |||||||||||||||||||
|
Melanesia |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
|
509 |
Fiji |
95 |
95 |
94 |
90 |
95 |
95 |
95 |
96 |
||||||||||
|
529 |
Papua New Guinea |
95 |
90 |
95 |
95 |
89 |
96 | ||||||||||||
|
537 |
Solomon Islands |
95 |
93 |
95 |
95 |
||||||||||||||
|
Other Melanesia | |||||||||||||||||||
|
526 |
New Caledonia |
95 |
96 |
89 |
|||||||||||||||
|
545 |
Vanuatu |
||||||||||||||||||
|
Micronesia | |||||||||||||||||||
|
511 |
Guam |
88 |
88 |
96 |
93 |
88 |
90 |
93 |
|||||||||||
|
513 |
Kiribati |
||||||||||||||||||
|
514 |
Marshall Islands |
||||||||||||||||||
|
515 |
Nauru |
||||||||||||||||||
|
525 |
Northern Mariana Islands |
85 |
85 |
||||||||||||||||
|
527 |
Pacific Islands (Trust Territory) |
80 |
|||||||||||||||||
|
Polynesia | |||||||||||||||||||
|
503 |
American Samoa |
90 |
|||||||||||||||||
|
507 |
Cook Islands |
91 |
91 |
93 |
|||||||||||||||
|
533 |
French Polynesia |
92 |
90 |
89 |
|||||||||||||||
|
521 |
Niue |
||||||||||||||||||
|
535 |
Samoa |
81 |
|||||||||||||||||
|
538 |
Tokelau |
||||||||||||||||||
|
539 |
Tonga |
94 |
90 |
94 |
86 |
94 |
|||||||||||||
|
543 |
Tuvalu |
||||||||||||||||||
|
512 |
Wallis and Futuna Islands |
||||||||||||||||||
|
Latin America and the Caribbean | |||||||||||||||||||
|
Caribbean | |||||||||||||||||||
|
201 |
Anguilla |
92 |
92 |
91 |
91 |
||||||||||||||
|
203 |
Antigua and Barbuda |
91 |
91 |
91 |
91 |
91 |
|||||||||||||
|
206 |
Aruba |
94 |
94 |
94 |
94 |
94 |
94 |
94 |
|||||||||||
|
207 |
Bahamas |
95 |
95 |
96 |
96 |
96 |
96 |
95 |
95 |
96 |
94 |
95 |
96 |
91 |
|||||
|
209 |
Barbados |
96 |
96 |
96 |
95 |
96 |
95 |
95 |
95 |
96 |
96 |
96 |
96 |
96 |
|||||
|
211 |
Belize |
96 |
96 |
96 |
96 |
96 |
96 |
96 |
96 |
96 |
96 |
96 |
96 |
92 |
|||||
|
213 |
Bermuda |
96 |
91 |
91 |
|||||||||||||||
|
297 |
British Virgin Islands |
91 |
91 |
91 |
91 |
91 |
91 |
91 |
94 |
||||||||||
|
221 |
Cayman Islands |
91 |
94 |
94 |
94 |
||||||||||||||
|
227 |
Cuba |
95 |
90 |
95 |
95 |
||||||||||||||
|
231 |
Dominica |
89 |
89 |
91 |
89 |
81 |
|||||||||||||
|
233 |
Dominican Republic |
95 |
95 |
97 |
96 |
97 |
97 |
97 |
95 |
95 |
95 |
92 | |||||||
|
243 |
Grenada |
88 |
91 |
91 |
91 |
91 |
88 |
81 |
|||||||||||
|
245 |
Guadeloupe |
95 |
90 |
94 |
91 |
93 |
95 |
82 |
|||||||||||
|
249 |
Guyana |
95 |
92 |
92 |
92 |
92 |
95 |
95 |
93 | ||||||||||
|
253 |
Haïti |
95 |
90 |
88 |
90 |
95 |
95 |
88 |
87 | ||||||||||
|
257 |
Jamaica |
95 |
95 |
96 |
96 |
96 |
96 |
96 |
96 |
96 |
96 |
95 |
95 |
95 |
92 |
93 | |||
|
259 |
Martinique |
95 |
90 |
95 |
86 |
||||||||||||||
|
263 |
Montserrat |
91 |
91 |
80 |
|||||||||||||||
|
265 |
Netherlands Antilles |
97 |
97 |
97 |
96 |
96 |
97 |
97 |
96 |
96 |
97 |
97 |
96 |
97 |
|||||
|
277 |
Puerto Rico |
97 |
97 |
95 |
97 |
97 |
95 |
97 |
90 |
97 |
|||||||||
|
279 |
Saint Kitts and Nevis |
91 |
91 |
80 |
|||||||||||||||
|
281 |
Saint Lucia |
96 |
96 |
96 |
80 |
||||||||||||||
|
285 |
Saint Vincent and the Grenadines |
91 |
91 |
91 |
91 |
91 |
91 |
91 |
91 |
94 |
|||||||||
|
287 |
Suriname |
95 |
95 |
96 |
96 |
96 |
96 |
96 |
96 |
96 |
95 |
95 |
93 |
||||||
|
289 |
Trinidad and Tobago |
96 |
96 |
95 |
95 |
96 |
96 |
96 |
96 |
96 |
96 |
96 |
96 |
95 |
92 | ||||
|
290 |
Turks and Caicos Islands |
80 |
|||||||||||||||||
|
299 |
United States Virgin Islands |
90 |
93 |
97 |
80 |
||||||||||||||
|
Latin America | |||||||||||||||||||
|
205 |
Argentina |
95 |
95 |
95 |
96 |
94 |
95 |
96 |
96 |
96 |
97 |
95 |
95 |
97 |
91 | ||||
|
215 |
Bolivia |
96 |
90 |
96 |
96 |
96 |
96 |
96 |
96 |
96 |
96 |
96 |
91 | ||||||
|
217 |
Brazil |
96 |
90 |
95 |
94 |
95 |
96 |
96 |
96 |
95 |
96 |
96 |
95 | ||||||
|
229 |
Chile |
97 |
97 |
97 |
97 |
94 |
97 |
97 |
97 |
95 |
94 |
97 |
95 |
97 |
96 |
94 | |||
|
223 |
Colombia |
97 |
97 |
97 |
94 |
96 |
97 |
97 |
97 |
97 |
97 |
96 |
97 |
96 |
95 | ||||
|
225 |
Costa Rica |
97 |
97 |
97 |
97 |
95 |
97 |
97 |
97 |
96 |
97 |
96 |
97 |
96 | |||||
|
235 |
Ecuador |
97 |
97 |
97 |
97 |
97 |
97 |
96 |
97 |
95 |
96 |
95 | |||||||
|
237 |
El Salvador |
97 |
97 |
97 |
97 |
97 |
96 |
97 |
97 |
96 |
96 |
95 | |||||||
|
239 |
Falkland Islands (Malvinas) |
||||||||||||||||||
|
251 |
French Guiana |
93 |
93 |
93 |
82 |
||||||||||||||
|
247 |
Guatemala |
95 |
91 |
93 |
89 |
95 |
95 |
95 |
96 |
89 | |||||||||
|
255 |
Honduras |
97 |
97 |
97 |
97 |
95 |
97 |
96 |
97 |
95 |
96 |
96 | |||||||
|
261 |
Mexico |
97 |
97 |
97 |
97 |
97 |
97 |
96 |
97 |
97 |
97 |
97 |
93 |
97 |
96 |
97 |
97 |
97 |
92 |
|
267 |
Nicaragua |
95 |
92 |
97 |
97 |
95 |
95 |
97 |
93 | ||||||||||
|
269 |
Panama |
97 |
97 |
97 |
97 |
95 |
96 |
95 |
94 |
97 |
95 |
95 |
91 | ||||||
|
273 |
Paraguay |
95 |
95 |
94 |
96 |
96 |
95 |
90 |
95 |
95 |
94 |
95 | |||||||
|
275 |
Peru |
97 |
97 |
97 |
97 |
97 |
96 |
97 |
97 |
96 |
97 |
94 | |||||||
|
293 |
Uruguay |
95 |
93 |
95 |
97 |
95 |
95 |
92 |
95 |
95 |
97 |
||||||||
|
295 |
Venezuela |
95 |
95 |
93 |
95 |
94 |
97 |
95 |
96 |
96 |
95 |
95 |
97 |
96 |
95 | ||||
|
Sub-Saharan Africa | |||||||||||||||||||
|
Eastern Africa | |||||||||||||||||||
|
021 |
Burundi |
95 |
91 |
92 |
95 |
95 |
91 |
90 | |||||||||||
|
029 |
Comoros |
95 |
90 |
95 |
95 |
||||||||||||||
|
040 |
Eritrea |
95 |
90 |
95 |
|||||||||||||||
|
041 |
Ethiopia |
95 |
94 |
95 |
96 |
96 |
94 |
94 |
95 |
95 |
95 |
82 | |||||||
|
055 |
Kenya |
95 |
94 |
95 |
95 |
95 |
95 |
97 |
92 | ||||||||||
|
063 |
Madagascar |
95 |
90 |
95 |
95 |
93 |
95 |
95 |
88 |
93 | |||||||||
|
065 |
Malawi |
95 |
87 |
91 |
95 |
95 |
95 |
91 | |||||||||||
|
073 |
Mauritius |
95 |
95 |
95 |
92 |
97 |
96 |
97 |
95 |
95 |
97 |
92 | |||||||
|
075 |
Mozambique |
95 |
90 |
95 |
95 |
94 |
|||||||||||||
|
083 |
Réunion |
95 |
90 |
90 |
93 |
95 |
82 |
||||||||||||
|
087 |
Rwanda |
96 |
90 |
96 |
95 |
86 |
93 | ||||||||||||
|
093 |
Seychelles |
87 |
97 |
||||||||||||||||
|
108 |
Tanzania (Tanganyika) |
||||||||||||||||||
|
107 |
Tanzania, United Rep. of |
95 |
90 |
95 |
95 |
95 |
91 |
93 | |||||||||||
|
117 |
Uganda |
95 |
94 |
94 |
94 |
94 |
92 |
91 |
95 |
95 |
90 |
93 | |||||||
|
121 |
Zambia |
95 |
90 |
93 |
95 |
95 |
94 |
93 | |||||||||||
|
109 |
Zanzibar |
||||||||||||||||||
|
123 |
Zimbabwe |
95 |
94 |
97 |
95 |
95 |
96 |
90 | |||||||||||
|
Middle Africa | |||||||||||||||||||
|
015 |
Angola |
95 |
90 |
96 |
95 |
85 |
93 |
||||||||||||
|
023 |
Cameroon |
95 |
90 |
93 |
95 |
95 |
95 |
84 | |||||||||||
|
027 |
Central African Republic |
95 |
88 |
90 |
95 |
94 |
95 |
95 |
95 |
93 |
|||||||||
|
111 |
Chad |
95 |
90 |
95 |
95 |
||||||||||||||
|
031 |
Congo |
95 |
90 |
95 |
95 |
88 |
|||||||||||||
|
032 |
Congo, Democratic Republic of |
95 |
95 |
95 |
|||||||||||||||
|
048 |
Equatorial Guinea |
95 |
90 |
95 |
95 |
||||||||||||||
|
043 |
Gabon |
95 |
90 |
95 |
95 |
95 |
|||||||||||||
|
089 |
Sao Tome and Principe |
81 |
|||||||||||||||||
|
119 |
Zaire |
90 |
95 |
||||||||||||||||
|
Southern Africa | |||||||||||||||||||
|
019 |
Botswana |
96 |
91 |
92 |
96 |
95 |
96 |
95 |
97 |
85 | |||||||||
|
057 |
Lesotho |
95 |
90 |
95 |
95 |
85 |
93 | ||||||||||||
|
077 |
Namibia |
95 |
91 |
90 |
95 |
91 |
94 |
||||||||||||
|
099 |
South Africa |
95 |
91 |
93 |
95 |
96 |
95 |
95 |
95 |
93 | |||||||||
|
105 |
Swaziland |
95 |
92 |
95 |
95 |
96 |
|||||||||||||
|
Western Africa | |||||||||||||||||||
|
017 |
Benin |
95 |
92 |
90 |
92 |
95 |
95 |
95 | |||||||||||
|
020 |
Burkina Faso |
95 |
90 |
94 |
92 |
95 |
95 |
83 |
|||||||||||
|
025 |
Cape Verde |
95 |
90 |
90 |
95 |
95 |
95 |
||||||||||||
|
033 |
Côte d'Ivoire |
95 |
90 |
96 |
92 |
95 |
95 |
90 |
88 | ||||||||||
|
045 |
Gambia |
95 |
90 |
93 |
95 |
95 |
93 |
92 | |||||||||||
|
047 |
Ghana |
95 |
91 |
97 |
94 |
95 |
95 |
95 |
92 | ||||||||||
|
049 |
Guinea |
95 |
83 |
90 |
95 |
95 |
96 |
91 | |||||||||||
|
051 |
Guinea-Bissau |
95 |
90 |
95 |
95 |
96 |
91 | ||||||||||||
|
059 |
Liberia |
95 |
90 |
95 |
95 |
86 |
|||||||||||||
|
067 |
Mali |
95 |
90 |
96 |
95 |
95 |
|||||||||||||
|
071 |
Mauritania |
95 |
90 |
95 |
95 |
90 | |||||||||||||
|
079 |
Niger |
95 |
91 |
95 |
91 |
91 |
95 |
95 |
87 |
92 | |||||||||
|
081 |
Nigeria |
95 |
86 |
90 |
93 |
95 |
95 |
85 |
93 | ||||||||||
|
091 |
Senegal |
95 |
90 |
93 |
95 |
95 |
94 |
91 | |||||||||||
|
095 |
Sierra Leone |
95 |
90 |
95 |
95 |
93 |
89 | ||||||||||||
|
101 |
St. Helena |
96 |
87 |
||||||||||||||||
|
113 |
Togo |
95 |
90 |
95 |
95 |
84 |
89 | ||||||||||||
|
Middle East and North Africa | |||||||||||||||||||
|
Middle East | |||||||||||||||||||
|
305 |
Bahrain |
95 |
94 |
96 |
97 |
97 |
95 |
95 |
94 |
||||||||||
|
035 |
Djibouti |
95 |
|||||||||||||||||
|
318 |
Gaza Strip |
95 |
90 |
95 |
|||||||||||||||
|
325 |
Iran, Islamic Rep. of |
95 |
86 |
96 |
96 |
95 |
94 |
93 |
|||||||||||
|
327 |
Iraq |
95 |
90 |
95 |
95 |
||||||||||||||
|
333 |
Jordan |
95 |
93 |
96 |
95 |
96 |
95 |
92 | |||||||||||
|
341 |
Kuwait |
95 |
90 |
95 |
95 |
94 |
|||||||||||||
|
345 |
Lebanon |
95 |
90 |
95 |
95 |
||||||||||||||
|
357 |
Oman |
95 |
90 |
95 |
93 |
96 |
|||||||||||||
|
363 |
Qatar |
95 |
90 |
95 |
95 |
94 |
|||||||||||||
|
367 |
Saudi Arabia |
95 |
90 |
95 |
95 |
89 |
|||||||||||||
|
097 |
Somalia |
95 |
90 |
95 |
86 |
||||||||||||||
|
375 |
Syrian Arab Republic |
95 |
83 |
91 |
91 |
91 |
95 |
95 |
95 |
||||||||||
|
381 |
United Arab Emirates |
95 |
90 |
95 |
95 |
||||||||||||||
|
384 |
Yemen |
95 |
90 |
95 |
92 | ||||||||||||||
|
385 |
Yemen, Former Arab Republic of |
||||||||||||||||||
|
387 |
Yemen, Former Democratic Rep. of |
||||||||||||||||||
|
North Africa | |||||||||||||||||||
|
013 |
Algeria |
95 |
95 |
90 |
97 |
92 |
95 |
95 |
95 |
96 |
95 | ||||||||
|
037 |
Egypt |
95 |
95 |
92 |
95 |
95 |
95 |
95 |
95 |
95 |
91 | ||||||||
|
061 |
Libyan Arab Jamahiriya |
95 |
90 |
95 |
95 |
||||||||||||||
|
069 |
Morocco |
95 |
91 |
92 |
88 |
96 |
95 |
95 |
95 |
91 | |||||||||
|
103 |
Sudan |
95 |
90 |
92 |
95 |
95 |
92 |
||||||||||||
|
115 |
Tunisia |
95 |
89 |
94 |
94 |
81 |
96 |
94 |
95 |
95 |
95 |
90 | |||||||
|
088 |
Western Sahara |
||||||||||||||||||
|
Former USSR | |||||||||||||||||||
|
603 |
USSR: before September 1991 |
|
|
|
90 |
|
|
|
|
|
|
|
|
|
89 |
90 |
|
|
|
|
| |||||||||||||||||||
1. Key Indicators of the Labour Market, ILO, Geneva, 1999. Copies will be available at the Committee's meeting.
2. The International Labour Office has developed country and area designations and rules for their use in English, French and Spanish; see the ILO website at http://www.ilo.org/public/english/220relco/ctry-ndx.htm.
3. International Standard ISO 3166-1, codes for the representation of names of countries and their subdivisions. Part 1: Country codes, 1997 (Geneva, International Organization on Standardization, 1997); website: http://www.un.org/Depts/unsd/methods/m49.htm.
4. From this point forward, the term "countries" is used to represent countries, areas and territories. The term should not be interpreted to imply political independence or official recognition by the ILO but refers to any territory or economy for which labour market information is available.
5. It is important to note that the country groupings developed for KILM are intended exclusively for statistical and analytical convenience and are not intended to express judgement or appraisal as to a given country's current stage in the development process.
6. The former USSR, before September 1991, appears in several of the statistical tables as a seventh major grouping.
7. Despite best efforts to include concise and informative notes to the KILM tables, the notes are often limited in terms of the level of detail that were available from the various data repositories. As the KILM project evolves, the ILO will continue to collect data and work in close cooperation with the data repositories, with the particular aim of resolving irregularities and clarifying data notes.
8. Resolution concerning statistics of the economically active population, employment, unemployment and underemployment, adopted by the 13th International Conference of Labour Statisticians, Geneva, 1982; website: http://www.ilo.org/public/english/120stat/res/ecacpop.htm.
9. United Nations: Statistical implications of recent major United Nations conferences, Statistical Commission, Economic and Social Council, 29th Session, New York, Feb. 1997.
10. United Nations: 1993 International Classification by Status of Employment (St/ESA/STAT/SER.M/4/Rev.3) (New York, 1993; Sales Number E.90XVII.11); website: http://www.ilo.org/public/english/120stat/class/isic.htm.
11. The use of the OECD estimates for this indicator should not be interpreted as a decision on the part of the ILO to favour the 30-hour definition. Rather, it was selected because it represented the broadest, most consistent data set available for a majority of the countries for which KILM 5 data are available.
12. The international definition of employment, adopted in 1982 by the 13th ICLS, includes all persons engaged in the production of goods and services, even if only for one hour, during a specified short reference period, and all persons who have a job from which they are absent (such as for personal reasons or union-management disputes) but in which they normally work (Resolution concerning statistics of the economically active population ..., op. cit.).
13. Resolution concerning statistics of employment in the informal sector, adopted by the 15th International Conference of Labour Statisticians, Geneva, 1993; website: http://www.ilo.org/public/english/120stat/res/infsec.htm.
14. Resolution concerning statistics of the economically active population ..., op. cit.
15. For further details about ISCED, see UNESCO: International Standard Classification of Education/ISCED 1997 (Paris, 1998); website: http://unescostat.unesco.org/Documents/isced.asp.
16. Resolution concerning statistics of the economically active population ..., op. cit.
17. ILO: Current international recommendations on labour statistics (Geneva, 1988).
18. Resolution concerning the measurement of underemployment and inadequate employment situations, adopted by the 16th International Conference of Labour Statisticians, Geneva, 1998; website: http://www.ilo.org/public/english/120stat/res/underemp.htm.
19. Also known as the LABORSTA database. KILM incorporates several international repository databases and other sources of wage statistics, in addition to LABORSTA. However, to distinguish it from UNIDO data, it is referred to here as the ILO series.
20. This indicator derives hourly compensation costs from national accounts aggregates rather than from KILM 16 (hourly compensation costs).
21. The Gini index measures the extent to which the distribution of income (or in some cases, consumption expenditure) among individuals or households within an economy deviates from perfect distribution. A Gini index of zero represents perfect equality, and 100 perfect inequality.
22. It is important to note the publication's restrictions on coverage, as noted in the overview. The printed version of KILM includes data for the years 1980 and 1990 to the latest year available. The KILM CD-ROM includes all data available, including data in the 1980s not produced in the publication. Therefore, if a "81" appears in the table, indicating 1981 as the latest year for which data are available, readers should note that the data will appear in the KILM CD-ROM but not in the publication.