Key Indicators of Labour Market (KILM)

The labour force participation rate (LFPR) is a measure of the proportion of the working age population in Malaysia who are employed or actively looking for gainful employment. At any point in time in Malaysia, the working age population is defined to be all persons between the ages of 15-64 years old. The LFPR thus provide information on the size of the labour or work force available to engage in productive activities in the economy. The workforce at any point in time is composed of persons who are employed and those who are unemployed, including those looking for employment for the first time or in transition between jobs. In general, the working age population who are not in the labour force are those persons who are in learning or training institutions; those who are retired and have no intention of rejoining the labour market; those who are physically or mentally or health-wise unable to work and those who are otherwise not actively looking for work. The workforce can also be separated by gender, age cohorts and other analytical groups. The workforce and working age population includes Malaysian and non-Malaysian citizens. The LFPR is expressed in percentage and is derived as follows: The data for estimating the LFPR is captured through the Labour Force Survey conducted periodically by the Department of Statistics Malaysia (DOS) using the household survey methodology.

FPR plays a central role in determining the size and composition of the workforce as well as contributing to projecting the future labour force. The variety of profiles that can be generated using this indicator is very helpful for understanding the labour market behaviour of different categories in the population, for example by gender, age group, strata, state and more. LFPR is also crucial in formulating employment policies as well as training needs in efforts to raise the participation rate in the labour market.

Though LFPR is one of the main indicators of the labour market, there are some limitations to analysing the data. The LFPR data are obtained from household surveys which are designed to reflect the specific characteristics of Malaysia. Over time as seen in the indicators above, definitions and coverage may change as the demographic and economic characteristics of the country evolve. Thus great care must be taken when comparing indicators across time and analytical groups to take into consideration variations in concepts and methodologies. This is especially the case when benchmarking against the development in other countries. Labour force data may vary from one country to another, depending on the type of questions asked and the coverage in the survey questionnaires. Moreover, much of the information collected reflect activities in the formal sector of the economy, while there may be important informal activities which may be judged significant enough for consideration and thus need to be captured in the analysis.

For the future there are plans to further disaggregate and analyse the LFPR indicator and undertake additional research to collect evidence to explain the changes and trends observed in this indicators. In particular, further information and understandings are needed to support purposeful efforts to increase the female LFPR in general and to encourage them to remain within the workforce for longer. ILMIA will work with Talent Corporation and the Ministry of Women, Family and Community Development in this endeavour. The Ministry for Women has introduced initiatives for flexible working arrangement for women called “flexWorkLife.my”. This initiative aims to create better connection between employers and employees to optimise work-life balance as well as maximising work efficiency. It also offers many appealing benefits that should help to boost the female participation in the labour market moving forward. There are also plans to undertake further work to better understand not only the LFPR for youth but also other labour market indicators focussed on the young population, e.g. KILM 10.

This ratio provides the answer to the question: "What proportion of the working-age population is employed?". In Malaysia, the working age population is composed of persons 15-64 years old. Relationship to the employment level. While the employment level reflects net changes in the number of jobholders, the employment ratio show net changes in the number of jobholders relative to changes in the size of the population. Because the population is continually growing, a rise in employment may or may not appear as an increase in the employment-population ratio, while a decrease in employment will always be reflected as a decline in the ratio. Relationship to the labour force participation rate (LFPR). The LFPR reflects the proportion of the population who want to work, whereas the employment ratio measures the success of the economy at creating jobs. Relationship to unemployment rate. A lot more attention is focused on the unemployment rate than on the employment-population ratio. However, the concept of unemployment is fuzzier than that of employment. To be counted as unemployed, a person must be without a job, be available for work, and have actively sought a job, or must be on layoff expecting re-employment. To be counted as employed, a person must have worked at least 1 hour during the week for pay or profit (or at least 1 hour as an unpaid worker in a family business), or have a job but is temporarily absent from it. In other words, being employed is an observable experience, while being unemployed often lacks that same concreteness, i.e. seeking a job is not as clear-cut a condition as having a job. The employment to population ratio is presented as a percentage of the relevant population. Members of the armed forces and residents of penal and mental institutions may be excluded. The ratio is further disaggregated by gender; by age groups (usually youth (15-24 years) and adults (25-64 years); and by states or geographical areas. The data for calculating the employment ratio is captured through the Labour Force Survey conducted periodically by the Department of Statistics Malaysia (DOS) using the household survey methodology.

This ratio measures the economy's ability to provide jobs for a growing population and is useful for evaluating demographic employment trends. Put simply it measures whether jobs are being created fast enough for those who want to work. Thus a country with a higher ratio can be said to be more successful in creating jobs to meet the needs of its citizens. Accordingly, persons who are not in employment status are either classified as the unemployed or they choose not to participate in the workforce at all. While a high overall ratio may be considered positive, by itself this is not sufficient to assess if decent work is being created or if there are deficits in decent work within the workplace. Additional information would be needed for such assessment including worker earnings, hours of work, presence of informal sector employment, underemployment and working conditions. Overall, the employment ratio in Malaysia at 63.6 % in 2012 appears to have stagnated as it already stood at 63.5% in 1990. During this period the ratio has tended to fall and was as low as 61% in 2005 only improving marginally to 61.6% in 2010. Since unemployment has been relatively low in Malaysia, this implies that a large part of the population is not participating in the labour force, especially the female population, as depicted by the LFPR under KILM 1. This reflects that while the country has been effective in creating employment as Malaysia progressed towards middle income status, the rate of job creation has been lower than desired as the trend in the ratio is pointing to employment barely keeping pace with the growing population. The rate of employment creation has been quite variable, largely because of the effects of the various global economic crisis that Malaysia has suffered, the latest being the global financial crisis as reflected in the 2010 ratio. More importantly, the stagnant or decline in the employment ratio points to the need for structural changes to drive new growth areas for augmenting the job creation potential of the country, improve LFPR and liberate the economy from the middle-income trap.

Depending on the frequency or timing in the collection of data, seasonality may affect employment creation and thus lead to variations in the employment ratio which has to be appropriately accounted for (for example, employment usually spikes whenever there are festivities such as Eid Mubarak and Chinese New Year). Also when comparing this ratio between countries, variations in the definitions of employment, the population (age bracket, armed forces, etc) and collection methodology (LFS versus household census) have to be taken into consideration.

Other than the general aggregate working age population and employment, which includes both Malaysian citizens and non-citizens, it may be useful to separate the employment ratio to allow a focus only on the situation of citizens. This may contribute to better targeting of policies to improve the skills and educational needs of the youth population to meet market demand and also to support job creation in economically lagging regions/states. It would also be useful to benchmark the trend in various facets of Malaysia’s employment ratio with surrounding Asian economies and other similar countries elsewhere in the world.

The status of employment indicator is used to separate two categories of the total employed workforce in the country. The first predominant group is made up of wage and salaried workers (usually also referred to as employees), the second group represents a range of self-employed workers. The self-employed workers are further divided into 5 sub-groups comprising a) employers, b) own-account workers, c) members of producers’ cooperative, d) contributing family members (also known as unpaid family workers) and e) non classifiable workers. The definition of each category and sub-group follows the ILO standards agreed at the 1993 15th International Conference of Labour Statisticians (ICLS), viz: a. Waged and Salaried workers - these workers usually have the kind of job that is consider as paid employment and usually have oral or written contract of employment with entitlement to basic remuneration. b. Self- employment jobs comprise: - Employers People who work on their own account or with the help of one or few partners and for which their remuneration is directly dependent on the profits from goods and services produced. Employers have the capacity to engage continuously one or more persons as employees. - Own-account workers People who work on their own account or with one or more partners and for which their remuneration is directly dependent on the profit from goods and services produced. However, they do not engage continuously employees to work for them. - Members of producer's cooperatives Workers who receive remunerations through revenue and profits generated by cooperatives producing goods and services. - Contributing family members Workers who are engaged in a market oriented establishment operated by a related person living within the same household and for which they may or may not receive a set remuneration. Workers not classifiable by status are those persons who do not fit into any of the sub groups above or where insufficient information is available. In Malaysia information is available for only 3 sub-groups of the self-employed which are: employers, own account workers and contributing family members. The status of employment data in Malaysia is obtained through the Labour Force Survey that is conducted by The Department of Statistic Malaysia. The two categories of workers in KILM 3 are presented as a percentage of the total employed, and also further disaggregated by socio-economic factors, e.g. gender.

This indicator provides information on the proportion of the working population that are salaried employees, which over time also traces the transition path of a country as it moves from low income to middle income and eventually to high income status. A large proportion of salaried workers is consistent with an economy in advanced development and is associated with the prevalence of decent work. The tendency is for the ratio of salaried workers to rise in the initial stage of economic development reflecting the creation of remunerated jobs in the formal economy, which then peaks before the country enter the high income stage, as a larger proportion of the population become highly skilled and are able to work on their own account or start their own businesses as self-employed or employers particularly in the knowledge-based services sector. The experience from developed economies demonstrates that the services sector become the dominating area of economic activities as the degree of entrepreneurship of the working population prospers. An economy with significant proportion of the workers as self employed without employees and as unpaid family workers is associated with a low level rural agricultural environment with few formal job opportunities and prevalent poverty. Unpaid family workers often have no formal work arrangements, lack elements of decent employment, social security and labour rights. Such workers in self-employed status are considered to be in a vulnerable employment position, which is common in low income countries.

The quality of the questions posed in the LFS is important for collating KILM 3 information. For example, it is not very clear if salaried workers have formal or regular contracts or are casual workers. Moreover, it is unclear if salaried workers have protection from unfair dismissals to be deemed decent work. The category of self-employed as workers in cooperatives is not recorded in Malaysia. When benchmarking against other countries due care has to be taken because of the different definitions and survey methods used by some countries.

Efforts would need to be devoted to better understand the situation of unpaid family workers to ensure decent job status and to move them to salaried worker positions. In recent years, this category of workers has seen increases in the urban areas. Finally, analysis of KILM 3 by state could provide insights into the evolving job markets nationwide.

Employment by sector separates the working population of the country into three broad group of economic activities: namely the agriculture, industry and services sectors. Employment in each sector is usually shown as a percentage of total employment. These three main economic sectors can be disaggregated into additional sub-sectors to provide further details following the International Standard Industrial Classification (ISIC) System. However, ISIC itself has undergone several revision which has expanded the sub-sectoral coverage, the latest version of which is ISIC Revision 4 2008. Catalogue A below conveniently tabulates the evolution of ISIC from Revision 2 1968, to Revision 3 1990, and finally to the current applicable standard from 2008. The data for KILM 4 is captured through the Labour Force Survey conducted periodically by the Department of Statistics Malaysia (DOS) using the household survey methodology. The indicator is further disaggregated by gender, age groups and states or regional areas.

KILM 4 is useful for identifying broad shifts in employment and stages of development as well as identifying individual sub-sectors where employment is growing or stagnating. As the economy move to more developed higher income phases the proportion of jobs have shifted between sectors, usually from agriculture to industry and finally to the services sector. This shift also traces the internal migration of the population from rural to urban areas reflecting greater creation of jobs in the industry and services sectors predominantly in urban locations. In many instances this shift also represents a move from labour intensive primary activities to increased automation in production activities, greater innovation and the knowledge-driven economy. This conglomeration of the population and economic activities are common to the experience of many developed economies. Together with information on vacancies, KILM 4 data on changing job trends in individual sub-sectors provides a useful picture on where labour demand is most pressing. This knowledge then contributes to policy initiatives to improve training and skill upgrading programmes to meet talent shortages in the dynamic growth sectors of the economy to support further productivity improvements. The analysis is focused on employment in the three main economic sectors. Information and analysis of the other sub-sectors will be provided at the next update. In 2014, employment in the services sector accounted for 60.2 % of total employment, much higher than the 46.3% observed in 1990 and in line with the growing importance of the services sector as the economy reached the upper-middle income level of development. By comparisons, in terms of output, the services sector contributed 53.5% of Gross Domestic Product (GDP) in 2014 or 53.8% at current prices. In contrast, the proportion of people finding work in the agriculture sector at 12.3% in 2014 is less than half that in 1990 (26.4%) after showing sustained declines in most years over this period. This trend is consistent with the structural shift in Malaysia’s economy as it progressed from low-value added labour-intensive agro-based production to higher value and more innovative manufacturing and knowledge-based services activities where Malaysia increasingly has better comparative advantage. In terms of output, agriculture contributed just 8.9% of real GDP in 2014 compared to 16% in 1990 and a massive 32% back in 1970. Manufacturing employment has experienced relatively more variability over the years. While employment in industry (comprising of manufacturing, mining and quarrying, electricity and water supply activities) for 2014 recorded 27.5 %, manufacturing was a sector where many people found jobs in the past, 32.3% in 1995, rising from 27.5% in 1990, during Malaysia’s manufacturing boom phase before the new growth areas saw faster job creation in the services sectors.

The limitation and comparability considerations relate mainly to the data collection process. In particular, the definition of employment and the status in employment (KILM 3) if not captured appropriately may cause some distortions or understate employment in some sectors. Thus the self employed, like unpaid family workers and jobs in cooperatives, may be unduly left out thus misrepresenting the share of jobs in the agriculture sector where such persons may be prevalent. Similarly, self-employed service professionals like accountants, financial advisors as well as unpaid family workers in family retail outlets and eateries, may escape capture and thus lead to understatement of service jobs. In transition, the changing ISIC sub-sector classification may affect comparisons where they overlap or when analysing time series trends. Above all most caution is needed when comparing employment by sector information between countries. It must be clear which ISIC codes the country is applying and to make adjustment for countries that include the members of the armed forces in the labour force. Countries may also use different survey methodologies or combine LFS and household census information to generate their KILM 4 data.

More details from the ISIC sub-sectors should be presented in the next round of updates together with the relevant analysis of evolution in employment prospects for the workforce and across gender, age group and geographical dimensions. Selected benchmarking against the experience of other countries will contribute to better contextualising the issues and improve policy formulation to strengthen employment prospects and job creation.

The employment by occupation indicator classifies jobs according to major groups as defined in the 2008 Malaysian Standard Classification of Occupations (MASCO-08). Before 2011 statistics were collected under the 1988 MASCO-88 together with the 1980 Malaysia Dictionary of Occupational Classification. MASCO-08 follows the ILO International Standard Classification of Occupations (ISCO-08). KILM 5 can be further disaggregated by greater granularity in a four-level hierarchical structure for job types; by socio-economic factors e.g. gender; and by skill sets in relation to the levels of education specified following the International Standard Classification of Education (ISCED). MASCO-08 applies three skill levels – skilled or semi-skilled or low skilled workers. With regards to skills, the nature of the work performed in relation to characteristic tasks, defined for each skill level, takes precedence over formal educational requirements. The use of ISCED categories to assist in defining the skill levels does not imply that the skills necessary to perform the tasks and duties of a given job can be acquired only through formal education. The skills may be, and often are, acquired through (both formal & informal) training and experience. The emphasis should be on skills required to carry out the tasks and duties of an occupation, and not on whether a worker employed in a particular occupation is more or less skilled, or more or less qualified, than another worker in the same occupation. The ILO defines occupation as a set of jobs whose main tasks and duties are characterised by a high degree of similarity. A job is a set of tasks and duties performed, or meant to be performed, by one person, including for an employer or in self-employment. MASCO-08 has 9 occupational categories comprising (1) Managers; (2) Professionals; (3) Technicians and associate professionals; (4) Clerical support workers; (5) Service and sales workers; (6) Skilled agricultural, forestry and fishery workers; (7) Craft and related trades workers; (8) Plant and machine-operators and assemblers; and (9) Elementary occupations. Statistics for members of the armed forces and other security agencies are available but not included in MASCO-08 and KILM 5. The data for occupation is captured through the Labour Force Survey conducted periodically by the Department of Statistics Malaysia (DOS) using the household survey methodology.

Occupation statistics are useful for research on workforce and workplace issues ranging from labour market jobs outlook, occupational safety and health to labour market segmentation. Occupational analyses also inform economic and labour policies including supporting educational planning, skills training and employment services. KILM 5 contributes to the identification of changes in skill levels to meet the requirements of industry, provides essential inputs to employment projection models with links to future skills needs, as well as to advice students and jobseekers on expected job prospects and the associated training and educational qualifications. Trends in the proportion of the workforce by occupational categories reflect the country’s transition through various stages of economic development. For example, rising skill requirements are likely to be reflected in a decreasing share of elementary occupations off-set hopefully by rising shares of high-skilled occupational groups such as professionals and technicians. This in turn signals the need for increasing the educational and higher-skills attainment levels, as Malaysia strives to become a knowledge-based innovative high income nation.

There is a need for more detailed information to understand why the trend in skilled workers remains stagnant and against the ETP and NEM aspiration for raising the proportion of skilled workers to 50% of the workforce by 2020. In this endeavour it would be useful to better align MQS and NOSS certification of skills to the information on occupation categories of MASCO-08. Better KILM 5 information will contribute positively to meeting the needed future skill requirements of the economy to achieve the knowledge-based high income nation objective of the NEM.

For the future there are plans to further disaggregate and analyse the LFPR indicator and undertake additional research to collect evidence to explain the changes and trends observed in this indicators. In particular, further information and understandings are needed to support purposeful efforts to increase the female LFPR in general and to encourage them to remain within the workforce for longer. ILMIA will work with Talent Corporation and the Ministry of Women, Family and Community Development in this endeavour. The Ministry for Women has introduced initiatives for flexible working arrangement for women called “flexWorkLife.my”. This initiative aims to create better connection between employers and employees to optimise work-life balance as well as maximising work efficiency. It also offers many appealing benefits that should help to boost the female participation in the labour market moving forward. There are also plans to undertake further work to better understand not only the LFPR for youth but also other labour market indicators focussed on the young population, e.g. KILM 10.

The objective of KILM 7 is to show the amount of time an employed person devotes to work activities (see Box 1 for some definitions). Two primary indicators are used for this purpose. The first indicator is a measure of the number of hours an employed person works per week. The ILO recommends that this work hours per week measure be depicted by six time bands of: a) less than 25 hours; b) between 25 and 34 hours; c) between 35 and 39 hours; d) 40 hours and over; e) between 40 and 48 hours; and f) between 49 and 59 hours. Where available countries may add two additional time bands of 50 hours plus and 60 hours plus. In Malaysia, the work hours per week measure presented here utilizes four bands comprising: a) less than 20 hours; b) between 20 and 29 hours; c) between 30 and 39 hours; and d) 40 hours and over. The second KILM 7 indicator captures the annual average hours actually worked per employed person. In most instances, countries and research institutions derive this indicator from the data from hours worked per week of the overall employed workforce, employing in the process appropriate weights and other statistical adjustments. Some countries also use and combine information from establishment surveys or those coming from the System of National Accounts Framework, in which case the information may focus mostly on wage or salaried workers. This indicator of annual work hours for Malaysia is not provided here and we hope to have it available in the next update of the ILMIA dashboard. In general work time measures the “hours usually worked” in the reference period of a typical work schedule (say one week). This concept needs to be contrasted with the measure of “hours actually work” which represents the modal value of work time over a longer period, i.e. one year. The modal value of the work time is a number or value that appears most often within a set of data. Hours of work are measured for all categories of workers (KILM3 – employment status), whether with or without formal contracts, paid or unpaid, and including the self-employed and family workers. Work time is counted in all locations whether at the physical workplace, in the field, at home, on the road, on business trips, etc. While most often it is expected to cover workers in the formal sector of the economy, there is no reason why it would not also cover workers in the informal sector since this indicator is often collected through household surveys. Work hours include systematic overtime work and is not to be affected by irregular or unusual overtime whether for premium pay, regular pay or without compensation. The measure specifically excludes work time not undertaken on a usual basis. Work measures time spent at the workplace on productive activities (direct hours) as well as other activities that are part of the tasks or duties of the job (related hours). Other activities may include cleaning and preparing working tools, purchasing trips, transporting tasks, transiting to work location other than from home to usual normal workplace, training and skills enhancements required for the job, as well as some on-call duties. Work time includes inactive periods related to the production process or work organization, or when machines or the internet malfunctions, or waiting for business (down time), because workers will still be at the disposal of the employer for other duties (e.g. fire drills, etc.) and the self-employed would engage in other tasks. Work time typically includes short rest periods (resting time) because workers are human beings and there may need to be provisions for cultural norms, e.g. prayer time. However, longer rest periods like lunch breaks are excluded. The annual hours actually worked makes adjustments for part-time and part-year workers, for paid annual, sick and other types of leave (e.g. public holidays, maternity/paternity, etc.), for training/education not directly related to the job even if paid for by employer, as well as for flexibility in daily or weekly work schedules. Some adjustments may be made for labour conflicts resulting in work stoppages if these are frequent and widespread in the country.

In 2008, the 18th International Conference of Labour Statisticians (ICLS) adopted a resolution concerning the measurement of work time. The resolution revised the previous standards on work time set in the 13th conference in 1962, providing better technical guidance and measurement methodologies and guidelines on an expanded menu of indicators aimed at improving the consistency and international comparability of this statistic. The definition for seven concepts of work time of an employed was set forth: 1. Hours actually worked, the key concept of working time defined for statistical purposes applicable to all jobs and to all working persons. Measures time spent in a job for activities that contribute to the production of goods and/or services during a specified reference period. Includes direct hours, related hours, down time and resting time. 2. Hours paid for, linked to remuneration of hours that may not all correspond to production. 3. Normal hours of work, refers to legally prevailing collective hours. 4. Contractual hours of work, individuals are expected to perform according to contractual relationships as distinct from normal hours. 5. Hours usually worked, most commonly in a job over an observation period. Measures regular hours worked above contractual hours. 6. Overtime hours of work, performed beyond contracts or norms. 7. Absence from work hours, when working persons do not work. In Malaysia, KILM 7 information is captured from Labour Force Surveys conducted by the Department of Statistics Malaysia (DOS). This KILM can be further disaggregated by gender, age group and employment status of employers, employees, self-employed and own account workers.

Measuring the level and trends in work time for different groups of persons and for individuals is important when monitoring working and living conditions as well as for analysing economic and broader social developments. In recent years, the use of KILM 7 has drawn increasing attention from two dimensions. The first aspect groups discussions around macroeconomic issues. For example, it has been argued that in the context of the recent global financial crisis developed economies have seen sharp losses in output, with many countries suffering steep increases in and also prolonged unemployment. However, many countries have since experienced some stability in unemployment rates, which has been attributed to adopting flexibility in employment time or hours. The most common practice has been to retain the worker on the payroll but adjust the number of hours worked. For firms the number of hours put in by employees affect the production costs and have implications in determining productivity calculations. Annual hours actually worked in particular are usually used for productivity estimates (output per hour worked) in combination with National Accounts and by economic sectors and sub-sectors wherever sufficiently granular statistical information may be available. There has been increasing interest on the part of both employers and employees in enhancing the flexibility of work time arrangements, while moving away from traditional or standard work time plans. Depending on the industry and occupation, employees have increasing options on work time arrangements. Work time flexibility may be bundled into day or night shifts or weekends; into longer than daily and weekly durations like two-weekly or monthly periods. Workers may thus enter and leave the workplace at different times during a day and increasingly account for work time not only at the physical workplace but also elsewhere, including especially from home. Consequently, it is also becoming a challenge to measure the weekly work time of a worker. A second facet in KILM 7 focuses on the health and well-being of workers directly stemming from the hours they need to work. For example, workers in some developing countries must by necessity be required to work very long hours to secure a decent level of income to support their families because wage levels are wretched. Long working hours may have a negative impact on family and community life. Work time in excess of 50 hours per week is normally considered to be excessive. Long work hours may be voluntary or involuntary giving rise to the notion of “over-employment” where a worker actually desires to work less in the reference period with a corresponding adjustment in earnings. However, this personal choice is unknown and depends very much on cultural norms, the level of economic development and the wages paid.

It is obvious that in KILM 7 the indicator for hours usually worked per week are not strictly comparable to the indicator on annual hours actually worked per employed person. It is common that the hours actually worked would normally be higher than the hours usually worked because the latter makes no adjustments for temporary reductions in work time from annual leave, sickness, public holidays, etc. Moreover seasonality in some jobs and long period of absence due to festivity seasons may affect the value of these two work time categories. Another major factor accounting for differences is that in some countries significant numbers of people may have more than one job; the main job and another or a third job. It may become unclear if one is measuring the usual or actual work time on the main job or on all jobs for that person. For cross country comparisons, as is common for all KILMs, the various data collection and estimation methods of each jurisdiction represent an important source of variation in the work time indicators. For example, in Malaysia the four time bands for weekly work time is different from current ILO norms and the information available in a few other countries. Household based information may contain readings with greater variations in integrity but has wider coverage compared to data obtained from establishment surveys where record keeping may be more standardized and subject to accounting, auditing or disclosure norms but may be limited to salaried/wage formal sector workers. Accordingly, as recommended by the OECD multiple forms and sources of data gathering would be advisable for work time information, using the standards and agreements from the resolution adopted by the 18th International Conference of Labour Statisticians, 2008 (Box 1). More importantly, it should be noted that the hours usually worked per week and the average annual hours of actual work by employed persons should be mainly used for understanding variations in trend over time and should not be utilized for comparing the level of time actually worked between countries at any point in time.

The next update of KILM 7 should try to include analysis of the average annual actual work time per employed persons. We will also attempt to collect more granular information on work time by industry sub-sector, by occupation, by geographic location and where possible by educational attainment. It would be useful to have information for benchmarking against the staistics from countries in the ASEAN region, others at a similar stage of development as Malaysia and developed ones. In the future, developments in work time could also be analysed in combination with information on household income to obtain a broader understanding about trends in and the relationship between household income and work hours. Working with other stakeholders, including from academia, the implications of work hours and health, family and community life could also be examined.

KILM 8 provides a measure of employment in the informal sector. This information can be used to gauge the contribution of the informal sector to the economy which could then be subsequently treated as input for estimating the Gross Domestic Product (GDP) of a country (1993 System of National Accounts). This concept of informal sector employment is quite awkward and even bewildering to understand because of the wide variations in the definitions of what constitutes the informal sector and what makes up informal employment. It is useful here to clearly understand and to accept the differences in the terms being used, which are explained in the following paragraphs. In accordance with the International Labour Organization (ILO), the informal sector refers to economic activities of workers and entities which are in law or practice not covered by formal arrangements. The informal sector refers to groups of unincorporated informal enterprises owned by households, including informal own-account entities and production units of informal employers. Informal enterprises are small-scale private unincorporated enterprises, with little to no equity capital, does not keep conventional accounts, which are unregistered with the authorities or professional bodies (operating with a trade license or business permit does not constitute registration) and which produce goods or services for sale or barter. All workers in informal enterprises are considered to have employment in the informal sector, whether this represent their main or a secondary job (see Figure 1, the sum of blocks 3 to 8). Informal wage employment refers to all jobs that lack contractual rights, legal status, social protection, health benefits and labour law privileges. Thus it is possible to be informally employed in the formal sector, which gives an aura of clandestinely to it (block 7). Such informal workers would include those that have jobs that are casual or seasonal and are in some instances paid household helpers. Employment in the informal economy (see Figure 1) thus is the sum of a) informal jobs in informal enterprises, including household workers (blocks 6 and 10); b) employers and own-account workers of informal enterprises (blocks 3 and 4); c) informal wage earners in formal sector enterprises (block 2); d) members of informal cooperatives (block 8); e) contributing unpaid family members in formal and informal sector enterprises (blocks 1 and 5); and f) workers producing goods or services for their own consumption (block 9). A summary of employment in the informal sector and employment in the informal economy is depicted in Figure 1 below. Notes: (a) White blocks are types of informal jobs. Blue blocks are types of formal jobs. Black blocks are not applicable. (b) Households are own-account workers producing goods/services exclusively for their own final use and employ household paid domestic workers. Informal employment : Blocks 1 to 6 and 8 to 10. Employment in the informal sector : Blocks 3 to 8. Informal employment outside the informal sector : Blocks 1, 2, 9 and 10. The ICLS approach is based on the measurement of informal employment from an enterprise perspective, so that everyone engaged in an informal enterprise is considered to be in informal employment. Informal enterprises in Malaysia are small-scale private unincorporated enterprises with less than 10 workers and unregistered with Companies Commission of Malaysia (CCM) or professional bodies that produce goods or services for sale or barter. Enterprises have a wide usage here and include those that hire workers, those run by workers on their own account and those involving self-employed workers, sometimes assisted by unpaid family workers. For example, self-employed street vendors, taxi drivers and home-based workers all fall under the definition of enterprise in this usage. Agricultural and related activities as well as households producing goods and services for own consumption are excluded from this enterprise definition. Thus subsistence farming, domestic care and household work are excluded.The information on employment in the informal sector used in KILM 8 here follows the measurement and definitions in accordance with the 1993 Resolution of the 15th International Conference of Labour Statisticians (ICLS) which is also the approach followed by the United Nations Expert Group on Informal Statistics or the “Delhi Group”, established in 1997. The information for KILM 8 is captured through labour force surveys (LFS) conducted periodically by the Department of Statistics Malaysia (DOS) following the 15th ICLS approach, officially available starting in 2012. But there is also the recognition that there are informal workers employed in formal enterprises that should be captured in the statistics for informal workers. Workers in the formal sector show aspects of informality in the sense that they lack contractual rights, legal status, social protection, health benefits and labour law privileges. To take this into consideration the Delhi Group in 2001 agreed to complement the enterprise-based concept of informal employment by including a job-based concept of informal employment, which has broader coverage that would encompass both the formal and informal sectors where informal employment may occur. These two distinct concepts are useful because any suggested policy inventions to reduce informality so as to meet the inclusiveness objective of government would likely be different when targeting informal enterprises and when focussing on informal job-based issues. The main measures of employment in the informal sector are shown as an absolute number (i.e. number of persons employed and not number of jobs) and as a percentage of the non-agricultural employed workforce. Where information is available, these statistics are supplemented by an indicator of employment in the informal economy, which is made up of the sum of employment in the informal sector and informal employment outside of the informal sector (i.e. those informal workers in the formal sector and those not included in the enterprise framework of the main indicator). KILM 8 can be further disaggregated by gender, by age groups, by educational attainment, by status in employment, by industry sector, by state, by strata and other socio-economic dimensions.

In many countries the informal sector may make sizable contributions to the economy with associated importance in employment creation and income generation. The informal economy is found not only in less developed countries but also in middle income economies and some developed nations, where their presence may be quite notable. In countries where the pace of population expansion is faster than formal job creation can keep up with, the informal sector acts as an outlet to provide employment. Similarly, potential social issues from rapid urbanization or large shifts in rural to urban migration may be mitigated by a burgeoning informal economy and informal work. Sometimes, the informal economy is fostered by regulatory arbitrage involving the sub-contracting or outsourcing of economic activities by formal enterprises to the informal sector where compliance with legal, labour, health and environmental regulations are disregarded or deliberated overlooked through bribery. In developed countries, informal employment is associated with workers or enterprises seeking to supplement their income or profits by engaging in irregular activities or underreporting of income (for more details see “A Study on Employment in the Informal Sector of Malaysia” a report commissioned by ILMIA, forthcoming in ILMIA’s portal). The output of goods and services from the informal sector usually costs less than those stemming from the formal market and may be accessible from locations which are more convenient to customers. These features help the clientele of informal sector outputs to stretch their limited financial resources further and save them valuable time in making purchases. Those who use the outputs of the informal sector as inputs in their formal sector productive activities then has a cost advantage to strengthen their competitiveness position relative to other producers. Thus the motivation for informal activity may be attributed to necessity-driven for survival factors and/or opportunity-seeking entrepreneurship incentives. The downside of consuming informal sector outputs are that health and quality standards may be compromised as they would most likely not be complied with. The process within which the informal sector outputs are generated may also lead to violations of labour, other social and environmental standards since they eschew such controls. On balance this may compromise the long-term sustainability objectives and liveability aspirations of the country. The informal sector is sometimes thought of as being economic activities at the margins or fringes of officialdom or regulatory reach. In many instances the informal sector could be confused to being the underground or shadow economy which tends to associate them with criminal or illegal elements of society. Yet it is generally accepted that the goods and services generated by the informal sector are legitimate and satisfies the utility value of the customers who purchase them or barter for them. Outputs from the informal sector should thus be distinctly separated from the criminal activities of drug trafficking, human trafficking, prostitution, illegal gaming, weapons smuggling, the illegal movements of other goods (e.g. timber, cigarettes, alcohol, precious metals or stones, currencies or other monetary instruments, etc.) and money laundering and terrorist financing involving the transfer of proceeds of criminal activities, including funds from tax evasion, corruption, theft, misappropriation, embezzlement, etc. However, it is not often very clear cut as sometimes the line can become blurred, for example counterfeiting luxury and other high-valued goods is frowned upon but seems to have a market whereas counterfeiting currencies or medications are definitely criminal. The existence of informal employment represents a challenge to the authorities as they strive to improve the wellbeing of citizens, ensure a safe working environment, strengthen social protection, foster inclusiveness and reduce income inequalities and poverty. The informal sector is most often associated with poverty, labour exploitation and low productivity. However, for the people actually forming the informal sector, this negative perception is irrelevant as they do not have much of a choice but to survive to the best of their abilities no matter the circumstances. Studies have shown that informal employment tends to expand when the economy experiences an economic downturn or suffers social or political turmoil. For women in particular, employment in the informal sector is an important source of livelihood, where cultural norms may place obstacles for gainful employment outside the home, or where household and family obligations make it impossible for them to take on formal jobs because of limitations in work-hours, labour/legal restrictions, or physical presence at the workplace. Self-employment modes are most common in informal employment which seem to suit women the best. The informal sector may also be where young workers need to turn to for gainful employment if they do not have the requisite qualifications, skills or experience to secure work in the formal economy. This segment of youth could be school dropouts, or face difficult family financial situations forcing them to support the family, or are social outcast from previous illicit activities or behaviour. Finally, there is a segment of the population that may be shunned by or face undue obstacles from seeking employment in the formal economy, who may find access to the informal sector to better suit their requirements. This segment comprises people who are physically or slightly mentally challenged (handicapped or orang kurang upaya), ex-convicts, older citizens and undocumented or displaced/asylum seeking individuals.

As is the case for all KILMs, due consideration must be given when making cross country comparisons of informal employment indicators. Differences would naturally arise from variations in data collection and estimation methods which each country utilizes. For KILM 8, differences could arise from the definition of informal enterprises, which includes their size as measured by number of workers and that they should be unregistered, where the understanding of what constitutes registration may vary from country to country. While agricultural activities are generally excluded some countries are more limited in their capability to cover all economic sectors and may only collect data from the manufacturing and main services sectors, while some may limit coverage to narrow geographical areas, i.e. mainly urban neighbourhoods. Countries may also differ in the broader coverage which includes informal cooperatives, domestic household workers and workers producing goods/services for own consumption. To enhance comparability among countries, the Delhi Group published a manual “Measuring informality: a Statistical Manual on the informal sector and informal employment”. This manual assist countries to collect informal sector statistics and provide practical guidance on technical issues.

For the future, attempts would be made to benchmark informal employment in Malaysia against other countries in ASEAN and similarly situated economies from other regions. It would also be useful to link the contributions of the informal sector workers to the GDP of the country. Further details and links to government agencies for facilitating the formalization of the informal sector or to assist informal sector participants would be provided where appropriate. It is also possible that some workers in informal enterprises have formal employment. While such workers would be counted as informal sector employees by virtue of being part of an informal enterprise, for purposes of employment in the informal economy they should be excluded.

The unemployment rate (KILM 9) together with the employment-to-population ratio (KILM2) are the most well-known statistics utilized for explaining the labour market situation at any point of time in most countries around the world. KILM 9 is a stock indicator of employment for which further dynamic situational insights may be obtained through analysis of inflows and outflows of unemployment between observations periods. Information on unemployment flows contribute to a better understanding of variations in unemployment resulting from changes in the pace workers move from a status of employment to one of unemployment and vice versa. Unemployment as defined by 13th International Conference of Labour Statisticians (ICLS) in 1982 refer to a worker “………..who during the reference period was without work, was seeking work in a recent period and is currently available for work………”. Mathematically the unemployment rate is calculated as a ratio resulting from dividing the total number of unemployed by the total working age population or the economically active portion of the population (or the workforce as defined in KILM 1: Labour Force Participation Rate). In Malaysia the working age population is composed of persons 15-64 years old. By definition the workforce would be composed of the sum of the total persons employed and the unemployed. There are several issues related to this definition of unemployment. The most important one is the person who is currently without a job, who potentially could be available for work but nevertheless in currently not actively seeking a job – this person is not considered to be among the unemployed because he/she is also not part of the workforce. Following KILM 1, in general, the working age population who are not in the labour force are those persons who are in learning or training institutions; those who are retired and have no intention of re-joining the labour market; those who are physically or mentally or health-wise unable to work and those who are otherwise not actively looking for work. People who want to work but are not actively seeking work are sometime referred to as the “hidden unemployed”. This segment of the population whether by choice or circumstances are not in the workforce because they may have become disillusioned from past job search attempts and limited job opportunities, faced discrimination or cultural barriers, and have limited job mobility or relocation problems. Some countries consider that this definition of unemployment based on the need to be actively seeking work may not be very helpful, especially for an economy where informal economic activities are prevalent and many people are engaged in self-employment activities. To cater for these anomalies, the 19th ICLS in 2013 created a separate category of “potential labour force” which would be able to accommodate potential job seekers who may not have been actively seeking out a job to be counted as part of the unemployed. The information for KILM 9 in Malaysia uses the 1982 13th ICLS definition of unemployment and is captured through Labour Force Surveys conducted by Department of Statistics of Malaysia (DOS) using the household survey methodology.

KILM 9 provides a measure of workers that are without a job within the workforce. It is usually accepted that an unemployed worker would be considered to be in an undesirable situation. Nevertheless, in some situations short-term unemployment could be considered normal, particularly if the economy is undergoing structural adjustments to better long-term economic sustainability, resulting in the shedding of jobs in failing industries and their replacement hopefully with better jobs in new growth areas. Unemployment may result from short-term or cyclical (seasonal) factors or from more complicating structural or longer-term competitive issues where possible policy responses would differ markedly. In some countries, the trends in the unemployment rates over time are also used to reflect business cycle conditions, with recessionary episodes often associated with higher than usual and/or prolonged unemployment rates. In this connection, government policies during a down business cycle are usually directed at lowering unemployment to an appropriate level. In the economic literature there are voluminous research on what this appropriate level of unemployment should be and which policies are more effective in restoring employment to the economy sustainably. Analyst have developed a notion that unemployment should not be pushed below a “natural unemployment” level beyond which a trade-off involving accelerating inflationary impulses begin to manifest themselves.[1] Associated with this natural employment level is the concept that an economy is enjoying “full employment” if the level of unemployment is close to 3% or below. This level of unemployment may be the natural rate in the sense that the persons who are unemployed are considered to be in-between jobs, either through the normal process of leads and lags in changing jobs, or has the luxury to afford a longer search time to look for a replacement job which satisfy their desire (often referred to as frictional unemployment). For many countries, unemployment rates can be further disaggregated by gender, age groups, occupation, economic sectors and geographically which provides useful information for addressing the vulnerabilities of any of these group of workers facing joblessness. For example, unemployment rates for women are generally higher than for men, which in most instances reflect the fact that jobs suitable for women are in narrower categories compared to those available for men. But most importantly, women have traditionally been most subjected to unemployment stemming from more numerous instances of exit from and re-entry into employment because of family-related issues and obligations. Access to education and training schemes may also have an influence on the unemployment status of women and their success is securing decent jobs. While the unemployment rate may be the most important indicator of hardship suffered by the workforce, there are other supplementary labour market indicators that have to be viewed together in combination to offer a more wholesome view of worker joblessness difficulties. The unemployment rate measures the utilization level of the workforce and the inability of the proportion of workers actively searching for jobs to secure one. Other information on the educational qualifications, work experience, socio-economic background and even ethnic origin may have additional relevance. An important issue is whether there is a worker safety net for a worker who faces unemployment. These should include unemployment insurance benefits, redundancy payments from a previous job and access to employment services providing job search facilities, retraining or upskilling possibilities and relocation assistance to new growth areas. While it is obviously desirable that a country would want to experience low employment rates, this indicator by itself may also conceal some underlying economic problems. Low unemployment could be closely linked to high incidences of poverty, particularly in less developed economies. In poorer and less developed countries in the absence of worker safety nets and effective social welfare systems, a person cannot afford to be without a job to survive and must eke out a living whether in the formal or informal economy. A person may be considered employed even if working just one hour during the week. Thus even if a person is not unemployed, he/she may still be faced with a dire financial situation due to the number of hours work, the wage rate, the location of the job, and other aspects that would need to be taken into consideration, to gauge the living condition of the worker. KILM 9 would need to be seen in conjunction with other indicators to provide a broader picture of the condition of the labour market; including the hours of work under KILM 7; KILM 2: employment to population ratio; KILM 12: time related underemployment; KILM 13: inactivity rates; KILM 3: status in employment; and KILM 18: working poverty and labour productivity. In combination, trends in the different components of the labour market may be evaluated with greater comprehensiveness to address the issues faced by the workforce. The availability of statistical information on unemployment flows may contribute to a better understanding of why high unemployment persist in an economy. The dynamic factors which affect flows into unemployment can often be separated from the factors that affect the flows out of unemployment. The information provides insights into the speed which workers become unemployed following an economic disruption and how fast they are able to find re-employment and where. It can also contribute to estimating probabilities that a worker would become unemployed or when unemployed, the probability of getting another job. This information contributes to the design of policies to understand and address distress in the labour market affecting employment or unemployment. For Malaysia, information on inflows and outflows of unemployment are not yet well developed for analysis purposes.

Due consideration must be given when making cross country comparisons of the unemployment rates, because as is a common issue for all KILMs differences would naturally arise from variations in data collection and estimation methods which each country utilizes. For KILM 9, other than labour force surveys (LFS), some countries also rely on population census, household surveys and official estimates in the presentation of the unemployment rate. Many countries (especially developed economies or those with unemployment insurance benefits) also show data for the registered unemployed, as compared to the total unemployment derived from LFS. There are also differences arising from the “potential labour force” where the notion of actively seeking work has been granted a more relaxed definition, thus giving rise to measurement anomalies in both the unemployment rate, the employment ratio and even the labour force participation rate. Also the number of observations during the year on the unemployment situation may account for differences. In countries where there are greater frequency of observations, seasonality factors affecting the workforce would generate differences compared to countries with less frequent or only annual observations. Some countries may have geographical limitations in their collection of employment and unemployment data, and thus may only limit collections to urban settings or selected large cities, which of course is then not representative of the country as a whole. It is observed that unemployment in urban areas tend to be larger than for rural settings, wherein economic activities are largely agricultural and where workers have less of a choice and are more likely to be employed, whether they are under-employed, self-employed, informal workers, or unpaid family workers. The differences in measures of unemployment may also come from variations in the conceptual framework underlying the meaning of a person actively searching for work. If a country follows the ILO convention, then a person actively looking for work should be using one or more of the following methods – a) applying directly to vacancies on offer by employers; b) visiting an employment exchange office if such services are available; or c) otherwise soliciting jobs by other means, e.g. by joining a job queue for contractors seeking daily helpers, visiting work sites like construction or farms, consider starting a self-employment or business scheme, etc. For example, some countries consider consultation of vacancy advertisements in a newspaper as meeting the active job search criteria. Whereas others consider that this is not sufficient and the workers must actually take steps to apply for the position before they are considered to be searching. In some countries, like in the Caribbean, discouraged workers who have withdrawn from looking for jobs are still considered to be among the unemployed.

Future analysis would include disaggregating the unemployed workers by their educational qualifications, to the extent that such information is available and are sufficiently representative. It is also anticipated that benchmarking would be undertaken of the unemployment rates with countries in ASEAN and similarly situated economies from other regions. It will also be useful to look into options for collection of inflow and outflow information of unemployed workers to better understand trends in the labour market and their links to changes to the economic structural make-up of growth in the nation. [1] For further details on this unemployment-inflation trade-off, sometimes referred to as the Phillip’s Curve phenomenon, please refer to Robert J. Gordon: “The Phillips Curve is Alive and Well:…”, NBER Working Paper No. 19390, August 2013; or Robert J. Gordon: “The History of the Phillips Curve: Consensus and Bifurcation”, Northwestern University, NBER, and CEPR; March 2009.

Ensuring that young people are gainfully employed is generally a major consideration of policy makers regardless of the stage of development of the economy. The term “Youth” used in this indicator covers the segment of the population in the 15 to 24 years age group, while those 25 years and older are considered to be adults. KILM 10 depicts four distinct aspects of youth unemployment: (a) the youth unemployment rate (youth unemployment as a percentage of the youth labour force); (b) the ratio of the youth unemployment rate to the adult unemployment rate; (c) youth unemployment as a proportion of total unemployment; and (d) youth unemployment as a proportion of the youth population. A supplementary indicator, which is useful to have if such information is collected, is a measure of the proportion of the youth population not in employment, education or training, or the “NEET” rate. The NEET thus accounts for the young people who are either unemployed or not in the workforce all together for reasons other than education or training. KILM 10 can be further disaggregated by gender, by state and by strata. The data for estimating KILM 10 is captured through the Labour Force Survey conducted periodically by the Department of Statistics Malaysia (DOS) using the household survey methodology.

In today's modern world, young men and women are faced with increasing challenges, elevated expectations and demands foisted upon them by family and the community, as well as great uncertainties as they embark into the next phase of life in search of gainful employment with financial independence. This experience could be sometimes traumatic for certain people, especially when they are burdened by education-related debts or tight family financial situations. Under these circumstances, the prospect of unemployment, or actual unemployment, or even underemployment may compound the anxieties of young people and lead to disillusionment which at worst may contribute to their withdrawal from participation in the economy. Evidence from industrial countries suffering large youth unemployment rates show that the psychological consequences for young people include greater likelihood of feeling ashamed, rejected, lost, anxious, insecure, down and depressed, isolated and unloved. Unemployed youths are likely to have problems with health, friendships and family life compared to those with work or studying. They have less confidence about the future, are more likely to turn to drugs, think that there is nothing to look forward to and sense that their life has no direction. Some long-term unemployed youth reported having suicidal thoughts. These sentiments are sometimes referred to as the 'scarring effects' of youth joblessness. Youth unemployment has also been shown to have lifelong effects on income and employment stability, because the affected persons start out with weaker early-career credentials, and show lower confidence and resilience in dealing with labour market opportunities and setbacks over the course of their working lives. Relatively large numbers or increasing amount of unemployment among youth could have particularly negative economic implications. Unemployed youth would not be able to contribute effectively to national economic development, especially in this important stage of economic life when their propensity to consume is the largest. In other words, if youth unemployment rates are unduly high, targeted policies to increase youth employment could have multiplier effects for the economy through the boosting of consumer demand and adding to tax revenue. At the same time, there would be incremental enhancements in social benefits as youth disenchantment leading to potential for disturbances, violence or crime would be reduced and youth as a group would sense the inclusiveness of national policies and feel less vulnerable. Gainful decent work also helps youth to escape poverty, be self-sufficient and eschew social dependency while allowing them to fulfil their aspirations and dreams. Against this background, it is not surprising that many governments around the world prioritize concerted efforts and policies to address youth unemployment. But before the authorities can develop programmes and policies to effectively manage youth unemployment they must first understand why young people cannot find jobs. Research and evidence from around the world, applicable to Malaysia, indicate the most common reasons are structural changes in the labour market that affect young people particularly severely, which at times may be further exacerbated by economic recessions or downturns. But a more insidious reason is just plain discrimination by employers. It is understandable that firms prefer older workers because, other than having more experience, they believe adults are more reliable, elicit better trust from customers or clients and have less issues with absenteeism. Thus when the firm faces business troubles or the economy is facing a down cycle, employers tend to use the “last in, first out” principle in downsizing the workforce which mainly negatively affects the youth segment of the workforce. Structural economic changes may include shifts from agriculture and low-end manufacturing to other areas of economic growth. Agriculture and also some areas of manufacturing/factory work has traditionally provided many youth with jobs or apprenticeships. But the progressive shift to services and more dynamic cum innovative sub-sectors of manufacturing (see KILM 4: employment by economic sector in Malaysia) with less labour intensive processes have reduced job opportunities for youth overall, especially for those lacking the skills and educational level to transit into the new growth segments. Moreover, within the growing services sector, transformations stemming from rapid innovation in information technology has also reduced the need for low to semi-skilled office clerical and sales personnel, which has had a particularly negative impact for female youth. Another noteworthy question that needs to be addressed is why unemployed youth cope with the situation much worse than unemployed adults. Everywhere in the world, youth unemployment rates are consistently higher than adult rates and there are some factors unique to young people that shape how the lack of a job is managed. Young people encounter difficulties in the labour market because of lack of work-relevant skills. They also have insufficient knowledge, information and connections on how to acquire the relevant or appropriate skills, especially youth from poor households. In some instances, there is a reputational issue because first-time young workers and their parents perceive that certain jobs or the qualifications identified with training institutions like vocational ones are considered “low” status. They fail to appreciate that these jobs may actually require a high level of skill or that vocational/ specialized training agency offer high skill accredited courses. In some instances, the career prospects and future earning potential may be superior to that of the academic as opposed to that of Technical and Vocational Education and Training (TVET) streams. Young people searching for a job for the first time most often lack knowledge about what the world of work is actually like, and have insufficient understanding of potential career choices. They may also not possess the credentials that could get them started on an upward path, especially when there are limited opportunities for entry-level work that is career oriented. Employers are often reluctant to invest in training young people when more experienced adult workers are available, thus youth is unable to acquire workplace relevant skills, including on cooperation, communication, critical thinking, creativity, and the needs of the enterprise. Another factor accounting for reluctance by firms in hiring young workers maybe inflexibility in labour market regulations which may be antiquated and not responsive to newer job modules or structures of innovative future new growth areas, which calls for greater flexibility in hiring and laying off staff to reflect changing environments and in setting work hours matrices or workplace arrangements. Thus there may be a need to frequently review labour market policies that maybe inevitable affecting youth job prospects to make sure they continue to be consistent with economic realities which may call for greater agility, mobility and transferability in the workforce and the workplace settings. All in all, to address youth unemployment, policy makers need to have effective partnerships with education institutions, training providers, vocational institutions, employment services providers, other engaged stakeholders and enterprises, to help young people reach their full human potential and allow them to make contributions to the workplace and to society at large. Educators do not always know what employers want, yet they always believe that they do. There must be clear efforts to ensure that the transition from the education or training system of youth to the workplace is as close to market needs as possible so that entry-level workers do not face an environment where the expected jobs no longer exist because the system has lagged behind and failed to respond to changes in the labour market demand for workers. Young workers coming out of school may have the skills but not the right ones for where the jobs are being created. Nevertheless, if the youth have a good core repertoire of fundamental skills they could be given supplemental training within a short period to meet the additional skill requirements of enterprises. The proportion of youth not in employment, education or training (NEET), is among the KILM 10 indicators that are currently not published in Malaysia. It would be useful as a measure of the potential untapped human resources for the workforce represented by youth that are not only absent from the labour force and thus not accumulating work experience but are not studying or training for skills to become effective contributors to national output. Thus this NEET segment of the young population is not only excluded from the workforce but also the fruits of society at large in direct contradiction to the aspiration of economic inclusiveness expounded by the NEM. A high NEET rate for female youth would suggest there are significant barriers for entry of women into the workforce, which would need further examination to generate a better understanding and appropriate responses. KILM 10 information on youth unemployment shows the different dimensions affecting young people who are classified as unemployed. Accordingly, the higher the numerical indicator presented in Tables 1-3, the worse off is the situation that the youth segment find themselves in. The four indicators for youth unemployment have a tendency for moving in the same direction, and would in general offer more insights when viewed with other labour market indicators that has information on the youth cohort, e.g. labour force participation rate, employment to population ratio, unemployment by educational level, etc.

As applicable for all KILMs, due consideration must be given when making cross country comparisons of the youth unemployment indicators. Differences would naturally arise from variations in data collection and estimation methods which each country utilizes. For example, the definition of the youth group differs among countries and even within countries different definitions of the youth groupings are utilized for varying purposes. Then there are also issues regarding the definition of unemployment as set out in KILM 9, which may add to differences when comparing country experiences. Most importantly, the timing in the collection of information is critical, as known periods within which people leave school or other learning institutions or the onset of school breaks or vacation time, would have a direct influence on measuring unemployment, which may vary significantly over the year.

For the future, attempts would be made to collect the ratio for NEET to better understand youth unemployment. ILMIA would also work towards further disaggregating the youth unemployed workers by their educational qualifications and fields of studies, analysis of which would be useful for improving the employability of youth, to the extent that such information is available and are sufficiently representative. It may also be useful to look into the factors that account for variations in KILM 10 indicators among states and the federal territories, so that state and federal administrators can better target policies to address youth unemployment. Finally, a benchmarking could be undertaken of the youth unemployment rates among countries in ASEAN and similarly situated economies from other regions.

While being unemployed could be considered a distressing experience for a person, the length of time that someone is unemployed and seeking a job add further dimensions of pain and stress on the self-esteem of individuals in suffering unemployment. Normally, two measures are used in this indicator to evaluate unemployment. One presents long-term employment as all persons without a job continuously for more than a year (12 months). The second measure classifies the amount of individuals into different unemployment duration clusters. The long-term unemployment indicator is further separated into: a) the long-term unemployment rate – measured as the sum of all those unemployed for longer than a year as a percentage of the labour force; b) the incidence of long-term unemployment – measured as the sum of all those unemployed longer than a year as a percentage of the total unemployed. As recommended by the ILO, the unemployment duration clusters include the amount of unemployed in each cluster and their share among the total unemployed in six duration clusters of: a) less than one month; b) one month to less than three months; c) three months to less than six months; d) six months to less than twelve months; and e) twelve months or more. The data for KILM 11 is captured through the Labour Force Survey conducted periodically by the Department of Statistics Malaysia (DOS) using the household survey methodology. The indicator is further disaggregated by gender and age groups as highlighted in next section.

Long-term unemployment leads to the accumulation of a host of undesirable effects for the individual. Other than income loss and the shame of being unable to provide for the family, prolonged unemployment perpetuates diminishing employability of the worker. In many countries the presence of an effective worker safety net, like unemployment insurance, provides temporary loss-of-income compensation payments. Additionally, employment services may help the unemployed to seek a new position or facilitate training to upskill and thereby contribute to diversifying options for re-employment. However, such assistance are usually limited in duration and serves to sustain the short-term unemployed, but the longer-term unemployed would require distinct help to get out of their predicament. Such assistance becomes more difficult to put in place if the rate of long-term unemployment is high, leading to complications on the social and political front. The chances that the long-term unemployed become disillusioned with work life becomes very high leading to withdrawal into inactive status as described in KILM 13. In this instance, any reduction in the unemployment rate is probably not a favourable outturn. An increasing ratio in long-term unemployment, as has been observed in developed economies in Europe and North America in the aftermath of the recent global financial crisis, usually signals that the economy must undergo structural changes in the labour and product/services markets to encourage the sustain creation of jobs for the workforce. Policies to address long-term unemployment merits special attention and have to be tailored to the special needs of this segment of diverse jobseekers. KILM 11 is thus useful for identifying the size and more importantly the trend of long-term unemployment and the characteristics of the persons within this group, e.g. gender, age group, their educational attainment and skill levels, and their geographic location. If the long-term unemployment is attributed to the lack of jobs then help has to be focused on job creation. It is generally accepted that the longer a person is without a job, the less likely he/she is likely to find one. In this situation, the personal attributes of the long-term unemployed then needs to be taken into consideration. If a large proportion of the unemployed are older workers with skills sets and experience that are no longer in demand, which is likely the case when the country transforms from low performing industries to more dynamic ones, the retraining and reskilling efforts coupled with relocation would need priority. If the unemployed are mostly young people, their situation is likely to be more dire, as even assuming there is unemployment insurance, they are not likely to qualify thus making them face more pronounce financial hardship because they have insuffient to no savings to fall back on. Also, prolonged unemployment is likely to lead to the young to withdraw from the workforce in resignation. Policies to address the needs of the young would in addition to training and reskilling need to focus on special employment programs and apprenticeships for them to gather the work experience and improve their chances of landing permanent jobs in new areas of growth. With prolonged unemployment, there is also the possibility that workers are pressured to take on any job available, which in many instances may not commensurate with their skill levels and experience, leading to skills related underemployment and the likelihood of a decline in their earnings potential and future employment outlook.

As is common for most KILMs, the limitation and comparability considerations relate mainly to the data collection process. This is especially relevant for KILM 11. Survey timing tend to strongly influence how the duration clusters are populated. Moreover, the presence or absence of effective workers safety nets like unemployment insurance or employment services has a bearing on how many people fall into long-term unemployment or the different duration clusters. For example, the more generous and lengthy the unemployment compensation pay outs persist, the more likely that a worker will stay unemployed to await a better job or take part in training as required by the insurance rules. Another limitation is how individuals response to questions on their duration of unemployment. The responses may be imprecise, particularly if joblessness has been prolonged. The individuals may not recall exactly when they became unemployed, so that 10 months may seem to be one year or longer. Also, the person may have in the interim taken on a temporary job, which may not be considered as real employment and thus claim continuous status as an unemployed. Nevertheless, even with these caveats a measure of long-term unemployment provides an indicator that is important for addressing the special needs of this segment of the unemployed.

We would seek to update KILM 11 with unemployment duration clusters consistent with ILO standards. Moreover, we would need to work further on collecting more details on the long-term unemployed, like the age group clusters, educational attainment and geographic location. It would also be useful to expand the analysis to benchmarking against the experience of other countries in the region and also elsewhere in the world, providing where possible lessons to be drawn on policies adopted to manage long-term unemployment.

Employed person are deemed to be in time-related underemployment if they consider their work hours insufficient and they are willing and available to engage in extra hours of work in the reference period. In the past, this situation was also known as “visible underemployment”. Underemployment could also be understood by workers to involve work hours that are perceived to be “unsatisfactory” because of insufficient hours or insufficient compensation or inadequate recognition of their skill level. The challenge then would be to find an acceptable way to quantify this perception of dis-satisfaction. It was agreed that “visible” underemployment would be best quantified in terms of the hours of work giving rise to the indicator on time-related underemployment. As a corollary, “invisible” underemployment could then be understood to refer to measures in terms of insufficient income earned and the more difficult measurement of productivity forgone because of the underutilization or mismatch of skills. Hence, time-related underemployment is considered as the best indicator to measure underemployed persons in the labour force. The definition of time-related underemployment was first adopted in 1998 at the 16th International Conference of Labour Statisticians (ICLS) and further revised in the 19th ICLS in 2013. Three criteria are considered relevant for this purpose, involving employed persons in a reference period that are: 1. Willing to work additional hours 2. Available to work additional hours 3. Had worked less than a threshold relating to working time The measure of underemployment reflects the desire of workers to seek additional work hours, even if they are not actively seeking them out. This could be contrasted to the definition of unemployment where the person must be actively seeking employment but cannot find any acceptable offers. This means that if potential workers are not actively seeking employment they are considered to be inactive or outside the labour force (see KILM 1 and 9). The criteria discussed above give rise to difficulties in standardizing the measurement of desired additional work hours. In an attempt to overcome this problem, there was agreement to use work hour thresholds to designate underemployment by grouping them around three concepts or definition codes: 1. Employed persons reporting as having part-time work or whose hours of work (actual or usual) were below a certain cut-off point involuntarily – “involuntary part-time workers”. 2. Employed persons whose hours of work (actual or usual) were below a certain cut-off point and who wanted to work additional hours. 3. Employed persons whose hours of work (actual or usual) were below a certain cut-off point and who actively sought to work additional hours. Code 3 is considered to be the strictest code and aligned with the definition of unemployment. If available, information from all three codes would provide information on how the amount of underemployment reported differs due to the definitions used. KILM 12 has two measures of the amount of workers in time-related underemployment: a) one as a percentage of the labour force; and b) another as a percentage of total employment. The indicators are further disaggregated by gender and age group. The information is captured through Labour Force Surveys conducted by Department of Statistics of Malaysia (DOS) using the household survey methodology.

KILM 12 is used as a measure of the underutilization of the workforce’s productive capacity. This statistics can be used to supplement information from other KILMs on employment and unemployment to enrich the analysis of the efficiency of the labour market. To give an even broader picture of the condition of the labour market, this indicator could be further assessed in conjunction with other KILMs such as the hours of work under KILM 7; KILM 2: employment to population ratio, KILM 13: inactivity rates, KILM 3: status in employment and KILM 18: working poverty and labour productivity. In combination, analyst would be able to evaluate comprehensively trends in the varied facets of the labour market thus contributing to policies to generate employment for all segments of the workforce. In should be recognized that in most circumstances just identifying whether a person is employed or unemployed does not add very much to better understand the issues certain segments may be facing. So time-related underemployment adds some detail to challenges some citizens face as workers, particularly in situations involving small-scale agriculture activities, the provision of basic services and an array of informal activities, where workers are most often on the edge of survival eking out a living which provide meagre earnings whether in cash or in kind. Few people with these jobs and working only a few hours a week would consider themselves to be gainfully employed, even though in statistical terms they may be classified as such, and therefore KILM 12 would single them out to be a segment of the workforce that deserve some attention. Low unemployment need not necessarily signify that a country’s labour market is functional and near full employment, if time-related unemployment is prevalent. This has implications for the earning levels of the workforce, their productivity capability and a possible mismatch or underutilization of their skills. Furthermore, this may well lead to a situation where a large segment of the workforce is constantly looking for additional work hours or jobs, thereby competing with people who are without a job, particularly young workers first entering the workforce.

As is a common issue for all KILMs, due caution must be taken into consideration when making cross country comparisons because the various data collection and estimation methods of each jurisdiction contribute to important variations in KILM 12 statistics. Most countries count workers who want to have additional hours of activities (code 2), but many countries also predominantly include workers who report involuntary reasons for either not working longer hours or the current hours worked (code 1). However, what constitutes “involuntary” varies across countries giving rise to comparability problems. Finally, very few countries actually ask workers whether they have actively sought to secure more hours of work (code 3). Since no international definition of “part-time” work (KILM 6) has been agreed to, each country may differ in their description of the threshold of “hours actually worked” below which time-related underemployment is said to be present. For example, some countries define the threshold as the legal hours worked, others consider it to be the usual hours worked of full-time employed persons, and the OECD consider the underemployed as those involuntarily working part-time at or below 30 hours a week.

As is a common issue for all KILMs, due caution must be taken into consideration when making cross country comparisons because the various data collection and estimation methods of each jurisdiction contribute to important variations in KILM 12 statistics. Most countries count workers who want to have additional hours of activities (code 2), but many countries also predominantly include workers who report involuntary reasons for either not working longer hours or the current hours worked (code 1). However, what constitutes “involuntary” varies across countries giving rise to comparability problems. Finally, very few countries actually ask workers whether they have actively sought to secure more hours of work (code 3). Since no international definition of “part-time” work (KILM 6) has been agreed to, each country may differ in their description of the threshold of “hours actually worked” below which time-related underemployment is said to be present. For example, some countries define the threshold as the legal hours worked, others consider it to be the usual hours worked of full-time employed persons, and the OECD consider the underemployed as those involuntarily working part-time at or below 30 hours a week. Moving forward Future analysis would be broaden to give information, if available, on which sectors of the economy are susceptible to underemployment. If possible at attempt at highlighting the prevalence of underemployment by broad categories of occupation could also be useful. Finally, while benchmarking with other countries might seem difficult for this KILM we should try to compare at least the trend in this indicator, even if it is not possible to compare the amount of underemployment between countries directly.

The proportion of the working age population (aged 15-64 years) that is not in the labour force makes up the inactivity rate expressed in percent as KILM 13. The inactivity rate thus represents the inverse of the Labour Force Participation Rate (LFPR) presented in KILM 1. Accordingly, the sum of KILM 1 and KILM 13 gives us the working age population within the country, which includes the presence of non-Malaysian citizens. Alternatively, the sum of the employed, the unemployed and the inactive people constitutes the working age population. In general, inactive people are those persons who are in learning or training institutions; those who are retired and have no intention of rejoining the labour market; those who are physically or mentally or health-wise unable to work and those who are otherwise not actively looking for work. Inactive people are also considered to be a) potential job seekers who are not available for work; b) potential jobseekers who are available but not seeking employment; and c) those people who are neither available nor seeking for employment. Inactivity rates are further disaggregated by gender and by age groups. Other than gathering the reasons for why people are inactive, it would also be useful if information is available about the education, skill level and geographical distribution of this segment of the population. The data for estimating KILM 13 is captured through the Labour Force Survey (LFS), conducted periodically by the Department of Statistics Malaysia (DOS) using the household survey methodology.

While much of the discussions on the labour market are focused on the activities and intricacies of the workforce, it is also particularly important to pay attention to developments in the inactive segment of the working-age population. It is useful to understand the evolving reasons for why people who want to work are currently not seeking work. This is very relevant for Malaysia which has a relatively small population and has been facing a tight labour market situation for many years, requiring the rising use of foreign workers. Adopting policy measures or facilitating work-friendly arrangements or flexible work-time systems would potentially entice inactive people into the workforce. The largest segment within the inactive group are women, many of whom are highly educated and skilled, but stay home because of family obligations like childcare or aged parental attention or otherwise for cultural motives which are adverse to traditional forms of employment. This also suggest that households are well off enough to afford having a female spouse (sometimes a male spouse) to not enter the labour market with a preference for tending to the household and bring up children, in many instances with household helpers which are quite prevalent in urban areas. In Malaysia the LFPR among women is much lower than compared to other countries in the region and elsewhere in the world that are economically similarly situated. Thus KILM 13 is an important component for understanding the pattern of the female working age population. Information from inactivity could contribute to continuous efforts to create decent and productive employment by taking into consideration elements that would serve to reduce the proportion of inactive people. Inclusive employment policies are especially pertinent for addressing the needs of persons with disabilities and special challenges. Another important insight that could be provided by KILM 13 is the variation of a segment of the inactive people who have such negative experiences in interacting with the labour market that they have become disillusioned and discouraged, leading them to withdraw altogether from consideration of employment. In an environment where the labour market is tight, like it is for Malaysia, it would be worthwhile to address the causes behind why people have become discouraged and withdraw from job search. Perhaps there is a need to augment job placement and other active employment services to restore hope and thereby lower the inactivity rate.

The quality of the questions posed in the LFS is important for collating KILM 13 information. It may sometimes not be very clear why a person declares he/she is both unavailable for work and is not seeking employment. Moreover, it is unclear if the general and specific reasons for inactivity are recorded in a manner amiable for further analysis. When benchmarking against other countries due care has to be taken because of the different definitions and survey methods used by some countries.

To improve and deepen the analysis of inactive people, greater efforts would be warranted for obtaining information on the education, skill level and geographical distribution of this segment of the population. Additional insights provided by such information would serve to enhance policies for reducing the inactivity rate which would simultaneously increase LFPR and make a slight dent to excessive reliance on foreign worker. In the next update of KILM 13 we hope to have further disaggregation of inactivity by age cohorts, which would present a better picture of evolution in the inactivity rate. We will also provide some benchmark against regional countries and similar extra-regional countries.

KILM 14 shows the distribution of the knowledge base of the labour force which could also be extended to reflect the skills level of the workforce, both employed and unemployed. At the international level, the educational attainment of the work force is usually depicted according to five different categories of schooling: less than one year, pre-primary level, primary level, secondary level, and tertiary level. In Malaysia, consistent with the international norm, the educational attainment is classified into four broad levels comprising - no formal education (including responders giving no information), primary (UPSR), secondary (PMR, SPM, STPM) and tertiary (TVET, Diplomas, Degrees). The categories of educational attainment adopted by Malaysia is based upon the 1997 International Standard Classification of Education (ISCED-97) developed by the United Nations Education, Scientific and Cultural Organization (UNESCO). Details of the Malaysia’s ISCED-97 classification are provided in the table below (source: Department of Statistics). The use of standardized indicators and statistics in the area of education allows developments to be comparable across countries and internationally and thus permit benchmarking and the drawing of policy lessons from the experience of other countries that have undertaken successful reforms of their education and skills training systems. ISCED provides contents on the levels of education and the fields of education. ISCED-97 is an expanded version of the earlier ISCED-76. An updated version, ISCED-2011, with broader classifications is scheduled for implementation by 2014. The ILO states that literacy is defined as the skills to read and write a simple sentence about everyday life. The absence of such skills makes one an illiterate. The definition of illiteracy often varies from country to country. In Malaysia, illiteracy applies to people who have had no formal or informal schooling and have never enrolled in any form of educational or training institutions. The measurements of educational attainment and illiteracy are often disaggregated further by gender and age group. Information for KILM14 are captured through periodic Labour Force Surveys conducted by the Department of Statistics Malaysia using the household survey methodology.

In an economy, human resources (labour) is the most important factor of production, other than capital and land, that in combination contribute to the output of goods and services leading to the generation of income, consumption and trade. To meet the economic growth aspirations of the country, the strength, health and skill levels of the workforce are very important determinants. In this context, the education attainment of the workforce has a direct role in shaping the skill level of workers. There are several ways for portraying skills, which in Malaysia and elsewhere have been represented by both education attainment as well as by occupation as explained in KILM 5. More importantly, in coordination with KILM 5 on occupation, information from KILM 14 on education attainment support the formulation of economic and labour policies as well as provide essential inputs for educational planning or investments, skills training and employment services. KILM 14 also contributes to the identification of the needed changes in skill levels to meet the requirements of industry, provides key variables to employment projection models with links to future skills needs, as well as supply advice to students and jobseekers on expected job prospects and the associated training and educational qualifications. It gives insights into the skills structure in the labour force to determine skills gaps and shortages in the labour market. In addition, the concept of employability must supplement the educational attainment level of the workforce, which requires the acquisition of the requisite core, hard and soft skills. As Malaysia aspires to be a high income nation with a focus on innovative, technological and knowledge-based new growth areas, the educational attainment level must keep pace in order to achieve these objectives. Malaysia is a small open economy with a relatively narrow but tight labour market and thus it must mostly rely on the skill capabilities as reflected in educational attainment of the workforce to successfully compete economically in the global markets in a sustained manner. The information from KILM 14 will help the country to augment and adjust the needed level of skills to be acquired by the workforce through the accumulation of experience at the workplace and supplemented through informal and formal education, training and upskilling. Employment services would need to be expanded to emphasize life-long-learning and human resources functions need to prioritize career management. KILM 14 also provides information about issues surrounding employment creation. Specifically, viewed together with KILM 9 on Unemployment, it provides insight into the relationship of trends in unemployment and educational attainment, especially among the youth population. For example, persistent unemployment among the workforce with tertiary education classified as high skilled, may indicate either issues with employability, i.e. mismatch of skills to jobs available, or more of concern, that the economy is not creating sufficient jobs to accommodate the growing workforce with these educational attainment (see KILM 2 on employment creation). One could have a situation where a worker is pressured to take a job well below the educational or skill level attained because of financial obligations, leading to the presence of skills-related underemployment. In some countries, and may be also in Malaysia, this may lead to a situation of “brain drain” where educated professionals migrate abroad to seek jobs to match their educational or skill levels and aspirations. Minimum basic skills are essential to be an effective worker, which requires some rudimentary literacy and numeracy. The measure of illiteracy is thus an indicator and one measure of how distant the workforce is from supporting sustained growth to allow the population to reduce the incidence of poverty that is closely associated with illiteracy. In Malaysia, illiteracy is no longer an issue for the workforce.

A number of factors limit the comparability of education attainment information over time and across countries. As such information is collated through labour force surveys, over time definitions and coverage may change as the demographic and economic characteristics of the country evolve. This is especially relevant, as ISCED-97 has evolved from ISCED-76 and ISCED-2011 is about to become effective. Even so, different countries have adapted their system to the international standard, which allows some variation and therefore need reconciliation to permit comparability. For example, assigning individuals among the different levels or types of education may differ quite substantially between countries. Many countries have difficulties in mapping the national definition to the standard set by ISCED. This is especially so when considering technical or professional training programmes, short term programmes and adult- oriented programmes. Although illiteracy is not an issue for Malaysia, there some limitations on comparability of this indicator. The main factor is variations in the definition of illiteracy. While Malaysia prefers a definition based on school attendance, many countries utilize the ability to read and write a simple sentence as the yardstick. As countries have diverse social and cultural environments there are also other definitions. Some countries in Africa consider the inability to read a newspaper as illiteracy, while some in Europe would consider as illiterate someone who did not complete primary schooling.

For the future we would want to further disaggregate and analyse KILM 14 supported by additional research to collect evidence to explain the changes and trends observed in the indicators. In particular, further information and understandings are needed for the gender disparity in educational attainment and implications for the economy of the low female LFPR which increasingly are comprised of highly educated women and professionals with the needed critical high skills to drive Malaysia up the high value-added supply chain. At the same time, efforts would be needed to better link educational attainment with employability, skill levels, occupation and the salary structure.