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Key Statistics of Labour Force in Malaysia March 2018

IM Insights
By IM Insights
4 years ago
Key Statistics of Labour Force in Malaysia March 2018


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  1. EMBARGO : Only to be published or disseminated at 1200 Hours, Thursday, 10 May 2018 DEPARTMENT OF STATISTICS MALAYSIA PRESS RELEASE KEY STATISTICS OF LABOUR FORCE IN MALAYSIA, MARCH 2018
  2. Labour force participation rate 68 .2% Labour force participation rate in March 2018 remained at 68.2 per cent for the three consecutive months. On year-on-year basis, labour force participation rate increased by 0.5 percentage points in March 2018 as compared to March 2017.
  3. Unemployment rate 3 .3% Unemployment rate in March 2018 remained at 3.3 per cent for the two consecutive months. In terms of year-on-year comparison, unemployment rate was 0.1 percentage point lower than March 2017. On a seasonally adjusted month-on-month basis, the unemployment rate (seasonally adjusted) for March 2018 increased 0.1 percentage point to 3.3 per cent. TECHNICAL NOTES This information is derived from the Labour Force Survey (LFS) which was conducted to collect information on the structure and distribution of labour force, employment and unemployment. Concepts and definitions used in LFS are based on the standard guidelines of International Labour Organizations (ILO) through “Manual on Concepts and Methods: Surveys of Economically Active Population, Employment, Unemployment and Underemployment” which is also used by other country. LFS covers both urban and rural areas of all states in Malaysia through personal interview method. The survey population cover persons who live in private living quarters and excludes persons residing in institutions such as hotels, hostels, hospitals, prisons, boarding houses and workers residing in construction work site. The survey comprises of the economically active and inactive population. To measure the economically active population, the LFS uses the age limit of 15 to 64 years. The economically active population comprises of those employed and unemployed whereas those who are inactive is classified as outside the labour force. LFS uses the actual status approach, where a person is classified on the basis of his labour force activity during the reference week. Labour force refers to those who, during the reference week are in the 15 to 64 years (in completed years at last birthday) and who are either employed or unemployed. Employed refers to all persons who, at any time during the reference week worked at least one hour for pay, profit or family gain (as an employer, employee, own-account worker or unpaid family worker). Also considered as employed are persons who did not work during the reference week because of illness, injury, bad weather, leave, labour dispute and social or religious reasons but had a job, farm, enterprise or other family enterprise to return to. Also included are those on temporary lay-off with pay who would definitely be called back to work.
  4. Unemployed Unemployed refers to those who do not have a job but are interested to work . There are two groups of unemployed that is the actively unemployed and inactively unemployed. Outside Labour Force All persons not classified as employed or unemployed as stated above are classified as outside labour force. Includes housewives, students (including those going for further studies), retired, disabled persons and those not interested in looking for a job. Labour Force Participation Rate The economic activity of a population depends on the demographic characteristics of that population. The proportion of economically active population, therefore, differs between sub-groups of that population. These variations are measured by specific activity rates termed as labour force participation rate. Labour force participation rate is defined as the ratio of the labour force to the working age population (15 to 64 years), expressed as percentage. Unemployment rate is the proportion of unemployed population to the total population in labour force. This rate measures the percentage of unemployed population in the labour force. Seasonally adjusted Malaysian economic time series data are affected by major religious festivals such as the Eid-ul Fitr, the Chinese New Year and the Deepavali. The major festivals in this country are usually related to the religious activities and such as, the dates are determined by the respective religious calendar. The dates of these holidays are not in line with the Gregorian calendar. Hence, they tend to move along the Gregorian calendar and has strong seasonal influence on many economic time series data. Since these non-fixed holidays have large impact on the time series data, they need to be taken into account when performing seasonal adjustment process so as to avoid confusion in seasonally adjusted data and trend estimates. Furthermore, the presence of the non-fixed holidays effects may complicate the interpretation of the data. Seasonal adjustment is a process of removing the estimated effects of normal seasonal variation from the original series so that the effects of other influences on the series may be more clearly recognized. Seasonal adjustment can be derived by various methods and the results may vary according to the procedure adopted. The approach used for seasonal adjustment in Malaysia is the Seasonal Adjustment for Malaysia (SEAM). SEAM is a procedure to remove moving holiday effect on the selected Malaysian economic time series data by introducing steps that can be used to overcome the limitations of the existing seasonal adjustment procedure. To apply the SEAM procedure, the XARIMA program in Statistical Analysis Software (SAS) is used. This seasonal adjusted rate will be revised when a complete 12 months time series for the particular year are obtained. Population Benchmarks Population by characteristics of age group, ethnicity and state were used as benchmarks to produce labour statistics. Starting with the monthly release of the Principal Statistics of Labour Force, Malaysia, January 2016, the principal statistics of labour is estimated based on the current population estimates as compared to the previous series which used population projections based on the Population and Housing Census of Malaysia, 2010. This rebase is to obtain statistics that is more consistent with current population structure. Release in PDF.
  5. Released By : DATO' SRI DR. MOHD UZIR MAHIDIN CHIEF STATISTICIAN MALAYSIA DEPARTMENT OF STATISTICS, MALAYSIA DrUzir_Mahidin Dr_Uzir 10 May 2018 Contact person: Ho Mei Kei Public Relation Officer Strategic Communication and International Division Department of Statistics, Malaysia Tel : +603-8885 7942 Fax : +603-8888 9248 Email : mkho[at]