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Last modified by Helena on 2025/07/31 14:18
From version 3.16
edited by Helena
on 2025/06/17 11:45
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To version 3.19
edited by Helena
on 2025/06/17 11:47
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232 232  
233 233  = Data classification =
234 234  
235 -1. Statistics of employment-related income should be classified by economic activity, status in employment and occupation or occupational group, at least according to the major groups and categories of the most recent version of the relevant international classifications. These statistics should be systematically disaggregated by sex in all analyses. Other important variables for cross-classifications of data on income related to employment for pay or for profit are sex, age, level of education, level of skill, seniority in job and the formal or informal status of the job.
236 -1. Disaggregations of the main status in employment categories, as defined in ICSE according to the type of economic risk, may be relevant in order to distinguish specific groups such as owner-operators of corporations from employees, employers from other independent workers, permanent employees from temporary, seasonal or casual employees, etc.
237 -1. In order to measure the relationship between employment and income, account should be taken of all activities performed during the reference year, including simultaneous jobs. The employment experience of individuals during the reference period may be assessed through the identification of periods when they were employed (full or part time), unemployed and out of labour force. At the aggregate level, the main situations may be regrouped into broad categories relevant to the measurement of employment-related wellbeing, such as:
238 -1*. full-year/full-time employment;
239 -1*. part-year/part-time employment with no unemployment:
235 +61. Statistics of employment-related income should be classified by economic activity, status in employment and occupation or occupational group, at least according to the major groups and categories of the most recent version of the relevant international classifications. These statistics should be systematically disaggregated by sex in all analyses. Other important variables for cross-classifications of data on income related to employment for pay or for profit are sex, age, level of education, level of skill, seniority in job and the formal or informal status of the job.
240 240  
241 -o for voluntary reasons; o for involuntary reasons;
237 +62. Disaggregations of the main status in employment categories, as defined in ICSE according to the type of economic risk, may be relevant in order to distinguish specific groups such as owner-operators of corporations from employees, employers from other independent workers, permanent employees from temporary, seasonal or casual employees, etc.
242 242  
243 -1.
244 -1*. part-year employment with some unemployment; ● mainly unemployment: o with some employment; o without employment;
245 -1*. mainly out of labour force with some employment.
246 -1. Further variables may be introduced, such as length of employment, spells and duration of unemployment, etc. Such classifications would permit the identification of the main types of employment-related hardship, the severity of employment problems and the degree of labour force attachment of persons experiencing economic hardship.
239 +63. In order to measure the relationship between employment and income, account should be taken of all activities performed during the reference year, including simultaneous jobs. The employment experience of individuals during the reference period may be assessed through the identification of periods when they were employed (full or part time), unemployed and out of labour force. At the aggregate level, the main situations may be regrouped into broad categories relevant to the measurement of employment-related wellbeing, such as:
247 247  
241 +* full-year/full-time employment;
242 +* part-year/part-time employment with no unemployment:
243 +** for voluntary reasons;
244 +** for involuntary reasons;
245 +* part-year employment with some unemployment;
246 +** mainly unemployment:
247 +** with some employment;
248 +** without employment;
249 +* mainly out of labour force with some employment.
250 +
251 +64. Further variables may be introduced, such as length of employment, spells and duration of unemployment, etc. Such classifications would permit the identification of the main types of employment-related hardship, the severity of employment problems and the degree of labour force attachment of persons experiencing economic hardship.
252 +
248 248  === Periodicity ===
249 249  
250 250  65. Countries should endeavour to regularly collect, compile and disseminate statistics of employment-related income at least every five years.