Survey ID Number
YEM_2013_LFS_v01_M
Title
Labour Force Survey 2013-2014
Data Appraisal
COVERAGE ERRORS
Probability sampling requires each element in the target population to have a known non-zero probability of being selected in the sample. This condition is violated if the target population is not fully represented in the sample frame or if the sample selection of units from the frame is not according to the procedures specified in the sample design. The violation of these conditions generates coverage errors.
Coverage errors may occur due to imperfect frame (under-coverage, over-coverage, or duplication of units) or to practical problems such as confusion in boundary of units or in rules of association between units of different types. Coverage errors may also occur at the stage of selection of individual persons in the sample household because of failure to identify some eligible persons, for example, lodgers, domestic workers or other non-family members of the household. It can even happen due to incorrect data on personal characteristics, for example, if the age of the person is incorrectly recorded as below the age set for measuring labour force characteristics (under-coverage error), or vice versa the age is incorrectly recorded as above the threshold age (over-coverage error).
A measure of coverage errors in the LFS 2013-14 is obtained by comparing the number of households in the sampling enumeration area obtained during the listing operations with the corresponding number according to the population census 2004, discussed earlier in connection with Table B5.
NON-RESPONSE ERRORS
Non-response occurs due to failure to obtain the required information from the units selected in the sample (unit non-response) or to failure to obtain some items of information for the selected unit (item non-response). Unit non-response may occur due to incorrect address of the sample household, or inaccessibility of certain dwellings or refusal of the sample household to be interviewed, or because no one was at home when the interviewer contacted the household, or for other reasons. Vacant or demolished dwellings, non-existent or out-of-scope addresses, such as finding an enterprise or workshop instead of a household dwelling, are not generally considered as unit non-response.
Among the 13,167 target sample households, some of 12,646 provided data for all members of the households and 16 for some but not all members. In addition, 323 eligible sample households could not be contacted due to temporary absence and 155 refused to participate in the survey. There were also 11 sample households who could not be contacted because the dwelling was found vacant or the address could not found. Finally, there were 2 sample dwellings found destroyed and an additional 14 that could be interviewed for other reasons.
In total, there were 13,140 eligible households, among which 13,140 responded and 478 not responded, giving a non-response rate of 3.6%. The non-response rate was about the same in all quarters (4.4% in Q1, 3.3% .in Q2, 2.8% in Q3 and 4.0% in Q4). Corrections for non-response errors were made by inflating the design weights for each quarter by the inverse of the response rate (one minus the non-response rate defined above) for each sample enumeration area as described earlier. This procedure assumes that non-respondent households within an enumeration area have similar characteristics as the responding households in those areas.
RESPONSE ERRORS
Response errors refer to errors originating at the data collection stage. In relation to an individual respondent, response errors may occur because the respondent was unwilling to divulge certain information or because the respondent did not know the answer to the question asked or did not fully understand the meaning of the question. Response errors can also occur due memory lapses, for example by forgetting to report an event, or incorrectly reporting its timing. Response errors may also occur because of errors made by the interviewer or by the instrument used for measurement. Interviewers may introduce errors because of haste and misreporting the responses, or because of misunderstanding of the survey concepts and procedures, or preconceptions and subjective biases. The questionnaire itself may be faulty, with wrong question wordings and incorrect skipping patterns.
The measurement of response errors is one of the most difficult parts of quality assessment of survey data. It generally requires carefully designed re-interview programs. In the absence of such data, the quality of survey responses may be assessed by measuring the degree of self-response against proxy-response, or by testing the internal consistency of certain sets of inter-related responses, or by comparison of the survey results with corresponding information from more reliable external sources such as administrative sources.
The total number of teachers in primary and secondary education from the administrative source (229,405) is substantially higher than the corresponding estimate from the labour force survey (171,722). In relative terms, the difference is more significant for secondary education than for primary education. The difference between the two sources may be due to differences in definitions and classifications. The survey estimates refer to teachers in their main jobs, while the administrative source cover all teachers, whether those on their main or secondary activity.
The number of civil service employees from the administrative source (589,806) is about ten percent higher than the corresponding estimate from the labour force survey (533,444). The unaccounted difference (-56’162) may be partly due to civil service employees classified in other branches of economic activity in the labour force, for example, civil service employees employed in public radio and television institutions, or national museums or embassies abroad. The differences between the survey estimates and the administrative source are larger than the sampling errors, especially, for women employees.
Other comparisons with administrative sources may be performed, for example, comparing the survey estimate of the number of unemployed jobseekers reporting to be registered at the labour office or at civil service bureau with the corresponding data from the administrative source.