Reference metadata describe statistical concepts and methodologies used for the collection and generation of data. They provide information on data quality and, since they are strongly content-oriented, assist users in interpreting the data. Reference metadata, unlike structural metadata, can be decoupled from the data.
Please take note of the abbreviations used in the report
Abbreviation
Explanation
CV
Coefficient of variation (or relative standard error)
Y/N
Yes / No
H/P
Households/Persons
M?
Member State doesn’t know
NA
Not applicable/ Not relevant
UNA
Information unavailable
NR
Non-response: Member State doesn’t answer to Eurostat request for information. Blank is allowed only in boxes with comments
LFS
Labour Force Survey
NUTS
Nomenclature of territorial units for statistics or corresponding statistical regions in the EFTA and candidates countries
2.1. Data description
Coverage
Coverage
Household concept
Definition of household for the LFS
Inclusion/exclusion criteria for members of the household
Questions relating to employment status are put to all persons aged ...
The whole geographical territory of Portugal is covered, i.e. mainland, Madeira and Açores. Only private dwellings are covered. Persons living as usual residents in collective dwellings are excluded.
The housekeeping concept is used to define households (see the definition of household for the LFS).
Private household means a person living alone or a group of persons who live together, providing oneself or themselves with the essentials of living.
Inclusion criterion: All people who are usually resident, whether related or not related to other members of the private household, are to be considered as members of a private multi-person household if they share household income or household expenses with other household members.
Exclusion criterion: Flatmates or housemates who occupy a housing unit on a house-sharing basis and share only house-related expenses, but not income, shall not be considered as part of a multi-person household occupying this housing unit, even if they share some other subsidiary household expenses.
16 to 89
Population concept
Specific population subgroups
Primary/secondary students
Tertiary students
People working out of family home for an extended period for the purpose of work
People working away from family home but returning for weekends
Children alternating two places of residence
The usual residence for all persons in the target population is established based on the ‘most of the time’ criterion, i.e., a person is assigned to the dwelling where he/she spends the majority of the year (more than 6 months). It means that, when a person regularly lives in more than one dwelling, the dwelling where one spends most of the year is taken as one’s place of usual residence.
Primary/secondary students and persons working away from their family home during the week but returning to their family home for weekends always have their family home as the usual residence.
Tertiary students always have their term address as main residence if it is a private address. They are out of the target population if their term address is a tertiary student hall of residence. These students can also consider their family home as their usual residence in case they benefit from the household
income and are not usual residents of any other private household.
For people living outside the family home for an extended period for the purpose of work, the family home is considered as usual residence in case the person significantly contributes to the household income and is not a usual resident of any other private household.
For people working away from family home but returning for weekends, the family home is considered as usual residence.
Children alternating between two places of residence and spending an equal amount of time with both guardians/parents, the place of usual residence of the legal guardian who receives the child benefits (if applicable) or the place of residence of the legal guardian who contributes more to the child-related costs. If neither of these criteria apply, the place where the child is present during the reference week is taken as the usual residence. This place of usual residence is the same between the first and following interviews unless some life-changing situation occurs.
Reference week
Fixed week (data collection refers to one reference week, to which the observation unit has been assigned prior to the fieldwork)
Rolling week (data collection always refers to the week before the interview)
Yes
No
Participation is voluntary/compulsory?
Compulsory
2.2. Classification system
[not requested for the LFS quality report]
2.3. Coverage - sector
[not requested for the LFS quality report]
2.4. Statistical concepts and definitions
[not requested for the LFS quality report]
2.5. Statistical unit
[not requested for the LFS quality report]
2.6. Statistical population
[not requested for the LFS quality report]
2.7. Reference area
[not requested for the LFS quality report]
2.8. Coverage - Time
[not requested for the LFS quality report]
2.9. Base period
[not requested for the LFS quality report]
3.1. Source data
Sampling design & procedure
Sampling design (scheme; simple random sample, two stage stratified sample, etc.)
Base used for the sample (sampling frame)
Last update of the sampling frame (continuously updated or date of the last update)
Primary sampling unit (PSU)
Final sampling unit (FSU)
Date of sample selection
Two stage cluster sampling.
From the 4th quarter of 2014 onwards the sampling frame is selected from National Dwellings Register (NDR) based on Census 2011 data. The NDR is composed by all private dwellings from Census 2011 (excludes collective households and institutions).
Note: To ensure compliance with the precision criteria laid down in Annex II of the Regulation (EU) 2019/1700 of the European Parliament and of the Council of 10 October 2019, during 2021 the sample size was increased by approximately 7 500 dwellings (the sample size of the previous series was around 22 500 dwellings). Given the sample rotation scheme, this over sample size has been introduced in a phased manner, starting in the 1st quarter of 2021 until the 2nd quarter of 2022 (1 250 dwellings per quarter). From this quarter onwards the sample will be composed by 30 096 dwellings per quarter.
The NDR was built in 2012 and it has been continuously updated using information of national surveys and administrative data.
Geographical areas.
Dwellings
(all households and their respective residents are interviewed).
2022Q1
04-11- 2021
12-11-2021
2022Q2
03-03-2022
11-03-2022
2022Q3
03-05-202
12-05-2022
2022Q4
02-08-2022
12-08-2022
Sampling design & procedure
First (and intermediate) stage sampling method
Final stage sampling method
Stratification (variable used)
Number of strata (if strata change quarterly, refer to Q4).
Rotation scheme (2-2-2, 5, 6, etc.)
In each stratum (NUTS 3) the clusters (geographical areas) were selected systematically with probability proportional to size (number of private dwellings of usual residence). The clusters are composed by one or more contiguous grid INSPIRE cells with 1 km² of area, also aiming to have at least near 300 private dwellings of usual residence in each of them - 1254 PSUs are selected. The selection of PSU are made with probability to size (in the number of private dwellings of usual residence).
Dwellings are selected systematically in each PSU. For each rotation and NUTS 2 region, 300 dwellings are selected by PSU.
NUTS3
7
6
Yearly sample size & Sampling rate
Overall theoretical yearly sampling rate
Size of the theoretical yearly sample
(i.e. including non-response)
(i.e. including non-response)
2.9%
119 130 dwellings
Quarterly sample size & Sampling rate
Overall theoretical quarterly sampling rate
Size of the theoretical quarterly sample
(i.e. including non-response)
(i.e. including non-response)
0.7%
2022Q1 - 28 842 dwellings
2022Q2 - 30 096 dwellings
2022Q3 - 30 096 dwellings
2022Q4 - 30 096 dwellings
Average per quarter - 29 783 dwellings
Use of subsamples to survey structural variables (wave approach)
Only for countries using a subsample for yearly variables
Wave(s) for the subsample
Are the 30 totals for ILO labour status (employment, unemployment and inactivity) by sex (males and females) and age groups (15-24, 25-34, 35-44, 45-54, 55+) between the annual average of quarterly estimates and the yearly estimates from the subsample all consistent? (Ref.: Commission Reg. 2019/2240, ) (Y/N)
If not please list deviations
List of yearly variables for which the wave approach is used (Ref.: Commission Reg. 2019/2240, Annex I)
1st
Y
HHLINK
HHSPOU
HHFATH
HHMOTH
MIGREAS
SIZEFIRM
MAINCLNT
SUPVISOR
TEMPAGCY
TEMPREAS
FINDMETH
WAYJFOUN
NEEDCARE
VARITIME
SHIFTWK
EVENWK
NIGHTWK
SATWK
SUNWK
HWWISH
LOOKOJ
ISCOPR3D
NACEPR2D
STAPROPR
EDUCFED12
HATFIELD
HATYEAR
HATWORK
EDUCNFE12
INCGROSS
GENHEALTH
GALI
Brief description of the method of calculating the quarterly core weights
Is the sample population in private households expanded to the reference population in private households? (Y/N)
If No, please explain which population is used as reference population
Gender is used in weighting (Y/N)
Which age groups are used in the weighting (e.g., 0-14, 15-19, ..., 70-74, 75+)?
Which regional breakdown is used in the weighting (e.g. NUTS 3)?
Other weighting dimensions
The weight is derived as the product of a design weight (which incorporates design information and non-response) and a factor that calibrates the sample to the independent demographic estimates (using a posteriori stratification method by NUTS 2, sex and 5-year age groups; NUTS 3 (or groups of NUTS 3) by six age groups; and NUTS 3 (or groups of NUTS 3) by sex).
N
Total population
Y
Five-year age groups
NUTS 2 and NUTS 3 (or groups of NUTS 3)
NA
Brief description of the method of calculating the yearly weights (please indicate if subsampling is applied to survey yearly variables)
Gender is used in weighting (Y/N)
Which age groups are used in the weighting (e.g., 0-14, 15-19, ..., 70-74, 75+)?
Which regional breakdown is used in the weighting (e.g. NUTS 3)?
Other weighting dimensions
The calculation of the estimates is based on the conditions laid down in Article 9 (6) of Commission Implementing Regulation (EU) 2019/2240. Thus, each individual (respondent) in the sample is assigned a weight that results from the product of three factors:
- an initial weight based on the sample design corresponding to the inverse of the probability of selection of the respective dwelling;
- a correction factor for total non-responses to compensate for the effect of non-responses on the sample size
- a factor that calibrates (or adjusts) the sample to ensure consistency with the annual average estimates of the resident population by NUTS 2 region, sex and five-year age group, as well as the annual average labour status by major age groups, calculated on the basis of the full sample of the IE - 2021 series.
Y
Population by five-year age group (0-4, 5-9; …,75+).
ILOSTAT by age group 16-24, 25-34, 35-44, 45-54, 55-64.
NUTS 2
Brief description of the method of calculating the weights for households
External reference for number of households etc.?
Which factors at household level are used in the weighting (number of households, household size, household composition, etc.)
Which factors at individual level are used in the weighting (gender, age, regional breakdown etc.)
Identical household weights for all household members? (Y/N)
NA
Note: The household weights are equal to the individual weights (living in the same household)
NA
NA
NA
Y
3.2. Frequency of data collection
[not requested for the LFS quality report]
3.3. Data collection
Data collection methods: brief description
Use of dependent interviewing (Y/N)?
In case of Computer Assisted Methods adoption for data collection, could you please indicate which software is used?
The information is obtained directly, through computer-assisted interview. Until the first fortnight of March 2020, the data were collected by using a mixed data collection mode: the initial interview was done face-to-face by an interviewer visiting the household and the other five interviews were done by telephone if certain requirements are met. Following the COVID-19 pandemic and the measures adopted by the competent authorities, Statistics Portugal has decided, as of that date and until further notice, to suspend the face-to-face collection mode, replacing it exclusively with the telephone interview one.
Y
.NET
Are any LFS data collected from registers (Y/N)?
If Yes, please indicate which variables are collected from registers.
N
3.4. Data validation
[not requested for the LFS quality report]
3.5. Data compilation
[not requested for the LFS quality report]
3.6. Adjustment
[not requested for the LFS quality report]
4.1. Quality assurance
[not requested for the LFS quality report]
4.2. Quality management - assessment
[not requested for the LFS quality report]
5.1. Relevance - User Needs
Description of users with respect to the statistical data
The regular users of the LFS data are: Statistics Portugal, Ministry of Labour, Ministry of Finance, Ministry of Economy, Ministry of Education, Portuguese Central Bank, trade unions, public administration services in general, media in general, researchers and universities, OECD, ILO, UNESCO, IMF.
Indication of the needs and uses for which users want the statistical outputs; information on unmet user needs and any plans to satisfy them in the future
UNA
5.2. Relevance - User Satisfaction
[not requested for the LFS quality report]
5.3. Completeness
NUTS level of detail
Regional level of an individual record (person) in the national data set
Lowest regional level of the results published by NSI
Lowest regional level of the results delivered to researchers by NSI
Brief description of the method which is used to produce NUTS-3 unemployment and labour force data sent to Eurostat?
The regional level of the collected data is distrito/município/frequesia
NUTS2
NUTS2
NA
5.3.1. Data completeness - rate
[not requested for the LFS quality report]
6.1. Accuracy - overall
[not requested for the LFS quality report]
6.2. Sampling error
There is no assessment of the contribution of sampling and non-sampling errors on bias, since we do not know the true population values (with the exception of the independent estimates of the population by region NUTS 2, sex and five-year age groups).
6.2.1. Sampling error - indicators
Coefficient of variation (CV) Annual estimates Sampling error - indicators - Coefficient of variation (CV), Standard Error (SE) and Confidence Interval (CI)
Employment rate
Unemployment-to-population ratio
Youth unemployment rate as a percentage of labour force
Age group: 16 -74
Age group: 16 -74
Age group: 16 -24
CV
0.54
2.86
5.94
SE
0.0035
0.0012
0.0113
CI(*)
63.01 - 64.37
3.87 - 4.33
16.82 - 21.25
Unemployment-to-population ratio 16-74 (NUTS 2 regions)
CV
SE
CI(*)
PT11 Norte
4.85
0.0019
3.57 - 4.32
PT16 Centro
7.66
0.0027
2.94 - 3.98
PT17 Área Metropolitana de Lisboa
5.35
0.0027
4.46 - 5.51
PT18 Alentejo
7.69
0.0025
2.80 - 3.79
PT15 Algarve
8.40
0.0034
3.37 - 4.70
PT20 Região Autónoma dos Açores
10.20
0.0040
3.15 - 4.72
PT30 Região Autónoma da Madeira
7.55
0.0035
3.94 - 5.31
Description of the assumption underlying the denominator for the calculation of the CV for the employment rate
The CV for the number of employed persons (aged 16-74) and for the employment rate (aged 16-74) are identical because the denominator of the employment rate (aged 16-74) is the total of population (aged 16-74) which has a zero CV.
Reference on software used:
Reference on method of estimation:
R
Jackknife technique
(*) The value is based on a CI of 95%. For the rates the CI should be given with 2 decimals.
6.3. Non-sampling error
[not requested for the LFS quality report]
6.3.1. Coverage error
Frame quality (under-coverage, over-coverage and misclassifications(b))
Under-coverage rate (%)
Over-coverage rate (%)
Misclassification rate (%)
Comments: specification and impact on estimates(a)
Undercoverage
Overcoverage
Misclassification(b)
Reference on frame errors
UNA
4.41
UNA
With regard to the undercoverage rate, people living in collective households or institutions are excluded from the sampling frame. According to the last Census (2011), this population represents less than 1% of the total population. Nevertheless, calibration ensures that LFS weighted sample sums the estimates of resident population in Portugal.
In addition, the new or renewed buildings and dwellings constructed after the last Census are also excluded, but it is not known the occupation status, that is if they are being used as usual residence or if they are vacant, and the percentage of the population they represent.
UNA
UNA
UNA
(a) Mention specifically which regions / population groups are not suitably represented in the sample.
(b) Misclassification refers to statistical units having an erroneous classification where both the wrong and the correct one are within the target population.
6.3.1.1. Over-coverage - rate
[Over-coverage rate, please see concept 6.3.1 Coverage error in the LFS quality report]
6.3.1.2. Common units - proportion
[not requested for the LFS quality report]
6.3.2. Measurement error
Errors due to the medium (questionnaire)
Was the questionnaire updated for the 2022 LFS operation? (Y/N)
Synthetic description of the update
Was the questionnaire tested? (Y/N)
If the questionnaire has been tested, which kind of tests has been applied (pilot, cognitive, internal check)?
N
NA
NA
NA
Main methods of reducing measurement errors
Error source
Respondent
Letter introducing the survey (Y/N)
Phone call for booking or introducing the survey (Y/N)
Y
N
Interviewer
Periodical training (at least 1 time per year) (Y/N)
Feedbacks from interviewer (reports, debriefings, etc.) (Y/N)
Y
N
Fieldwork
Monitoring directly by contacting the respondents after the fieldwork (Y/N)
Monitoring directly by listening the interviews (Y/N)
Monitoring remotely through performance indicators (Y/N)
IN THIS SECTION INFORMATION REFERS TO THE FINAL SAMPLING UNITS *
Methods used for adjustments for statistical unit non-response
Adjustment via weights (Y/N)
Variables used for non-response adjustment
Description of method
Y
Resident population by NUTS 3
Each individual in the sample receives a weight which is derived as the product of a design weight (which incorporates design information and non-response) and a factor that calibrates the sample to the independent demographic estimates.
Substitution of non-responding units (Y/N)
Substitution rate
Criteria for substitution
N
Other methods (Y/N)
Description of method
N
Rates of non-response by survey mode. Annual average
Survey
CAPI
CATI
PAPI
CAWI
POSTAL
65.35%
31.03%
NA
NA
NA
Non-response rates. Annual average (% of the theoretical yearly sample by survey mode)
Quarter
Non-response rate
Total (%)
of which:
Refusals (%)
Non-contacts (including people who migrated (or moved) internally or abroad) (%)
1
43.99
1.64
35.08
2
46.19
1.72
40.79
3
40.33
2.05
35.92
4
26.38
2.90
20.75
Annual
39.36
2.07
33.28
Units who refused to participate in the survey (Please indicate the number of the units concerned in the cells where the wave is mentioned)
Subsample
Quarter1_2022
Quarter2_2022
Quarter3_2022
Quarter4_2022
Subsample_Q4_2020
40
Subsample_Q1_2021
68
47
Subsample_Q2_2021
91
76
79
Subsample_Q3_2021
89
94
88
142
Subsample_Q4_2021
97
111
124
147
Subsample_Q1_2022
78
76
93
141
Subsample_Q2_2022
97
106
128
Subsample_Q3_2022
102
99
Subsample_Q4_2022
144
Total in absolute numbers
463
501
592
801
Total in % of theoretical quarterly sample
1.61
1.66
1.97
2.66
Units who were not contacted (including people who migrated (or moved) internally or abroad) (Please indicate the number of units only in the cells where the wave is mentioned)
Subsample
Quarter1_2022
Quarter2_2022
Quarter3_2022
Quarter4_2022
Subsample_Q1_2020
1752
Subsample_Q1_2021
2137
2475
Subsample_Q2_2021
1620
2009
1971
Subsample_Q3_2021
1805
2114
2136
1125
Subsample_Q4_2021
1642
2033
2026
1160
Subsample_Q1_2022
932
2264
2267
1294
Subsample_Q2_2022
1001
1560
1110
Subsample_Q3_2022
433
584
Subsample_Q4_2022
451
Total in absolute numbers
9888
11896
10393
5724
Total in % of theoretical quarterly sample
34.28
39.53
34.53
19.02
Non-response rates. Annual averages (% of the theoretical yearly sample)
NUTS-2 region (code + name)
Non response rate (%)
PT11 Norte
41.79
PT15 Algarve
43.95
PT16 Centro
40.15
PT17 Área Metropolitana de Lisboa
41.55
PT18 Alentejo
42.40
PT20 Região Autónoma dos Açores
24.82
PT30 Região Autónoma da Madeira
22.90
* If the final sampling unit is the household it must be considered as responding unit even in case of some household members (not all) do not answer the interview
6.3.3.2. Item non-response - rate
Item non-response (*) - Quarterly data (Compared to the variables defined by the Commission Implementing Regulation (EC) No 2019/2240)
Variable status
Column
Identifier
Quarter 1
Quarter 2
Quarter 3
Quarter 4
Short comments on reasons for non-available statistics and prospects for future solutions
Compulsory / optional
Compulsory
244
TEMPDUR
27.3%
25.8%
25.3%
25.2%
More than half of the non-responses are due to proxy interviews (67.2% average):
2022Q1 - 68.8%
2022Q2 - 66.5%
2022Q3 - 66.2%
2022Q4 - 67.2%
However, non-responses in no-proxy interviews are still significant (32.8% average) and largely concern individuals without formal contracts (without written contracts). Another possible explanation is related to fixed-term contracts for an uncertain period of time (the work lasts for the time necessary to replace an absent worker or to conclude an activity, task or work whose execution justifies its conclusion). As a result, in these particular situations it may not be possible to determine the duration of the work contract.
We will reinforce to the interviewers the need, in case of a non-response, to try to get a more concrete answer whenever possible.
Compulsory
277-279
CONTRHRS
13.6%
12.4%
11.7%
11.2%
More than half of the non-responses are due to proxy interviews (70.4% average):
2022Q1 - 70.8%
2022Q2 - 69.9%
2022Q3 - 71.1%
2022Q4 - 69.9%
Concerning no-proxy interviews (29.6% average), it is relatively common to find respondents who do not know their contractual hours.
We will reinforce to the interviewers the need, in case of a non-response, to try to get a more concrete answer whenever possible.
Compulsory
298-300
HWACTU2J
10.1%
12.7%
More than half of the non-responses are due to proxy interviews (55.2% average):
2022Q1 - 53.9%
2022Q2 - 52.2%
Concerning no-proxy interviews (44.8% average), most of the non-responses were given by self-employed persons. It should be noted that many of the secondary jobs are required to have a certain flexibility in terms of working hours since they have to be combined with the main job. This circumstance could make it difficult to identify the hours actually worked in a secondary job. Additionally, the fact that individuals with a second job are subject to a longer interview may cause fatigue and decrease their cooperation in answering the questions.
We will reinforce to the interviewers the need, in case of a non-response, to try to get a more concrete answer whenever possible.
Item non-response (*) - Annual data (Compared to the variables defined by the Commission Implementing Regulation (EC) No 2019/2240)
Variable status
Column
Identifier
This reference year
Short comments on reasons for non-available statistics and prospects for future solutions
(*) "C" means all the records have the same value different from missing.
6.3.4. Processing error
Editing of statistical item non-response
Do you apply some data editing procedure to detect and correct errors? (Y/N)
Overall editing rate (Observations with at least one item changed / Total Observations )
Y
UNA
6.3.4.1. Imputation - rate
Imputation of statistical item non-response
Are all or part of the variables with item non response imputed? (Y/N)
Overall imputation rate (Observations with at least one item imputed / Total Observations )
Y
Please see information below
Main variables
Imputation rate
Describe method used, mentioning which auxiliary information or stratification is used
INCGROSS derived from "employee (aged 16 to 89) net income variables from main job":
1) Monthly salary (quarterly; all waves).
2) Holiday allowance (annual; only 1st wave).
3) Christmas allowance (annual; only 1st wave).
4) Other types of income (annual; only 1st wave).
1) 17.4%
2) 10.6%
3) 10.8%
4) 44.4%
1) Nearest neighbour imputation: 18 imputation cells/groups: based on the employee monthly salary tax rates by region (Mainland, Azores and Madeira), civil status (single or married/civil union – 1 or 2 holders) and no. of dependents (restricted to with or without dep.). 10 auxiliary variables for distance measure (Euclidean) between receptors and donors: ageclass (4): 16-24; 25-44; 45-64; 65-89 sex (2): male; female hatlevel (3): low (ISCED 0-2); medium (ISCED 3-4); high (ISCED 5-8) isco (9): 0-1; 2; …; 9 nace (17): A; B+D+E; C; F; …; R; S+T+U sizefirm (2): 1-9; 10+ supvisor (2): yes; no temp (2): permanent job; temporary job ftpt (2): full-time; part-time proxy (2): direct participation; another member of the household Extreme values are winsorized to lower limit=1st percentile and upper limit=99th percentile.
2) Deductive imputation.
3) Deductive imputation.
4) Nearest neighbour imputation where the respondent reported to have received or expect to receive (observed or imputed) other types of income. Extreme values are winsorized to lower limit=1st percentile and upper limit=95th percentile.
6.3.5. Model assumption error
[not requested for the LFS quality report]
6.4. Seasonal adjustment
Do you apply any seasonal adjustment to the LFS Series? (Y/N)
If Not, please provide a description of the used methods and tools
N
6.5. Data revision - policy
Do you adopt a general data revision policy fully compliant with the ESS Code of Practice principles? (in particular see the 8th principle) (Y/N)
Are you compliant with the ESS guidelines on revision policy for PEEIs? (ref. Eurostat/documents) (Y/N)
Y (In the Portuguese LFS the revisions have been made every 10 years due to the Census)
Y
6.6. Data revision - practice
[not requested for the LFS quality report]
6.6.1. Data revision - average size
[not requested for the LFS quality report]
7.1. Timeliness
Restricted from publication
7.1.1. Time lag - first result
Restricted from publication
7.1.2. Time lag - final result
Restricted from publication
7.2. Punctuality
The data was sent on time and there were no delays.
7.2.1. Punctuality - delivery and publication
[not requested for the LFS quality report]
8.1. Comparability - geographical
Divergence of national concepts from European concepts
(European concept or National proxy concept used) List all concepts where any divergences can be found
Is there a divergence between the national and European concepts for the following characteristics?
(Y/N)
Give a description of difference and provide an assessment of the impact of the divergence on the statistics
Definition of resident population (*)
N
Identification of the main job (*)
N
Employment
N
Unemployment
N
8.1.1. Asymmetry for mirror flow statistics - coefficient
[not requested for the LFS quality report]
8.2. Comparability - over time
Changes at CONCEPT level introduced during the reference year and affecting comparability with previous reference periods (including breaks in series)
Changes in
(Y/N)
Description of the impact of the changes
Statistics also revised backwards (if Y: year / N)
Variables affected
Break in series to be flagged (if Y: year and quarter/N)
concepts and definition
N
coverage (i.e. target population)
N
legislation
N
classifications
N
geographical boundaries
N
Changes at MEASUREMENT level introduced during the reference year and affecting comparability with previous reference periods (including breaks in series)
Changes to
(Y/N)
Description of the impact of the changes
Statistics also revised backwards (if Y: year / N)
Variables affected
Break in series to be flagged (if Y: year and quarter/N)
sampling frame
Y
Due to the COVID-19 pandemic, the CAPI data collection mode was suspended and replaced exclusively by the CATI mode from the second half of March 2020 to the 2nd quarter of 2022. During this period the sampling frame was restricted to private dwellings as usual residence with telephone.
From the 3rd quarter of 2022 onwards, both the CAPI mode and the usual sampling frame were resumed.
N
N
sample design
Y
Same as above.
N
N
rotation pattern
N
questionnaire
N
instruction to interviewers
N
survey mode
Y
From the 3rd quarter of 2022 onwards, the CAPI mode was resumed.
N
N
weighting scheme
N
use of auxiliary information
N
8.2.1. Length of comparable time series
[not requested for the LFS quality report]
8.3. Coherence - cross domain
Coherence of LFS data with Business statistics data
Description of difference in concept
Description of difference in measurement
Give an assessment of the effects of the differences
Give references to description of differences
Total employment
Staff (persons employed): The persons who during the reference period participated in the business of the firm/institution, regardless of the duration of this participation, under the following conditions: a) staff bound to the enterprise/institution by na employment contract, receiving remuneration in return; b) staff which has ties to the enterprise/institution, who, for not being bound by na employment contract, does not receive regular remuneration for the hours worked or the labour supplied (e.g. owner-managers, unpaid family workers, active members of cooperatives); c) staff with ties to other enterprises/institutions who worked at the enterprise/institution and receive remuneration directly from it; d) persons in the above situations, absent for a period of no more than one month due to holidays, labour dispute, vocational training, as well as disease and occupational accident. The following persons are not considered to be staff: i) those in the situations described in a), b), and c) above and who are absent for a period of over one month; ii) workers with ties to the enterprise/institution who moved to other enterprises/institutions, receiving remuneration directly from the latter; iii) workers in the enterprise/institution whose remuneration is borne by other enterprises/institutions (e.g. temporary workers); iv) self-employed workers (e.g. service providers, that use the so-called 'recibos verdes', which is the popular name of the receipt form).
UNA
See table in item Annexes
UNA
Total employment by NACE
Excluded:
Public administration and defence; compulsory social security;
Activities of households as employers of domestic staff
Extra-territorial organization and bodies
UNA
See table in item Annexes
UNA
Number of hours worked
Covers all units considered in the population.
UNA
UNA
UNA
Coherence of LFS data with registered unemployment
Description of difference in concept
Description of difference in measurement
Give references to description of differences
The registered unemployment includes the individuals registered in a "Centro de Emprego" (on a voluntary basis), who declare: not having a work, seeking for a job as employees and being are available to work.
UNA
UNA
Assessment of the effect of differences of LFS unemployment and registered unemployment
Give an assessment of the effects of the differences
Give an assessment of the effects of the differences
Give references to description of differences
Total employment
Included:
Non residents who work in resident units of production.
Absent from work with assurance of return, receiving or not total or patial payment from the employer.
non paid volunteers whose activity produce goods or services.
Excluded:
Residents who work in non resident units of production.
Included in NA: non-resident border workers + members of the country armed forces stationed in the rest of the world + nationals who are on the staff of diplomatic missions abroad + local employees of general government bodies situated outside the economic territory.
Not included in NA: residents who are border workers or seasonal workers, i.e. who work in another economic territory + members of the armed forces of a foreign country who are stationed in the country + members of armed forces working with international military organisations located on the geographic territory of the country + nationals working in foreign scientific bases established in the economic territory + members of foreign diplomatic missions stationed in the country
See table in item Annexes
International Tourism Expenditure Survey+ Public Accounts and DGAEP (Directorate General for Administration and Public Employment).
Answers LFS: Work Abroad and NACE 99
Total employment by NACE
UNA
UNA
See table in item Annexes
UNA
Number of hours worked
UNA
UNA
UNA
UNA
Which is the use of LFS data for National Account Data?
Country uses LFS as the only source for employment in national accounts.
Country uses mainly LFS, but replacing it in a few industries (or labour status), on a case-by-case basis
Country not make use of LFS, or makes minimal use of it
Country combines sources for labour supply and demand giving precedence to labour supply sources (i.e. LFS)
Country combines sources for labour supply and demand not giving precedence to any labour side
Country combines sources for labour supply and demand giving precedence to labour demand sources (i.e. employment registers and/or enterprise surveys)
Please provide a list of type and frequency of publications
Press release, in Portuguese and English, with the main indicators from the national Labour Force Survey, both quarterly and yearly; a set of tables with more detailed information is simultaneously placed at the Statistics Portugal internet website.
Statistical data bank to enable the users to obtain the tables as they wish.
Anonimysed microdata bases, to be used by researchers under a specific agreement between Statistics Portugal and the Ministry of Science and Technology, quarterly.
Other publications from Statistics Portugal that disseminate labour market data.
9.3. Dissemination format - online database
Documentation, explanations, quality limitations, graphics etc.
Note: The national LFS information is spread across multiple theads, like as: Statistical data, Press releases, Publications, and metada system (concepts, methodological documents).
The LFS regular modules microdata, and the corresponding methodological notes, concepts, questionnaire, etc., are available in DVD/CD-Rom (only for researchers).
For all results considered in a pre-defined set of tables from the national Labour Force Survey, the related coefficients of variation are presented.
The source of information (national Labour Force Survey) is referred with all disseminated/published information.
The anonimysed microdata bases as well as the available information in internet have also methodological notes.
Under specific requests from the users, it is possible to provide crossed tabulations of several variables under certain conditions: they exist in the data base, they have a logical relation in the context of the survey, the results have acceptable levels of quality (e.g., they respect the reliability limits followed by Statistics Portugal for this survey).
All information can be provided in several possible supports: paper, CD, by e-mail or by downloading from the site.
9.3.1. Data tables - consultations
[not requested for the LFS quality report]
9.4. Dissemination format - microdata access
Accessibility to LFS national microdata (Y/N)
Who is entitled to the access (researchers, firms, institutions)?
Conditions of access to data
Accompanying information to data
Further assistance available to users
Y
Researchers
Statistics Portugal has established a Protocol with the Ministry of Education and Science, with a view to making it easier for researchers to access the statistics they need to carry out their activity. They have to submit some documets on the project for which they need the data, to be accredited as researchers.
Metadata, variable-description and methodological document.
Help on the clarification of the data.
9.5. Dissemination format - other
[not requested for the LFS quality report]
9.6. Documentation on methodology
References to methodological notes about the survey and its characteristics
The Portuguese LFS methodology is described in Documento Metodológico do Inquérito ao Emprego, which is available at the Statistics Portugal website. DocumentacaoMetodologica.
9.7. Quality management - documentation
[not requested for the LFS quality report]
9.7.1. Metadata completeness - rate
[not requested for the LFS quality report]
9.7.2. Metadata - consultations
[not requested for the LFS quality report]
Restricted from publication
11.1. Confidentiality - policy
[not requested for the LFS quality report]
11.2. Confidentiality - data treatment
Please provide information on the policy for anonymizing microdata in your country
The Portuguese LFS microdata anonymization consists in the suppression of personal identification, the variables used in the selection of the sample and of those associated with the fieldwork, as well as the use of top/bottom coding and grouping in several variables in order to eliminate the risk of identification.
[not requested for the LFS quality report]
Coverage
Coverage
Household concept
Definition of household for the LFS
Inclusion/exclusion criteria for members of the household
Questions relating to employment status are put to all persons aged ...
The whole geographical territory of Portugal is covered, i.e. mainland, Madeira and Açores. Only private dwellings are covered. Persons living as usual residents in collective dwellings are excluded.
The housekeeping concept is used to define households (see the definition of household for the LFS).
Private household means a person living alone or a group of persons who live together, providing oneself or themselves with the essentials of living.
Inclusion criterion: All people who are usually resident, whether related or not related to other members of the private household, are to be considered as members of a private multi-person household if they share household income or household expenses with other household members.
Exclusion criterion: Flatmates or housemates who occupy a housing unit on a house-sharing basis and share only house-related expenses, but not income, shall not be considered as part of a multi-person household occupying this housing unit, even if they share some other subsidiary household expenses.
16 to 89
Population concept
Specific population subgroups
Primary/secondary students
Tertiary students
People working out of family home for an extended period for the purpose of work
People working away from family home but returning for weekends
Children alternating two places of residence
The usual residence for all persons in the target population is established based on the ‘most of the time’ criterion, i.e., a person is assigned to the dwelling where he/she spends the majority of the year (more than 6 months). It means that, when a person regularly lives in more than one dwelling, the dwelling where one spends most of the year is taken as one’s place of usual residence.
Primary/secondary students and persons working away from their family home during the week but returning to their family home for weekends always have their family home as the usual residence.
Tertiary students always have their term address as main residence if it is a private address. They are out of the target population if their term address is a tertiary student hall of residence. These students can also consider their family home as their usual residence in case they benefit from the household
income and are not usual residents of any other private household.
For people living outside the family home for an extended period for the purpose of work, the family home is considered as usual residence in case the person significantly contributes to the household income and is not a usual resident of any other private household.
For people working away from family home but returning for weekends, the family home is considered as usual residence.
Children alternating between two places of residence and spending an equal amount of time with both guardians/parents, the place of usual residence of the legal guardian who receives the child benefits (if applicable) or the place of residence of the legal guardian who contributes more to the child-related costs. If neither of these criteria apply, the place where the child is present during the reference week is taken as the usual residence. This place of usual residence is the same between the first and following interviews unless some life-changing situation occurs.
Reference week
Fixed week (data collection refers to one reference week, to which the observation unit has been assigned prior to the fieldwork)
Rolling week (data collection always refers to the week before the interview)
Yes
No
Participation is voluntary/compulsory?
Compulsory
Not Applicable
[not requested for the LFS quality report]
[not requested for the LFS quality report]
[not requested for the LFS quality report]
[not requested for the LFS quality report]
Not Applicable
[not requested for the LFS quality report]
Not Applicable
[not requested for the LFS quality report]
Sampling design & procedure
Sampling design (scheme; simple random sample, two stage stratified sample, etc.)
Base used for the sample (sampling frame)
Last update of the sampling frame (continuously updated or date of the last update)
Primary sampling unit (PSU)
Final sampling unit (FSU)
Date of sample selection
Two stage cluster sampling.
From the 4th quarter of 2014 onwards the sampling frame is selected from National Dwellings Register (NDR) based on Census 2011 data. The NDR is composed by all private dwellings from Census 2011 (excludes collective households and institutions).
Note: To ensure compliance with the precision criteria laid down in Annex II of the Regulation (EU) 2019/1700 of the European Parliament and of the Council of 10 October 2019, during 2021 the sample size was increased by approximately 7 500 dwellings (the sample size of the previous series was around 22 500 dwellings). Given the sample rotation scheme, this over sample size has been introduced in a phased manner, starting in the 1st quarter of 2021 until the 2nd quarter of 2022 (1 250 dwellings per quarter). From this quarter onwards the sample will be composed by 30 096 dwellings per quarter.
The NDR was built in 2012 and it has been continuously updated using information of national surveys and administrative data.
Geographical areas.
Dwellings
(all households and their respective residents are interviewed).
2022Q1
04-11- 2021
12-11-2021
2022Q2
03-03-2022
11-03-2022
2022Q3
03-05-202
12-05-2022
2022Q4
02-08-2022
12-08-2022
Sampling design & procedure
First (and intermediate) stage sampling method
Final stage sampling method
Stratification (variable used)
Number of strata (if strata change quarterly, refer to Q4).
Rotation scheme (2-2-2, 5, 6, etc.)
In each stratum (NUTS 3) the clusters (geographical areas) were selected systematically with probability proportional to size (number of private dwellings of usual residence). The clusters are composed by one or more contiguous grid INSPIRE cells with 1 km² of area, also aiming to have at least near 300 private dwellings of usual residence in each of them - 1254 PSUs are selected. The selection of PSU are made with probability to size (in the number of private dwellings of usual residence).
Dwellings are selected systematically in each PSU. For each rotation and NUTS 2 region, 300 dwellings are selected by PSU.
NUTS3
7
6
Yearly sample size & Sampling rate
Overall theoretical yearly sampling rate
Size of the theoretical yearly sample
(i.e. including non-response)
(i.e. including non-response)
2.9%
119 130 dwellings
Quarterly sample size & Sampling rate
Overall theoretical quarterly sampling rate
Size of the theoretical quarterly sample
(i.e. including non-response)
(i.e. including non-response)
0.7%
2022Q1 - 28 842 dwellings
2022Q2 - 30 096 dwellings
2022Q3 - 30 096 dwellings
2022Q4 - 30 096 dwellings
Average per quarter - 29 783 dwellings
Use of subsamples to survey structural variables (wave approach)
Only for countries using a subsample for yearly variables
Wave(s) for the subsample
Are the 30 totals for ILO labour status (employment, unemployment and inactivity) by sex (males and females) and age groups (15-24, 25-34, 35-44, 45-54, 55+) between the annual average of quarterly estimates and the yearly estimates from the subsample all consistent? (Ref.: Commission Reg. 2019/2240, ) (Y/N)
If not please list deviations
List of yearly variables for which the wave approach is used (Ref.: Commission Reg. 2019/2240, Annex I)
1st
Y
HHLINK
HHSPOU
HHFATH
HHMOTH
MIGREAS
SIZEFIRM
MAINCLNT
SUPVISOR
TEMPAGCY
TEMPREAS
FINDMETH
WAYJFOUN
NEEDCARE
VARITIME
SHIFTWK
EVENWK
NIGHTWK
SATWK
SUNWK
HWWISH
LOOKOJ
ISCOPR3D
NACEPR2D
STAPROPR
EDUCFED12
HATFIELD
HATYEAR
HATWORK
EDUCNFE12
INCGROSS
GENHEALTH
GALI
Brief description of the method of calculating the quarterly core weights
Is the sample population in private households expanded to the reference population in private households? (Y/N)
If No, please explain which population is used as reference population
Gender is used in weighting (Y/N)
Which age groups are used in the weighting (e.g., 0-14, 15-19, ..., 70-74, 75+)?
Which regional breakdown is used in the weighting (e.g. NUTS 3)?
Other weighting dimensions
The weight is derived as the product of a design weight (which incorporates design information and non-response) and a factor that calibrates the sample to the independent demographic estimates (using a posteriori stratification method by NUTS 2, sex and 5-year age groups; NUTS 3 (or groups of NUTS 3) by six age groups; and NUTS 3 (or groups of NUTS 3) by sex).
N
Total population
Y
Five-year age groups
NUTS 2 and NUTS 3 (or groups of NUTS 3)
NA
Brief description of the method of calculating the yearly weights (please indicate if subsampling is applied to survey yearly variables)
Gender is used in weighting (Y/N)
Which age groups are used in the weighting (e.g., 0-14, 15-19, ..., 70-74, 75+)?
Which regional breakdown is used in the weighting (e.g. NUTS 3)?
Other weighting dimensions
The calculation of the estimates is based on the conditions laid down in Article 9 (6) of Commission Implementing Regulation (EU) 2019/2240. Thus, each individual (respondent) in the sample is assigned a weight that results from the product of three factors:
- an initial weight based on the sample design corresponding to the inverse of the probability of selection of the respective dwelling;
- a correction factor for total non-responses to compensate for the effect of non-responses on the sample size
- a factor that calibrates (or adjusts) the sample to ensure consistency with the annual average estimates of the resident population by NUTS 2 region, sex and five-year age group, as well as the annual average labour status by major age groups, calculated on the basis of the full sample of the IE - 2021 series.
Y
Population by five-year age group (0-4, 5-9; …,75+).
ILOSTAT by age group 16-24, 25-34, 35-44, 45-54, 55-64.
NUTS 2
Brief description of the method of calculating the weights for households
External reference for number of households etc.?
Which factors at household level are used in the weighting (number of households, household size, household composition, etc.)
Which factors at individual level are used in the weighting (gender, age, regional breakdown etc.)
Identical household weights for all household members? (Y/N)
NA
Note: The household weights are equal to the individual weights (living in the same household)
NA
NA
NA
Y
Not Applicable
Restricted from publication
Divergence of national concepts from European concepts
(European concept or National proxy concept used) List all concepts where any divergences can be found
Is there a divergence between the national and European concepts for the following characteristics?
(Y/N)
Give a description of difference and provide an assessment of the impact of the divergence on the statistics
Definition of resident population (*)
N
Identification of the main job (*)
N
Employment
N
Unemployment
N
Changes at CONCEPT level introduced during the reference year and affecting comparability with previous reference periods (including breaks in series)
Changes in
(Y/N)
Description of the impact of the changes
Statistics also revised backwards (if Y: year / N)
Variables affected
Break in series to be flagged (if Y: year and quarter/N)
concepts and definition
N
coverage (i.e. target population)
N
legislation
N
classifications
N
geographical boundaries
N
Changes at MEASUREMENT level introduced during the reference year and affecting comparability with previous reference periods (including breaks in series)
Changes to
(Y/N)
Description of the impact of the changes
Statistics also revised backwards (if Y: year / N)
Variables affected
Break in series to be flagged (if Y: year and quarter/N)
sampling frame
Y
Due to the COVID-19 pandemic, the CAPI data collection mode was suspended and replaced exclusively by the CATI mode from the second half of March 2020 to the 2nd quarter of 2022. During this period the sampling frame was restricted to private dwellings as usual residence with telephone.
From the 3rd quarter of 2022 onwards, both the CAPI mode and the usual sampling frame were resumed.
N
N
sample design
Y
Same as above.
N
N
rotation pattern
N
questionnaire
N
instruction to interviewers
N
survey mode
Y
From the 3rd quarter of 2022 onwards, the CAPI mode was resumed.
