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.
Institutul National de Statistica Bd Libertatii nr.16 sector 5, Bucuresti
1.6. Contact email address
Restricted from publication
1.7. Contact phone number
Restricted from publication
1.8. Contact fax number
Restricted from publication
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 ...
Ussualy resident population in private households in Romania
Housekeeping concept
Persons living regularly together in the same dwelling and sharing income, household expenditures, food and other essentials for living. A person who lives alone or occupies a separate room in a dwelling (eg tenant) but who declares that he or she does not join with any of the other occupants of the housing unit to form part of a multi-person household is considered to be a single-person household.
Are considered memebers of the household those persons who:
- are usually resident at the address
- provide themselves with food and other essentials for living
- are sharing income or household expenses
15-89 years
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
Usualy resident population
Family home
Term address (if they live in a private household; otherwise - familly home)
The dwelling where they spend most of the time
Family home
The place where the child is found during the reference week
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)
Y
N
Participation is voluntary/compulsory?
Voluntary
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
The sampling plan is a two-stage stratified sample.
Because of the lack of appropriate registers (dwelling register, population register etc), the household surveys carried out by NSI-Romania are based on the repeated use of a master sample, which involves further the use of multi-stage sampling design.
After Census 2011
The primary sampling unit, corresponding to the selection of the master sample, is a group of census section
The secondary (ultimate) sampling unit, corresponding to the selection of the survey sample, is the dwelling.
2020
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 the first stage, a stratified random sample of 792 areas, Primary Sampling Units (PSUs), was designed after the 2011 Census, This is the Multifunctional Sample of Territorial Areas, so called the master sample. EMZOT. The EMZOT sample has 450 PSUs selected from urban area and 342 PSUs selected from rural area.
In the second stage, the dwellings are systematically selected from the initial sample of PSUs. The final quarterly sample consists of 28512 dwellings units. All households within each dwelling are included.
Stratification concerns only the first stage, using as stratification criteria the residence area(urban/rural) and county (NUTS3- level).
There are 88 strata.
Each sampling unit is observed for four quarters according to the rotation pattern 2-(2)-2.
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)
The overall sampling rate, estimated as ratio between number of sampled dwellings, after the two sampling stages, and number of dwelling at country level, is about 1.51 %.
The size of the theoretical yearly sample is 114.048 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)
0.38%
≈ 28512 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)
Wave approach is not used for yearly nor biannually variables. Only 8-year variables are collected on a subsample that consist of wave 2 in each quarter.
NA
NA
NA
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 weights are calculated in three steps. The first step assigns the inverse of the selection probabilities to each sampled dwelling unit. The second step adjusts for non-response, categorising the responding dwelling units by the following characteristics: county (NUTS 3) and urban/rural residency. The third and final steps consists of calibrating the secondary weights to the best latest available population totals by region / urban-rural residency, gender, 14 age groups and the households totals by region, using the SAS macro Calmar
Y
NA
Y
00-14, 15-19, 20-24, 25-29, 30-34, 35-39, 40-44, 45-49, 50-54, 55-59, 60-64, 65-69, 70-74, 75 and over for all the regions, except Bucuresti-Ilfov,where we used more aggregated age groups (0-14, 15-44, 45-64, 65 and over)
NUTS2
Residential area (urban/rural)
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
Average of the quarterly core weights.
NA
NA
NA
NA
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)
See description for quarterly core weights
Y
Number of households, household size
Gender, 5 years age groups (0-14, 15-19, 20-24, 25-29, 30-34, 35-39, 40-44, 45-49, 50-54, 55-59, 60-64, 65-69, 70-74, 75 years old), area of residence (urban/rural), regional(NUTS2-level) breakdown
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 data are collected only by face-to-face interviews (CAPI).
N
Survey Solutions
Are any LFS data collected from registers (Y/N)?
If Yes, please indicate which variables are collected from registers.
N
NA
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
In Romania, official statistics is under the responsibility of National Institute for Statistics. In order to ensure the objectivity, transparent and scientific, character of the methodologies, indicators and classifications used in statistics, and to ensure that statistical programme cover all user requirements, the National Statistics Council was established. The representatives of the Council meet quarterly or more frequent when is necessary in working groups by statistical fields. During these meetings National Institute for Statistics is receiving a strong feed-back from the users in terms of the results already disseminated (including the level of details, breakdowns etc.) and the requests for further needed information to be included in next statistical inquiries.
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?
NUTS3
NUTS2
usually NUTS2
3-year average from the LFS dataset is the method used to produce NUTS-3 unemployment and labour force data sent to Eurostat (to Unit of regional statistics) - if requested
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
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: 15 -74
Age group: 15 -74
Age group: 15 -24
CV
1.06
8.46
8.02
SE
0.57
0.27
1.83
CI(*)
52.83 - 55.08
2.68 - 3.75
19.21 - 26.38
Unemployment-to-population ratio 15-74 (NUTS 2 regions)
CV
SE
CI(*)
RO11
22.53
0.42
1.03 - 2.66
RO12
23.26
0.70
1.64 - 4.39
RO21
21.68
0.83
2.22 - 5.49
RO22
28.86
1.11
1.67 - 6.03
RO31
15.56
0.68
3.05 - 5.72
RO32
12.50
0.23
1.36 - 2.25
RO41
25.29
1.19
2.37 - 7.03
RO42
27.41
0.54
0.92 - 3.04
Description of the assumption underlying the denominator for the calculation of the CV for the employment rate
The denominator in the calculation of the employment rate is in fact the 'known' total of population aged 20-64 used in calibration. Thus, there is no sampling variability
Reference on software used:
Reference on method of estimation:
ReGenesees package in R
Taylor-linearization
(*) 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
4.83
T1= 3.03
T2= 2.85
T3= 2.79
T4= 2.77
Due to the lack of appropriate information, the new dwellings, built after 2011 Census of the Population and Dwellings, that could possibly constitute a sampling frame of the new dwellings, have not been taken into account. Thus, an updates (of the addresses of dwellings) will be envisaged for the PSU included in EMZOT. Under-coverage rate was estimated as the ratio between number of new permanent dwellings, built in the period end of 2011 year (the year of the last census)- end of 2020 year (Source: Romanian Statistical Yearbook, 2022), and number of dwellings at the end of 2020 year (Source: Romanian Statistical Yearbook, 2022). Thus, it was assumed that the proportion of the new dwellings in total dwellings should be the same in the master sample.
Over-coverage rates were estimated on the basis of the survey samples, as ratio between the number of not-eligible dwellings and number of sampled dwellings
NA
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)?
Y
2022 ad-hoc module and DEP module added; 2021 regular module removed; small changes in wording of the questions/ response categories based on the observation of the most frequent errors encountered during 2021
Y
informal check and field test on a small number of questionnaires
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
Y
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
County (NUTS 3 level) and area of residence (U/R)
As it was already mentioned in previous item regarding the computation of the weights, in order to contra balance the non-respondent households, it is proceed at a re-weighting, by adjusting the weights of the respondent households with the inverse of the response rate. The non-response are not globally adjusted, at the entire sample level, but separately, on groups of households, groups generated by the intersection of the variables considered as explicative variables of the non response: county (NUTS 3 level) and area of residence (urban \ rural). This correspond to the so-called 'response-homogenous groups" method, which assumes that in a certain group all the units have the same probability. In order to minimize the effects induced by the presence of non-response another adjustment is done: re-weighting by calibration of the weights.
Substitution of non-responding units (Y/N)
Substitution rate
Criteria for substitution
N
NA
NA
Other methods (Y/N)
Description of method
N
NA
Rates of non-response by survey mode. Annual average
Survey
CAPI
CATI
PAPI
CAWI
POSTAL
13.01
NA
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
12.82
2.87
6.95
2
12.82
2.73
7.09
3
13.24
2.79
7.41
4
13.17
2.69
7.52
Annual
13.01
2.77
7.24
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
201
Subsample_Q1_2021
183
181
Subsample_Q2_2021
181
173
Subsample_Q3_2021
183
180
Subsample_Q4_2021
177
167
Subsample_Q1_2022
193
166
Subsample_Q2_2022
190
196
Subsample_Q3_2022
186
171
Subsample_Q4_2022
189
Total in absolute numbers
754
718
735
707
Total in % of theoretical quarterly sample
2.6
2.5
2.6
2.5
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_Q4_2020
393
Subsample_Q1_2021
393
358
Subsample_Q2_2021
452
402
Subsample_Q3_2021
466
418
Subsample_Q4_2021
488
452
Subsample_Q1_2022
553
450
Subsample_Q2_2022
602
488
Subsample_Q3_2022
592
467
Subsample_Q4_2022
637
Total in absolute numbers
1827
1862
1948
1974
Total in % of theoretical quarterly sample
6.4
6.5
6.8
6.9
Non-response rates. Annual averages (% of the theoretical yearly sample)
NUTS-2 region (code + name)
Non response rate (%)
RO11-Nord-Vest
10.40
RO12-Centru
12.83
RO21-Nord-Est
10.26
RO22-Sud-Est
18.25
RO31-Sud - Muntenia
8.36
RO32-Bucuresti - Ilfov
33.44
RO41-Sud-Vest -Oltenia
2.50
RO42-Vest
8.08
* 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
COBFATH
0.004
-
-
-
Less than 10% item non-response
COBMOTH
0.002
-
-
-
Less than 10% item non-response
CONTRHRS
3.163
3.359
3.173
3.016
Less than 10% item non-response
COUNTRPR
-
-
-
0.746
Less than 10% item non-response
LEAVREAS
0.437
0.237
0.159
2.045
Less than 10% item non-response
MONTHPR
-
-
-
2.768
Less than 10% item non-response
MSTARTWK
-
-
-
2.709
Less than 10% item non-response
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
FINDMETH
2022
Less than 10% item non-response
ISCO08_3DPR
2022
Less than 10% item non-response
NACE2_2DPR
2022
Less than 10% item non-response
STAPROPR
2022
Less than 10% item non-response
(*) "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
aprox. 4%
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
aprox.30%
Main variables
Imputation rate
Describe method used, mentioning which auxiliary information or stratification is used
INCGROSS
aprox.30%
The procedure is using Hot-Deck method, missing items being taken from a donor record. The dentification of the donor record is made on the basis of the sample of respondents, taking into account a set of variables well correlated with the variable to be imputed.
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
NA
NA
NA
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. Europa documents) (Y/N)
Y
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
Not requested for the LFS quality report.
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
NA
Identification of the main job (*)
N
NA
Employment
N
NA
Unemployment
N
NA
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
NA
NA
NA
NA
coverage (i.e. target population)
N
NA
NA
NA
NA
legislation
N
NA
NA
NA
NA
classifications
N
NA
NA
NA
NA
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
N
NA
NA
NA
NA
sample design
N
NA
NA
NA
NA
rotation pattern
N
NA
NA
NA
NA
questionnaire
N
NA
NA
NA
NA
instruction to interviewers
N
NA
NA
NA
NA
survey mode
N
NA
NA
NA
NA
weighting scheme
N
NA
NA
NA
NA
use of auxiliary information
N
NA
NA
NA
NA
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
If an employer also has working contract with his/her own enterprise, he/she will be considered as employee in SBS but as employer in LFS
SBS data: beside survey data, administrative sources (mainly balance sheets) and other statistical surveys data used as well as methods of estimations are applied
LFS estimates on employment (in economic activities covered by both statistics, i.e. from B to N sections, excluding K) is higher than SBS estimates (but LFS comprises own-account workers as well)
No special documentation is produced for both LFS and SBS. For SBS, more detailed methodological information can be retrieved on INS website
Total employment by NACE
SBS does not comprise budgetary sector (public administration, health, education) and part of services
Enterprise' main economic activity is considered - in SBS (as against local unit economic activity in LFS)
UNA
UNA
Number of hours worked
SBS comprise data on hours worked only by employees.
Idem
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
Registered unemployment is measured according to national legislation and differs considerably from ILO unemployment.
LFS unemployment - survey data; Registered unemployment - registered data
UNA
Assessment of the effect of differences of LFS unemployment and registered unemployment
Give an assessment of the effects of the differences
Overall effect
Men under 25 years
Men 25 years and over
Women under 25 years
Women 25 years and over
Regional distribution (NUTS-3)
ILO
18785
108337
17034
94908
Registered
71481
216809
47016
129053
8.4. Coherence - sub annual and annual statistics
Not requested for the LFS quality report.
8.5. Coherence - National Accounts
Coherence of LFS data with National Accounts 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
NA data uses domestic concept;
In NA: LFS is the main data source; LFS data are adjusted for domestic concept with administrative data (from Ministry of Labour, Ministry of Internal Affairs, Ministry of External Affairs) with: -add the non-residents working in Romanian embassies abroad and subtract ones working in foreign embassies in Romania; -add non-resident workers and subtract residents working abroad; - net immigrants in Romania.
No important effects are imposed by differences;
Annual National Accounts Brochure
Total employment by NACE
NA data uses domestic concept;
NA uses the concept of "homogenous industry" (both main and secondary activities are included and are expressed in FTEs)
Adjustments on LFS data by NACE due to reconciliation with other data source, at two digits NACE: - SBS is used for mining and manufacturing; - accounting statements for financial intermediation; - government statistics data for real estate and business services, public administration, other collective services.
No important effects are imposed by differences by total, but increased quality of the NA data in terms of distribution by economic activities is achieved because of using more reliable data sources
idem
Number of hours worked
NA uses concept of actual working hours, in full and part time jobs in main and secondary jobs.
Total hours-worked from LFS (mainand secondary activities) are adjusted with: hours not-worked by women in parental leave
No important differences, but higher then for LFS since all (main and seconday) activities are included
idem
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)
Y
N
N
N
N
N
8.6. Coherence - internal
Not requested for the LFS quality report.
9.1. Dissemination format - News release
Not requested for the LFS quality report.
9.2. Dissemination format - Publications
Please provide a list of type and frequency of publications
Main publications on survey results are: -LFS annual detailed publication; - Statistical Yearbook; - Social Trends
9.3. Dissemination format - online database
Documentation, explanations, quality limitations, graphics etc.
Web link to national methodological publication
Conditions of access to data
Accompanying information to data
Further assistance available to users
Link to the national web page (national language(s)): - online database
Survey results are available on electronic format also. Upon requests data are processed in order to answer to a larger number of users (internal and international). The synthesis of the annual Quality Report is available on INS-WEB (INSSE website) and INTRANET. Data for main indicators are loaded into INS database (TEMPO), also available on the INS-WEB.
Publications on LFS results (published in Romanian and English) contain survey methodology and organisation, analysis (including graphs) and tables with detailed data.
The publications are stored in the electronic library of INS. Upon users request, the entire publication or parts of it may be extracted and delivered in e-format or on paper
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
Data on CD, provided after a contract is signed
Database description
Upon request
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
Please provide information on the policy for anonymizing microdata in your country
Same as Eurostat except few variables
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 ...
Ussualy resident population in private households in Romania
Housekeeping concept
Persons living regularly together in the same dwelling and sharing income, household expenditures, food and other essentials for living. A person who lives alone or occupies a separate room in a dwelling (eg tenant) but who declares that he or she does not join with any of the other occupants of the housing unit to form part of a multi-person household is considered to be a single-person household.
Are considered memebers of the household those persons who:
- are usually resident at the address
- provide themselves with food and other essentials for living
- are sharing income or household expenses
15-89 years
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
Usualy resident population
Family home
Term address (if they live in a private household; otherwise - familly home)
The dwelling where they spend most of the time
Family home
The place where the child is found during the reference week
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)
Y
N
Participation is voluntary/compulsory?
Voluntary
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
The sampling plan is a two-stage stratified sample.
Because of the lack of appropriate registers (dwelling register, population register etc), the household surveys carried out by NSI-Romania are based on the repeated use of a master sample, which involves further the use of multi-stage sampling design.
After Census 2011
The primary sampling unit, corresponding to the selection of the master sample, is a group of census section
The secondary (ultimate) sampling unit, corresponding to the selection of the survey sample, is the dwelling.
2020
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 the first stage, a stratified random sample of 792 areas, Primary Sampling Units (PSUs), was designed after the 2011 Census, This is the Multifunctional Sample of Territorial Areas, so called the master sample. EMZOT. The EMZOT sample has 450 PSUs selected from urban area and 342 PSUs selected from rural area.
In the second stage, the dwellings are systematically selected from the initial sample of PSUs. The final quarterly sample consists of 28512 dwellings units. All households within each dwelling are included.
Stratification concerns only the first stage, using as stratification criteria the residence area(urban/rural) and county (NUTS3- level).
There are 88 strata.
Each sampling unit is observed for four quarters according to the rotation pattern 2-(2)-2.
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)
The overall sampling rate, estimated as ratio between number of sampled dwellings, after the two sampling stages, and number of dwelling at country level, is about 1.51 %.
The size of the theoretical yearly sample is 114.048 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)
0.38%
≈ 28512 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)
Wave approach is not used for yearly nor biannually variables. Only 8-year variables are collected on a subsample that consist of wave 2 in each quarter.
NA
NA
NA
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 weights are calculated in three steps. The first step assigns the inverse of the selection probabilities to each sampled dwelling unit. The second step adjusts for non-response, categorising the responding dwelling units by the following characteristics: county (NUTS 3) and urban/rural residency. The third and final steps consists of calibrating the secondary weights to the best latest available population totals by region / urban-rural residency, gender, 14 age groups and the households totals by region, using the SAS macro Calmar
Y
NA
Y
00-14, 15-19, 20-24, 25-29, 30-34, 35-39, 40-44, 45-49, 50-54, 55-59, 60-64, 65-69, 70-74, 75 and over for all the regions, except Bucuresti-Ilfov,where we used more aggregated age groups (0-14, 15-44, 45-64, 65 and over)
NUTS2
Residential area (urban/rural)
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
Average of the quarterly core weights.
NA
NA
NA
NA
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)
See description for quarterly core weights
Y
Number of households, household size
Gender, 5 years age groups (0-14, 15-19, 20-24, 25-29, 30-34, 35-39, 40-44, 45-49, 50-54, 55-59, 60-64, 65-69, 70-74, 75 years old), area of residence (urban/rural), regional(NUTS2-level) breakdown
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
NA
Identification of the main job (*)
N
NA
Employment
N
NA
Unemployment
N
NA
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
NA
NA
NA
NA
coverage (i.e. target population)
N
NA
NA
NA
NA
legislation
N
NA
NA
NA
NA
classifications
N
NA
NA
NA
NA
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)
