Employment and unemployment (Labour force survey) (employ)

Publication thresholds
Annual average estimates	Yearly estimates - wave approach
Limit below which figures cannot be published	Limit below which figures must be published with warning	Limit below which figures cannot be published	Limit below which figures must be published with warning
3 000	6 000	5 000	14 000
Biennial variables estimates	Household estimates	Household average estimates
Limit below which figures cannot be published	Limit below which figures must be published with warning	Limit below which figures cannot be published	Limit below which figures must be published with warning	Limit below which figures cannot be published	Limit below which figures must be published with warning
5 000	14 000	3 000	6 000	3 000	6 000

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 ...
Private households only. Institutional households not covered. Sampling frame covers all dwellings where at least one person has a registered main residence.	Housekeeping Unit	A private household is either: (a) A one-person household that is a person who lives alone in a separate housing unit or who occupies, as a lodger, a separate room (or rooms) of a housing unit but does not join with any of the other occupants of the housing unit to form part of a multi-person household as defined below; or (b) A multi-person household that is a group of two or more persons who combine to occupy the whole or part of a housing unit and to provide themselves with food and possibly other essentials for living. Members of the group may pool their incomes to a greater or lesser extent.	All household members who have their centre of life in the sampled household during the reference week, independent of residence registration.	15+

Population concept	Specific population subgroups
Population concept	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
Usual residence	Family home	Term address (if living in a private household)	Family home	Family home	Most of the time

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)
Week assigned to households during sampling, surveying usually within five weeks following the reference week.	N

Participation is voluntary/compulsory?
Compulsory

Not Applicable

[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
Stratified random sample	Register of Residents	The register is continuously updated.	There is only one sampling unit.	The sampling unit is the dwelling with at least one person with main residence. All the people in the selected dwellings are sampled.	Sampling is done three months before the start of the survey.

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.)
Random Sampling within Bundesländer (NUTS 2).	There is only one.	Stratification is carried out according to Bundesländer (NUTS 2).	Number of strata is constant: 9 (number of Bundesländer in Austria)	5

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)
2.4%	90 000 households gross sample size

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)
0.6%	22 500

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)
NA	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 two steps. In the first step for each record a basic weight which depends on the stratum and the domain is calculated. In the second step the weights are adjusted in such a manner that the resulting distribution is in accordance to the population within the federal provinces (Bundesländer, NUTS 2). Calibration is performed by iterative proportional fitting. The weights are adjusted in such a manner, that the figures correspond to the population with main residence at the beginning of each quarter minus persons in institutional households.

The following specifications are used for calibration:

*) Pbas … total number of persons in private households in NUTS-2 region b (= 1, …, 9), age class a (1 = 0-2 years, 2 = 3-5 years, 3 = 6-9, 4 = 10-14, … (5-year classes) …, 18 = 80-84, 19 = 85+) and sex s (= 1, 2).

*) Pbn … total number of persons in private households in NUTS-2 region b (= 1, …, 9) with nationality n (1 = Austria, 2 = EU-15 without Austria, 3 = EU from 2004 onwards, 4 = European non-EU states, 5 = Turkey, 6 = others).

*) Pbse … total number of persons in private households in NUTS-2 region b (=1, …,9), administrative employment status e (1=standard employment, 2=non-standard employment, 3=self-employment, 4=unemployment, 5=out of labour force) and sex s (=1, 2).

*) Wbg … total number of households in NUTS-2 region b (= 1, …, 9) with g (= 1, 2, …, 5+) residents.

5 year age groups up to 84 years, except for children aged 0 - 2 and 3 - 5 years are weighted separately; last age class ist 85+.

NUTS 2

Nationality (Austria, EU-15 without Austria, EU from 2004 onwards, European non-EU states, Turkey, others),

Size of households (1, 2, 3, 4, 5+),

Register based labour status (standard employment, non-standard employment, self-employment, unemployment, out of labour force)

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 quarterly weights	Same as in quarterly weights	Same as in quarterly weights	Same as in quarterly weights	Same as in quarterly weights

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)
There are no extra weights on household level. All weights are on individual level. Individual weight of each household's reference person is identical with the household weight. The number and size of private households is based on the register based census for the census years (2011, 2021, etc.) and the register-based labour market statistics for the years in between.	Yes, see quarterly weights.	See quarterly weights.	The individual weights are the same for all members of the household.	Y

Not Applicable

Quarterly LFS data Reference period, transmission date and coverage
Quarter	Main dates in the national production process
Quarter	Start date of data collection	End date of the quality check for statistics requested by Eurostat	Date of national publication
1	10 January 2022	25 May 2022	09 Juin 2022
2	11 Arpil 2022	24 August 2022	08 September 2022
3	11 July 2022	23 November 2022	07 December 2022
4	10 october 2022	22 February 2023	14 Mars 2023

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	However, prospective information (intention to stay at least one year) is not available
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	N	NA	N
coverage (i.e. target population)	N	NA	N	NA	N
legislation	N	NA	N	NA	N
classifications	N	NA	N	NA	N
geographical boundaries	N	NA	N	NA	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	N	NA	NA	NA	N
sample design	N	NA	NA	NA	N
rotation pattern	N	NA	NA	NA	N
questionnaire	N	NA	NA	NA	N
instruction to interviewers	N	NA	NA	NA	N
survey mode	N	NA	NA	NA	N
weighting scheme	N	NA	NA	NA	N
use of auxiliary information	N	NA	NA	NA	N

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

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?
First wave: Face-to-Face-Interviews, using CAPI (Computer assisted personal interviews). Second to fifth wave CAWI (Computer assisted web interviewing) or CATI (Computer assisted telephone interviewing). CAWI available from the second quarter of 2021 onwards.	Y	The internally developed software "STATsurv" is used.

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	0,16	2,05	4,78
SE	0,10	0,07	0,45
CI^(*)	65,16 ; 65,56	3,13 ; 3,39	8,57 ; 10,35

Unemployment-to-population ratio 15-74 (NUTS 2 regions)
	CV	SE	CI(**)
AT11	7,15	0,20	2,43 ; 3,21
AT12	5,4	0,15	2,4 ; 2,93
AT13	3,55	0,22	5,8 ; 6,68
AT21	5,68	0,17	2,63 ; 3,26
AT22	6,1	0,15	2,23 ; 2,82
AT31	7,05	0,14	1,74 ; 2,29
AT32	7,33	0,16	1,83 ; 2,47
AT33	6,37	0,15	2 ; 2,56
AT34	6,86	0,16	1,96 ; 2,57

Frame quality (under-coverage, over-coverage and misclassifications^(b))
Under-coverage rate (%)	Over-coverage rate (%)	Misclassification rate (%)	Comments: specification and impact on estimates^(a)
Under-coverage rate (%)	Over-coverage rate (%)	Misclassification rate (%)	Undercoverage	Overcoverage	Misclassification^(b)	Reference on frame errors
UNA	UNA	UNA	From 2004 onwards the sample for the Austrian LFS is drawn from the Austrian Register of Residents. This register was set up in 2002. The sample is drawn three months before the start of the quarter. This results in a time lag of three to six months. Therefore dwellings where persons moved in after the due date for the survey are not covered. Furthermore, undercoverage of migrants can be observed, although the questionnaires are translated into several languages.	UNA	UNA	UNA

Reference on software used:	Reference on method of estimation:
R	Calibrated Rescaled Bootstrap

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	Only help was revised; warnings or autofills were adapted.	Y	Internal checks have been carried out.

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	Y
Interviewer	Periodical training (at least 1 time per year) (Y/N)	Feedbacks from interviewer (reports, debriefings, etc.) (Y/N)
	Y	Y (during annual training, furthermore questions can be asked at any time)
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)
	Y (for CAWI)	Y (for CATI-Interviews)	Y
Questionnaire	Questionnaire in several languages (Y/N)	On-line checks (for computer assisted interviews (Y/N)
	Y	Y
Other / Comments	NA

Methods used for adjustments for statistical unit non-response
Adjustment via weights (Y/N)	Variables used for non-response adjustment	Description of method
Y	Age, sex, nationality, size of households, NUTS 2 according to register of residents, labour status from administrative data.	Post-stratification
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
Mode can change any time during the survey; mode is therefore not meaningful.	see CAPI	NA	see CAPI	NA

Non-response rates by survey mode. Annual average (% of the theoretical yearly sample by survey mode)
Quarter	Non-response rate
	Total (%)	of which:
	Total (%)	Refusals (%)	Non-contacts (including people who migrated (or moved) internally or abroad) (%)
1	4,54	3,36	0,41
2	5,33	3,39	0,85
3	5,96	3,81	0,89
4	5,54	3,28	0,79
Annual	5,34	3,46	0,73

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_Q1_2021	190
Subsample_Q2_2021	157	182
Subsample_Q3_2021	136	171	213
Subsample_Q4_2021	133	128	185	192
Subsample_Q1_2022	103	135	171	152
Subsample_Q2_2022		110	133	129
Subsample_Q3_2022			112	133
Subsample_Q4_2022				96
Total in absolute numbers	719	726	814	702
Total in % of theoretical quarterly sample	3,20	3,23	3,62	3,12

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_2021	21
Subsample_Q2_2021	16	55
Subsample_Q3_2021	20	47	53
Subsample_Q4_2021	18	21	62	44
Subsample_Q1_2022	13	35	29	43
Subsample_Q2_2022		23	23	39
Subsample_Q3_2022			24	23
Subsample_Q4_2022				20
Total in absolute numbers	88	181	191	169
Total in % of theoretical quarterly sample	0,39	0,80	0,85	0,75

Non-response rates. Annual averages (% of the theoretical yearly sample)
NUTS-2 region (code + name)	Non response rate (%)
AT11 Burgenland	4,33
AT12 Niederösterreich	3,77
AT13 Wien	9,55
AT21 Kärnten	3,81
AT22 Steiermark	4,56
AT31 Oberösterreich	5,78
AT32 Salzburg	6,17
AT33 Tirol	4,02
AT34 Vorarlberg	4,59

*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	Column	Identifier	Quarter 1	Quarter 2	Quarter 3	Quarter 4
Compulsory	C199	WANTWORK	0,12	0,13	0,35	0,19	According to Flow Charts imputation not allowed.
Compulsory	C193-194	ABSREAS	0,04	0,05	-	-	According to Flow Charts imputation not allowed.

Do you apply any seasonal adjustment to the LFS Series? (Y/N)	If Yes, is your adopted methodology compliant with the ESS guidelines on seasonal adjustment? (ref. ESS guidelines on seasonal adjustment - Products Manuals and Guidelines - Eurostat (europa.eu) (Y/N)	If Yes, are you compliant with the Eurostat/ECB recommendation on Jdemetra+ as software for conducting seasonal adjustment of official statistics. (ref. Jdemetra-officially-recommended-as-software-for-the-seasonal-adjustment-of-official-statistics) (Y/N)	If Not, please provide a description of the used methods and tools
N	NA	NA	NA

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	Y

*Item non-response () - Annual data (Compared to the variables defined by the Commission Regulation (EC) No 377/2008)**
Variable status	Column	Identifier	This reference year	Short comments on reasons for non-available statistics and prospects for future solutions
Compulsory	C316-323	INCGROSS	Y	Delivered yearly with delay since basic data originates from registers.
Compulory	C324-325	INCGROSS_F	Y	Delivered yearly with delay since basic data originates from registers.
Compulsory	C326	REGISTER	Y	Delivered yearly with delay since basic data originates from registers.

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	Overall editing rates are not calculated. The editing rate is monitored per national variable.

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	Overall editing rates are not calculated. The editing rate is monitored per national variable.
Main variables	Imputation rate	Describe method used, mentioning which auxiliary information or stratification is used
UNA	UNA	UNA

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	SBS: The SBS covers nearly all economic activities (see below) that are performed on a market basis. The statistical population is defined by the market production criterion which means that the SBS describe the economic activities of market producers only. The distinction between market and non-market producers is made, based on the definitions of the European System of Accounts 2010 (ESA 2010) and can be taken directly from the SBR.	Structural Business Statistics is a combination of business survey, administrative data and modell based data. The number of employees and self-employed is measured as an annual average using data for at least each quarter or month of the year covering the number of persons who work during part of during the entire reference period in the legal unit and are paid by it, as well as those persons working outside of the unit but belonging to it and who are paid by the legal unit. The concept of SBS is a statistical survey of the legal units exceeding legally defined turnover or employment thresholds and use of administrative sources (social security data for employment) of all units below these thresholds. LFS is a household survey, the net sample is weighted to fit population figures.	In most recent data (2021) of BS total employment in NACE B to N and P to S is slightly lower than in the LFS (-6.6% employed).	NA
Total employment by NACE	SBS: The SBS coverage affects all enterprises, their legal units and local units , whose main economic activities are covered by sections B to N, P to R as well as divisions S95 and S96 according to the classification of economic activities (ÖNACE 2008). LFS gives information on the employed according to ILO definitions, sample is evenly spread over the quarter/year.	LFS: NACE as reported by respondents, people working with a temporary employment agency report the NACE they actually work in. See above	Deviations are greatest in NACE section P with LFS employment being six times higher than in BS. In section Q LFS data are twice as high as in BS. Further bigger deviations: In NACE section N BS is 44% higher than LFS and in section L BS employment is 41% higher.	NA
Number of hours worked	SBS: Total Hours worked by employees represents the number of hours actually worked by employees, for the output of the unit during the reference period.	SBS: The concept of SBS is a statistical survey of the legal units exceeding legally defined turnover or employment thresholds and model based estimation of all units below these thresholds	Comparing the actual hours worked by employees in 2021, volume of work in BS is lower than in LFS (-23%). The largest difference is shown in sector P.	NA

Coherence of LFS data with registered unemployment
Description of difference in concept	Description of difference in measurement	Give references to description of differences
ILO-Concept on unemployment versus registration at employment agency	Number of unemployed according LFS definitions is lower than registered unemployment (Data on registered unemployment as published by the Austrian Public Employment Service, Arbeitsmarktservice/AMS).	Number of unemployment according to the ILO-Concept is 16% smaller (221 100 vs. 263 100) than the number of unemployed according to the national statistics of AMS.

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)
LFS is 16% lower	LFS is 77% higher	LFS is 28% lower	LFS is 113% higher	LFS is 27% lower	NA

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	Contrary to LFS National Accounts (NA) count employees working in Austria but living abroad (domestic versus national concept). People working in civilian or military service are included in the NA, but excluded from the LFS. Employees living in institutional homes are included in the NA but excluded from the LFS. Employees below the age of 15 are excluded from the LFS but included in the NA.	National Accounts use different data sources, above all administrative data.	Annual volume of work (actual hours, main and second job) in National Accounts is slightly higher than in LFS (7 032 Mio. hours in National Accounts vs. 6 718 Mio. h in LFS - 2021 data)	Std_b_mz-arbeitskraefte-wohnungserhebung_ab_2004.
Total employment by NACE	see above	see above	LFS: NACE as reported by respondents, people working with a temporary employment agency report the NACE they actually work in.	see above
Number of hours worked	see above	National Accounts use different data sources, related to the hours worked mainly LFS and STS (short time statistics) data are used. LFS data on hours worked are adapted by National Accounts.	Employment in National Accounts is higher than in LFS (3 951 800 in National Accounts vs. 3 688 200 in LFS - 2021 data)	see above

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)
N	N	Y	N	N	N

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	Everybody	All users have to confirm compliance with Statistic Austria's terms of use.	Questionnaire, description of variables and levels, list of articles on methodology, technical report, further important notes.	Users can contact Statistics Austria and AUSSDA for further support.

Number of staff involved in the LFS in central and regional offices, excluding interviewers Consider only staff directly employed by the NS	Full-time equivalents
Total	17
- of which professional and managerial	8

1.1. Contact organisation

1.2. Contact organisation unit

1.3. Contact name

1.4. Contact person function

1.5. Contact mail address

1.6. Contact email address

1.7. Contact phone number

1.8. Contact fax number

2.1. Data description

2.2. Classification system

2.3. Coverage - sector

2.4. Statistical concepts and definitions

2.5. Statistical unit

2.6. Statistical population

2.7. Reference area

2.8. Coverage - Time

2.9. Base period

3.1. Source data

3.2. Frequency of data collection

3.3. Data collection

3.4. Data validation

3.5. Data compilation

3.6. Adjustment

4.1. Quality assurance

4.2. Quality management - assessment

5.1. Relevance - User Needs

5.2. Relevance - User Satisfaction

5.3. Completeness

5.3.1. Data completeness - rate

6.1. Accuracy - overall

6.2. Sampling error

6.2.1. Sampling error - indicators

6.3. Non-sampling error

6.3.1. Coverage error

6.3.1.1. Over-coverage - rate

6.3.1.2. Common units - proportion

6.3.2. Measurement error

6.3.3. Non response error

6.3.3.1. Unit non-response - rate

6.3.3.2. Item non-response - rate

6.3.4. Processing error

6.3.4.1. Imputation - rate

6.3.5. Model assumption error

6.4. Seasonal adjustment

6.5. Data revision - policy

6.6. Data revision - practice

6.6.1. Data revision - average size

7.1. Timeliness

7.1.1. Time lag - first result

7.1.2. Time lag - final result

7.2. Punctuality

7.2.1. Punctuality - delivery and publication

8.1. Comparability - geographical

8.1.1. Asymmetry for mirror flow statistics - coefficient

8.2. Comparability - over time

8.2.1. Length of comparable time series

8.3. Coherence - cross domain

8.4. Coherence - sub annual and annual statistics

8.5. Coherence - National Accounts

8.6. Coherence - internal

9.1. Dissemination format - News release

9.2. Dissemination format - Publications

9.3. Dissemination format - online database

9.3.1. Data tables - consultations

9.4. Dissemination format - microdata access

9.5. Dissemination format - other

9.6. Documentation on methodology

9.7. Quality management - documentation

9.7.1. Metadata completeness - rate

9.7.2. Metadata - consultations

11.1. Confidentiality - policy

11.2. Confidentiality - data treatment

Duration of the interview by Final Sampling Unit	Minutes
Duration of the interview by Final Sampling Unit	Total	First wave	Later waves
Average duration of the interview	13:34	25:54	10:59
Core questionnaire (pr person)	05:38	10:28	04:28
Ad hoc Modules (pr person)	03:00	03:00	NA
Note: This table should only show the burden on the respondents, not time spent in the field to contact the household or fill in adminstrative forms.