ISTAT - Istituto Nazionale di Statistica
ESS Standard for Quality Report Structure (ESQRS) V2 (ESQRS_MSD 3.0 ESTAT)
Employment and unemployment (Labour Force Survey)
2013 - A0
1. Contact
1.1 Contact organisation

ISTAT

1.2 Contact organisation unit

Education, Training and Labour Division

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. Statistical presentation
2.1 Data description

Please specify 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 or blank Non-response: Member State doesn’t answer to Eurostat request for information
LFS Labour Force Survey
NUTS Nomenclature of territorial units for statistics or corresponding statistical regions in the EFTA and candidates countries
NC No change from last report.

 

Coverage
Coverage Inclusion/exclusion criteria for members of the household Questions relating to employment status are put to all persons aged ...
The reference population is the "resident population", that is the population recorded in the registry offices in the Italian municipalities. All the Italian regions are covered. Only private households are included in the sample. Private households are made up either of persons living alone or of two or more persons, whether or not of the same family, usually living in the same dwelling and with family (marriage, relationships, adoption, guardianship) or affection ties. Non resident households, people not living in private households and household members emigrated abroad or absent from the selected household for more than 1 year are not covered. 15 and over. From the first quarter 2008 onwards Italian LFS data on people aged 15 years old don’t include neither employed nor unemployed (they are all classified as inactive people).

 

Reference week
The sample is evenly spread over the 13 weeks of each quarter. The first week of the year or quarter is the week including the first Thursday of the year or quarter.

 

Sampling design & procedure
Sampling design Base used for the sample (sampling frame) Last update of the sampling frame Primary sampling unit (PSU) Final sampling unit (FSU)
 The sample design is a two stage sampling with stratification of the primary units.  Population frame from registry offices of the Italian municipalities

The annual sample is composed by households which belong to 16 rotation groups (4 waves X 4 quarters = 16 rotation groups).

A new sample of households is introduced every year starting from the first wave of the third quarter, This sample is selected from the most updated available frame (October 2011).  This new sample is gradually introduced as the first wave rotation group.
 Municipalities  Households

 

Sampling design & procedure
First (and intermediate) stage sampling method Final stage sampling method Stratification Description of the rotation scheme
 In each NUTS 3 domain, large municipalities, with population over a given threshold (also called self-representative municipalities), are always included in the sample; smaller municipalities (not self-representative) are grouped in strata, then one municipality in each stratum is selected with probability proportional to the population. Households are randomly selected from the registry offices in all the municipalities drawn at the first stage. Stratification of primary units is carried out in each NUTS-3 domain and it is based on the population of the municipalities. In 2012 a new stratification of the municipalities was made, to take into account updated information on their population. Consequently a new selection of the municipalities has been done, the new selected municipalities entered in the sample in the third quarter 2012. Due to rotation scheme, for 5 quarters until 2013Q3, old and new sampling designs have been  overlapped. The households are rotated according to a 2-(2)-2 rotation scheme. Households are interviewed during two consecutive quarters. After a two-quarters break, they are again interviewed twice in the corresponding two quarters of the following year. As a result, each household is included in four waves of the survey.

 

Sample size & Sampling rate
Overall theoretical yearly sampling rate
(i.e. including non-response)
Size of the theoretical yearly sample
(i.e. including non-response)
In 2013 the overall theoretical sampling rate has been 1.13%. In 2013 the theoretical sample size has been 288,483 households. Due to budget cuts, in 2012 the theoretical sample size was reduced by about 9% respect to 2011 one.

 

Sample size & Sampling rate
Overall theoretical quarterly sampling rate
(i.e. including non-response)
Size of the theoretical quarterly sample
(i.e. including non-response)
In 2013 the overall theoretical quarterly sampling rate has been 0.28%. In 2013 the theoretical quarterly sample size has has been on average 72.113.

 

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. 430/2005, Annex I) (Y/N) If not please list deviations List of yearly variables for which the wave approach is used (Ref.: Commission Reg. 377/2008, Annex II)
We don't use wave approach  NA  NA  NA

 

Data collection methods: brief description Participation is voluntary/compulsory?

The information is collected through computer assisted personal (CAPI) or telephonic (CATI) interviews, carried out by professional interviewers.

CAPI mode is usually used for the 1st wave, whereas CATI mode is usually used for later waves. Households without a telephone and non-Italian households are interviewed always by CAPI mode.

 Compulsory

 

Brief description of the method of calculating the weights Is the sample population in private household expanded to the total population (including those in collective households)? (Y/N) 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 calibration estimator is used to obtain LFS estimates. Grossing weights are determined as follows:
1. Firstly, initial weights are obtained as the inverse of the inclusion probabilities of any household in the sample.
2. Then, correction factors for households non-response are worked out as the reciprocal of the response ratios (computed for specific kind of households and territorial domains). Intermediate weights corrected for non-response are then computed multiplying initial weights by these correction factors.
3. Then, starting from intermediate weights, final grossing weights are obtained solving a minimization problem under constraints. The function to be minimised is a distance between final and intermediate weights; the constraints regard the estimates of some auxiliary variables that have to be equal to the totals in the reference population derived by external sources (main constraints are population by gender and 14 5-year age groups at NUTS-2 level and population by gender and 5 age groups of different width at NUTS-3 level). Final weights ensure that all members of a given household have the same weight.
Through the calibration estimator, applying final grossing weights, the sample reproduces the same distribution of the population according to the chosen auxiliary variables.
Grossing weights are computed on quarterly basis, whereas annual estimates are calculated as averages of quarterly estimates.
N Y 14 5-year age groups (0-14, 15-19, ..., 70-74, 75+ ) at NUTS2 level and 5 age groups of different width at NUTS3 level Till NUTS3  Monthly population by gender (at NUTS2), number of households by wave (at NUTS2), foreigner population (Male, Female, EU and Not EU at NUTS2), population in metropolitan areas (municipalities with resident population over than 250 thousands units) by gender and 5 age groups.

 

 

2.2 Classification system

Not available.
New concept added with the migration to SIMS 2.0.
Information (content) will be available after the next collection.

2.3 Coverage - sector

Not available.
New concept added with the migration to SIMS 2.0.
Information (content) will be available after the next collection.

2.4 Statistical concepts and definitions

Not available.
New concept added with the migration to SIMS 2.0.
Information (content) will be available after the next collection.

2.5 Statistical unit

Not available.
New concept added with the migration to SIMS 2.0.
Information (content) will be available after the next collection.

2.6 Statistical population

Not available.
New concept added with the migration to SIMS 2.0.
Information (content) will be available after the next collection.

2.7 Reference area

Not available.
New concept added with the migration to SIMS 2.0.
Information (content) will be available after the next collection.

2.8 Coverage - Time

Not available.
New concept added with the migration to SIMS 2.0.
Information (content) will be available after the next collection.

2.9 Base period

Not available.
New concept added with the migration to SIMS 2.0.
Information (content) will be available after the next collection.

3. Statistical processing

[not requested for the LFS quality report]

3.1 Source data

[not requested for the LFS quality report]

3.2 Frequency of data collection

[not requested for the LFS quality report]

3.3 Data collection

[not requested for the LFS quality report]

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. Quality management
4.1 Quality assurance

Not available.
New concept added with the migration to SIMS 2.0.
Information (content) will be available after the next collection.

4.2 Quality management - assessment

[not requested for the LFS quality report]

5. Relevance

[not requested for the LFS quality report]

5.1 Relevance - User Needs
5.2 Relevance - User Satisfaction

[not requested for the LFS quality report]

5.3 Completeness
5.3.1 Data completeness - rate
6. Accuracy and reliability

[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
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)

Under-coverage rate (%) Over-coverage rate (%) Misclas-sification rate (%) Comments: specification and impact on estimates (a) Reference on frame errors
Undercoverage Overcoverage Misclassification (b)
   2.30  1.99 Households are selected once a year from the municipalities’ registry offices; they cover the whole reference population. The data might contain errors as for information such as addresses (due for instance to recent change of the address), wrong inclusions (recent emigration) and missed inclusions (recent immigration).
As for the survey’s management strategies, Istat requires that each non-responding household be replaced with a household having similar characteristics of the first one, in order to maintain as much as possible the sample representativeness and to minimise the impact of unit non-response. No more than 3 replaces are admitted.
     
6.3.1.1 Over-coverage - rate

[Over-coverage rate, please see chapter 5.3.1 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 reporting units and the interviewers

Give brief comments on the assessment of errors due to:
Reporting unit Interviewers
 UNA  UNA

Errors due to the medium (questionnaire)

Date of the last update of the questionnaire (before the end of the reference period for this report) Date of the last pilot survey in order to test the questionnaire Number of respondents to the pilot survey Report from cognitive laboratory available (Y/N)
January 2013 for Q1, Q3 and Q4 - April 2013 for AHM in Q2 November 2012 1,000 households  N

Main methods of reducing measurement errors

Error source Brief comments
Respondent Advance letter to the household; translation of the advance letter and of the questionnaire in 11 languages, including English and German, in order to increase the participation for the non-nationals; telephone free line for the respondents; non-response analysis.
Interviewer Briefing ad hoc, performance rates, news group, check-phone call on interviewed households
Questionnaire On-line help, on-line check, personalised questions, test and analyses of output, test of different kinds of question
Other  

Methodological notes (main references) on the measurement errors?

Main references
• F. della Ratta-Rinaldi, M. Tibaldi, M. E. Pontecorvo, “Strategie di Text Mining per il controllo e la correzione della codifica dell’attività economica nell’indagine Istat sulle forze di lavoro”, in E. Née, J.M. Daube, M. Valette, S. Fleury, (eds), Actes des 12es Journées internationales d’Analyse statistique des Données Textuelles. Paris: Sorbonne Nouvelle – Inalco, 2014
• M. G. Grassia, F. Pintaldi, L. Quattrociocchi, Wage and Salary in the Labour Force Survey, 2006
• F. Camillo, M. G. Grassia, F. Pintaldi, L. Quattrociocchi, How to estimate the effectiveness of on-line codify with searching engines -The Italian experience of Istat Labour Force Survey, Miami, 2006
• G. Giuliani, M. G. Grassia, L. Quattrociocchi, R. Ranaldi, New methods for measuring quality indicators of ISTAT’s new CAPI/CATI Labour Force Survey, ISTAT - Department for statistical production and technical-scientific coordination Labour Force Survey ,2004
• S. Bergamasco, S. Gazzelloni, L. Quattrociocchi, R. Ranaldi, A.Toma, V. Triolo
New strategies to improve quality of ISTAT new CAPI/CATI Labour Force Survey,  ISTAT - Department for statistical production and technical-scientific coordination Labour Force Survey, 2004
• M. G. Grassia, F. Pintaldi, L. Quattrociocchi  The electronic questionnaire in ISTAT’s new CAPI/CATI Labour Force Survey ISTAT - Department for stati• Istat 3 June 2004 S. Gazzelloni, M. Albisinni, L. Bagatta, C. Ceccarelli, L. Quattrociocchi, R. Ranaldi, A. Toma The new Labour Force Survey Contents methodology organisation, 2004
• S. Bergamasco, G. Budano, L. Quattrociocchi, A.Toma, The new Istat network for capturing interview data: the technological architetture ISTAT - Department for statistical production and technical-scientific coordination Labour Force Survey, 2003
• C. Ceccarelli, S. Rosati Data editing for the Italian Labour Force survey, 2005 stical production and technical-scientific coordination Labour Force Survey, 2004
• Metodi e Norme ISTAT vol. 32, 2006 - "La rilevazione sulle forze di lavoro: contenuti, metodologie, organizzazione".
6.3.3 Non response error

Impact of non response: underestimation and overestimation bias of main characteristics

  Underestimation assessment Overestimation assessment
Quantitative Descriptive Quantitative Descriptive
Total employment M? We have the idea the LFS underestimates irregular employment and the number of persons with second jobs, but we're not able to assess these effects.    
Part-time employment        
Unemployment        
Numbers of hours actually worked        
Other characteristic        
Other characteristic        

 

Methods used for adjustments for statistical unit non-response

Adjustment via weights (Y/N?) Variables used for non-response adjustment Description of method
 Y In the second step, correction factors for household non-response are computed according to household typologies (number of members and reference person's age) and territorial domains. In the third step calibration is applied: main constraints are population by gender and 14 5-year age groups at NUTS-2 level and population by gender and 5 age groups of different width at NUTS-3 level. Other constraints are: monthly population by gender (at NUTS2), number of households by wave (at NUTS2), foreigner population (Male, Female, EU and Not EU at NUTS2), population in metropolitan areas (municipalities with resident population over than 250 thousands units) by gender and 5 age groups.  Grossing weights are determined as follows:
1. Firstly, initial weights are obtained as the inverse of the inclusion probabilities of any household in the sample.
2. Then, correction factors for households non-response are worked out as the reciprocal of the response ratios (computed for specific kind of households and territorial domains). Intermediate weights corrected for non-response are then computed multiplying initial weights by these correction factors.
3. Then, starting from intermediate weights, final grossing weights are obtained solving a minimization problem under constraints. The function to be minimised is a distance between final and intermediate weights; the constraints regard the estimates of some auxiliary variables that have to be equal to the totals in the reference population derived by external sources (main constraints are population by gender and 14 5-year age groups at NUTS-2 level and population by gender and 5 age groups of different width at NUTS-3 level). Final weights ensure that all members of a given household have the same weight.
Through the calibration estimator, applying final grossing weights, the sample reproduces the same distribution of the population according to the chosen auxiliary variables. It is useful to reduce the bias effects of unit non-response.

 

Substitution of non-responding units (Y/N?) Substitution rate Criteria for substitution
 Y 31% of the first selected households have been substituted: 21%  have been substituted with the first substitute unit, 6.5% with the second one, 3.4% with the third one. Non responding households (non-contacts, refusals, other non-respondents, ineligible units, etc.) are substituted only in the 1st wave or if they are assigned to CAPI technique. When the sample is drawn, for each selected household three additional households are chosen as substitute units, according to the same sampling design. That is for each household it is possible to do up to 3 substitutions. In order to correct for higher non response for non national people, households with foreigner reference person are substituted with households with the same characteristic.

 

Other methods (Y/N?) Description of method
 N  

 

Methods used for imputation of statistical item non-response

Characteristic Imputation rate Describe method used, mentioning which auxiliary information or stratification is used
The imputation rate expresses the percentage of records in which at least one variable has been imputed; for imputing we mean modification of original values (missing or not) 4% of individual record were imputed (1 variable or more) After data captured contradictory information and item non-response are detected by using an automatic system based on Fellegi and Holt model of editing (1976). This operation is also performed during each quarter in order to notify in time possible errors due to the electronic questionnaire. The explicit edits relating to categorical variables (i.e. variables which are not subject to a meaningful metric) are implemented in SCIA (System for editing and automatic imputation), developed by ISTAT according to the Fellegi and Holt methodology (Barcaroli and Venturi, 1997). More exactly, the version of SCIA included in CONCORD (CONtrol and Data CORrection), a system designed for Windows environment, is used (Riccini Margarucci and Floris, 2000). The large number of edit rules and the complicated skip patterns of the questionnaire poses several computational problems that the entire set of edits need to be partitioned into two subsets. The problems arise since the Fellegi and Holt system runs to check the logical consistency of the entire edit system.  
   
   

 

References to methodological notes on non response rates and their treatment
 CECCARELLI, C., ROSATI, S. (2005). Data Editing for the Italian Labour Force Survey, Conference of European Statisticians, Work Session on Statistical Data Editing, United Nations Statistical Commission and Economic Commission for Europe, Ottawa, Canada, 16-18 May 2005.

 

6.3.3.1 Unit non-response - rate
Calculation of non-response. Annual average
Is the non response rate weighted? (Y/N) Is the non-response on household level or person level? (H/P) If weighted, state the definition of the weights
 N  H  

 

Rates of non response by survey wave. Annual average
Waves
1 2 3 4 5 6 7 8
 26.14 4.87  6.15  4.02  NA NA NA NA

 

Rates of non response by survey mode. Annual average
Survey
CAPI CATI PAPI CAWI POSTAL
 22.72 3.53   NA NA NA

 

Divisions of non-response into categories. Quarterly data and annual average
Quarter Non response rate (%) Refusals (%) Non-contacts (%) Other reasons(%)
1 12.06 4.05 7.16 0.85
2 12.21 4.01 7.32 0.89
3 12.73 4.34 7.84 0.56
4 9.63 0.85 7.92 0.87
Annual  11.67 3.33 7.56 0.79

 

Rates of non response. Annual average
NUTS-2 region (code + name) Non response rate (%)
ITC1 Piemonte 13.36
ITC2 Valle d’Aosta/Vallée d’Aoste 13.60
ITC3 Liguria 11.40
ITC4 Lombardia 11.69
ITF1 Abruzzo 10.90
ITF2 Molise 8.46
ITF3 Campania 13.01
ITF4 Puglia 10.20
ITF5 Basilicata 8.50
ITF6 Calabria 10.79
ITG1 Sicilia 13.91
ITG2 Sardegna 10.90
ITH1 Provincia Autonoma di Bolzano/
Bozen
8.47
 ITH2 Provincia Autonoma di Trento 13.59
 ITH3 Veneto 10.45
 ITH4 Friuli-Venezia Giulia 12.01
 ITH5 Emilia-Romagna 11.15
 ITI1 Toscana 9.51
 ITI2 Umbria 10.87
 ITI3 Marche 10.01
 ITI4 Lazio 12.83
   

 

Rates of non response. Annual average
NUTS-3 region (code + name) Non response rate (%)
ITC11 Torino 13.54
ITC12 Vercelli 9.48
ITC13 Biella 12.29
ITC14 Verbano-Cusio-Ossola 14.87
ITC15 Novara 15.81
ITC16 Cuneo 13.06
ITC17 Asti 11.55
ITC18 Alessandria 16.80
ITC20 Valle d’Aosta/Vallée d’Aoste 13.60
ITC31 Imperia 13.35
ITC32 Savona 9.83
ITC33 Genova 12.56
ITC34 La Spezia 8.47
ITC41 Varese 9.40
ITC42 Como 10.60
ITC43 Lecco 6.85
ITC44 Sondrio 7.33
ITC4C Milano 14.61
ITC4D Monza e della Brianza 15.29
ITC46 Bergamo 12.69
ITC47 Brescia 13.38
ITC48 Pavia 12.22
ITC49 Lodi 10.42
ITC4A Cremona 8.59
ITC4B Mantova 10.18
ITF11 L’Aquila 12.91
ITF12 Teramo 8.39
ITF13 Pescara 12.57
ITF14 Chieti 9.95
ITF21 Isernia 12.80
ITF22 Campobasso 6.64
ITF31 Caserta 16.75
ITF32 Benevento 12.67
ITF33 Napoli 12.08
ITF34 Avellino 11.10
ITF35 Salerno 13.06
ITF46 Foggia 6.84
ITF47 Bari 10.96
ITF48 Barletta-Andria-Trani 7.49
ITF43 Taranto 9.64
ITF44 Brindisi 14.12
ITF45 Lecce 10.80
ITF51 Potenza 8.75
ITF52 Matera 7.97
ITF61 Cosenza 12.05
ITF62 Crotone 8.96
ITF63 Catanzaro 8.63
ITF64 Vibo Valentia 8.32
ITF65 Reggio di Calabria 13.02
ITG11 Trapani 12.49
ITG12 Palermo 14.10
ITG13 Messina 16.68
ITG14 Agrigento 16.68
ITG15 Caltanissetta 17.88
ITG16 Enna 13.53
ITG17 Catania 7.14
ITG18 Ragusa 13.72
ITG19 Siracusa 11.05
ITG25 Sassari 8.45
ITG26 Nuoro 11.53
ITG27 Cagliari 12.27
ITG28 Oristano 10.72
ITG29 Olbia-Tempio 13.91
ITG2A Ogliastra 9.75
ITG2B Medio Campidano 9.28
ITG2C Carbonia-Iglesias 10.56
ITH10 Bolzano-Bozen 8.47
ITH20 Trento 13.59
ITH31 Verona 9.00
ITH32 Vicenza 13.03
ITH33 Belluno 8.14
ITH34 Treviso 10.88
ITH35 Venezia 11.05
ITH36 Padova 11.34
ITH37 Rovigo 9.91
ITH41 Pordenone 9.81
ITH42 Udine 15.76
ITH43 Gorizia 11.50
ITH44 Trieste 8.15
ITH51 Piacenza 10.01
ITH52 Parma 10.56
ITH53 Reggio nell’Emilia 8.77
ITH54 Modena 13.05
ITH55 Bologna 12.75
ITH56 Ferrara 8.85
ITH57 Ravenna 15.45
ITH58 Forlì-Cesena 13.52
ITH59 Rimini 7.54
ITI11 Massa-Carrara 11.31
ITI12 Lucca 7.15
ITI13 Pistoia 9.16
ITI14 Firenze 14.45
ITI15 Prato 9.64
ITI16 Livorno 10.94
ITI17 Pisa 9.00
ITI18 Arezzo 8.13
ITI19 Siena 8.00
ITI1A Grosseto 5.96
ITI21 Perugia 11.15
ITI22 Terni 9.98
ITI31 Pesaro e Urbino 10.40
ITI32 Ancona 8.10
ITI33 Macerata 10.89
ITI34 Ascoli Piceno 9.89
ITI35 Fermo 11.15
ITI41 Viterbo 14.57
ITI42 Rieti 10.14
ITI43 Roma 13.86
ITI44 Latina 11.96
ITI45 Frosinone 8.17

 

 

Availability and calculation of non-response at NUTS-3 level
Is non response rate available (Y/N) Is the non response rate weighted? (Y/N) If weighted, state the definition of the weights
 Y  N  
6.3.3.2 Item non-response - rate

Item non-response - Quarterly data (Compared to the variables defined by the Commission Regulation (EC) No 377/2008)

Variable status
compulsory / optional
Column Identifier Quarter 1 Quarter 2 Quarter 3 Quarter 4 Short comments on reasons for non-available statistics and prospects for future solutions
 compulsory Col_073/74 HWWISH . . 16.3 . The questions on WISHMORE-HWWISH in the IT questionnaire are referred to the wish of working more than the actual number of hours. Most of the item non-responses are due to persons that did not want to work at all in the reference week (code "0" is not available); they are mainly concentrated in the 3rd quarter in which there are summer holidays. A little percentage of item non-responses is due to "don't know" answers.
  Col_101 - Employed SEEKTYPE 25.1 19.9 22.4 22.9 Item non-responses are due to persons that do not have preferences about an employment as self-employed or employee.
  Col_101 - Not employed SEEKTYPE 27.8 27.4 26.3 27.8 Item non-responses are due to persons that do not have preferences about an employment as self-employed or employee.

 

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 Col_150/151 COUNTR1Y 12.7 Item non-response is due to people aged less than 15 years, for which this information is not collected in the national questionnaire
6.3.4 Processing error

Information available about data capture errors and the error rates

Info.on data capture errors(Y/N/NA) Error ratein% Comments
 N    

 

Information available about codification errors and the error rates

Info. on data codification errors (Y/N) Error rate in % Comments
 N    

 

Information available about editing errors and the error rates

Info. on errors during the editing phase (Y/N) Error rate in % Comments
 N    

 

Information available about other processing errors and the error rates

Info. on other process errors (Y/N) Error rate in % Comments
 N    
6.3.4.1 Imputation - rate

[not requested for the LFS quality report]

6.3.5 Model assumption error

[not requested for the LFS quality report]

6.4 Seasonal adjustment

[not requested for the LFS quality report]

6.5 Data revision - policy

[not requested for the LFS quality report]

[not requested for the LFS quality report]

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. Timeliness and punctuality

[not requested for the LFS quality report]

7.1 Timeliness
7.1.1 Time lag - first result

[not requested for the LFS quality report]

7.1.2 Time lag - final result

[not requested for the LFS quality report]

7.2 Punctuality
7.2.1 Punctuality - delivery and publication

[not requested for the LFS quality report]

8. Coherence and comparability

[not requested for the LFS quality report]

[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  

 

Improvements in THIS reference year that have been made on the questionnaire so that it complies with the Twelve Principles
(See Annex 2 of Commission Regulation (EC) No 1897/2000)

Principle Description of improvement
   

 

Improvements in THIS reference year that have been made on the questionnaire so that it accurately transcodes to the EU list of variables.
(See Commission Regulation (EC) No 377/2008)

Variable Description of improvement
   

 

Improvements in THIS reference year that have been made on the questionnaire so that the transmitted data comply with the EU definition of unemployment.
(See Annex 1 of Commission Regulation (EC) No 1897/2000)

Concept Description of improvement
   

 

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 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        
coverage (i.e. target population)        
legislation        
classifications        
geographical boundaries        

 

Changes at MEASUREMENT level introduced during the reference year and affecting comparability with previous reference periods (including breaks in series)

Changes in 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        
sample design        
rotation pattern        
questionnaire        
instruction to interviewers        
survey mode        
weighting scheme        
use of auxiliary information        
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 LFS counts the number of persons employed, both in regular or irregular jobs, whatever the number of jobs they have. Business statistics’ surveys consider the number of regular jobs i.e. complying with tax and social security legislation and which can therefore be traced by business, institutional and administrative sources.   Due to the number of different sources used by business statistics’ surveys and to the relevant differences in concepts and measures with those used in Italian LFS, no comparisons between LFS and business statistics’ data have been done up to now.  
Total employment by NACE Economic data relating to Italian businesses in the fields of industry and services arise from two integrated sources: (i) a sample survey on medium and small enterprises and (ii) a census survey on enterprises with 100 workers and more. Further ISTAT’s surveys focus on businesses in the field of farm. In any case, both LFS and business surveys use the same classification of economic activity, referring to NACE    
Number of hours worked LFS collects individual information on the number of hours worked. Business surveys collect information on firm's total amount of hours     

 

Coherence of LFS data with registered unemployment

Description of difference in concept Description of difference in measurement Give references to description of differences
Differences between Public Employment Services (in Italian "Servizi Pubblici per l'Impiego" SPI) and LFS data concern: (1) LFS excludes from unemployment all individuals who have any kind of job, whereas SPI include individuals who have temporary jobs or salaries below a given amount; (2) the immediate availability for a job required by LFS is based on self declarations. On the contrary, SPI exclude individuals who miss scheduled encounters or refuse a fair job offer; (3) in LFS registration at SPI in order to find a job is only one of the possible active search actions. At present, data from administrative sources are not available. The specification of the concept of unemployment adopted by the Public Service for Employment (SPI) is provided by the Legislative Decree no.181/2000 as amended by the Decree Law no.297/2002 containing provisions to facilitate the meet of supply and demand. LFS follows the Commission Regulation 1897/2000.

 

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)
No estimation is possible No estimation is possible No estimation is possible No estimation is possible No estimation is possible No estimation is possible

[not requested for the LFS quality report]

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 Differences in concepts between LFS and National Accounts (NA) are due to the different purposes of the two estimates: description of labour market conditions for the LFS; estimate of the amount of work as productive factor underlying GDP for NA. Employment in NA refers to “domestic employment” whereas LFS definition of employment is more similar to the idea of “national employment”. NA estimates are obtained starting from the LFS figures, adding: a) foreign workers present on the national territory for a period longer than one year, but not included in population registers; b) foreign seasonal workers (in the country for a period less than one year) not included in population registers; c) members of the country’s armed force who are abroad; d) staff of national embassies located abroad; e) resident workers permanently living in collective households, f) conscripted persons; g) non-resident frontier workers working in resident establishments; h) unpaid trainees working for national firms; i) employed individuals with an age of less than 15 years;  j) irregular workers not included in the LFS; and subtracting resident frontier workers working abroad. In addition to domestic employment, NA estimates full-time equivalent Labour Units (In Italian ULA: Unità di LAvoro) starting from domestic employment and considering part-time work and lay-off periods. This measure of labour input is used as an alternative to the total number of hours worked. To produce their estimates NA collect and process information from different sources of various nature: household surveys, business surveys, administrative sources.  Figures refer to 2013:
LFS (employment): 22,420 thousands;                                         NA (employment): 24,173 thousands;                                           NA (ULA): 23,295 thousands
Details on the methodology used by the National Account to estimate employment have been provided in the report to Eurostat “Inventario delle fonti e dei metodi della contabilità nazionale interna” of December 2002.
Total employment by NACE As for differences in concept and measures of the total employment by NACE, it is firstly to note that National Account estimates refer to the concept of local level economic unit (UAEL), which is closely linked with that of economic activity unit (UAE). This concept traces the parties of a business that contribute to perform an economic activity at the class level (4 digits) in the NACE classification. UAEL is that part of the economic activity unit corresponding to one single local unit. On the other hand, LFS estimates the employment at local unit level (UL). In the production of their estimates, NA verify and amend the information on economic activity of employed people collected by households surveys following UAEL criterion.
Number of hours worked There are no conceptual differences between LFS and NA estimates of numbers of hours worked. Neverthless LFS data on hours worked refer to LFS employment whereas NA data on hours worked refer to NA employment Negligible in terms of weekly hours
8.6 Coherence - internal

[not requested for the LFS quality report]

9. Accessibility and clarity

[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
Every month/quarter new figures are disseminated by a press-release. Together with the quarterly press release a large number of indicators are made available on the Istat data warehouse http://dati.istat.it/. Annual averages are also disseminated in Istat data warehouse. Moreover for specific topics ad hoc releases or dedicated volumes are produced.
9.3 Dissemination format - online database

Documentation, explanation, quality limitations, graphics etc.

Web link to national methodological publication Conditions of access to data Accompanying information to data Further assistance available to users Possible improvements, compared to the previous situation.
 (Y/N):Y

Link to the national web page (national language(s)):http://www.istat.it/it/archivio/8263
http://dati.istat.it/?lang=it
http://siqual.istat.it/SIQual/visualizza.do?id=5000098

Link to the national web page (English):http://dati.istat.it/?lang=en
http://siqual.istat.it/SIQual/lang.do?language=UK

Access to macrodata: the main data distribution means is Internet, through the Istat website. As a matter of facts, all publications and a large set of already processed indicators are freely available on line. Specific users requests of indicators not already available are satisfied subject to a preliminary check on estimates reliability and against the payment of a fee which covers the cost related to time necessary for data processing. In this case data are provided in Excel format by e-mail. Access to microdata: Microdata are free of charge. Users are divided in three groups: Institutions belonging to the National Statistical System (SISTAN), such as Ministries, Municipalities; University or researcher, and other users. Two first users access to a greater level of detail in comparison with other users. .

A second difference concerns the list of blanked variables. For SISTAN users only variables with reliability problems are blanked, whereas for other users some variables are blanked also for anonymization reasons. Istat also gives external users the possibility to process microdata in his premise in a specific laboratory for the analysis of individual data (Laboratorio per l’Analisi dei Dati ELEmentari – ADELE ). In this case users can access the complete datasets, but Istat controls that the information produced by users respect privacy laws.

Press releases include a short description of the main survey characterstics. Together with microdata files the list of columns and codes of the variables, the questionnaire and an Excel file useful to estimate sampling errors are provided. On every publication a reference person is indicated, with telephone number and e-mail adress, to whom it is possible to ask for any clarification.  
9.3.1 Data tables - consultations

[not requested for the LFS quality report]

9.4 Dissemination format - microdata access

[not requested for the LFS quality report]

9.5 Dissemination format - other

[not requested for the LFS quality report]

9.6 Documentation on methodology

[not requested for the LFS quality report]

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]

10. Cost and Burden
11. Confidentiality

[not requested for the LFS quality report]

11.1 Confidentiality - policy

[not requested for the LFS quality report]

11.2 Confidentiality - data treatment

[not requested for the LFS quality report]

12. Comment

[not requested for the LFS quality report]