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 |
Viale Oceano Pacifico, 171
00144 Rome - Italy |
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 |
Definition of household for the LFS |
Inclusion/exclusion criteria for members of the household |
Questions relating to employment status are put to all persons aged ... |
| The 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. |
|
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. Statistical processing |
3.1 Source data |
| 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 (1st January 2014). 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 |
Size of the theoretical yearly sample |
| (i.e. including non-response) |
(i.e. including non-response) |
| In 2014 the overall theoretical sampling rate has been 1.11%. |
In 2014 the theoretical sample size has been 286,144 households. |
| 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) |
| In 2014 the overall theoretical quarterly sampling rate has been 0.28%. |
In 2014 the theoretical quarterly sample size has has been on average 71,536. |
| 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 |
| 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.
On January 2015 new population figures were available for the period 2002-2014, according to the results of the 2011 Population Census, Post Enumeration Survey of the 15th Italian population census and administrative register updates for the post censal period. Consequently LFS weights have been recalculated for the period 2002Q2-2014Q3.
|
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. |
|
3.2 Frequency of data collection |
[not requested for the LFS quality report] |
3.3 Data collection |
| 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 |
|
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 requested for the LFS quality report] |
4.2 Quality management - assessment |
[not requested for the LFS quality report] |
5. Relevance |
5.1 Relevance - User Needs |
| Assessment of the relevance of the main LFS statistics at national level (e.g. for policy makers, other stakeholders, media and academic research) |
| Most of this statistics are so important to describe and analyse the labour market that they are very relevant for all the actors (policy makers, social actors, media, etc.). So it would be hard to distinguish between high and low relevance. |
|
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 (stratification of primary units is at NUTS3 level and some constraints at NUTS3 level have been introduced in the final weights computation to allow the production on yearly basis of NUTS3 estimates). Starting from 2012 the new classification NUTS-2010 has been adopted. |
NUTS3 for annual estimates, NUTS2 for quarterly estimates, NUTS1 for monthly estimates |
NUTS3 |
NUTS3 estimates are produced through the usual calibration estimator |
|
5.3.1 Data completeness - rate |
| Assessment of errors (bias) in the registration of unemployment |
| Only for those countries using registered unemployment to produce NUTS-3 level data on unemployment or labour force. |
| NA |
|
6. Accuracy and reliability |
6.1 Accuracy - overall |
[not requested for the LFS quality report] |
6.2 Sampling error |
| Publication thresholds |
| Annual estimates |
Annual estimates - wave approach |
| (if different from full sample thresholds) |
| 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 |
| 1500 |
2500 |
We don't use wave approach |
We don't use wave approach |
|
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) |
| |
Number of employed persons |
Employment rate as a percentage of the population |
Number of part-time employed persons |
Number of unemployed persons |
Unemployment rate as a percentage of labour force |
Youth unemployment rate as a percentage of labour force |
Average actual hours of work per week(*) |
| |
Age group: 20 - 64 |
Age group: 20 - 64 |
Age group: 20 - 64 |
Age group: 15 - 74 |
Age group: 15 - 74 |
Age group: 15 - 24 |
Age group: 20 - 64 |
| CV |
0,20 |
0,20 |
0,76 |
0,85 |
0,84 |
1,38 |
0,12 |
| SE |
43787 |
0,12 |
30346 |
25783 |
0,10 |
0,56 |
0,04 |
| CI (**) |
(21807881-21979527) |
(60,29-60,77) |
(3933368-4052322) |
(2982719-3083787) |
(11,73-12,13) |
(39,23-41,41) |
(35,47-35,63) |
(*) The coefficient of variation for actual hours worked should be calculated for the sum of actual hours worked in 1st and 2nd jobs, and restricted to those who actually worked 1 hour or more in the reference week.
(**) The value is based on a CI of 95%. For the rates the CI should be given with 2 decimals.
| Description of the assumption underlying the denominator for the calculation of the CV for the employment rate |
| Coefficient of variation for the number of employed persons (aged 20-64) and the employment rate (aged 20-64) are identical, since the denominator of the employment rate is the total population and for this particular age group (individuals aged 20-64) it is one of the population totals used in the calibration procedure, thus the only source of sampling variability is the numerator. |
| Reference on software used : |
Reference on method of estimation: |
| Genesees: software produced by Istat |
1) Metodi e Norme ISTAT vol. 32, 2006 - "La rilevazione sulle forze di lavoro: contenuti, metodologie, organizzazione"; 2) Tecniche e Strumenti ISTAT vol. 2, 2005 - "Genesees, v. 3.0. – Funzione riponderazione". |
| Coefficient of variation (CV) Annual estimates at NUTS-2 Level |
| NUTS-2 |
CV of regional (NUTS-2) annual aggregates (in %) |
| Regional Code |
Region |
Number of employed persons |
Employment rate as a percentage of the population |
Number of part-time employed persons |
Number of unemployed persons |
Unemployment rate as a percentage of labour force |
Youth unemployment rate as a percentage of labour force |
Average actual hours of work per week(*) |
| |
|
Age group: 20 - 64 |
Age group: 20 - 64 |
Age group: 20 - 64 |
Age group: 15 -74 |
Age group: 15 -74 |
Age group: 15 -24 |
Age group: 20 - 64 |
|
ITC1
|
Piemonte
|
0.57 |
0.57 |
2.52 |
3.38 |
3.35 |
4.52 |
0.43 |
|
ITC2
|
Valle d'Aosta/Vallée d'Aoste
|
0.74 |
0.74 |
3.32 |
5.29 |
5.25 |
6.93 |
0.59 |
|
ITC3
|
Liguria
|
0.99 |
0.99 |
3.61 |
5.35 |
5.29 |
7.81 |
0.6 |
|
ITC4
|
Lombardia
|
0.42 |
0.42 |
2.12 |
2.44 |
2.41 |
4.05 |
0.31 |
|
ITF1
|
Abruzzo
|
1.21 |
1.21 |
5.08 |
5.14 |
5.05 |
6.55 |
0.64 |
|
ITF2
|
Molise
|
2.18 |
2.18 |
6.02 |
7.78 |
7.59 |
10.56 |
1.3 |
|
ITF3
|
Campania
|
1.08 |
1.08 |
2.72 |
2.78 |
2.62 |
3.46 |
0.48 |
|
ITF4
|
Puglia
|
1.08 |
1.08 |
3.41 |
2.75 |
2.63 |
4.18 |
0.54 |
|
ITF5
|
Basilicata
|
1.29 |
1.29 |
5.59 |
4.65 |
4.52 |
2.63 |
0.81 |
|
ITF6
|
Calabria
|
1.5 |
1.5 |
5.35 |
5.63 |
5.41 |
8.15 |
0.78 |
|
ITG1
|
Sicilia
|
0.89 |
0.89 |
2.64 |
2.06 |
1.92 |
2.62 |
0.39 |
|
ITG2
|
Sardegna
|
1.22 |
1.22 |
3.62 |
2.78 |
2.57 |
4.11 |
0.66 |
|
ITH1
|
Provincia Autonoma di Bolzano/
Bozen
|
0.72 |
0.72 |
2.81 |
7.21 |
7.17 |
14.78 |
0.69 |
|
ITH2
|
Provincia Autonoma di Trento
|
0.87 |
0.87 |
3.16 |
5.71 |
5.66 |
8.94 |
0.55 |
|
ITH3
|
Veneto
|
0.77 |
0.77 |
2.93 |
4.36 |
4.31 |
5.54 |
0.45 |
|
ITH4
|
Friuli-Venezia Giulia
|
0.85 |
0.85 |
3.25 |
4.95 |
4.9 |
7.36 |
0.56 |
|
ITH5
|
Emilia-Romagna
|
0.53 |
0.53 |
2.3 |
3.14 |
3.11 |
5.68 |
0.35 |
|
ITI1
|
Toscana
|
0.6 |
0.6 |
2.59 |
2.81 |
2.77 |
5.72 |
0.46 |
|
ITI2
|
Umbria
|
1.02 |
1.02 |
3.37 |
3.76 |
3.66 |
6.55 |
0.7 |
|
ITI3
|
Marche
|
0.89 |
0.89 |
3.87 |
4.1 |
4.04 |
8.85 |
0.64 |
|
ITI4
|
Lazio
|
0.65 |
0.65 |
2.58 |
2.46 |
2.41 |
3.56 |
0.4 |
| Coefficient of variation (CV) Annual estimates at NUTS-3 level |
| Region (NUTS-3) |
CV of regional (NUTS-3) annual aggregates (in %) |
| Regional Code |
Region |
Sample size (number of responding persons) |
Number of employed persons
Age group: 20 - 64 |
Number of unemployed persons
Age group: 15 -74 |
Unemployment rate as a percentage of labour force
Age group: 15 -74 |
|
ITC11
|
Torino
|
12980 |
0.98 |
4.98 |
4.92 |
|
ITC12
|
Vercelli
|
4525 |
1.7 |
8.25 |
8.14 |
|
ITC13
|
Biella
|
3768 |
1.75 |
10.59 |
10.5 |
|
ITC14
|
Verbano-Cusio-Ossola
|
4383 |
1.53 |
11.31 |
11.22 |
|
ITC15
|
Novara
|
3191 |
1.76 |
11.82 |
11.71 |
|
ITC16
|
Cuneo
|
7253 |
1.08 |
10.22 |
10.17 |
|
ITC17
|
Asti
|
4488 |
1.93 |
8.26 |
8.12 |
|
ITC18
|
Alessandria
|
4487 |
1.43 |
6.87 |
6.79 |
|
ITC2
|
Valle d'Aosta/Vallée d'Aoste
|
18599 |
0.74 |
4.89 |
4.85 |
|
ITC31
|
Imperia
|
3067 |
1.83 |
9.98 |
9.84 |
|
ITC32
|
Savona
|
4492 |
2.04 |
9.47 |
9.36 |
|
ITC33
|
Genova
|
6436 |
1.55 |
8.1 |
7.99 |
|
ITC34
|
La Spezia
|
3727 |
2.13 |
9.2 |
9.08 |
|
ITC41
|
Varese
|
4764 |
1.37 |
8.39 |
8.3 |
|
ITC42
|
Como
|
5405 |
1.21 |
5.95 |
5.86 |
|
ITC43
|
Lecco
|
6164 |
1.22 |
7.63 |
7.54 |
|
ITC44
|
Sondrio
|
4348 |
1.5 |
8.73 |
8.65 |
|
ITC46
|
Bergamo
|
5964 |
1.79 |
12.5 |
12.39 |
|
ITC47
|
Brescia
|
6108 |
1.36 |
6.21 |
6.11 |
|
ITC48
|
Pavia
|
4431 |
2.02 |
8.57 |
8.42 |
|
ITC49
|
Lodi
|
4541 |
1.42 |
7.7 |
7.61 |
|
ITC4A
|
Cremona
|
4188 |
1.55 |
7.96 |
7.82 |
|
ITC4B
|
Mantova
|
5281 |
1.75 |
7.92 |
7.78 |
|
ITC4C
|
Milano
|
17188 |
0.7 |
5.29 |
5.26 |
|
ITC4D
|
Monza e della Brianza
|
4929 |
1.39 |
7.13 |
7.04 |
|
ITF11
|
L'Aquila
|
2762 |
3.39 |
10.84 |
10.63 |
|
ITF12
|
Teramo
|
3336 |
2.22 |
6.75 |
6.33 |
|
ITF13
|
Pescara
|
3011 |
2.36 |
10.5 |
10.35 |
|
ITF14
|
Chieti
|
3103 |
2.07 |
10.76 |
10.62 |
|
ITF21
|
Isernia
|
2132 |
3 |
10.52 |
10.29 |
|
ITF22
|
Campobasso
|
6019 |
2.97 |
9.5 |
9.23 |
|
ITF31
|
Caserta
|
6724 |
3.14 |
9.36 |
8.74 |
|
ITF32
|
Benevento
|
2389 |
4.32 |
12.77 |
12.11 |
|
ITF33
|
Napoli
|
26199 |
1.41 |
4.01 |
3.83 |
|
ITF34
|
Avellino
|
3304 |
4.07 |
9.06 |
8.66 |
|
ITF35
|
Salerno
|
9471 |
2.54 |
5.16 |
4.73 |
|
ITF43
|
Taranto
|
3494 |
3.53 |
7.34 |
7 |
|
ITF44
|
Brindisi
|
3245 |
3.34 |
9.48 |
9.21 |
|
ITF45
|
Lecce
|
6710 |
2.67 |
6.35 |
6.07 |
|
ITF46
|
Foggia
|
4684 |
2.82 |
7.34 |
6.98 |
|
ITF47
|
Bari
|
10200 |
1.72 |
4.24 |
4.04 |
|
ITF48
|
Barletta-Andria-Trani
|
3567 |
3.57 |
7.65 |
7.29 |
|
ITF51
|
Potenza
|
11839 |
1.62 |
5.74 |
5.59 |
|
ITF52
|
Matera
|
5392 |
2.25 |
8.04 |
7.75 |
|
ITF61
|
Cosenza
|
5364 |
3.02 |
9.2 |
8.46 |
|
ITF62
|
Crotone
|
2026 |
5.45 |
17.79 |
17.2 |
|
ITF63
|
Catanzaro
|
3059 |
3.24 |
7.22 |
6.94 |
|
ITF64
|
Vibo Valentia
|
1926 |
4.23 |
9.94 |
9.44 |
|
ITF65
|
Reggio di Calabria
|
4954 |
2.55 |
8.41 |
8.18 |
|
ITG11
|
Trapani
|
3891 |
2.46 |
7.24 |
6.92 |
|
ITG12
|
Palermo
|
14223 |
1.96 |
4.15 |
3.86 |
|
ITG13
|
Messina
|
6901 |
2.15 |
5.86 |
5.6 |
|
ITG14
|
Agrigento
|
4883 |
3.32 |
6.3 |
5.92 |
|
ITG15
|
Caltanissetta
|
2902 |
4.3 |
9.34 |
8.33 |
|
ITG16
|
Enna
|
2983 |
3.22 |
9.79 |
9.38 |
|
ITG17
|
Catania
|
11420 |
2.26 |
5.3 |
4.96 |
|
ITG18
|
Ragusa
|
3848 |
2.46 |
10.83 |
10.27 |
|
ITG19
|
Siracusa
|
4286 |
2.71 |
7.16 |
6.74 |
|
ITG25
|
Sassari
|
3110 |
3.16 |
8.54 |
7.96 |
|
ITG26
|
Nuoro
|
1907 |
6.12 |
10.63 |
9.95 |
|
ITG27
|
Cagliari
|
3977 |
2.02 |
6.99 |
6.77 |
|
ITG28
|
Oristano
|
1688 |
2.7 |
5.48 |
5.04 |
|
ITG29
|
Olbia-Tempio
|
2346 |
3.94 |
9.82 |
9.41 |
|
ITG2A
|
Ogliastra
|
2238 |
5.04 |
10.35 |
9.4 |
|
ITG2B
|
Medio Campidano
|
1940 |
2.51 |
10.63 |
9.9 |
|
ITG2C
|
Carbonia-Iglesias
|
1717 |
3.19 |
9.32 |
8.87 |
|
ITH10
|
Bolzano/Bozen
|
15270 |
0.72 |
7.21 |
7.17 |
|
ITH20
|
Trento
|
16290 |
0.87 |
5.71 |
5.66 |
|
ITH31
|
Verona
|
4357 |
1.7 |
10.62 |
10.55 |
|
ITH32
|
Vicenza
|
4364 |
1.55 |
14.6 |
14.5 |
|
ITH33
|
Belluno
|
5270 |
1.31 |
8.77 |
8.68 |
|
ITH34
|
Treviso
|
3749 |
2.08 |
10.92 |
10.81 |
|
ITH35
|
Venezia
|
3747 |
2.63 |
9.25 |
8.99 |
|
ITH36
|
Padova
|
4443 |
1.53 |
8.48 |
8.38 |
|
ITH37
|
Rovigo
|
3036 |
2.13 |
11.71 |
11.6 |
|
ITH41
|
Pordenone
|
4173 |
1.42 |
9.81 |
9.74 |
|
ITH42
|
Udine
|
7248 |
1.58 |
8.27 |
8.2 |
|
ITH43
|
Gorizia
|
4259 |
1.74 |
8.65 |
8.51 |
|
ITH44
|
Trieste
|
3767 |
1.1 |
6.34 |
6.27 |
|
ITH51
|
Piacenza
|
6054 |
1.55 |
8.67 |
8.59 |
|
ITH52
|
Parma
|
5412 |
1.59 |
8.95 |
8.86 |
|
ITH53
|
Reggio nell'Emilia
|
6521 |
1.62 |
9.6 |
9.5 |
|
ITH54
|
Modena
|
4796 |
1.46 |
8.73 |
8.65 |
|
ITH55
|
Bologna
|
5962 |
1.18 |
7.68 |
7.62 |
|
ITH56
|
Ferrara
|
4229 |
1.52 |
6.52 |
6.44 |
|
ITH57
|
Ravenna
|
4046 |
1.66 |
9.41 |
9.28 |
|
ITH58
|
Forlì-Cesena
|
3962 |
1.81 |
15.91 |
15.82 |
|
ITH59
|
Rimini
|
3214 |
2.36 |
11.63 |
11.48 |
|
ITI11
|
Massa-Carrara
|
1953 |
2.61 |
11.46 |
11.26 |
|
ITI12
|
Lucca
|
3707 |
2.47 |
8.69 |
8.5 |
|
ITI13
|
Pistoia
|
2508 |
2.76 |
10.02 |
9.83 |
|
ITI14
|
Firenze
|
5044 |
1.34 |
7.94 |
7.89 |
|
ITI15
|
Prato
|
2477 |
1.19 |
9.52 |
9.46 |
|
ITI16
|
Livorno
|
3387 |
1.93 |
9.4 |
9.18 |
|
ITI17
|
Pisa
|
3740 |
1.42 |
8.38 |
8.25 |
|
ITI18
|
Arezzo
|
3215 |
1.62 |
8.43 |
8.32 |
|
ITI19
|
Siena
|
4901 |
1.49 |
7.28 |
7.16 |
|
ITI1A
|
Grosseto
|
3596 |
1.76 |
10.81 |
10.67 |
|
ITI21
|
Perugia
|
11079 |
0.99 |
5.63 |
5.56 |
|
ITI22
|
Terni
|
3512 |
2.78 |
7.78 |
7.49 |
|
ITI31
|
Pesaro e Urbino
|
4671 |
2.13 |
6.82 |
6.62 |
|
ITI32
|
Ancona
|
4159 |
1.54 |
10.67 |
10.61 |
|
ITI33
|
Macerata
|
3554 |
2.1 |
9.56 |
9.37 |
|
ITI34
|
Ascoli Piceno
|
2269 |
2.25 |
8.95 |
8.76 |
|
ITI35
|
Fermo
|
2855 |
2.12 |
10.73 |
10.61 |
|
ITI41
|
Viterbo
|
3486 |
3.09 |
10.09 |
9.92 |
|
ITI42
|
Rieti
|
3621 |
2.22 |
9.49 |
9.25 |
|
ITI43
|
Roma
|
27927 |
0.72 |
3.38 |
3.33 |
|
ITI44
|
Latina
|
4540 |
2.3 |
5.56 |
5.33 |
|
ITI45
|
Frosinone
|
3625 |
3.32 |
7.88 |
7.49 |
| For the calculation of the CV for NUTS-3 regions, the national design effect can be used as an approximation of the true regional design effect. Please indicate if this approximation is used (Y/N): |
| N |
|
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)
|
|
| Undercoverage |
Overcoverage |
Misclassification (b) |
Reference on frame errors |
| |
2.17 |
1.63 |
Households are selected once a year from the municipalities’ registry offices; they cover the whole reference population. The frame 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, each non-responding household is replaced with a household having similar characteristics of the first one (more precisely, they live in the same address and the reference persons have the same citizenship), in order to maintain as much as possible the sample representativeness and to minimise the impact of unit non-response. No more than 3 substitutions are admitted. |
|
|
|
|
6.3.1.1 Over-coverage - rate |
[Over-coverage rate, please see chapter 6.3.1 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 2015 |
October 2014 |
1,019 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? |
LFS likely underestimates irregular workers and employed people having a second job. No quantitative assessment of this effect is available. |
|
|
| Part-time employment |
NA |
|
|
|
| Unemployment |
NA |
|
|
|
| Numbers of hours actually worked |
NA |
LFS likely overestimates the number of hours actually worked, due to underestimation of the absences. No quantitative assessment of this effect is available. |
|
|
| Other characteristic |
NA |
|
|
|
| Other characteristic |
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 |
In the second step (see the “description of method” column), correction factors for household non-response are computed according to household typologies (number of family 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. First, 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 cells identified by household typologies and territorial domains). Intermediate weights corrected for non-response are then computed multiplying initial weights by these correction factors.
3. Finally, starting from intermediate weights, final grossing weights are obtained through calibration, 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. This estimator is able to reduce the bias effect of unit non-response. |
| Substitution of non-responding units (Y/N?) |
Substitution rate |
Criteria for substitution |
| Y |
32.2% of the first selected households have been substituted: 22.1% have been substituted with the first substitute unit, 6.6% with the second one, 3.5% 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 collection 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 timely notify 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 pose several computational problems that the entire set of edits needs 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 |
| 28.5 |
5.4 |
5.3 |
3.7 |
NA |
NA |
NA |
NA |
| Rates of non response by survey mode. Annual average |
| Survey |
| CAPI |
CATI |
PAPI |
CAWI |
POSTAL |
| 23.3 |
3.9 |
NA |
NA |
NA |
| Divisions of non-response into categories. Quarterly data and annual average |
| Quarter |
Non response rate (%) |
Refusals (%) |
Non-contacts (%) |
Other reasons(%) |
| 1 |
12.32 |
4.41 |
7.03 |
0.88 |
| 2 |
12.76 |
4.34 |
7.41 |
1.01 |
| 3 |
12.63 |
4.32 |
7.53 |
0.78 |
| 4 |
12.20 |
4.43 |
7.05 |
0.71 |
| Annual |
12.48 |
4.37 |
7.26 |
0.85 |
| Rates of non response. Annual average |
| NUTS-2 region (code + name) |
Non response rate (%) |
| ITC1 Piemonte |
14.0 |
| ITC2 Valle d’Aosta/Vallée d’Aoste |
11.7 |
| ITC3 Liguria |
11.2 |
| ITC4 Lombardia |
12.5 |
| ITF1 Abruzzo |
10.4 |
| ITF2 Molise |
9.4 |
| ITF3 Campania |
14.6 |
| ITF4 Puglia |
12.1 |
| ITF5 Basilicata |
10.2
|
| ITF6 Calabria |
14.5
|
| ITG1 Sicilia |
14.5
|
| ITG2 Sardegna |
11.1
|
ITH1 Provincia Autonoma di Bolzano/
Bozen |
9.9
|
| ITH2 Provincia Autonoma di Trento |
13.4
|
| ITH3 Veneto |
11.9
|
| ITH4 Friuli-Venezia Giulia |
13.0
|
| ITH5 Emilia-Romagna |
11.3
|
| ITI1 Toscana |
11.1
|
| ITI2 Umbria |
12.0
|
| ITI3 Marche |
12.5
|
| ITI4 Lazio |
12.2
|
| Rates of non response. Annual average |
| NUTS-3 region (code + name) |
Non response rate (%) |
| ITC11 Torino |
15.2 |
| ITC12 Vercelli |
9.3 |
| ITC13 Biella |
13.3 |
| ITC14 Verbano-Cusio-Ossola |
14.9 |
| ITC15 Novara |
15.2 |
| ITC16 Cuneo |
14.3 |
| ITC17 Asti |
13.0 |
| ITC18 Alessandria |
14.0 |
| ITC20 Valle d’Aosta/Vallée d’Aoste |
11.7 |
| ITC31 Imperia |
11.9 |
| ITC32 Savona |
7.8 |
| ITC33 Genova |
14.4 |
| ITC34 La Spezia |
8.6 |
| ITC41 Varese |
9.1 |
| ITC42 Como |
12.2 |
| ITC43 Lecco |
7.6 |
| ITC44 Sondrio |
10.4 |
| ITC4C Milano |
15.3 |
| ITC4D Monza e della Brianza |
15.4 |
| ITC46 Bergamo |
12.9 |
| ITC47 Brescia |
14.9 |
| ITC48 Pavia |
12.3 |
| ITC49 Lodi |
8.1 |
| ITC4A Cremona |
10.0 |
| ITC4B Mantova |
12.0 |
| ITF11 L’Aquila |
16.3 |
| ITF12 Teramo |
7.8 |
| ITF13 Pescara |
7.0 |
| ITF14 Chieti |
9.8 |
| ITF21 Isernia |
12.4 |
| ITF22 Campobasso |
8.2 |
| ITF31 Caserta |
17.6 |
| ITF32 Benevento |
17.6 |
| ITF33 Napoli |
12.6 |
| ITF34 Avellino |
15.1 |
| ITF35 Salerno |
16.5 |
| ITF46 Foggia |
10.9 |
| ITF47 Bari |
13.0 |
| ITF48 Barletta-Andria-Trani |
8.9 |
| ITF43 Taranto |
12.8 |
| ITF44 Brindisi |
13.8 |
| ITF45 Lecce |
11.8 |
| ITF51 Potenza |
9.9 |
| ITF52 Matera |
11.0 |
| ITF61 Cosenza |
14.5 |
| ITF62 Crotone |
13.1 |
| ITF63 Catanzaro |
10.8 |
| ITF64 Vibo Valentia |
14.4 |
| ITF65 Reggio di Calabria |
17.1 |
| ITG11 Trapani |
14.0 |
| ITG12 Palermo |
14.3 |
| ITG13 Messina |
17.0 |
| ITG14 Agrigento |
18.2 |
| ITG15 Caltanissetta |
11.2 |
| ITG16 Enna |
7.8 |
| ITG17 Catania |
14.5 |
| ITG18 Ragusa |
13.3 |
| ITG19 Siracusa |
13.5 |
| ITG25 Sassari |
11.4 |
| ITG26 Nuoro |
11.7 |
| ITG27 Cagliari |
10.9 |
| ITG28 Oristano |
13.4 |
| ITG29 Olbia-Tempio |
10.6 |
| ITG2A Ogliastra |
8.9 |
| ITG2B Medio Campidano |
9.9 |
| ITG2C Carbonia-Iglesias |
13.0 |
| ITH10 Bolzano-Bozen |
9.9 |
| ITH20 Trento |
13.4 |
| ITH31 Verona |
9.1 |
| ITH32 Vicenza |
14.0 |
| ITH33 Belluno |
11.3 |
| ITH34 Treviso |
11.1 |
| ITH35 Venezia |
15.4 |
| ITH36 Padova |
13.3 |
| ITH37 Rovigo |
7.6 |
| ITH41 Pordenone |
9.1 |
| ITH42 Udine |
15.8 |
| ITH43 Gorizia |
13.1 |
| ITH44 Trieste |
11.6 |
| ITH51 Piacenza |
7.6 |
| ITH52 Parma |
12.6 |
| ITH53 Reggio nell’Emilia |
9.1 |
| ITH54 Modena |
12.9 |
| ITH55 Bologna |
12.5 |
| ITH56 Ferrara |
8.6 |
| ITH57 Ravenna |
15.1 |
| ITH58 Forlì-Cesena |
15.1 |
| ITH59 Rimini |
9.6 |
| ITI11 Massa-Carrara |
13.3 |
| ITI12 Lucca |
14.5 |
| ITI13 Pistoia |
11.6 |
| ITI14 Firenze |
10.3 |
| ITI15 Prato |
14.7 |
| ITI16 Livorno |
16.4 |
| ITI17 Pisa |
9.7 |
| ITI18 Arezzo |
10.1 |
| ITI19 Siena |
7.9 |
| ITI1A Grosseto |
5.7 |
| ITI21 Perugia |
11.4 |
| ITI22 Terni |
13.7 |
| ITI31 Pesaro e Urbino |
10.9 |
| ITI32 Ancona |
10.6 |
| ITI33 Macerata |
15.4 |
| ITI34 Ascoli Piceno |
14.1 |
| ITI35 Fermo |
12.6 |
| ITI41 Viterbo |
12.7 |
| ITI42 Rieti |
9.6 |
| ITI43 Roma |
12.8 |
| ITI44 Latina |
12.3 |
| ITI45 Frosinone |
9.2 |
| 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 |
7 |
5.1 |
16.7 |
7.1 |
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 |
19.4 |
20.4 |
20.2 |
19.1 |
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 |
25.8 |
27.4 |
26.7 |
26.7 |
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 |
12.4 |
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 rate in% |
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] |
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 |
7.1 Timeliness |
Quarterly LFS data
Reference period, transmission date and coverage |
| Quarter |
Main dates in the national production process |
| |
Date of data collection beginning |
Date of end of the quality check for statistics requested by Eurostat |
Date of national publication |
| 1 |
05/01/2015 |
09/06/2015 |
03/06/2015 |
| 2 |
06/04/2015 |
08/09/2015 |
01/09/2015 |
| 3 |
06/07/2015 |
19/11/2015 |
11/12/2015 |
| 4 |
05/10/2015 |
22/02/2016 |
10/03/2016 |
| NUTS-3 level LFS data on unemployment and labour force: Reference period, transmission date and coverage |
| Main dates in the national production process |
| Date of data collection beginning |
Date of end of the quality check for statistics requested by Eurostat |
Date of national publication |
| 05/01/2015 |
22/02/2016 |
10/03/2016 |
|
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 |
| Quarterly LFS Data : |
| Delay of delivery to Eurostat of the full dataset or of the main characteristics and reasons for late delivery |
|
| Quarter |
Full dataset
|
Single characteristic(s)
|
| |
Deadline |
Delivery date |
Reason for late delivery |
Characteristic(s) |
Delay (days) |
Reason for late delivery |
| 1 |
21-Jun-15 |
08-Jun-15 |
|
|
|
|
| 2 |
20-Sep-15 |
08-Sep-15 |
|
|
|
|
| 3 |
20-Dec-15 |
11-Dec-15 |
|
|
|
|
| 4 |
27-Mar-16 |
10-Mar-16 |
|
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|
|
| Yearly weights (*) |
|
|
|
|
|
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| Measures to improve timeliness and punctuality |
| Quarter |
Ways for improving |
| 1 |
From 1° quarter 2012 editing and imputation process has been improved in order to deliver earlier final micro-data file. At the moment we do not see any further possible improvement. |
| 2 |
|
| 3 |
|
| 4 |
|
| NUTS-3 level LFS data on unemployment and labour force : |
| Reason for late delivery to Eurostat |
| NA |
| NUTS-3: Ways for improving timeliness |
| NA |
|
7.2.1 Punctuality - delivery and publication |
[not requested for the LFS quality report] |
8. Coherence and comparability |
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 |
| NA |
|
| 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 |
| NA |
|
| 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 |
| 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 |
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 |
NA |
|
|
|
| coverage (i.e. target population) |
NA |
|
|
|
| legislation |
NA |
|
|
|
| classifications |
NA |
|
|
|
| geographical boundaries |
NA |
|
|
|
| Changes at MEASUREMENT level introduced during the reference year and affecting comparability with previous reference periods (including breaks in series) |
| Changes to |
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 |
NA |
|
|
|
| sample design |
NA |
|
|
|
| rotation pattern |
NA |
|
|
|
| questionnaire |
NA |
|
|
|
| instruction to interviewers |
NA |
|
|
|
| survey mode |
NA |
|
|
|
| weighting scheme |
NA |
|
|
|
| use of auxiliary information |
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 |
LFS estimates the number of employed persons, both in regular or irregular jobs, whatever the number of jobs they have. Business statistics consider the number of regular jobs i.e. complying with tax and social security legislation and which can therefore be traced by business surveys, institutional and administrative sources. |
|
Even if the number of different sources used by business statistics and the significant differences in concepts and measures between LFS and business statistics make it difficult to evaluate the impact on the final estimates, an integrated approach is being used in the analysis of labour market data: quarterly estimates obtained from LFS and business surveys are disseminated in a unique press-release, in which an analysis on the labour market is condicted considering both the supply and the demand sides. |
|
| Total employment by NACE |
Business 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 having 100 workers and more. Further ISTAT’s surveys focus on businesses in the field of agriculture. 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 actually and usually worked. Business surveys collect information on firm's total amount of hours (thus considering only regular worked hours for employees) |
|
|
| 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 |
|
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 ;k)since september 2014 the National Institute of Statistics releases the estimates of national accounts in accordance with the definitions of the European System of Accounts (Esa 2010) and Council Regulation n. 549/2013, so the new national accounts include illegal activities and the relative employment. 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 2015:
LFS (employment): 22,465 thousands; NA (employment): 24,481 thousands; NA (ULA): 23,506 thousands |
Details on the methodology used by the National Account to estimate employment have been provided in the report “I nuovi Conti nazionali in SEC 2010” of 6th October 2014 (http://www.istat.it/it/files/2014/10/Nuovi_conti-2014_NOTA-INFORMATIVA_defdocx.pdf?title=I+nuovi+conti+nazionali+in+SEC+2010+-+06%2Fott%2F2014+-+Testo+integrale.pdf).
|
| 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 |
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: Istat website is the the main dissemination media for Italian LFS. As a matter of facts, all publications and a large set of already processed indicators are freely available on line on the corporate datawarehouse, I.STAT. Specific user requests of indicators not already available are usually satisfied. A preliminary check on estimates reliability is performed, It is asked the payment of a fee which covers the cost related to 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 and Municipalities; Universities or researchers; other public users. The first two users groups access to a greater level of detail in comparison with other users. Micro data files for public users are available on the Istat website, to acquirethem it is necessary to register at the dedicated area of the Istat website.
Another difference concerns the list of blanked variables. For SISTAN users only variables affected by reliability problems are blanked, whereas for other users some variables are blanked also because of anonymization reasons.
Istat also gives external users the possibility to process microdata in his premise in a dedicated 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 respects 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 |
Number of staff involved in central and regional offices, excluding interviewers
Consider only staff directly employed by the NS |
| |
Full-time equivalents |
| Total |
34 |
| - of which professional and managerial |
10 |
| Duration of the interview |
|
Minutes |
| Total |
First wave |
Later waves |
| Average time spent in the household |
10.1 |
15.0 |
7.6 |
| Core questionnaire (pr person) |
3.7 |
5.0 |
3.2 |
| Ad hoc questionnaire (pr person) |
- |
- |
- |
| 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. |
| Number of units |
| |
Number |
| Total |
First wave |
Later waves |
| Households visited over the year |
261,081 |
69,034 |
192,047 |
| Persons interviewed over the year |
597,872 |
160,047 |
437,825 |
| Persons interviewed for the ad hoc module over the year |
- |
- |
- |
|
11. Confidentiality |
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 |