Reference metadata describe statistical concepts and methodologies used for the collection and generation of data. They provide information on data quality and, since they are strongly content-oriented, assist users in interpreting the data. Reference metadata, unlike structural metadata, can be decoupled from the data.
The Structure of Earnings Survey (SES) is a 4-yearly survey which provides EU-wide harmonised structural data on gross earnings, hours paid and annual days of paid holiday leave, which are collected every four years under Council Regulation (EC) No 530/1999 concerning structural statistics on earnings and on labour costs, and Commission Regulation (EC) No 1738/2005 amending Regulation (EC) No 1916/2000 as regards the definition and transmission of information on the structure of earnings.
The SES 2018 provides detailed information on relationships between the level of hourly, monthly and annual remuneration, personal characteristics of employees (sex, age, occupation, length of service, highest educational level attained, etc.) and their employer (economic activity, size and economic control of the enterprise).
Regional data is available on NUTS1 level.
2.2. Classification system
The economic activity is coded in NACE Rev. 2 whereas the occupation is coded in ISCO-08.
Information on the highest successfully completed level of education and training varable is classified using the ISCED2011.
2.3. Coverage - sector
The Albanian SES refers to local units belonging to enterprises with at least 10 employees in the areas of economic activities defined by NACE Rev. 2 sections B to S excluding O.
2.4. Statistical concepts and definitions
Employees are all persons who have a direct employment contract with the enterprise or local unit and receive remuneration, irrespective of the type of work performed, the number of hours worked (full or part-time), and the duration of the contract (fixed or indefinite).
Average annual gross earnings also cover all 'non-standard payments', i.e. payments not occurring in each pay period, such as 13th or 14th-month payments, holiday bonuses, quarterly or annual company bonuses, and annual payments in kind.
Average monthly gross earnings in the reference month cover remuneration in cash paid before any tax deductions and social security contributions payable by wage earners and retained by the employer, and are restricted to gross earnings which are paid in each pay period during the reference month.
Average hourly gross earnings are defined as gross earnings in the reference month divided by the number of hours paid during the same period.
The number of hours paid includes all normal and overtime hours worked and remunerated by the employer during the reference month. Hours not worked but nevertheless paid are counted as 'paid hours' (e.g. for annual leave, public holidays, paid sick leave, paid vocational training, paid special leave, etc.).
2.5. Statistical unit
The statistical unit is the enterprise and the employees working within the selected unit.
2.6. Statistical population
The population of employees covered in the SES are those who received remuneration for the reference month (October), as requested by the Regulation, in the enterprises and institutions belonging to the Private and Public sectors with at least 10 employees in the NACE Rev. 2 sections B to S excluding O.
2.7. Reference area
Data cover the entire country and aggregate estimates are disseminated at national level and NUTS 1 level.
2.8. Coverage - Time
The structure of the Earning Survey is conducted for the first time in 2019.
2.9. Base period
Not Applicable.
3.1. Source data
As a source of data for SES is the survey on enterprises. The frame population for SES 2018 contains 124,186 unique enterprises from the Business register that have local unit’s information in it with the respective geographical information. The stratification criteria were the economic activity, the number of employed, and the region of the local unit.
The SES 2018 was conducted based on a two-stage sampling approach. In the first stage, a stratified random sample of local units was drawn. The sample size selected is 3,381 enterprises.
The questionnaire, the explanation, and a list of local units for which the survey needed to be filled were sent to the head offices of the selected local units. In the second stage, the local unit had to select a number of employees according to the instructions in the explanation.
With regard to the size of the enterprise, Albania chose to exclude small enterprises with fewer than ten employees. We also excluded the NACE section O in our sample. This means that the Albanian datasets only include the local units covered by the Regulation.
Distribution of sampled enterprises based on “number of employed" size classes is given as follows:
Total number of employed
Proportion
10 - 49 employed
50%
50 - 249 employed
25%
250 - 499 employed
22%
500 - 999 employed
20%
1000+ employed
13%
3.2. Frequency of data collection
Every 4 years.
3.3. Data collection
The data were collected using the PAPI method, Paper Assisted Personal Interview. In some cases, electronic questionnaires were sent by e-mail.
An important phase in the preparation for data collection is the preparation of all the necessary materials and the preparation of data entry software. Should be identified the enterprises to be interviewed, the sample is divided among enumerators; the enumerators are selected and trained. At the training, the enumerators receive the preparation materials such as guidelines of the questionnaire, enumerator’s tasks, list of economic activity, notification letter for enterprises.
Everything reported by enterprises is recorded in the data collection process. In case of lack of clarity, the reporting unit is contacted. In the case of non-reporting, an official letter signed by the head of the Institution is sent to the reporting unit. The enumerator is required to behave ethically in the event of refusals by enterprises.
3.4. Data validation
Data validation consists of global checks and plausibility checks. Global checks are necessary to ensure that complete data are available. Plausibility checks on all variables were done to ensure that the data are reasonable and consistent with other variables. In addition, more checks were done during the analysis stage where data was compared with administrative data.
In terms of data validation, data editing procedures generally refer to micro-level or otherwise enterprise-level editing.
Data editing in the data entry program.
Control of incoming questionnaires, Completeness checks, valid values checks, range checks, logical control of the questionnaire. The number of incoming questionnaires should be equal to the number of distributed questionnaires in the prefectures.
Individual checks are done for cases of refusal and no contacts.
The answered active enterprises are checked for the coherence of data given in different sessions of the questionnaire.
2. Control of some questions through the information that can be found from individual contact of the enterprise.
An appropriate weight is calculated for each unit that reported its data. This weight is calculated for various reasons: the unequal probability of selection, nonresponse adjustment, enterprises that result out of scope. Outlier treatment is taken into consideration at the weighting procedure
3.5. Data compilation
The process of data compilation is done through two procedures:
Quality of data
There are applied some rules for analyzing the quality of data:
- Mathematic control of the questionnaire · Logic control of the questionnaire’s data
- Comparison of data with administrative register
- Analyze huge deviations from average.
Treatment of non-response
Are considered as all cases of:
- Non-contact
- Full refuse
- Partial refuses (for different indicators).
The treatment of non-response is done using direct methods or their combinations such as:
- Data from the administrative register;
- Data from enterprises that have similar conditions are used.
3.6. Adjustment
Not applicable.
4.1. Quality assurance
INSTAT is committed to ensuring the highest quality with respect to the compilation of official statistics. In accordance with the “Law on Official Statistics”, Nr.17/2018, date 17.04.2018, INSTAT use statistical methods and processes in compliance with internationally recognized scientific principles and standards and conduct ongoing analyses of the statistics with a view to quality improvements and ensure that statistics are as up-to-date. In performing its tasks, INSTAT follows the general principles of quality management in line with the European Statistics Code of Practice. INSTAT declares that it takes into account the following principles: impartiality, quality of processes and products, user orientation, employee orientation, the effectiveness of statistical processes, reducing the workload for respondents. Quality controls and validation of data are actions carried out throughout the process. The staff is involved in different stages such as the data collection, data control, data input and other final controls.
4.2. Quality management - assessment
SES microdata is checked for completeness and consistency. They are checked for any large changes in the data, especially due to large deviations in the main variables concerned. In case of changes, data from other available sources are used to confirm the situation of cases where are encountered large differences in the behavior of any unit within the dataset.
5.1. Relevance - User Needs
The results and data of the Structure of Earnings Survey (SES) are often used by the Albanian general public. Students, Research centres, Universities, Trade unions, The Media, Private companies and Public administration institutions can all be considered as important users of the SES.
SES is the only national source where earnings can be linked with important personal characteristics such as the level of education or the occupation of the worker. The rather unique combination between individual features on the one hand and enterprise characteristics on the other hand can also explain the broad use of the SES.
5.2. Relevance - User Satisfaction
No User Satisfaction Survey referring to the SES data is carried out.
5.3. Completeness
All requirements of the regulation are met.
5.3.1. Data completeness - rate
The degree of completeness of the data, for the SES 2018 is 100%. This calculation took into account Council Regulation (EC) No 530/1999 concerning structural statistics on earnings and on labour costs, and Commission Regulation (EC) No 1738/2005 amending Regulation (EC) No 1916/2000 as regards the definition and transmission of information on the structure of earnings.
6.1. Accuracy - overall
Overall, the data is checked to identify any significant changes within the dataset. Where changes occur, the survey data is checked with alternative sources, if any. When there is no information from alternative sources, INSTAT corrects or confirms the data using emails or by calling the respondents. Measures taken by INSTAT for SES, to increase response rates or to reduce the impact of nonresponse by imputing them are as follow:
Data are collected directly from the enterprise.
The enumerator's staff is trained on how to handle difficult respondents.
Due to the lack of an address system, it is often difficult for enumerators to find enterprise. For this reason, INSTAT staff, via email addresses or phone numbers, contacts the person responsible for completing the survey and receives more information on the location as well as the date and time of the meeting.
Priority is given to larger businesses. When these enterprises refuse to respond to the interviewer, an official request, in particular, is directed for the president of enterprises and signed by INSTAT director-general; it is also done for enterprises that require only this way to give the information.
A formal request is also sent to other companies that agree to respond only if the information is formally requested.
The enterprises are invited to contact the Statistical Office in case of questions and always qualified staffs are available to answer the enterprise's calls.
In order to detect outliers and other quality problems, several aggregated checks were integrated into different data collection tools.
More complicated inconsistency problems were solved internally or by contacting the local unit on a bilateral basis.
6.2. Sampling error
Please refer to Annex1 for the Coefficients of variation for the main indicators estimates. All indicators values are weighted to represent the whole population.
6.2.1. Sampling error - indicators
In Annex1 are shown the Coefficients of variation for the Average of Gross Monthly earnings and Coefficients of variation for the Average of Gross Hourly earnings.
6.3. Non-sampling error
Since the SES is a sample survey, all SES estimates are subject to both sampling error and non-sampling errors. The non-sampling errors can arise at any stage of the collection and processing of the survey data and include all errors not related to the selection. These include measurement errors, response errors, interviewer errors, processing errors, etc. Interviewers are instructed to make all reasonable attempts to obtain SES interviews with employees of selected enterprises. After all, attempts have been made to obtain interviews completed, a small number of unit non-response remained still. For more refer to Annex 2.
Data completeness is one of the advantages of an administrative register. Consequently, for non-responses, we impute information through tax administrative authorities.
6.3.1. Coverage error
Over-coverage occurs when a unit is registered in SBR as active, but during the interview, the status is not active anymore (closed/sleeping) or changed the size of the enterprise (less than 10 employed) and are not within the scope of the survey.
6.3.1.1. Over-coverage - rate
Over coverage rate for SES 2018 is 7.93%.
6.3.1.2. Common units - proportion
Not applicable.
6.3.2. Measurement error
Measurement errors may result due to the reporting units and interviewers. Errors in interviewing are identified whenever survey follow-ups are conducted. These errors are fixed accordingly. Other errors are captured during data editing and coding stage, or at the data cleaning stage. Imputations are used to fix these errors accordingly.
6.3.3. Non response error
For all unit non-response data completeness is assured by the usage of administrative register information. Consequently, for non-responses, we impute information through tax administative authorities.
6.3.3.1. Unit non-response - rate
See 6.3.
6.3.3.2. Item non-response - rate
See 6.3.
6.3.4. Processing error
Processing errors result from codification errors. National occupation codes (according to ISCO-08), Level of Education (ISCED2011) and Economic activity codes (NACE Rev2) are inserted based on the free text option in the questionnaire (job title and description of the job; economic activity description and name of the place of work, and the highest successfully completed level of education and training variables) are carefully checked.
6.3.4.1. Imputation - rate
For the Structure of Earnings Survey, the response rate was 80.7%. The rest was imputed by INSTAT from administrative data. Anex.2 shows the response rate by economic activities.
6.3.5. Model assumption error
Not applicable.
6.4. Seasonal adjustment
No seasonal adjustments are made to the SES data
6.5. Data revision - policy
Structure of Earning Statistics Review Policies is made in accordance with the revision policy and the policy of settling errors set by INSTAT. For more information refer to:
The time lag between the delivery date and the end of the reference period is approximately 680 days (T+680). Publication takes place strictly in accordance with published release dates for Labour Market Statistics in the INSTAT webpage.
7.1.1. Time lag - first result
The structure of Earning Statistics data does not include the publication of a preliminary result.
7.1.2. Time lag - final result
The results of the SES are published based on the publication calendar, in the INSTAT website, with the frequency every 4 years.
7.2. Punctuality
At the end of each year, INSTAT publishes a Fixed Release Calendar ( Calendar | Instat ) for the next year
7.2.1. Punctuality - delivery and publication
For the results of SES 2018, INSTAT has been punctual in time, 100%.
8.1. Comparability - geographical
The SES 2018 complies with the standard set up on the Council Regulation (EC) No 530/1999 concerning structural statistics on earnings and on labour costs and with the definitions of variables adopted in the Commission Regulation 1737/2005. The sampling unit in the first stage is the enterprises, but the register information allows to localize the employee in the region in which he/she is employed.
8.1.1. Asymmetry for mirror flow statistics - coefficient
Calculated by EUROSTAT.
8.2. Comparability - over time
Not applicable. SES is conducted for the first time in INSTAT.
8.2.1. Length of comparable time series
Not applicable.
8.3. Coherence - cross domain
The only possible data source to which data from SES could be compared is regular Monthly administrative data on persons employed and wages. See cross-domain comparison on Annex 3. For this purpose, data on monthly gross earnings per employee for October 2018 from both sources were compared. The differences in data come out from coverage. Data from SES 2018 are sample-based while those from Administrative sources relate to all of the persons employed in each activity NACE section.
8.4. Coherence - sub annual and annual statistics
Not applicable.
8.5. Coherence - National Accounts
Not applicable.
8.6. Coherence - internal
Internal data consistency has been checked before finalizing SES results. The links between the variables and the coherence within the data set are also checked before the publication.
9.1. Dissemination format - News release
The press release contains information on key indicators provided by the survey such as Structure of employment, wages, hours of work, gender pay gap, etc. The press release is published online on INSTAT's website.
Databases at the micro-level are not published due to confidentiality reasons. Aggregated data is the only type of data that is provided to external users. Even the micro data are not published they can be accessed based on the article 34, point 17 of Law No. 17/2018, “On official statistics”.
9.5. Dissemination format - other
Users can submit specific requests for data from the SES survey through the INSTAT website, dedicated section: Data request
9.6. Documentation on methodology
Methodological documentation on SES 2018 is done the following 'Implementing arrangements for SES 2018' provided by Eurostat.
9.7. Quality management - documentation
Labour Market and Wages Statistics sector document the entire work process and the Structure of Earning Survey procedures for internal purposes.
9.7.1. Metadata completeness - rate
Calculated by EUROSTAT.
9.7.2. Metadata - consultations
Not applicable
Persons working for SES are: • Total staff in Central Office: 2 employees • Not permanent staff of INSTAT: 4 Operators • Staff in Regional Offices: 70 Interviewers, 15 Controllers.
11.1. Confidentiality - policy
Data are considered strictly confidential and are used only for statistical and research purposes based on national “Law on Official Statistics”, No.17/2018, and on Law No.9887, date 10.03.2008 “Personal Data Protection”. Article 31 of the “Law on Official Statistics”, reads as follows: Data collected for the production of official statistics shall be treated by INSTAT as confidential and shall be used only in aggregated tables that will not identify the source information unit. Direct identification means when a statistical unit is directly identified from its name, address or any officially allocated and commonly known identification number. When data processing is made in a manner that allows the identification of the data subject, the data should immediately be encrypted in order for the subjects to be no longer identifiable.
11.2. Confidentiality - data treatment
In accordance with national Statistical Law No.17/2018 “On Official Statistics”, at microdata level, Name/Surname, date/month/year of birth, workplace and the employer’s name and address are excluded.
Annex 1: Coefficients of variation
Coefficients of variation - Monthly earnings
MEAN
SE
CV (%)
Total
50,735
74
0.1
Full-time men
53,185
120
0.2
Full-time women
48,429
88
0.2
Part-time men
44,929
472
1.1
Part-time women
45,712
640
1.4
NACE
B
81,794
1,035
1.3
C
35,008
110
0.3
D
77,726
431
0.6
E
41,903
197
0.5
F
45,096
236
0.5
G
40,358
136
0.3
H
53,036
493
0.9
I
33,282
165
0.5
J
74,784
865
1.2
K
102,351
850
0.8
L
50,345
1,789
3.6
M
63,812
461
0.7
N
56,720
257
0.5
P
61,794
145
0.2
Q
56,543
204
0.4
R
54,937
586
1.1
S
56,957
657
1.2
Occupation
1
98,892
735
0.7
2
67,162
159
0.2
3
61,120
326
0.5
4
57,121
219
0.4
5
35,426
114
0.3
6
29,550
250
0.8
7
36,479
114
0.3
8
37,798
120
0.3
9
33,415
93
0.3
Age
< 20
33,423
243
0.7
20-29
45,960
113
0.2
30-39
53,541
145
0.3
40-49
51,672
172
0.3
50-59
51,052
174
0.3
≥ 60
56,946
393
0.7
Region (NUTS 1)
AL
50,735
74
0.1
Size
E10_49
41,830
116
0.3
E50_249
47,911
128
0.3
E250_499
54,144
202
0.4
E500_499
69,786
325
0.5
E1000
63,200
173
0.3
ISCED
1(Basic Education)
31,825
109
0.3
2 (Secondary Education)
38,393
71
0.2
3 (Tertiary education)
63,044
165
0.3
4 (Master/Doctoral
72,537
226
0.3
Coefficients of variation - Hourly earnings
MEAN
SE
CV (%)
Total
293
0.4
0.1
Full-time men
302
0.7
0.2
Full-time women
281
0.5
0.2
Part-time men
321
3.4
1.1
Part-time women
326
4.4
1.4
NACE
B
464
5.8
1.2
C
195
0.6
0.3
D
441
2.5
0.6
E
239
1.1
0.5
F
253
1.3
0.5
G
224
0.8
0.3
H
300
2.8
0.9
I
187
0.9
0.5
J
423
4.8
1.1
K
586
4.9
0.8
L
292
10.3
3.5
M
363
2.6
0.7
N
333
1.5
0.5
P
389
0.9
0.2
Q
326
1.2
0.4
R
313
3.3
1.1
S
331
3.8
1.2
Occupation
1
568
4.2
0.7
2
399
0.9
0.2
3
348
1.8
0.5
4
333
1.3
0.4
5
200
0.7
0.3
6
161
1.5
0.9
7
204
0.6
0.3
8
211
0.7
0.3
9
189
0.5
0.3
Age
< 20
193
1.5
0.8
20-29
264
0.7
0.2
30-39
308
0.8
0.3
40-49
299
1.0
0.3
50-59
295
1.0
0.3
≥ 60
330
2.2
0.7
Region
AL
293
0.4
0.1
Size
E10_49
238
0.7
0.3
E50_249
273
0.7
0.3
E250_499
313
1.2
0.4
E500_499
405
1.8
0.4
E1000
378
1.0
0.3
ISCED
1(Basic Education)
178
0.6
0.4
2 (Secondary Education)
217
0.4
0.2
3 (Tertiary education)
366
0.9
0.3
4 (Master/Doctoral
428
1.3
0.3
Annex 2: Response rate (percent), by NACE section
Economic Activity
Response rate (percent)
Total
80.7
B
84.0
C
85.6
D
70.6
E
90.1
F
78.2
G
80.0
H
84.3
I
83.0
J
72.7
K
73.3
L
80.0
M
75.0
N
74.9
P
79.4
Q
85.1
R
79.7
S
74.3
Annex 3: Average monthly earnings per employee by economic activity
NACE rev.2
SES (B42)
Administrative data (Average monthly wage, October 2018)
(SES-Administrative data )/SES %
B
81,794
83,584
-2.19
C
35,008
34,432
1.65
D
77,726
73,020
6.05
E
41,903
38,406
8.35
F
45,096
43,687
3.13
G
40,358
38,457
4.71
H
53,036
44,822
15.49
I
33,282
28,149
15.42
J
74,784
76,127
-1.80
K
102,351
101,955
0.39
L
50,345
44,627
11.36
M
63,812
75,809
-18.80
N
56,720
52,033
8.26
P
61,794
62,388
-0.96
Q
56,543
52,978
6.30
R
54,937
44,910
18.25
S
56,957
50,215
11.84
Total
50,735
50,487
0.49
The Structure of Earnings Survey (SES) is a 4-yearly survey which provides EU-wide harmonised structural data on gross earnings, hours paid and annual days of paid holiday leave, which are collected every four years under Council Regulation (EC) No 530/1999 concerning structural statistics on earnings and on labour costs, and Commission Regulation (EC) No 1738/2005 amending Regulation (EC) No 1916/2000 as regards the definition and transmission of information on the structure of earnings.
The SES 2018 provides detailed information on relationships between the level of hourly, monthly and annual remuneration, personal characteristics of employees (sex, age, occupation, length of service, highest educational level attained, etc.) and their employer (economic activity, size and economic control of the enterprise).
Regional data is available on NUTS1 level.
Not Applicable
Employees are all persons who have a direct employment contract with the enterprise or local unit and receive remuneration, irrespective of the type of work performed, the number of hours worked (full or part-time), and the duration of the contract (fixed or indefinite).
Average annual gross earnings also cover all 'non-standard payments', i.e. payments not occurring in each pay period, such as 13th or 14th-month payments, holiday bonuses, quarterly or annual company bonuses, and annual payments in kind.
Average monthly gross earnings in the reference month cover remuneration in cash paid before any tax deductions and social security contributions payable by wage earners and retained by the employer, and are restricted to gross earnings which are paid in each pay period during the reference month.
Average hourly gross earnings are defined as gross earnings in the reference month divided by the number of hours paid during the same period.
The number of hours paid includes all normal and overtime hours worked and remunerated by the employer during the reference month. Hours not worked but nevertheless paid are counted as 'paid hours' (e.g. for annual leave, public holidays, paid sick leave, paid vocational training, paid special leave, etc.).
The statistical unit is the enterprise and the employees working within the selected unit.
The population of employees covered in the SES are those who received remuneration for the reference month (October), as requested by the Regulation, in the enterprises and institutions belonging to the Private and Public sectors with at least 10 employees in the NACE Rev. 2 sections B to S excluding O.
Data cover the entire country and aggregate estimates are disseminated at national level and NUTS 1 level.
Not Applicable
Overall, the data is checked to identify any significant changes within the dataset. Where changes occur, the survey data is checked with alternative sources, if any. When there is no information from alternative sources, INSTAT corrects or confirms the data using emails or by calling the respondents. Measures taken by INSTAT for SES, to increase response rates or to reduce the impact of nonresponse by imputing them are as follow:
Data are collected directly from the enterprise.
The enumerator's staff is trained on how to handle difficult respondents.
Due to the lack of an address system, it is often difficult for enumerators to find enterprise. For this reason, INSTAT staff, via email addresses or phone numbers, contacts the person responsible for completing the survey and receives more information on the location as well as the date and time of the meeting.
Priority is given to larger businesses. When these enterprises refuse to respond to the interviewer, an official request, in particular, is directed for the president of enterprises and signed by INSTAT director-general; it is also done for enterprises that require only this way to give the information.
A formal request is also sent to other companies that agree to respond only if the information is formally requested.
The enterprises are invited to contact the Statistical Office in case of questions and always qualified staffs are available to answer the enterprise's calls.
In order to detect outliers and other quality problems, several aggregated checks were integrated into different data collection tools.
More complicated inconsistency problems were solved internally or by contacting the local unit on a bilateral basis.
Not Applicable
The process of data compilation is done through two procedures:
Quality of data
There are applied some rules for analyzing the quality of data:
- Mathematic control of the questionnaire · Logic control of the questionnaire’s data
- Comparison of data with administrative register
- Analyze huge deviations from average.
Treatment of non-response
Are considered as all cases of:
- Non-contact
- Full refuse
- Partial refuses (for different indicators).
The treatment of non-response is done using direct methods or their combinations such as:
- Data from the administrative register;
- Data from enterprises that have similar conditions are used.
As a source of data for SES is the survey on enterprises. The frame population for SES 2018 contains 124,186 unique enterprises from the Business register that have local unit’s information in it with the respective geographical information. The stratification criteria were the economic activity, the number of employed, and the region of the local unit.
The SES 2018 was conducted based on a two-stage sampling approach. In the first stage, a stratified random sample of local units was drawn. The sample size selected is 3,381 enterprises.
The questionnaire, the explanation, and a list of local units for which the survey needed to be filled were sent to the head offices of the selected local units. In the second stage, the local unit had to select a number of employees according to the instructions in the explanation.
With regard to the size of the enterprise, Albania chose to exclude small enterprises with fewer than ten employees. We also excluded the NACE section O in our sample. This means that the Albanian datasets only include the local units covered by the Regulation.
Distribution of sampled enterprises based on “number of employed" size classes is given as follows:
Total number of employed
Proportion
10 - 49 employed
50%
50 - 249 employed
25%
250 - 499 employed
22%
500 - 999 employed
20%
1000+ employed
13%
Not Applicable
The time lag between the delivery date and the end of the reference period is approximately 680 days (T+680). Publication takes place strictly in accordance with published release dates for Labour Market Statistics in the INSTAT webpage.
The SES 2018 complies with the standard set up on the Council Regulation (EC) No 530/1999 concerning structural statistics on earnings and on labour costs and with the definitions of variables adopted in the Commission Regulation 1737/2005. The sampling unit in the first stage is the enterprises, but the register information allows to localize the employee in the region in which he/she is employed.
Not applicable. SES is conducted for the first time in INSTAT.
