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For any question on data and metadata, please contact: Eurostat user support |
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1.1. Contact organisation | Instituto Nacional de Estadística de España (INE). |
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1.2. Contact organisation unit | Labour Market Statistics Directorate (INE) |
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1.5. Contact mail address | Avenida de Manoteras 50-52 28050 Madrid Spain |
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2.1. Data description | |||
The harmonised labour cost index is a Laspeyres Index of the labour cost per hour worked, linked annually and based on a fixed structure of the economic activity broken down by sections of the CNAE-09. All necessary information to elaborate the Labour Cost Index (LCI) is provided by the Quarterly Labour Cost Survey (QLCS) except for section O, Public Administration, where the QLCS should be completed with administrative information.
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2.2. Classification system | |||
Data is broken down by economic activities defined by NACE Rev. 2 sections. Labour costs indices are provided separately for the following four categories:
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2.3. Coverage - sector | |||
The activities covered are NACE Rev. 2. Sections B to S. |
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2.4. Statistical concepts and definitions | |||
The Labour cost is the total quarterly cost incurred by the employer for using the work factor. The Labour Cost comprises a large set of items that the survey includes in two main blocks: Cost of Wages and Other Costs. The total wage cost comprises all remunerations, both in cash and in kind, made to employees for the performance of their work services for others, whether it rewards effective work, whatever the method of remuneration, or the rest periods accounted for as work. Other Costs include Non-Wage Payments and obligatory Social Security Contributions; Effective hours of work are the hours actually worked, during both normal working hours and overtime hours. They are obtained as the sum of agreed hours, plus overtime and/or complementary hours, minus hours not worked, from which are excluded hours lost in the workplace, since they are considered working hours. |
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2.5. Statistical unit | |||
The unit used is the "account of contributions". It is an administrative concept that companies use to pay the social contributions of their employees and usually coincide with the local unit. |
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2.6. Statistical population | |||
The population scope is formed by all local units, irrespective of their size, whose economic activity is classified in Sections B to S of the CNAE-09. It excludes agricultural, livestock and fishing activities, domestic personnel and extraterritorial bodies. |
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2.7. Reference area | |||
The geographic area includes the whole national territory (including Canary Island, Balearic Island and Ceuta and Melilla). |
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2.8. Coverage - Time | |||
For the temporal scope, the reference period is the calendar quarter. |
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2.9. Base period | |||
The base period is the year 2016. |
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3.1. Source data | |||
The main source is the Quarterly Labour Cost Survey (QLCS). It is a sample survey. The population is formed by all employees working for an employer. The framework used for the selection is the General Register of Accounts of Social Security Contributions, held by the Ministry of Labour and Social Economy. An Account of Social Security Contribution is an administrative concept that companies use to pay the social contributions of their employees and usually coincides with the local unit. The procedure for random selection of units corresponds to stratified sampling with optimal allocation, in which the sampling units are the accounts. The stratification criterion is accomplished attending to three variables: Autonomous Community (17 regions), the economic activity (division level of NACE rev.2, from B to S) and eight size intervals. The size of the unit is the number of employees in it. The following groups are considered for the stratification: 1. 1-4 employees 2. 5-9 employees 3. 10-19 employees 4. 20-49 employees 5. 50-99 employees 6. 100-199 employees 7. 200-499 employees 8. 500 and more employees Within each stratum, the units are selected through systematic sampling with random start. The stratum eighth is exhaustively treated. All units are selected. The sample is composed of around 28.000 units that will be interviewed each quarter. The total sample is split into five groups of rotation so that in the first quarter of each year the oldest group is replaced such that one-fifth of the sample is renewed. An exception is made for the units in the exhaustive strata (units of more than 500 employees and those belonging to strata so small that their sampling size necessarily coincides with the population), that are not renovated unless they cease to exist. These units account for 28% of the sample. There is only one questionnaire format for the whole survey population. The questionnaire is revised periodically. It changes when the labour legislation makes it necessary. No changes are currently planned. The survey is carried out by postal questionnaire, web questionnaire, etc. Separate ratio estimators are used based on the number of employees in the Register of Accounts of Social Security Contributions as the auxiliary variable. The DARETRI system: DARETRI was created by Order PRE/390/2002 of 22 February 2002. Its purpose is to collect payment data on Central Government public-sector employees. The DARETRI system automatically captures the compensation data contemplated under articles 11 to 15 of chapter 1 of the State Expenditure Budget. Therefore, the bodies and units in charge of making up payrolls compile a file called F-DARETRI to provide data on the personnel within their remit. By the 5th of every month, Ministry departments and the autonomous bodies must send the F-DARETRI files compiled by the units in charge of making up the relevant payrolls to provide data on the preceding month. So there are monthly data for the employees not covered by the survey. |
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3.2. Frequency of data collection | |||
The QLCS is conducted quarterly. The reference period for the information requested in the questionnaire is a month. However, the reference for the results is the quarter. The sample is distributed among the three months of the quarter and the estimates are calculated as the monthly average of the whole quarter. There are monthly data from DARETRI System. |
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3.3. Data collection | |||
The survey is carried out by postal questionnaire, web questionnaire, etc. The main method used by respondents is the Web-based questionnaire. The enterprise receives a letter the first time that it is interviewed with the username and the password to access to the web site and then it could fill in the questionnaire directly field by field or upload the XML file. There is a minimal validation process to consider the questionnaire sent and the process ended. The following times INE sends an email to the respondent reminding the contacts and the survey to be filled. There is a free telephone number in the letter to contact with INE where the respondents could ask all their doubts and also request an excel questionnaire and email address to send it. The sample is composed of around 28.000 units that will be interviewed each quarter. The sample is distributed in three monthly sub-samples during the quarter, such that the first sub-sample is always interviewed in the first month of each quarter, the second sub-sample is interviewed in the second month of each quarter and the third sub-sample in the last month of each quarter. This way, each unit is interviewed only four times a year instead of every month reducing the burden of the informants and distributing the monthly workload of INE provincial offices . The DARETRI system: DARETRI was created by Order PRE/390/2002 of 22 February 2002. Its purpose is to collect payment data on Central Government public-sector employees. The DARETRI system automatically captures the compensation data contemplated under articles 11 to 15 of chapter 1 of the State Expenditure Budget. Therefore, the bodies and units in charge of making up payrolls compile a file called F-DARETRI to provide data on the personnel within their remit. By the 5th of every month, Ministry departments and the autonomous bodies must send the F-DARETRI files compiled by the units in charge of making up the relevant payrolls to provide data on the preceding month. The unit in charge of this system collects all the files and validates the figures. The fisrt day of the month "t+2" sends the Daretri file of month "t" to INE. |
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3.4. Data validation | |||
The process of carrying out the statistics has established controls to detect and correct errors in order to ensure the quality of it since the beginning of the process. The collection, recording and validation phases are key development stages of any statistical research. The collection of questionnaires and the recording thereof are carried out in the provincial offices of the INE . In any case, if something wrong or inconsistent is found , the provincial office responsible for the questionnaire will establish telephone contact with the informant to clarify.
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3.5. Data compilation | |||
In cases of empty units (either by incident or by non-response) imputations of questionnaires are made to increase the quality of quarterly estimates. Two methods are used:
Partial non-response is not allowed. To obtain grossing-up estimations, separate ratio estimators are used based on the number of employees in the Register of Accounts of Social Security Contributions as the auxiliary variable. Once the data are estimated, the index is calculated from the results obtained from the survey. |
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3.6. Adjustment | |||
In order to allow a full interpretation of the results, the series of indices are obtained in the following ways: a) gross Series: the original series, unadjusted. b) calendar adjusted series: the series adjusted for working days (including the Easter effect ) c) calendar and seasonally adjusted series: the series is corrected both for calendar and periodic or seasonal effects (bonuses, holidays, ...).
The seasonal adjustment of these indicators has been performed according to the standard of INE to correct for seasonal and calendar effects in short-term series. This standard is available in the methods and standards sections of the INE website. The INE standard is the result of the working group of the INE Seasonal adjustment and follows the recommendations of the European Union listed in ESS guidelines on seasonal adjustment. The method is based on regression models with the intervention of variables using TRAMO SEATS through JDemetra program. The models are fixed and revised each year before sending the first quarter. The parameters are adjusted each quarter. The method used to obtain the adjusted series for the aggregates is the indirect approach. |
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4.1. Quality assurance | |||
Quality assurance framework for the INE statistics is based on the ESSCoP, the European Statistics Code of Practice made by EUROSTAT. The ESSCoP is made up of 15 principles, gathered in three areas: Institutional Environment, Processes and Products. Each principle is associated with some indicators which make possible to measure it. In order to evaluate quality, EUROSTAT provides different tools: the indicators mentioned above, self-assessment based on the DESAP model, peer review, user satisfaction surveys and other proceedings for evaluation. |
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4.2. Quality management - assessment | |||
The Quarterly Labour Cost Survey is a high quality product. The sample size offers labour cost indicators within a reasonable sampling errors. The harmonized methodology used allows international comparisons with a high level of solvency and provides an invaluable measure of the evolution of labour costs. As for the limitations of the survey. it should be pointed out those inherent to the sampling statistical operations such as non-response rates and the aforementioned sampling errors or variation coefficients of the estimates. In both cases are kept within reasonable limits. Detailed information on sampling errors is provided periodically in the tables of results published in INEBASE. |
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5.1. Relevance - User Needs | |||
The main users could be classified in the following groups:
Each of these users have different needs depending on the destination and usefulness of the information they require. Specifically, changes in labor costs per hour worked is an important indicator for analyzing the short and medium term economic developments. The Commission and the European Central Bank use the Labour Costs Index, which shows the short-term evolution of labour costs, to assess the potential inflationary pressures due to the evolution of costs in the labour market . |
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5.2. Relevance - User Satisfaction | |||
The INE has carried out general user satisfaction surveys in 2007, 2010, 2013, 2016 and 2019 and it plans to continue doing so every three years. The purpose of these surveys is to find out what users think about the quality of the information of the INE statistics and the extent to which their needs of information are covered. Additional surveys are carried out in order to better acknowledge other fields such as dissemination of the information, quality of some publications... The user satisfaction survey, which can be consulted on the INE website (see Methods and Projects / Quality and Code of Practice / INE quality management / User surveys are available surveys conducted to date or click next link), includes the evaluation of "labor market" group in which this statistical operation is framed. The survey provide indications of user opinions about this statistical operation. Users seem to be generally satisfied. Nevertheless, they consider that the survey should have a bigger sample size so as to offer more detailed breakdown of some variables (in particular regions, branch of activity and cost components). The most important users such as the Commission and the European Central Bank, generally indicate satisfaction, although they would appreciate shorter timeframes in the publication of information. |
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5.3. Completeness | |||
The QLCS meets all requirements established by national and international regulations related to labour costs statistics aimed at local units or enterprises. As the main source of information to produce the Labour Cost Index (LCI), is subject to the regulation of this statistical operation (Reg. 450/2003). The DARETRI system: DARETRI was created by Order PRE/390/2002 of 22 February 2002. Its purpose is to collect payment data on Central Government public-sector employees. The DARETRI system automatically captures the compensation data contemplated under articles 11 to 15 of chapter 1 of the State Expenditure Budget. Therefore, the bodies and units in charge of making up payrolls compile a file called F-DARETRI to provide data on the personnel within their remit. By the 5th of every month, Ministry departments and the autonomous bodies must send the F-DARETRI files compiled by the units in charge of making up the relevant payrolls to provide data on the preceeding month. So, monthly data for the employees not covered by the QLCS are available through DARETRI. |
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5.3.1. Data completeness - rate | |||
100% |
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The statistical accuracy and reliability is determined by the accuracy and reliability of the sources of information used in preparing the LCI: the Quarterly Labour Cost Survey (QLCS) and DARETRI file. |
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6.1. Accuracy - overall | |||
The design of the sample attempts to minimize sampling errors and the various processes of the survey are intended to eliminate or reduce as far as possible the errors both in the collection phase (response rate and debugging control) and in subsequent stages of editing and imputation. The administrative source used to obtain data on public employees under the State Employee Pension Scheme includes full information about these employees. |
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6.2. Sampling error | |||
The calculation of the coefficients of variation of key variables is performed in each survey implementation and disseminated in the publication of their results and in the successive quality reports. |
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6.2.1. Sampling error - indicators | |||
A link with the Quarterly Labour Cost Survey sampling errors estimations is included in the annex. Annexes: Sampling errors |
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6.3. Non-sampling error | |||
A control of non-sampling errors is performed in every statistical process. It also has specific information on the non-response rate. |
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6.3.1. Coverage error | |||
The study population consists on all employees who work for an employer during the reference month of the survey. The framework used for the sample selection is the General Register of Accounts of Social Security Contributions, held by the Ministry of Labour and Social Economy. When the Register is received from the Social Security, a first debugging is made prior to the selection of the sample. This implies several stages: - To eliminate economic activities regarding agricultural, livestock, fishery, households with domestic employees and extra-territorial organisms since these are not part of the survey. - To eliminate the units that belong to the special regime of Social Security sales agents, whose main compensation consists in commissions on sales and who, consequently cannot be surveyed either. After this, the sample is selected and the questionnaires are sent to the selected units. In the processes of data collection and debugging some errors in the surveyed units can be revealed. Several tables are included as an annex: 1. A table showing the percentage of the employees represented in the sample(s)/register(s) relative to the number of employees according to ESA. The source used to obtain the employees according to ESA is the Quarterly National Accounts. Data are annual averages of the four quarters of 2022 of the number of employees by groups of sections of NACE rev.2. The breakdown could be showed in table 1 of the annex. Taking into account the following observations:
The coverage of the employees represented by the sample based on the number of employees according to ESA for year 2022 is about 32,4% (The breakdown could be showed in the table 2 in the annex). 2. An additional table compares the number of local units and the number of employees in the reference population and in the QLCS sample in 2022. The population is obtained from the General Register of Accounts of Social Security Contributions, taking into account the units classified under the industries covered by the survey (sections B-S). The table provides:
Annexes: Coverage |
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6.3.1.1. Over-coverage - rate | |||
Data collection for 2022 showed that 1.6% in average of the units were inactive or closed . Only 0.3% were erroneously included units. All these units are replaced by others that belong to the same stratum in the next quarter survey. A 1.0% showed no activity during the month surveyed but remained in the sample since they can be units with seasonal activities. |
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6.3.1.2. Common units - proportion | |||
The sample is composed of around 28.000 units that will be interviewed each quarter. The total sample is split into five groups of rotation so that in the first quarter of each year the oldest group is replaced such that one-fifth of the sample is replaced. An exception is made for the units in the exhaustive strata (units of more than 500 employees and those belonging to strata so small that their sampling size necessarily coincides with the population), that are not renovated unless they cease to exist. These units account for 28% of the sample. |
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6.3.2. Measurement error | |||
The questionnaire has been elaborated approaching the required information to documents (payslips and social contributions bulletins) that the employer must fill in in relation to their employees. This facilitates the answer to the informants. Debugging errors: This first debugging consists of using filters that allow separating valid questionnaires from those with inconsistencies to be revised. The filters are of two kinds: those detecting type I and type II errors. Type I errors: If they are not thoroughly corrected, the questionnaire cannot be considered as valid. Type II errors: They affect norms that have to be complied with to assure the coherence of the data. The non-satisfaction of these norms does not necessarily mean that the questionnaire is not valid, but that the stated error should be explained. In cases of doubts, a telephone call is made to the respondent for him to elucidate them. There are more than 200 rules of this type that are checked in each questionnaire. |
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6.3.3. Non response error | |||
See next points |
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6.3.3.1. Unit non-response - rate | |||
The average non-response for year 2022 has been 12.0%. |
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6.3.3.2. Item non-response - rate | |||
It is not allowed by the collection procedure. All the variables are inter-related by validation criteria and a system of filters is available to assure the questionnaire’s internal consistency and to prevent the lack of essential data. The omitted data are requested again to the informant. |
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6.3.4. Processing error | |||
See next points |
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6.3.4.1. Imputation - rate | |||
There are two cases:
For example, to impute the value of total payroll for the non-response unit, the total payroll per employee in the stratum of that unit is calculated and then multiplied by the number of employees in the unit. The average imputation rate for year 2021 has been 5.5% |
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6.3.5. Model assumption error | |||
Estimation procedure for section O As stated above, the QLCS provides full information to elaborate the LCI for sections B to S, except section O that is only partly covered by the survey. Additional information is necessary to obtain the LCI for section O: 1. The figures for public employees under the Social Security General Scheme come from the QLCS as for the rest of the sections. 2. To estimate the labour cost and its components for public sector employees under the State Employee Pension Scheme the following sources are used:
3. The aggregation of both sets of data as a weighted average of 1+2 using the number of employees as a weight. |
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6.4. Seasonal adjustment | |||
In order to allow a full interpretation of the results, the series of indices are obtained in the following ways: a) gross Series: the original series, unadjusted. b) calendar adjusted series: the series adjusted for working days (including the Easter effect ) c) calendar and seasonally adjusted series: the series is corrected both for calendar and periodic or seasonal effects (bonuses, holidays, ...).
The seasonal adjustment of these indicators has been performed according to standard of INE to correct for seasonal and calendar effects in short-term series that is available in the methods and standards section of the INE website. This standard is the result of the working group of the INE Seasonal adjustment and follows the recommendations of the European Union listed in ESS guidelines on seasonal adjustment. The method is based on regression models with the intervention of variables using TRAMO SEATS program through the software JDemetra +. The models are fixed and revised each year before sending the first quarter. The parameters are adjusted each quarter. The method used to obtain the adjusted series for the aggregates is the indirect approach. Annexes: Standard for adjusting seasonal and calendar effects in short-term series Quality report on SA |
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6.5. Data revision - policy | |||
Advance notice of major changes in methodology expected to take place during a particular year is given in the annual publication " Programa Anual del Instituto Nacional de Estadística" (in Spanish), which is published in the last quarter of the previous year. The LCI provisional data for a quarter is published (and sent to EUROSTAT) 70 days after the reference period. It is revised and published as final data with the release of the provisional data of next quarter. See next points |
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6.6. Data revision - practice | |||
The introduction of one revision has been necessary because the first calculation of LCI is based on provisional data from the QLCS. The checking, validation and debugging processes have not finished and those questionnaires with "rare responses" pending the confirmation from the enterprises are imputed. 80 days after the reference period the QLCS is published and the LCI recalculated with their final data producing the revision of the LCI. This revision is sent with the provisional data of next quarter. So, there is only one revision for each quarter except during 2009 due to the implementation of NACE rev.2 (see 2009 quality report). |
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6.6.1. Data revision - average size | |||
The average size of revisions, being the revision the difference between the final and provisional estimate for 2021 for the total labour cost has been 0.1. A table showing the revisions in the published year-on-year growth rates for total labour costs using the unadjusted series, for the last 16 quarters brokendown by sections of Nace Rev.2 is included in the annex; as it can be observed from the table, the revision not always produce a new data and most of revisions are lesser than one porcentual point. Annexes: Revision history |
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7.1. Timeliness | |||
2022Q1: t+ 70 days 2022Q2: t+ 70 days 2022Q3: t+ 70 days 2022Q4: t+ 69 days |
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7.1.1. Time lag - first result | |||
t+70 days |
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7.1.2. Time lag - final result | |||
The final result for quarter "t" is published in "t"+160 days |
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7.2. Punctuality | |||
The results of the LCI are published according to Short-term Statistics Availability Calendar of INE. Annexes: Statistics availability calendar |
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7.2.1. Punctuality - delivery and publication | |||
The results of the LCI are published according to Short-term Statistics Availability Calendar of INE. |
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8.1. Comparability - geographical | |||
Regarding the international comparability of the survey, the methodology follows the concepts and definitions of Regulation (EC) No 450/2003 of the European Parliament and of the Council of 27 February 2003 concerning the labour cost index which provides statistical homogeneity with other European Union countries that broadcast this same information. |
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8.1.1. Asymmetry for mirror flow statistics - coefficient | |||
Optional |
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8.2. Comparability - over time | |||
The results broken down by sections and divisions of NACE-2 are comparable in time since 2000. |
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8.2.1. Length of comparable time series | |||
The results broken down by sections of the NACE-Rev.2. are comparable over time since 2000. For total economic activities must take into account that NACE section O- is collected since 2006 . Thus the number of elements of the comparable time series is 92. |
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8.3. Coherence - cross domain | |||
The use of a single national classification of economic activities allows the possibility to compare the information with other economic statistics on common variables such as National Accounts. Comparability over NACE sections |
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8.4. Coherence - sub annual and annual statistics | |||
Since 2001, an annual survey is conducted to obtain annual data. This survey with reference period year "t", is collected during three consecutive months of the year "t+1" jointly with the Quarterly Labour Cost Survey, adding an annual questionnaire to the quarterly ones. This way, short-term data are adjusted with the annual questionnaire to obtain annual data and the coherence between short term and structural data is assured. |
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8.5. Coherence - National Accounts | |||
The Regulation Nº 1216/2003 says that this point has to include " a graph and a table showing annual unadjusted growth rates of the total labour cost index (NACE Rev. 1 sections) and of the ESA 95 compensation of employees per hour worked (A6 breakdown) with explanations for the differences in the growth rates for the last 12 quarters;” Data available from Quarterly National Accounts (QNA) are not broken down by NACE Rev.2 sections. In order to do the comparison an approximate correspondence between the breakdown of QNA and LCI series has been set as follows:
In general, both series have a similar trend in time. The QNA seems to have sharper movements specially related to the Covid effect. The tables and graphs are included as an annex. Annexes: NA-LCI coherence |
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8.6. Coherence - internal | |||
Estimates of the labour cost variables and hours worked have complete internal consistency as they are based on the same corpus of microdata and administrative data. Moreover, they are calculated using the same methods of estimation. |
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9.1. Dissemination format - News release | |||
The LCI is published quarterly according to the Short-term Statistics Availability Calendar of the INE. An advance release calendar which gives at least one-quarter-ahead notice of the precise release dates is disseminated on INE Internet website (http://www.ine.es). The main results of the LCI, the series of Total labour cost, Wages, Other costs and Labour costs excluding bonuses, are disseminated in a special release with a brief explanation of the results each quarter. The very detailed set of series is disseminated without explanation. The data are available on INE web site and are free of charge. Annexes: LCI National press release |
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9.2. Dissemination format - Publications | |||
Users can access to QLCS and LCI data via the INE website. Specifically, the following information is available:
Annexes: INE website. Wages and labour costs |
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9.3. Dissemination format - online database | |||
INEbase is the system used to store and disseminate at INE Website all statistical information. It contains all the information produced by the INE in electronic format. It is organized basically following the thematic classification of the Inventory of Statistical Operations of the State General Administration. The basic unit is the statistical operation, defined as the set of activities that lead to the collection of statistics for a particular sector or theme, from data collected individually. Data from QLCS and LCI are in INEbase. Annexes: Online database |
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9.3.1. Data tables - consultations | |||
Optional |
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9.4. Dissemination format - microdata access | |||
Optional |
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9.5. Dissemination format - other | |||
Customized information must be requested via the User Services Area, indicating the contact person’s data (name and postal address, telephone, fax or e-mail) and detailing precisely what information you are requesting Requests will pass through a viability analysis process, programming and subsequent verification that the data obtained safeguard statistical secrecy and are representative. Annexes: Customised requests |
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9.6. Documentation on methodology | |||
The methodology of the LCI is published with the data on the INE Internet website. Annexes: LCI Methodology |
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9.7. Quality management - documentation | |||
The statistics are prepared in accordance with EU guidelines in order to meet the Code of Practice implemented by Eurostat, following the quality criteria on relevance, accuracy, timeliness and punctuality, accessibility and clarity, comparability, consistency, and completeness (along this report). |
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9.7.1. Metadata completeness - rate | |||
100% |
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9.7.2. Metadata - consultations | |||
Optional |
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The LCI is elaborated using already existing information. Its main source of information is the Quarterly Labour Cost Survey (QLCS). There are several tasks to minimize the cost and burden: To achieve a balance between sample stability and the burden for the informants, the following actions are carried out in the QLCS: - Distribution of the sample in three monthly sub-samples during the quarter: The sample is distributed in three monthly sub-samples during the quarter. The first sub-sample is interviewed every first month in each quarter, the second sub-sample is interviewed every second month in each quarter and the third every last month in each quarter. This way, each unit is interviewed only four times a year instead of every month reducing the burden of the informants and distributing the monthly workload of INE provincial offices. - Renewal or annual rotation of the sample: The total sample is divided into five groups of rotation. In the first quarter of each year the oldest group is replaced, representing an annual renewal of 20% of the sample. In this way most companies will collaborate in the survey for five years. An exception is made for the units in the exhaustive strata (units with more than 500 employees and those belonging to strata so small that their sampling size necessarily coincides with the population), that are not renovated unless they cease to exist. These units represent 28% of the sample. - To facilitate the responses, the questionnaire approximates official information that any employer must fill in in relation to their employees and that is requiered by other official bodies (payslips, social contributions bulletins...). That is particularly so for the last section of the questionnaire. The estimated budgetary appropriation needed to finance this statistic, as provided for in the 2022 Annual Programme, is €47.58 thousand.
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11.1. Confidentiality - policy | |||
The Law 12/1989 of the Public Statistic Function, states that INE can not disseminate, or make available in any way, individual or aggregate data that could lead to the identification of any individual person or entity. Moreover, the European Regulation 223/2009 on European statistics sets the need to establish common principles and guidelines ensuring the confidentiality of the data used to produce European statistics and the access to those confidential data taking into account the technical developments and the needs of users in a democratic society. |
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11.2. Confidentiality - data treatment | |||
The INE takes the necessary logical, physical and administrative provisions for the protection of confidential data from data collection to publication. Confidential data are not published. They are aggregated with other confidential or non-confidential cells to produce a non-confidential data aggregate. For example section B at division level is confidential so only section level is published. |
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More information on INE web site: More information about LCI |
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