- Methods and Projects
- Standards and Classifications
Standardised Methodological Report
Monthly Estimates of Births
- 1Contact
- 1.1Contact organisation
National Statistics Institute of Spain
- 1.5Contact mail address
Avenida de Manoteras 50-52 - 28050 Madrid
- 1.1Contact organisation
- 2Metadata update
- 2.1Metadata last certified
19/02/2025
- 2.2Metadata last posted
22/01/2025
- 2.3Metadata last update
19/02/2025
- 2.1Metadata last certified
- 3Statistical presentation
- 3.1Data description
The EMN offers rapid estimates on the number of births occuring each month using the entries registered in the computerized Civil Registries.
These statistics offer information that is disaggregated by autonomous community and province.
- 3.2Classification system
- Clasificaciones utilizadas
Comunidades Autonomas:
01 Andalucia
02 Aragon
03 Asturias, Principado de
04 Balears, Illes
05 Canarias
06 Cantabria
07 Castilla y Leon
08 Castilla - La Mancha
09 Cataluña
10 Comunitat Valenciana
11 Extremadura
12 Galicia
13 Madrid, Comunidad de
14 Murcia, Region de
15 Navarra, Comunidad Foral de
16 Pais Vasco
17 Rioja, La
18 Ceuta
19 Melilla
No residente
Provincias:
02 Albacete
03 Alicante/Alacant
04 Almeria
01 Araba/Álava
33 Asturias
05 Ávila
06 Badajoz
07 Balears, Illes
08 Barcelona
48 Bizkaia
09 Burgos
10 Caceres
11 Cadiz
39 Cantabria
12 Castellon/Castello
13 Ciudad Real
14 Cordoba
15 Coruña, A
16 Cuenca
20 Gipuzkoa
17 Girona
18 Granada
19 Guadalajara
21 Huelva
22 Huesca
23 Jaen
24 Leon
25 Lleida
27 Lugo
28 Madrid
29 Malaga
30 Murcia
31 Navarra
32 Ourense
34 Palencia
35 Palmas, Las
36 Pontevedra
26 Rioja, La
37 Salamanca
38 Santa Cruz de Tenerife
40 Segovia
41 Sevilla
42 Soria
43 Tarragona
44 Teruel
45 Toledo
46 Valencia/València
47 Valladolid
49 Zamora
50 Zaragoza
51 Ceuta
52 Melilla
No residente
- Clasificaciones utilizadas
- 3.3Sector coverage
It collects births occuring in Spain, regardless of whether the population is resident or non-resident
- 3.4Statistical concepts and definitions
- Age
Age in years refers to the number of birthdays reached by the reference date, in other words, the age last birthday.
- Newborn
A foetus will only be classified as born if it has a human-like appearance and lives for twenty-four hours completely outside the mother's womb
- Age
- 3.5Statistical unit
The basic statistical unit is birth.
- 3.6Statistical population
The population under study are births in Spain.
- 3.7Reference area
The statistics cover the whole of the national territory. Disaggregated data at the Autonomous Community and province level is published.
- 3.8Time coverage
Monthly Statistics of Births disseminate data from January 2013, although it has been ruled and included in the Inventory of statistical operations in 2022. However, there are birth results published in the Birth Statistics included in Natural Movement of the Population since 1900 on an annual basis.
- 3.9Base period
Year 1975
- 3.1Data description
- 4Unit of measure
- 4.1Unit of measure
The data is published:
- In absolute numbers (number of births).
- Accumulated thus far this year.
- Absolute and percentage interannual variation of the accumulate.
- 4.1Unit of measure
- 5Reference period
- 5.1Reference period
Data referring to the period: Monthly Y: 2024 MONTH: 01
- 5.1Reference period
- 6Institutional mandate
- 6.1Legal acts and other agreements
The compilation and dissemination of the data are governed by the Statistical Law No. 12/1989 "Public Statistical Function" of May 9, 1989, and Law No. 4/1990 of June 29 on “National Budget of State for the year 1990" amended by Law No. 13/1996 "Fiscal, administrative and social measures" of December 30, 1996, makes compulsory all statistics included in the National Statistics Plan. The National Statistical Plan 2009-2012 was approved by the Royal Decree 1663/2008. It contains the statistics that must be developed in the four year period by the State General Administration's services or any other entity dependent on it. All statistics included in the National Statistics Plan are statistics for state purposes and are obligatory. The National Statistics Plan 2025-2028, approved by Royal Decree 1525/2024, of 3 December, is the Plan currently implemented. This statistical operation has governmental purposes, and it is included in the National Statistics Plan 2021-2024. (Statistics of the State Administration).
- 6.2Data sharing
The exchanges of information needed to elaborate statistics between the INE and the rest of the State statistical offices (Ministerial Departments, independent bodies and administrative bodies depending on the State General Administration), or between these offices and the Autonomic statistical offices, are regulated in the LFEP (Law of the Public Statistic Function). This law also regulates the mechanisms of statistical coordination, and concludes cooperation agreements between the different offices when necessary.
There are no planned exchanges of information with other statistics producing organizations.
- 6.1Legal acts and other agreements
- 7Confidentiality
- 7.1Confidentiality - policy
The Statistical Law No. 12/1989 specifies that the INE cannot publish, or make otherwise available, individual data or statistics that would enable the identification of data for any individual person or entity. Regulation (EC) No 223/2009 on European statistics stipulates the need to establish common principles and guidelines ensuring the confidentiality of data used for the production of European statistics and the access to those confidential data with due account for technical developments and the requirements of users in a democratic society
- 7.2Confidentiality - data treatment
INE provides information on the protection of confidentiality at all stages of the statistical process: INE questionnaires for the operations in the national statistical plan include a legal clause protecting data under statistical confidentiality. Notices prior to data collection announcing a statistical operation notify respondents that data are subject to statistical confidentiality at all stages. For data processing, INE employees have available the INE data protection handbook, which specifies the steps that should be taken at each stage of processing to ensure reporting units' individual data are protected. The microdata files provided to users are anonymised.
- 7.1Confidentiality - policy
- 8Release policy
- 8.1Release calendar
The advance release calendar that shows the precise release dates for the coming year is disseminated in the last quarter of each year.
- 8.2Release calendar access
The calendar is disseminated on the INEs Internet website (Publications Calendar)
- 8.3User access
The data are released simultaneously according to the advance release calendar to all interested parties by issuing the press release. At the same time, the data are posted on the INE's Internet website (www.ine.es/en) almost immediately after the press release is issued. Also some predefined tailor-made requests are sent to registered users. Some users could receive partial information under embargo as it is publicly described in the European Statistics Code of Practice
- 8.1Release calendar
- 9Frequency of dissemination
- 9.1Frequency of dissemination
The frequency of dissemination is monthly.
- 9.1Frequency of dissemination
- 10Accessibility and clarity
- 10.1News release
The results of the statistical operations are normally disseminated by using press releases that can be accessed via both the corresponding menu and the Press Releases Section in the web
- 10.2Publications
The results of these statistics are disseminated through the INE website, and certain results are collected in publications such as INE Figures, etc.
- 10.3On-line database
INEbase is the system the INE uses to store statistical information on the Internet. It contains all the information the INE produces in electronic formats. The primary organisation of the information follows the theme-based classification of the Inventory of Statistical Operations of the State General Administration . The basic unit of INEbase is the statistical operation, defined as the set of activities that lead to obtaining statistical results on a determined sector or subject based on the individually collected data. Also included in the scope of this definition are synthesis preparation.
No. of queries to data tables AC1=314,173
No. of queries to metadata AC2=378 - 10.4Micro-data access
A lot of statistical operations disseminate public domain anonymized files, available free of charge for downloading in the INE website Microdata Section
You can access the anonymized microdata of the Birth Statistics up to the last year published. Microdata for estimated data are not available.
- 10.5Other
Through the INE User Service Area, interested users can request specific exploitation of information, while preserving the confidentiality of the data and signing the corresponding agreement or document.
Watch:
- 10.6Documentation on methodology
The methodology document can be accessed at the following link:
https://www.ine.es/en/metodologia/t20/meto_emn_en.pdf
AC3=100
- 10.7Quality documentation
Sections 10.6 to 17 of this document are considered the user-oriented quality report for this operation.
- 10.1News release
- 11Quality management
- 11.1Quality 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 16 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.
In order to manage the quality of these statistics, exhaustive controls are carried out during all process phases. Special emphasis is placed on controlling coverage, assuring that the values of the variables are valid and making sure that there are no inconsistencies in the information received.
The information is of high quality since it comes from the data recorded by the Civil Registries through the Ministry of Justice’s INFOREG and DICIREG applications. These applications have been implemented over the last few years in the national territory, reaching a high degree of implementation (by early 2024, only about 4% of births are not recorded and have to be estimated, a figure that will reach 0% with the full implementation of DICIREG in September 2025) and stability.
A strong point of these statistics is the great speed in providing reliable information on the number of births.
- 11.2Quality assessment
Not applicable.
- 11.1Quality assurance
- 12Relevance
- 12.1User needs
Users of this statistic include:
- Researchers and Universities.
- territorial administrations
- Enterprises
- individuals
Each of these users has different needs depending on the destination and usefulness of the information they require. In particular:
- Researchers and Universities require detailed data on births, disaggregated by variables (sex, mother's age) to conduct fertility studies, identify sociodemographic patterns, and develop research on maternal and child health and birth policies.
- Territorial administrations need monthly estimates of births by region and mother's characteristics in order to plan birth support policies, allocate resources for health and education services, and evaluate the impact of related public policies.
- Businesses require birth estimates to analyze demographic trends that may influence their business strategies, such as the design of products and services for children, and to evaluate opportunities in specific markets based on birth trends.
- Individuals seek general information on births in their community or province to better understand local demographic trends and assess their impact on services such as childcare, schools or family infrastructure.
Despite the progress in this statistical operation, some unmet needs are identified:
- Inequality in the coverage of birth registries: the computerization of civil registries is not homogeneous at the national level, which generates discrepancies in the quality and timeliness of the data.
- Lack of greater disaggregation of data, which would allow for the analysis of more complex or specific sociodemographic patterns.
- Delays in receiving data from civil registries, which affects the immediacy with which results can be provided, which in turn limits their usefulness for certain users.
However, these needs are being progressively addressed with the rapid implementation of the DICIREG computerized system at the national level, which is scheduled for completion by September 2025. In addition, work is underway to expand the number of variables available and to provide a greater level of disaggregation of data, which will allow users to access more detailed and timely information.
- 12.2User 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. In addition, additional surveys are carried out in order to acknowledge better other fields such as dissemination of the information, quality of some publications...
On the INE website, in its section Methods and Projects / Quality and Code of Practice / INE quality management / User surveys are available surveys conducted to date.(Click next link)
Not applicable.
- 12.3Completeness
The information collected allows us to attend to all requests received.
The data completeness rate is 100%.
R1=100%.
The monthly birth estimation prepared by the INE complies with several regulations and standards that guide the collection, processing, and dissemination of statistical data. These include:
- Regulation (EC) No. 223/2009 of the European Parliament and of the Council on European statistics:
- This regulation establishes the framework for the production and dissemination of European statistics, including those related to population and birth data. The INE follows these guidelines to ensure the quality and comparability of the data at the European level.
- Regulation (EU) No. 1260/2013 of the European Parliament and of the Council on population statistics:
- This regulation governs the collection and transmission of data on births and other demographic aspects. The INE adapts its methods and practices to comply with this regulation to ensure the consistency of the information provided in line with European standards.
- Law 12/1989, of May 9, on the Public Statistical Function:
- This law establishes the legal framework for public statistical activities in Spain, setting the principles of objectivity, professionalism, confidentiality, and rigor in data collection and dissemination. The INE’s birth estimation complies with the requirements of this law to guarantee the quality and reliability of the statistics.
- Resolution of the Government Delegated Commission for Economic Affairs:
- Approved on October 24, 2007, this resolution provides specific guidelines for the preparation and publication of demographic statistics in Spain. The INE follows these regulations when performing the monthly birth estimation.
- EUROSTAT International Guidelines:
- The guidelines and standards established by EUROSTAT, the European Union’s statistical office, are followed by the INE to ensure that birth estimations conform to international statistical practices. This includes adherence to the European System of National and Regional Accounts (ESA).
- Good Practices Guide for Statistical Production:
- The INE is also guided by good practices recommended by institutions such as the EU Statistical Office and the United Nations. This involves a meticulous approach to ensure the accuracy, quality, and transparency of the birth estimation process.
By complying with these regulations, guidelines, and directives, the INE ensures that the monthly birth estimation is consistent, accurate, and of high quality, making it suitable for both national and international use.
- Regulation (EC) No. 223/2009 of the European Parliament and of the Council on European statistics:
- 12.1User needs
- 13Accuracy and reliability
- 13.1Overall accuracy
The quality of data recording in Civil Registries, error correction, data validation, imputation of the lack of information or adjustments for delays in information reception allow for a high degree of reliability of the statistics.
The main sources of errors can be both random and systematic, and their impact may vary depending on the nature and occurrence of the error. Below are the main sources of error and their potential impact on the key statistical results:
Random Errors:
-
Errors in birth reporting:
- Source: Birth information is provided by hospitals, clinics, and other healthcare facilities, and sometimes there may be delays or errors in transmitting the data.
- Impact: Random errors in reporting may cause small fluctuations in the monthly estimates, affecting the accuracy of the results in the short term. However, these errors are typically compensated over time by other correct records.
-
Coding errors in the database:
- Source: Incorrect assignment of codes or erroneous information in the birth registration process may occur due to human error or system automation failures.
- Impact: These errors may introduce minor inaccuracies in the data, but they tend to be less significant if identified and corrected quickly.
-
Estimation of births in rural or hard-to-reach areas:
- Source: In some rural or less accessible areas, birth data may arrive late or incomplete, affecting how quickly information is updated.
- Impact: Random errors due to missing information from these areas can cause slight discrepancies in the monthly estimates, although these errors are usually small.
Systematic Errors:
-
Underreporting of births in areas with administrative challenges:
- Source: In certain regions with administrative or logistical issues, some births may not be properly registered.
- Impact: This type of systematic error may result in underestimates in the statistical results, as some births are not reflected in the estimates, affecting the reliability of the monthly estimation results.
-
Systematic delays in data transmission:
- Source: Occasionally, birth data is not reported on time due to administrative issues or delays in data transmission systems.
- Impact: Delays in transmission may affect the temporal accuracy of the monthly estimates, causing discrepancies or biases in the results, particularly if the most recent births are not included in the calculation of the estimates.
-
Errors in imputing missing data:
- Source: In cases where birth data is missing (e.g., birthplace or sex), imputation methods may be used to complete the data.
- Impact: If imputation is not done correctly or if inappropriate methods are used, this may introduce systematic bias in the results, affecting the accuracy of the estimates.
-
Errors in birth categorization:
- Source: Births may be incorrectly registered under specific categories, such as nationality, type of birth, or mother's age, due to inaccurate interpretation of classification criteria.
- Impact: This type of error may distort the monthly estimation results, particularly when analyzing subgroups of the population, such as births by origin or mother’s characteristics.
Impact on Key Results:
-
Accuracy of monthly estimates: Random errors typically affect the monthly birth estimates in a less significant way, causing minor variations in the results that tend to balance out over time. However, systematic errors can have a more lasting impact and affect the reliability of the estimates continuously, making it more difficult to obtain accurate birth figures for certain periods.
-
Comparability with other statistics: Systematic errors may cause the monthly estimates to be less comparable with data from previous years or with other statistical systems, especially if there are issues with birth registration or data transmission.
-
Reliability for decision-making: If systematic errors are not addressed properly, this can affect users’ confidence in the statistics, especially in cases where the data is used for public policy planning, health, and education.
In summary, while random errors in birth estimation tend to have a smaller impact and are compensated over time, systematic errors can lead to significant biases that affect the quality and accuracy of birth statistics. It is essential to identify and correct these errors to ensure the reliability of the results.
-
- 13.2Sampling error
Since it is a statistic based on administrative records, there are no sampling errors.
- 13.3Non-sampling error
Births registered in the Civil Registries and recorded in the Ministry of Justice's INFOREG or DICIREG applications represent approximately 97% of births in Spain. This, together with corrections of delays in birth registrations, is corrected thanks to the implementation of two expansion coefficients.
A4=2.93%.
The non-sampling errors affecting the statistical operation include the following key aspects:
1. Overcoverage and Undercoverage:
- Overcoverage: This refers to including birth records that do not belong to the target population (e.g., incorrectly registered or duplicate births).
- Undercoverage: Occurs when legitimate births are not properly recorded, especially in rural areas or regions with administrative difficulties, leading to underestimation.
2. Measurement Errors:
- Measurement errors can occur when data collected about births (e.g., gender, date, place of birth) is incorrect due to human errors or lack of clarity in registration procedures.
3. Non-response:
- Non-response refers to the absence of data from some birth records, which can happen due to delays in reporting or issues in data transmission systems.
- Causes: This can be due to administrative challenges, failures in healthcare infrastructure, or misinformation in rural areas.
4. Processing Errors:
- These occur during the compilation and validation process of data. They may include errors in coding, database handling issues, or problems with record updates, which affect the quality and accuracy of the information.
5. Modeling Errors:
- Refers to inaccuracies when using statistical methods to estimate missing data or extrapolate information. This can introduce bias if the models used do not adequately reflect the reality.
- 13.1Overall accuracy
- 14Timeliness and punctuality
- 14.1Timeliness
Monthly, in month m, data for month m-2 are published.
As provisional and definitive data on birth statistics (Natural Population Movement) based on Birth Statistics Bulletin documents become available, estimates will be replaced by definitive data. Thus, data on births that occurred in 2023 are considered definitive from November 2024.
TP1: 45 days
TP2: 11 months
- 14.2Punctuality
Data dissemination is carried out in accordance with the statistics availability calendar prepared and published each year by the INE.
TP3=0 (there are no publication delays)
- 14.1Timeliness
- 15Coherence and Comparability
- 15.1Comparability - geographical
Under-registration coefficients are calculated and applied according to the province of registration.
Until May 2024, the estimated data were published according to province of registration. However, as of this date, the estimated data are published according to province of residence in order to improve the comparability of the provisional data with the definitive data from previous years.
On occasions, the residence of the pregnant mother is not always well informed in INFOREG/DICIREG, so in these cases, the province of residence has been imputed according to the place where the registration was made.
- 15.2Comparability - over time
The statistics are comparable throughout the period. There has been no methodological break
CC2 = 93 months
- 15.3Coherence - cross domain
This statistic is consistent with the Birth Statistics.
- 15.4Coherence - internal
The coherence between the variables is contrasted in all phases of the statistical process.
- 15.1Comparability - geographical
- 16Cost and burden
- 16.1Cost and burden
As a statistic based on an administrative record, there is no additional burden to the informants.
The estimate of the budget credit necessary to finance the Monthly Birth Statistics provided for in the 2025 Annual Program is 45.63 thousand euros.
To increase production efficiency, the complete computerization of civil registries, the improvement of interoperability between the different databases and the improvement of predictive statistical models will be of great help.
- 16.1Cost and burden
- 17Data revision
- 17.1Data revision - policy
The INE of Spain has a policy which regulates the basic aspects of statistical data revision, seeking to ensure process transparency and product quality. This policy is laid out in the document approved by the INE board of directors on 13 March of 2015, which is available on the INE website, in the section "Methods and projects/Quality and Code of Practice/INE’s Quality management/INE’s Revision policy" (link).
This general policy sets the criteria that the different type of revisions should follow: routine revision- it is the case of statistics whose production process includes regular revisions-; more extensive revision- when methodological or basic reference source changes take place-; and exceptional revision- for instance, when an error appears in a published statistic-.
The revision policy for the Monthly Birth Estimation statistical operation focuses on ensuring the quality and reliability of the provided data, guaranteeing its accuracy throughout the data collection, estimation, and updating process. The main aspects of this revision policy are:
1. Review of Provisional and Final Data:
- Provisional Data: Initially, the published birth data are provisional estimates based on preliminary records. These data are updated monthly as new information becomes available, and more complete data is obtained.
- Final Data: Final data, which come from the civil registries after verification, replace previous estimates. The revision process ensures that final data are used to replace provisional estimates once they are available.
2. Data Validation and Verification:
- All received data, whether from civil registries or other sources, undergo a rigorous validation and verification process. This includes detecting possible inconsistencies, coding errors, missing data, or duplicate records.
- Cross-checking with External Sources: Birth data are compared with other databases, such as hospital reports and other health sources, to detect any errors or discrepancies.
3. Review of Statistical Estimates:
- Since some data are estimated, statistical models are used to project births in areas or periods where final data are not yet available. These models are reviewed periodically to ensure that projections are representative and reflect current demographic trends.
- When estimates do not align with final data, the model parameters and estimation techniques are reviewed and adjusted to improve accuracy.
4. Quality Control:
- Internal reviews are conducted to verify the quality of the process. This includes audits of data collection procedures, methodologies used in estimates, and data processing.
- Detected Errors: If errors are identified during the review, they are promptly corrected, and if necessary, an official correction is issued and published for transparency.
5. Continuous Procedure Updates:
- As new technologies and information systems (such as the digitization of civil registries) are implemented, the revision policy also includes updates to procedures to integrate technological improvements that make data collection and processing more efficient and accurate.
6. Periodic Review of the Estimation Process:
- The policy includes the periodic review of the entire estimation process. This review considers the results of each monthly estimate, the performance of statistical models, and data quality. Feedback from users and related institutions is also taken into account to make adjustments to the data collection process and estimates.
7. Transparency and Publication of Results:
- After the data review, the final results are published in a transparent and accessible manner. If errors are found later, a public correction is made with a clear explanation of the adjustment made.
8. Interinstitutional Collaboration:
- Agreements with other public and private institutions (such as civil registries, hospitals, and health services) are reviewed to ensure proper data transmission and use. This includes optimizing data flows and integrating new sources that could contribute to improving birth estimates.
This revision policy aims to ensure that the Monthly Birth Estimation is as accurate, complete, and up-to-date as possible, providing high-quality data for use in demographic analysis and other statistical reports.
- 17.2Data revision - practice
Two types of data coexist in the project:
- Definitive data (births from 2016 to 2023).
- Estimated data (births from January 2024 to the last published month).
Estimated data are reviewed and updated in each monthly publication.
A6-RMAR=0.22%
Calculated based on the total of the last 12 months
- 17.1Data revision - policy
- 18Statistical processing
- 18.1Source data
The original source of the data is the registration of births in the civil registries. For several years, the Ministry of Justice has launched an application known as Inforeg, for recording the different registry entries, including births. This application has been implemented in the Civil Registries although not all use it (around 4% of births registered in Spain are not recorded in Inforeg).
From October 2021, Inforeg begins to be gradually replaced by a new application, DICIREG, which should ideally be implemented throughout Spain within approximately three years.
- 18.2Frequency of data collection
The INE receives a monthly file, on the first working day of each month, which includes all births recorded up to the previous day.
- 18.3Data collection
To carry out these statistics, information is obtained from:
- The definitive files of the Birth Statistics (from the year 2013 to the year 2023)
- The monthly files received on the first day of each month from the Ministry of Justice with the births registered in the Civil Registries in the month prior to the reception of the file (from January 2024 to the last month published).
- 18.4Data validation
Multiple analyses of data evolution coherence are carried out
- 18.5Data compilation
Firstly, the INE verifies the reception, reading and processing of the files received from the Ministry of Justice. The data is then purified and validated. The expansion coefficients are then applied. Births recorded in Inforeg for each week in each geographic area are calculated by applying two expansion coefficients. The first coefficient is for undercoverage correction of the original Inforeg and Dicireg data. It is an expansion factor that historically relates births recorded and occuring in each geographical area. The second factor corrects for the delay in data recording. This coefficient is used for the most recent three months published. They are updated and corrected with each new publication of results.
The last stage before information dissemination is aimed at analyzing the aggregate information and verifying the consistency of the information offered.
Quality Indicator 'Imputation rate' A7=0%.
- 18.6Adjustment
No seasonal adjustments are applied.
- 18.1Source data
- 19Comment
- 19.1Comment
- 19.1Comment