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Methodology

CSO statistical release, , 11am
Frontier Series Output

CSO Frontier Series outputs may use new methods which are under development and/or data sources which may be incomplete, for example new administrative data sources. Particular care must be taken when interpreting the statistics in this release.
Learn more about CSO Frontier Series outputs.

Introduction

This section provides an overview of the methodological approach taken when producing the population estimates under the Administrative Population concept. The Administrative Population concept has been defined by the CSO as follows:

“The concept of Administrative Population uses a Signs of Life statistical method to estimate those persons resident in the State for most of the time in the 12 months prior to April of the reference year. The method is based on CSO-pseudonymised versions of administrative data collected by Government Departments, agencies, and public bodies other than the CSO. This data can be indicative of the actual presence and usual residence of a person in the State.”

The results presented in this release are based on linking administrative datasets from a range of public service bodies, which are listed in the Background Notes. A series of rules is then applied to decide who should be included in or excluded from the Administrative Population. This provides an estimate of the number of people usually resident in Ireland in April of the reference year.

IPEADS 2023 is the fourth iteration. Over each iteration, the methodology has continued to evolve; however, there have been very limited changes between the 2022 and 2023 iterations.

The rationale for the Signs of Life approach is that almost every person who usually lives in Ireland has some level of interaction with the State, either directly or indirectly. This can be through a spouse or dependant, due to taxation, receipt of a benefit, pension payments, or enrolment in education. Administrative data records from government bodies allow the CSO to identify all persons who interacted with the State up to and including April 2023. These interactions provide the basis for determining the Administrative Population used in IPEADS 2023.

The following sections explain how administrative data is grouped, how people are linked across systems, and how the concept of usual residence is applied in practice. The sections are divided into four phases:

  • Phase I – How People are Counted
  • Phase II – Geocoding and Statistical Geography Assignment
  • Phase III – Family Estimates Methodology
  • Phase IV – Household Estimates Methodology

How People are Counted

The aim of this method for estimating the Administrative Population is to count people who meet the international definition of usual residence, based on their activity in administrative data around April 2023.
Administrative data is grouped according to the type of population it covers. For this project, the CSO organises the data into three main groups:

  1. Children
  2. Students
  3. Adults

The complete list of administrative datasets used in this release can be found in the Background Notes.
Each person is identified using a pseudonymised version of their Personal Public Service Number (see the Background Notes for more detail). This allows their records to be linked across different datasets while protecting their privacy. The result is a single record for each person who interacted with the State during a 12-month period up to and including the reference month (April 2023).
These consolidated records also contain attribute data, which includes key analysis variables such as date of birth, sex, and nationality. This attribute data is used to summarise the characteristics of the Administrative Population, as well as to create statistics on family and households in the Administrative Population.
Once the data is linked, each individual is assessed to see if their activity meets the conditions for usual residence.

Usual Residence

Usual residence is a widely used concept in demographic statistics and is defined in Article 2 of the Regulation (EU) 1260/2013 of the European Parliament and of the Council. A person’s usual residence is defined as follows:
The place where a person normally spends their daily period of rest, regardless of temporary absences for purposes of recreation, holidays, visits to friends and relatives, business, medical treatment, or religious pilgrimage.

The following qualifications apply to usual residence.
Only the following persons shall be considered to be usual residents of a specific geographical area in question:
i. those who have lived in their place of usual residence for a continuous period of at least 12 months before the reference time (date); or
ii. those who arrived in their place of usual residence during the 12 months before the reference date with the intention of staying there for at least one year.

Where the circumstances described in point (i) or (ii) cannot be established, "usual residence" shall mean the place of legal or registered residence.

In surveys and censuses, the concept of usual residence can be established through direct questions. This is not possible using administrative data. For determining the usually resident Administrative Population in IPEADS 2023, the usual residence is established through patterns of interaction with public sector bodies, the Signs of Life approach. In short, persons who display continuous interaction (or “Signs of Life”) with the State, as recorded in administrative data, for 12 months around a reference period are deemed to be usually resident and part of the Administrative Population. The rules used to determine usual residence in this publication are outlined in the section below.

Using Administrative Data to Identify Usual Residence

Whether a person is included in the Administrative Population depends on how often they appear in the data and which sources they appear in.

There are two main types of administrative datasets:

Annual Datasets

Annual datasets contain a single record for each person during the year. These include, for example, tax returns or education enrolments. In general, anyone who appears in an annual dataset is counted as usually resident, unless:

  • The dataset shows that the person has left the country, or
  • There is another clear indicator that they were not living in Ireland at the time.

Examples of annual datasets include:

  • Enrolments in primary, post-primary, and higher education
  • Income tax data for the self-employed
  • Medical card eligibility (GMS scheme)

More detail about each dataset is available in the Background Notes.

Monthly Datasets

Monthly datasets are more detailed and allow for closer analysis. They are essential for identifying patterns of activity over time. In this release, the monthly datasets used were employment data and social benefit records.

To meet the definition of usual residence, it is necessary to examine people’s activity both before and after the reference month. For this release, the CSO looked at monthly data from January 2022 to December 2023.
This two-year window helps identify whether someone is a long-term resident, a new arrival, or has recently left the country.

Four main groups are identified:

  1. Long-term Residents
    Most people fall into this category.
    Included if they were active in the data for at least 12 months, including April 2023.
  2. Outgoing Migrants
    People who appear to have left the country.
    Excluded if they had no activity between April and December 2023.
  3. Short-term Residents
    People such as seasonal workers who were in Ireland for only part of the period.
    Excluded if they were active for fewer than 12 months between January 2022 and December 2023.
  4. New Arrivals
    People who recently moved to Ireland.
    Included if they first appeared between February and April 2023 and remained active through December 2023.

Sometimes people flagged as short-term or outgoing may still be counted if they appear in an annual dataset. For example, a university student who worked in Ireland for only five months might still be included based on their enrolment in education.

Additional Inclusion Rules

Two final rules apply to all data sources:

  • People born after 1st April 2023 are not included in the estimate.
  • People who died on or before 1st April 2023 are also excluded.

The CSO uses administrative data on births and deaths to apply these exclusions.

Geocoding and Statistical Geography Assignment

Phase I of the IPEADS methodology is described above in the “How People are Counted” section. The Eircode Pseudonymised Identifier Key (Eircode PIK) is fundamental to the final three phases of the IPEADS methodology:

Phase II: Geocoding and Statistical Geography Assignment
Phase III: Family Estimates Methodology
Phase IV: Household Estimates Methodology

Each person identified as a member of the Administrative Population needs to be “geocoded” where possible. This involves adding the Eircode PIK using pseudonymised linkage between the Eircode PIK and pseudonymised PPSN. When a person’s record has an associated Eircode PIK, it is possible to produce statistics on that person at all levels of statistical geography. The levels of statistical geography used in IPEADS 2023 were the CSO 2022 Small Area, the CSO 2022 Electoral Division, the CSO 2022 Local Electoral Area, and County & City statistical areas.

The administrative datasets that were key during the separate geocoding exercise are listed in the Background Notes. The geocoding exercise is described in the seven steps below.

Step 1. The Eircode PIK was assigned by identifying the address with the latest administrative activity associated with the person. If that address had an associated Eircode PIK, it was assigned to the person.

Step 2. If no Eircode PIK was associated with the address, a matching exercise was conducted to establish if there was an Eircode PIK for that address on an alternative dataset.

Step 3. In cases where no Eircode PIK was assigned to a person, an Eircode PIK from the 2022 Census of Population was added to a record where a match was possible.

Step 4. The resulting file from Step 3 was used as an input to Phase III – the methodology for the family estimates.

Step 5. A key result from the family estimates methodology is the Family Unit PIK. This unique identifier for families in IPEADS is used to assign Eircode PIKs to members of the same family unit. In cases where an Eircode PIK is assigned within a Family Unit PIK, all members of that PIK will be assigned the same Eircode PIK.

Step 6. Where no Eircode PIK was found, the CSO matched the address to an address database to allocate an Eircode PIK. Step 5 is repeated for those records that now have an Eircode PIK allocated.

Step 7. Finally, it was not always possible to allocate an Eircode PIK. In these cases, a Small Area Code was allocated using hot-deck imputation.

It was possible to directly assign an Eircode PIK from an administrative source to 94% of persons. The addition of Census Eircode PIKs brought this up to 98%, and the matching exercise brought the percentage over 99%.

Family and Household Estimates

Currently, Family and Household statistics in Ireland are produced through the Census of Population. As a Frontier Release, IPEADS takes a different approach. All statistics are produced using data collected from administrative records. Information in administrative data may potentially be used as sources of information on relationships and residence status. This developmental study attempts to estimate family and household counts in Ireland in April 2023 through administrative data using a methodology devised by the CSO.

These family and household counts are less mature than the Administrative Population and may be subject to significant further methodological developments. Therefore, particular care is required when interpreting these statistics.

A Note on Family and Household Definitions

While IPEADS attempts to measure household and family structure using similar classifications to those of the Census, the methodologies used are not directly comparable due to being based on administrative data-based analysis. The family classification used, for example, can assign families into married couples, cohabiting couples, or one-parent families. Further disaggregations are not currently available.

In the case of households, two different methods for identifying households based on administrative records are used to illustrate the range of potential approaches that may be used. Future iterations of this release may feature different or additional methods for identifying households or families.

Family Estimates Methodology

In this release, a family is defined as a married couple (with or without children), a cohabiting couple (with or without children), or a one-parent family. Family members must be usual residents of the relevant household. The steps below detail how these families are counted in administrative data.

Identifying Families

The Central Records System (CRS) from the Department of Social Protection relationship dataset is used to create a method to link individuals based on their family relationships, such as parents, partners, and children.

The process begins by selecting each unique individual by a unique pseudonymised Protected Identifier Key (PIK) and extracting all associated relationships, including children, parents, and partners. These are then used to create a matrix of family relationships in the Administrative Population.

This matrix excludes individuals who do not meet the definition of a family, such as single individuals without children, who are not, in turn, classified as children in another family.

Each identified family is assigned a unique pseudonymised Protected Identifier Key called the Family Unit PIK.

Since the methodology, similar to the Census, currently does not consider multigenerational family structures, adjustments are made to prevent individuals incorrectly appearing in multiple roles. Individuals who are classified as parents or partners are reviewed to ensure that they are not also incorrectly listed as children in another family.

Assigning Familial Roles

To ensure consistency and comparability, a Family Nuclei Code (FNC) is assigned to define each person’s role within a family, structured around a selected Head of Family. This Head of Family designation is chosen randomly as a technical measure to help organise the family data.

FNC Codes:
FNC 1: Identifies the Head of Family.
FNC 2: Assigned to the partner of the Head of Family (if applicable).
FNC 3: Designates children within the family. These include biological, step, and foster children under the care of the Head of Family and their partner.

Classifying Family Types

Families are grouped by their Family Unit PIK, and they are then analysed to determine the roles of members and classified into family types:

  • One-Parent Families: Classified as either “Single Mother” or “Single Father” families based on the parent’s sex as recorded in administrative data. These are then aggregated into the broader category of “One Parent (Fathers and Mothers).”
  • Two-Parent Families:
    • With children: Classified as “Married Couple with Children” or “Cohabiting Couple with Children.”
    • Without children: Classified as “Married Couple without Children” or “Cohabiting Couple without Children.”

These family types are then aggregated into the broader categories of “Married with/without Children” and “Cohabiting with/without Children.”

Addressing Gaps in Data

Adult Children:
Adult children (FNC 3) aged over 18 are evaluated to determine if they reside with their parents or live independently. The CSO uses pseudonymised Eircode data as described in the “Geocoding and Statistical Geography Assignment” section above.

If an adult child’s Eircode indicates a separate residence, they are reclassified as “Single with No Children” and removed from the family nucleus.

Challenges of the Family Methodology

  1. Cohabiting Couples Without Children
    Couples living together without children may be less likely to report their relationship status, as there is often no perceived administrative requirement to do so. This can create challenges in accurately representing these families in data.
  2. One-Parent Families
    Differentiating between single mothers and single fathers requires careful consideration. Developments are ongoing to improve processes for identifying the primary caregiver in cases where parents are separated, ensuring the statistics reflect these arrangements accurately.
  3. Couples with Children
    For couples with children, understanding the dynamics of families with young adults (who are often highly mobile due to work or further education) requires particular attention to ensure accurate statistics.

Household Estimates Methodology

Introduction

As described in the “Geocoding and Statistical Geography Assignment” section, Eircode PIKs are added to a person’s record where possible.

Using the Eircode PIK allocation, the CSO was able to develop two methodologies that estimate the number of Household Units in the State using administrative records. These methods are now described. Each method can be considered as a potential definition of households under administrative data.

Method One

Step 1. Allocate an Eircode PIK to persons as described in the Introduction.
Step 2. Take only those records with an Eircode PIK allocated.
Step 3. Group persons within unique Eircode PIKs to create Household Units.

Method Two

Step 1. This begins by following steps 1, 2, and 3 from Method One.
Step 2. Isolate Household Units with under 7 persons allocated and create a Household Unit PIK based on unique Eircode PIKs.
Step 3a. Isolate household units with 7 or more persons allocated and:
Step 3b. Create separate Household Units by splitting persons into their unique Family Unit PIKs. For example, a household unit with 9 persons allocated with two unique Family Unit PIKs will now be considered as two Household Units of size four and five. Note that this split does not take place for Eircode PIKs where all persons are classified as “Single with No Children.”
Step 3c. Create a Household Unit PIK based on the result from Step 3b.
Step 4. Combine the results from Step 2 and Step 3c and group persons within unique Household Unit PIKs to create Household Units.

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