Tenure and Households in Ireland 2016-2019

Introduction

This new CSO report, ‘Tenure & Households in Ireland, 2016 – 2019’, examines recent social and economic conditions in Ireland with a focus on households by tenure type, dwelling type and family unit composition (see Table 1.1 for the broad classifications adopted). Themes such as housing characteristics, income and labour force participation are examined.

Some of the findings include:

• In Q2 2019, people in households ‘rented from a local authority’ recorded an unemployment rate of 17.1%, down 4.6 percentage points on the previous year (State: 5.4%, down 0.6 percentage points).
• Family units composed of ‘couple with children’ had the highest labour force participation rate in Q2 2019, at 71.6% compared to 'single person household' at 46.7%.  The participation rate for the State was 62.1% in Q2 2019.
• In 2018 the highest median equivalised disposable income was among people in household tenures that 'own with a mortgage or a loan’ at €27,082, while those who 'rented from a local authority' had the lowest income at €14,612 (State median: €22,872).
• People who ‘rented from a local authority’ had the highest ‘at risk of poverty' rate among housing tenures in 2018 of 41.7% (State: 14.0%) and the highest deprivation rate of 39.6% (State: 15.1%).
• In 2016 in all 58.4% of homes that were ‘owned outright’ were a ‘detached house’, while ‘detached house’ was also the most prevalent dwelling type for those who 'own with a mortgage or loan' (47.8%).
• A couple with children, totalling four people, was the most common family unit category in 2016 by number of persons, at 240,762 households, or 14.2% of all households.

Data sources

The primary CSO data sources for this publication were:

• Censuses of 2006, 2011 and 2016
• EU Statistics on Income and Living Conditions (SILC) 2017 and 2018
• Labour Force Survey (LFS) Q2 2018 and Q2 2019
• Household Finance and Consumption Survey (HFCS) 2018
• Geographical Profiles of Income in Ireland 2016

Standardised categories for tenure type and dwelling type (see Table 1.1) were applied to Census, LFS, HFCS and SILC, while a standardised category for family unit type was applied to Census and LFS only.

These classifications were also applied to pseudonymised datasets from a range of administrative data sources, to produce further insight. These administrative data sources were from:

• Revenue
• Department of Employment Affairs and Social Protection
• Housing Assistance Payment (HAP)

This report is an example of the policy-relevant research projects the CSO are developing as part of its leadership role in the Irish Statistical System. Our goal is to maximise the variety and volume of data available to provide high quality information to the Government, businesses and citizens, through the development of a National Data Infrastructure (NDI).

The NDI plays an integral part in facilitating the CSO to develop new and improved statistical products for the benefit of citizens and policymakers. The core concept of the NDI involves the collection, maintenance and storage on all public-sector data holdings, of the associated PPSN, Eircode and Unique Business Identifier (UBI) to be developed whenever they are relevant to Public Sector Body transactions with customers. This supports the development of targeted policy interventions.

Under the auspices of the Statistics Act 1993, and in compliance with all relevant data protection legislation, the CSO is in a unique position to gather and link administrative data sources held by Government departments and agencies and evaluate their potential for statistical use.

The demand for data and insight into Irish society continues to grow unabated. The growth is not just apparent in terms of the broad range of themes (e.g. globalisation, productivity and well-being) that Official Statisticians are being asked to provide information on but also in relation to the level of detail being required in the analysis (e.g. socio-demographic variables). It is clear that the range and depth of demand cannot be met from survey data alone but through analysis of new data sources including administrative records held by public sector bodies. 

Acknowledgements

We would like to thank the following people for their help and assistance in the production and compilation of this report.

The Statistical and Data Analytics Unit, and their colleagues, in the Department of Housing , Planning and Local Government

Central Statistics Office:

Cormac Halpin - Census Outputs

Deirdre Lynch - Census Dissemination

Edel Flannery – Labour Market & Earnings

Jim Dalton – Labour Market Analysis

Gerard Reilly – Income, Consumption & Wealth

Eva O’Regan – Income, Consumption & Wealth

Lianora Bermingham - Income, Consumption & Wealth

Stephen Lee - Income, Consumption & Wealth