The Household Finance and Consumption Survey (HFCS) was conducted under the auspices of the European Central Bank’s Household Financial and Consumption Network (HFCN). This is a network of Eurosystem experts (drawn mainly from national central banks in the Eurozone) and was set up in December 2006 with all Euro area countries participating. The HFCN is the guiding body in all matters relating to the HFCS and their website can be found at:
The fieldwork for the first wave of HFCS surveys were carried out in most countries (except for Ireland and Estonia) in 2010 and 2011. The second wave was carried out between 2013 and 2015 and the third was carried out in 2017 and 2018. The results of the first two waves are available on the HFCN website above.
The HFCS is a household survey which collects data on household consumption and finances. It covers areas such as demographics, real and financial assets, liabilities, consumption and saving, income and employment, future pension entitlements, intergenerational transfers, gifts and attitudes to risk. The main aim of the survey is to gather micro-level, structural information on households’ assets and liabilities in the Euro area. In addition, in order to adequately capture and analyse economic decisions of households, it is necessary that some additional information is also collected (e.g. on income, consumption, etc.).
While participation in the HFCN is voluntary for respondents, all Eurozone countries contribute to the HFCN and conduct the survey in their respective countries. A common Eurosystem blueprint questionnaire is the starting point for country questionnaires.
The common questionnaire is composed of a common set of core output variables, which all countries report to the ECB according to the agreed common standards and definitions. In addition, there is a set of standardised non-core extensions that countries may voluntarily collect, and which therefore also provide comparable output for participating countries.
The HFCN questionnaire was used in Ireland but it was amended slightly to include questions of national interest. The HFCS questionnaire is split into nine sections, including:
The HFCS data was collected directly from private households. Institutional households, (e.g. nursing homes, barracks, boarding schools, hotels etc.) were not covered by the survey. A household was defined as a single person or group of people who regularly reside together in the same accommodation and who share the same catering arrangements. The household members were not necessarily related by blood or marriage. The HFCS had a further requirement that dwellings where members were financially independent of each other were to be considered separate households.
The overall sample for the HFCS was 13,200 households. The selection process for the survey was divided into two elements:
This 82/18 split in the sample between those selected proportionally from the entire population and those selected as part of the oversampling process is common for countries when oversampling for the wealthy in HFCS and is recommended by the HFCN.
This process gave us a sampling distribution for the entire sample of 66% of all selected households in the bottom 80% of households (as measured by the affluence/deprivation index), and 34% of the sample for the top 20% of households as measured by the deprivation/affluence index.
In line with HFCN guidelines, household substitution was not used in the survey. This ensured that the HFCS used probability sampling, i.e. every household in the target population had a non-zero probability of being included in the sample. This probability could also be determined ex-ante, i.e. before selecting the units included in the initial sample.
The survey started in April 2018 and field work continued until early January 2019. Data was collected for the main sample of 10,800 households by permanent CSO interviewers. A temporary team of interviewers was hired and trained specifically to collect data from the 2,400 ‘oversample’ households. Household interviewers, in as much as was possible resided within, or adjacent to, the areas they were responsible for.
Interviewers were provided with a map of each of their interview areas as well as a listing of the address of each of the selected households. All interviewers were provided with specific HFCS training. The permanent team of interviewers are very experienced, having previously worked on CSO surveys such as the Household Budget Survey, the Survey on Income and Living Conditions and the Labour Force Survey.
Interviewers received a manual with information such as detailed explanations about the questionnaire and definitions of the concepts involved. There was also a thorough review of the questionnaire as it appeared on the laptop as well as a detailed examination of the more complex elements of the questionnaire.
The co-operation of sample households was mainly canvassed by interviewers on the basis of the importance of the survey and the usefulness of the results
Each participating household completed a detailed household questionnaire which covered general household-level questions while each household member aged 16 years and over also completed a personal questionnaire which covered income, education, work status and other demographic related questions.
The data was captured by means of CAPI (Computer Assisted Personal Interviewing) in face to face interviewing. This enabled the use of extensive checks in the BLAISE interviewing software to make sure correct and coherent data was collected. It also ensured that respondents were only asked relevant questions, that all applicable questions were answered (although it was possible for many questions to accept a “Don’t know” or “Refused to answer” reply) and specific answers were within valid ranges. In many cases the BLAISE also made sure that the relationship between linked answers was within acceptable limits. In certain cases, the BLAISE alerted the interviewer to the fact that an answer, while not incorrect, was implausible. In these cases, the interviewer might have to probe further.
The field work ran for 39 weeks with 2 extra weeks at the end of the survey period to get outstanding returns. The field work for the survey was fully completed by mid-January 2019.
The final status of the survey is as follows:
There were 4,793 respondent households and a response rate of 45.1% when vacant properties and properties that were not attempted are excluded. No interview was attempted at 15% of properties due to resourcing issues.
|Table 10.1 Summary of outcomes|
|Status||Number of households|
|No contact with anyone at sampled dwelling||2,014|
|Contact made at sampled dwelling/household, but not with any responsible resident known to live at the address||18|
|Refusal at introduction/before interview (either by desired respondent or by proxy)||3,255|
|Away / at hospital during survey period||124|
|Physically or mentally unavailable/incompetent/ Ill at home during survey period||112|
|Unknown whether address contains residential housing; other unknown eligibility||41|
|Non-residential address/ business purpose / Communal establishment/institution||12|
|Address occupied, but no resident household (not the main residency – it is only used as a secondary home)||25|
The average interview length was around one hour, with the time varying according to the size of household and its circumstances. Approximately 10 per cent of interviews lasted one hour and 20 minutes or longer.
Other Data Sources
As is usual for CSO household surveys, information other than survey data was used to construct HFCS variables. This included data from the Department of Social Protection on state transfer payments, data from the Irish Agriculture and Food Development Authority (Teagasc) who provided the CSO with data on Standard Outputs (SOs) for farm animals and hectare of various crops, data from Revenue who provided income tax records, data from the Residential Tenancies Board (RTB) who provided data on rental properties, data from local councils on HAP payments and data from SUSI on student grant payments
Once the data was back in the CSO it was checked and if necessary queried with the field force. After the data collection phase was complete the field data was aggregated together with data from other sources. In certain cases, text strings (used as an “other” category for some questions) were re-coded to the proper category while further validation checks were done.
This is a process to assign values to missing data. While unit non-response (i.e. the complete record is missing) was dealt with by the weighting procedure, item non-response (where the respondent has either refused to answer a question or doesn’t know the answer) had to be assigned a value. Certain variables were defined by the HFCN as requiring a 100% response so where the answer could not be derived from other sources this nonresponse was corrected by imputation.
Multiple Imputation, based on Gibbs sampling and Hot deck methodology were used to impute missing values. With these methods, five imputed values based on different random draws are provided to the user for each missing value, resulting in five copies of the complete dataset. Gibbs sampling is an iterative Markov procedure of successive simulation of the distribution of variables conditioned on both observed data and distributions of variables previously simulated in the same iteration. The model imputes each missing observation using a maximal set of covariates (from the list determined by the user) from the appropriate subpopulation. For example, in the imputation of the value of bonds, only households that have bonds are considered. Hot-deck imputation is where a missing value is imputed form a randomly selected similar record.
The level of item non-response for certain variables was:
|Table 10.2 Summary of response rates for selected variables|
|Variable Description||HFCN Code||% of values imputed|
|Current value of the household main residence (HMR)||HB0900||13.4|
|Amount still owed on the mortgage on HMR||HB1701||19.5|
|Total value of cars||HB4400||3.4|
|Amount of outstanding credit line/overdraft balance||HC0220||31.7|
|Amount outstanding on private loans||HC0361||5.8|
|Value of self-employment business||HD0801||38.5|
|Value of deposit accounts||HD1110||33.4|
|Value of savings accounts||HD1210||27.5|
|Amount of outstanding credit card balance||HC0320||18.2|
The highest imputation rates needed to be done to get the value of the self-employment business a household member had an interest in. However, the difficulty in collecting accurate data from households for this variable has been noted in many of the national HFCS surveys carried out in the Eurozone previously.
Derivation of Results
In order to provide national results, the survey results were weighted to represent the entire population. The process used was as follows:
All cells in the result tables with less than 25 observations are suppressed.
The regional classifications in this release are based on the NUTS 2 (Nomenclature of Territorial Units) classification used by Eurostat. Changes made under the 2014 Local Government Act prompted a revision to the Irish NUTS 3 Regions. Three Regional Assemblies were established (Northern & Western, Southern, Eastern & Midland). The composition of the regions is set out below and here.
|Table 10.3 NUTS2 Regions|
|Northern and Western||Southern||Eastern and Midland|
The Pobal Haase-Pratschke Deprivation Index is based on Census of Population 2016 data. There are three dimensions of affluence/disadvantage Demographic Profile, Social Class Composition and Labour Market Situation. Each Census Small Area (SA) has a deprivation score calculated, based on the following indicators:
1: Demographic Profile:
2: Social Class Composition:
3: Labour Market Situation:
The scores are combined and an overall score for the SA is calculated. A relative score of over 30 implies extreme affluence while a score of 0 to 10 means the SA is marginally above average. On the other hand, a relative score of -30 or less implies extreme disadvantage in the SA.
The highest level of education of a person is defined as the highest attainment of an educational programme the person has successfully completed. The HFCS used the International Standard Classification of Education (ISCED 2011) to code the data received in the survey. The basic classifications used in this report are:
Degree of Urbanisation
The degree of urbanisation indicates the character of the area where the household lives on the basis of population size and density. It distinguishes three types of areas: densely, intermediate, and thinly populated areas.
The classification of local administrative units (LAU2) in densely, intermediate and thinly populated areas uses as a criterion the geographical contiguity in combination with the share of local population living in different type of clusters. In a first step, clusters are defined by classifying grid cells of 1km2 to one of the three following clusters, according to their population size and density:
High-density cluster/urban centre: contiguous grid cells of 1km2 with a density of at least 1,500 inhabitants per km2 and a minimum population of 50,000;
Urban cluster: cluster of contiguous grid cells of 1km2 with a density of at least 300 inhabitants per km2 and a minimum population of 5,000;
Rural grid cell: grid cell outside high-density clusters and urban clusters.
Local administrative units (LAU2) are then classified to one of three types of area:
Densely populated area: at least 50% lives in high-density cluster in addition, each high-density cluster should have at least 75% of its population in densely-populated LAU2s; this also ensures that all high-density clusters are represented by at least one densely-populated LAU2, even when this cluster represents less than 50% of the population of that LAU2;
Intermediate density area: less than 50% of the population lives in rural grid cells and less than 50% live in high-density clusters;
Thinly-populated area: more than 50% of the population lives in rural grid cells
This is a common concept used in this report. The median value is the value below which 50 per cent of the observations lie. Because financial and income data is often highly skewed, it is often preferred as a measure compared to the mean, which may be affected by a small number of very high values. For example, in the dataset 1,4,10,20 and 100, the median value is 10 but the mean value is 27.
The wealth or income quintile groups are five equal-sized groups of households, each group containing 20% of households. The income quintile “Less than 20” also referenced in this publication as ”First (or bottom) income quintile” contains the fifth of households with the lowest gross household income, group “20-39” contains the fifth of households with the next lowest gross household income etc. The group “80-100” also referenced in this publication as “Fifth (or top) income quintile” contains the fifth of households with the highest gross household income. Likewise, the wealth quintile “Less than 20” or “First (or bottom) net wealth quintile” contains the fifth of households with the lowest net household wealth (and so on).
Net Wealth Deciles
The net wealth decile groups are ten equal-sized groups of households, each group containing 10% of households. The first (bottom) decile contains the tenth of households with the lowest net household wealth, whereas the tenth (top) decile contains the tenth of households with the highest net household wealth.
Equivalised Income and Wealth
When conducting joint distributional analysis differences in household composition and size should be accounted for. As a household’s size increases then the potential sources of income increase as does the consumption needs of the household. To account for differences in household size and composition an equivalised household size was calculated for each HFCS household. The first adult in each household was attributed a weight of 1, each subsequent adult (aged 14+ living in the household) was attributed a weight of 0.66 and each child aged less than 14 was attributed a weight of 0.33. The weights for the individuals in each household were then summed to calculate the equivalised household size. Gross household income was then divided by the equivalised household size to calculate equivalised gross income for each person. Likewise, household net wealth was divided by the equivalised household size to calculate equivalised net wealth for each person in the household. Essentially these equivalised income and wealth values are approximate measures of how much of the household income and wealth can be attributed to each member of the household. When considering wealth as an economic resource that may be used to support current consumption, the OECD in the ‘Framework for Statistics on the Distribution of Household Income, Consumption and Wealth’ publication advise that it is appropriate to equivalise wealth with the same equivalence scales used to equivalise income.
In the HFCS income information was only collected on gross household income. Ideally net income should be used when conduction joint distributional analysis as net income supports consumption. The SILC survey collects information on both gross and net income. Analysis of 2018 SILC gross and net equivalised income shows that over 80% of individuals are in the same equivalised gross and net income quintiles. 86.5% of SILC individuals in the top net equivalised quintile were also in the top gross equivalised income quintile, the remainder (13.5%) were in the fourth gross equivalised income quintile.
A household is defined as a person living alone or a group of people who live together in the same private dwelling and share expenditures, including the joint provision of the essentials of living, such as catering arrangements. The household members defined in this fashion are usually, but not necessarily, related by blood or by marriage. Any other individual or group of people living in the same dwelling constitutes a separate household.
Persons usually resident, but temporarily absent from the dwelling for a period of less than six months (for reasons of holiday travel, work, education or similar) are included as household members.
Persons financially dependent and not having their private household somewhere else (like students studying away from home, persons away for work regularly returning and considering the sampled dwelling as their main place of residence) are included as household members even if their length of absence may exceed six months.
Persons with usual residence in the dwelling but not sharing expenditures (e.g. lodgers, tenants, etc.) are treated as separate households. Consequently, in some specific cases there can be more than one household in a dwelling.
Household Reference Person
This person is considered to be the person who is most knowledgeable about the financial situation of the household and provides the financial information for the whole household, since this information is collected together for the whole household instead of by individual members. This is done to both minimise response burden and to avoid duplications (since many assets and liabilities are shared between household members).
No specific direction is given as to who is to be taken as the reference person of the household, but it has to be an adult member. It is left to individual households to determine who the appropriate person is. There is no problem in normal family-type situations. In other cases (e.g. man, wife and a married child with family) decisions made depend on the circumstances and the approach followed is to take the person whom the household regards as its reference person. This person was also known as the financially responsible person.
Household Main Residence
This is defined as the dwelling where the members of the household usually live, typically a house or an apartment. A household can only have one main residence at any given time, although they may share the residence with people not belonging to the household.
Household income includes all money receipts which accrue to the household regularly at annual or more frequent intervals. The gross receipts, (i.e. before subtraction of income tax and social insurance deductions) of individual household members are combined to give the average income for the households. The components of gross income are direct income and social transfers.
Direct income is composed of employee income and gross cash benefits or losses from self-employment. It also includes pensions from individual private plans, income from rental of property or land, regular inter-household cash transfers received, interests, dividends and profit from capital investments in unincorporated business. Social transfers include Jobseekers payments, state pensions and family/children related allowances such as maternity/adoptive benefit, child benefit, one-parent family payments and carers’ payments). It also includes housing allowances such as rent supplement, free phone/electricity etc, fuel allowances and exceptional needs payments. Other social transfers include survivors’ payments, sickness payments, disability payments, education-related allowances and social exclusion not elsewhere classified.
Gross household income excludes certain receipts which are generally of an irregular and non-recurring nature. The principal exclusions are receipts for sale of possessions, withdrawals from savings, loans obtained, loan repayments received, windfalls, prizes, retirement gratuities, maturing insurance policies etc. Furthermore, transfers of money between household members (e.g. pocket money, housekeeping money etc.) are ignored since the household is treated as a single unit.
Most respondents aged 16 years and over supplied the CSO with their Personal Public Service Number (PPS No). In these cases, the Department of Social Protection supplied the CSO with detailed information regarding state transfer payments received by the respondent in the interview week and in the 12-month period prior to the interview date. Revenue supplied the CSO with detailed information regarding income received by the respondent in the 12-month period prior to the interview date.
Calculations for farming income was based on UAA (Utilised Agriculture Area) = The number of hectares of land owned + number of hectares rented in – the number of hectares let out – number of hectares in bog land – number of hectares in woodland – number of hectares in other areas e.g. lakes. The Farm Accountancy Data Network (FADN code) for the farm was derived from the detailed questions asked regarding the hectares of farmland under different crop types and activity (i.e. stock on farm).
The Irish Agriculture and Food Development Authority Teagasc provided the CSO with Standard Outputs (SOs) for each hectare of crop and for each type of animal. Farms were then classified into groups, according to the proportion of total SO which came from each enterprise. Farm income was then estimated by applying the relevant income co-efficient (supplied by Teagasc). Coefficients were supplied for different farm classifications of different ‘Utilised Agriculture Area’ size.
Publicly Traded Shares
Publicly traded shares are shares that are listed on a stock exchange or other form of secondary market, i.e. they can be bought and sold there.
This includes items such as jewellery, works of art, antiques etc.
These are businesses in which somebody in the household is either self-employed in or has an active part in running the business. Examples would include a self-employed plumber, partner in an accounting firm or the director and part-owner of a haulage company.
This includes items such as all types of deposit and savings accounts as well as positive balance on current accounts
Money market funds (MMF) are defined as those collective investment undertakings the shares/units of which are, in terms of liquidity, close substitutes for deposits. They are funds primarily invested in money market instruments, MMF shares/units and in other transferable debt instruments with a residual maturity of up to and including one year.
These are bearer instruments, are usually negotiable but do not grant the holder any ownership rights to the institutional unit issuing them. They provide the holder with the unconditional right to a fixed or contractually determined variable money income in the form of coupon payments (interest) and/or a stated fixed sum on a specified date or dates or starting from a date fixed at the time of issue. The issuer owes the holders a debt and is obliged to repay the principal and interest (the coupon) at a later date, termed maturity. A bond is generally transferrable from one person to another. For the purposes of HFCS, Post Office savings bonds and prize bonds are classified as ‘Bonds’.
Voluntary Pensions and Life Assurance
These are personal (voluntary) plans, access to which is not linked to an employment relationship. Individuals independently purchase and select material aspects of the arrangements without intervention of their employers. Some personal plans may have restricted membership (e.g. to the self-employed, to members of a particular craft or trade association, to individuals who do not already belong to an occupational plan, etc).
Holders of life insurance policies, both with profit and without profit, make regular payments to an insurer (there may be just a single payment), in return for which the insurer guarantees to pay the policy holder an agreed minimum sum or an annuity, at a given date or at the death of the policy holder, if this occurs earlier. Term life insurance, where benefits are provided in the case of death but in no other circumstances, is excluded here
This is defined as the sum of real and financial assets.
Only certain assets and liabilities are included. In particular, the present value of all future, expected defined benefit pensions is excluded, which can be a sizable portion of the wealth of many households. The present value of future, voluntary, expected defined contribution pensions is included.
This is defined as gross wealth less total debt.
This is the ratio between total liabilities and total gross assets for indebted households. It is expressed as the (weighted) median. Households with zero debt are excluded from the calculation.
This is the ratio between total liabilities and total gross income for indebted households. It is expressed as the (weighted) median. Households with zero debt are excluded from the calculation.
Debt Service-income Ratio
This is the ratio between total monthly debt payments and household gross monthly income for indebted households. Households with zero debt are excluded from the calculation.
Mortgage Debt Service-income Ratio
This is the ratio between the mortgage debt service repayments of a household to the income of that household, for households with mortgage debt. Households with zero income are excluded from the calculation.
Loan-Value Ratio of HMR
This is the ratio between the remaining debt on the household main residence to the value of that main residence, for households with mortgage debt.
Net Liquid Assets to Income
Net liquid assets are calculated as the sum of value of deposits, mutual funds, bonds, non-self-employment business wealth, (publicly traded) shares and managed accounts net of overdraft debt, credit card debt and other non-mortgage debt. This is calculated for all households excluding those with zero income.
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