# EU statistics on income and living conditions (EU-SILC) methodology - 2012 housing conditions

This article is part of a set of articles describing the methodology applied for the computation of the statistical indicators pertinent to the subject area of 2012 Housing conditions (ilc_hcm) within the overall domain of Income and living conditions. It should be noted that in this article only the computation of indicators coming from 2012 EU-SILC module on housing conditions is described. The computation of other housing related indicators based on EU-SILC data is described in the articles on housing conditions and housing deprivation. For the 2012 housing conditions indicators, the article provides a methodological and practical framework of reference. The indicators relevant to this subject area are the following:

- Average size of dwelling along with different dimensions
- Share of population living in a dwelling not comfortably cool during summer time along with different dimensions
- Distribution of population by level of overall satisfaction with the dwelling along with different dimensions
- Share of population having moved to other dwelling within the last five year period along with different dimensions
- Distribution of population by level of difficulty in accessing public transport along with different dimensions

Moreover, since the indicators are of multidimensional structure and can be analysed simultaneously along several dimensions, the separate datasets providing these indicators along with the different combinations of dimensions are also presented.

## Full article

### Description

- The
**average size of dwelling**along with different dimensions with which is disseminated refers to the weighted mean of the dwelling size expressed in square meters - The
**share of population living in a dwelling not comfortably cool during summer time**along with different dimensions with which is disseminated describes the proportion of population that perceives their dwelling being not comfortably cool during the summer time - The
**distribution of population by level of overall satisfaction with the dwelling**along with different dimensions with which is disseminated refers to the share of population divided according to their level of satisfaction (HC080) with their dwelling. Assessment of satisfaction is based on the following levels (HCDW1):

- Very high
- High
- Low
- Very low

- The
**share of population having moved to other dwelling within the last five year period**along with different dimensions with which is disseminated describes the proportion of population that has changed the dwelling within the last five year period - The
**distribution of population by level of difficulty in accessing public transport**along with different dimensions with which is disseminated refers to the share of population divided according to the level of difficulty they perceive in accessing public transport (HC120). Assessment of difficulty is based on the following levels (HCDW2):

- Very high
- High
- Low
- Very low

### Statistical population

The statistical population consists of all persons living in private households. Persons living in collective households and in institutions are generally excluded from the target population.

Households and individuals therein with missing values for any of the relevant dimensions, as well as with missing values for any variables used are excluded from calculations.

### Reference period

All indicators are collected and disseminated on an annual basis and refer to the survey year.

The reference period for all dimensions along with the indicators are disseminated is the survey year, except for income and household type. The income reference period is a fixed 12-month period (such as the previous calendar or tax year) for all countries except the United Kingdom, for which the income reference period is the current year, and Ireland, for which the survey is continuous and income is collected for the last twelve months. Household type is the household type of the respondent at the end of income reference period.

Additionally, for the average size of the dwelling, satisfaction with the dwelling and difficulties in accessing public transport, the reference period is current situation; for the information if the dwelling is comfortably cool during summer, the reference period is ordinary summer time, while for the changing the dwelling the reference period is related to last five years.

### Unit of measurement

All indicators presented are made available as a percentage, with the exception of the average size of dwelling which is expressed in square meters.

### Dimensions

The separate datasets provide each indicator along with the Geopolitical entity dimension and the dimensions presented below.

The average size of dwelling is presented along with the following dimensions:

The share of population living in a dwelling not comfortably cool during summer time is disseminated broken down by:

- income quintile
- degree of urbanisation (DEGURBA)

The distribution of population by level of overall satisfaction with the dwelling is presented along with the following dimensions:

- household type

The share of population having moved to other dwelling within the last five year period is disseminated broken down by:

- tenure status
- degree of urbanisation (DEGURBA)

The distribution of population by level of difficulty in accessing public transport is presented along with the following dimensions:

- income quintile
- degree of urbanisation (DEGURBA)

### Calculation method

**1. Average size of dwelling:**

Weighted average size of dwelling along with the dimensions (k) [math](SIZE\_OF\_DWELLING_{at\_k})[/math], is calculated as weighted average of the dwelling size expressed in square meters.

The weight variable used is the Household Cross Sectional Weight (DB090).

- [math]SIZE\_OF\_DWELLING_{at\_k}=\frac{\sum\limits _{\forall i\_at\_k} DB090_i\times \;HC020_i }{\sum \limits_{\forall{i}}DB090_i}[/math]

where k denotes the respective dimensions.

With regard to the calculation of the average size of dwelling, the following methodological issues should be taken into consideration:

- The dwelling size refers to the useful floor space using the same definition as for the population and housing census and as recommended in the Programme of Current Housing and Building Statistics for Countries in the UNECE Region (Statistical Standards and Studies No. 43).
- Useful floor space is defined as the floor space measured inside the outer walls excluding non-habitable cellars and attics and, in multi-dwelling buildings, all common spaces. Household should declare the area of dwelling that can be exclusively used.
- If part of the dwelling area is shared with other households (within the same dwelling) the procedure is as follow:
- If the number of persons living in all households occupying the same dwelling is known, the shared area should be divided by the number of persons living there and the part of shared area should be added to each household according to the number of its members;
- If only the number of households occupying the same dwelling is known, the shared area should be divided by the number of households and the equal share should be added to each household;
- In all other cases the shared space should be added to each household

**2. Share of population living in a dwelling not comfortably cool during summer time:**

The share of population living in a dwelling not comfortably cool during summer time presented along with the dimensions (k) [math](NOT\_COOL_{at\_k})[/math] is calculated as the percentage of people living in a dwelling not comfortably cool during summer time (HC070 = 2) in each dimension k over the total population in that k.

The weight variable used is the Adjusted Cross Sectional Weight (RB050a).

- [math]NOT\_COOL_{at\_k}=\frac{\sum \limits_{\forall i\; where\;HC070=2\_at\_k} RB050a_i}{\sum \limits_{\forall i\_at\_k} RB050a_i } \times 100[/math]

where k denotes the respective dimensions.

**3. Distribution of population by level of overall satisfaction with the dwelling:**

Let HCDW be the variable that describes the level of overall satisfaction with the dwelling. Distribution of population by level of overall satisfaction with the dwelling broken down by each combination of dimensions (k) [math](SAT\_DWELLxxx_{at\_k})[/math] is calculated as the percentage of people in each k with different levels of satisfaction with their dwelling. The levels of satisfaction are outlined in HCDW1.

The weight variable used is the Adjusted Cross Sectional Weight (RB050a).

- [math]SAT\_DWELLxxx_{at\_k}=\frac{\sum \limits _{\forall i\;where\;HCDW1=xxx\_at\_k} RB050a_i} {\sum \limits _{\forall i\_at\_k} RB050a_i} \times 100[/math]

where k denotes the respective dimensions and xxx takes the values VHIGH (very high), HIGH (high), LOW (low) and VLOW (very low) as described above.

With regard to the calculation of the distribution of population by level of overall satisfaction with the dwelling, the following methodological issues should be taken into consideration:

- Overall satisfaction with dwelling refers to the respondent’s opinion/feeling about the degree of satisfaction with the dwelling in terms of meeting the household needs/opinion on the price, space, neighbourhood, distance to work, quality and other aspects (including the availability of a garage or parking space).

**4. Share of population having moved to other dwelling within the last five year period:**

The share of population having moved to other dwelling within the last five year period presented along with the dimensions (k) [math](CHANGE\_DWELL_{at\_k})[/math] is calculated as the percentage of people having moved to other dwelling within the last five year period (PC170 = 1) in each dimension k over the total population in that k.

The weight variable used is the Adjusted Cross Sectional Weight (RB050a).

- [math]CHANGE\_DWELL_{at\_k}=\frac{\sum \limits_{\forall i\; where\;PC170=1\_at\_k} RB050a_i}{\sum \limits_{\forall i\_at\_k} RB050a_i } \times 100[/math]

where k denotes the respective dimensions.

**5. Distribution of population by level of difficulty in accessing public transport:**

Let HCDW be the variable that describes the level of difficulty in accessing public transport. Distribution of population by level of difficulty in accessing public transport broken down by each combination of dimensions (k) [math](ACCESS\_TRANSxxx_{at\_k})[/math] is calculated as the percentage of people in each k with different levels of difficulty in accessing public transport. The levels of difficulty are outlined in HCDW2.

The weight variable used is the Adjusted Cross Sectional Weight (RB050a).

- [math]ACCESS\_TRANSxxx_{at\_k}=\frac{\sum \limits _{\forall i\;where\;HCDW2=xxx\_at\_k} RB050a_i} {\sum \limits _{\forall i\_at\_k} RB050a_i} \times 100[/math]

where k denotes the respective dimensions and xxx takes the values VHIGH (very high), HIGH (high), LOW (low) and VLOW (very low) as described above.

With regard to the calculation of the distribution of population by level of difficulty in accessing public transport, the following methodological issues should be taken into consideration:

- The public transport refers to the bus, metro, tram and similar.
- As the accessibility should be assessed in terms of physical and technical access, if the respondent or another household member has a physical disability and if the available public transport is not adapted to his disability, a difficulty in the accessibility should be recorded.
- If the public transport are too far away or have inappropriate timetable, the access would also be considered as difficult.

### Main concepts used

For the production of the indicators relevant to the subject area of housing deprivation, the variables listed below are also involved in computations:

### SAS program files

The SAS programming routines developed for the computation of the EU-SILC housing conditions datasets along with the different dimensions, are listed below.

Dataset | SAS program file |
---|---|

Average size of dwelling by income quintile and tenure status (ilc_hcmh01) | _hcmh01.sas |

Average size of dwelling by household type and degree of urbanisation (ilc_hcmh02) | _hcmh02.sas |

Share of population living in a dwelling not comfortably cool during summer time by income quintile and degree of urbanisation (ilc_hcmp03) | _hcmp03.sas |

Distribution of population by level of overall satisfaction with the dwelling and household type (ilc_hcmp04) | _hcmp04.sas |

Share of population having moved to other dwelling within the last five year period by tenure status and degree of urbanisation (ilc_hcmp05) | _hcmp05.sas |

Distribution of population by level of difficulty in accessing public transport, income quintile and degree of urbanisation (ilc_hcmp06) | _hcmp06.sas |

## Direct access to

- Living conditions and welfare (livcon)

- Income and living conditions (ilc)
- EU-SILC ad-hoc modules (ilc_ahm)
- 2012 Housing conditions (ilc_hcm)

- EU-SILC ad-hoc modules (ilc_ahm)

- Quality of life - Facts and views (2015)
- Living conditions in Europe (2014)
- European social statistics (2013) — Statistical books
- Employment and Social Situation Quarterly Review — September 2013
- Employment and Social Developments in Europe (2013)
- Combating poverty and social exclusion. A statistical portrait of the European Union (2010)
- Income and living conditions in Europe (2010) — Statistical books
- Housing conditions in Europe (2009) — Statistics in focus 4/2011
- The continuity of indicators during the transition between ECHP and EU-SILC
- Comparative EU quality reports
- Modules: assessment of implementation

- Income and living conditions (ilc) (ESMS metadata file — ilc_esms)
- Operation guidelines
- Methodological guidelines and description of EU-SILC target variables

- Regulation 1177/2003 of 16 June 2003 concerning Community statistics on income and living conditions (EU-SILC)
- Summaries of EU Legislation: EU statistics on income and living conditions
- Regulation 1553/2005 of 7 September 2005 amending Regulation 1177/2003 concerning Community statistics on income and living conditions (EU-SILC)
- Regulation 1791/2006 of 20 November 2006 adapting certain Regulations and Decisions in the fields of ... statistics, ..., by reason of the accession of Bulgaria and Romania

- OECD — Housing
- The Housing Sector in Europe — Household Consumption Long Term and During the Crisis —
*Peter Parlasca*, RICS research report, October 2013 - United Nations — Housing and its environment
- WHO — Housing