eusilc: Synthetic EU-SILC survey data

Description Usage Format Details Source References Examples

Description

This data set is synthetically generated from real Austrian EU-SILC (European Union Statistics on Income and Living Conditions) data.

Usage

1

Format

A data frame with 14827 observations on the following 28 variables.

db030

integer; the household ID.

hsize

integer; the number of persons in the household.

db040

factor; the federal state in which the household is located (levels Burgenland, Carinthia, Lower Austria, Salzburg, Styria, Tyrol, Upper Austria, Vienna and Vorarlberg).

rb030

integer; the personal ID.

age

integer; the person's age.

rb090

factor; the person's gender (levels male and female).

pl030

factor; the person's economic status (levels 1 = working full time, 2 = working part time, 3 = unemployed, 4 = pupil, student, further training or unpaid work experience or in compulsory military or community service, 5 = in retirement or early retirement or has given up business, 6 = permanently disabled or/and unfit to work or other inactive person, 7 = fulfilling domestic tasks and care responsibilities).

pb220a

factor; the person's citizenship (levels AT, EU and Other).

py010n

numeric; employee cash or near cash income (net).

py050n

numeric; cash benefits or losses from self-employment (net).

py090n

numeric; unemployment benefits (net).

py100n

numeric; old-age benefits (net).

py110n

numeric; survivor's benefits (net).

py120n

numeric; sickness benefits (net).

py130n

numeric; disability benefits (net).

py140n

numeric; education-related allowances (net).

hy040n

numeric; income from rental of a property or land (net).

hy050n

numeric; family/children related allowances (net).

hy070n

numeric; housing allowances (net).

hy080n

numeric; regular inter-household cash transfer received (net).

hy090n

numeric; interest, dividends, profit from capital investments in unincorporated business (net).

hy110n

numeric; income received by people aged under 16 (net).

hy130n

numeric; regular inter-household cash transfer paid (net).

hy145n

numeric; repayments/receipts for tax adjustment (net).

eqSS

numeric; the equivalized household size according to the modified OECD scale.

eqIncome

numeric; a slightly simplified version of the equivalized household income.

db090

numeric; the household sample weights.

rb050

numeric; the personal sample weights.

Details

The data set consists of 6000 households and is used in the examples of package laeken. Note that this is a synthetic data set based on original EU-SILC survey data.

Only a few of the large number of variables in the original survey are included in this example data set. The variable names are rather cryptic codes, but these are the standardized names used by the statistical agencies. Furthermore, the variables hsize, age, eqSS and eqIncome are not included in the standardized format of EU-SILC data, but have been derived from other variables for convenience. Moreover, some very sparse income components were not included in the the generation of this synthetic data set. Thus the equivalized household income is computed from the available income components.

Source

This is a synthetic data set based on Austrian EU-SILC data from 2006. The original sample was provided by Statistics Austria.

References

A. Alfons and M. Templ (2013) Estimation of Social Exclusion Indicators from Complex Surveys: The R Package laeken. Journal of Statistical Software, 54(15), 1–25. URL http://www.jstatsoft.org/v54/i15/

A. Alfons, M. Templ, P. Filzmoser (2011) Simulation of close-to-reality population data for household surveys with application to EU-SILC. Statistical Methods and Applications, vol 20 (3), 383-407.

Eurostat (2004) Description of target variables: Cross-sectional and longitudinal. EU-SILC 065/04, Eurostat.

Examples

1
2

Example output

Loading required package: boot
Loading required package: MASS
     db030          hsize                 db040          rb030       
 Min.   :   1   Min.   :1.000   Upper Austria:2805   Min.   :   101  
 1st Qu.:1516   1st Qu.:2.000   Lower Austria:2804   1st Qu.:151602  
 Median :2993   Median :3.000   Vienna       :2322   Median :299304  
 Mean   :3005   Mean   :3.234   Styria       :2295   Mean   :300471  
 3rd Qu.:4493   3rd Qu.:4.000   Tyrol        :1317   3rd Qu.:449302  
 Max.   :6000   Max.   :9.000   Carinthia    :1078   Max.   :600002  
                                (Other)      :2206                   
      age          rb090          pl030        pb220a          py010n      
 Min.   :-1.0   male  :7267   1      :5162   AT   :11073   Min.   :     0  
 1st Qu.:21.0   female:7560   5      :3146   EU   :  283   1st Qu.:     0  
 Median :39.0                 7      :1207   Other:  751   Median :  2566  
 Mean   :39.2                 2      :1160   NA's : 2720   Mean   :  9121  
 3rd Qu.:56.0                 4      : 736                 3rd Qu.: 16896  
 Max.   :97.0                 (Other): 696                 Max.   :151894  
                              NA's   :2720                 NA's   :2720    
     py050n           py090n            py100n          py110n        
 Min.   : -1653   Min.   :    0.0   Min.   :    0   Min.   :    0.00  
 1st Qu.:     0   1st Qu.:    0.0   1st Qu.:    0   1st Qu.:    0.00  
 Median :     0   Median :    0.0   Median :    0   Median :    0.00  
 Mean   :  1105   Mean   :  412.5   Mean   : 3641   Mean   :   72.66  
 3rd Qu.:     0   3rd Qu.:    0.0   3rd Qu.:    0   3rd Qu.:    0.00  
 Max.   :112073   Max.   :27354.3   Max.   :75837   Max.   :21281.02  
 NA's   :2720     NA's   :2720      NA's   :2720    NA's   :2720      
     py120n             py130n          py140n             hy040n        
 Min.   :    0.00   Min.   :    0   Min.   :    0.00   Min.   :     0.0  
 1st Qu.:    0.00   1st Qu.:    0   1st Qu.:    0.00   1st Qu.:     0.0  
 Median :    0.00   Median :    0   Median :    0.00   Median :     0.0  
 Mean   :   51.05   Mean   :  363   Mean   :   39.65   Mean   :   772.8  
 3rd Qu.:    0.00   3rd Qu.:    0   3rd Qu.:    0.00   3rd Qu.:     0.0  
 Max.   :31472.40   Max.   :52480   Max.   :19440.37   Max.   :118083.6  
 NA's   :2720       NA's   :2720    NA's   :2720                         
     hy050n          hy070n            hy080n             hy090n         
 Min.   :    0   Min.   :   0.00   Min.   :     0.0   Min.   :     0.00  
 1st Qu.:    0   1st Qu.:   0.00   1st Qu.:     0.0   1st Qu.:     0.50  
 Median : 1563   Median :   0.00   Median :     0.0   Median :    62.65  
 Mean   : 2995   Mean   :  87.96   Mean   :   652.3   Mean   :   468.36  
 3rd Qu.: 4823   3rd Qu.:   0.00   3rd Qu.:     0.0   3rd Qu.:   230.48  
 Max.   :96449   Max.   :4871.81   Max.   :107951.9   Max.   :109857.80  
                                                                         
     hy110n             hy130n            hy145n              eqSS      
 Min.   :    0.00   Min.   :    0.0   Min.   :-28690.3   Min.   :1.000  
 1st Qu.:    0.00   1st Qu.:    0.0   1st Qu.:  -295.3   1st Qu.:1.500  
 Median :    0.00   Median :    0.0   Median :     0.0   Median :2.000  
 Mean   :   32.73   Mean   :  328.6   Mean   :  -132.5   Mean   :1.984  
 3rd Qu.:    0.00   3rd Qu.:    0.0   3rd Qu.:     0.0   3rd Qu.:2.400  
 Max.   :13627.23   Max.   :49285.3   Max.   : 27018.1   Max.   :4.500  
                                                                        
    eqIncome          db090            rb050       
 Min.   :     0   Min.   : 357.9   Min.   : 357.9  
 1st Qu.: 13463   1st Qu.: 492.9   1st Qu.: 492.9  
 Median : 18081   Median : 527.6   Median : 527.6  
 Mean   : 19907   Mean   : 551.8   Mean   : 551.8  
 3rd Qu.: 24194   3rd Qu.: 614.7   3rd Qu.: 614.7  
 Max.   :152208   Max.   :1032.0   Max.   :1032.0  
                                                   

laeken documentation built on Jan. 10, 2019, 5:07 p.m.