Imputation of income data with generalized calibration procedure and GB2 law: illustration with SILC data
| Résumé |
In sample surveys of households and persons, questions about income
are often sensitive and thus subject to a higher non-response rate.
Nevertheless, the household or personal incomes are among the
important variables in surveys of this type. The distribution of
such collected incomes is not normal, neither log-normal.
Hypotheses of classical regression models to explain the income (or
their log) are not fulfilled. Imputations using such models modify
the original and true distribution of the data. This is not
suitable and may conduct the user to wrong interpretations of
results computed from data imputed in this way. The generalized
beta distribution of the second kind (GB2) is a four parameters
distribution. Empirical studies have shown that it adapts very well
to income data. The advantage of a parametric income distribution is
that there exist explicit formulae for the inequality measures like
the Laeken indicators as functions of the parameters. We present a
parametric method of imputation, based on the fit of a GB2 law on
the income distribution by the use of suitably adjusted weights
obtained by generalized calibration. These weights can compensate
for non ignorable non-response that affects the variable of
interest. We validate our imputation system on data from the Swiss
Survey on Income and Living Conditions (SILC). |
| Mots-clés |
GB2, generalized calibration, imputation, inequality measures, non-ignorable non-response, SILC |
| Citation | Graf, E., & Tillé, Y. (2013). Imputation of income data with generalized calibration procedure and GB2 law: illustration with SILC data. Presented at The 59th ISI World Statistics Congress, Hong Kong. |
| Type | Présentation (Anglais) |
| Date | 31-8-2013 |
| Evénement | The 59th ISI World Statistics Congress (Hong Kong) |
| URL | http://www.isi2013.hk/en/index.php |
| Liée au projet | Convention Université de Neuchâtel/Office fédéral de la s... |