|Unemployed|(0.139)<br>_[0.01]_<sup>_***_</sup><br>1.122<sup>***</sup>|(0.136)<br>_[0.01]_<sup>_***_</sup><br>1.054<sup>***</sup>|(0.158)<br>_[0.04]_<sup>_**_</sup><br>1.209<sup>***</sup>|(0.254)<br>_[0.05]_<sup>_**_</sup><br>0.902<sup>**</sup>|(0.260)<br>_[0.28]_<br>0.730|
|---|---|---|---|---|---|
||(0.253)<br>_[0.01]_<sup>_***_</sup>|(0.244)<br>_[0.01]_<sup>_***_</sup>|(0.395)<br>_[0.01]_<sup>_***_</sup>|(0.400)<br>_[0.04]_<sup>_**_</sup>|(0.531)<br>_[0.27]_|
|Missing employment status|0.587|0.661|2.197<sup>***</sup>|3.514<sup>***</sup>|-1.432<sup>*</sup>|
||(0.731)<br>_[0.45]_|(0.683)<br>_[0.40]_|(0.683)<br>_[0.09]_<sup>_*_</sup>|(0.920)<br>_[0.01]_<sup>_***_</sup>|(0.704)<br>_[0.34]_|
|Income group: reference group, lowest income||||||
|group.||||||
|2nd income group|-0.440<sup>***</sup>|-0.453<sup>***</sup>|-0.515<sup>*</sup>|-0.096|-0.645<sup>**</sup>|
||(0.142)|(0.140)|(0.266)|(0.307)|(0.306)|
||_[0.01]_<sup>_***_</sup><br>|_[0.01]_<sup>_***_</sup><br>|_[0.12]_<br>|_[0.87]_|_[0.04]_<sup>_**_</sup><br>|
|3rd income group|-0.683<sup>***</sup>|-0.665<sup>***</sup>|-0.868<sup>***</sup>|-0.246|-0.730<sup>*</sup>|
||(0.201)|(0.194)|(0.236)|(0.341)|(0.349)|
||_[0.03]_<sup>_**_</sup>|_[0.03]_<sup>_**_</sup>|_[0.01]_<sup>_***_</sup>|_[0.50]_|_[0.03]_<sup>_**_</sup>|
|4th income group|-1.249<sup>***</sup>|-1.188<sup>***</sup>|-1.207<sup>***</sup>|-0.673<sup>**</sup>|-1.495<sup>***</sup>|
||(0.123)<br>_[0.01]_<sup>_***_</sup>|(0.125)<br>_[0.01]_<sup>_***_</sup>|(0.212)<br>_[0.01]_<sup>_***_</sup>|(0.245)<br>_[0.02]_<sup>_**_</sup>|(0.307)<br>_[0.01]_<sup>_***_</sup>|
|Highest income group|-1.957<sup>***</sup>|-1.808<sup>***</sup>|-1.915<sup>***</sup>|-1.299<sup>**</sup>|-1.968<sup>***</sup>|
||(0.219)<br>_[0.01]_<sup>_***_</sup>|(0.205)<br>_[0.01]_<sup>_***_</sup>|(0.336)<br>_[0.01]_<sup>_***_</sup>|(0.504)<br>_[0.06]_<sup>_*_</sup>|(0.374)<br>_[0.01]_<sup>_***_</sup>|
|Missing income group|-0.530<sup>**</sup>|-0.456<sup>**</sup>|-0.301|-0.471|-0.633|
||(0.213)|(0.217)|(0.289)|(0.285)|(0.441)|
||_[0.03]_<sup>_**_</sup>|_[0.13]_|_[0.36]_|_[0.12]_|_[0.18]_|
|Observations|26825|26825|11603|6430|8792|
|_R_<sup>2</sup>|0.219|0.223|0.238|0.173|0.233|

Notes: OLS regressions where the dependent variable is the perceptions of equality expressed in Gini index equivalent (minimum value 20, maximum value 42). Column 2 restricts the sample for those observation with non-missing data on the political ideology variable (individuals that answer “no political preference” or counted as missing). Column 3 restricts the sample to those who have a value of 1 (far-left) or 2 (left) in the political ideology variable. Column 4 restricts the sample to those who have a value of 3 (center) in the political ideology variable. Column 5 restricts the sample to those who have a value of 4 (right) or 5 (far right) in the political ideology variable. Country and year dummies included in all regressions but not reported. Clustered standard errors at the country level in parentheses. Wild bootstrap country level clustered p-values in brackets. Significance: * p<0.10, ** p<0.05, *** p<0.01.

With respect to individual characteristics, we also find some important differences. The age and employment differences are more notable for the left and center individuals than for right wing individuals; and gender appears to be relevant only for those in the center. This means that individual characteristics, that seem to matter for most of the population, are not so relevant for right-leaning individuals. There is an exception: individuals` self-interest variables are relevant in shaping inequality perceptions for all groups. In other words, it seems as if individuals leaning to the right of the ideology spectrum shape their perceptions differently than the rest.

A main limitation of the above regression is that the sample size gets significantly reduced because the political ideology variable is missing for many individuals. To overcome this limitation Table 2c uses an alternative variable to proxy for political ideology. This proxy is derived from the answer to question 12 in the ISSP questionnaire which asks about the importance of “what is needed to support a family” in determining how much people ought to earn. Five possible answers range from essential to not important at all. As in the earlier case, we divide the sample into three groups depending on the degree to which individuals assign importance to this factor. When we include this variable in the regression as a control 31