# **ANNEX 2: PUBLIC SUPPORT FOR REDISTRIBUTION**

53. To better understand the observed variation in level of public support for government involvement in redistribution, we apply an ordered probit model to the LiTS data to analyze respondents’ expressed level of support for state involvement in reducing the income-gap between the rich and poor, according to the following model specification: 54. We do not observe<sup>_y_</sup> _i_ *<sup>directly, but rather only observe whether</sup><sup>_y_</sup> _i_<sup>= 1, 2, and 3 if</sup> * α _j_ − 1 <<sup>_y_</sup> _i_ < α _j_ (j= 1, 2, and 3 respectively)—i.e. the responses are “Not involved”, “Moderately involved” and “Strongly involved” respectively. A relatively parsimonious set of factors that we think influence the level of support for redistribution of the respondent is summarized in the table below.

|**Variable**|**Obs.**|**Mean**|**Std. Dev.**|**Min**|**Max**|
|---|---|---|---|---|---|
|Govt_role|8,001|2.55|0.61|1|3|
|Lnpcexp|7,988|8.98|0.66|4.08|11.14|
|Unjust|8,002|0.38|0.49|0|1|
|Crim_corr|8,002|0.27|0.44|0|1|
|Diff|8,002|-0.82|2.08|-9|9|
|Urban|8,002|0.63|0.48|0|1|

Govt_role: Do you think the state should be involved in reducing the gap between the rich and the poor? coded as 1 = Not involved, 2 = Moderately involved, 3 = Strongly involved.

Lnpcexp: (Log) per equivalent adult (using OECD scales) annual expenditures (in PPP$) Unjust: Dummy variable indicating response to “Why are some people in need today?” is “injustice in our society” vs. “because they are unlucky”, “laziness / lack of willpower”, “inevitable part of modern life”, or “other”. Crim_corr: Dummy variable indicating response to “Which of the factors in the list is the most important to succeed in life in this country now?” is either “Criminal/corrupt ties” or “Political connections” as opposed to “effort and hard work”, “intelligence and skills”, or “other”.

Diff: Change in self-perceived decile group ranking between 1989 and present Urban: Dummy variable indicating respondent lives in urban areas

# 55. The results of the ordered probit regression are as summarized below

|_____________<br>`Ordered pro`|________________<br>`bit regressio`|________________<br>`n`|__________________|________________<br>`Number of ob`<br>`LR chi2(12)`<br>`Prob > chi2`|<br>`s =`<br>`7987`<br>`=`<br>`983.18`<br>`=`<br>`0.0000`|
|---|---|---|---|---|---|
|`Log likelih`<br>`Dependent v`|`ood`<br>`= -6`<br>`ariable: Govt`|`897.2434`<br>`_role`||`Pseudo R2`|`=`<br>`0.0665`|
|`___________`|`_____________`<br>`Coef.`|`______________`<br>`Std. Err.`|`______________`<br>`z`<br>`P>z`|`______________`<br>`[95% Conf.`|`_____________`<br>`Interval]`|
|`___________`<br>`Lnpcexp`|`_____________`<br>`-.141359`|`______________`<br>`.0226207`|`______________`<br>`-6.25 0.000`|`______________`<br>`-.1856947`|`_____________`<br>`-.0970233`|
|<br>`Unjust`|`.3861695`|`.0284654`|`13.57 0.000`|`.3303784`|`.4419607`|
|<br>`Crim_corr`|`.2399325`|`.0292308`|`8.21`<br>`0.000`|`.1826413`|`.2972238`|
|`Diff`|`-.0616844`|`.0064181`|`-9.61 0.000`|`-.0742636`|`-.0491052`|
|`Urban`|`-.1211775`|`.0282053`|`-4.30 0.000`|`-.1764589`|`-.065896`|
|`Czech Repub`|`lic`|`(omi`|`tted country)`|||
|<br>`Poland`|<br>`.0673337`|<br>`.0398107`|<br>`1.69`<br>`0.091`|`-.0106939`|`.1453612`|
|`Slovakia`|`.3627363`|`.0597159`|`6.07`<br>`0.000`|`.2456953`|`.4797772`|
|`Estonia`|`.5002743`|`.1050907`|`4.76`<br>`0.000`|`.2943003`|`.7062482`|
|`Hungary`|`.5140795`|`.0515831`|`9.97`<br>`0.000`|`.4129785`|`.6151804`|
|<br>`Latvia`|<br>`.6754206`|`.0882011`|`7.66`<br>`0.000`|`.5025497`|`.8482916`|
|`Lithuania`|`.7862243`|`.0772582`|`10.18 0.000`|`.6348009`|`.9376476`|
|`Slovenia`|`1.019498`|`.0980691`|`10.40 0.000`|`.8272863`|`1.21171`|

``` _______________________________________________________________________________ ``` 28