Deserving a Just Pension: A Factorial Survey Approach*

Abstract

Objective. This study analyzes which characteristics of pension recipients are taken into account when evaluating the fairness of pensions. Furthermore, it identifies some respondents' characteristics and preferences that could be related to the justice evaluation of different pension amounts. Methods. A factorial survey was designed to simultaneously analyze the association of respondents' and recipients' characteristics with the pensions' justice evaluation. Results. Findings indicate that although there is a consensual demand for larger pensions, it is still believed that pensions should be allocated primarily based on individual achievement. Conclusions. Although in general, larger pensions are on average considered as more just, the justice criteria rely heavily on individual achievement over redistributive considerations, showing willingness to accept very low pensions for those considered not deserving them.

The ethnic penalty in welfare deservingness: A factorial survey experiment on welfare chauvinism in pension attitudes in Germany

“…An individual's pension contribution history is most important in determining pension benefits and average income and years of contribution show the strongest effects. This is in line with previous research (Castillo et al, 2019;Schrenker, 2009) and shows the importance of the reciprocity criteria. For example, having an average income of €800 instead of €400 should result in a pension increase of €153 according to the public.…”

The perceived fair duration of unemployment benefits for older workers. The role of lifetime achievements in the labour market

“…Factorial survey experiments—also called vignette studies—are a well‐established instrument in empirical justice research (Jasso, 2006; Liebig et al, 2015). In the social policy field, they have been applied to different research fields, such as just pensions (Castillo et al, 2019), perceptions of fairness regarding wage settlements (Pfeifer et al, 2017) or the perceived deservingness of welfare claimants (Buss, 2019; Reeskens & van der Meer, 2019).…”

Analyzing factorial survey data with structural equation models

“…One solution is to estimate a separate regression model for each individual respondent (see row 4 in Table 1). These individual-level regression weights could then be used in a subsequent analysis in which the weights are linked to individual background variables such as age or sex (Jasso 2006) and/or other observed respondent-level variables (Castillo, Olivos, and Azar 2019; Finger 2016). As an example, Jasso and Opp (1997) study how characteristics of protests (economical/political discontent, legal/illegal protest, low/high personal influence, personal risk, expected number of participants, gender) affect normative evaluations of protest participation among German citizens, using individual-level regression models to account for the fact that respondents differentially weigh the protest characteristics in their evaluations.…”