"Trading places": Does individual status change affect poverty attributions?

Project Summary

Many studies have confirmed a strong attribution bias in lay explanations of poverty, indicating that people accentuate individualistic reasons rather than structural explanations. This tendency especially holds for members of high status groups. When facing the major risk factors of poverty and economic deprivation, this attribution bias turns out to be highly inappropriate. The aim of the underlying project is to test whether individual experiences of losing a high status position lead to a correction of this attributional bias. Based on existing data of a previous experiment, a series of two studies with repeated measures is planned. In study 2, participants will be either assigned to a loser- or winner-condition. They will play an economic decision game for eight rounds. In the loser-condition, players will systematically fail six of eight rounds and lose a small amount of money, while the opposite will be the case in the winner-condition. At a time delayed second measurement, participants will play the game for a second time and will be switched from the winner- to the loser-condition and vice versa. We will test the effect of status change on individual perceptions of game fairness and attributions of the economic outcomes. In study 3, we will use the same paradigm, but support for redistributive game policies and pro-social donation behavior will be focused as dependent variables.

Theoretical Background

Economic success and failure strongly depend on individual starting conditions in a person’s early life (Duncan, 1996; Carter & Barrett, 2006). During the past century, numerous empirical studies have investigated the causes of poverty and economic deprivation (see Hsieh & Pugh, 1993; Sahn & Stifel, 2000; Stifel & Christiaensen, 2007; Jahan, 2007; Reddy & Minoiu, 2007 for meta-analyses and comparative data). It has been repeatedly demonstrated that a person’s social status and economic success is strongly related to unalterable antecedents like: Parental status (Jahan, 2007; Ashby & Schoon, 2010), ethnicity (Emigh et al., 2001; Platt, 2009), sex (Buvinic, 1998; Christopher et al., 2002), individual health (Filmer, 2008), residential neighborhood (Van Ham et al., 2013), or school location (Sirin, 2005; Milam et al., 2010). There is also much evidence that poverty is transmitted from one generation to the next (e.g. Barrett & Swallow, 2006; Bird, 2013). This leads to a perpetuation of poverty and economic struggles within marginalized parts of society. Exemplarily, in educational contexts, it has been shown that parents’ socio-economic status reliably predicts school performance and educational attainment of students (Walpole, 2003; Sirin, 2005; Kiernan & Mensah, 2011). However, when looking at individual explanations of poverty, unemployment or homelessness, many people tend to attribute the economic failure of others rather to individual than to structural causes (Feagin, 1972, Smith & Stone, 1989; Flanagan & Tucker, 1999; Cozzarelli, Wilkinson, & Tagler, 2001). This is especially true for people with high income (Nilson, 1981; Bullock, 1999; Nasser, 2007; Kluegel & Smith, 2017), which means that relatively advantaged individuals tend to explain poverty more by laziness, a general lack of entrepreneurial spirit, or inappropriate money management of the poor (see Nilson, 1981; Furnham, 1982; Bullock, 1999). Studies on relevant moderators of poverty attribution showed, that just world beliefs, and protestant work ethic also explain people’s accentuation of individualistic causes of poverty (Furnham & Gunter, 1984; Cozzarelli et al., 2001). Additionally, Forgas and colleagues (1982) found that more leftist, younger, and higher educated individuals attributed individual poverty significantly more frequently to external than to internal factors. Moreover, findings by Tagler and Cozarrelli (2013) indicate that affective-cognitive consistency plays an important role in predicting pro-social behavior in favor of the poor. In a survey study with 198 undergraduate students, they found that students with negative feelings and individualistic attribution bias towards the poor were more likely to refuse welfare programs and individual help for the poor compared to respondents with positive feelings and attitudes towards the poor who attributed poverty stronger to structural causes. All these findings on the relationship between one’s own status position and attribution of poverty are highly relevant when facing poverty alleviation, as redistributive policies, welfare programs, and affirmative action strategies strongly depend on the support of the middle and upper classes of society (e.g., Ervasti & Kangas, 1993; Caputo, 2005; Roosma et al., 2016). Regarding real poverty reduction, there are indeed several studies implicating that especially government spending on education and health services is able to decrease poverty rates (Gupta et al., 2002; Mosley et al., 2004; Litschig & Morrison, 2013). This equalizing effect also holds for non-education expenditures (Cantillon et al., 2003) and for affirmative action policies (Arcidiacono, 2005; see Harper & Reskin, 2005 for a systematic review).

The central question that appears with regard to the attribution bias of poverty explanation is how to change attribution styles of members of the middle and upper income classes of society. One answer can be found in dominant economic theories on justice (e.g. Rawls, 1958, 1971, 1975; Dworkin, 1981; Roemer, 1998). A core concepts of Rawls’ pioneering work is the so called “veil of ignorance”, i.e., an imagination of not knowing the conditions under which one will be born. No one knows his/her individual dispositions, the social class one will belong to, nor his/her place in society. Given this mindset, Rawls assumes that from a rational perspective, individuals should tend to prefer a social distribution of economic wealth which enables everybody independent of his/her starting conditions to have similar opportunities of development. In his vocabulary, this does also lead to an inherent preference of the so called “difference principle” which states that social and economic inequalities should be arranged so that the least advantaged members of society benefit the most. Translated to the socio-political sphere, this is equivalent to support for affirmative action policies. The aim of this proposal is to “unveil” the veil of ignorance by actively switching the perspectives of individuals from economic winner to loser positions and vice versa. By doing so, it is planned to shed more light on the relationship between self-experienced economic failure, the attribution of other people’s economic outcomes, and support for egalitarian policies.

Previous Findings

In a pre-registered previous study (https://osf.io/vs5wr), we already tested whether individual loss experiences affect attribution styles and fairness ratings of the economic context. An online experiment with 221 American participants (63.8 % male, 36.2 % female, Mage = 36.66, SD = 11.26) was conducted in which participants were randomly assigned to three conditions. In the loser-condition, participants first played a short economic game with eight trials, lost a small amount of money (Mlosses = $ -.57, SD = .11), and then saw a second (fictitious) player losing the same game. In the winner-condition, participants first won the game (Mwinnings = $ 1.28, SD = .85) and then saw the second player losing. We also assessed for a neutral observer-condition. We hypothesized that people who have experienced economic losses will evaluate the game as less fair than winners of the game or observers. We also expected that losers attribute the economic failure of the second player more to external than to internal factors compared to winners and observers. First results confirm the expected pattern for both fairness ratings and attribution styles. Participants who have experienced economic failure evaluated the game significantly as less fair than participants in the winner- and observer-condition. Also in line with the hypotheses, losers highlighted external explanations for game outcomes of the second player while observers and winners emphasized internal factors.

Planned Studies

Required Sample Size and Design

Two online experiments with repeated measures are planned to investigate in the effect of self-experienced economic failure on attribution styles, fairness evaluations, and welfare related attitudes and behaviors. An a priori power analysis for a repeated measures MANOVA with two varied factors and two measurements using G*Power (Faul et al., 2007) proposes an optimal sample size of N = 212 participants (with f = .25, r = .80, α < .05, 1 – β = .95), respectively. To allow for potential dropout, we aim to collect data of 250 participants per experiment. To avoid memory effects, a time interval of a minimum of two weeks is planned between both games. After having confirmed the informed consent, participants will be randomly assigned to one of two experimental conditions at t1. Using the same paradigm as in the previous study, participants play an economic game labeled as “investment game” for eight rounds. They will start with a credit of £ 1.00. In each round they can chose between four different boxes which contain varying chances and risks to lose or win a small amount of money (ranging from £ – .15 to + .15). Hence, game outcomes depend on both individual risk preferences as well as pure coincidence. In the winner-condition, players will systematically win 6 of 8 rounds, while participants in the loser-condition will lose 6 of 8 rounds. After having played the first game, fairness ratings, attributions of the economic outcomes, and (in study 3) preferences for redistributive game policies and donation behavior will be measured. At t1 potential moderators and control variables will be also assessed. After two weeks, participants will be recontacted and invited to play the “investment game” for a second time (t2). Those who have been in the winner-condition at t1 will be assigned to lose the game at t2 and vice versa. Afterwards, the same measures like at t1 will be used to assess fairness ratings, attribution styles, and redistributive policy preferences and donation behavior. At the end of the study, participants will be debriefed and both winners and losers will be rewarded with the maximum amount of winnings of the game. Participants who will have not reregistered for the second game will be also debriefed and compensated with the maximum winning of t1.


Manipulation check

To check whether the experimental manipulation has worked, a manipulation check will ask participants whether they perceive themselves to be “a loser” or “a winner” of the game.

Perceived fairness of the game

Four items measured on a 7-point Likert-scale will be used to assess perceived fairness (“I think the game is quite fair,” “Taken together, I think everybody has the same opportunities to win the game,” “The distribution of money seems to be fair.”, “I could imagine that there are more people losing the game than winning it,” Cronbach’s alpha Exp. 1 = .82).

Attribution of economic outcomes

Attribution style will be assessed with 2 items, respectively. Internal attributions will be measured by agreements to the statements: “The outcome of the game depends on skills and competences,” “My game tactic has influenced the payoff at the end of the game.” (using a 7-point Likert scale , Spearman’s Rho Exp. 1 = .77). External attributions will be assessed by compliance with the statements: “The outcome of the game depended only on chance,” “Whether I have won or lost the game was mere coincidence,” Spearman’s Rho Exp. 1 = .72).

Preferences for redistributive game policies

Redistribution preferences will be measured by 3 items: “I think ‘losers’ should also receive a symbolic amount of money by the experimenter at the end of the game,” “The general probability to win in the game should be increased,” “I think ‘winners’ should make small ‘donations’ of their money to the ‘losers’ of the game.” on a 7-point Likert-scale (Cronbach’s alpha Exp. 1 = .66).

Donation behavior

Will be measured by a respondents’ intention to spend money for social compensation of losers (“I can imagine to donate £ ._____ of my own credit to ‘losers’ of the game.”).


Social dominance orientation (SDO) and Just World Beliefs (JWB) will be included as relevant moderators. SDO will be measured with the 16-item scale by Pratto and colleagues (1994). General JWB will be assessed by an English version of the 6-item scale by Dalbert and colleagues (1987).


We assume that participants need about 15 minutes in total for both games. These will be compensated with a total of £ 2.00. This results in £ 700 for 250 participants. For the implementation of both studies, this requires a total of £ 1,400 (including taxes and service fees).

Open Science Practice and Feasibility Statement

To ensure the greatest possible transparency, all measurements, experimental designs, methods, and planned sample sizes will be pre-registered at the open science framework (see OSF). Collected data will be made available as soon as possible. In addition, short and easy-to-read press releases will be posted on the departments’ website.


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