Humans have ever devoted some of their resources to improve the situation of family members, friends, peers, community members, or fellow compatriots. For instance, parents use resources to finance their children a light-hearted youth and invest in their education. Unfortunately, not all children are lucky to have affluent parents, such that the human trait to care for other people - though in all aspects commendable - inevitably generates inequality. A defining aspect of such inherited inequality is that the individuals or groups on the receiving end are not involved in the process that generates inequality, yet end up with different amounts of resources or opportunities based solely on relations that are often unrelated to individual deserts. While inherited inequality may be undesirable, disallowing individuals to deploy resources for the sake of those who they care for may be as well, as it constitutes a restriction to their personal freedom.
Because individuals may generally differ in how they weigh the ideals of equality and personal freedom, opinions can diverge on the question of whether inherited inequality is undesirable, tolerable, or even desirable in a given situation. Numerous studies have documented that people care deeply whether institutions and the distribution of resources they imply are fair. Perceived unfairness might polarize society and contribute to an increasing discontentment with democracy. To mitigate this danger, it is of considerable importance to understand people’s attitudes towards inherited inequality and how they are shaped by individual characteristics and contextual features. Similarly, such an understanding makes it easier for economists and policymakers to predict support for policies related to inherited inequality. This might, for instance, help to clarify the conditions under which a welfare-improving tax reform is likely to be supported by a majority of taxpayers.
We have designed an online experiment to study attitudes towards inherited inequality among the US general population, and how they relate to preferences over real-world institutions and policies.
In particular, we ask the following questions:
- How do individuals redistribute in situations with “classic” (i.e., non-inherited) vs. inherited inequality?
- How do redistributive preferences depend on whether
- inequality is (originally) based on luck vs. effort?
- individuals on the dispensing and receiving end are meaningfully vs. randomly associated?
- consumption inequality or inequality of opportunity is inherited?
The design can be readily extended to study how different contextual features shape these attitudes, making it an ideal workhorse for subsequent research on this topic.
Our design is based on the impartial spectator paradigm (Cappelen et al., 2013) and consists of two stages:
- In the work stage, economic inequality between pairs of participants is generated.
- In the redistribution stage, impartial spectators can freely redistribute within these pairs.
We are interested in spectators’ redistribution decisions and how these relate to preferences over real-world policies elicited after the redistribution stage.
Each spectator is randomly assigned to one of three treatments. Moreover, within each treatment, we confront each spectator with different situations. We will first focus on the baseline treatment and explain how these situations differ. Then, we will outline how the two other treatments differ from the baseline.
Figure 1 illustrates the situations a spectator faces in the baseline treatment. We distinguish between classic inequality and inherited inequality.
Under classic inequality , an initial allocation of 10$ is determined based on the relative performance of the two participants on a real effort task (Effort) or a random draw (Luck). The spectator is informed whether inequality was determined by luck or effort and can redistribute the 10$ freely between the two participants.
Under inherited inequality , the earnings of active participants are determined in the same way. However, each active participant additionally appoints one real-life friend as his or her passive counterpart. The initial earnings of each passive participant are identical to the earnings of the associated active participant. The spectator can redistribute only between the two passive individuals.
Figure 1: Illustration of the Baseline Treatment.
Crossing classic/inherited inequality with effort/luck yields four different conditions. Each spectator makes incentivized redistribution decisions in all four conditions, which allows us to relate our findings on attitudes towards inherited inequality to previous research on classic inequality (for an overview, see Cappelen et al., 2020).
In addition to the Baseline treatment, we have designed two other treatments, which are illustrated in figure 2.
- Random Associations: This treatment was designed to investigate whether the nature of associations between active and passive participants is an important determinant of attitudes towards inherited inequality. The treatment mirrors the baseline in all aspects except that active and associated passive participants are not friends but randomly assigned strangers.
- Inequality of Opportunity: This treatment was designed to investigate whether individuals reject inherited inequality of opportunity more readily than inherited consumption inequality. The treatment differs from the baseline in that passive participants engage in a work stage, where their marginal return to performance is dependent on their active counterparts’ performance/random draw.
Figure 2: Illustration of the inherited-inequality parts of all three treatments.
We apply for Prolific-credit to recruit the spectator sample.
We want to power the between-subjects treatment comparisons of the average amount of inequality equalized by spectators for each of the four conditions. Assuming - based on Almas et al. (2020) - that the distribution of the amount of inequality equalized between spectators has a standard deviation of 0.425 and specifying a minimum detectable effect size of 7%p, we require 580 spectators per treatment to get 80% power at alpha = 0.05.
At 5.50$ (4 GBP) per spectator (40 minutes on Prolific), this amounts to 4 x 3 x 580 = 6960 x 1.33 = 9256.8 GBP. To additionally finance a small pilot to make sure that spectators understand that active and passive participants are meaningfully related in the baseline treatment, we would like to apply for 10000 GBP in total.
The study has been preregistered on the AEA RCT registry (https://www.socialscienceregistry.org) under the title “Attitudes Towards Inherited Inequality”. Further, we will make data, analysis code, and oTree code publicly available after peer-reviewed publication of the study.
Almås, I., Cappelen, A. W., & Tungodden, B. (2020). Cutthroat capitalism versus cuddly socialism: Are Americans more meritocratic and efficiency-seeking than Scandinavians?. Journal of Political Economy, 128(5), 1753-1788.
Cappelen, A. W., Konow, J., Sørensen, E. Ø., & Tungodden, B. (2013). Just luck: An experimental study of risk-taking and fairness. American Economic Review, 103(4), 1398-1413.
Cappelen, A. W., Falch, R., & Tungodden, B. (2020). Fair and Unfair Income Inequality. Handbook of Labor, Human Resources and Population Economics, 1-25.