A Network-Based Explanation of Perceived Inequality

Abstract

Across income groups and countries, the public perception of economic inequality and many other macroeconomic variables such as inflation or unemployment rates is spectacularly wrong. These misperceptions have far-reaching consequences, as it is perceived inequality, not actual inequality informing redistributive preferences. The prevalence of this phenomenon is independent of social class and welfare regime, which suggests the existence of a common mechanism behind public perceptions. We propose a network-based explanation of perceived inequality building on recent advances in random geometric graph theory. The literature has identified several stylised facts on how individual perceptions respond to actual inequality and how these biases vary systematically along the income distribution. Our generating mechanism can replicate all of them simultaneously. It also produces social networks that exhibit salient features of real-world networks; namely, they cannot be statistically distinguished from small-world networks, testifying to the robustness of our approach. Our results, therefore, suggest that homophilic segregation is a promising candidate to explain inequality perceptions with strong implications for theories of consumption behaviour.

A Network Approach to Consumption

“…We are thus able to replicate the main finding of the canonical model of 'expenditure cascades' by Frank et al (2014) within plausible and endogenously evolving social networks. However, we also find that effect sizes are both state-dependent for the very same behavioural parameters and decrease with homophily because for the given graph-generating process, two counteracting effects mediate the effect of actual inequality on perceived inequality (Schulz et al 2021). Firstly, holding the network-topology constant, increases in aggregate inequality also increase inequality within perception groups and thus decrease savings.…”

“…These include the small-world property which holds across many different domains (Galaskiewicz 2007;Newman 2001;Uzzi & Spiro 2005;Weeden & Cornwell 2020), homophily in tie-formation, especially for economic class (Boucher 2015;Cepić & Tonković 2020;Huckfeldt 1983;Malacarne 2017;Mayer & Puller 2008) and their sparsity, especially when focusing on close ties (Mac Carron et al 2016;De Giorgi et al 2020). Schulz et al (2021) present a model of homophilic tie formation that can generate these stylised facts of empirical graph topologies as well as being able to replicate all the relevant findings on positional self-assessment and perceptions of inequality. Since our argument builds on status consumption, which rests on the individuals' perception of consumption, we adopt this modelling framework as an algorithm for plausible social networks.…”

“…The link function's exponential character ensures that those with large income differences become unlikely picks even at low homophily strengths. For an extensive analytical discussion of this linkage behaviour, see Schulz et al (2021). Our linkage function represents a tractable reduced-form representation of the empirically well-established homophily.…”

“…The foundational contribution byFrank et al (2014) only builds on classifications according to income deciles and does not include a discussion of inner-decile links thatSchulz et al (2021) find to be of crucial importance for perceptions.2 Cf Sen's (1984). foundational discussion about absolute and relative dimensions of poverty.…”