The (Internet) Information Inequality Machine?
67 Pages Posted: 3 Nov 2018 Last revised: 20 Nov 2018
Date Written: September 20, 2018
Advances in information technology have fundamentally altered how we make decisions, as well as the range of alternative options we might consider when deciding. From fairly trivial decisions to important ones, our decisions are increasingly informed by online expert or “crowd-sourced” ratings. The use of this ratings information is no surprise as it helps reduce uncertainty. As the prevalence and usage of ratings information increase, so too does the concentration of income and wealth as “superstars” garner an increasing share of returns. There is reason to believe these trends are entwined as predicted by seminal theories in both sociology (Merton’s “Matthew Effect”) and economics (Rosen’s star markets). Both Merton’s and Rosen’s theories imply that increasing availability of ratings information should exacerbate inequality. Viewed from a different perspective, however, increasing availability of ratings information may help facilitate comparison of entities on some dimensions, thereby allowing for differentiation and consumer sorting on other dimensions. This, in turn, should reduce inequality. I test these propositions in the context of the NYC restaurant industry from 1994 – 2013 using restricted-access administrative data and matched time-varying restaurant ratings. This period purposefully envelopes Yelp’s market entry and expansion, and the greater accessibility of ratings information it afforded. Results are economically meaningful, and show heterogeneous information effects across different markets. For those market segments with less local information (e.g., tourists) making larger cultural purchases, ratings exacerbate sales disparities between competitors. Theoretical implications for both the Matthew Effect and Star Markets theories are discussed throughout.
Keywords: Economic Sociology, Information Technology, Matthew Effect, Star Markets, Imperfect Competition and Differentiation
JEL Classification: D11, D12, L1, L14, L15, L17, M20, Z13, Z30
Suggested Citation: Suggested Citation