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When two people coincidentally have something in common (such as a name or birthday), they tend to like each other more and are thus more likely to offer help and comply with requests. This dynamic can have important legal and ethical consequences whenever these incidental similarities give rise to unfair favoritism. Using a large-scale, longitudinal natural experiment, covering nearly 200,000 annual earnings forecasts over more than 25 y, we show that when a CEO and a securities analyst share a first name, the analyst's financial forecast is more accurate. We offer evidence that name matching improves forecast accuracy due to CEOs privately sharing pertinent information with name-matched analysts. Additionally, we show that this effect is especially pronounced among CEO-analyst pairs who share an uncommon first name. Our research thus demonstrates how incidental similarities can give way to special treatment. Whereas most investigations of the effects of similarity consider only one-shot interactions, we use a longitudinal dataset to show that the effect of name matching diminishes over time with more interactions between CEOs and analysts. We also point to the findings of an experiment suggesting that favoritism born of sharing a name may evade straightforward regulation in part due to people's perception that name similarity would exert little influence on them. Taken together, our work offers insight into when private disclosures are likely to be made. Our results suggest that the effectiveness of regulatory policies can be significantly impacted by psychological factors shaping the context in which they are implemented.
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Stored only when both papers are in the corpus — 11 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.