Migration Fear, Information Access, and Analyst Forecast Accuracy

We document a racial accuracy gap in analyst forecast accuracy linked to societal immigration fears. Using 1.3 million EPS forecasts (1990–2023) and a news-based migration fear measure, we find that a one-standard-deviation increase in fear raises Non-White analysts' absolute forecast errors by $0.04 EPS, with no effect on White peers. Using the 2015–2016 U.S. presidential election as an inflection point in immigration sentiment, we find consistent results. The migration fear penalty is most pronounced in firms with high idiosyncratic volatility and is attenuated under Non-White CEO leadership and sanctuary jurisdictions. These findings suggest that societal tensions reduce private information sharing with minority analysts. Supporting this, we find that Non-White analysts experience a 5.7 percentage point reduction in conference call participation during high-fear periods, which coincides with their increased forecast errors. Overall, anti-immigrant sentiment can impede trust and information flows, with implications for market efficiency and labor market consequences.

Keywords: Migration, immigration, financial analyst, earnings forecasts, earnings announcement, forecast accuracy

JEL Classification: J71

Suggested Citation: Suggested Citation

Wan, Chi and Wang, Sean and Wang, Yakun and Yorulmaz, Alptug, Migration Fear, Information Access, and Analyst Forecast Accuracy (January 27, 2026). SMU Cox School of Business Research Paper No. 25-8, Available at SSRN: https://ssrn.com/abstract=5193858 or http://dx.doi.org/10.2139/ssrn.5193858