Market Contagion: Evidence from the Panics of 1854 and 1857

By C. Gráda, Morgan Kelly. 2000

261 citations recorded by the source corpus.

To test a model of contagion--where individuals hear some bad news and communicate it to their acquaintances, who then pass it on, leading to a market panic--requires a knowledge of the information networks of participants, something hitherto unavailable. For two panics in the 1850s this paper examines the behavior of Irish depositors in a New York bank. As recent immigrants, their social network was determined largely by their place of origin in Ireland, and where they lived in New York. During both panics this social network turns out to be the prime determinant of behavior.

Subfields: Economics and Econometrics, Finance, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/3b637988969fa14be364a343b528a3d0b00e33c1

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Citations in the corpus

Social Transmission Bias and Investor Behavior (2021, unknown): “Massa and Simonov (2006) find that hedging motives for human capital risk, which is a fundamental source of individual investor risk, do not explain heterogeneous investment behavior among individual investors well.”
Deposit Competition and Financial Fragility: Evidence from the US Banking Sector (2017, unknown): “We model banks’ endogenous default decisions in a simple framework based on Leland (1994). Each period, equity holders decide whether to continue operations by repaying deposits and the long-term debt coupon.”
Herd Behaviour and Cascading in Capital Markets: A Review and Synthesis (2003, background): “Kelly and O’Grada (2000) and Hong et al. (2001) provide further evidence that social interactions between individuals affects decisions about equity participation and other financial decisions.”
Information linkages and correlated trading (2007, unknown): “Our ndings are similar to previous results obtained with US data: for example, Krinsky and Lee (1996) report that at a high frequency level, volume increases prior to earnings announcements; more recently, Chae (2005) uncovers a pattern for volume quite similar to ours, using daily data.”