Contagious Bank Runs: Evidence from the 1929–1933 Period

Saunders, Anthony; Wilson, Berry

doi:10.1006/jfin.1996.0022

Cited by 153 publications

(73 citation statements)

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“…Kaufman (1994) reviews empirical studies that measure the adverse e¤ects on banks' equity returns of default of a major bank and of a sovereign borrower or unexpected increases in loan-loss provisions announced by major banks. Others have studied contagion through the ‡ow of deposits (Saunders and Wilson 1996), and using historical data (Gorton 1988, Schoenmaker 1996and Calomiris and Mason 1997. Whatever the methodology, these studies support the view that pure panic contagion is rare.…”

Section: Introductionmentioning

confidence: 70%

Systemic Risk, Interbank Relations, and Liquidity Provision by the Central Bank

Freixas¹,

Parigi²,

Rochet³

2000

Journal of Money, Credit and Banking

1,106

626

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Section: Introductionmentioning

confidence: 70%

Systemic Risk, Interbank Relations, and Liquidity Provision by the Central Bank

Freixas¹,

Parigi²,

Rochet³

2000

Journal of Money, Credit and Banking

1,106

626

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“…4,5 1 Allen et al (2011, chapter 3) identify five sources for systemic risk: common exposure to asset price bubbles; mispricing of assets; fiscal deficits and sovereign default; currency mismatches in the banking system; maturity mismatches and liquidity provision. A growing literature examines a wide range of channels through which contagion in the banking sector may occur, such as common asset exposure (Acharya, 2009;Ibragimov et al, 2011;Wagner, 2010), domino effects through the payments system or interbank markets due to counterparty risk (Allen and Gale, 2000;Dasgupta, 2004;Freixas and Parigi, 1998;Freixas et al, 2000;Rochet and Tirole, 1996), or price declines and resulting margin requirements (Brunnermeier and Pedersen, 2009). Beyond these recent events, the contagion of deposit withdrawals across banks has been documented for the U.S. during the Great Depression (Calomiris and Mason, 1997;Saunders and Wilson, 1996) as well as more recently in emerging markets (De Graeve and Karas, 2010;Iyer and Puri, 2012). However, the existing literature provides only scarce guidance on which underlying economic and informational conditions may foster contagious bank runs.…”

Section: Introductionmentioning

confidence: 99%

Understanding Bank-Run Contagion

2017

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. The refereeing process of this paper has been coordinated by a team composed of Gerhard Rünstler, Kalin Nikolov and Bernd Schwaab (all ECB). Terms of use: Documents inThe paper is released in order to make the research of MaRs generally available, in preliminary form, to encourage comments and suggestions prior to fi nal publication. The views expressed in the paper are the ones of the author(s) and do not necessarily refl ect those of the ECB or of the ESCB. Acknowledgements Abstract:We study experimental coordination games to examine through which transmission channels, and under which information conditions, a panic-based depositor-run at one bank may trigger a panic-based depositor-run at another bank. We find that withdrawals at one bank trigger withdrawals at another bank by increasing players' beliefs that other depositors in their own bank will withdraw, making them more likely to withdraw as well. Importantly though, observed withdrawals affect depositors' beliefs, and are thus contagious, only when depositors know that there are economic linkages between their bank and the observed bank.JEL classification: D81; G21; G28

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“…Super-aggregation in adversity may also take place in humans, as suggested by the occurrence of sudden bank runs [10][11][12] and human stampedes [13][14][15][16][17][18][19]. It is, however, unclear whether these events actually emerge from superaggregation, from other causes such as sudden changes in the private information towards a single preferred option, or from a combination of both.…”

Section: Contrast With Experimental Datamentioning

confidence: 99%

“…This phenomenon is well documented in groups of moving animals, which often form tighter groups in response to the detection of a predator [1][2][3][4][5][6]; but it also takes place in other adverse conditions, such as in the absence of food [7] or when animals are introduced into an unknown environment [8,9]. In humans, the occurrence of sudden bank runs [10][11][12] and human stampedes [13 -19] suggests increased aggregation in adversity, although data are insufficient to draw definitive conclusions. We will use the term super-aggregation in adversity to describe all these situations, regardless of whether aggregation occurs in physical space (as in groups of prey fleeing from a predator) or in the space of possible choices (as in investors deciding what shares to buy or sell).…”

Section: Introductionmentioning

confidence: 99%

Adversity magnifies the importance of social information in decision-making

Pérez‐Escudero

Polavieja

2016

Preprint

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Decision-making theories explain animal behaviour, including human behaviour, as a response to estimations about the environment. In the case of collective behaviour, they have given quantitative predictions of how animals follow the majority option. However, they have so far failed to explain that in some species and contexts social cohesion increases when conditions become more adverse (i.e. individuals choose the majority option with higher probability when the estimated quality of all available options decreases). We have found that this failure is due to modelling simplifications that aided analysis, like low levels of stochasticity or the assumption that only one choice is the correct one. We provide a more general but simple geometric framework to describe optimal or suboptimal decisions in collectives that gives insight into three different mechanisms behind this effect. The three mechanisms have in common that the private information acts as a gain factor to social information: a decrease in the privately estimated quality of all available options increases the impact of social information, even when social information itself remains unchanged. This increase in the importance of social information makes it more likely that agents will follow the majority option. We show that these results quantitatively explain collective behaviour in fish and experiments of social influence in humans.

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Contagious Bank Runs: Evidence from the 1929–1933 Period

Cited by 153 publications

References 0 publications

Systemic Risk, Interbank Relations, and Liquidity Provision by the Central Bank

Systemic Risk, Interbank Relations, and Liquidity Provision by the Central Bank

Understanding Bank-Run Contagion

Adversity magnifies the importance of social information in decision-making

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