Third-person Effect and Financial Contagion in the Context of a Global Game

Tai-kuang Ho; Ming-yen Wu

doi:10.1007/s11079-011-9215-3

Open Economies Review

November 2012, Volume 23, Issue 5, pp 823–846 | Cite as

Third-person Effect and Financial Contagion in the Context of a Global Game

Authors
Authors and affiliations

Tai-kuang HoEmail author
Ming-yen Wu

Research Article

First Online: 21 September 2011

233 Downloads
2 Citations

Abstract

In this paper we present a psychological channel of financial contagion. We incorporate this new channel of financial contagion in the global game. Our basic assumption is that agents are overestimating the influence of negative messages they ascribe to others, and are thus acting on the basis of this perception. We resort to the psychological studies on the so-called third-person effect to justify this assumption. We show that the third-person effect is rationalizable. Our model has the feature that a crisis in a foreign country can be transmitted to the domestic country, even though there has been no changes in domestic fundamentals. Our model also provides intuitive explanations to the empirical observations that many governments have lost in a confidence game in the past crisis episodes.

Keywords

Global game Financial contagion Third-person effect

JEL Classification

C72 G15 G18

This is a preview of subscription content, to check access.

Notes

Acknowledgements

The authors thank Shyh-fang Ueng, Jen-hung Wang and Kuo-chun Yeh for helpful discussions. The authors thank editor George S. Tavlas and an anonymous referee for their insightful comments and suggestions. Financial support from Taiwan’s National Science Council NSC 96-2415-H-194-006 is acknowledged.

Appendix A

The third-person effect, proposed by Davison (1983) and discussed mainly in the mass communication literature, refers to a tendency for people to perceive that the media messages have a greater impact on the beliefs and behaviors of others than on themselves. Examples of third-person effect can be found in voter behavior, fluctuations in the stock market, hoarding of goods when supplies of consumer goods are irregular, and the phenomenon of censorship. The third-person effect is mediated by the nature of the comparison other and the type of media content. The effect is more pronounced when people consider potential impact of negative media content such as violence, sexism, and racism, and when people compare themselves with vague and distant others (Duck and Mullin 1995). We have mentioned in the main text the conditions that facilitate the third-person effect. In this Appendix, we describe the processes through which the third-person effect operates.

The first psychological explanation to the processes that underlie the third-person effect is downward comparison. Perloff and Fetzer (1986) argue that downward comparison makes an individual to perceive himself as invulnerable to negative messages. When confronted by the question of whether negative messages have a greater impact on him or on the others, an individual tends to compare himself to a group of ‘lower than average’ people. The attributes of these people make them more susceptible to the threat of victimization.

What motivates an individual to compare downward? A possible reason is an ego-defensive function, namely, such a comparison helps to reduce self-anxiety and to preserve control and self-esteem. For instance, when asking an individual whether he is more likely to be influenced by violence in the media than others, refusing the idea that he is more vulnerable to the media than others will help to sustain self-esteem and alleviate the pressures that he is a victim of violence in media. Another reason is cognitive. An individual tends to compare himself to a stereotype of people who have a greater risk of becoming the victims of the negative messages. A vivid example is to ask an individual whether he is more likely to get cancer than others. The individual being questioned usually compares his risk of getting cancer to the risk of elders or people addicted to smoking. This phenomenon is more likely to happen when the questioner does not clearly specify who the others are. The same mechanism also makes people judge themselves as less likely than others to get divorced.

The second psychological explanation is based on attribution theory. In general, attribution theory refers to the study of processes people use to infer causes of behavior. It is postulated that there is a widespread tendency for people to attribute their actions to situational (or external) factors and to attribute the same actions of others to dispositional (or internal) factors. Applied to a media message, people assume themselves being aware of situational factors and are less influenced by the message, while others do not take account of situational factors regarding the message and are more likely to be affected by it. The third-person effect arises from this consistent bias in estimating the situational response.

Appendix B

We follow Morris and Shin (2003) to prove the existence of a unique equilibrium. The proof consists of two steps. First, we show that there is a strategy that survives n rounds of iterated elimination of dominated actions. Second, we show that there is only one strategy that solves the model. Following the main text, we assume that the expected payoff function v(x _i, k) is continuous in both x _i and k. It is monotonically increasing in x _i and monotonically decreasing in k. A strategy survives n rounds of iterated elimination of dominated actions if and only if

$$ \begin{array}{ccc} s\left( x_{i}\right) =1 & if & x_{i}\leq \underline{\xi }_{\;n} \\ s\left( x_{i}\right) =0 & if & x_{i}>\overline{\xi }_{n} \end{array} $$

where s(·) indicates investor i’s behavioral action, s = 0 denotes the continuation of the investment and s = 1 denotes investment withdrawal. We define $\underline{\xi }_{\;n}$ and $\overline{\xi }_{n}$ recursively as:

$$ \underline{\xi }_{\;n+1}=\min \left\{ x_{i}:v\left( x_{i},\underline{\xi } _{\;n}\right) =0\right\} $$

$$ \overline{\xi }_{n+1}=\max \Big\{ x_{i}:v\Big( x_{i},\overline{\xi } _{n}\Big) =0\Big\} $$

where $\underline{\xi }_{\;0}=-\infty $ and $\overline{\xi }_{0}=\infty $. We first show that there is only one value of $\underline{\xi }_{\;n}$ and $ \overline{\xi }_{n}$, respectively, that survives n rounds of iterated elimination of dominated actions. Let us start from n = 0 and suppose $ \underline{\xi }_{\;0}=-\infty <\underline{\theta }$ and $v\left( \underline{ \theta },\underline{\xi }_{\;0}\right) <0$. It is possible to find a $ \underline{\xi }_{\;1}$ such that $v\left( \underline{\xi }_{\;1},\underline{ \xi }_{\;0}\right) =0$. Since $v\left( x_{i},k\right) $ is increasing in x _i and decreasing in k, $\underline{\xi }_{\;1}$ must satisfy the condition that $\underline{\xi }_{\;0}<\underline{\theta }<\underline{\xi } _{\;1} $. We can proceed a step further and find a $\underline{\xi }_{\;2}$ such that $v\left( \underline{\xi }_{\;2},\underline{\xi }_{\;1}\right) =0$. Since $ v\left( \cdot \right) $ is decreasing in k, it must be the case that $ \underline{\xi }_{\;1}<\underline{\xi }_{\;2}$. We can employ the same argument and start from $\overline{\xi }_{0}$. Suppose $\overline{\xi }_{0}=\infty > \overline{\theta } $ and $v\left( \;\overline{\theta },\overline{\xi } _{0}\right) >0$. It is possible to find a $\overline{\xi }_{1}$ such that $ \overline{\xi }_{\;0}>\overline{\theta }>\overline{\xi }_{1}$ and $v\left( \;\overline{\xi }_{1},\overline{\xi }_{0}\right) =0$. And so forth. The above argument demonstrates that $\underline{\xi }_{\;n}$ is an increasing sequence and $\overline{\xi }_{n}$ is a decreasing sequence. Thus, as n approaches ∞, $\underline{\xi }_{\;n}$ will approach $\underline{\xi }$ and $ \overline{\xi }_{n}$ will approach $\overline{\xi }$. An equilibrium requires that there exists a fixed point such that $v\left( \underline{\xi }, \underline{\xi }\right) =0$ and $v\left(\; \overline{\xi },\overline{\xi } \right) =0$. This completes our first step of proving the existence of equilibrium.

The second step is fairly intuitive in that, we only have to show that there is a single solution to the expected payoff function. This has already been done in Section 3 of our main text. Therefore, $\underline{\xi }$ is just $ \overline{\xi }$, and there is only one strategy remaining after eliminating all iteratively dominated strategies.

References

Banerjee A (1992) A simple model of herd behavior. Q J Econ 107(3):797–818CrossRefGoogle Scholar
Bikhchandani S, Hirshliefer D, Welch I (1992) A theory of fads, fashion, custom, and cultural change as informational cascades. J Polit Econ 100(5):992–1026CrossRefGoogle Scholar
Bikhchandani S, Hirshliefer D, Welch I (1998) Learning from the behavior of others: conformity, fads, and informational cascades. J Econ Perspect 12(3):151–170CrossRefGoogle Scholar
Broner FA, Gelos GR, Reinhart CM (2006) When in peril, retrench: testing the portfolio channel of contagion. J Int Econ 69:203–230CrossRefGoogle Scholar
Calvo S, Reinhart C (1996) Capital flows to Latin America: is there evidence of contagion effect? In: Calvo G, Goldstein M, Hochreiter E (eds) Private capital flows to emerging markets after the Mexican crisis. Institute for International Economics, Washington DCGoogle Scholar
Calvo GA, Mendoza EG (2000) Rational contagion and the globalization of securities markets. J Int Econ 51:79–113CrossRefGoogle Scholar
Carlsson H, van Damme E (1993) Global games and equilibrium selection. Econometrica 61(5):989–1018CrossRefGoogle Scholar
Conners JL (2005) Understanding the third-person effect. Commun Res Trends 24(2):3–22Google Scholar
Corsetti G, Pesenti P, Roubini N (1999) What caused the Asian currency and financial crisis? Japan World Econ 11(3):305–373CrossRefGoogle Scholar
Corsetti G, Pesenti P, Roubini N (2002) The role of large players in currency crises. In: Edwards S, Frankel J (eds) Preventing currency crises in emerging markets. NBER and Chicago University PressGoogle Scholar
Corsetti G, Dasgupta A, Morris S, Shin HS (2004) Does one soros make a difference? A theory of currency crises with large and small traders. Rev Econ Stud 71:87–113CrossRefGoogle Scholar
Costain J (2007) A herding perspective on global games and multiplicity. BE J Theor Econ 7(1):Article 22Google Scholar
Davison WP (1983) The third-person effect in communication. Public Opin Q 47:1–15CrossRefGoogle Scholar
Degroot MH (1970) Optimal statistical decisions. McGraw-Hill Book CompanyGoogle Scholar
Dellas H, Stockman A (1993) Self-fulfilling expectations, speculative attack, and capital controls. Journal of Money, Credit, and Banking 25(4):721–730CrossRefGoogle Scholar
Duck JM, Mullin B-A (1995) The perceived impact of the mass media: reconsidering the third person effect. Eur J Soc Psychol 25(1):77–93CrossRefGoogle Scholar
Edison HJ, Reinhart CM (2000) Capital controls during financial crises: the case of Malaysia and Thailand. Board of Governors of the Federal Reserve System, International Finance Discussion Papers no 662Google Scholar
Edwards S (2000) Contagion. World Econ 23(7):873–900CrossRefGoogle Scholar
Forbes K, Rigobon R (2001) Measuring contagion: conceptual and empirical issues. In: Claessens S, Forbes K (eds) International financial contagion. Kluwer Academic Publishers, Boston, pp 43–66Google Scholar
Gerlach S, Smets F (1995) Contagious speculative attacks. Eur J Polit Econ 11:45–63CrossRefGoogle Scholar
Goldstein I (2005) Strategic complementarities and the twin crises. Econ J 115:368–390CrossRefGoogle Scholar
Gunther AC, Mundy P (1993) Biased optimism and the third-person effect. Journal Q 70:58–67CrossRefGoogle Scholar
Hondroyiannis G, Kelejian HH, Tavlas GS (2009) Spatial aspects of contagion among emerging economies. Spatial Econ Ana 4(2):192–211Google Scholar
Kaminsky GL, Reinhart CM (2000) On crises, contagion, and confusion. J Int Econ 51:145–168CrossRefGoogle Scholar
Kaminsky GL, Reinhart CM, Végh CA (2003) The unholy trinity of financial contagion. J Econ Perspect 17(4):51–74CrossRefGoogle Scholar
Keister T (2009) Expectations and contagion in self-fulfilling currency attacks. Int Econ Rev 50(3):991–1012CrossRefGoogle Scholar
Kelejian HH, Tavlas GS, Hondroyiannis G (2006) A spatial modelling approach to contagion among emerging economies. Open Econ Rev 17:423–441CrossRefGoogle Scholar
Kodres LE, Pritsker M (2002) A rational expectations model of financial contagion. J Finance 57(2):769–799CrossRefGoogle Scholar
Lasorsa DL (1992) How media affect policymakers: the third-person effect. In: David Kennamer J (eds) Public opinion, the press and public policy. Praeger, New York, pp 163–175Google Scholar
Manz M (2002) Coordination failure and financial contagion. Diskussionsschriften no dp0203. Universitaet Bern, Departement VolkswirtschaftGoogle Scholar
Masson P (1999a) Contagion: macroeconomic models with multiple equilibria. Journal of International Money and Finance 18(4):587–602CrossRefGoogle Scholar
Masson P (1999b) Contagion: monsoonal effects, spillovers and jumps between multiple equilibria. In: Agenor P-R, Marcus M, David V, Axel W (eds) The Asian financial crisis: causes, contagion and consequences. Cambridge University PressGoogle Scholar
Morris S, Shin HS (1998) Unique equilibrium in a model of self-fulfilling currency attacks. Am Econ Rev 88(3):587–597Google Scholar
Morris S, Shin HS (2000) Rethinking multiple equilibria in macroeconomic modelling, pp 139–161. NBER Macroeconomics AnnualGoogle Scholar
Morris S, Shin HS (2003) Global games: theory and applications. In: Dewatripont M, Hansen L, Turnovsky S (eds) Advances in economics and econometrics (proceedings of the eighth world congress of the econometric society). Cambridge University Press, CambridgeGoogle Scholar
Mutz DC (1989) The influence of perceptions of media influence: third person effects and the public expression of opinions. Int J Public Opin Res 1(1):3–23CrossRefGoogle Scholar
Obstfeld M (1996) Models of currency crises with self-fulfilling features. Eur Econ Rev 40(3–5):1037–1047CrossRefGoogle Scholar
Obstfeld M (1997) Destabilizing effects of exchange-rate escape clauses. J Int Econ 43:61–77CrossRefGoogle Scholar
Paul B, Salwen MB, Dupagne M (2000) The third-person effect: a meta-analysis of the perceptual hypothesis. Mass Commun Soc 3(1):57–85CrossRefGoogle Scholar
Perloff RM (1993) Third-person effect research 1983–1992: a review and synthesis. Int J Public Opin Res 5(2):167–184CrossRefGoogle Scholar
Perloff RM (1996) Perceptions and conceptions of political media impact: the third-person effect and beyond. In: Crigler AN (ed) The psychology of political communication. University of Michigan Press, Ann Arbor, pp 177–191Google Scholar
Perloff LS, Fetzer BK (1986) Self-other judgments and perceived vulnerability to victimization. J Pers Soc Psychol 50(3):502–510CrossRefGoogle Scholar
Rzepkowski B (2003) The devaluation expectations in Hong Kong and their determinants. J Jpn Int Econ 17:174–191CrossRefGoogle Scholar
Sbracia M, Zaghini A (2001) Expectations and information in second generation currency crises models. Econ Model 18(2):203–222CrossRefGoogle Scholar
Taketa K (2004) A large speculator in contagious currency crises: a single George Soros makes countries more vulnerable to crises, but mitigates contagion. IMES Discussion Paper no 2004-E-23Google Scholar
Vaugirard VE (2004) Informational contagion of sudden stops in a global games framework. Open Econ Rev 15(2):169–192CrossRefGoogle Scholar

Copyright information

Authors and Affiliations

Tai-kuang Ho
- 1
Email author
Ming-yen Wu
- 1

1.Department of Quantitative FinanceNational Tsing Hua UniversityHsinchuTaiwan

Third-person Effect and Financial Contagion in the Context of a Global Game

Abstract

Keywords

JEL Classification

Notes

Acknowledgements

References

Copyright information

Authors and Affiliations

Personalised recommendations

Cite article