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EVENTS

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Lecture:Whom to Educate? Financial Fraud and Investor Awareness

Seminar of Economic and Social Research Institute (N0.43)

Whom to Educate? Financial Fraud and Investor Awareness


Seminar | April 19, 2017 | 3:00-4:15 p.m. | 106B conference room in Zhonghui Building

Speaker: Huang Yang-guang, Hong Kong University of Science and Technology

Sponsor: JNU Economic and Social Research Institute


ABOUT HUANG YANG-GUANG

Huang Yang-guang is assistant professor of economics of Hong Kong University of Science and Technology. He obtained his bachelor’s degree from Sun Yat-sen University, master’s and doctor’s degree in economics from University of Washington. His main research fields are industrial organization economics and applied microeconomics. He focuses on studying policy-oriented topics by combing economic model and structural econometrics.


Abstract:

Financial fraud is a prevailing issue, especially in developing countries. We study how investors are exploited by too-high-to-be-true financial products using a model in which a fraction of investors are unaware of the possibility of financial fraud. Unaware investors purchase financial products that are inconsistent with their risk attitudes, and their behaviors, in turn, provide incentive for firm to conduct financial fraud. Reducing the fraction of unaware investor induces firm to behave honestly and financial fraud disappear if this fraction drops below a certain threshold.


With this insight, we conduct a field experiment in Shenzhen, China, which experimentally measure investor's risk attitude and the effect of an eye-opening financial education program. We find that, the efficacy of education program depends on investor's risk attitude, financial literacy measure, and demographic characteristics. The education program significantly reduces an investor's possibility of investing in financial frauds, especially for those who are risk-averse. Therefore, compared to assigning the education program randomly, targeting on risk averse investors will be more effective. Using the data from our experiment and survey, we conduct a counterfactual analysis to quantify this effect.


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