The Good News-Bad News Effect: Asymmetric Processing of Objective Information about Yourself

2011 ◽  
Vol 3 (2) ◽  
pp. 114-138 ◽  
Author(s):  
David Eil ◽  
Justin M Rao
Keyword(s):  
Negative Feedback ◽  
Confirmation Bias ◽  
Bad News ◽  
Good News ◽  
Bayes Rule ◽  
Past Work ◽  
Objective Information ◽  
New Information ◽  
Accuracy And Precision ◽  
News Effect

We study processing and acquisition of objective information regarding qualities that people care about, intelligence and beauty. Subjects receiving negative feedback did not respect the strength of these signals, were far less predictable in their updating behavior and exhibited an aversion to new information. In response to good news, inference conformed more closely to Bayes' Rule, both in accuracy and precision. Signal direction did not affect updating or acquisition in our neutral control. Unlike past work, our design varied direction and agreement with priors independently. The results indicate that confirmation bias is driven by direction; confirmation alone had no effect. (JEL D82, D83)

The Demand for, and Avoidance of, Information

2021 ◽  
Author(s):  
Russell Golman ◽  
George Loewenstein ◽  
Andras Molnar ◽  
Silvia Saccardo
Keyword(s):  
Decision Making ◽  
Time Lag ◽  
Relevant Information ◽  
Behavioral Theory ◽  
Bad News ◽  
Good News ◽  
Focus Attention ◽  
New Information ◽  
Attention Demand ◽  
Aid Decision

Management scientists recognize that decision making depends on the information people have but lack a unified behavioral theory of the demand for (and avoidance of) information. Drawing on an existing theoretical framework in which utility depends on beliefs and the attention paid to them, we develop and test a theory of the demand for information encompassing instrumental considerations, curiosity, and desire to direct attention to beliefs one feels good about. We decompose an individual’s demand for information into the desire to refine beliefs, holding attention constant, and the desire to focus attention on anticipated beliefs, holding these beliefs constant. Because the utility of resolving uncertainty (i.e., refining beliefs) depends on the attention paid to it and more important or salient questions capture more attention, demand for information depends on the importance and salience of the question(s) it addresses. In addition, because getting new information focuses attention on one’s beliefs and people want to savor good news and ignore bad news, the desire to obtain or avoid information depends on the valence (i.e., goodness or badness) of anticipated beliefs. Five experiments (n = 2,361) test and find support for these hypotheses, looking at neutrally valenced as well as ego-relevant information. People are indeed more inclined to acquire information (a) when it feels more important, even if it cannot aid decision making (Experiments 1A and 2A); (b) when a question is more salient, manipulated through time lag (Experiments 1B and 2B); and (c) when anticipated beliefs have higher valence (Experiment 2C). This paper was accepted by Yan Chen, behavioral economics and decision analysis.

scholarly journals How People Update Beliefs about Climate Change: Good News and Bad News

2018 ◽  
Author(s):  
Cass R Sunstein ◽  
Sebastian Bobadilla-Suarez ◽  
Stephanie C. Lazzaro ◽  
Tali Sharot
Keyword(s):  
Climate Change ◽  
Temperature Rise ◽  
Scientific Evidence ◽  
Bad News ◽  
Good News ◽  
International Agreement ◽  
Average Temperature ◽  
New Information ◽  
Politics And Law ◽  
New Evidence

102 Cornell L. Rev. 1431 (2017)People are frequently exposed to competing evidence about climate change. We examined how new information alters people’s beliefs. We find that people who are not sure that man-made climate change is occurring, and who do not favor an international agreement to reduce greenhouse gas emissions, show a form of asymmetrical updating: They change their beliefs in response to unexpected good news (suggesting that average temperature rise is likely to be less than previously thought) and fail to change their beliefs in response to unexpected bad news (suggesting that average temperature rise is likely to be greater than previously thought). By contrast, people who strongly believe that manmade climate change is occurring, and who favor an international agreement, show the opposite asymmetry: They change their beliefs far more in response to unexpected bad news (suggesting that average temperature rise is likely to be greater than previously thought) than in response to unexpected good news (suggesting that average temperature rise is likely to be smaller than previously thought). The results suggest that exposure to varied scientific evidence about climate change may increase polarization within a population due to asymmetrical updating. We explore the implications of our findings for how people will update their beliefs upon receiving new evidence about climate change, and also for other beliefs relevant to politics and law.

scholarly journals THE ASYMMETRIC VOLATILITY OF THE ISLAMIC CAPITAL MARKET DURING THE COVID-19 PANDEMIC

2021 ◽  
Vol 7 ◽  
Author(s):  
Achmad Nurdany ◽  
Muhammad Hanif Ibrahim ◽  
Muhammad Fathul Romadoni
Keyword(s):  
Capital Market ◽  
Bad News ◽  
Good News ◽  
Stock Index ◽  
Asymmetric Volatility ◽  
Future Value ◽  
Variance Equation ◽  
The Government ◽  
News Effect ◽  
Parameter Coefficient

This study attempts to identify the existence of asymmetric volatility in the Islamic capital market in Indonesia during the Covid-19 pandemic. The paper employs the symmetric analysis of the GARCH (1,1) model and the asymmetric analysis of the TGARCH (1,1) model in order to identify Islamic capital market behaviour duringthe first 200 days after the first Covid-19 cases were confirmed. We used the daily closing prices of the Indonesia Sharia Stock Index (ISSI). The symmetric analysis of the GARCH (1,1) model revealed that the current value of return on the ISSI does not have a significant impact on its future value. On the other hand, the TGARCH (1,1) model showed that the asymmetric parameter coefficient was positive and statistically significant. Good news and bad news does not have the same level of impact on the volatility of returns on the ISSI. Furthermore, coefficients αi and γi in the variance equation indicate that good news has a higher volatility impact than bad news. The results indicate that investors should not to worry about the bad news effect of theCovid-19 pandemic, while the government should continue the mitigation of the spread of the coronavirus along with its economic recovery policy.

Do you want the good news or the bad news first?

2011 ◽  
Author(s):  
Angela Legg ◽  
Kate Sweeny
Keyword(s):  
Bad News ◽  
Good News

Volatility Transmission in Indian Banking Sector

2019 ◽  
Vol 118 (7) ◽  
pp. 161-165
Author(s):  
Cyano Prem ◽  
Dr M. Babu ◽  
C. Hariharan ◽  
R. Muneeswaran
Keyword(s):  
Financial Markets ◽  
Banking Sector ◽  
Bad News ◽  
Private Bank ◽  
Volatility Transmission ◽  
The People ◽  
New Information ◽  
High Volatility ◽  
The Government ◽  
Awareness Programme

Any new information about the economy is transmitted fast and it may influence the financial markets, positively or negatively. The present study used GARCH (1, 1) and EGARCH models, to investigate the volatility of Indian banking sectors indices, namely, Nifty PSU Index and Nifty Private Bank Index of NSE India Ltd. The result of the study confirmed that the high volatility was found in both the bank indices. At the same time, negative information about Indian economics did affect the PSU and Private Bank Sector indices during the study period. Finally, the study concluded that bad news travels fast and it increased volatility more than good. Hence the Government should give more information and awareness programme to the people before the implementation of any economic policy.

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