Bo Cowgill:

At OVERCOMING BIAS, Robin Hanson blogs about the overconfidence of CEOs, CFOs and software managers. Our paper also measured overconfidence in the workplace. We found that our marketplace was overconfident as a whole, although the market&#8217-s optimistic bias subsided as time passed. We also pointed out the particular overconfidence exhibited by new employees &#8212- but prediction markets can be used to measure overconfidence and other biases for any part of an organization. Note that our study was about overconfidence regarding their employers&#8217- prospects on a variety of fronts. In a future draft, we hope to measure overconfidence for by looking at how people bet in markets related to their day-to-day jobs. In Table 9 of our paper, you can see some other information about what parts of the company produced the biases (although admittedly not in the most readable format).

Here&#8217-s the table 9. Right-click on the thumbnail to open it in another of your browser tabs.

&#8212-

Related Links:

Using Prediction Markets to Track Information Flows: Evidence From Google – (PDF file – PDF file) – by Bo Cowgill (Google economic analyst), Justin Wolfers (University of Pennsylvania) and Eric Zitzewitz (Dartmouth College)

Read the previous blog posts by Chris. F. Masse:

• Why you should launch your brand-new prediction exchange at a conference
• Why Indian Software Outsourcing Companies are Outsourcing to China
• Midas Oracle is the only popular, independent, exhaustive, multi-author, multi-exchange, Web-based resource on prediction markets.
• Here’s an example of the total crap that the BetFair blog is publishing.
• P(election) = P(nomination) * P(election conditional on nomination)
• Journalism Failures — Big Time
• South Carolina showdown: Barack Obama vs. Hillary Clinton