Abstract: Consider a mechanism design setting in which agents acquire costly informa- tion about an unknown, payoff-relevant state of nature. Information gathering is covert. We investigate conditions under which (i) efficient implementation and (ii) full surplus extraction are Bayesian incentive compatible and interim individually rational. This is joint work with Ichiro Obara. This paper can be found at http://www.anderson.ucla.edu/x996.xml Bio: Professor Bikhchandani has been at UCLA Anderson since 1985. He is interested in auctions, market institutions, herd behavior and information economics. Dr. Bikhchandani currently teaches Data and Decisions in the MBA core and a Ph.D. course on decision theory. He was vice chair of UCLA Anderson in 1997-98 and was director of the Doctoral Program from 1999 to 2003.