Knowledge that Transforms

An experiment analyzing behavior in English common value auctions is reported. English auctions raise more revenue than first-price auctions only when bidders do not suffer from a strong winner's curse. Agents employ other bidders' dropout prices along with their private information as Nash bidding theory predicts. However, a simple and natural signal-averaging rule, that does not require recognizing the adverse-selection effect of winning the auction, better characterizes the data than the Nash rule. Monte Carlo simulations using FIML estimates of the signal-averaging rule predict a number of data characteristics not directly employed in the estimation procedure.

Monetary policy makers are uncertain about the state of the economy and learn from the economy's reaction to policy. Private agents, however, anticipate any systematic attempt to incorporate this information into future policy. We analyze this feedback in the context of a monetary authority's attempt to stimulate an economy in recession. We show that modest stimuli may prove ineffectual. If small reductions in interest rates are unlikely to promote a response, then they may be followed by further cuts. A vicious circle develops in which the expectation that the policy could fail leads investors to delay investment thereby promoting failure.