【主讲】周俊杰 助教授 (上海财经大学国际工商管理学院)
【主题】Are Information-gathering and Producing Complements or Substitutes?
【时间】2014年3月25日 (周二) 15：30-17：00
【地点】上海财经大学经济学院楼710室
【语言】英文
【摘要】We aim at some simple theoretical underpinnings for the study of a complex empirical question studied by labor economists and others: does Information-technology improvement lead to occupational shifts | toward information workers" and away from other occupations | and to changes in the productivity of non-information workers? In our simple model there is a Producer, whose payoff depends on a production quantity and an unknown state of the world, and an Information-gatherer (IG) who expends e ffort to learn more about the unknown state. The IG's eff ort yields a signal which is conveyed to the Producer. The Producer uses the signal to revise prior beliefs about the state and uses the posterior to make an expected-payo ff-maximizing quantity choice. Our central aim is to nd conditions on the IG and the Producer under which more IG eff ort leads to a larger average production quantity (Complements) and conditions under which it leads to a smaller average quantity (Substitutes). For each of the IG's possible e fforts there is an information structure, which specfies a signal distribution for every state and (for a given prior) a posterior state distribution for every signal. We start by considering a Blackwell IG. For such an IG, the possible structures can be ranked so that a higher-ranking structure is more useful to every Producer, no matter what the prior and the payo function may be. For the Blackwell IGs whom we consider, a higher-ranking structure is reasonably interpreted as a higher-e ffort structure. The Blackwell theorems state that one structure ranks above another if and only if the expected value (over the possible signals) of any convex function on the posteriors is not less for the higher-ranked structure. So we have Complements (Substitutes) if the Producer's best quantity is indeed a convex (concave) function of the posteriors. That gives us Complements/Substitutes results for a variety of Producers. We then turn to a non-Blackwell IG who partitions the state set into n equalprobability intervals. The IG can choose any positive integer n and n is the e ort measure. We recapture some of the results from the Blackwell-IG case, but far di erent techniques are needed, since the Blackwell theorems cannot be used. This is a joint work with Thomas Marschak,and George Shanthikumar.
