Does more information-gathering effort raise or lower the average quantity produced?

Thomas Marschak, J. George Shanthikumar and Junjie Zhou

Journal of Mathematical Economics, 2017, vol. 69, issue C, 104-117

Abstract: We aim at some simple theoretical underpinnings for 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 effort to learn more about the unknown state and then sends the Producer a signal. The Producer responds by revising prior beliefs about the states and using the posterior to make an expected-payoff-maximizing quantity choice. We consider a variety of IGs and variety of Producers. For each IG there is a natural effort measure. Our central aim is to find conditions under which more IG effort leads to a larger average production quantity (“Complements”) and conditions under which it leads to a smaller average quantity (“Substitutes”). We start by considering Blackwell IGs, who meet the strong conditions required in the Blackwell theorems about the comparison of experiments. We then turn to non-Blackwell IGs, where the Blackwell theorems cannot be used and special techniques are needed to obtain Complements/Substitutes results.

Keywords: Information technology and productivity; Blackwell theorems; Garbling (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:mateco:v:69:y:2017:i:c:p:104-117

DOI: 10.1016/j.jmateco.2017.01.004

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