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B02: Strategic information disclosure

In many situations, agents need to rely on information that is strategically influenced by interested parties. The focus of this project lies on determining the economic forces that shape the strategic disclosure of information and, in particular, its dynamics. In the second funding period, we want to study this problem with a particular focus on questions related to R&D. Indeed, adequately understanding and regulating R&D is fundamental in modern societies. Unlike other economic activities, R&D investments impose positive and negative externalities, dynamically change the structure of markets, and increase the information asymmetry between economic agents. We will build on the output of the first funding period to study the efficiency of the outcome of some R&D activities and the corresponding policy implications. To this end, we will explore a number of different channels through which strategic disclosure and dynamic information transmission affect R&D activities and their outcomes.

First, we examine the effects that the endogenous adverse selection generated by R&D investments has on trade. We investigate how the endogenous gains from trade, the observability of the investment, or the competitiveness of the market, affect the incentives to invest in and disclose R&D activities, the trade probability and delay, and the resulting social welfare.

Second, we study team incentives to contribute to R&D projects, particularly in environments in which direct monetary transfers are not available. We view R&D as a creative process in teams that relies on agents disclosing new content to each other. We examine how competition and organizational design features such as team size and team composition affect incentives to share information and resulting R&D outcomes.

Third, we investigate the role of uncertainty in R&D. The standard approach in the literature is to capture expected R&D outcomes in terms of risk, yet, in many cases, e.g., in fundamental research, these outcomes are inherently uncertain. Therefore, a new focus of the project is the question of how agents process investment-relevant information and act upon it when R&D outcomes cannot be captured by a Bayesian framework. To answer this question, we will introduce dynamic models of ambiguity to the literature of R&D and study the implications of robust decision rules on R&D investments and the adoption and disclosure of new technologies.


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