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Subsidizing research programs with “if” and “when” uncertainty in the face of severe informational constraints
Author(s) -
Besanko David,
Tong Jian,
Wu Jason Jianjun
Publication year - 2018
Publication title -
the rand journal of economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.687
H-Index - 108
eISSN - 1756-2171
pISSN - 0741-6261
DOI - 10.1111/1756-2171.12227
Subject(s) - subsidy , monopoly , competition (biology) , shadow (psychology) , investment (military) , economics , matching (statistics) , microeconomics , shadow price , government (linguistics) , face (sociological concept) , welfare , public economics , deadweight loss , market economy , politics , political science , psychology , ecology , mathematical optimization , linguistics , statistics , philosophy , social science , mathematics , sociology , law , psychotherapist , biology
We study subsidy policies for research programs when firms have private information about the likelihood of project viability, but the government cannot form a unique prior about this likelihood. When the shadow cost of public funds is zero, first‐best welfare can be attained as a (belief‐free) ex post equilibrium under both monopoly and competition, but it cannot be attained when the shadow cost is positive. However, max‐min subsidy policies exist under monopoly and competition and consist of pure matching subsidies. Under a Research and Development (R&D) consortium, the highest max‐min matching rate is lower than under competition, and R&D investment intensity is higher.