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Effectiveness of fiscal incentives for innovation: Evidence from meta‐regression analysis
Author(s) -
Jose Manu,
Sharma Ruchi
Publication year - 2021
Publication title -
journal of public affairs
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.221
H-Index - 20
eISSN - 1479-1854
pISSN - 1472-3891
DOI - 10.1002/pa.2146
Subject(s) - additionality , subsidy , endogeneity , economics , incentive , government (linguistics) , empirical evidence , meta regression , public economics , meta analysis , econometrics , microeconomics , medicine , linguistics , philosophy , epistemology , market economy
This article examines the microeconometric evidence on the impact of government support for R&D and innovation. Our meta‐regression analysis uses a dataset of empirical evidence on the effects of government R&D policies on innovation and investigates the factors that may explain the differences in the estimated effects. The meta‐analysis is structured to include both the direct and indirect government support for R&D and innovation. The estimated results reveal the heterogeneity of empirical studies with respect to the type of incentive, data, and econometric methodology used. The results indicate that the output additionality effect is on average stronger for R&D tax incentives than subsidies. Studies that use the subsample of high technology sector show a stronger additionality effect of fiscal incentives on innovation. Moreover, small and medium enterprises have a stronger input additionality effect. The results also suggest that studies considered endogeneity issues have on average stronger additionality effect.