R&D tax credits and subsidies: implications for innovation novelty in emerging economies
File(s)
Published version
Author(s)
Demirel, Pelin
Kesidou, Effie
Wu, Lichao
Type
Journal Article
Abstract
The impact of different policy instruments and policy mixes on innovation novelty remains unclear, particularly in emerging economies. This study contributes to the literature by examining the context-specific associations between innovation policies and different magnitudes of novelty in innovation outcomes. Our findings suggest that exposure to R&D tax credits is associated with increases in innovations that can be considered both as relatively more novel and less novel, in line with the market conforming design R&D tax credits that mimic firms' existing R&D portfolios. Conversely, R&D subsidies, often characterised by ‘picking the winners’, are mainly associated with relatively less novel innovation outcomes. We further show that policy mixes that involve R&D subsidies are more likely to support relatively less novel, domestic innovations. Building on Sanjaya Lall's technological capability approach, we propose a conceptualization of incremental innovation and argue that R&D subsidies should not be viewed merely as a misallocation of resources toward relatively less novel innovations at the expense of more novel alternatives. Instead, they should be seen as a context-specific policy mechanism for enabling emerging economies to build and accumulate the technological capabilities necessary for innovation. We empirically test these hypotheses using a unique longitudinal dataset (2013−2021) of 4162 publicly traded firms in China and estimate conditional treatment effects using a propensity score matching method. Our results underscore the nuanced and context-specific effects of R&D tax credits and subsidies on innovation novelty, offering new insights for innovation policy in emerging economies.
Date Issued
2026-09-01
Date Acceptance
2026-04-29
Citation
Technological Forecasting and Social Change, 2026, 230
ISSN
0040-1625
Publisher
Elsevier BV
Journal / Book Title
Technological Forecasting and Social Change
Volume
230
Copyright Statement
© 2026 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
License URL
Publication Status
Published
Article Number
124729
Date Publish Online
2026-05-15