Evaluation of Public R&D Policy: A Meta-Regression Analysis

Syoum Negassi and Jean-François Sattin (jean-francois.sattin@univ-paris1.fr)
Additional contact information
Syoum Negassi: UP1 - Université Paris 1 Panthéon-Sorbonne, PRISM Sorbonne - Pôle de recherche interdisciplinaire en sciences du management - UP1 - Université Paris 1 Panthéon-Sorbonne
Jean-François Sattin: UP1 - Université Paris 1 Panthéon-Sorbonne, PRISM Sorbonne - Pôle de recherche interdisciplinaire en sciences du management - UP1 - Université Paris 1 Panthéon-Sorbonne

Post-Print from HAL

Abstract: Economic theory and empirical evidence indicate that technological innovation is an important determinant of long-term economic development. Various country policies have been launched in favour of private research and development (R&D) with economic development as the main objective. As often in economics, public intervention is grounded on the presumed existence of market failures. The purpose of this paper is two-fold. First, it provides an overview of the history of R&D-related tax policies in more than ten industrial countries. Second, after reviewing the existent empirical evidence on the effectiveness of R&D tax credits policies, it presents a meta-regression analysis based on an econometric model. Our results show that an R&D tax credit is strongly significant in the studies taken cumulatively.

Keywords: R&D; Meta-Analysis (search for similar items in EconPapers)
Date: 2019
References: Add references at CitEc
Citations:

Published in Technology and Investment, 2019, 10 (01), pp.1-29. ⟨10.4236/ti.2019.101001⟩

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04012341

DOI: 10.4236/ti.2019.101001

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD (hal@ccsd.cnrs.fr).