The Effect of R&D Subsidies on Private R&D

TLDR: In this paper, the authors investigated the relationship between government support for R&D and expenditure financed privately by firms using a comprehensive plant level data set for the manufacturing sector in the Republic of Ireland.

Abstract: This paper investigates the relationship between government support for R&D and R&D expenditure financed privately by firms using a comprehensive plant level data set for the manufacturing sector in the Republic of Ireland. We find that for domestic plants small grants serve to increase private R&D spending, while too large a grant may crowd out private financing of R&D. In contrast, evidence for foreign establishments suggests that grant provision causes neither additionality nor crowding out effects of private R&D financing, regardless of the size of the subsidy.

Figures

Table 2 – Summary Statistics by Grant Categories

Table 4 – Regression Results of Effect of Subsidy on Private R&D Spending

Table 1: R&D Summary Statistics by Sector

Table 3 – Indicators of Matching Quality

Full text

Görg, Holger; Strobl, Eric
Working Paper
The effect of R&D subsidies on private R&D
Research Paper, No. 2005/38
Provided in Cooperation with:
Kiel Institute for the World Economy – Leibniz Center for Research on Global Economic
Challenges
Suggested Citation: Görg, Holger; Strobl, Eric (2005) : The effect of R&D subsidies on private
R&D, Research Paper, No. 2005/38, Leverhulme Centre for Research on Globalisation and
Economic Policy, University of Nottingham, Nottingham
This Version is available at:
http://hdl.handle.net/10419/3821
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research paper series
Globalisation, Productivity and Technology
Research Paper 2005/38
The Effect of R&D Subsidies on Private R&D
by
Holger Görg and Eric Strobl
The Centre acknowledges financial support from The Leverhulme Trust
under Programme Grant F114/BF

The Authors
Holger Görg is a Reader in International Economics in the School of Economics, University of
Nottingham and an Internal Research Fellow in GEP. Eric Strobl is Professor of Economics at
Ecole Polytechnique, Paris.
Acknowledgements
The authors are grateful to Forfás for the provision of the data. Financial support through the
Leverhulme Trust (Grant No. F114/BF) is gratefully acknowledged.

The Effect of R&D Subsidies on Private R&D
by
Holger Görg and Eric Strobl
Abstract
This paper investigates the relationship between government support for R&D and R&D
expenditure financed privately by firms using a comprehensive plant level data set for the
manufacturing sector in the Republic of Ireland. Our empirical strategy combines a non-
parametric matching procedure with a difference-in-differences estimator in order to deal with
the potential selection problem inherent in the analysis. We find that for domestic plants small
and medium sized grants serve to increase private R&D spending, particularly for the former
where it can induce R&D spending even beyond the subsidy, while too large a grant may crowd
out private financing of R&D. In contrast, evidence for foreign establishments suggests that
grant provision causes neither additionality nor crowding out effects of private R&D financing,
regardless of the size of the subsidy.
JEL classification: L2, H2, F2, O3
Keywords: research and development (R&D), subsidies, matching, difference-in-differences
Outline
1. Introduction
2. Grant Provision in Ireland
3. Data and preliminary empirics
4. Econometric methodology
5. Empirical results
6. Conclusion Remarks

Non-Technical Summary
Nowadays almost all OECD countries offer some sort of grants or subsidy schemes to encourage private
research and development (R&D) activity. As a matter of fact such incentives represent on average the
second highest form of support to industry. It is a priori not clear whether public support will be an
effective means to stimulate private R&D activity. Ideally, government subsidisation of R&D should invoke
what is commonly known as ‘additionality’ effects. Accordingly, an R&D subsidy may, by lowering private
costs, turn a previously unprofitable project into a profitable one or speed up the completion of a current
project and thereby encourage private R&D activity. Also, if it can reduce the fixed costs of other current
or potential projects by the creation or upgrading of research facilities, it may further stimulate the
spending on other non-subsidised R&D projects.
However, there is also the possibility that public funding will ‘crowd out’ private financing of R&D. Since it
is likely to be cheaper for firms to apply for a government grant than raise funds in the capital market,
some projects may be funded that would have been undertaken even without the receipt of government
support.
Whether additionality effects of government subsidies outweigh any crowding out of private R&D activity
in reality clearly requires an empirical investigation using appropriate data and estimation techniques.
One crucial issue in the empirical literature has been how to deal with the problem of what privately
financed R&D activity would have been without government support. Ideally, the researcher would want
to observe what would have happened to R&D activity in the firm if it had not received a subsidy. Clearly,
however, this is unobservable; one can only witness a funded firm’s actual expenditure and not what it
would have spent without a subsidy. This leaves as control group only those firms that were not
subsidised. The use of non-recipients as a comparison group, however, would only be justified if the
provision of grants were a completely random process, otherwise the analysis would suffer from selection
bias. In reality, of course, this is unlikely to be the case as authorities will select recipients among the pool
of candidates according to some selection criteria.
In this paper we re-examine the issue of whether government support stimulates or crowds out privately
financed R&D expenditure. In terms of methodological innovation, we contribute to the literature by
combining a non-parametric matching approach and the difference-in-differences estimator as suggested
by Blundell and Costa Dias (2000). The empirical analysis is carried out using a large and extensive
panel data set of manufacturing plants in the Republic of Ireland. Ireland arguably presents a good case
study in that it has implemented an extensive policy of directly supporting industry, in particular with
regard to technology intensive activity. The data set provides us with exhaustive information on plants’
receipts of grants for R&D purposes.
Our results suggest that for domestic plants while grant provision at a small or medium scale does not
`crowd out ’ private spending, and in the case of small amounts may even create additionality effects, too
large grants may act to finance R&D activity that would have been taking place anyway. In contrast, we
find that there is no evidence of such additionality or crowding out effects for foreign multinationals
regardless of grant amount size.

Frequently asked questions

Q1. What have the authors contributed in "The effect of r&d subsidies on private r&d" ?

This paper investigates the relationship between government support for R & D and R & D expenditure financed privately by firms using a comprehensive plant level data set for the manufacturing sector in the Republic of Ireland. Their empirical strategy combines a nonparametric matching procedure with a difference-in-differences estimator in order to deal with the potential selection problem inherent in the analysis. The authors find that for domestic plants small and medium sized grants serve to increase private R & D spending, particularly for the former where it can induce R & D spending even beyond the subsidy, while too large a grant may crowd out private financing of R & D. In contrast, evidence for foreign establishments suggests that grant provision causes neither additionality nor crowding out effects of private R & D financing, regardless of the size of the subsidy. 

Q2. What is the information available from this source that is relevant to the current paper?

The information available from this source that is relevant to the current paper are the nationality of ownership, sector of production, output, employment, exports, wages, total and domestically purchased inputs, and total R&D expenditure. 

Q3. What is the important sector in Irish manufacturing?

Of the three most important sectors in Irish manufacturing, i.e., Chemicals, Food, and Metals and Engineering, only Metals and Engineering is characterised by above average R&D activity. 

Q4. What is the main concern with the estimations so far?

One possible concern with the estimations thus far may be that, given that ourdependent variables is in logged levels, their results even after matching could be driven by the possibility that larger plants spend more of their own money on R&D and are also more likely to receive a grant. 

Q5. What is the PSM’s appeal in addressing the ‘common support’ problem?

Despite its appeal in addressing the ‘common support’ problem, the PSM estimatorstill crucially rests on the conditional independence assumption. 

Q6. What is the main problem of the DID estimator?

A second weakness of the DID estimator is that it does not guarantee that, in terms of observables, similar plants are being compared since OLS estimation implicitly assumes a linear effect across any range of7values of a covariate. 

Q7. How many non-recipients were able to match?

15 In doing so, from a total amount of 5422 non-recipients, 321 small grant recipient, 317 medium grant recipient, and 318 large grant recipient observations were able to match 381, 118, 171, and 168 observations, respectively. 

Q8. What is the main argument for the use of multinationals in the Irish economy?

A large literature now argues that multinationals can serve as an important stimulus to the domestic sector by enabling technology spillovers; see, for instance, Görg and Strobl (2001). 

Q9. How did the authors determine the effect of the grant on the performance of the non-recipient?

In order to ensure that the lower performance of the matched pairs involving non-recipients was indeed due to their dominance in these pooled samples, the authors thus also experimented with using random samples of 317 observations from the non-recipient group in the relevant pooled samples. 

Q10. What is the measure of grant intensity in the furniture and wood and wood products sectors?

Here one finds that while grant provision is still high in the Furniture and Wood and Wood Products sectors and relatively low in the Chemicals and Drink and Tobacco sectors, the measure of grant intensity is sensitive to the choice of denominator. 

Q11. How many employees are in the sample?

One should note that by linking information across data sources their sample consists of plants of generally at least 10 employees. 

Q12. What is the pseudo R-squared of the same probits?

For instance, as can be seen the pseudo R-squared of running the same probits with only the matched sample is considerably lower in all cases except where non-grant receipt is used as the treatment group.