R&D subsidies and foreign ownership: Carrying Flemish coals to Newcastle?.

R&D subsidies; R&D expenditure; innovative performance; economic value creation; foreign ownership; multinational; policy evaluation; semi-parametric matching;

Who writes the pay slip? Do R&D subsidies merely increase researcher wages?.

Government intervention in private R&D activity is common practice nowadays. However, its impact may not be unambiguously positive. First, companies may simply replace private R&D budgets with the public R&D grant. Second, even if an increase in private R&D investment is confirmed, it may not automatically induce more R&D output: the additional R&D budget may be crowded out by duplicate or more risky research, or a mere increase in researcher wages. This paper empirically analyzes the effect of public R&D subsidies on private R&D investments, employment and wages in Flanders, using a parametric treatment effects models on the funding status as well as IV regression models on the amount of funding. Positive additionality effects are supported, measured in terms of R&D expenditure, employment and wages. However, partial crowding out cannot be rejected.R&D subsidies; R&D expenditure; R&D employment; R&D wages; policy evaluation; treatment effects model; IV model;

Two for the price of one? On additionality effects of R&D subsidies: A comparison between Flanders and Germany

In this paper we empirically test whether public R&D subsidies crowd out private R&D investment in Flanders and Germany, using firm level data from the Flemish and German part of the Community Innovation survey (CIS III and IV). Both the non-parametric matching estimator and the conditional difference-in-difference estimator with repeated cross-sections (CDiDRCS) clearly indicate that the crowding-out hypothesis can be rejected: funded firms are significantly more R&D active than non-funded firms. In the domain of additionality effects of R&D subsidies, this paper is the first to apply the CDiDRCS method. --R&D,Subsidies,Policy Evaluation,Conditional Difference-in-Difference

Profit sharing and innovation.

profit sharing; product innovation; process innovation; non-parametric matching; conditional difference-in-differences;

Additionality effects of public R&D funding: ‘R’ versus ‘D’.

Several studies have already addressed the question whether R&D subsidies lead to additionality effects or crowd out firms’ private investment. This paper provides insights into the impact of R&D grants on private R&D expenditure, distinguishing between research and development activities. We employ parametric treatment effects models and IV regression methods. The hypothesis that firms respond differently to R&D subsidies depending on the nature of the R&D activity is confirmed. R&D subsidies are found to mainly contribute to an increase in development expenditure. By contrast, crowding out effects for the research part cannot be rejected.R&D subsidies; R&D expenditure; research; development; policy evaluation; treatment effects model; IV model;

Using Innovation Survey Data to Evaluate R&D Policy: The Case of Belgium

This study focuses on the impact of R&D policies in Flanders. We conduct a treatment effects analysis at the firm level to investigate possible crowdingout effects on the input side of the innovation process. Different specifications of R&D activity are considered as outcome variables in the treatment effects analysis. Applying a non-parametric matching, we conclude that subsidized firms would have invested significantly less in R&D activities, on average, if they had not received public R&D funding. Thus, crowding-out effects can be rejected in this case. --R&D,Subsidies,Policy Evaluation,Non-parametric matching

Critical role and screening practices of European business incubators.

Business incubators guide starting enterprises through their growth process and as such constitute a strong instrument to promote innovation and entrepreneurship. In this article we sketch the European business incubator landscape. Then we describe screening practices by European business incubators in 2003 and compare these results with the American incubators in the eighties. In the last phase a cautious link between screening practices and performance, measured in terms of tenant failure, is established. Most incubators do not screen potential tenants on a balanced set of factors, but concentrate either on the characteristics of the tenant's market or on the characteristics of the tenant's management team. However, we found that the tenant survival rate is positively related to a more balanced screening profile. Based on our study results, we propose some recommendations for the main stakeholders in the field: authorities, incubators and innovative entrepreneurs.Characteristics; Entrepreneurs; Factors; Field; Growth; Innovation; Management; Market; Performance; Processes; Recommendations; Research; Stakeholders; Studies;

Using Innovation Survey Data to Evaluate R&D Policy: The Case of Belgium

This study focuses on the impact of R&D policies in Flanders. We conduct a treatment effects analysis at the firm level to investigate possible crowdingout effects on the input side of the innovation process. Different specifications of R&D activity are considered as outcome variables in the treatment effects analysis. Applying a non-parametric matching, we conclude that subsidized firms would have invested significantly less in R&D activities, on average, if they had not received public R&D funding. Thus, crowding-out effects can be rejected in this case

Two for the price of one? On additionality effects of R&D subsidies: a comparison between Flanders and Germany

In this paper we empirically test whether public R&D subsidies crowd out private R&D investment in Flanders and Germany, using firm level data from the Flemish and German part of the Community Innovation survey (CIS III and IV). Both the non-parametric matching estimator and the conditional difference-in-difference estimator with repeated cross-sections (CDiDRCS) clearly indicate that the crowding-out hypothesis can be rejected: funded firms are significantly more R&D active than non-funded firms. In the domain of additionality effects of R&D subsidies, this paper is the first to apply the CDiDRCS method