Principle-agent theory suggests managers might under-invest into R&D for reasons of risk tied to project failure, such as reduced remuneration and job loss. However, managers might over-invest into innovation for reasons of growth implying higher remuneration, power and prestige. Using a sample...

We develop a simple model of competition for the market that shows that, contrary to the Arrow view, endogenous entry threat in a market induces the average firm to invest less in R&D and the incumbent leader to invest more. We test these predictions with a Tobit model based on a unique dataset...

This paper tests for the sensitivity of R&D to financing constraints conditional on restrictions in external financing. Financing constraints of firms are identified by an exogenously calculated rating index. Restrictions in external financing are determined by (i) the specific time period...

This paper discusses theoretically the different incentives of managers versus firm owners to invest in innovative activities. There are opposing effects concerning R&D intensity in the manager-controlled firm. Our study on the determinants of R&D intensity presents empirical results concerning...

Principle-agent theory suggests managers might under-invest into R&D for reasons of risk tied to project failure, such as reduced remuneration and job loss. However, managers might over-invest into innovation for reasons of growth implying higher remuneration, power and prestige. Using a sample...

Principle-agent theory suggests managers might under-invest into R&D for reasons of risk tied to project failure, such as reduced remuneration and job loss. However, managers might over-invest into innovation for reasons of growth implying higher remuneration, power and prestige. Using a sample...

We develop a simple model of competition for the market that shows that, contrary to the Arrow view, endogenous entry threat in a market induces the average firm to invest less in R&D and the incumbent leader to invest more. We test these predictions with a Tobit model based on a unique dataset...