State property systems and orthogonality

The structure of a state property system was introduced to formalize in a complete way the operational content of the Geneva-Brussels approach to the foundations of quantum mechanics, and the category of state property systems was proven to be equivalence to the category of closure spaces. The first axioms of standard quantum axiomatics (state determination and atomisticity) have been shown to be equivalent to the $T_0$ and $T_1$ axioms of closure spaces, and classical properties to correspond to clopen sets, leading to a decomposition theorem into classical and purely nonclassical components for a general state property system. The concept of orthogonality, very important for quantum axiomatics, had however not yet been introduced within the formal scheme of the state property system. In this paper we introduce orthogonality in a operational way, and define ortho state property systems. Birkhoff's well known biorthogonal construction gives rise to an orthoclosure and we study the relation between this orthoclosure and the operational orthogonality that we introduced.Comment: 10 pages, 2 figures, proceeding of the IQSA 2002 conference in Vienn

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

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