The Influence of Federal Laboratory R&D on Industrial Research

Over the past 60 years the United States has created the world's largest system of government laboratories. The impact of the laboratories on the private economy has been little studied though their research accounts for 14% of total U.S. R&D, more than the R&D of all colleges and universities combined. In this paper we study the influence of federal laboratory R&D on industrial research using a sample of industrial laboratories. In head-to-head comparisons with alternative measures, we find that Cooperative Research and Development Agreements or CRADAs, are the primary channel by which federal laboratories increase the patenting and R&D of industrial laboratories. With a CRADA industrial laboratories patent more, spend more on company-financed R&D and spend more of their own money on federal laboratories. Without a CRADA patenting stays about the same and only federally funded R&D increases, mostly because of direct subsidies by government. These results are consistent with the literature on endogenous R&D spillovers, which emphasizes that knowledge spills over when recipients work at making it spill over. CRADAs are legal agreements between federal laboratories and firms to work together on joint research. They are backed by real budgets and accompanied by cost sharing that could bind the parties together in joint research. Moreover, the CRADA instrument is the main form of such agreements. Thus, both in theory and in fact CRADAs may be more beneficial to firms than other public- private interactions, precisely because of the mutual effort that they require of firms and government laboratories.

The Influence of Federal Laboratory R&D on Industrial Research

This paper studies the influence of R&D in the federal laboratory system, the world's largest, on firm research. Our results are based on a sample of 220 industrial research laboratories that work with a variety of federal laboratories and agencies and are owned by 115 firms in the chemicals, machinery, electrical equipment, and motor vehicles industries. Using an indicator of their importance to R&D managers, we find that Cooperative Research and Development Agreements or CRADAs dominate other channels of technology transfer from federal laboratories to firms. With a CRADA industry laboratories patent more, spend more on company-financed R&D, and devote more resources to their federal counterparts. Without this influence patenting stays about the same, and only federally funded R&D increases, mostly because of government support. The Stevenson-Wydler Act and amendments during the 1980s introduced CRADAs, which legally bind federal laboratories and firms together in joint research. In theory the agreements could capitalize on complementarities between public and private research. Our results support this perspective and suggest that CRADAs may be more beneficial to firms than other interactions with federal laboratories, precisely because of the mutual effort that they demand from both parties.

Controlling for performance capacity confounds in neuroimaging studies of conscious awareness

Studying the neural correlates of conscious awareness depends on a reliable comparison between activations associated with awareness and unawareness. One particularly difficult confound to remove is task performance capacity, i.e. the difference in performance between the conditions of interest. While ideally task performance capacity should be matched across different conditions, this is difficult to achieve experimentally. However, differences in performance could theoretically be corrected for mathematically. One such proposal is found in a recent paper by Lamy, Salti and Bar-Haim [Lamy D, Salti M, Bar-Haim Y. Neural correlates of subjective awareness and unconscious processing: an ERP study. J Cognitive Neurosci 2009,21:1435-46], who put forward a corrective method for an electroencephalography experiment. We argue that their analysis is essentially grounded in a version of High Threshold Theory, which has been shown to be inferior in general to Signal Detection Theory. We show through a series of computer simulations that their correction method only partially removes the influence of perfor- mance capacity, which can yield misleading results. We present a mathematical correction method based on Signal Detection Theory that is theoretically capable of removing performance capacity confounds. We discuss the limitations of mathemati- cally correcting for performance capacity confounds in imaging studies and its impact for theories about consciousness