15,605 research outputs found

    The knowledge-based software assistant

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    Where the Knowledge Based Software Assistant (KBSA) is now, four years after the initial report, is discussed. Also described is what the Rome Air Development Center expects at the end of the first contract iteration. What the second and third contract iterations will look like are characterized

    Relaxation Penalties and Priors for Plausible Modeling of Nonidentified Bias Sources

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    In designed experiments and surveys, known laws or design feat ures provide checks on the most relevant aspects of a model and identify the target parameters. In contrast, in most observational studies in the health and social sciences, the primary study data do not identify and may not even bound target parameters. Discrepancies between target and analogous identified parameters (biases) are then of paramount concern, which forces a major shift in modeling strategies. Conventional approaches are based on conditional testing of equality constraints, which correspond to implausible point-mass priors. When these constraints are not identified by available data, however, no such testing is possible. In response, implausible constraints can be relaxed into penalty functions derived from plausible prior distributions. The resulting models can be fit within familiar full or partial likelihood frameworks. The absence of identification renders all analyses part of a sensitivity analysis. In this view, results from single models are merely examples of what might be plausibly inferred. Nonetheless, just one plausible inference may suffice to demonstrate inherent limitations of the data. Points are illustrated with misclassified data from a study of sudden infant death syndrome. Extensions to confounding, selection bias and more complex data structures are outlined.Comment: Published in at http://dx.doi.org/10.1214/09-STS291 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

    Finance, Human Capital, Technical Assistance, and the Business Environment in Romania

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    Although the development of a new private sector is generally considered crucial to economic transition and development, there has been little empirical research on the determinants of startup firm growth. This paper uses panel data techniques to analyze a survey of 297 new small enterprises in Romania containing detailed information from the startup date through 2001. We find strong evidence that access to external finance (loans) increases the growth of both employment and sales. Taxes appear to constrain growth. There is some evidence that entrepreneurial skills increase growth, but only weak evidence for the effectiveness of technical assistance, and only when it is provided by foreign partners or international agencies. A wide variety of alternative measures of the business environment (contract enforcement, property rights, and corruption) are tested, but are found to have little or no association with firm growth.http://deepblue.lib.umich.edu/bitstream/2027.42/40025/3/wp639.pd
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