15,605 research outputs found
The knowledge-based software assistant
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
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
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Inferring informal risk-sharing regimes: Evidence from rural Tanzania
This paper studies informal risk-sharing regimes in a unified framework by examining intertemporal consumption behavior of rural households in Tanzania. We exploit a theoretically-consistent link between interest rates and cross-sectional consumption moments to test alternative risk-sharing models without requiring data on interest rates or assuming a restriction to eliminate the need for such data, which are often unavailable in developing economies. We specify tests that allow us to distinguish among models even with temporal dependence in income shocks. Our analysis shows that the consumption pattern in rural Tanzania is consistent with the self-insurance regime, and that risk aversion varies substantially across districts. Imposing a strict condition on interest rates, as often done in prior literature, misses their intertemporal heterogeneity and biases the estimation of risk aversion
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Inferring Informal Risk-Sharing Regimes: Evidence from Rural Tanzania
This paper studies informal risk-sharing regimes in a unified framework by examining intertemporal consumption behavior of rural households in Tanzania. We exploit a theoretically-consistent link between interest rates and cross-sectional consumption moments to test alternative risk-sharing models without requiring data on interest rates or assuming a restriction to eliminate the need for such data, which are often unavailable in developing economies. We specify tests that allow us to distinguish among models even with temporal dependence in income shocks. Our analysis shows that the consumption pattern in rural Tanzania is consistent with the self-insurance regime, and that risk aversion varies substantially across districts. Imposing a strict condition on interest rates, as often done in prior literature, misses their intertemporal heterogeneity and biases the estimation of risk aversion
Finance, Human Capital, Technical Assistance, and the Business Environment in Romania
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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