2 resultados para Bootstrap reality check

em University of Connecticut - USA


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Alexander's Dictum--"to be is to have causal powers"--appears to furnish an argument against the reality of familiar medium-sized objects. For every time a familiar object appears to cause a familiar macro-event, it sets up a rival claim by its component microparticles to have caused the complex swarm of microphysical events that composes into that macro-event. But this argument, argues this paper, wrongly assumes that even after familiar objects are removed from the picture, there is a phenomenon of joint causation which unites all and only the microparticles within each familiar object.

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The Data Envelopment Analysis (DEA) efficiency score obtained for an individual firm is a point estimate without any confidence interval around it. In recent years, researchers have resorted to bootstrapping in order to generate empirical distributions of efficiency scores. This procedure assumes that all firms have the same probability of getting an efficiency score from any specified interval within the [0,1] range. We propose a bootstrap procedure that empirically generates the conditional distribution of efficiency for each individual firm given systematic factors that influence its efficiency. Instead of resampling directly from the pooled DEA scores, we first regress these scores on a set of explanatory variables not included at the DEA stage and bootstrap the residuals from this regression. These pseudo-efficiency scores incorporate the systematic effects of unit-specific factors along with the contribution of the randomly drawn residual. Data from the U.S. airline industry are utilized in an empirical application.