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We provide a new definition of breakdown in finite samples with an extension to asymptotic breakdown. Previous definitions center around defining a critical region for either the parameter or the objective function. If for a particular outlier constellation the critical region is entered,...
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This paper proposes new, simple, and more accurate statistical tests in a cointegrated system that allows for endogenous regressors and serially dependent errors. The approach involves first transforming the time series using some orthonormal basis functions in L2[0,1], which has energy...
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A Bayesian semi-parametric estimation of the binary response model using Markov Chain Monte Carlo algorithms is proposed. The performances of the parametric and semi-parametric models are presented. The mean squared errors, receiver operating characteristic curve, and the marginal effect are...
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We consider Bayesian inference by importance sampling when the likelihood is analytically intractable but can be … unbiasedly estimated. We refer to this procedure as importance sampling squared (IS2), as we can often estimate the likelihood … itself by importance sampling. We provide a formal justification for importance sampling when working with an estimate of the …
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We consider fixed-smoothing asymptotics for the Diebold and Mariano (1995) test of predictive accuracy. We show that this approach delivers predictive accuracy tests that are correctly sized even when only a small number of out of sample observations are available. We apply the fixed-smoothing...
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