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结构变化检验的自助法AI 解读

This paper demonstrates the asymptotic validity of methods based on the wild recursive and wild fixed bootstraps for testing hypotheses about discrete parameter change in linear models estimated via Two Stage Least Squares. The framework allows for the errors to exhibit conditional and/or unconditional heteroscedasticity, and for the reduced form to be unstable. Simulation evidence indicates the bootstrap tests yield reliable inferences in the sample sizes often encountered…

变换前后矩的联系及其在厚尾分布重抽样中的应用AI 解读

Let x be a transformation of y , whose distribution is unknown. We derive an expansion formulating the expectations of x in terms of the expectations of y . Apart from the intrinsic interest in such a fundamental relation, our results can be applied to calculating E( x ) by the low-order moments of a transformation which can be chosen to give a good approximation for E( x ). To do so, we generalize the approach of bounding the terms in expansions of characteristic functions,…

美国通胀动态中的行为异质性AI 解读

In this article we develop and estimate a behavioral model of inflation dynamics with heterogeneous firms. In our stylized framework there are two groups of price setters, fundamentalists and random walk believers. Fundamentalists are forward-looking in the sense that they believe in a present-value relationship between inflation and real marginal costs, while random walk believers are backward-looking, using the simplest rule of thumb, naive expectations, to forecast…

厚尾分布的参数 bootstrapAI 解读

It is known that Efron’s bootstrap of the mean of a distribution in the domain of attraction of the stable laws with infinite variance is not consistent, in the sense that the limiting distribution of the bootstrap mean is not the same as the limiting distribution of the mean from the real sample. Moreover, the limiting bootstrap distribution is random and unknown. The conventional remedy for this problem, at least asymptotically, is either the m out of n bootstrap or…