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连续时间模型中的非因果性AI 解读

In this paper, we study new definitions of noncausality, set in a continuous time framework, illustrated by the intuitive example of stochastic volatility models. Then, we define CIMA processes (i.e., processes admitting a continuous time invertible moving average representation), for which canonical representations and sufficient conditions of invertibility are given. We can provide for those CIMA processes parametric characterizations of noncausality relations as well as…

间接推断AI 解读

In this paper we present inference methods which are based on an 'incorrect' criterion, in the sense that the optimization of this criterion does not directly provide a consistent estimator of the parameter of interest. Moreover, the argument of the criterion, called the auxiliary parameter, may have a larger dimension than that of the parameter of interest. A second step, based on simulations, provides a consistent and asymptotically normal estimator of the parameter of…

共同根检验AI 解读

In this paper, the authors propose a simple procedure for testing the existence of common roots in lag polynomials. They first show, by using a generalized Bezout property, that this hypothesis can be put under a "mixed" form that is linear with respect to the auxiliary parameters and with respect to the initial parameters. It follows that the test procedures can be implemented only by using regressions packages. Copyright 1989 by The Econometric Society.