In this paper, new noncausality tests built on a general nonlinear framework are proposed and their performance studied by a Monte Carlo experiment and a variety of nonlinear artificial series. Two of these test are based on a Taylor expansion of the nonlinear model around a given point in a sample space. Another test is based on artifitical neural networkd. The test appear to be well-sized and have good power properties.
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Paper provided by Universite Aix-Marseille III in its series G.R.E.Q.A.M. with number
99a42.
Length: 22 pages Date of creation: 1999 Date of revision: Handle: RePEc:fth:aixmeq:99a42
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Find related papers by JEL classification: C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
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