
Contents
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22.1 Background 22.1 Background
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22.2 Formulation of the statistical system 22.2 Formulation of the statistical system
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22.3 The conditional model 22.3 The conditional model
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22.4 The test procedure 22.4 The test procedure
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22.5 Monte Carlo evidence on null rejection frequencies 22.5 Monte Carlo evidence on null rejection frequencies
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22.6 Non-null rejection frequency 22.6 Non-null rejection frequency
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22.7 Simulating the potency of the super-exogeneity test 22.7 Simulating the potency of the super-exogeneity test
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22.7.1 Level shift in marginal: no weak exogeneity 22.7.1 Level shift in marginal: no weak exogeneity
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22.8 Power of the optimal infeasible test 22.8 Power of the optimal infeasible test
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22.9 Testing exogeneity in DHSY 22.9 Testing exogeneity in DHSY
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22.10 IIS and economic interpretations 22.10 IIS and economic interpretations
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Cite
Abstract
An automatically computable test is described, with null rejection frequencies that are close to the nominal size, and potency for failures of super exogeneity. Impulse-indicator saturation is undertaken in the marginal models of the putative exogenous variables that enter the conditional model contemporaneously, and all significant outcomes are recorded. These indicators from the marginal models are added to the conditional model and tested for significance. Under the null of super exogeneity, the test has the correct gauge for a range of sizes of marginal-model saturation tests, both when those processes are constant, and when they undergo shifts in either mean or variance. Failures of super exogeneity from a violation of weak exogeneity are shown to be detectable when there are location shifts in the marginal models. The distribution and potency of the test are derived and simulated, with an application to testing super exogeneity for UK consumers’ expenditure.
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