1998
DOI: 10.1017/s0266466698143013
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Consistent Specification Testing With Nuisance Parameters Present Only Under the Alternative

Abstract: The nonparametric and the nuisance parameter approaches to consistently testing statistical models are both attempts to estimate topological measures of distance between a parametric and a nonparametric fit, and neither dominates in experiments. This topological unification allows us to greatly extend the nuisance parameter approach. How and why the nuisance parameter approach works and how it can be extended bear closely on recent developments in artificial neural networks. Statistical content is prov… Show more

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Cited by 275 publications
(188 citation statements)
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“…This is accomplished by constructing conditional moment tests which employ an infinite number of moment conditions (see e.g. Bierens (1982Bierens ( ,1990, Ploberger (1997), de Jong (1996), Hansen (1996a), Lee, Granger and White (1993) and Stinchcombe and White (1998), Corradi and Swanson (2002)). …”
Section: The Frameworkmentioning
confidence: 99%
“…This is accomplished by constructing conditional moment tests which employ an infinite number of moment conditions (see e.g. Bierens (1982Bierens ( ,1990, Ploberger (1997), de Jong (1996), Hansen (1996a), Lee, Granger and White (1993) and Stinchcombe and White (1998), Corradi and Swanson (2002)). …”
Section: The Frameworkmentioning
confidence: 99%
“…R +1 may be used instead (Bierens 1990). Stinchcombe and White (1998) provide the only detailed explanation for Bierens' seminal result by proving (2) for any real analytic 1 non-polynomial  (), where  0   is a¢ne (i.e. a constant term must be included) and  is bounded.…”
Section: An Interior Point Of ©mentioning
confidence: 99%
“…Elegant solutions to this problem have been proposed in the literature on specification testing, and we shall in particular follow here the approach of Stinchcombe and White (1998). The key idea is simple: an element m ∈ L 1 (G) is equal to zero, m = 0 a.s., if and only if for every…”
Section: Existence Using Strong Cramér Conditionmentioning
confidence: 99%