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Consistent Specification Testing With Nuisance Parameters Present Only Under The Alternative
, 1995
"... . 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 ex ..."
Abstract

Cited by 55 (10 self)
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. 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 bears closely on recent developments in artificial neural networks. Statistical content is provided by viewing specification tests with nuisance parameters as tests of hypotheses about Banachvalued random elements and applying the Banach Central Limit Theorem and Law of Iterated Logarithm, leading to simple procedures that can be used as a guide to when computationally more elaborate procedures may be warranted. 1. Introduction In testing whether or not a parametric statistical model is correctly specified, there are a number of apparently distinct approaches one might take. T...
The Econometric Consequences of The Ceteris Paribus Condition in Economic Theory
 Journal of Econometrics
, 2000
"... The ceteris paribus condition in economic theory assumes that the world outside the environment described by the theoretical model does not change, so that it has no impact on the economic phenomena under review. In this paper, we examine the econometric consequences of the ceteris paribus assumptio ..."
Abstract

Cited by 3 (2 self)
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The ceteris paribus condition in economic theory assumes that the world outside the environment described by the theoretical model does not change, so that it has no impact on the economic phenomena under review. In this paper, we examine the econometric consequences of the ceteris paribus assumption by introducing a ”state of theworld”variableintoawellspecified stochastic economic theory, and we show that the difference between the conditional distribution implied by the theoretical model and the actual conditional distribution of the data is due to different ways of conditioning on the state of the world. We allow the ”state of the world ” variable to be, alternatively and equivalently, an index variable representing omitted variables, or a discrete random parameter representing a sequence of models. We construct a probability that can be interpreted as the upperbound of the probability that the ceteris paribus condition is correct. The estimated upperbound can in turn be interpreted as a measure of the information about the datagenerating process that is provided by a theoretical model which is constrained by a set of ceteris paribus assumptions. In order to illustrate our findings from both a theoretical and an empirical perspective, we examine a linearized version of the real business cycle model proposed by King, Plosser, and Rebello (1988b).