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**1 - 6**of**6**### unknown title

, 2008

"... R function swain Correcting structural equation model fit statistics and indexes under small-sample and/or large-model conditions ..."

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R function swain Correcting structural equation model fit statistics and indexes under small-sample and/or large-model conditions

### Correspondence should be addressed to:

"... This article is an elaboration of a paper presented at the 71st Annual Meeting of the ..."

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This article is an elaboration of a paper presented at the 71st Annual Meeting of the

### AN ASYMPTOTIC EXPANSION OF THE DISTRIBUTION OF THE DM TEST STATISTIC ∗

, 2009

"... This paper has three parts: theoretical results, simulations and an economic application. In the theoretical part, after the Distance Metric (DM) test statistic is expanded to the second order, the Edgeworth approximation of the distribution of the DM test statistic is derived and the Bartlett-type ..."

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This paper has three parts: theoretical results, simulations and an economic application. In the theoretical part, after the Distance Metric (DM) test statistic is expanded to the second order, the Edgeworth approximation of the distribution of the DM test statistic is derived and the Bartlett-type correction factor is obtained based on the results of Phillips and Park (1988) and Hansen (2006); in the simulation part, simple examples are given to illustrate the theoretical results; in the application part, the theoretical results are applied to study the covariance structures of earnings. JEL Classification: C12

### Bartlett-type Correction of Distance Metric Test∗

, 2012

"... We derive a corrected distance metric (DM) test of general restrictions. The correc-tion factor is a function of the uncorrected statistic, and the new statistic is Bartlett-type. In the setting of covariance structure models, we show using simulations that the quality of the new approximation is go ..."

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We derive a corrected distance metric (DM) test of general restrictions. The correc-tion factor is a function of the uncorrected statistic, and the new statistic is Bartlett-type. In the setting of covariance structure models, we show using simulations that the quality of the new approximation is good and often remarkably good. Especially at around the 95th percentile, the distribution of the corrected test statistic is strikingly close to the relevant asymptotic distribution. This is true for various sample sizes, distri-butions, and degrees of freedom of the model. As a by-product we provide an intuition for the well-known observation in labor economic applications that using longer panels results in a reversal of the original inference. JEL Classification: C12