Bootstrapping the Information Matrix Test

Bootstrapping the Information Matrix Test

In this paper we provide considerable Monte Carlo evidence on the finite sample performance of several alternative forms of White’s [1982] IM test. Using linear regression and probit models, we extend the range of previous analysis in a manner that reveals new patterns in the behavior of the asymptotic version of the IM test – particularly with respect to curse of dimensionality effects. We als...

Bootstrapping the Conditional Moment Test for Parametric Duration Models

This letter evaluates the performance of auxiliary regression-based specification tests for parametric duration models estimated with censored data. The test using asymptotic critical values has poor size. Bootstrapping corrects the size problem but results in a biased power curve.

Assessing Individual Change Without Knowing the Test Properties: Item Bootstrapping

Assessing significant change (or reliable change) in a person often involve comparing the responses of that person in two administrations of a test or scale. Several procedures have been proposed to determine if a difference between two observed scores is statistically significant or rather is within the range of mere random fluctuations due to measurement error. Application of those procedures...

Bootstrapping the Hausman Test in Panel Data Models

The Hausman test statistic in panel data models is asymptotically pivotal under the null hypothesis. It could therefore be refined using the bootstrap resampling technique. Edgeworth expansion shows that coverage of a bootstrap version of the Hausman test is second-order correct. The asymptotic vis-à-vis the bootstrap version of Hausman test are compared by Monte Carlo simulations. Results show...

Secure Information Flow in Mobile Bootstrapping Process