Testing data for conformity to Benford's law is used not only by auditors exploiting a numerical phenomenon to detect fraudulently reported data. Operationally goodness-of-fit tests are used to conclude if data that should, does indeed comply with Benford's law. Naturally, not all statistical...

In simple static linear simultaneous equation models the empirical distributions of IV and OLS are examined under alternative sampling schemes and compared with their first-order asymptotic approximations. We demonstrate that the limiting distribution of consistent IV is not affected by...

Item response theory is one of the modern test theories with applications in educational and psychological testing. Recent developments made it possible to characterize some desired properties in terms of a collection of manifest ones, so that hypothesis tests on these traits can, in principle,...

Item response theory is one of the modern test theories with applications in educational and psychological testing. Recent developments made it possible to characterize some desired properties in terms of a collection of manifest ones, so that hypothesis tests on these traits can, in principle,...

This note discusses some problems possibly arising when approximating via MonteCarlo simulations the distributions of goodness-of-fit test statistics based on the empirical distribution function. We argue that failing to reestimate unknown parameters on each simulated Monte-Carlo sample - and...

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

We develop theory of a novel fast bootstrap for dependent data. Our scheme deploys i.i.d. resampling of smoothed moment indicators. We characterize the class of parametric and semiparametric estimation problems for which the method is valid. We show the asymptotic re refinements of the new...

We propose new scoring rules based on partial likelihood for assessing the relative out-of-sample predictive accuracy of competing density forecasts over a specific region of interest, such as the left tail in financial risk management. By construction, existing scoring rules based on weighted...

In this paper we study the finite sample behavior of the Hill estimator under α-stable distributions. Using large Monte Carlo simulations we show that the Hill estimator overestimates the true tail exponent and can hardly be used on samples with small length. Utilizing our results, we introduce...