We provide a methodology for testing a polynomial model hypothesis by extending the approach and results of Baek, Cho, and Phillips (2015; Journal of Econometrics; BCP) that tests for neglected nonlinearity using power transforms of regressors against arbitrary nonlinearity. We examine and...

The paper develops an asymptotically valid F test that is robust to spatial autocorrelation in a GMM framework. The test is based on the class of series covariance matrix estimators and fixed-smoothing asymptotics. The fixed-smoothing asymptotics and F approximation are established under mild...

I derive a rigorous method to help determine whether a true parameter takes a value between two arbitrarily chosen points for a given level of confidence via a multiple testing procedure which strongly controls the familywise error rate. For any test size, the distance between the upper and...

Inference using large datasets is not nearly as straightforward as conventional econometric theory suggests when the disturbances are clustered, even with very small intra-cluster correlations. The information contained in such a dataset grows much more slowly with the sample size than it would...

The paper proposes a new algorithm for finding the confidence set of a collection of forecasts or prediction models. Existing numerical implementations for finding the confidence set use an elimination approach where one starts with the full collection of models and successively eliminates the...

The paper is a keynote lecture from the Tilburg-Madrid Conference on Hypothesis Tests: Foundations and Applications at the Universidad Nacional de Educación a Distancia (UNED) Madrid, Spain, 15-16 December 2011. It addresses the role of tests of statistical hypotheses (specification tests) in...

The replicability and credibility crisis in psychology and economics sparked the debate on underpowered experiments, publication biases, and p-hacking. Analyzing the number of independent observations of experiments published in Experimental Economics, Games and Economic Behavior, and the...

In this paper we address a challenging aspect that arises in the regulatory requirement of back-testing the accuracy of distributional forecasts. The latter are core to measurement and capitalization of counterparty risk for banks under the IMM (Internal Models Method). The problem is very...

The problem of determining the probability model (distribution) that generates observed data commonly arises in econometrics, decision making under ambiguity, robust control, and allied fields. We develop novel procedures that use the Hellinger distance to distinguish distributions based on...

Permutation techniques, where one recompute the test statistic over permutations of data, have a long history in statistics and have become increasingly useful as the availability of computational power has increased. Until now, no permutation tests for examining returns to scale assumptions,...