To facilitate crossing from the "black box" to "glass box" in the application of neural net- works, we extend Horel and Giesecke (2020) and develop a variable/feature significant test for multi-layer perceptrons (MLP). The proposed test permits one to assess the statistical significance of the...

This paper extends the analysis of infinite dimensional vector autoregressive models (IVAR) proposed in Chudik and Pesaran (2010) to the case where one of the variables or the cross section units in the IVAR model is dominant or pervasive. This extension is not straightforward and involves...

Economists sometimes interpret the failure of a significance test to disconfirm a hypothesis as evidence that this hypothesis is valid. Six examples of this are cited from recent journals. But this is a misinterpretation of what significance tests show. While in general it is correct that every...

This paper proposes nonparametric consistent tests of conditional stochastic dominance of arbitrary order in a dynamic setting. The novelty of these tests lies in the nonparametric manner of incorporating the information set into the test. The test allows for general forms of unknown serial and...

This paper proposes nonparametric consistent tests of conditional stochastic dominance of arbitrary order in a dynamic setting. The novelty of these tests resides on the nonparametric manner of incorporating the information set into the test. The test allows for general forms of unknown serial...

We propose a new specification test to assess the validity of the judge leniency design. We characterize a set of sharp testable implications, which exploit all the relevant information in the observed data distribution to detect violations of the judge leniency design assumptions. The proposed...

We derive distribution free tests based on the Maximum Entropy densities to test the null hypotheses of symmetry and normality. The proposed tests are derived from maximizing the differential entropy subject to moment constraints. By exploiting the equivalence between Maximum Entropy and Maximum...