Testing for Differences in Stochastic Network Structure

Testing for Stochastic Non- Linearity in the Rational Expectations Permanent Income Hypothesis

The Rational Expectations Permanent Income Hypothesis implies that consumption follows a martingale. However, most empirical tests have rejected the hypothesis. Those empirical tests are based on linear models. If the data generating process is non-linear, conventional tests may not assess some of the randomness properly. As a result, inference based on conventional tests of linear models can b...

Symmetric Error Structure in Stochastic DEA

Stochastic Techniques in Influence Diagrams for Learning Bayesian Network Structure

The problem of learning Bayesian network structure is well known to be NP–hard. It is therefore very important to develop efficient approximation techniques. We introduce an algorithm that within the framework of influence diagrams translates the structure learning problem into the strategy optimisation problem, for which we apply the Chen’s self–annealing stochastic optimisation algorithm. The...

Testing for stochastic monotonicity

We propose a test of the hypothesis of stochastic monotonicity. This hypothesis is of interest in many applications in economics. Our test is based on the supremum of a rescaled U-statistic. We show that its asymptotic distribution is Gumbel. The proof is difficult because the approximating Gaussian stochastic process contains both a stationary and a nonstationary part and so we have to extend ...

The Testing Paradigm Applied to Network Structure

The testing paradigm provides a simple framework for comparing networks of processes. To apply the testing paradigm, one needs a suite of tests and a test criterion expressing when a network passes a test. Two networks are considered testing equivalent when they pass the same tests. In all applications of the testing paradigm that we have seen, tests “probe” (some of) the behavior of the proces...