Many time series in diverse fields have been found to exhibit long memory. This paper analyzes the behavior of some of the most used tests for long memory: the R/S or rescaled R/S, the GPH (Geweke and Porter-Hudak) and the DFA (Detrended Fluctuation Analysis). Some of these tests exhibit size...

This paper proposes Lagrange Multiplier based panel unit root tests allowing for structural breaks through simple extensions of existing group mean and combination tests. The proposed tests are more general than those previously suggested. They consider potential breaks in the intercept, in the...

In this paper, I examine the properties of the class of generalized empirical likelihood estimators of moment-condition models. These nonparametric likelihood estimators satisfy exactly the moment conditions and automatically remove any bias due to a lack of centering. Moreover, the bias of the...

We propose new approaches to test for spanning in the return and stochastic discount factor mean-variance frontiers, which assess if either the centred or uncentred mean and cost representing portfolios are shared by the initial and extended sets of assets. We show that our proposed tests are...

This paper considers two models to deal with an outcome variable that contains a large fraction of zeros, such as individual expenditures on health care: a sample-selection model and a two-part model. The sample-selection model uses two possibly correlated processes to determine the outcome: a...

This paper shows how a high level matrix programming language may be used to perform Monte Carlo simulation, bootstrapping, estimation by maximum likelihood and GMM, and kernel regression in parallel on symmetric multiprocessor computers or clusters of workstations. The implementation of...

The performance of Monte Carlo integration methods like importance-sampling or Markov-Chain Monte-Carlo procedures depends greatly on the choice of the importance- or candidate-density. Such a density must typically be "close" to the target density to yield numerically accurate results with...