We propose a class of new robust GMM tests for endogenous structural breaks. The tests are based on supremum, average and exponential functionals derived from robust GMM estimators with bounded influence function. We study the theoretical local robustness properties of the new tests and show...

We analyze Granger causality testing in a mixed-frequency VAR, where the difference in sampling frequencies of the variables is large. Given a realistic sample size, the number of high-frequency observations per low-frequency period leads to parameter proliferation problems in case we attempt to...

The empirical likelihood ratio (ELR) test for the problem of testing for normality is derived in this paper. The sampling properties of the ELR test and four other commonly used tests are provided and analyzed using the Monte Carlo simulation technique. The power comparisons against a wide range...

We propose an easily implementable test of the validity of a set of theoretical restrictions on the relationship between economic variables, which do not necessarily identify the data generating process. The restrictions can be derived from any model of interactions, allowing censoring and...

This paper compares recently developed semiparametric estimators of Type-3 Tobit model using Monte Carlo simulations. In particular, we examine the finite sample performance of the recently proposed method by Li and Wooldridge and compare it to some alternative semiparametric estimators....

The main goal of this paper is to better understand the behavior of credit spreads in the past and the potential risk of unexpected future credit spread changes. One important consideration to note regarding credit spreads is the fact that bond spreads contain a liquidity premium, which...

Markov chain Monte Carlo (MCMC) methods have an important role in solving high dimensionality stochastic problems characterized by computational complexity. Given their critical importance, there is need for network and security risk management research to relate the MCMC quantitative...

This working paper contains facts and introductory concepts about Markov Chain Monte Carlo (MCMC) methods and algorithms. The aim is to provide the reader with a general introduction to the MCMC framework

This paper is a solution to a problem that was put forward by Pandit(2002). The problem is to increase the reliability of a system, which, depends on a set of components connected in series. The increment can be done, by connecting to each of the components, similar components in parallel under...

A method to price American-style option contracts in a limited information framework is introduced. The pricing methodology is based on sequential Monte Carlo techniques, as presented in Doucet, de Freitas, and Gordon's text "Sequential Monte Carlo Methods in Practice", and the least-squares...