This paper is a substantially revised version of our earlier working paper, "Truth and Robustness in Cross-country Growth Regressions." The most important revisions concern the handling of missing observations in the cross-country data set. In the earlier paper, these had been handled through...

This paper presents two new tools for the identification of faking interviewers in surveys. One method is based on Benford?s Law, and the other exploits the empirical observation that fakers most often produce answers with less variability than could be expected from the whole survey. We focus...

Various noninformative prior distributions have been suggested for scale parameters in hierarchical models. We construct a new folded-noncentral- t family of conditionally conjugate priors for hierarchical standard deviation parameters, and then consider noninformative and weakly informative...

In this paper, the Partial Distribution (PD) and multivariate Partial Distribution (MPD) are presented in their concepts, properties and applications, and PD is compared with the lognormal and the levy distribution. Though the levy distribution is better to describe the exchange returns in...

One approach to analyzing inequality is to compare average economic choices from a classical theoretical framework. Another approach considers the impact of the formation of society, through statutes and institutions, on average economic outcomes. This paper studies the effects of slavery on...

Reproducibility is an absolute necessity in experimental sciences. In fact, the randomness of scientific findings based on P-values, that are the vast majority, should be taken into account. When a significance threshold α is fixed, the outcome of the test has a Bernoullian nature, i.e. is in...

Particle Markov Chain Monte Carlo (PMCMC) is a widely used method to handle estimation problem in the context of nonlinear structural dynamic models whose likelihood function is analytically intractable. PMCMC can be constructed upon a GMM likelihood representation when one does not want to rely...

Particle Markov Chain Monte Carlo (PMCMC) is a widely used method to handle estimation problem in the context of nonlinear structural dynamic models whose likelihood function is analytically intractable. PMCMC can be constructed upon a GMM likelihood representation when one does not want to rely...

This paper proposes a predictive maintenance policy using modified failure mode effect and criticality analysis (Mod-FMECA) technique. FMECA is used to identify failure modes, reasons, effects and criticality of the system (machine/plant) but in Mod-FMECA in addition to the analysis carried for...