A Linear Errors-in-Variables Model with Unknown Heteroscedastic Measurement Errors

In the classic measurement error framework, covariates are contaminated by independent additive noise. This paper considers parameter estimation in such a linear errors-in-variables model where the unknown measurement error distribution is heteroscedastic across observations. We propose a new generalized method of moment (GMM) estimator that combines a moment correction approach and a phase function-based approach. The former requires distributions to have four finite moments, while the latter relies on covariates having asymmetric distributions. The new estimator is shown to be consistent and asymptotically normal under appropriate regularity conditions. The asymptotic covariance of the estimator is derived, and the estimated standard error is computed using a fast bootstrap procedure. The GMM estimator is demonstrated to have strong finite sample performance in numerical studies, especially when the measurement errors follow non-Gaussian distributions

A new approach to function-based hypothesis testing in location-scale families

Motivated by two applications in the mining industry, we introduce a new approach to testing the hypothesis that two-sampled distributions are simply location and scale changes of one another. The test, applicable to both paired data and two-sample data, is based on the empirical characteristic function. More conventional techniques founded on the empirical distribution function suffer from serious drawbacks when used to test for location-scale families. In the motivating applications, knowing that the distributions differ only in location and scale has significant operational and economic advantages, enabling protocols for one type of data to be applied directly to another. Supplementary material in the form of Matlab code is available onlin

Police cynicism in Serbia: prevalence, nature and associations with job satisfaction

Purpose The purpose of this paper is to present the results of the first research on prevalence, nature and correlates of the police cynicism in Serbia, with particular attention to the associations of cynicism with job satisfaction. Design/methodology/approach Data were collected using a paper-based survey, and obtained from 472 police officers from five police departments across the country. For the purpose of measuring of organizational and work aspects of police cynicism a new developed 24 five-level Likert-type items scale was used. Findings The results show that cynicism is normally distributed. No statistically significant gender, education or police rank differences were identified, and the length of service does not appear to influence cynical attitudes significantly. Cynicism scores statistically significantly varied across police departments and predicted job dissatisfaction. The underlying four-factor structure of police cynicism was identified. The factors include: general organizational cynicism; cynicism toward police hierarchy/superiors; cynicism toward public/citizen cooperation; and cynicism toward modernization of policing in the crime control field. Research limitations/implications The generalizability of the sample is limited, giving that participants come from only five out of a total of 27 police departments in the country, while the female police officers and officers with education higher than high school were somewhat overrepresented. Originality/value This research provides some more evidence on the nature and determinants of police cynicism that might inspire future research in this important but under-researched area. It implies that the need to explore more deeply relations between police cynicism and stress, burnout and particularly contextual and departmental factors that might be influential to police cynicism. It might also incite future research on the internal structure of police cynicism