Summary of Mitchell v. Clark County Sch. Dist., 121 Nev. Adv. Op. 21

Julie Mitchell, a Clark County classroom teacher, inexplicably fell down a flight of stairs while at work. The Court held that stairs, in and of themselves, and other things that are not peculiar to the employment environment, are not sufficiently dangerous to be the cause of a workers’ compensation claim

A Heteroskedasticity Robust Breusch-Pagan Test for Contemporaneous Correlation in Dynamic Panel Data Models

This paper proposes a heteroskedasticity-robust Breusch–Pagan test of the null hypothesis of zero cross-section (or contemporaneous) correlation in linear panel data models, without necessarily assuming independence of the cross-sections. The procedure allows for either fixed, strictly exogenous and/or lagged dependent regressor variables, as well as quite general forms of both non-normality and heteroskedasticity in the error distribution. The asymptotic validity of the test procedure is predicated on the number of time series observations, T, being large relative to the number of cross-section units, N, in that: either (i) N is fixed as T→∞; or, (ii) N 2/T→0 as both T and N diverge, jointly, to infinity. Given this, it is not expected that asymptotic theory would necessarily provide an adequate guide to finite sample performance when T/N is “small”. Because of this we also propose, and establish asymptotic validity of, a number of wild bootstrap schemes designed to provide improved inference when T/N is small. Across a variety of experimental designs, a Monte Carlo study suggests that the predictions from asymptotic theory do, in fact, provide a good guide to the finite sample behaviour of the test when T is large relative to N. However, when T and N are of similar orders of magnitude, discrepancies between the nominal and empirical significance levels occur as predicted by the first-order asymptotic analysis. On the other hand, for all the experimental designs, the proposed wild bootstrap approximations do improve agreement between nominal and empirical significance levels, when T/N is small, with a recursive-design wild bootstrap scheme performing best, in general, and providing quite close agreement between the nominal and empirical significance levels of the test even when T and N are of similar size. Moreover, in comparison with the wild bootstrap “version” of the original Breusch–Pagan test (Godfrey and Yamagata, 2011) our experiments indicate that the corresponding version of the heteroskedasticity-robust Breusch–Pagan test appears reliable. As an illustration, the proposed tests are applied to a dynamic growth model for a panel of 20 OECD countries

A heteroskedasticity robust Breusch-Pagan test for contemporaneous correlation in dynamic panel data models

Working paper dated August 16, 2011This paper proposes a heteroskedasticity-robust Breusch-Pagan test of the null hypothesis of zero cross-section (or contemporaneous) correlation in linear panel data models. The procedure allows for either xed, strictly exogenous and/or lagged de- pendent regressor variables, as well as quite general forms of both non-normality and heteroskedasticity in the error distribution. Whilst the asymptotic validity of the test procedure, under the null, is predicated on the number of time series observations, T, being large relative to the number of cross-section units, N, independence of the cross-sections is not assumed. Across a variety of experimental designs, a Monte Carlo study suggests that, in general (but not always), the predictions from asymptotic the- ory provide a good guide to the finite sample behaviour of the test. In particular, with skewed errors and/or when N=T is not small, discrepancies can occur. However, for all the experimental designs, any one of three asymptotically valid wild bootstrap approximations (that are considered in this paper) gives very close agreement between the nominal and empirical signi cance levels of the test. Moreover, in comparison with wild bootstrap version of the original Breusch-Pagan test (Godfrey and Yamagata, 2011) the corresponding version of the heteroskedasticity-robust Breusch-Pagan test is more reliable. As an illustration, the proposed tests are applied to a dynamic growth model for a panel of 20 OECD countries

Analysis of a Train-operating Company’s Customer Service System during Disruptions:Conceptual Requirements for Gamifying Frontline Staff Development

This paper provides an account of an action research study into the systemic success factors which help frontline staff react to and recover from a rail service disruption. This study focuses on the effective use of information during a disruption to improve customer service, as this is a priority area for train-operating companies (TOCs) in Great Britain. A novel type of systems thinking, known as Process-Oriented Holonic Modelling (PrOH), has been used to investigate and model the ‘Passenger Information During Disruption’ (PIDD) system. This paper presents conceptual requirements for a gamified learning environment; it describes ‘what’; ‘how’ and ‘when’ these systemic success factors could be gamified using a popular disruption management reference framework known as the Mitigate, Prepare, React and Recover (MPRR) framework. This paper will interest managers of and researchers into customer service system disruptions, as well as those wishing to develop new gamified learning environments to improve customer service systems

First-order asymptotic theory for parametric misspecification tests of Garch models

publication-status: Publishedtypes: ArticleFinal version of the article as published in Econometric Theory, vol. 35, issue 2, pp. 364-410. Copyright © Cambridge University Press 2009. Available online at http://journals.cambridge.org/This paper develops a framework for the construction and analysis of parametric misspecification tests for generalized autoregressive conditional heteroskedastic (GARCH) models, based on first-order asymptotic theory. The principal finding is that estimation effects from the correct specification of the conditional mean (regression) function can be asymptotically nonnegligible. This implies that certain procedures, such as the asymmetry tests of Engle and No. (1993, Journal of Finance 48. 1749-1777) and the nonlinearity test of Lundbergh and Terasvirta (2002, Journal of Econometrics 110, 417-435), are asymptotically invalid. A second contribution is the proposed use of alternative tests for asymmetry and/or nonlinearity that, it is conjectured, should enjoy improved power properties. A Monte Carlo study supports the principal theoretical findings and also suggests that the new tests have fairly good size and very good power properties when compared with the Engle and Ng (1993) and Lundbergh and Terasvirta (2002) procedures

Phylogenetic non-independence in rates of trait evolution

Statistical non-independence of species’ biological traits is recognized in most traits under selection. Yet, whether or not the evolutionary rates of such biological traits are statistically non-independent remains to be tested. Here we test the hypothesis that phenotypic evolutionary rates are non-independent, i.e. contain phylogenetic signal, using empirical rates of evolution in three separate traits: body mass in mammals; beak shape in birds; and bite force in amniotes. Specifically, we test whether rates are non-independent throughout the evolutionary history of each tree. We find evidence for phylogenetic signal in evolutionary rates in all three case studies. While phylogenetic signal diminishes deeper in time, this is reflective of statistical power owing to small sample and effect sizes. When effect size is large, e.g., owing to the presence of fossil tips, we detect high phylogenetic signals even in deeper time slices. Thus, we recommend that rates be treated as being non-independent throughout the evolutionary history of the group of organisms under study, and any summaries or analyses of rates through time – including associations of rates with traits – need account for the undesired effects of shared ancestry

Changes in electric-field noise due to thermal transformation of a surface ion trap

We aim to illuminate how the microscopic properties of a metal surface map to its electric-field noise characteristics. In our system, prolonged heat treatments of a metal film can induce a rise in the magnitude of the electric-field noise generated by the surface of that film. We refer to this heat-induced rise in noise magnitude as a thermal transformation. The underlying physics of this thermal transformation process is explored through a series of heating, milling, and electron treatments performed on a single surface ion trap. Between these treatments, $^{40}$Ca$^+$ ions trapped 70 $\mu$m above the surface of the metal are used as detectors to monitor the electric-field noise at frequencies close to 1 MHz. An Auger spectrometer is used to track changes in the composition of the contaminated metal surface. With these tools we investigate contaminant deposition, chemical reactions, and atomic restructuring as possible drivers of thermal transformations. The data suggest that the observed thermal transformations can be explained by atomic restructuring at the trap surface. We hypothesize that a rise in local atomic order increases surface electric-field noise in this system