Lag Length Selection for Unit Root Tests in the Presence of Nonstationary Volatility

A number of recent papers have focused on the problem of testing for a unit root in the case where the driving shocks may be unconditionally heteroskedastic. These papers have, however, taken the lag length in the unit root test regression to be a deterministic function of the sample size, rather than data-determined, the latter being standard empirical practice. We investigate the finite sample impact of unconditional heteroskedasticity on conventional data-dependent lag selection methods in augmented Dickey–Fuller type regressions and propose new lag selection criteria which allow for unconditional heteroskedasticity. Standard lag selection methods are shown to have a tendency to over-fit the lag order under heteroskedasticity, resulting in significant power losses in the (wild bootstrap implementation of the) augmented Dickey–Fuller tests under the alternative. The proposed new lag selection criteria are shown to avoid this problem yet deliver unit root tests with almost identical finite sample properties as the corresponding tests based on conventional lag selection when the shocks are homoskedastic.     

Buffon's needle and the estimation of migration distances

A procedure is suggested for estimating migration distances from data on the proportion of migrants crossing regional boundaries. The method makes use of Buffon's needle, a problem in geometrical probability from the eighteenth century that was originally used as an empirical means of estimating π. The procedure is described for various scenarios that differ in their assumptions about region shape, the spatial distribution of population, and the distribution of migration distances. An application to migration distances in the United States is given, and additional attention is given to the estimation of intraregional migration distances.     

The Temporal Structure of Scientific Consensus Formation

This article engages with problems that are usually opaque: What trajectories do scientific debates assume, when does a scientific community consider a proposition to be a fact, and how can we know that? We develop a strategy for evaluating the state of scientific contestation on issues. The analysis builds from Latour's black box imagery, which we observe in scientific citation networks. We show that as consensus forms, the importance of internal divisions to the overall network structure declines. We consider substantive cases that are now considered facts, such as the carcinogenicity of smoking and the non-carcinogenicity of coffee. We then employ the same analysis to currently contested cases: the suspected carcinogenicity of cellular phones, and the relationship between vaccines and autism. Extracting meaning from the internal structure of scientific knowledge carves a niche for renewed sociological commentary on science, revealing a typology of trajectories that scientific propositions may experience en route to consensus.     

Some principles for surveillance adopted for multivariate processes with a common change point

The surveillance of multivariate processes has received growing attention during the last decade. Several generalizations of well-known methods such as Shewhart, CUSUM and EWMA charts have been proposed. Many of these multivariate procedures are based on a univariate summarized statistic of the multivariate observations, usually the likelihood ratio statistic. In this paper we consider the surveillance of multivariate observation processes for a shift between two fully specified alternatives. The effect of the dimension reduction using likelihood ratio statistics are discussed in the context of sufficiency properties. Also, an example of the loss of efficiency when not using the univariate sufficient statistic is given. Furthermore, a likelihood ratio method, the LR method, for constructing surveillance procedures is suggested for multivariate surveillance situations. It is shown to produce univariate surveillance procedures based on the sufficient likelihood ratios. As the LR procedure has several optimality properties in the univariate, it is also used here as a benchmark for comparisons between multivariate surveillance procedures     

Running hard to stand still: Communication and information technology within social work training

Recent years have seen rapid technological changes and these have impacted on social work and social work education. Social work educators struggle to keep pace with these changes. Drawing on the author's own experience, this article outlines some key resources that are available to social work educators and students, reflects on the role of 'Communication and Information Technology' within the social work curriculum, and looks towards future developments in relation to online learning.