Understanding the relationship between crime victimisation and mental health: a longitudinal analysis of population data

Being a victim of violent crime has a damaging effect on mental health, particularly for women, according to this report. The needs and experiences of victims of crime have become increasingly recognised as an important aspect of criminal justice and public policy. In Australia, victim support services grew from community-based organisations and lobby groups. With the passage of time, these services have become increasingly formalised, with the State progressively assuming a greater role in advocacy and service provision for victims of crime. While we know that many Australians will experience an incident of crime in their lifetime, the effect of this victimisation on health has not been sufficiently explored. This is unfortunate given the demand for victim support services; close to 6,000 applications for counselling assistance in 2011/12 were received by the Victims Compensation Tribunal, New South Wales. As such, it is timely to examine more closely the nature of the relationship between becoming a victim of crime and an individual’s subsequent mental health.   &nbsp

VLF, magnetic bay and Pi2 substorm signatures at auroral and midlatitude ground stations

A superposed epoch analysis of 100–300 substorms is performed to determine the median size and shape of the substorm-associated VLF chorus, magnetic bay, and Pi2 pulsation burst observed at the near-auroral Halley research station, Antarctica, and at the midlatitude Faraday station at three different local times (2230, 2330, 0130 MLT). The spatial and temporal properties of the magnetic bay signatures are compared with the University of York implementation of the Kisabeth–Rostoker substorm current wedge (SCW) model and the Weimer pulse model, respectively. These constitute the best analytical models of the substorm to date. It is shown that the polarities and relative amplitudes of the observed magnetic bays in the H, D, and Z components at Halley at midnight MLT and at Faraday in the premidnight sector are consistent with the York model for a SCW 3 hours wide in MLT with its westward electrojet at 67°S magnetic latitude. In particular the little-discussed Z component of the bay agrees with the model and is shown to be the clearest substorm signature of the three components, especially at midlatitude. The midnight and postmidnight bays are similar to the premidnight case but progressively smaller and cannot be fully reconciled with the model. The shape of the H and Z bays at Halley and the D bays at Faraday fit a normalized Weimer pulse well, with Weimer's 2 h−1 recovery rate, but the other components do not. The D component at Halley and H at Faraday do fit the Weimer pulse shape but with a faster recovery rate of 4 h−1. It is proposed that this is due to the effect of a decaying current in the SCW combining with the geometrical effect of changing SCW configuration and position relative to the observing station. The Z component at Faraday recovers more slowly than the 2 h−1 Weimer prediction; we cannot explain this. Secondary bays at Halley and Faraday show a clear tendency to recur after 2 hours. Inflection points just prior to onset at Halley and Faraday are argued to be related to reduced convection associated with northward turning of the IMF. The median substorm signature at Halley in the Pi2 frequency band (7–25 mHz) is well correlated with the bay structure, showing that it is part of a broader band, possibly turbulent, spectrum in the substorm-dependent DP2 current. There is evidence of a minor additional narrow band component occurring at substorm onset. This is the dominant signal at Faraday which shows the classic midlatitude substorm signature, a short Pi2 pulsation burst at onset, that decreases progressively in intensity with increasing local time, implying a source region biased to the evening side or else preferred propagation to the east from a near-midnight source

Determining military expenditures: arms races and spill-over effects in cross-section and panel data

This paper considers the determinants of military spending, building on an emerging literature that estimates military expenditure demand functions in cross-section and panel data, incorporating ‘arms-race’ type effects. It updates Dunne and Perlo-Freeman (2003b) using the SIPRI military expenditure database for the period 1988-2003, finding broadly similar results. It also shows differences in results across panel methods, particularly the within and between estimates and illustrates the importance of recognising and modelling dynamic processes within panel data. Heterogeneity is also found to be an important issue and when countries are broken up into groups on the basis of per capita income there is no obvious systematic pattern in the results. This is seen to imply that the demand for military spending, even between two mutually hostile powers, may depend on the whole nature of the relationship between them (and other countries and events in the region), and not simply Richardsonian action-reaction patterns

Determining Military Expenditures: Arms Races and Spill-Over Effects in Cross-Section and Panel Data

This paper considers the determinants of military spending, building on an emerging literature that estimates military expenditure demand functions in cross-section and panel data, incorporating ‘arms-race’ type effects. It updates Dunne and Perlo-Freeman (2003b) using the SIPRI military expenditure database for the period 1988-2003, finding broadly similar results. It also shows differences in results across panel methods, particularly the within and between estimates and illustrates the importance of recognising and modelling dynamic processes within panel data. Heterogeneity is also found to be an important issue and when countries are broken up into groups on the basis of per capita income there is no obvious systematic pattern in the results. This is seen to imply that the demand for military spending, even between two mutually hostile powers, may depend on the whole nature of the relationship between them (and other countries and events in the region), and not simply Richardsonian action-reaction patterns.Military Spending; Demand; Arms races; Spillovers; Panel data