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Purpose – Driver education and licensing are two mechanisms used to reduce crash rates. The purpose of this chapter is to provide an overview of these countermeasures and consider how simulators can be used to augment more traditional approaches.

Approach – A literature review was undertaken evaluating key concepts in driver licensing including graduated driver licensing (GDL), the role of parents in licensing, compliance and enforcement, driver testing and how the driver licensing system impacts on levels of unlicensed driving. Literature regarding driver education for individuals who have and not yet obtained a licence was also reviewed.

Findings – GDL is a successful countermeasure for reducing the crash rates of young novice drivers as it limits their exposure to higher risk situations. The support for driver education initiatives is mixed. As there are big differences between education programs, there is a need to consider each program on its own merits. Driving simulators provide a safe environment for novices to gain experience. In particular, they may be bifacial for development of hazard perception and visual scanning skills.

Practical Implications – GDL systems should be introduced where appropriate. Existing systems should be strengthened where possible by including additional, best-practice and restrictions. When considering driver education as a countermeasure, the type of program is very important. Education programs that have been shown to increase crashes should not be introduced. Further research and development are necessary to ensure that driver education and licensing adequately equip novice drivers with the skills necessary to drive in the 21st century.

Drawing upon the Traffic Safety Culture (TSC) perspective, this chapter outlines the reinforcing and transforming functions of advertising and illustrates such approaches by drawing upon examples from Australian road safety advertising campaigns. The argument put forth is that road safety advertising can be a robust tool; it can reinforce other countermeasures (enforcement) as well as transform community expectations and values and thus ultimately contribute to social as well as behavioral change.

In the context of Dynamic Factor Models, we compare point and interval estimates of the underlying unobserved factors extracted using small- and big-data procedures. Our paper differs from previous works in the related literature in several ways. First, we focus on factor extraction rather than on prediction of a given variable in the system. Second, the comparisons are carried out by implementing the procedures considered to the same data. Third, we are interested not only on point estimates but also on confidence intervals for the factors. Based on a simulated system and the macroeconomic data set popularized by Stock and Watson (2012), we show that, for a given procedure, factor estimates based on different cross-sectional dimensions are highly correlated. On the other hand, given the cross-sectional dimension, the maximum likelihood Kalman filter and smoother factor estimates are highly correlated with those obtained using hybrid procedures. The PC estimates are somehow less correlated. Finally, the PC intervals based on asymptotic approximations are unrealistically tiny.

This chapter explores religion and spirituality as a form and source of demographic differences relevant to the study of occupational stress and well-being. The purpose of the chapter is to provide a resource and starting point to occupational health and stress researchers who may be interested in religion/spirituality. A review of critical religion/spirituality concepts is provided, along with a discussion of how religion/spirituality can be integrated into common occupational stress theories and reconciled with commonly studied variables within this domain. A series of future research directions involving religion/spirituality and occupational health and stress are ultimately presented.

This article provides an overview of the panel vector autoregressive models (VAR) used in macroeconomics and finance to study the dynamic relationships between heterogeneous assets, households, firms, sectors, and countries. We discuss what their distinctive features are, what they are used for, and how they can be derived from economic theory. We also describe how they are estimated and how shock identification is performed. We compare panel VAR models to other approaches used in the literature to estimate dynamic models involving heterogeneous units. Finally, we show how structural time variation can be dealt with.

Disaster responders play a crucial role in providing aid to individuals and communities following catastrophic events. Being tasked to protect and preserve life and property, these groups of professionals are constantly exposed to various hazards, which puts them at risk of negative mental health consequences. This chapter describes and discusses these mental health effects and interventions for disaster responders in Southeast Asia. The chapter defines who the disaster responders are in Southeast Asian countries. Drawing from the literature, this chapter enumerates the various positive and negative psychological consequences of disaster response, and the risk and protective factors associated with disaster response work. This chapter also describes the different interventions, such as psychological first aid and psychotherapy, following the Inter-agency Standing Committee (IASC) (2007) guidelines on conducting mental health and psychosocial support services (MHPSS), and focusing on the Southeast Asian context. This chapter ends with a discussion of the different challenges of providing MHPSS in Southeast Asia and with some recommendations on how to improve the delivery of these services and the mental health of disaster responders in general.

Since 1934, the federal government has provided a process for municipalities to declare bankruptcy, and approximately 500 governments have done so. In recent years, an average of less than one city government declares bankruptcy each year. In this article, the authors identify five factors that contribute to financial distress for cities which, if left unattended, can lead to municipal bankruptcy. This discussion is followed by an examination of the events that led to the bankruptcy of the City of Prichard, Alabama, once a prosperous suburb of Mobile. The authors conclude that this municipal bankruptcy occurred, in large part, because Prichard failed to face the factors of financial distress identified by the authors in the years prior to filing for bankruptcy.

Several official institutions (NBER, OECD, CEPR, and others) provide business cycle chronologies with lags ranging from three months to several years. In this paper, we propose a Markov-switching dynamic factor model that allows for a more timely estimation of turning points. We apply one-step and two-step estimation approaches to French data and compare their performance. One-step maximum likelihood estimation is confined to relatively small data sets, whereas two-step approach that uses principal components can accommodate much bigger information sets. We find that both methods give qualitatively similar results and agree with the OECD dating of recessions on a sample of monthly data covering the period 1993–2014. The two-step method is more precise in determining the beginnings and ends of recessions as given by the OECD. Both methods indicate additional downturns in the French economy that were too short to enter the OECD chronology.

An annual citizen survey can be a valuable component of the municipal budgeting process for cities that elect to institutionalize the process as a way to translate citizen feedback into budgetary priorities. This article explores uses of citizen surveys in identifying latent needs of the community that may not be detected through public hearings or other citizen participation methods. The authors suggest that properly developed and conducted citizen surveys can provide decision-makers with research data that will lead to more responsive public spending and debt financing decisions. The article concludes with a case study of Auburn, Alabama, a city that has successfully used citizen surveys in its budgeting system for the past seventeen years.

This paper attempts to resolve the conflicting results on sticky cost behavior in prior literature. Large sample studies find that selling, general, and administrative costs (SG&A) and cost of goods sold (CGS) are sticky, that is, costs are less likely to decrease when activity decreases than to increase when activity increases. In contrast, studies limited to one industry find little or no sticky cost behavior.

We investigate whether SG&A and CGS sticky cost behavior differ across/ four major industry groups (manufacturing, merchandising, financial, and services) characterized by different production, operational, and economic environments. In addition, we study whether sticky cost behavior arises for all changes in activity level (as measured by revenue changes) or for only large changes in activity level. Finally, we investigate whether determinants of sticky cost behavior vary across industries.

Our results suggest that costs in the manufacturing industry are the “stickiest,” while costs in the merchandising industry are the “least sticky,” with financial and service industries exhibiting some level of sticky cost behavior. Further, we find that sticky cost behavior is industry-specific, both in the magnitude of activity changes that give rise to sticky cost behavior and in the determinants that drive the behavior.

Our investigation of 20 distinct sub-industries within the “stickiest” manufacturing industry finds that while some sub-industry groupings show significant sticky behavior, most do not. This result may explain why, contrary to large sample studies, single industry studies find little or no sticky behavior in costs.

Our research is the first to try and reconcile the conflicting results on sticky cost behavior. Understanding the pervasiveness of stickiness is necessary to move research forward in this domain.