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In this article we propose a multivariate dynamic probit model. Our model can be viewed as a nonlinear VAR model for the latent variables associated with correlated binary time-series data. To estimate it, we implement an exact maximum likelihood approach, hence providing a solution to the problem generally encountered in the formulation of multivariate probit models. Our framework allows us to study the predictive relationships among the binary processes under analysis. Finally, an empirical study of three financial crises is conducted.

In this chapter we extend the concept of serial correlation common features to panel data models. This analysis is motivated both by the need to develop a methodology to systematically study and test for common structures and comovements in panel data with autocorrelation present and by an increase in efficiency coming from pooling procedures. We propose sequential testing procedures and study their properties in a small scale Monte Carlo analysis. Finally, we apply the framework to the well known permanent income hypothesis for 22 OECD countries, 1950–1992.

Southeast Asia has been actively undergoing land conversion into agricultural lands over past few decades. This creates the challenges to the nation in dealing with the non-point source pollutants in many fluvial systems, thus requiring an effective approach in sediment source apportionment for an appropriate target mitigation procedure. The trace element property from different source points was used for catchment classification of Galas River. Sediment sample collection was carried out at the sources and sink areas of the catchment system. Fine sediment was analysed using X-ray fluorescence to obtain elemental composition followed by the statistical test and numerical model. Out of 83 elements, 12 elements (Mn, Ca, Cr, Ga, Dy Hf, Y, V, Th, Pb, Zn and Sr) have been selected as best tracer signatures. The solver model has indicated Pergau River as the major sediment contributor to this large catchment system. The model output could directly be proportional with the land-use practice, indicating excessive terrestrial alteration has taken place within the sites for agricultural plantation purposes. Thus, this highly recommends for the decision-making use to the targeted areas to overcome the serious sedimentation issues caused by the tillage operation in affected stream points and to improve the watershed quality.

This chapter looks at how various scholars have attempted to structure the “infinite field” by defining the appropriate theory and methods. These efforts have centered on a conception of what it would take to make comparative education a “science,” and how one could achieve “objective knowledge.” While these concerns were important for comparative educationists throughout the nineteenth century, who mostly favored a historical approach, the debate became more heated and more urgent in the 1960s when a number of key players published competing positions. This coincided with a time when the claim to a basis in science was being used to introduce a range of new subjects to higher education and establish disciplines like sociology on a firm institutional footing. Subsequently some of the heat went out of the debate about theory and method. A number of possible causes can be identified, including (i) that it became apparent comparative education was not going to achieve disciplinary status on a par with sociology; (ii) de facto comparative educationists handed the palm to Bereday, and carried on doing comparative education as he had described it; and (iii) the appetite for global theorizing waned to be replaced by partial theories, many of them based on general concerns for social justice and drawing on a broadly Marxist definition of “science.” The chapter concludes with reflections on the fact that healthy debate about methodology and theory can drive the development of the field, and that in the absence of explicit debate there is the danger that certain assumptions, especially assumptions that do not recognize the importance of context, can come to dominate the field by stealth.

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.

After briefly reviewing the past history of Bayesian econometrics and Alan Greenspan's (2004) recent description of his use of Bayesian methods in managing policy-making risk, some of the issues and needs that he mentions are discussed and linked to past and present Bayesian econometric research. Then a review of some recent Bayesian econometric research and needs is presented. Finally, some thoughts are presented that relate to the future of Bayesian econometrics.